THE DEFINITIVE GUIDE
THE INTERNET
OF THINGS
FOR BUSINESS
3RD EDITION
FOREWORD
The Internet of Things is hitting its
stride. It is a critical enabler of digital
transformation efforts happening around
the globe. For consumers, businesses,
and governments, IoT is playing an
increasing role in how we consume
information to make decisions and how
we interact with the world around us.
More than that, IoT also is changing how
we personally experience our world―our
daily interactions with our connected car,
smart homes, and connected wearables
make us digitally linked to the physical
world in a way that would seem like
magic to people living just 100 years ago.
We’ve journeyed from a world of M2M
(Machine-to-Machine), which was little more
than connected endpoints providing descriptive
data about a “thing’s” behavior, to an IoT
world of intricate and complex endpoints
capable of capturing and transmitting
predictive information.
Because of this, Cloud has become a critical
enabler of many successful IoT deployments,
yet the need to enable processing and
computational capabilities at the edge of the
network is becoming increasingly important.
IDC expects that in the next phase of the IoT,
more than 50% of data will be processed at
the edge. Data captured will become more
prescriptive and intelligent—allowing proactive
actions to be taken based on these insights.
This guide examines the increasing use of data
as a driver of business, as well as other critical
aspects of IoT.
Successfully planning, deploying, and scaling
IoT solutions is a challenge for businesses in
every industry, and the goal of this book is to
provide entry and insight into the IoT world. It
also serves as a valuable guide for businesses
who want to leverage IoT to expand revenue,
stay relevant, and advance business objectives
in the connected economy.
Whether you want to attempt initial entry
into the IoT-sphere, or expand your existing
deployments, this book can help you meet
your goals, providing deep understanding into
all aspects of IoT. From concept to lifecycle
management, or platform selection to data
analytics, The Internet of Things for Business
(3rd ed.) guides each step of the way.
Carrie MacGillivray
Group Vice President & Global IoT Lead
IDC
THE DEFINITIVE GUIDE
THE
INTERNET
OF THINGS
FOR
BUSINESS
3RD EDITION
by Syed Zaeem Hosain, Chief Technology Officer
The Definitive Guide | The Internet of Things for
Business, 3rd Edition
By Syed Zaeem Hosain, CTO, Aeris
Aeris® and AerPort™ are the trademarks and / or
registered trademarks of Aeris Communications, Inc.
All third-party trademarks are the property of their
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Copyright © 2018 Aeris Communications, Inc. All
rights reserved. No part of this book may be used or
reproduced in any manner whatsoever without the
explicit permission of the publisher.
Third Edition: August 2018
Editor: Carmi Brandis
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CONTENTS
1
WHAT IS THE INTERNET OF THINGS?
3
4
6
6
8
10
12
Machine-To-Machine (M2M)
Internet of Things (IoT)
Impact for Businesses and Consumers
Consumer IoT Applications
Enterprise IoT Applications
Using IoT for a Better World
An Intro to the Guide to IoT For Business
2
14
THE FUTURE OF PLATFORMS
15
19
21
22
IoT Platform Layers and Services
From Many to One
Advantages of a Single vs Multi-Platform Deployment
Platform Requirements
3
25
IoT CONNECTIVITY: TYPES AND CHOICES
27
28
32
34
37
44
45
47
Basic Internet Concepts
Choice of Connectivity
Proprietary Protocols
Standardized Protocols
Types of Cellular Technologies
Cellular Fallback
How To Determine Location
Global Positioning System
4
52
CONNECTIVITY MANAGEMENT PLATFORMS
54
55
56
59
61
What is a Connectivity Management Platform?
The Difficulties of Managing IoT Connectivity
Why Businesses Need Connectivity Management Platforms
Essential Connectivity Management Platform Features
CMPs are Integral to the IoT Environment
1
The Definitive Guide | The Internet of Things for Business, 3rd Edition
i
CONTENTS
5
63
IoT SENSORS AND DATA COLLECTION
65
66
72
76
What is a Sensor?
Sensor Types
Conversion to Digital Data
Calibration and Linearization
6
7
78
IoT ANALYTICS
80
81
85
IoT Data and Analytics
Types of Analytics
Future of Analytics
87
SCHEDULING, ENCODING, AND PROCESSING
89
91
93
98
98
99
100
Data Transmission Schedules
UDP or TCP
Content Encoding / Transport Protocols
Gateways
Application Servers
Cloud Computing
Fog Computing
8
102
IMPLEMENTING AN IoT SOLUTION
104
104
106
107
107
108
109
111
112
Supply Chain Management
Cellular Operator Selection
Cloud System Selection
Platform Selection
Network Operator Service Level Agreement
Device Certification
Considerations
Application Communications Call Flow
Customer Support Process
9
113
IoT SCALABILITY AND
ALTERNATIVE TECHNOLOGIES
117
119
120
What is Scalability
End-of-Life Management
Scalability and Connectivity
The Definitive Guide | The Internet of Things for Business, 3rd Edition
ii
CONTENTS
10
128
SECURITY, PRIVACY, AND THE INTERNET
OF THINGS
130
133
133
135
137
141
142
Privacy and Security
International Data Transport
Security Objectives
Security Issues for IoT
Risk Management and Assessing Impact of Breaches
Encryption as an IoT Tool
Choice of Encryption Algorithm
11
143
IoT USE CASES
145
146
149
152
154
Renewable Solar Energy
Automotive
Healthcare
Smart Cities
Financial / Insurance
12
156
THE FUTURE OF THE INTERNET OF THINGS
158
158
159
160
160
163
164
165
166
166
IoT Will Positively Affect All Markets
IoT Will Come First
Homes Will Get Smarter, And More Connected
Enterprises Will Spend More on IoT
IoT Standards Will Improve
Security Concerns Will Continue
Over-The-Air Updates Will Become the Norm
Privacy Concerns and Government Regulations
IoT Value Realized Though Data Analytics
The Future Is Now
167
DIRECTORY OF IoT TERMS
168
178
Acronyms
Glossary
The Definitive Guide | The Internet of Things for Business, 3rd Edition
iii
CHAPTER 1
WHAT IS THE
INTERNET OF
THINGS?
3
4
6
6
8
10
12
MACHINE-TO-MACHINE (M2M)
INTERNET OF THINGS (IoT)
IMPACT FOR BUSINESSES AND CONSUMERS
CONSUMER IoT APPLICATIONS
ENTERPRISE IoT APPLICATIONS
USING IoT FOR A BETTER WORLD
AN INTRO TO THE GUIDE TO
IoT FOR BUSINESS
Chapter 1 What Is The Internet of Things?
WHAT IS THE
INTERNET OF THINGS?
The Internet of Things envisions a world where both ordinary and exotic devices are
connected wirelessly to the internet and to each other. This means devices that do
not already have a network connection may have one added in the future, when it is
logical and appropriate to do so.
For example, an IoT device could be a temperature
Most IoT projects are motivated by a need to reduce
gauge, a location sensor, a device measuring
operating costs or increase revenue. Occasionally,
humidity, or a vibration detector. One or all of these
legislation compels companies to deploy IoT
sensors then could be attached to manufacturing
applications that support a new law’s data needs.
machinery, and the data transmitted would help a
Mobility is an obvious factor driving cellular adoption
business track the machine’s operations. This data
in markets like transportation. Desire for competitive
could track required maintenance, improve production
features will inspire IoT applications in consumer
efficiencies, reduce downtime, increase safety, and
high-tech. But whatever the specific purpose,
more. Plus, IoT devices can provide information
connected IoT devices can give your business
on the ambient environment of the manufacturing
the data and information needed to streamline
space, such as the temperature, pollution, and
workflows, predict necessary maintenance,
other conditions near the machinery, which can be
analyze usage patterns, automate manufacturing,
particularly relevant for remote installations.
and more.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
2
Kevin Ashton in 1999, may no longer apply in its original form.
Some clarity is needed to differentiate Internet of Things from Machineto-Machine technologies. Following are definitions and examples of these
overlapping technologies, and how they have evolved over time to improve
business efficiencies, produce multiple new revenue streams, or simply
enrich the quality of life.
Chapter 1 What Is The Internet of Things?
However, the very term “Internet of Things,” coined by British entrepreneur
MACHINE-TO-MACHINE (M2M)
By many indicators, M2M seems a lot like IoT. The difference,
however, is that M2M is a solution that optimizes existing
operations functionality through automation, while IoT
transforms the functionality into new business capabilities
via analytics. Hence, M2M can be thought of as a sub-set
of IoT.
Though initially not built as a sub-set of anything, M2M technologies
represent closed, point-to-point communications between machines or
between machine and management systems, without the need of human
intervention. M2M devices, enabling bidirectional remote monitoring and
transfer of data, consist of a sensor or an RFID tag and a communication
module. Machine-to-machine devices, as the industrial precursors to the
IoT, can include items ranging from in-house / in-office machinery, such as
printers or scanners to manufacturing equipment, including heavy machinery.
But don’t assume that the IoT will replace M2M. Predictions show that
cumulative M2M connections will grow from 995 million in 2014 to a
projected 2.7 billion connections by 2018.
M2M use cases include telemetry; traffic control; security; tracking and
tracing; machinery maintenance and control; metering; manufacturing and
facility management; as well as a multitude of additional applications.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
3
The Internet of Things goes beyond the scope of M2M,
encompassing and surpassing it in functionality by adding
devices and electronic equipment with embedded sensors,
control systems, and processors that enable communication
across a multi-node, open network of objects.
Chapter 1 What Is The Internet of Things?
INTERNET OF THINGS (IoT)
An Internet of Things ‘thing’ can refer to a connected medical device, a
biochip transponder for livestock, a solar panel, a connected automobile with
sensors that alert the driver to a myriad of possible issues (fuel, tire pressure,
need for maintenance, and more), or any object, outfitted with sensors, that
has the ability to gather and transfer data over a network.
The meaning and application of the term IoT will continue to evolve as new
connected technologies emerge. For many, IoT means connecting parts of the
supply chain, increasing proficiency and outcomes, and providing indicators
about product environments. For others, IoT is about life-changing insights
via wearables, medical adherence, or household security. The possibilities just
keep growing.
IoT use cases are widespread, limited only by our ability to connect certain
devices. But that, too, is changing rapidly. IoT applications already in
production include connected cars, smart cities (water / gas meters, lighting,
traffic / parking, waste management, and more), patient monitoring / medical
adherence, wearables, agriculture, and energy, with more uses seeing
daylight with each passing week. IoT use cases in the future will be limited
only by our own imagination as, eventually, all other barriers will fall.
Connected for Data
The Internet of Things is the next logical step in the story of a connected
world. At the heart of the IoT is data—the ability to collect it, analyze it,
and react to it, so as to create new revenue streams, new value. The IoT
combines the technologies found in M2M and earlier data telemetry terms
and expands them with an even greater accumulation of data and inferences.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
4
People—Using end-nodes connected to the internet to
share information and activities. Examples include social networks,
health, and fitness sensors, among others.
Things—Physical sensors, devices, actuators, and other
items generating data or receiving information from other
sources. Examples include smart thermostats and home
automation gadgets.
Chapter 1 What Is The Internet of Things?
The IoT is comprised of four key elements:
Data—Raw data analyzed and processed into useful information
to enable intelligent decisions and control mechanisms. An
example includes temperature logs converted into an average
number of high-temperature hours per day to evaluate
energy requirements.
Processes—Leveraging connectivity among data, things, and
people to add value. An example of this includes the use of
smart fitness devices and social networks to advertise relevant
healthcare offerings to prospective customers.
The IoT establishes an end-to-end ecosystem, including technologies,
processes, and concepts employed across all connectivity use cases.
5
The concepts of the IoT and M2M are inherently subject
to the confusion surrounding limitations associated with
meanings, use cases, and adoption.
While there are not yet comprehensive standards and regulations for IoT
from appropriate authorities (such as 3GPP1), these concepts will continue to
Chapter 1 What Is The Internet of Things?
IMPACT FOR BUSINESSES
AND CONSUMERS
evolve in response to technology innovation, changing consumer trends, and
varied marketing tactics. Businesses evaluating the promise and potential
of connectivity offerings will, therefore, have to dig into the specifics of each
situation instead of establishing conclusions based solely on the proposed
labels of IoT or M2M.
As new as the Internet of Things may seem, many network-connected
devices already are in use all around us. You probably have heard of
connected homes or the smart grid—these are just a few of the IoT systems
aimed at both everyday consumers and large-scale enterprises.
IoT innovation is taking place in a wide range of industries, locations, and
types of business. IoT creativity will be unlimited, as the technology largely
exists—although it may not be readily available everywhere as of yet. Or as
William Gibson so famously stated, “The future is here. It’s just not widely
distributed yet.”
CONSUMER IoT APPLICATIONS
While the focus of this book is on business uses for IoT
technology, seeing how it applies to consumer devices
is relevant for a sense of scale and direct application
in everyday lives.
IoT devices let individuals control their own network-connected devices
from their smartphones or wearables or get information about their status
from a webpage.
1
The 3rd Generation Partnership Project (3GPP) is an association of seven telecommunications
standard development organizations (ARIB, ATIS, CCSA, ETSI, TSDSI, TTA, TTC), providing
standardization oversight for cellular telecommunications network technologies.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
6
categories. The first is the connected home, which includes the smart
thermostat, intelligent lights, connected appliances, and smart door locks.
Next, wearables dominate the consumer market with the smartwatch,
activity / fitness tracker, and smart glasses. Finally, the connected car rounds
out the consumer categories with remote car controls, trip navigation, and
vehicle diagnostics.
Here are a couple of examples of popular consumer IoT applications:
The Nest thermostat arguably is one of the most well-known of the
products in this category. Nest, currently owned by Google, provides a
Chapter 1 What Is The Internet of Things?
The most popular consumer IoT devices typically are found in three major
Wi-Fi-connected thermostat that is capable of learning a person’s activities
and setting room temperature based on those preferences. The idea behind
the product is to always keep a home comfortable while boosting energy
efficiency. The Nest thermostat can be integrated with automated IoT
lighting, security systems, and other tools, thereby making the long-imagined
connected home more of a reality.
Internet-connected fitness trackers, such as Fitbit and smartwatches like
the Apple Watch, do everything from act as pedometers to sleep alarms to
personal coaches. These devices are part of a “quantified self” movement that
started in the mid-2000s to gain greater personal understanding through
data and technology. Devotees feel that these wearables help to achieve
health goals, and they even are used by businesses as part of employee
wellness programs to incentivize fitness and, potentially, reduce health
insurance premiums.
The connected car is one IoT application that has witnessed a large increase
in features. Many cars come equipped with systems that gather data within
the vehicle and can transmit them for a variety of applications. After-market
devices capture sensor data using the vehicle’s on-board diagnostic port
(OBD-II) for cars built since 1996. Examples include automatic notification
of crashes, notification of speeding, and safety alerts. Additionally, concierge
features provided by automakers or apps alert the driver of the best time to
leave for a prompt arrival to an appointment or sending text message alerts
to friends or business associates to alert them of arrival times. Users also can
unlock their cars, check the status of batteries on electric vehicles, find the
location of the car in a parking lot, or remotely activate the climate control
systems. As time passes, we expect an increasing number of applications,
including a truly self-driving or autonomous car, to be made possible
by IoT technology.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
7
To date, most industrial uses of IoT have been for preventive
maintenance. These applications detect when a machine
has variations in vibration, temperature, speed, or other
metrics so as to signal that they might require maintenance.
But using IoT for preventative maintenance was just a start. This didn’t fully
tap into the ability of network-connected devices to talk to each other, thus
Chapter 1 What Is The Internet of Things?
ENTERPRISE IoT APPLICATIONS
letting them work together. For example, a business could use a central
monitoring hub, or even an engineer with a smartphone, to reach out to the
machine and make changes on the device, or deliver new instructions. More
and more enterprises are realizing that these communications can create
greater efficiencies and reduce production costs far beyond IoT systems
aimed at simple maintenance functions.
The fleet industry was one of the earliest to adopt IoT because of its many
benefits. IoT-enabled trucks, ships, and vans can be tracked and managed in
a more efficient manner, thereby allowing visibility across the transportation
ecosystem. Fleet telematics allow the exchange of information between a
commercial vehicle fleet and a central dispatching office. Now, the physical
health of a vehicle can be checked at a fraction of the cost and in real time.
Additionally, GNSS-based tracking can guide a vehicle to its destination in the
most efficient manner and allow the central office to optimize the dispatch of
its fleet more effectively. Some of the leaders in the fleet management space
include PeopleNet and Omnitracs.
Here are examples of other industries with interesting IoT enterprise
applications that currently are deployed:
Point of Sale: Acceptacard is a provider of dedicated card-processing
solutions for UK businesses. Its mobile point-of-sale (POS) terminal is a
breakthrough from what typically is provided by the banking industry in that
there are no multi-year contracts with expensive terminals. The company
caters to a broad range of business types—from startups to established
companies looking to reduce costs or for greater payment functionality,
flexibility, and control. Its mobile payment solution is a terminal-independent
solution with reliable connectivity service, regardless of the location, and is
designed for businesses that want a payment solution on a self-service basis
with online access.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
8
services, regardless of the location or the mode of on-road transportation.
Combining cars, shared carpools, decentralized scooters and bikes, car
rentals, and even public transportation, Uber tries to find the most efficient
way to get you from here to there. Leveraging smartphones as a basis for its
business, Uber connects drivers with those needing conveyance. By relating
passenger locations with its drivers, Uber can route services optimally to
maximize results. And it doesn’t end with just driver services. Uber continues
to invest in self-driving technologies, acknowledging the near-future direction
of vehicles. Additionally, Uber uses other modes of transportation for that
‘last mile’ of transit. Bikes, scooters, and Uber Pools all can alleviate traffic
Chapter 1 What Is The Internet of Things?
Ride Sharing: Uber is fast becoming synonymous with IoT ride-sharing
congestion while providing mobility services to its clientele. In fact, Uber is
continuing to invest in new people-moving technology, including dockless
scooters and bikes (covering 70+ markets with more than 35,000 scooters
in service nationally). And within some cities, Uber has even partnered with
public transit, selling tickets via its own app. For inventive companies such as
Uber, the IoT is their highway to success.
Solar Energy: BBOXX designs, manufactures, distributes, and finances
innovative plug-and play, off-grid solar powered systems to improve access
to energy across Africa and the developing world. Because of the importance
of sustainable energy, BBOXX aims to provide 20 million people with
electricity by 2020. Its core products include a range of solar powered battery
boxes that sit in a home and allow users to power small appliances, such
as lights, mobile phones, refrigerators, or computers. BBOXX has more than
80,000 systems deployed so far across China, UK, and East Africa.
Healthcare: SimplyHome designs and installs wireless technology products
and related home care-focused services. The company is known for its highly
customizable systems that are tailored to meet each customer’s specific
needs. Its systems proactively alert patients and caregivers to changes in
behavioral patterns by communicating with multiple sensors to observe
activities of daily living. Its products and services range from voice-activated
environmental controls, personal emergency response systems, GPS
watches, motion sensors, stove monitors, and virtual care management. Text,
email, or phone alerts can be generated by a single event, an intersection
of multiple events, or by inactivity. The SimplyHome system helps residents
remain independent with environmental controls that operate beds, lights,
TVs, doors, and more via tablet or voice activation.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
9
While many enterprises are using IoT technology to make
money, nonprofit organizations and non-governmental
organizations (NGOs) are showing how IoT can be used
to make the planet a more habitable place and improve
people’s quality of life.
Aeris provides global connectivity services and solutions across multiple
Chapter 1 What Is The Internet of Things?
USING IoT FOR A BETTER WORLD
carriers and multiple technologies for social impact enterprises working in
some of the world’s most challenging environments.
Here are a couple of examples.
SweetSense is an organization that has teamed with governments and
NGOs to put IoT sensors on water pumps in rural Africa. This enables the
NGOs that install the pumps to track the pumps’ functionality and maintain
them more efficiently and in a cost-effective manner.
In a Rwanda study, only 56% of the water pumps were working
consistently. After adding the SweetSense technology to track the pumps’
function via cellular IoT systems and analytics, the water pumps were able
to be repaired more quickly, and 91% of the pumps could be kept working
on a regular basis. With projects like this from SweetSense, connected
devices can help provide clean water to more people on more days,
thereby improving health and well-being.
Hello Tractor helps Sub-Saharan African farmers with food production.
The company works closely with its partners to create an entire
ecosystem, with a sharing platform for income-generating products
(tractor leasing) and affordable service offerings. This enabled more
farmers to receive the services or equipment they needed to succeed.
With more than 500 tractors in operation, another crucial step to Hello
Tractor’s success was developing a pay-as-you-go plan that farmers could
afford and one that the banks and insurers could accept.
The process deployed by Hello Tractor produced greater efficiencies, higher
crop yields, and a proven business model that can be implemented around
the globe. Armed with this greater access to business-critical data, Hello
Tractor now has plans to expand projects into Bangladesh and South Africa.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
10
The Definitive Guide | The Internet of Things for Business, 3rd Edition
Chapter 1 What Is The Internet of Things?
Connected
devices can help
provide clean
water to more
people on more
days, thereby
improving health
and well-being.
11
In this book, we will focus on how the IoT ecosystem can
be used by businesses. In addition to providing real-time
information from devices in the field, IoT works in the other
direction too (i.e., it lets companies control devices from a
central location).
Chapter 1 What Is The Internet of Things?
AN INTRO TO THE GUIDE TO IoT
FOR BUSINESS
This ability provides everything from marketing intelligence to improved
preventative maintenance. Companies can use IoT for applications as diverse
as helping medical professionals care for more patients at the same time or
giving retailers the ability to customize advertising to a single individual.
To get started with IoT for your business, you will need a basic understanding
of what makes it all work. You don’t need to be an engineer or a data
scientist, but it is useful to have a grounding in the concepts of how IoT
systems are connected, how they communicate, how the data is analyzed,
and how this can positively impact your organization. We will present an
overview on connectivity and data collection, as well as an in-depth, detailed
description of the Internet of Things.
To do this, we will cover these broad topics:
•
The technology that connects the Internet of Things.
•
How wireless devices are networked and locate themselves.
•
Different types of sensors, how they work, and what they do.
•
An overview of security technologies used to protect IoT data.
•
How to scale up an IoT project to immense proportions.
•
Using Big Data analytics to gain insight from the IoT ecosystem.
•
IoT applications and their relationship to the IoT value chain.
•
Advice for managing the lifecycle of an IoT deployment.
•
A view into the future of the Internet of Things.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
12
for those running small to large businesses. In this guide, Aeris will look
behind the scenes into how these IoT devices are run and managed, where
the data they collect goes, and how it’s used. If you’re in the business of IoT
or looking to start up a deployment, this guide is for you.
Chapter 1 What Is The Internet of Things?
All of these IoT aspects will be addressed from an enterprise point of view
13
CHAPTER 2
THE
FUTURE OF
PLATFORMS
15
19
21
IoT PLATFORM LAYERS AND SERVICES
FROM MANY TO ONE
ADVANTAGES OF A SINGLE VS MULTI-PLATFORM
DEPLOYMENT
PLATFORM REQUIREMENTS
22
Chapter 2 The Future of Platforms
THE FUTURE
OF PLATFORMS
Often, the ability of a company to deploy an IoT application is limited by the expertise
and capability resources available to it. Engineering talent is difficult to find, and a
complete IoT solution may require significant software and systems development.
Experience has shown that this can lead to long schedules for deployment, which
can be problematic for a variety of reasons: the company may miss the product target
window, the project may be more expensive than expected, management may lose
confidence in the IoT application, or future support and maintenance may tie up
resources and make the IoT application fail to achieve its objectives.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
15
need an IoT platform. These days, everybody claims to have the best, the
fastest, the most secure, the most adaptable platform.
IoT platforms combine many of the tools needed to manage a deployment―
from device management to data prediction and insights―into one service.
Thus, it often is best to use a platform where much of the development and
operational work is done by a supplier who has the necessary expertise
and available capability and capacity to support the company. That supplier
Chapter 2 The Future of Platforms
In IoT, to get from the device sensors to the networks gathering data, you
provides what is called a “platform” that allows the customer to focus on the
objectives and development of the application rather than the mechanics
of an implementation. Some platforms also may provide core capabilities of
transport networks, data storage, and analytics functions that can be used
more rapidly than building in-house. The supplier can support and maintain
the platform in the future, including changes to support new services and
new technologies.
To figure out the best solution for your deployment,
look at both your company’s immediate needs, as
well as for long-term deployment requirements.
Certain criteria will differentiate platforms. These include scalability, ease of
use, security, cost, third-party software integration, and a slew of additional
functionality. So, what is best for your business? Well, it depends. Let’s break
down some of the criteria you need to look for in a highly functional platform.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
16
There are four basic layers to an IoT platform:
Connectivity Management, Device Management,
Data Management and Analytics, and Application
Development. It is important to look at all four layers,
along with an overarching layer of Security.
Chapter 2 The Future of Platforms
IoT PLATFORM LAYERS
AND SERVICES
Connectivity Management
This layer of an IoT platform includes the connectivity types supported, the
network protocols that are available to devices, the coverage and footprint
of the connectivity (whether it is regional, national, or global), the device
provisioning and subscription management, and rate, usage, and
billing management.
Beecham Research, 2017
The Definitive Guide | The Internet of Things for Business, 3rd Edition
17
The IoT Device Management platform can offer elements for automatic
discovery of new devices and their configuration, device health monitoring
and updates, library support for a diverse set of devices, scalability to allow
growth—beyond the 100,000 unit mark without problems, and edge
analytics where the platform processes data and potentially takes action at
the device and / or gateways.
Data Management and Analytics
Chapter 2 The Future of Platforms
Device Management
The Data Management and Analytics platform can offer data storage
capabilities (including cloud services and data centers), orchestration for
disparate sources of data, analysis and visualization tools, and advanced
analytics (such as predictive analytics).
Application Development
The Application Development platform may offer tools for the development
and deployment of applications, including dashboards and portals, application
programming interfaces (API) to the dashboard, data and cloud computing
services for critical functions, and modeling and simulation tools to enable
application development without actual deployment.
Security
Any Security platform that is expected to work with an IoT application must
provide services for access, authentication, and authorization of a device (or
groups of devices) for the user (or multiple users), content protection via data
encryption, and key management, as well as gateway security protection
and management (including updates).
18
A platform needs to provide a single interface to
manage and monitor usage across all deployed devices,
regardless of the underlying carrier. This visibility and
control can lower operational costs of IoT solutions.
Combining real-time information with actionable device
controls provides command throughout the entire
deployment lifecycle.
Chapter 2 The Future of Platforms
FROM MANY TO ONE
Manage device status—Provision, activate, suspend / unsuspend,
and cancel service on devices.
Monitor usage in real time—Run on-demand reports for network
traffic, billing information, and network registration events.
Set customizable alarms—Configure real-time alerts and alarms
on device activity for customized proactive control.
Understand device behavior—View daily and monthly summaries
with detailed reports and rated billing events.
Think of one platform to manage multiple technologies, with additional
capabilities to identify problems faster, resolve issues quicker, and control
costs at every stage of the device usage.
Businesses from every sector are requiring single-platform functionality
where all technologies, as well as connectivity from multiple carriers, could
be implemented, viewed, and managed. The platform needs to provide API
integration for visibility and management processes; seamless third-party
integration; a simplified process that would reduce costs; and an overall
reduction in operational complexities.
Using a single platform to manage the applications provides distinct
advantages from an on-going operational cost and complexity perspective.
Overall, the differences between single- and multi-platform deployments
can be quite extensive, with single platform deployments being much
more conducive to success. Devices may be deployed globally in multiple
networks (for example, cellular and non-cellular technologies) and managing
the entire deployment, including devices, the data, and analytics, particularly
at large scale, is best done with a “single pane” view of the solution. (See
table on the following page for even more details.)
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19
Chapter 2 The Future of Platforms
The bottom line–
IoT needs security
at the design
stage, and not as
an afterthought.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
20
for connecting to and managing the connected features of IoT devices.
Built using a micro-services architecture, the platform should include
an extensive set of software services, packaged as micro-containers,
which are functional building blocks that can be combined in a multitude
of configurations to create application-specific variations. The power
of the platform comes from its customizable ability to address
multi-variant complexity.
Chapter 2 The Future of Platforms
Today’s advanced IoT platforms include a cloud-based software solution
A global platform needs to allow for regional market variations (brand,
location, and more), thereby redefining and expanding the ability to gather,
analyze, and react to volumes of data. This concept could apply to multiple
business sectors (automotive and healthcare will lead the way, but other
sectors will engage this technology in the future).
ADVANTAGES OF A
SINGLE vs MULTI-PLATFORM
DEPLOYMENT
Multi-Platform Deployment
Single-Platform Deployment
Scalability
Deployment becomes a collection
of individually managed groups
Single management interface
worldwide simplifies large scale
operations
Complexity
Operations teams need to be
trained on and manage multiple
systems
One portal, one set of operational
processes to identify and resolve
issues
Efficiency
Operations teams take longer to
identify issues requiring larger
teams at a higher cost
Issues are identified faster
and resolved quicker, by fewer
resources
Visibility
Lack of consistent visibility into
devices and usage patterns
impacting end-user experience
and billing
Holistic reporting and analytics
provide complete insight into
entire deployment
Support
Multiple support processes to
follow with no standardized SLAs
One support process to follow for
all issues and all devices
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21
Global Scalability—Initially, global scaling must take into
account regional languages, local regulations, and differing
access capabilities. Make sure the documentation is available
in multiple languages. Likewise, partner with a local company
versed in the target country’s customs, language, and laws.
This will help resolve problems quickly and efficiently, saving
Chapter 2 The Future of Platforms
PLATFORM REQUIREMENTS
both time and money.
Since the nature of IoT is to deal with millions of devices, the
upgrading capacity becomes critical in pushing new services
to consumers in as little time as possible. Seamless and timely
upgrades must be part of any long-term solution, with over-theair (OTA) updates to limit the need for human intervention (thus
materially reducing costs). Additionally, in a global deployment,
having one portal (“single-pane-of-glass” view) to configure
and manipulate all devices is key to offering up-to-date and
continuous device management and configuration.
Also, understand device certification and equipment requirements
for each country. Just because a device is certified in one country
does not mean it will pass certification elsewhere. The bottom
line―find a service provider with international coverage and
roaming capabilities, local language support, 24x7 device
monitoring and management, and the ability to administer
devices from any location.
Platform Security—Securing an IoT platform requires an endto-end approach, from physical devices and sensors, to data
connections, to host systems, to the services and data stored
in the cloud. And while security risks can never be completely
eliminated, find a provider with the tools and expertise to mitigate
these risks with the responsible development of IoT applications.
The bottom line―IoT needs security at the design stage, and
not as an afterthought.
The Definitive Guide | The Internet of Things for Business, 3rd Edition
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requirement of every global business: regional flexibility. A
platform must allow deployment of a global program across a
multitude of public and private clouds in a manner that maximizes
operational efficiency and maintains local flexibility and autonomy
while also ensuring compliance with local regulations.
Customer Experience—When it comes to IoT solutions,
customers require and expect on-going, long-term reliability
Chapter 2 The Future of Platforms
Service Flexibility—IoT solutions need to address a key
without the need for constant human touch. Support needs to be
agile and responsive to customer concerns and needs. And the
platform itself needs to make IoT deployment management as
simple as possible, thereby saving work-hours and resources.
Modern platforms address these issues with a services delivery
architecture that optimizes an end-to-end system―from wireless
connection to telematics applications―while simultaneously
addressing key concerns around hardware power management,
cost structures, and visibility.
Today, there are hundreds of companies, as well as numerous startups,
concentrating on IoT platform development.
23
countries and continents, along with the ability to develop services and
enhance products seamlessly. The platform has to provide a superior
combination of coverage and operational time, while offering a heightened
level of security.
Seek a solution provider that has an end-to-end modular technology platform
that enables customers to make the pivotal change from unconnected
product to connected services offerings. This journey is a challenging and
Chapter 2 The Future of Platforms
Your IoT platform has to ensure the largest possible geo-coverage of
complex process and you need a vendor that has the knowledge, experience,
and technology to implement, accelerate, and optimize these services, which
include connectivity, storage, analytics, and service layer functionality.
24
CHAPTER 3
27
28
32
34
37
44
45
47
IoT CONNECTIVITY:
TYPES AND
CHOICES
BASIC INTERNET CONCEPTS
CHOICE OF CONNECTIVITY
PROPRIETARY PROTOCOLS
STANDARDIZED PROTOCOLS
TYPES OF CELLULAR TECHNOLOGIES
CELLULAR FALLBACK
HOW TO DETERMINE LOCATION
GLOBAL POSITIONING SYSTEM
Chapter 3 IoT Connectivity: Types and Choices
IoT NETWORK
TECHNOLOGY
To understand how the Internet of Things communications work, you need a basic
overview of the technology used for the internet. While technology always is
evolving, certain principles are common to how networking functions. What changes
more frequently are the tools and protocols used to access the network, such as
modems, cellular radios, transmitters, and more.
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Chapter 3 IoT Connectivity: Types and Choices
BASIC INTERNET CONCEPTS
IP—Traffic on the internet uses the Internet Protocol (IP) to
transmit data. This communications protocol has a routing
function designed for internet connectivity. IP is used to route data
packets across an IP network from a source host to a destination IP
address. Every node in such a network has an IP address, a unique
numerical label. The computers and printers in your office generally
have private, local-area network IP addresses, while websites,
such as Aeris.com, have public IP addresses.
Packet—Data travels across an IP network in packets. Each
packet has both a source and destination IP address, but many
packets may be needed to make up one complete “item”. For
example, a single email message can be comprised of many
different IP packets that, when assembled by the remote
network for the recipient’s email program, make a complete
piece of mail. A webpage retrieved by your browser also is
comprised of multiple packets.
Router—A router connects one network to another. For example,
your home or office wireless router connects the internal IP
network in your home or office to the public internet via an
Internet Service Provider (ISP). Your ISP connects to other
providers and internet backbones using routers.
Modem—A modem is a shortened term for “modulator
demodulator”. The modem modulates signals to encode digital
information and demodulates the received signal to retrieve the
information. Wireless broadband modems are a popular way for
The top countries for the fastest
average internet connection
speeds are led by South Korea
(28.6 Mbps); Norway (23.5
Mbps); Sweden (22.5 Mbps);
and Hong Kong (21.9 Mbps).
The U.S. enters the list in tenth
spot with averages speeds of
18.7 Mbps.1
smartphone and laptop users to get internet connections. Early
wireless modems used the 2G and 3G cellular standards, but
most have moved to the faster 4G LTE technology, which rapidly
is becoming available around the world.
Speed—Internet speed is measured in megabits per second
(Mbps). For example, Netflix HD video typically requires five
megabits per second for good video quality viewing, although
its service will work at speeds as slow as 0.5 Mbps.
1
Akamai Q1 2017 global average connection speeds ranking.
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27
The internet can be accessed in many ways, depending
on your device and application. There are pros and cons
to each form of connectivity technology, particularly when
implementing a large IoT project.
Internet Service Providers
An ISP connects offices and homes to the internet by taking their network
traffic and forwarding it to other networks until it gets to the desired
Chapter 3 IoT Connectivity: Types and Choices
CHOICE OF CONNECTIVITY
destination. An ISP could be, for example, Telstra in Australia. But it doesn’t
stop there because an ISP has to connect to other ISP networks. For
example, while Telstra runs a large internet network in Australia, it still
has to connect to other networks within the country and around the world.
Tier 1, Tier 2, and Tier 3 networks form the internet’s backbone. ISPs, such
as Telstra, connect to those networks, which become the principle routes for
internet data transmissions around the world.
Wireless operators, such as Aeris, connect IoT deployments to the internet
or private networks in a similar fashion. A wireless operator has a cellular
network that uses fixed base station radios at cell towers instead of wires
to transmit signals from the cellular devices into the network. Much like ISPs
using other ISPs, wireless operators also can connect to Tier 1, Tier 2, or
Tier 3 networks. This is how they deliver traffic on the wireless network
when a mobile device requests data.
Wired and Wireless IoT Connections
A home, office, or IoT-networked device can be connected to the internet
either via a wired or wireless connection. If the connection is wired, it
generally is connected directly into an internet router, and the device needs
to remain stationary. A device with a wireless connection can have a cellular
modem, a Wi-Fi router, or other connectivity technology, which, among
other things, lets the device be physically mobile.
Wired connectivity was common in the early days of M2M systems. For
example, many factories installed wired systems for supervisory control and
data acquisition. For business and residential security systems, alarm panels
could use telephone circuits to communicate events—like a burglary or fire—
to central monitoring stations.
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with setups possibly being complicated. These early applications tended to
be purpose-built, meaning each industry and company developed its own
devices and software systems from scratch for a specific purpose.
The 1990s saw a move towards using wireless radio technologies in these
applications. Ademco Corporation (now a division of Honeywell), a leader
in intrusion and fire detection systems, began to build out a private radio
network to address this need. In 1995, Siemens introduced the first cellular
radio module for data transmission applications. Very shortly afterwards,
New
technologies
enabled
machines to be
free from wires.
Aeris introduced its MicroBurst™ data services using the control channels
of the Advanced Mobile Phone System (AMPS) cellular service. Ademco
Chapter 3 IoT Connectivity: Types and Choices
Connectivity, however, depended on where the ISP’s lines could extend,
became the first major customer to deploy M2M devices using this transport.
These new technologies enabled machines to be free from wires, and more
IoT functions were possible in different industries, including consumer
products. For example, in 1995, OnStar ® became one of the first connected
car systems, offering a mix of safety services and entertainment options.
Fleet and container tracking solutions similarly made use of mobile telematics
for the trucking and railroad transportation industries. In addition to being
mobile, cellular connectivity could extend application reach to more remote
locations than wired networks could allow.
By the 2000s, changes in cellular technology introduced digital cellular
networks with features such as Short Message Service (SMS), General
Packet Radio Services (GPRS), and 1 Times Radio Transmission Technology
(1xRTT). However, there arose two competing types of digital cellular,
CDMA and GSM, with different industries choosing differing solutions.
In the U.S., for instance, the automotive and trucking industries mostly chose
The future holds
promise for
more varieties
of wireless data
technologies,
including wider
adoption of
4G LTE, and,
CDMA devices, while the alarm and security industries generally picked GSM.
eventually, 5G
Looking Forward
in the next
The future holds promise for more varieties of wireless data technologies,
including wider adoption of 4G LTE, and, eventually, 5G in the next few
few years.
years. Short-range data transport methods, such as Bluetooth, ZigBee,
and 6LoWPAN, may be used to augment long-range cellular in some
applications. We also are seeing the commercial deployment of Low Power
Wide Area Networks (LPWAN) that provide long-range communication
similar to traditional cellular, but consume much less power.
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29
Several new LPWA connectivity technologies, cellular and non-cellular,
licensed and unlicensed, are trying to win the hearts, minds, and
pocketbooks of companies worldwide. Overall, these connectivity
strategies will afford a diverse range of business sectors to seek out
operational efficiencies and competitive advantages through collecting,
%
30
storing, and analyzing business-critical data at levels of granularity
previously unseen.
This shift to LPWA is promising to bring in many more industries under the
IoT umbrella. For many industrial functions that require sensors or devices
obtaining and sending only small amounts of data, LPWA offers the best
It is predicted that by 2019,
30% of connected devices will
be on LPWA networks.
Chapter 3 IoT Connectivity: Types and Choices
Low Power Wide Area (LPWA) Networks
low-cost option. Additional factors are weighing heavy in the promotion
of LPWA networks, including less expensive devices that are reaching
the market; low throughput for long- or short-distance transmission; data
transfers that support small blocks of data intermittingly sent; and the
ability for extended coverage, both indoors and underground. What this
all means is extended reach, a much lower cost of entry, and a much lower
total cost of ownership.
For businesses, however, one size, or sometimes, one technology or
one cost structure, doesn’t fit all. So, the growth of multiple LPWA IoT
solutions is a good thing.
How LPWA Networks Work
LPWA networks are designed for IoT and M2M applications that have
low data transmission rates, need long battery lives, can provide lowcost services, sometimes operate in remote or hard to reach locations
(underground or geographically dispersed), and be easy to deploy across
basically every business sector, including manufacturing, automotive,
energy, utilities, agriculture, healthcare, wearables (for humans or animals),
or transport.
Present-day cellular mobile technologies are designed to work on costlier
consumer-oriented networks where a premium is placed on fast
connections that can transport large amounts of data. Low-cost LPWA
networks, however, can support devices requiring low mobility, low-power
consumption, long-range abilities, and heightened security. One of the
benefits of LPWA is that data transfer rates, as well as power consumption,
are very low. Device connectivity in this case requires less bandwidth than
standard cellular, which means that LPWA networks can operate with far
greater power efficiency.
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Initially, IoT services relied on licensed cellular, wireline, and satellite
networks for wide area connectivity requirements. These, however, were
not a good fit for widespread IoT usage due to excessive power consumption
and complex protocols that lowered battery life. Recently, to help alleviate
these issues, several (more) LPWA alternatives have appeared on the
market. These networks, generally, are more business friendly, with low data
rates, extended battery life, and extended coverage.
Chapter 3 IoT Connectivity: Types and Choices
Additionally, LPWA networks can support more
devices, at a lower cost, over a larger coverage area
than consumer mobile technologies.
Technologies, Protocols, and Players
There literally are dozens of participants in the burgeoning LPWA sector.
Basically, they can be broken into two overarching categories: standardized
and proprietary. The differences between the two categories are fairly basic.
Standardized LPWA connectivity runs in a licensed spectrum, generally
compatible with existing cellular standards. Proprietary technologies, run in
an unlicensed spectrum. They can get to market faster, but adoption of this
technology still is in question. Below, we will define some of the technologies
at play in the IoT sector, along with some primary advocates of each protocol.
31
Random Phase Multiple Access (RPMA)
Ultra-Narrow Band (UNB)
RPMA is a low-power, wide-area channel access
UNB technology transmits over a low bandwidth,
method used for IoT and M2M communications.
in a very narrow license-exempt radio spectrum
RPMA employs direct sequence spread spectrum
channel (less than 1 kHz) to achieve long-distance
(DSSS) modulation to access the best signal
data links between a transmitter and a receiver.
for both the network and its devices. It is IEEE
UNB is fully bidirectional, meets the long-range,
802.15.4k compliant; uses a globally available,
low-cost needs of business connectivity, does not
cost-free unlicensed spectrum; requires low-
rely on other networks, and already is in use in
power support, thereby extending battery life; and
multiple smart applications (lighting, meters, etc.)
provides high network capacity. Additional selling
UNB is gaining success by combining long-range
points of RPMA include extended coverage with
connectivity with an extended battery life
high capacity for multi-million-node networks.
(up to a decade).
RPMA uses standards-approved algorithms for
both device and messaging security.
As a major proponent of UNB, Sigfox provides
a software-based LPWA communications
In the RPMA sector, companies such as Ingenu
solution, where all the network and computing
(formerly OnRamp Wireless) are using RPMA
data is managed in the cloud. Working in the
protocols designed specifically for wireless IoT
unlicensed spectrum, its UNB proprietary solution
communications. The company’s commercial
uses a simple protocol with slow data speed.
deployments are in the unlicensed 2400 MHz
Originally France and European Union focused,
range. This service initially was deployed for
Sigfox started to deploy in the U.S. and elsewhere
private networks but now is publicly available in
in early 2017 and has partnered with a number
select areas of the U.S. RPMA has excellent noise
of firms for advancing UNB technologies,
immunity for range and throughput, with a high
including Texas Instruments, Silicon Labs,
link budget (less interference). Data is highly
and ON Semiconductor.
secure (using AES 128 bit encryption) and the
product has seen some success in utility markets
with private networks.
Chapter 3 IoT Connectivity: Types and Choices
PROPRIETARY PROTOCOLS
UNB provides end users with low device costs
and low energy consumption. It employs a simple
API to integrate radio modules, and this protocol
On the downside, this technology is playing catch-
has several chip suppliers. As stated, though,
up in the U.S., has radio costs that, generally, are
this technology is not fully engaged in the U.S.
higher than other protocols, and, as a proprietary
Its message size of 12 bytes (by design) limits
technology, deployment and support are limited.
its applications, and it has shown some
reliability issues.
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32
Nwave
The LPWA network specification LoRaWAN
Nwave uses ultra-narrow band (UNB) radio
focuses on secure bidirectional communication,
technology, combined with advanced software
mobility, and localization services and is a protocol
defined radio (SDR) techniques, to provide a
supported by the LoRa Alliance. It is intended
communications network for IoT. Ultra-narrow
for wireless, battery operated devices. This open
band, which operates in internationally available and
standard, developed by Semtech, and supported
unlicensed sub-1 GHz radio spectrum (ISM bands),
by IBM, SoftBank, and several other carriers,
allows for strong signal dissemination, giving
operates in unlicensed spectrum, using narrow
enhanced in-building penetration and range, while
spectrum in the 868-915 MHz ISM band, up to
using minimal power.
500 kHz bandwidths. LoRaWAN uses an adaptive
data rate (along with radio frequency output)
for each device so as to extend battery life and
increase overall network capacity.
Chapter 3 IoT Connectivity: Types and Choices
LoRaWAN
Unlike some other IoT communications technologies
that require the use of a mesh network, UNB also is
highly scalable, allowing for high capacity networks
with a simple star architecture, whereby devices
LoRaWAN data rates range from 0.3 kbps to
communicate directly, and securely, with base
50 kbps. This protocol uses spread spectrum
station transceivers.
technology, along with virtual channels, to separate
cross-channel interference. Additionally, LoRaWAN
provides encrypted data for higher security levels,
gateways and radios from multiple suppliers.
However, its message limit, defined by the user,
can be no more than five seconds in length to meet
compliance requirements. Its radio costs still are
high and, as of the publication of this book, U.S.
coverage is limited to select areas of the U.S.
The LoRa Alliance is lobbying hard for its global
protocol, LoRaWAN, in LPWA networks. IBM is
using LoRa’s wireless sensor network with its Long
Range Signaling and Control (LSRC) software,
as well as its IoT cloud-hosted service, to create
large-scale IoT deployments. Its open standard is
supported by several organizations and businesses,
and IBM’s global influence could be the thumb on
the scale, providing the business recognition, along
with a low price point, for this solution’s continued
growth. Efforts to deploy American public networks
are underway, but coverage still is limited today.
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IoT industry standards, as set by the 3rd Generation Partnership Project (3GPP),
recently saw more protocols join the LPWA sector. These include LTE-M (also
known as LTE-CatM1 or LTE-MTC) and Narrowband IoT (NB-IoT). Each wants
the crown of global LPWA standards coming their way. Each has an argument
for dominance.
LTE-M
Extended Coverage GSM (EC-GSM)
LTE-M is a bidirectional, standards-based protocol
Extended coverage GSM is a standards-based,
within a dedicated spectrum. It provides carrier-
LPWA technology. It is based on eGPRS and
grade security, long battery life, low data needs,
designed as a high-capacity, long-range, low-
and low-cost modules. This protocol has many
energy, and low-complexity cellular system for IoT
active followers, including Altair, Ericsson,
communications. The optimizations in EC-GSM
Qualcomm Technologies, WNC, and Xirgo, as well
from existing GSM networks can be accomplished
as a host of U.S. and international carriers.
via a software upgrade, ensuring coverage and
One of the strengths of LTE-M is that it does not
need new infrastructure as it can piggyback on
existing LTE networks. What that means is that
accelerated time to-market. Much longer battery
life (up to 10 years) will enhance usage in multiple
use cases.
a carrier can update software on its network and
The first commercial launch was in 2017.
get LTE-M functional. LTE-M, however, is a much
Supported by all major mobile equipment, chip set,
simpler product, only using 1.4 MHz of the channels
and module manufacturers, EC-GSM networks
instead of 20 MHz.
will co-exist with cellular mobile networks, along
Additionally, using an extended discontinuous
repletion cycle (eDRX), the data collection devices
can transmit data on a non-continuous schedule,
Chapter 3 IoT Connectivity: Types and Choices
STANDARDIZED PROTOCOLS
with all the security and privacy mobile network
features, including user ID confidentiality, entity
authentication, and data integrity.
as set by the end user. The device, when not
sending data, is not off, but just asleep. When data
is scheduled to be sent, the device does not need
to be re-activated to join the network, it just wakes
up. Having intermittent data send-schedules, which
are not active 24x7, can save battery life, leading to
significant cost savings. Data rates for LTE-M are
somewhat higher than NB-IoT, but it can transmit
larger blocks of data. LTE-M had an American
roll-out in 2017.
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NB-IoT is the newest entry to the IoT scene. With
licensed spectrum, it is secure with highly reliable
its standards-based LPWA technology, NB-IoT
data transmission, assuring a high quality of service.
has a global reach with better bidirectional data
than any of its unlicensed competitors. And, unlike
LTE-M, NB-IoT is based on Direct Sequence Spread
Spectrum (DSSS) modulation, which ‘spreads’ the
signal so as to reduce interference. It also might
make it a bit harder to go national (since it can’t yet
hook into a typical LTE network).
NB-IoT devices and hardware are at the lower end
of the cost spectrum and improved efficiency helps
batteries last more than a decade, allowing for longterm IoT application deployments. With its simpler
underlying technology, costs for NB-IoT modules
will continue to decrease as demand increases. The
Chapter 3 IoT Connectivity: Types and Choices
Narrow Band IoT (NB-IoT)
technology roll-out, with a commercial module and
NB-IoT has several large organizations, including
network, started in 2018 and will continue through
Huawei, Ericsson, Qualcomm, and Vodafone,
2019. In the U.S., the present expectations are
actively involved with this standard. Additionally,
that all of the big four wireless carriers will deploy
NB-IoT is supported by all major mobile equipment
nationally, with Verizon and T-Mobile hitting the
manufacturers and can work with 2G, 3G, and
market first, followed by Sprint and AT&T. Globally,
4G mobile networks, so it enjoys the heightened
a large number of carriers have begun NB-IoT
security of mobile networks, including user ID,
deployments in their coverage footprints to support
authentication, data integrity, and more.
IoT applications.
The NB-IoT LPWA solution is optimized for
applications that need to communicate small
amounts of data over long periods of time.
NB-IoT results in lower latency with a higher
transmit power limit (200 kHz bandwidth), which
improves range and reliability, even underground
or inside buildings. And since it operates in a
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Too Many Internet Devices for IPV4
Due to the explosion in the number of websites, mobile devices, and
always-on IP connections (the latter of which is crucial to future IoT
deployments), the internet’s governing bodies realized that the IPv4
address space would not be sufficient over the long term.
Luckily, the shortage noted in 2011 has not had a serious impact because
of techniques such as Network Address Translation (NAT). This allows
a router to share the same external public IP address, or set of public
addresses, for all the traffic generated by systems on the internal network.
Because of NAT, many internal systems can share a common IP address
Chapter 3 IoT Connectivity: Types and Choices
Address Spaces / Numbers
for external internet access.
But the long-term solution for accommodating the billions of devices
constantly being added to the internet, especially with IoT applications,
is to upgrade the IP address space to a much larger number range.
The World Is Moving to IPV6
The problem of not having enough IPv4 address numbers will be resolved
when the internet world moves to IPv6, where the total address space has
been expanded to 128 bits (from the 32 bits used in IPv4). This allows 2 to
the power 128 (or approximately 3.4 x 10 to the power 38) IPv6 addresses.
Although not yet fully deployed across the internet, IPv6 networks already
are in use by many large corporations and websites. For example, Google
and Facebook have provided access to their systems in IPv6 networks.
Ultimately, every device and router will use IPv6 addresses to access
the public internet. In the interim, gateway systems provide address
translation functions, thereby allowing older IPv4 systems to access
future IPv6 networks.
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Chapter 3 IoT Connectivity: Types and Choices
TYPES OF CELLULAR
TECHNOLOGIES
This section provides an overview of the cellular
technologies available to IoT devices and applications for
long-range data transmissions. These cellular technologies
are evolving and will continue to change over time. You
should assume that new cellular technologies completely
will replace existing deployed technologies over time, so
plan the device and application lifecycles accordingly.
Brief History of Cellular
New cellular
Cellular service has evolved over time. Often, a fairly major change in the
technologies
technology would render a previous technology incompatible and necessitate
a replacement of the radios and handset, along with changes in the network
completely will
to support the new radios.
replace existing
In the cellular industry, these major changes loosely are termed “generations”
deployed
to distinguish and summarize their technology, the protocols used, the network
changes, and the commercial deployment phases.
technologies
Analog Cellular
over time so
The first cellular service was an analog cellular system, later termed First
plan the device
Generation (1G). In North and South America, this was the Advanced Mobile
Phone System (AMPS). It was deployed in the U.S. in the early 1980s and
and application
was shut down in February 2008.
lifecycles
AMPS used radio frequencies (spectrum) distinct from other wireless services.
accordingly.
In particular, the technology used relatively low-power transmissions, which
restricted the distance of the radio signals, to reach a tower (also called a base
station) where the voice call could be sent into the landline telephone system.
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from a tower—each tower received and transmitted only to the cellular
radio devices within that range. Grouped into cells (hence, the term “cellular”)
resembling a beehive, the tower radio did not communicate with devices
outside its cell. Cellular devices communicating in remote cells could use the
same radio channels (i.e., re-use the frequencies) without interfering with
calls in the closer cell.
Eventually, AMPS and other analog cellular services were discontinued
in most parts of the world (in the U.S., this was the “AMPS Sunset” in
February 2008).
Chapter 3 IoT Connectivity: Types and Choices
This allowed re-use of the radio channels beyond a particular distance
TDMA and GSM
To maintain backwards compatibility with AMPS in the early deployments,
technologists in the U.S. used a mechanism to slice each AMPS radio channel
in time, hence the general term for the protocol: Time Domain Multiple Access
(TDMA). Humans are unaware of the missing “times” when the channel is
used for other voice calls, as long as the duration of the missing time is short
enough. The TDMA protocol is quite successful at this function.
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TDMA), and it improved the efficiency of the channel by a factor of three
(since each call only used the channel one-third of the time). Essentially, each
channel now could support three TDMA voice calls simultaneously rather
than one AMPS voice call.
In Europe (and eventually most of the world), another TDMA approach was
used, termed the Global System for Mobile Communications (GSM). The
European and U.S. TDMA technologies were incompatible due to spectrum
allocations and channel differences, which meant that a GSM cellphone could
not operate in an ANSI-136 TDMA network and vice versa.
GSM rapidly became popular in Europe and in other parts of the world and,
Chapter 3 IoT Connectivity: Types and Choices
The standard deployment was called EIA-136 TDMA (eventually ANSI-136
with a far larger deployed base of cellphones, the economies of scale meant
that GSM cellphones rapidly became lower in cost than ANSI-136 TDMA
cellphones. Thus, the operators in North and South America eventually
abandoned ANSI-136 TDMA in favor of GSM to take advantage of this
reduced cost.
CDMA
In the 1990s, another new digital protocol was deployed, mostly in Asia and
North America. Rather than using TDMA encoding, the digitized human
voice bits are combined, or multiplexed, with “codes” using a mathematical
algorithm. Thus, this encoding protocol is called Code Division Multiple
Access (CDMA).
The combination of voice bits combined with codes allows the data to be
transmitted over a single, wider channel. The bits essentially are “spread”
across the spectrum width of that channel, and it is thus a “spread-spectrum”
communications system. Over the long term, however, CDMA struggled
with adoption in other parts of the world, and this led to a much smaller
prevalence of CDMA devices that remains today.
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When cellular systems became digitally encoded, it was natural to consider
treating the transmitted digital bits as something other than human voiceencoded bits. This allowed the deployment of data transmission services for
purposes other than human voice. This included communications from mobile
radio devices (data handsets) and data cards for mobile computers (laptops)
to access the increasingly important internet and the World Wide Web.
The mechanism for treating the digital bits as application data, rather than
human voice, was different in the deployed technologies.
2G GSM DATA: GPRS, EDGE
Chapter 3 IoT Connectivity: Types and Choices
Data Transmissions
GSM introduced a practical data transmission technology called General
Packet Radio Service (GPRS), followed by an improvement called Enhanced
Data Rates for GSM Evolution (EDGE) with higher throughput.
These technologies were popular for cellular data communications, although
the throughput rates are extremely slow compared to today’s smartphone
needs. In IoT applications, however, where the throughput requirements
were lower, GPRS has been a sufficient technology for low-data rate
transmissions. Thus, GPRS was widely used around the world for early
cellular IoT and M2M applications.
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Like GPRS in GSM, CDMA operators in many countries deployed a data
transmission technology called 1x Real Time Transmission (1xRTT). This
was faster than GPRS in its base throughput rate and provided a reliable,
extensive coverage data network for IoT applications.
In the U.S., the wide availability of 1xRTT made it an easy choice for physically
mobile applications, such as the automotive and trucking industry, that
needed coverage across the continent. The early deployment and expansion
of CDMA and 1xRTT led to excellent cross-country coverage.
However, the complexity of the CDMA data encoding protocol compared
Chapter 3 IoT Connectivity: Types and Choices
2G CDMA DATA: 1XRTT
to TDMA resulted in a higher cost for the radio modules, since chipsets for
CDMA radios are more complex. Although CDMA technologies for data
transmission continued to evolve through 3G and 4G, very little was used
for IoT applications past the 2G CDMA 1XRTT iteration.
3G UMTS (HSPA / HSPA+)
Over time, it became clear that 2G GSM voice and data transports, like
GPRS and EDGE that used the TDMA encoding protocol, were not spectrum
efficient. The cost of adding new spectrum continued to increase, as national
governments began auctioning new spectrum for smartphone data uses.
3G UMTS was developed to solve these and other issues. However, in
most IoT / M2M applications, the performance and throughput of the 3G
technology outpaced the needs of the M2M marketplace at the time. The
rapid development of 4G LTE networks outpaced the expansion of M2M
throughput needs, and, therefore, many 2GSM IoT / M2M applications over
the last several years leapfrogged 3G technologies and went directly to 4G
LTE. The final choice generally becomes a function of the cost of available
radio modules and service coverage.
3G CDMA (EV-DO)
On the CDMA side, 3G data standards were improved substantially to
enhance their data throughput rates with EV-DO Rev. A and EV-DO Rev. B.
However, much like 3G UMTS, 3G EV-DO has not been used extensively for
IoT / M2M applications for the same three key reasons: the higher throughput
(compared to 1xRTT) is not strictly required, 1xRTT coverage and availability
in the U.S. was excellent, and the EV-DO radio module costs are higher.
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One of the limitations faced by 3G technologies was that they used fixedwidth channels. With the ever-increasing number of smartphone data users,
the availability of wireless spectrum has created many new bands that are
not always optimally usable by 3G technologies. National governments have
auctioned a large number of new bands for smartphone users.
To use these new bands, the standards entities developed a new technology
for more flexible spectrum use. Since they also had the opportunity to select
the encoding protocols to use these new bands, Long-Term Evolution (LTE)
was designed to use a new protocol called Orthogonal Frequency Domain
Multiple Access (OFDMA). The specific encoding details of OFDMA is
beyond the scope of this book, but it has been termed a Fourth Generation
(4G) technology, since it is quite different from 3G and also meets some of
the original performance requirements set for new cellular implementations
Chipsets now
are available
and are
substantially
lower in cost
under the umbrella of a 4G service.
because of
What is quite important, however, is that LTE is very flexible in terms of
the reduced
channel widths that can be used and, thus, the available spectrum bands
Chapter 3 IoT Connectivity: Types and Choices
4G LTE
requirements.
can be partitioned into smaller blocks with greater ease. And it also allows
existing spectrum to be partitioned into multiple blocks, which can allow an
operator to deploy 4G without having to entirely remove older technologies.
This flexibility comes at a price. There are more than 40 bands available for
LTE use, and countries have not auctioned or made available the full set of
possible bands. Indeed, some bands may be impossible to use for LTE in
certain countries because they are dedicated to other uses.
Therefore, handsets that can be used for LTE everywhere must support a
number of different bands, and the addition of each band adds cost, since
filters and power-amplifiers inside the radios must support each band. For
IoT / M2M applications, this can increase the overall cost of the radio module
substantially. Smartphones can absorb the higher cost of multiple band
support, since it is a smaller percentage of the overall cost of the phone.
LTE also introduces the concept of categories (CAT) to define a set of
performance metrics that are dependent on specific parameters such as
the number of spatial layers, antennas, and protocols. Originally defined
as CAT-1 through CAT-8, these provided a different range of performance,
from 10 Mbits/sec download speeds in CAT-1 through 1200 Mbits/sec
downloads in CAT-8.
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are sufficient for power users but needs continue to grow and higher
categories (through CAT-18) have been added. For most IoT applications,
CAT-1 radios would provide sufficient performance, but originally were not
developed since the LTE chipsets with CAT-1 support were not deemed
adequate for smartphone users. However, recent developments in LTE
chipsets have allowed manufacturers to release CAT-1 modules for IoT
and M2M applications.
The standards bodies also defined CAT-0 radios for LTE that have reduced
performance and network requirements, although CAT-0 appears to have
been skipped by module manufacturers in favor of the newer CAT-M and
Chapter 3 IoT Connectivity: Types and Choices
Most LTE smartphones use CAT-3 and CAT-4 to provide data rates that
NB-IoT technologies. Chipsets now are available and are substantially lower
in cost because of the reduced requirements. A subset of service providers
has started to roll out network support for these categories, and this support
can be expected to grow over the next several years.
5G: Next Generation Coming Soon
Due to hit the marketplace in 2020, 5G has the potential to advance and
expand the IoT industry by the addition of significant improvements and
greater bandwidth accessibility.
These improvements include expanding the use of spectrum for IoT; greater
download speeds; more than 1000 times the capacity of 4G; reduced
latency; lower battery consumption; advanced functionality when compared
to earlier protocols; and much more. But there still are many issues to resolve
before acceptance is assured. For instance, 5G might not be supported
in many parts of the world due to the huge speed increase; radio signal
issues; compatibility with older devices; and security and privacy issues. It
is unclear at this point how suitable 5G technologies will be for IoT / M2M
deployments in the short term, and 4G variants are expected to maintain the
IoT deployment stronghold for the next several years.
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During the early phases of any new cellular generation
deployment, it often is the case that the newer generation
is not fully deployed everywhere.
Typically, the geographical coverage starts small and expands over time.
Thus, the cellular devices must support multiple generations of technologies
until coverage is fully complete for the new technology.
Cellular radios essentially “fallback” from newer generations to older
Chapter 3 IoT Connectivity: Types and Choices
CELLULAR FALLBACK
generations when the newer generation service is not available at a
particular geographical location. The control of when to fall back (including
which technology to fall back to) is incorporated in the Subscriber Identity
Module (SIM) or other radio firmware.
Two Fallback Mechanisms
To accommodate this fallback requirement in GSM, all 3G cellular devices—
modules, smartphones, and cellphones—are expected to function in 2G
GSM / GPRS and EDGE modes. This allows them to be used in areas where
3G UMTS service may not be available. This increases the cost of the cellular
device, but is an acceptable trade-off since it is essential to provide robust
service coverage for all users of the services.
Similarly, in CDMA, the 3G EV-DO modules, smartphones, and cellphones are
capable of being used in 2G 1xRTT modes, thereby enabling use in markets
where 3G may not be available (this, however, is a relatively rare situation).
In 4G LTE, there are two technology fallback mechanisms. For the CDMA
operators who are deploying LTE, the radio must fall back from LTE to EVDO and 1xRTT. For the GSM operators deploying LTE, the radio must fall
back from LTE to UMTS (HSPA) and then to EDGE or GPRS (since 3G is not
available everywhere).
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Chapter 3 IoT Connectivity: Types and Choices
LTE-Only
These fallback mechanisms increase the complexity and cost of the
chipsets within the current modules and smartphones. In time, when LTE is
commonly available everywhere that cellular services are deployed, it makes
sense to use radios that only use LTE services—called LTE-Only modules.
These have begun appearing for purchase, and more manufacturers will
deploy LTE-Only modules soon.
LTE-Only can reduce the cost of modules substantially. With scale, these
LTE-Only devices will become less expensive than the lowest-cost 2G
GPRS radios available today. In a few more years, this should be true for all
suppliers that provide IoT modules.
Customers who want to migrate from 2G to 3G services to 4G may find it
worthwhile to use LTE-Only modules to make the transition. This transition
date is dependent on the customer’s product longevity requirements.
HOW TO DETERMINE LOCATION
For many IoT applications, knowledge of the physical
location of the devices is important—not only to the device
but also to the application servers that process data from
the devices.
For example, in consumer automotive IoT applications, knowledge of the
The E911 location
exact location, to a reasonable degree of accuracy, of a vehicle crash is vital
accuracy
so that emergency first responders can be sent to the crash site quickly.
Seconds may matter.
requirements are
In truck telematics, a dispatch service may need to know the location of the
not necessarily
vehicles in its fleet to optimize the selection of the correct vehicle to handle
the specific event—perhaps it is the nearest vehicle to the pickup or has
the available cargo capacity for the job. In both cases, knowledge of device
sufficient for some
IoT applications.
location is important to a particular degree of accuracy.
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(FCC) has defined location accuracy requirements that must be made
available to Public Safety Access Point (PSAP) personnel. These often are
called the “E911” requirements, since the number 911 is used to access
emergency services from landline phones and cellphones.
The E911 accuracy requirements are not necessarily sufficient for some
IoT applications. The location error may not allow proper calculation of
routes or dispatch with sufficient optimization. For these applications,
more accurate location fix mechanisms must be used.
Location from Cellular Network
Chapter 3 IoT Connectivity: Types and Choices
For emergency dispatch, the U.S. Federal Communications Commission
Location-Based Services—To support the E911 requirements for
physically mobile cellphones used by humans (i.e., which are not fixed
at a particular address like a landline phone), cellular operators have
implemented various device location mechanisms in their networks.
These generally rely on classic radio triangulation techniques that provide
the specified degree of accuracy for the E911 requirements.
These network-based location fixes are made available to the
PSAP personnel as needed, and also are available from operators
as Location-Based Service (LBS) information, generally for a fee
charged for each location fix of a cellular device. Unfortunately, the
cost of these location fixes may be too high for many IoT uses, and the
accuracy may not be sufficient for some uses and, so, has not proven
to be a common technique.
Therefore, using the U.S. GPS (and the other Global Navigation Satellite
Systems or GNSS) system may well prove to be a superior solution for
most IoT applications.
46
Many cellphones now are equipped with Global Positioning
System (GPS) support that allows the phones to determine
their location and provide that data to the cellular network,
for E911 and other purposes. Enabling this function often
is an available choice in cellphones equipped with GPS.
In IoT applications, most modules have built-in GPS support (sometimes
including support for both systems operated by the U.S. and Russian
Chapter 3 IoT Connectivity: Types and Choices
GLOBAL POSITIONING SYSTEM
governments). In the future, support for the European Galileo and other
national satellite systems (collectively called Global Navigation Satellite
Systems or GNSS) will be implemented in many modules and handsets.
These can be used by the application firmware in the device, when needed,
for a particular function, such as responding to a location fix request by a
dispatch application.
In the latter half of the last century, the U.S. Department of Defense
deployed a set of 24 satellites into Earth orbit for a very singular purpose—it
allowed a GPS-equipped device to determine its location anywhere on the
planet with very good accuracy.
Originally intended for military uses, the U.S. government made the system
and its information available for civilian use in the 1980s, without any
fee or subscription charge. This enabled a large number of new location
applications around the world.
For example, the truck telematics industry relies heavily on GPS to locate
trucks and trailers. Hikers and off-road personnel use hand-held GPS
trackers to avoid becoming lost. High-accuracy augmented GPS services are
used by farmers to locate the farm machinery to within a few centimeters
of present location. Survey equipment can use GPS to accurately measure
locations for mapping and thereby increase map quality and improve route
guidance systems in vehicles.
A satellite service similar to U.S. GPS, called GLONASS, has been deployed
by the Russian government. The European Union is in the process of
launching its own system called Galileo. The complete 30-satellite Galileo
system (24 operational and six active spares) is expected by 2020.
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Chapter 3 IoT Connectivity: Types and Choices
The Indian government has introduced its own localized system, called
IRNSS, to determine location, but only over the Indian subcontinent.
Similarly, the Chinese government satellite location systems, called
BeiDou-1, BeiDou-2, and BeiDou-3, for global location coverage similar to
the U.S. and Russian systems, with the final launch occurring in early 2018.
In time, Galileo will provide a free, low-precision location fix with an accuracy
of one meter, with higher precision fixes provided for a fee. Since it is a new
Ground-based
system, it also has new features that are not available in the older U.S. GPS
references
and Russian GLONASS systems. For example, Galileo has radios that will
can be used
support a unique relay service for Search-and-Rescue (SAR) distress signals,
allowing emergency dispatch around the planet.
In addition to the GNSS transmissions, enhancements are available to
dramatically improve location accuracy. For example, a set of ground-based
references can be used by certain receivers to greatly enhance the basic
accuracy of the U.S. GPS system from 15 meters to less than 10 centimeters.
This enhanced system is called Differential GPS and enables users to employ
by certain
receivers to
greatly enhance
the basic
accuracy of the
automated equipment that need a very high accuracy location fix.
GPS system
How Does Basic GPS Work?
from 15 meters
In the U.S. GPS system, more than 30 GPS satellites orbit the Earth twice
to less than 10
a day, in a very precise manner, at an altitude of approximately 20,000 km
while transmitting accurate time signals from its on-board atomic clocks to
centimeters.
ground GPS receivers.
These GPS receivers take the received time data and use triangulation
(more correctly, “trilateration” using points of intersection of circles on a
sphere; angles are not measured) techniques to determine the location of the
receiver. The receiver essentially compares the time a signal was transmitted
by a GPS satellite to the time it was received. This time difference allows the
receiver to determine its distance from that satellite.
When time difference and distance are determined from a number of GPS
satellites, the location of the receiver can be determined within 5 to 10
meters of accuracy on the surface of the Earth. At least three satellites must
be used for a latitude-longitude fix on the surface of the Earth, and a fourth
satellite then can determine the altitude of the receiver.
It should be emphasized that the above is a very general description of the
method used to determine location from the GPS satellite signals. There are
a number of other factors that affect the accuracy and are taken into account
by sophisticated receivers.
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Chapter 3 IoT Connectivity: Types and Choices
Einstein’s Special
and General Theories
of Relativity must
be used to correct
the data, since
time literally flows
at a different rate
for satellite clocks
compared to Earthbound clocks.
49
accuracy. Thus, a 10- or 12-channel GPS receiver (which allows it to listen
to 10 or 12 GPS satellites simultaneously) generally will provide a more
accurate location fix than an older 4- or 6-channel receiver. Modern GNSS
chips can listen to more than one satellite system simultaneously (such as
GPS and GLONASS) for best accuracy.
Furthermore, since the GNSS satellites are in motion and are quite far
above the Earth’s surface (i.e., operating in reduced gravity), Einstein’s
Special and General Theories of Relativity must be used to correct
the data, since time literally flows at a different rate for satellite clocks
compared to Earth-bound clocks.
Chapter 3 IoT Connectivity: Types and Choices
For example, the more satellites the receiver listens to, the better the
Without proper compensation, the relativistic effects of the speed of the
satellites, combined with their height, could create a net error of about
38 microseconds per day for the satellite clock compared to an identical
ground-based clock. This may seem quite inconsequential, but the
difference in time can make the location fix inaccurate within a matter
of minutes, to beyond the 5- to 10-meter accuracy of the system. Then,
accumulated errors could make the location fixes completely unreliable and
unusable in a matter of days since GPS requires nanosecond time accuracy.
Fortunately, the GNSS receivers uses these Einsteinian Relativity
calculations and corrects to ensure that the time and location accuracy
is excellent, and remains excellent, under most conditions.
With multiple location fixes (i.e., taken over time), the data fixes also can
be used to determine other information, such as speed and direction
(i.e., velocity). Sophisticated tracking devices can use the data to display
the location and provide route guidance in ways friendlier than a simple
latitude-longitude-height-time record that is displayed on a graphical
moving map, for example.
Limitations of GNSS
Location fixes from global location devices are not perfect. In “urban
canyons” (i.e., within cities with tall buildings), it may be difficult for GNSS
receivers to lock onto more than a few satellites since the signals may
be blocked by buildings. This may reduce the accuracy substantially.
Regardless, it may remain sufficiently capable for many uses of that location
data. A higher-performance GNSS receiver with many channels may
perform better in urban canyons since it has a better chance of listening to
satellites that may be “visible” and not blocked by tall buildings.
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to the signals from the satellites when inside buildings and underground
garages. This limits use in indoor applications, although new technologies for
indoor tracking to supplement outdoor GNSS performance are in the works.
Sometimes, heavily overcast days can reduce the strength of the GNSS
signal, enough to prevent the receiver from locking on to the signals,
particularly when the receiver has been re-started from a power-off
condition. If the internal clock of the receiver is not sufficiently accurate,
the measured time may have drifted and the receiver could be attempting
to listen to a set of satellite signals that are not present. Those particular
satellites may not be visible. Under these conditions, it may take a while for
Chapter 3 IoT Connectivity: Types and Choices
The signal strength is low enough that many GNSS receivers cannot listen
the receiver to lock onto the satellite transmissions and provide sufficient
accuracy.
IoT applications that depend on location accuracy must take this potential for
incorrect location fix data into account when deploying a device in the field.
51
CHAPTER 4
54
55
56
59
61
CONNECTIVITY
MANAGEMENT
PLATFORMS
WHAT IS A CONNECTIVITY MANAGEMENT PLATFORM?
THE DIFFICULTIES OF MANAGING IoT CONNECTIVITY
WHY BUSINESSES NEED CONNECTIVITY
MANAGEMENT PLATFORMS
ESSENTIAL CONNECTIVITY MANAGEMENT
PLATFORM FEATURES
CMPs ARE INTEGRAL TO
THE IoT ENVIRONMENT
Chapter 4 Connectivity Management Platforms
CONNECTIVITY
MANAGEMENT
PLATFORMS
Advanced, diversified, and cost-effective connectivity is integral to the success of
Internet of Things and machine-to-machine communications. Smart devices and
network endpoints generate unprecedented amounts of data that must be collected,
stored, and analyzed to perform IoT-driven business operations and services.
These processes involve data transmission using various connectivity services and
technologies that organizations must manage effectively to maximize the value
potential of their IoT deployments.
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53
technologies are being introduced regularly, successful IoT deployments
are able to rapidly change with the evolving wireless landscape to take
advantage of new technologies and reduced rates. The result is an
environment where multiple technologies are utilized across multiple
suppliers, adding operational complexities and costs to IoT deployments.
Connectivity Management Platforms (CMPs) exist to help reduce the
complexities of managing an IoT deployment, but also can make the problem
worse if not utilized correctly. This chapter explores the role of CMPs in
the modern IoT infrastructure, IoT organizations, and the evolving IoT
enterprise landscape.
Chapter 4 Connectivity Management Platforms
Furthermore, as wireless technologies become commoditized and new
WHAT IS A CONNECTIVITY
MANAGEMENT PLATFORM?
IoT devices have evolved into smart network endpoints
that extend the reach of cloud operating systems and
perform intelligent actions on their own. These devices
don’t require unique software embedded in every
hardware device.
Large IoT networks leverage multiple connectivity providers to address
diverse business needs. The result is an increasingly complex network
of smart devices that must be managed as a ubiquitous system. These
complexities not only cause problems from a technology perspective but
may drain financial and management resources merely to keep IoT systems
operational as a unified network.
With limited resource availability and increasing complexity of IoT networks,
organizations must automate the way they manage, configure, control, and
track IoT device information. CMPs automate these processes to enable
effective deployment, management, and utilization of IoT networks that span
disparate geographical locations, connected with multiple service providers,
and designed to scale exponentially.
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Managing IoT deployments on any wireless technology
is a complicated endeavor. Consider the geographic
considerations of IoT networks that span multiple
countries, each presenting its own set of financial, legal,
compliance, and technology challenges.
Lack of visibility and control is inherent in these circumstances, especially
Chapter 4 Connectivity Management Platforms
THE DIFFICULTIES OF MANAGING
IoT CONNECTIVITY
when operational excellence of multinational organizations is tied with supply
chains, inventories, logistics, and departments located in globally dispersed
sites—all of which use connected systems and devices to operate.
Merely keeping IoT deployments connected is a challenge in itself. Even
with high signal strengths, IoT networks may be impacted with hardware,
firmware, configuration, or application-level issues. Fast and effective issue
resolution is dependent upon real-time monitoring and accurate issuetracking capabilities. Failure to resolve connectivity issues not only increases
operational costs but also risks system-wide outages and downtime that
may lead to non-compliance and legal implications, as well as customer
dissatisfaction and damaged brand reputation.
In today’s wireless landscape, organizations need multiple connectivity
options to support large-scale IoT deployments. No single technology
or provider delivers the most reliable, cost-effective, high quality, and
advanced connectivity services. This means organizations must manage
multiple supplier agreements and manage their deployment across multiple
management platforms. And each platform will have its own set of features,
functionality, and capabilities. Disparate platforms force organizations to
collect, standardize, and analyze data from various platforms to perform
desired IoT operations. This inability to standardize connectivity operations
prevents cost optimization and restricts scalability.
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a single interface to proactively manage and monitor their IoT deployments,
connectivity channels, and the other associated financial, legal, and technical
aspects. This capability ensures reliable and high-value performance of
IoT systems—regardless of deployment location, network span, or
operator diversification.
WHY BUSINESSES NEED
CONNECTIVITY MANAGEMENT
PLATFORMS
Chapter 4 Connectivity Management Platforms
Organizations pursuing scalable IoT solutions need to find ways to create
The Internet of Things presents vast strategic business
advantages for the modern enterprise. IoT brings
automation and intelligence to everyday objects, devices,
and things―looking to revolutionize the consumer and
enterprise market segment alike.
And mirroring this automation and intelligence with a cost effective and
efficient management infrastructure has an often overlooked impact
on determining the success or failure of an IoT solution. Managing IoT
deployments cost effectively is essential, and exponentially difficult with
a multi-technology, multi-provider deployment.
A centralized CMP is required to address the consolidation challenges
associated with operating large deployments of IoT devices across multiple
providers and technologies. The following areas will be key for any business
looking to gain value from a CMP in a highly scalable IoT environment.
Market Drivers for CMPs
The economies of scale for using IoT platforms will affect all CMP consumers,
from the connectivity provider to the OEM / application service provider to the
developers. Scalable, flexible CMPs will be essential for these partners to
transition from custom vertical solutions to horizontal platform-based solutions.
This has the main advantage of enabling them to work with high velocity,
volume, and variety—or the “three Vs”. High velocity in a CMP will spread
the cost of infrastructure across many industry verticals. High volume will
result in shorter design cycles and rapid deployments. And variety as part
of a CMP means integrated network information can enable a richer
application experience.
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driver of the need for CMPs. Enterprises will first need to consider whether
they want wireless or wired connectivity or, for some applications, they may
need both. Within the realm of wireless, options range from varieties of
cellular and satellite data services to short-range wireless technologies such
as Wi-Fi and personal area networking, including Bluetooth or ZigBee. Bestin-class CMPs should be should be able to deal with all of these technologies
and manage the protocols effectively.
CMP Technology Needs
The most integral connectivity management functions sought by IoT
connectivity operators, as well as enterprise consumers and developers,
Chapter 4 Connectivity Management Platforms
It also is crucial to recognize the diversity in connectivity options as a primary
range from network visibility and control to data security to end-user
management, billing, and reporting.
Diverse vertical applications and environments will need to access a typical
CMP for industries such as healthcare, automotive, and manufacturing. Ease
of integration with enterprise applications, including APIs, network data
feeds, etc., is essential.
CMP Architecture
The CMP plays a vital role in an IoT technology stack, enabling the promised
technology and business functions within the IoT infrastructure. Enterprise
users expect “single pane of glass” access for multiple connectivity
technologies, whether they’re using cellular or Wi-Fi, so the CMP must
support a diverse set of IoT applications.
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Chapter 4 Connectivity Management Platforms
CMPs can offer a
diverse range of
capabilities to serve
your organization’s
unique requirements.
Getting the right
fit is critical for
effective connectivity
management.
58
CMPs can offer a diverse range of capabilities to serve your
organization’s unique requirements. Getting the right fit is
critical for effective connectivity management.
While not every solution in the market addresses all of the fundamental
enterprise and operator needs, you’ll want to consider these factors in your
prospective CMP:
Core CMP Functions—Your CMP should enable a range
of business and technology functions associated with the
connectivity of your IoT endpoints. These include the management
of zones, devices, users, accounts, pricing, policies, billing and
It is crucial to
recognize the
diversity in
connectivity
Chapter 4 Connectivity Management Platforms
ESSENTIAL CONNECTIVITY
MANAGEMENT PLATFORM
FEATURES
options as a
primary driver
of the need
for CMPs.
invoicing, alerts and reporting, and SIM lifecycle management,
among others.
Global and Multi-Carrier Footprint—IoT networks that span
disparate geographical locations and multiple countries use
services from multiple providers. Your CMP must support
this capability.
Security—Your CMP should offer features that ensure high
data security, availability, and end-user privacy. These features
typically include identity and access management, audit trails,
anomaly detection, denial of service prevention, and
strong encryption.
Multiple Carrier / Multiple Technology Support—Your CMP must
support multiple connectivity technologies—from cellular (LTE,
GSM, HSPA, CDMA) to non-cellular (Wi-Fi, Bluetooth ZigBee,
satellite, and LPWA). And you should have the flexibility to
bring your own connectivity from the operator or carrier of your
choice. All types of data transmission protocols, technologies,
and standards should be supported across different transmission
layers as required by your IoT solutions.
Quick Time to Market—It takes long design and deployment
cycles before custom vertical solutions are released and create
value for your IoT service organization. Using a CMP ensures that
IoT connectivity is managed right from the beginning, thereby making
the entire getting-to-market process much simpler and quicker.
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of pricing from multiple connectivity providers. To reduce the
total cost of connectivity services, your CMP should help you
optimize pricing for different IoT app needs in different business
functions and spread the infrastructure cost across multiple
tenants and verticals.
Billing and Real-Time Data—Accurate billing information
updated in real time ensures that you only pay for what your
devices consume.
Variety of IoT Application Needs—Different IoT applications
present different needs for connectivity management. Your
Chapter 4 Connectivity Management Platforms
Flexible Pricing—Enterprises need to accommodate a range
CMP should support these diverse and evolving needs as more
functionality is added to your IoT applications.
Open System—Strong integration with your infrastructure and
other enterprise applications via open APIs.
Flexible Accounts and User Access—Progressive and agile
organizations scale teams rapidly to meet evolving resource
requirements. The ability to create and manage new
accounts and streamline user access enables effective
connectivity management.
Diagnostics and Fault Resolution—CMPs can extend the
monitoring and diagnostic capabilities of your IoT systems with
rich graphical representations of connectivity patterns and
defined performance metrics.
Light Touch Integration—Your CMP should operate as a
standalone tool and connect with other enterprise applications
only as required.
Highly Scalable and Elastic—Your IoT needs will change.
Consider a connectivity management solution that can
accommodate changes. You want a solution that is future proven
so as to withstand changes in the connectivity marketplace.
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services across different IoT deployments, organizations risk connectivity
issues that present severe business, technology, and legal implications. The
traditional practice of using manual processes or individual platforms to
manage IoT connectivity service is both time consuming and ineffective,
but CMPs can help solve this issue.
CMPS ARE INTEGRAL TO THE
IoT ENVIRONMENT
Chapter 4 Connectivity Management Platforms
Without a single-pane-of-glass view for managing multiple connectivity
IoT deployments are driving business model innovation
among progressive organizations pursuing smart
technologies and advanced connectivity solutions to
generate unprecedented new revenue streams.
IoT deployments are driving business model innovation among organizations
pursuing smart technologies and advanced connectivity solutions to generate
unprecedented new revenue streams. Intelligent IoT devices generate
invaluable data in real time that is transmitted to back-end systems through
various transport systems, including cellular and Wi-Fi communication.
Today’s agile organizations increasingly rotate data between different
processes, functions, and teams.
61
organizational demands tend to create a performance bottleneck among
agile enterprises if users, technologies, performance, and processes are not
managed effectively. These issues only will grow with the rapid adoption of
IoT technologies. And since every company needs to be technology aware
in the present IoT-driven enterprise landscape, organizations will pursue a
diverse range of connectivity solutions to serve their specific exploding
IoT demands.
The bottom line—effective management of IoT connectivity can be a
major contributing factor to the success of an IoT deployment. Managing
multiple technologies and multiple providers from a single interface enables
Chapter 4 Connectivity Management Platforms
Advanced IoT connectivity systems that must scale rapidly to meet varying
scalability, reduces operational complexities and costs, and enables future
product evolution with minimal impact to business processes.
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CHAPTER 5
65
66
72
76
IoT SENSORS
AND DATA
COLLECTION
WHAT IS A SENSOR?
SENSOR TYPES
CONVERSION TO DIGITAL DATA
CALIBRATION AND LINEARIZATION
Chapter 5 IoT Sensors and Data Collection
IoT SENSORS AND
DATA COLLECTION
When deploying Internet of Things application devices, the connected device
generally needs to report more than just its physical location (although that is a
very typical use).
In this chapter, we describe a few of the more common sensor types, what they
measure, and how to use them.
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Dictionary.com defines a sensor as “a mechanical or
electrical device sensitive to light, temperature, radiation
level, or the like, that transmits a signal to a measuring
or control instrument.”
This is an easily understood definition that can be reworded a bit in the
context of IoT applications: a sensor is “a device, generally small and
mechanical, that is sensitive to a measurable physical parameter and provides
Chapter 5 IoT Sensors and Data Collection
WHAT IS A SENSOR?
a measurable signal level directly related to the measured amount of that
physical parameter.”
For example, an IoT device may measure a particular physical parameter,
such as temperature, at a location for an application purpose. These physical
parameter measurements require sensors that are capable of measuring,
recording, and transmitting the specific value of that physical parameter for
the IoT application to fulfill its functions.
Sensors often are integrated circuits that are designed for these kinds of
IoT applications since their small size and low cost make them appropriate
choices. For example, many of the sensors described in this chapter
are available in high-end smartphones. These include accelerometers,
thermometers, gyroscopes, magnetometers, and heart rate monitors, just
to name a few. But there are other sensors that are unique to a particular
industry or market.
65
In most typical sensors, the specific mechanism used
to measure the physical parameter depends on the
parameter ranges being measured, the desired sensitivity
and accuracy, whether the sensor is exposed to adverse
environmental conditions, the cost target, etc.
Since it is nearly impossible to list every possible sensor, its type and purpose,
its capabilities, and the physical parameter that is measured, this section
Chapter 5 IoT Sensors and Data Collection
SENSOR TYPES
focuses on general descriptions of a few types of sensors rather than making
specific recommendations.
Accelerometers
Acceleration is a change in velocity (a change of speed and / or direction).
Accelerometers are devices that measure acceleration. The parameter being
measured may be a static force, such as gravity exerted on a device. Other
accelerometers make dynamic force measurements so as to measure motion
changes and vibration.
An example of an accelerometer is a chip in a moving vehicle that measures
changes of speed and uses high acceleration (deceleration) readings—such
as those experienced in an automobile accident—to trigger airbags to
protect the passengers.
In some industrial applications, vibrations detected by an acceleration sensor
could be an excellent indicator of a potential problem with a moving part,
such as a motor with bearings that are worn. Timely transmission of data
from vibration sensors can enable early detection of potential problems where
preventative maintenance could avoid catastrophic failures.
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Chapter 5 IoT Sensors and Data Collection
Multi-Axis Accelerometers and Sensitivity
In some applications, there is a need to measure the change in speed,
or vibration, in more than one direction (or dimension). Thus, some
accelerometers can take readings from more than one axis. Typically, a
two-axis sensor measures motion changes and vibration in two dimensions,
and the third axis on a three-axis sensor can provide information for threedimensional physical motion detection.
Accelerometers use differing techniques for measuring the actual motion
changes. Generally, there is a physical component that changes an electrically
Y
measured characteristic (such as capacitance or resistance) in a material
when changes in motion are detected.
Due to the types of accelerations being measured, the sensitivity of the
X
Z
accelerometer often is in a limited range to the required accuracy specific to
a particular application use. The choice of sensor, therefore, depends on the
specific range of acceleration values to be measured for that application.
For example, a shock sensor designed to release an airbag in a vehicle
accident measures quite a different range of acceleration compared to a
vibration sensor that measures vibration on a high-speed motor to monitor
its bearings. The sensitivity, range, and accuracy required for these widely
disparate applications is, naturally, quite different.
Temperature Sensors
Temperature is a physical parameter that often is measured and reported—
particularly in industrial applications where an accurate temperature reading
may be needed for process control. Depending on the desired range, there
are various types of available sensors for measuring temperature.
Silicon chip (semiconductor) sensors are used in the range from -50 to
+150 degrees C (Celsius scale). These are quite accurate and linear—to
within 1 degree C—without a need for extensive calibration. They are as
rugged as most integrated circuits (plastic package and metal can style)
and relatively inexpensive.
Thermistor sensors can cover a wider range—from -100 to +450 degrees
C—for covering more applications. A thermistor often is more accurate than
a silicon chip temperature sensor, albeit at a slightly higher cost per sensor.
More important, they require complex correction algorithms to achieve that
good accuracy and linearity over the desired temperature range.
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to +900 degrees C, but are quite difficult to use since they are more fragile
than other types of temperature sensors. They are the most accurate—often
a hundred times more accurate than a silicon chip sensor—although this
requires the same complex solutions for linearization as thermistors, and
Light sensors
some models can be quite expensive.
can be used
Finally, for the widest temperature range, particularly for very high
with light
temperatures, a thermocouple is the correct choice. They are quite rugged
and can be used from -250 to +2000 degrees C for many industrial
applications, such as chemical process monitors and high-temperature
electric furnaces (for example, those used in the semiconductor industry).
that is not
visible to
Chapter 5 IoT Sensors and Data Collection
Resistance Temperature Detectors (RTD) provide yet more range, from -250
human eyes.
One important fact about temperature sensors is that the response time
for measuring changes in the temperature data can be quite slow since
temperature changes are not as “rapid” as other measured physical
parameters. The sensor readings must settle and equalize to the temperature
being measured. This must be taken into account when taking readings.
Light Sensors
Light sensors cover a broad range of potential applications, from automated
brightness control in cellphones to medical diagnostic equipment. Not
surprisingly, there also is a wide range of available light sensors that use
different methods for measuring light.
A very early example of ambient light sensors used in consumer applications
are photocells within lamps that automatically turn the lamps on at dusk
and turn them off at sunrise. These are simple ambient light detectors, with
equally simple sensitivity controls that are adjusted manually by the owner
of the product. The actual value (in lumens) of the ambient light is not
measured or reported—it simply is used to perform the designed function
of automatically turning the lamp on and off.
Simple light sensors also can be used for proximity detection. Counters in
manufacturing systems use the presence or absence of light on photocells
to measure products being moved past the counter on conveyors. Closing
garage doors can reverse direction to avoid hurting children or pets that
cross under the door by sending a beam of light across the door opening to
a photocell. Once the beam is cut, the sensors send a message to reverse
the garage door direction.
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Infrared light sensors can be used as motion sensors in alarm systems or to
automatically light a driveway or passage when people and pets come into
range. Full-range light sensors are used when the light measurements need
to correspond to human vision.
As with other types of sensors, the mechanism used to measure ambient
light varies depending on the application. Simple Cadmium Sulfide (CdS)
or Cadmium Selenide (CdSe) photoresistors change their resistance as a
function of the ambient light. This resistance change can be measured by
electronic circuits to provide an indication of a change in the ambient light.
Chapter 5 IoT Sensors and Data Collection
Often, light sensors can be used with light that is not visible to human eyes.
It should be noted that these photocell devices can be significantly affected
by temperature and are quite unsuitable when accuracy is required.
Common uses of photoresistors include
automated light controls in lamps, dimmers in
alarm clocks and audio system displays, or control
of street lighting systems—where the accuracy of
the reading is not of paramount importance.
Photodiodes and phototransistors with active semiconductor junctions
are used when greater accuracy is required, since the ambient light is
converted into a measurable current that can be amplified or converted for
a measurement. This measured current can be used to determine the amount
of ambient light on the sensor. And since semiconductor junctions are
affected by ambient light, integrated circuits where this effect is not desired
must be enclosed in opaque packages.
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In modern, high-end smartphones, integrated chip sensors that measure
motion, direction, pressure, magnetic fields, rotation speeds, and more
are becoming quite common. These can be used to augment the location
information and human motion in the cellphone.
In chip form, these usually are Micro-Electro-Mechanical Systems (MEMS)
sensors for many different parameter measurements. The implementation
of MEMS uses ultra-miniaturized physical structures—beams, arms, and
associated electronics—to measure the motion of the structures when the
chips move. The physical motion is converted into electrical signals that can
Chapter 5 IoT Sensors and Data Collection
MEMS Sensors
be measured for the specific function being measured—for example, whether
it is rotational motion or air pressure. The sensor essentially converts a
mechanical motion into an electrical signal.
A gyro sensor, for example, senses rotational motion and changes in
orientation. These can be used in a variety of applications, such as correcting
for hand-held shake in video and still-image cameras or for motion sensing
for video games. In smartphone applications, a screen display can be rotated
automatically between portrait to landscape display modes when the phone
is physically rotated.
MEMS sensors generally are manufactured in the same large-scale
facilities as semiconductors or chips. This means that the mechanical
precision of the devices can be very high and allow for excellent, reliable
performance at low cost.
Simple Switch Sensors
At the very low end of the sensor markets are the simple state or position
sensors that provide an “open” or “closed” state information. A door or
window sensor used in security systems often is a simple magnetic reedrelay switch that opens, or closes, an electrical circuit depending on the
position of a small magnet physically located close to the switch.
These simple magnetic reed-relay switches can be used for sensing
when a cabinet—such as a medicine cabinet, oven door, or food storage
compartment—has been opened in a senior citizen’s home-monitoring IoT
application. A detection of the change of state of such a switch—from open
to closed or vice-versa—can be interpreted as evidence that the monitored
person has performed their expected regular daily routine.
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In industrial and simple applications, many standard sensors have been
developed and commercialized over the years. These have evolved and
improved over time. The cost and size of sensors have been reduced with
increasing efficiency and practicality.
Recently, however, particularly with the start of the IoT revolution, there has
been a great demand for a variety of new parameters to be measured at
ever-larger scale and ever-lower cost.
The healthcare industry is among those at the forefront of this revolution.
Chapter 5 IoT Sensors and Data Collection
Specialized Sensors
New methods to measure human medical parameters are being researched
and commercialized, and this has seen an explosion of new techniques
(and sensors) to measure these parameters. In medical monitoring applications,
the need for new measurements, reduction in the size of devices, and the
rapid adoption of wearable fitness and medical products is driving significant
research and growth.
Beyond the sensors incorporated into hand-held or wearable products
(e.g., smartwatches, clothing, and bracelets) and for reading basic body
functions or medical monitoring products (such as continuous blood sugar
monitors and insulin dispensers), there also is a need for semi-permanent
sensors implanted within the human body. The research into tiny, implantable
sensors has been energized by the availability of semiconductor and MEMS
solutions, including for mission-critical applications such as cardiac
monitoring and vision correction.
For example, medical startups are developing MEMS sensors that are
implanted into pulmonary arteries using cardiac catheter procedures similar
to angioplasty. These sensors can measure artery pressure and transmit the
readings to a nearby wireless device within the patient’s home. The readings
then can be sent to a database for review by medical practitioners.
These new methods for measuring human parameters, the sensors using
these methods, and devices using these sensors have been commercialized
in the past few years. Newer sensors will be introduced in the next decade
and will completely revolutionize the medical healthcare industry in ways that
we cannot even imagine today.
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Because of the wide variety of sensors, the types,
the parameter being measured, and what physical
phenomenon is converted into a measurable signal,
it is difficult to provide implementation details. Thus,
this section will discuss general concepts rather
than specific information.
Chapter 5 IoT Sensors and Data Collection
CONVERSION TO DIGITAL DATA
Sensors often are used in local applications, where their signal is processed
using circuitry designed for that local application. However, in a sensor that is
used for transmission of the measurement to remote computing and analytics
systems, the measured electrical parameter must be converted into a digital
value, or number, for the transmission.
Furthermore, the specific electrical signal from different sensors may vary
over a wide range of current or voltage, or other electrical parameter (such as
resistance or capacitance) and often must be converted and amplified into a
voltage that can be measured more easily.
If necessary, the signal must be filtered electronically to eliminate signal noise
or to reduce the frequency of the measurement for the requirements of the
application. For example, a temperature sensor generally changes its value
relatively slowly as the sensor matches its environment. Therefore, a rapid
change in reported temperature may be an inaccurate reading, which should
be filtered to reduce potential errors.
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With devices that measure sensors for data transmissions, two input
capabilities generally are available:
• A digital input pin that reports an electrical “high” or “low” value in a single
digital bit (sometimes grouped into multiple pins and multiple bits).
• An analog input pin that receives a voltage from a sensor and converts
that voltage, using an Analog-to-Digital Converter (ADC), to a digital
number that represents the sensor value.
These devices also may have output pins where a received value is used to:
• Set a digital output pin to either a “high” or “low” state based on an
instruction to do so.
Chapter 5 IoT Sensors and Data Collection
Device Input / Output
• Set an analog output pin to an analog voltage, using a Digital-to-Analog
Converter (DAC), representing the received digital number.
ADC Techniques
In sensors that measure parameters over a range, a single bit is insufficient—
the range of the measured sensor readings must be converted into a range of
digital values for the application.
However, the specific signal from a sensor may differ widely in its current or
voltage or resistance value. This signal—whether it is a current or resistance
change—must be “conditioned” or converted to an analog voltage. If the
signal from the sensor is a voltage, it might not be in the correct range for an
ADC to convert to a digital number and, thus, may require amplification to a
higher or lower voltage range.
For example, a commonly available semiconductor temperature sensor
provides an electric current of 1 microamp per degree Kelvin when power is
applied to it. Over a useful range of -50 degrees C (or 223 degrees Kelvin)
to +150 degrees C (423 degrees Kelvin), this current is approximately 223
microamps to 423 microamps.
This current can be used in a circuit with an Operational Amplifier (Op-AMP)
and other components (resistors, capacitors, and diodes) to convert the
current to a voltage in the desired operating temperature range being
measured. This voltage then can be measured by an ADC and processed by
the device taking the temperature measurement for the application function.
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functions for converting the measured physical parameter directly to a
number that is sent to the device processor or communications
module for transmission.
For example, a GPS device may report continuous position and time readings
on a serial port using common National Maritime Electronics Association
(NMEA) formats called NMEA 0183 or NMEA2000. This data already is
“conditioned” into a text format that can be used by a device processor to
communicate and transmit the location data.
ADC and DAC Resolution
Chapter 5 IoT Sensors and Data Collection
Some sensors, usually more complex and expensive, may have built-in
When converting the analog voltage signal from a conditioned sensor to a
digital value or number, the ADC has a pre-defined resolution based on its
design. This means that the full range of the measured analog signal varies
from a zero value to a maximum numerical value, with incremental steps
defined by the resolution of the ADC.
For example, an 8-bit ADC will convert the voltage level to an integer
between a low value of 0 to a high value of 255 to represent the value of the
analog signal in approximately equal steps. This may be quite sufficient for
many IoT applications.
In other applications, it may be necessary to use a 12-bit, or perhaps even
a 16-bit, resolution ADC for the conversion. A 16-bit ADC provides a digital
numerical value between 0 and 65535 based on the input analog voltage.
With higher resolutions—particularly with low signal levels, the signal
conditioning and amplification circuits may need special design to ensure that
electrical noise does not result in erroneous readings.
It is important to note that resolution is not the same as accuracy or linearity.
It merely identifies the number of integral steps between the lowest and the
highest value being converted and reported.
A full discussion of these concepts is beyond the scope of this book.
Interested readers can refer to the data sheets and applications notes from
ADC and DAC suppliers for more information.
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Chapter 5 IoT Sensors and Data Collection
Resolution is not the
same as accuracy
or linearity. It merely
identifies the number
of integral steps
between the lowest
and the highest value
being converted
and reported.
75
Quite often, the communications modules or modems—particularly cellular
products used in industrial IoT applications—have multiple input and
output (I/O) pins that can provide the conversions from a measured physical
parameter to a number. This can be a simple on / off state using digital
input pins, or an analog voltage reading with an on-board Analog to Digital
Converter on an analog input pin that is converted into a number that is
transmitted on the communications network.
Some modules also have digital output pins for setting a state external to
the application—for example, to activate a relay to turn on a light, power on
Chapter 5 IoT Sensors and Data Collection
Modules or External Processors
an electrical device, disable a vehicle, or perform some similar remote
IoT function.
A few modules and modems also have DACs that take a digital number
received from the communications network and output an analog voltage on
an analog output pin in a specific voltage range. This may be used where an
analog voltage is used to perhaps control the position of a liquid flow valve or
the speed of a motor in an industrial IoT application.
CALIBRATION AND LINEARIZATION
As described earlier, a simple sensor application (such as
a photocell that controls a lamp to turn on or off based
on ambient light) may not need an accurate reading or
sensor value. However, when accuracy is important for
an application, calibration of the sensor signal may be
needed to ensure that the data reading is accurate to
the required degree.
For example, the semiconductor temperature sensor mentioned earlier
can provide a reading of 1 microamp per degree Kelvin for its environment.
However, does a reading of 273 microamps actually mean that the
temperature is exactly 273 degrees Kelvin (0 degrees C)? Or could the
reading be incorrect to a certain amount of error? Without calibration,
it is difficult to be completely certain, although it is a good estimate
of the temperature.
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Resistance Temperature Detectors can be a hundred times more accurate
than a semiconductor temperature sensor, but without correction, its readings
are quite useless. The RTD requires precise signal conditioning, linearization,
and calibration to achieve that accuracy.
These corrections often are applied digitally, as when a reading from the RTD
is first converted to a digital value, and then the correction is applied. Indeed,
different types of RTDs need different types of corrections. For example, a
platinum RTD has two distinct relationships to temperature with different
polynomial equations describing its resistance above and below 0 degrees C.
Chapter 5 IoT Sensors and Data Collection
Other temperature sensors are even more problematic. For example, the
In an RTD, to achieve the best accuracy, the measured signal can be
corrected using a variety of techniques, such as direct math, single linear
approximation, or piecewise linear approximation. Each has its advantages
and disadvantages.
It is beyond the scope of this book to describe how to correct the readings
from sensors (for example, for correcting the RTD measurement). Suffice it
to say that developers designing IoT applications must take linearization and
calibration into account for the specific needs of their application—particularly
if the desired accuracy is important to its function.
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CHAPTER 6
80
81
85
IoT
ANALYTICS
IoT DATA AND ANALYTICS
TYPES OF ANALYTICS
FUTURE OF ANALYTICS
Chapter 6 IoT Analytics
IoT ANALYTICS
In the context of IoT applications, looking at received data and finding meaningful
patterns in that data is the basis of analytics. These patterns could describe the state
of the data, predict an outcome, find correlations between variables, project trends
in the data, and a lot more. Analytics are used in many aspects of business, from
marketing to risk management. In this chapter, we will discuss analytics as it relates
to IoT data.
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of the large number of units expected in the future, as well as transmissions
over years of service. This is part of the Big Data revolution that is much
hyped in the media. For example, the Aeris IoT network manages traffic with
more than one billion IoT events each day. The more IoT data points being
collected, the more need for sophisticated analytics to understand and gain
Chapter 6 IoT Analytics
Over time, IoT applications can generate vast amounts of data, both because
value from the patterns.
New ways to process and store computing data has made it possible to apply
analytics to business problems faster and at a greater scale than ever before.
Successful organizations take advantage of these tools and analyze the data
from IoT deployments so as to gain insights into everything from how to
streamline manufacturing processes to the satisfaction levels of its customers.
IoT DATA AND ANALYTICS
IoT devices usually report data in constant streams or
periodic messages, and these must be processed both in
real time for immediate decisions and alerts, as well as in
batches for deeper insights into learning patterns
and behaviors.
Learning models built from batch and streaming analytics are used to define
thresholds for real-time analytics. This is a dramatic shift from traditional
analytics methods that mainly were single-file-oriented data processing
programs. Today, real-time analytics are possible, and business-necessary,
on streaming IoT data.
Another key to IoT analytics processing has been the development of
new tools, open-source distributed storage, and distributed processing
frameworks. The Hadoop ecosystem (Hadoop Distributed File System),
as well as products such as Riak, Cassandra, MongoDB, Apache HBase,
CouchDB, Redis, etc., are being leveraged for Big Data storage and analysis.
This allows processing of very large and streaming data sets over computer
clusters. Hadoop and components can be deployed as a cloud-computing
service by smaller organizations.
With these scalable technologies capable of analyzing and storing streams of
Big Data, businesses can use various types of analytics to better understand
their collected data from IoT applications and devices.
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Analytics can be grouped into four broad categories:
descriptive analytics, diagnostic analytics, predictive
analytics, and prescriptive analytics.
Chapter 6 IoT Analytics
TYPES OF ANALYTICS
Descriptive Analytics
Descriptive analytics, also called descriptive statistics, provide a numerical
or graphical representation of the data that is available right now. It
provides a way to express, in absolute, unambiguous terms, a quantitative
measurement of the current state. This analysis can draw conclusions from
the past as well.
In a broad sense, descriptive analysis answers these questions:
• What happened?
• How often did it happen?
• How reliable was it?
• How accurate was it?
Knowing the current status of IoT data provides a baseline against which
to compare future states. It is possible to compare basic data from the past
to the present, tracking progress along the way. Descriptive analytical tools
can be as simple as tracking website traffic or more complicated, such as
cluster analysis used in market research.
Diagnostic Analytics
This type of analytics often is merged with descriptive analytics, and,
together, they can give data greater interactivity. Where descriptive
analytics asks “what happened?”, diagnostic analytics asks “why did this
happen?” The diagnostic tools can be applied to the data to look for the root
causes behind the results observed in the original data.
Usage-based insurance (UBI) implemented with vehicle telematics is one
example of descriptive and diagnostic analytics in action, in tandem. This
type of vehicle insurance establishes the driver’s insurance premium rates
on behavior that is tracked via a GPS-enabled cellular transmitter in the
vehicle. The distance a person drives, when a vehicle is driven, and where
the vehicle is tracked, as well as other attributes, are used to calculate the
insurance cost.
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Chapter 6 IoT Analytics
By finding patterns
and trends in the
data, it may be
possible to predict
future results.
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Prediction is one of the main reasons that businesses use analytics in the first
place: predictive analytics provide a means of projecting what will happen
next, based on what has happened in the past. By finding patterns and
trends in the data, it may be possible to predict future results.
Chapter 6 IoT Analytics
Predictive Analytics
Of course, assuming that future behavior will be the same as past behavior
isn’t always the correct call. Although, unlike the stock market or consumer
purchasing habits, machine behavior generally is highly predictable. In a
factory, vibration and temperature data broadcast from an IoT-connected
device can indicate, with a high degree of accuracy, when a machine needs
preventive maintenance.
Businesses can use predictive analysis in their
own IoT deployments as part of supply chain
management and manufacturing processes to
increase efficiencies.
For example, brake balancing in trucking fleets is a complex and expensive
maintenance issue. Without regular maintenance, the risk of a truck
jackknifing on the highway is high. It takes a highly trained technician
significant time to check the combination of brake temperature and pressure
to know when to make an adjustment to the vehicle’s brakes.
In Michael Lawrence-Smith’s study, “Cooperating Artificial Neural and
Knowledge-Based Systems in a Truck Fleet Brake-Balance Application,”
he describes how machine learning techniques used predictive analysis to
improve brake maintenance. These computer-aided systems have a 90%
success rate at predicting when to replace brakes, resulting in an annual
savings of at least $100,000 for larger trucking companies.
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Prescriptive analytics is the logical next step from predictive analytics. It asks
what a business should do based on the data that has been collected and
analyzed. Prescriptive analytics uses models to both recommend actions and
forecast outcomes in order to reduce risk.
Chapter 6 IoT Analytics
Prescriptive Analytics
Just as descriptive and diagnostic analytics work well together, predictive
and prescriptive analytics also work hand-in-hand. As past data is used to
calculate future results, prescriptive analytics can be used to make better
choices and take advantage of opportunities.
Google’s self-driving cars, for example, use prescriptive analytics to make
countless driving decisions. The cars communicate with the cloud using
IoT systems to obtain data on traffic and weather, which becomes part of
its driving computations. The vehicle’s on-board computers apply machine
learning to the problem of what a car should do based upon predictions of
future outcomes. For example, the car’s computer may predict traffic based
on the time of day and then determine what route to take and what speed to
travel safely.
But analytics only will predict, for example, that a machine part will break if
it has seen signatures of such failures before. Therefore, gathering data from
large deployments is very important.
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Organizations continue to expect more from their
analytics tools and investments. The use of Artificial
Intelligence (AI) techniques and algorithmic approaches,
such as Machine Learning (ML) and Deep Learning (DL),
provide greater insights into the data than ever before
possible with traditional batch-oriented data crunching.
Indeed, as the number of IoT devices grow rapidly over
the next few years, the ability to provide information
processing at scale becomes critical.
Chapter 6 IoT Analytics
FUTURE OF ANALYTICS
If the analysis cannot be performed in the required intervals for the resulting
actions to be valid, the quality of business decision outcomes drops.
Companies must look at new architectures and solutions, including microservices and APIs to external processing systems, for example, to interact
with their existing mechanisms for analysis, and adapt accordingly.
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increasingly important to act on data in motion. These analytics systems
must ingest the streaming IoT data seamlessly, analyze it in the context of
past data and history stored in Big Data systems, and act, often automatically
without human intervention, when and where appropriate, at the scale
needed. Often, new hardware architectures will reduce the processing
Chapter 6 IoT Analytics
The need for speed—including real-time or near real-time analytics—is
constraints encountered with older computing systems. For example, using
high performance video graphics processing units (GPU), with their hundreds
to thousands of computing cores, can provide processing gains that easily
exceed traditional server capabilities.
Finally, the ability to deploy analytics platforms in the cloud plays a major role
in this space. IoT data is being generated globally, and local cloud services
allow the transport of that data to reach the data processing systems without
overwhelming long-range networks or crossing national boundaries that may
be regulated.
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CHAPTER 7
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SCHEDULING,
ENCODING, AND
PROCESSING
DATA TRANSMISSION SCHEDULES
UDP OR TCP
CONTENT ENCODING / TRANSPORT PROTOCOLS
GATEWAYS
APPLICATION SERVERS
CLOUD COMPUTING
FOG COMPUTING
Chapter 7 Scheduling, Encoding, and Processing
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bpm
SCHEDULING,
ENCODING,
AND PROCESSING
Data and sensor readings generally are transmitted to Internet of Things
and Machine-to-Machine application programs for processing, storage, and
business actions.
This may be a relatively short-range transmission from the IoT devices. Sensor readings can be delivered to a
smartphone application using a short-range wireless technology, such as Bluetooth, ZigBee, or Wi-Fi, for an
action by the owner of the smartphone. For example, a heart rate monitor may send heartbeats-per-minute to
a smartphone application during exercise, and this can be monitored to modify the specific physical activity.
The data can be logged by the application, possibly into a cloud application, to ensure that the desired fitness
goals are being met.
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to cloud systems, application servers, and programs where it is processed for
actions or stored for analytics. The data (or patterns in the data) may lead to
business actions, including automatic functions performed programmatically,
if appropriate for that specific application. For example, an airbag deployment
notification from a vehicle can be sent to an automotive Telematics Service
Provider (TSP) that contacts the driver and connects them to public safety
personnel for dispatch of emergency services.
This chapter describes the systems and methods used to encode, transmit,
store, and process the data in a server application.
Chapter 7 Scheduling, Encoding, and Processing
For other IoT applications, the data may be sent over a longer-range transport
DATA TRANSMISSION SCHEDULES
Devices may transmit their data in real time, a scheduled
rate, or when the device firmware requests a report of an
event. Application servers also can initiate a transmission
from a device by polling it with an appropriate control
message sent to the device.
Devices that send their data continuously in real time or near real time are
“streaming” applications. The processing of this streamed data requires
systems capable of handling the high throughput from a large number of
devices, particularly if the content is to be analyzed in real time for specific
actions at a remote site.
The cost of transmitting real-time streaming data on “metered”
communications networks that charge for “quantity of bytes sent”
may be prohibitive for many applications.
For a large deployment, the requirements for processing the data may be large
enough to clearly require a commercial cloud service provider that can handle
the necessary throughput with bandwidth, performance, and high-availability
systems to deal with the data stream. The application may need to store the
data for long periods of time for long-term analytics functions to be useful.
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In some applications, devices transmit on a regular schedule—sometimes
sleeping to conserve power until they are woken up by scheduled timers or
to report an unscheduled event.
Devices with accurate time (such as those equipped with GPS receivers)
must be careful when using regularly scheduled transmissions. In large
deployments, if all devices were to wake and transmit at exactly the same
time, the simultaneous connection attempts could overwhelm the connectivity
paths and the server systems that receive and process the data. If possible,
randomizing the time of the transmissions can have a major positive impact on
the capacity requirements of the connectivity and the server systems.
Chapter 7 Scheduling, Encoding, and Processing
Scheduled Transmissions
There are simple ways to achieve this randomization. For example, a device
identification number—such as the last four digits of the Mobile Directory
Number (MDN) or the Mobile Station ISDN (MSISDN) in a cellular device
(modulo 3600 to bring it into the correct range)—can be used to select the
“number of seconds past the hour” when a regular transmission is sent.
Transmit On-Demand
In most IoT applications, it is typical for the device to transmit “on demand”
when an event requires it to do so. For example, a business or residential
security system can transmit a signal when a break-in occurs; a car may
transmit an accident notification when an airbag deploys; or when the driver
pushes a concierge button for assistance. These generally are sporadic
enough and temporally spaced that they do not create traffic (and server
system) spikes.
Often, devices that transmit to report sporadic
events also are set to transmit a periodic, regular
“heartbeat” to report their condition and health.
These heartbeat transmissions also should
be randomized.
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We often are asked whether a device should use User
Datagram Protocol (UDP) packets or Transmission Control
Protocol (TCP) streaming sessions for the data. The
answer, not surprisingly, is: “It depends!”
The Internet Engineering Task Force (IETF) has detailed definitions for these
two protocols, but let’s briefly describe them to understand why one may be
better than the other for certain IoT data transmissions.
Chapter 7 Scheduling, Encoding, and Processing
UDP OR TCP
It is important to note that both UDP and TCP are used over an underlying
Internet Protocol (IP) data connection.
User Datagram Protocol (UDP)
The UDP format was first defined in an IETF Request for Comment (RFC)
specification―RFC 768. This protocol provides a procedure for application
programs to send messages to other programs with a minimum of protocol
overhead. This protocol is transaction-oriented, but delivery and duplicate
protection are not guaranteed.
If an application requires ordered, reliable delivery of streams of data, UDP
is not the preferred protocol. However, the UDP format has lower overhead
than TCP—i.e., fewer bytes are sent in the headers of the packets in UDP
than TCP.
Transmission Control Protocol (TCP)
The TCP format was first defined in an IETF RFC specification―RFC 761.
TCP is a connection-oriented, end-to-end reliable protocol that is intended for
use as a highly reliable host-to-host protocol in IP networks and especially in
interconnected systems of such networks.
TCP requires that a connection be opened and managed for the duration of
the data transmission on an IP network. Within the protocol, transmitted and
received packets are acknowledged by the device and the servers.
This format has more overhead than UDP—i.e., more bytes are sent in the
headers of the packets in TCP than UDP.
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In general, the choice of UDP vs. TCP must take into account:
• The desired balance between the reliability of TCP and the lower cost
of UDP, since UDP uses fewer bytes of overhead to transmit the same
amount of application data.
• The increased complexity of TCP, where the module must open a data
stream to a remote server where programs await connections.
• Careful design of TCP server programs to allow easy scaling as the
number of deployed devices increases for an IoT application.
• A requirement for the acknowledgments provided by TCP sessions.
• UDP is suited for real-time applications that can tolerate packet loss.
TCP is suited for applications that can tolerate delay but not packet loss.
Chapter 7 Scheduling, Encoding, and Processing
Which to Use?
However, it also is important to note that using these two protocols is not
mutually exclusive for a given IoT application.
For some data, a simple transmission of a UDP packet to a remote server may
be quite sufficient—including possibly using independent acknowledgments
also via UDP. If an acknowledgment is expected, but not received, either side
can retry intelligently (i.e., with limits on the number of retries, variable delays
between retries, etc.).
For other data, even in the same IoT application perhaps, a device may open
a TCP connection to a server and communicate with the higher reliability of
a TCP streaming session to a program that accepts these connections and
transmissions, while providing direct real-time acknowledgements.
Often, the amount of data for a particular data set may require TCP. For
example, if a device needs to transmit a large amount of data for a particular
set of gathered information (i.e., more than a kilobyte), it generally is better
to use TCP since the consequences of an error during transmission via UDP
could mean that the entire data set might require a complete retransmission.
It should be noted that in modern IP communications—including cellular IP
data—this unreliability concern is low, and UDP should suffice for a significant
set of the data transmitted for a particular IoT application.
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Chapter 7 Scheduling, Encoding, and Processing
CONTENT ENCODING /
TRANSPORT PROTOCOLS
When a device transmits its data to the servers and receives
commands and instructions from the servers, an encoding
format is required for the information sent in both directions.
In every application, the devices and servers must formally
agree on the format and information that is transmitted.
Proprietary Format
Devices and servers for a particular IoT application could choose to use a
proprietary format for the data encoding. This allows the devices and servers
The choice
to encode, decode, and interpret the content in ways unique to the needs
depends on the
of that application. This often can minimize the amount of data sent in any
connection session.
needs of the
Proprietary formats are more difficult to implement initially—since they must
application, the
be quite complete for that application to be deployed—as well as difficult
to maintain and update later when changes are needed. Most proprietary
bandwidth of
formats are not easily extensible.
the network,
Common Industry Formats for IoT
the compute
In addition to proprietary formats and early standardized formats, such as
power, as well
eXtended Markup Language (XML), there are some industry formats and
as other factors.
protocols in use for IoT data communications for messaging needs:
• JavaScript Object Notation (JSON)
• Constrained Application Protocol (CoAP)
• Message Queuing Telemetry Transport (MQTT)
• Extensible Messaging and Presence Protocol (XMPP)
These protocols fall into two basic categories: human-readable (JSON, XMPP)
and non-human-readable (CoAP, MQTT).
The human-readable ones generally are much more verbose, but far easier to
debug during application development and subsequent operations. The other,
non-human-readable ones are lighter weight and efficient and can minimize
the amount of data sent over the communications path.
Each format (and protocol) has pros and cons when used for IoT. The
choice depends on the needs of the application, the bandwidth of the
communications network, the compute power in the sensor or remote device,
and other factors.
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JSON is an open-standard format that sends key-value pairs of information.
The “key” generally is the attribute or description of the content sent in the
“value”. The protocol is described in RFC 7159 from the IETF.1
The JSON format is human-readable and language independent, and public
code for parsing and generating JSON text data is readily available in a variety
of programming languages. The format is effectively self-describing since the
definition and value are right next to each other.
For example, the following simplified text illustrates the encoding of a
temperature reading of 25 degrees Centigrade from a sensor with a
hypothetical sensorID of 123456789:
Chapter 7 Scheduling, Encoding, and Processing
JSON
{
“sensorID” : “123456789” ,
“temperature” : “25” ,
“units” : “Centigrade”
}
As you can see, the JSON content is verbose and very human-readable.
The key-value pairs immediately identify the attribute and its value—picking
appropriate terminology for the keys that are meaningful is, of course,
important for this capability to be useful.
JSON format messages also can be extended readily. For example, the
physical location and manufacturer might be added, along with a time stamp
noting the time that the temperature was measured.
Of course, the presence of this additional information depends on whether it
should be transmitted. In the above example, the value of sensorID could be
used to look up the physical location in a server database (assuming it was
stored there at installation of the sensor). Moreover, sending a time stamp
from the device for each transmission can be very useful since it provides
the time when the data was collected (assuming the device knows that time
information, of course).
1
See www.ietf.org/rfc/rfc7159.txt for more information.
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As the name implies, CoAP is a format and protocol intended for use in
bandwidth-limited networks or where minimizing the size of each message
transmission is important. The core of the protocol is described in RFC
7252 from the IETF, although extensions to add unique requirements for IoT
applications currently are in development.
CoAP is a simple protocol that is well-suited for transmissions from small
electronic components, such as sensors, and also can be used to control the
devices from remote servers. CoAP includes the concept of “multi-cast” (or
“one to many”) group communication, where many devices can receive the
control information at the same time.
Chapter 7 Scheduling, Encoding, and Processing
CoAP
The protocol provides two types of messages: requests and responses using
a “type-length-value” (TLV) coding that is different from the JSON format.
CoAP messages are sent using a UDP transport to adhere to the concept of
low overhead for the messages.
MQTT
MQTT is another light-weight messaging protocol that is designed for data
transmissions from devices operating in bandwidth-limited networks. The
devices transmit the data to message brokers that then are responsible for
sending the content of the messages to clients who are interested in that
data and who subscribe to the data feed.
This mechanism is the essence of a “publish-subscribe” approach, where
data from a device is published to a broker, and subscribers to that broker
can access the data.
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OASIS1 standards body and now is supported by that entity.
MQTT originally was designed for the IoT markets for devices transmitting
using TCP / IP. To allow simpler electronic devices (such as sensors) to use
this protocol, a version called MQTT for Sensor Networks (MQTT-SN) has
been released to extend the protocol beyond TCP / IP.
XMPP
XMPP is an open-standard communications protocol for messages based on
XML. It is intended for near real-time exchange of messages between two
(or more) elements on any network. Like XML, it is extensible and also can be
used for publish-subscribe message systems.
Chapter 7 Scheduling, Encoding, and Processing
Originally developed by IBM, the MQTT protocol was transferred to the
There are multiple RFCs from the IETF that specify the XMPP standards: the
core ones are RFC 3922, 3923, 6120, 6121, and 7622, although the XMPP
Standards Foundation2 is actively extending XMPP further.
The XMPP protocol evolved from an earlier open-standard protocol called
Jabber and was used for Instant Messaging (IM) services, as well as Voice
over IP (VoIP) control messages. In this last application, XMPP competes with
the Session Initiation Protocol (SIP).
When XMPP extensions are used for publish-subscribe services, they are
useful for IoT data applications. However, like JSON, they are human-readable
and verbose—perhaps even more verbose than JSON due to the XML roots.
This may make it difficult for a small sensor to encode XMPP directly, but
a communications device could make the necessary conversion from raw
sensor data.
In XMPP, binary files and content can be encoded (using base64 conversion
of the binary data to text) and sent using XMPP, but this is likely to use more
overhead than is desirable for IoT applications.
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Chapter 7 Scheduling, Encoding, and Processing
The gateway is a
good location in the
communications
path to implement
the data encoding,
as well as security
best practices.
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In most low-cost sensors—even the newer ones that
“speak IP”—it is difficult to provide the data encoding and
decoding functions within the sensor. Often, these sensing
devices use short-range communication paths—either
wireless or wired—to a device with more computing
capacity that actually encodes the data and transmits to a
remote server.
This device may be a physical unit serving a single sensor and associated
application. More often, it is a gateway—a product with multiple short-range
wireless and wired connections to local sensors and a long-range wireless or
wired connection to the remote IoT servers.
For example, gateways used in home automation applications typically
For large-scale
deployments,
the application
servers literally
must be running
Chapter 7 Scheduling, Encoding, and Processing
GATEWAYS
continuously
with high
availability and
communicate with sensors using Bluetooth, ZigBee, and low-power Wi-Fi,
processing
and to the remote servers with cellular or wired Ethernet IP connections.
redundancy.
The gateway is a good location in the communications path to implement the
data encoding, as well as security best practices, with software agents that
take the raw information from the sensors and encode the data in the formats
described above. The gateway also could implement encryption algorithms to
protect the data.
APPLICATION SERVERS
Remote data is transmitted to application programs
running on the servers that may be dedicated to the task
of processing that data—whether it is streaming data or
message oriented.
Typically, these servers are deployed in data centers on the customer premises
or in standalone data centers. The programs on the servers receive the data
and process them for the specific business action of the IoT application. This
may include storing the data in traditional databases, filtering for erroneous
information, alerting when the information is outside pre-determined bounds,
displaying the data or reports, etc. The needs vary greatly.
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server downtime for any significant duration. Thus, processes and network
infrastructure to automatically balance the loads on redundant servers,
including at multiple sites, are critical.
For large-scale deployments, the application servers literally must be running
continuously with high availability and processing redundancy (including
geographic redundancy), particularly for mission-critical applications. With
the projected growth of the IoT market, this will place an immense burden
on servers and data centers. This need creates a significant capital and
operations cost of systems, physical site maintenance, power distribution,
cooling, and more.
Chapter 7 Scheduling, Encoding, and Processing
Often, remote devices, even those that are transmitting lightly, cannot tolerate
The choice of which server platforms, operating systems, programming
languages, etc., is dependent entirely on the entities deploying the IoT
application. Traditional IT departments generally have all the relevant
expertise to make these decisions for the companies.
In most cases, however, where massive growth is expected to occur, IoT
deployments should consider taking advantage of newer IT deployment
architectures, like “cloud computing”, and data traffic reduction methods, such
as “fog computing”.
CLOUD COMPUTING
In recent years, the phrase “cloud computing” or simply
“the cloud” has been coined to describe the systems that
allow processing and storage of data in extremely large
data centers for a fee. Cloud vendors provide the ability and
flexibility to start and stop computing and storage of data,
while providing the networking resources based on the
specific needs of the customers and their applications using
these cloud services.
This has transferred the need for entities and corporations to maintain their
own physical hardware systems, data centers, and data networks, etc., to
the cloud vendors. This eliminates the “traditional” operational burdens of
physical site maintenance, electrical power management, environmental
conditioning, and system redundancy.
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customers then can be adjusted fairly dynamically to conform to the needs
of the applications being executed. The latest techniques and software for
managing large amounts of data can be applied to the data gathered from the
devices in the IoT applications.
These compute elements, storage, and data transport are, of course, provided
for a fee. The charges vary but often can be quite high for large-scale IoT
applications and large numbers of device deployments.
Chapter 7 Scheduling, Encoding, and Processing
The specific compute, storage, and transport requirements for the cloud
FOG COMPUTING
The volume of data gathered from a large number of
sensors and devices could overwhelm the IoT data
communications path (transmission and connectivity)
or the remote storage capacity and server systems that
process the data at customer sites.
While cloud solutions do alleviate this problem, the cost could be very
expensive—particularly for streaming applications. Often, a general
approach to remote data gathering is a “transmit everything and process
in the cloud” implementation.
However, if actions based on the data must be processed in real time or near
real time, it may be better to process or filter the data remotely—at the device,
or elsewhere hierarchically in the data path—before it gets to the servers.
This processing and filtering has been termed “fog computing” by Cisco.
Fog computing is not without its issues and concerns. If the filtering removes
essential information that could be better processed at a central site (such as
the cloud) to determine patterns, its use could result in a weaker application.
Sometimes, the specific filters used at the remote device may need to
evolve and change. Thus, IoT devices must be programmable, or sufficiently
configurable, to change the specific data that is transmitted, thereby
increasing the complexity of the overall solution.
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Good security practices can be implemented farther away from the central
servers, where a device (or groups of devices) that have been compromised
could be isolated, perhaps limiting damage to the overall application deployment.
It also reduces the transport costs of sending a lot of data—much of
which may be meaningless, repetitive, or simply not needed—on metered
transports where the transport of large sets of data can be expensive.
Chapter 7 Scheduling, Encoding, and Processing
One significant advantage of fog computing is the concern about IoT security.
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Chapter 8 Implementing an IoT Solution
CHAPTER 8
104
104
106
107
107
IMPLEMENTING
AN IoT
SOLUTION
SUPPLY CHAIN MANAGEMENT
CELLULAR OPERATOR SELECTION
CLOUD SYSTEM SELECTION
PLATFORM SELECTION
NETWORK OPERATOR SERVICE
LEVEL AGREEMENT
DEVICE CERTIFICATION
NORMAL OPERATION CONSIDERATIONS
APPLICATION COMMUNICATIONS
CALL FLOW
CUSTOMER SUPPORT PROCESS
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Chapter 8 Implementing an IoT Solution
IMPLEMENTING
AN IoT SOLUTION
An Internet of Things application deployment has to either increase business revenue
or reduce business costs (or both), otherwise there’s no reason for a company to
pursue it. Either of these objectives can provide a return on investment. It’s up to the
product manager to determine the specific goals and measurements of this ROI.
Related drivers for IoT projects can be new regulations and industry requirements,
greater efficiencies, more consistent control over processes, visibility into patterns or
opportunities, or gaining competitive features that can meet customer requirements.
As you build your IoT business model, these factors will weigh differently depending
on product needs and the industry.
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Supply chain management refers to planning for the flow
of materials and services into and out of the business,
and managing all the goods required to make your IoT
deployment happen. If your company is building its own
IoT devices from scratch, you’ll have many materials, parts,
and suppliers to account for. If you’re assembling devices
from ready-made components, you can reduce the
number of suppliers. However, even if you buy a complete,
off-the-shelf device, it still requires sourcing, testing, and
managing supply and demand.
Chapter 8 Implementing an IoT Solution
SUPPLY CHAIN MANAGEMENT
CELLULAR OPERATOR SELECTION
The service provider must be able to deliver several
essential requirements for the project, including reliable
network connectivity, robust service agreements, effective
application integration, cost management tools, and flexible
rate plans. If they can’t deliver on these prerequisites, they
are not going to be the right partner.
To help you select the ultimate service provider with the capacity to manage
a successful deployment, you may want to ask these questions of any cellular
carrier during the selection process:
• What are the costs for the entire device lifecycle, not just per kilobyte
rates? Make sure you won’t be hit with hidden costs from your cellular
operator that drive up your IoT service bill.
• Can the service provider expand cellular coverage beyond its own cell
towers? Traditional operators only optimize their cellular coverage based
on their cost of delivery, and they always prefer to use their own towers,
even if the coverage they provide is weak or intermittent. A carrier-agnostic
provider, like Aeris, can expand coverage where needed, and will offer the
strongest signal, regardless of operator, with no interruption in service.
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• Do they offer a dedicated IoT network? A network dedicated solely to
IoT traffic won’t experience the delays caused by crowds of consumer
handsets. The lower latency of an IoT-dedicated network means you’ll be
able to rely on mission-critical transmissions to get through the first time.
• Do they have APIs for easy integration with your existing systems? Can
the cellular operator provide a full suite of free APIs that let you extend the
capabilities of your customer-facing applications and back-office solutions,
leveraging business applications, such as those from SAP and Oracle?
These applications are integral elements of enterprise resource planningbased supply chains and are linked to back-office systems with APIs.
Chapter 8 Implementing an IoT Solution
• Do they offer remote troubleshooting, as well as hands-on support?
Cellular carriers with remote, real-time troubleshooting capabilities can
save you significant costs. Also, an operator with a network operations
center support team that deals only with IoT-related issues is going to be
more knowledgeable about your devices and connectivity issues.
• Do they offer pay-per-use, as well as per-device billing plans? Can
the cellular operator offer rate plans that are flexible enough to meet
your needs? When managing IoT services, it often makes more sense
to go with a pay-per-use plan than with a per-device or fixed-data plan.
Pay-per-use is most cost effective for lower-usage device profiles. If your
devices have higher-usage levels—10 MB or more—a per-device data
plan is your best option.
• Does their system provide cost management tools that automatically
notify the company, or take automatic limiting actions, when a device, or
a group of devices, are exceeding their cost models? Devices sometimes
malfunction and “run away”, transmitting more often than they should
or retry under conditions where it would be better to avoid network
attempts. In this case, it is important to automatically notify company
personnel to take action, or even set limits where device operation is
blocked to avoid uncontrolled costs.
These are some of the top-level concerns your company should consider
when choosing a cellular operator. You’ll want to partner with a service
provider that suits your business needs and can support your IoT project
over the long term.
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Often, the large number of devices that typically are
deployed for an IoT application necessitates the use of a
commercial cloud service that provides the performance
and high-availability capability required by the application.
This requires customers to carefully ascertain whether the cloud provider has
the right tools, cost models, and support for their needs. The right questions
Chapter 8 Implementing an IoT Solution
CLOUD SYSTEM SELECTION
are not always clear since some aspect of their service or cost model may be
appropriate until a certain size threshold is reached. This “scaling challenge”
often is one of the most difficult areas of assessing what is possible.
Consider the following:
• Does the cloud provider have a cost model that matches what the IoT
application can bear? Can the cloud provider assist you in simulating
the costs for your application transport, storage, and analysis needs?
If the costs do not meet expectations, the return on investment for the
application could fall short and lead to an unsuccessful deployment.
• Does the cloud provider offer data centers in the countries where the
devices are deployed? In some countries, there are regulations that require
that data must not cross past national boundaries and the presence of a
local data center may be critical to operating within the regulations of that
country. Indeed, an absence of a cloud data center in a vital market may
preclude the selection of that provider.
• Does the cloud provider have the tools to support high-availability
deployments? Do your software engineers and operations personnel
have the expertise to develop and maintain cloud solutions for your IoT
application? Sometimes, the selection of a cloud provider is guided by the
available personnel within your company who have experience with that
provider. It may be necessary, however, to hire additional resources or use
an IoT platform vendor who can guide you to the best possible solution.
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Many companies attempt to provide a platform for IoT
solutions. This appears to be an area where it is possible
to find hundreds of companies purporting to provide “IoT
platforms”. In this noisy environment, it is difficult to assess
what the capabilities and features of the platform are, let
alone how well they would fit for the requirements of your
specific IoT deployment.
The wrong
Given the large variety of possible IoT applications in many different types
of markets and businesses, and the large number of available platforms, it is
could
tough to determine the best one for your needs. Yet, it is important to make
significantly
the best selection as early as possible, since the wrong selection at the early
phase of any IoT application deployment could significantly impact and delay
selection
at the early
phase of any
IoT application
Chapter 8 Implementing an IoT Solution
PLATFORM SELECTION
deployment
impact and
the project.
delay the
For more information on platforms, please refer to Chapter 2, The Future
project.
of Platforms.
NETWORK OPERATOR SERVICE
LEVEL AGREEMENT
The Service Level Agreement (SLA) you negotiate with
the operator defines the scope of your contract with
the operator. This is where your business defines its
relationship with its network provider, so it’s important to
specify what will keep your IoT deployment running.
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• What are the expectations for connectivity? How reliable is the operator’s
network historically?
• What are the geographic restrictions of the operator’s network, if any?
Some carriers may not guarantee service at all towers or all sections of
particular metro areas.
• How long will it take the operator’s customer support to acknowledge and
then take care of a problem?
When entering into an SLA, make sure the agreement is realistic, actionable,
Chapter 8 Implementing an IoT Solution
Things to consider in your SLA include:
measurable, calculated, well-defined, mutually exclusive, and completely
exhaustive in covering all aspects of concerned networking services.
DEVICE CERTIFICATION
Devices must be approved or certified to run on the
operator’s network. For this certification, the focus generally
is on testing the cellular behavior of the device.
One example of this might be the behavior of the retry algorithm used by
the device if it fails to connect to the application server in your data center. A
continuous retry by thousands of devices at the same time could overload the
operator’s network. Implementing a random back-off algorithm, and testing it
prior to certification dictates better device behavior.
Operator certification also provides an opportunity to use the application
host server software to perform additional tests that stress the interaction
between the device and the server. Unusual scenarios, such as delayed
responses from the server (that might be observed during congestion or
server scaling), can be used to see if a device handles them gracefully.
In certain markets, such as the healthcare industry, additional regulations
for device performance in medical environments and data privacy rules may
apply. Additional certification may be required by standards organizations,
regulatory agencies (such as the Federal Communications Commission in
the U.S.), or even your customers, particularly if there is end-user integration.
Each company deploying such IoT applications must determine how to best
meet all the regulations that apply to them.
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Here are a few of the concerns to be dealt with when
IoT devices are deployed:
• What is the definition of “normal”? What are the baseline transmission
patterns and server performance measurements?
• What happens if the IoT device can’t connect to the cloud platform?
In addition to having a random back-off retry algorithm, what will the
device do with its data? Remember that stale data would be inaccurate
when transmitted too late. The device needs to know when to generate
an alarm.
Chapter 8 Implementing an IoT Solution
NORMAL OPERATION
CONSIDERATIONS
• What should a mobile IoT device do if it loses its cell signal? The device
needs to know when it is appropriate to hold the data in its queue and
retry later.
The range of normal operations will vary for each deployment, so you’ll need
to set initial parameters for all aspects of the program. Then you can track
performance against this baseline moving forward.
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Chapter 8 Implementing an IoT Solution
The range of normal
operations will vary
for each deployment,
so you’ll need to set
initial parameters
for all aspects of the
program. Then you
can track performance
against this baseline
moving forward.
110
This is where the details of the IoT transmission are agreed
upon. Some design issues are:
• Should the device assume there will be a connection when needed or
should it be able to queue data for later delivery?
• Will the application “fire and forget” data or will it wait for an
acknowledgment? At the network layer, “fire and forget” means to use
UDP protocols for transmission.
Chapter 8 Implementing an IoT Solution
APPLICATION COMMUNICATIONS
CALL FLOW
• The general call flow is to establish a connection, transmit data, wait
for acknowledgment, then disconnect. This generally is a TCP protocol
implementation.
• Does the data need to be encrypted? That can increase the amount of
data being sent.
Your developers will need to outline each aspect of the IoT application’s call
flow, accounting for both standard, predictable behaviors and for outliers.
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Support staff will need to be trained on the product
features and how to operate them. But it also is very
important for the support team to receive training on
identifying connectivity issues. This is where a rich set
of diagnostic tools from the carrier, if available, become
a huge benefit.
Chapter 8 Implementing an IoT Solution
CUSTOMER SUPPORT PROCESS
If your engineer can log into a portal and see if the device in question has
registered on the carrier network and started a data session, then the
engineer can observe the recent behavior and immediately can focus the
investigation on the root problem. Using this observation, the engineer can
provide quick feedback to customers. If these tools are not available, then
support sessions are much slower.
Implementing an IoT network project requires a great deal of forethought.
But this advance planning pays off in a scalable product with a higher return
on investment.
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Chapter 9 IoT Scalability and Alternative Technologies
CHAPTER 9
117
119
120
IoT SCALABILITY
AND ALTERNATIVE
TECHNOLOGIES
WHAT IS SCALABILITY?
END-OF-LIFE MANAGEMENT
SCALABILITY AND CONNECTIVITY
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Chapter 9 IoT Scalability and Alternative Technologies
20
20 22
20 21
20 20
19
20
18
IoT SCALABILITY
AND ALTERNATIVE
TECHNOLOGIES
Over the years, the predictions for growth in the Internet of Things and
machine-to-machine markets have been staggering.
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50 B
30 B
connected devices
by 20202
connected devices
by 20203
75 B
31 B
40.9 B
connected devices
by 20204
connected devices
by 20205
connected devices
by 20206
We appear
20.8 B
200 B
connected devices
by 20207
connected devices
by 20208
Various predictions of device growth over time
Although the specific predictions and the numbers differ, what is remarkable
to finally
be moving
Chapter 9 IoT Scalability and Alternative Technologies
1B
connected devices
by 20151
beyond the
hype into
reality.
is that the numbers started extremely high, and only have grown over the
years. IoT markets are experiencing explosive growth around the world, and
the numbers still are performing at what Gartner calls the “peak of inflated
expectations” in its well-known “Hype Cycle” diagrams.
Even if the huge numbers forecasted are inaccurate by large percentages,
or even off by a factor of 10 or more, they still represent enormous growth.
Indeed, the estimated number of connected devices by 2020 exceeds the
projected population of the entire planet by many multiples.
1
2
3
4
5
6
7
8
“IBM: A World with 1 Trillion Connected Devices,” ReadWrite.com, June 7, 2010.
“CEO to Shareholders: 50 Billion Connections 2020,”Ericsson.com, April, 13, 2010.
“More Than 30 Billion Devices Will Wirelessly Connect to the Internet of Everything in 2020,” ABI
Research, May 9, 2013.
“Morgan Stanley: 75 Billion Devices Will Be Connected to the Internet of Things by 2020,” Business
Insider, October 2, 2013.
“The Internet of Things in 2020,” VisualCapitalist.com, August 23, 2014.
“The Internet of Things Will Drive Wireless Connected Devices to 40.9 Billion in 2020,” ABI Research, August 20, 2014.
“Gartner Says 6.4 Billion Connected ‘Things’ Will Be in Use in 2016, Up 30 Percent From 2015,”
Gartner, November 10, 2015.
“A Guide to the Internet of Things Infographic,” Intel.com, 2016.
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come close to the predictions for what these markets and industries can do
for all of us. Although wireline solutions likely will continue to be the dominant
technology for overall IoT connections, wireless technologies, including
cellular as well as LPWA deployments, will see tremendous growth over
the next several decades, driven largely by deployments that require mobility,
like automobiles and asset tracking.
All of this anticipated growth in the IoT markets will bring new challenges:
• Scaling for growth in the numbers of devices and applications.
• Providing effective security solutions for the content and solutions
(as discussed in the previous chapter).
• Storing the data and providing rapid analysis for action.
Chapter 9 IoT Scalability and Alternative Technologies
This explosive growth needs to be managed and planned if we are going to
• Deploying new wireless and wired connectivity technologies for the
increased traffic.
• Managing the connectivity and device “subscriptions” for large numbers
of devices.
This chapter will briefly review some alternative transport technologies that
likely are to be used for large-scale IoT deployments.
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In the context of IoT, scalability is the ability to grow the
application, the solution, and the platform to keep up with
the projected growth in the number of devices, the data
traffic from these devices, the applications servers that
process and store the received data, the real-time (or near
real-time) streaming data alert systems, the pattern and
predictive analytics, etc.
Successful organizations plan for the entire application lifecycle—from
development to operation to scaling to end-of-life.
Chapter 9 IoT Scalability and Alternative Technologies
WHAT IS SCALABILITY?
Essentially, this is the ability of the IoT ecosystem, both for any given
application and all such applications in general, to grow at the same
rate as the predictions—to make them a reality rather than hype. The
demand for IoT applications, devices, and services will continue to grow
exponentially, and companies with connected devices will need to scale
resources accordingly. For example, most IoT platforms let the customers
rapidly provision cellular devices for service at volume. Requests are not sent
in by humans; rather, automated systems make the provisioning requests,
and automated systems process these requests.
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Chapter 9 IoT Scalability and Alternative Technologies
The Growth Stall
Many companies run into difficulty after deploying their first few hundred
or thousands of IoT devices or, in rare cases, even after tens of thousands
of devices. This is not totally surprising because planning for scalability is
difficult and involves many factors, both technological and business related.
Sometimes, systems and processes simply reach design capacity, and it is
time-consuming and costly to change the architecture of the solution or add
capacity. Or the cost of operations becomes higher than expected or planned
for, which has a deep impact on smaller companies and startups that are
resource constrained. Even seemingly simple tasks, such as generating enduser bills and invoices, can place unexpected burdens on organizations when
scaling up for large numbers of devices.
The key issue for businesses caught in this growth stall is that planning for
growth was secondary to getting their products and services launched. This
Successful
is quite common, but it doesn’t have to happen. Successful organizations plan
organizations
for the entire application lifecycle―from development to operation to scaling
to end-of-life.
plan for
How Big Can IoT Resource Requirements Grow?
the entire
The predictions for deployed numbers of devices clearly are enormous
application
numbers. This has created a need to change some of the resources used for
IoT applications.
Even before IoT needs became evident, the number of computer systems
lifecycle―from
development
on the public internet had increased to the point where the internet address
to operation
numbering method, called IPv4, had been exhausted years ago. The
to scaling to
approximately four billion possible IPv4 addresses had been used up, as
discussed in earlier chapters.
end-of-life.
And, with the ever-increasing number of IP devices, including cellular
smartphones that need an IP address, it is no longer possible to consider
using stopgap measures, such as the Network Address Translation (NAT),
which was introduced to the internet for computing devices.
Thus, IPv6, which was introduced to increase the number of potential IP
addresses, is a real requirement for all future deployments. In theory, this
range is large enough that it is unlikely to get exhausted for millennia.
Computing resources also can be scalable, particularly if the device traffic
and application processing can be stored and processed. New database
technologies have been deployed that are far more expandable than the
traditional databases used in the past three or four decades for data processing.
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Cloud computing technologies have provided a scalable solution for storing
and processing the data gathered by IoT devices.
Since the numbers of devices are growing rapidly, systems to process the
data must grow equally fast. Adding capacity at private data centers is not
easy for most companies, since purchasing the physical space, providing
for additional power and cooling, increasing the network bandwidth and
throughput, installing the computing systems, etc., can take significant effort
and time.
Commercial cloud computing suppliers excel at this task. It’s their business to
provide the compute resources, network bandwidth, and general facilities for
exactly this growth purpose. Customers using cloud services can “spin up”
Chapter 9 IoT Scalability and Alternative Technologies
Cloud Computing
resources as needed, in step with their IoT application growth.
END-OF-LIFE MANAGEMENT
Many IoT devices have an end-of-life that must be
managed. The in-service period generally is much longer
than the typical period we expect for electronic devices
and consumer cellphones today, particularly for industrial
applications. But, once the end-of-life of a device is
reached, its removal from service must be managed to
avoid tying up resources.
For example, in cellular networks, devices have a number that identifies them
to the network for operational, accounting, and authentication purposes. In
CDMA, this is the Mobile Identification Number (MIN), International Mobile
Subscriber Identity (IMSI), or Mobile Directory Number (MDN). In GSM, this
may be the IMSI or the Mobile Station ISDN (MSISDN).
These numbers are assigned from an allocated range, or number pool, and
create a resource that must be managed. Ideally, these assigned numbers
then are re-used when devices are removed from service permanently.
Devices removed from business service still may have a presence on the
networks and impact performance if they still are electronically operational.
For example, cellular devices used in automotive applications can be removed
from service but still could attempt to “register” on the cellular network every
time the vehicle is turned on and off.
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permanently or temporarily—with code in the software of the device that can
be executed remotely. This would allow the application servers to properly
remove the device from service and, in the case of permanent removal, allow
the device resources (such as the numbers in the device) to be re-used for
other devices or applications.
SCALABILITY AND CONNECTIVITY
When building scalability into an IoT deployment, selecting
the appropriate network connectivity is crucial. The range
of available data transport technologies for IoT devices is
varied, and new options are becoming available. When
planning for scalability, it’s important to understand the
current choices and what’s on the horizon. However, this
decision is largely dependent on the type of application.
Chapter 9 IoT Scalability and Alternative Technologies
Thus, it is important for devices to have an ability to be turned off—
The first question to be resolved is whether the application is fixed
or mobile.
For simplicity, IoT applications can be classified into two categories: those
that are fixed (immobile) at one location and those that are in motion while
providing the function of the application. These two categories have differing
characteristics that affect the specific network selection and implementation
for the transport of data from devices.
Satellite
Wi-Fi
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• They generally do not move during the normal day-to-day operation of the
applications (although they could be re-installed at some other location
during their lifetime).
• During this operation, they generally are in a single service boundary.
• The devices often use wired networks in deployments where easy wired
solutions are available.
• Wireless networks also are used, however, since network wiring may not
be convenient or available.
• The solutions may be hybrid―using short-range wireless to reach a
gateway that uses a cellular or wired connection to connect to the servers.
Chapter 9 IoT Scalability and Alternative Technologies
In fixed location applications:
• The devices are installed at a single location.
Fixed location devices often are wired. This could be with a Local Area
Network (LAN), such as Ethernet using IP protocols. Older deployments
used dial-up telephone lines to reach a remote server directly or connect
to the internet, and cable modem connections are used where available
(also using IP protocols).
In physically mobile applications:
• The devices are installed on moving objects to provide the functionality
of the IoT application.
• They physically move from one place to another during the normal
operation of the applications.
• During this operation, they often traverse multiple service boundaries
(for example, cellular switch boundaries).
• Using some form of long-range wireless network is natural and required.
• In this category, using cellular or satellite networks is quite common.
• For some applications that must transmit while traversing service
boundaries, the technology must be a Wide Area Network (WAN)
with mobility management.
For short-range data transmissions, where using a wired solution may not
be practical, wireless technologies, such as Bluetooth, Wi-Fi, ZigBee, etc.,
are quite popular. These are common industry standards for which low-cost
implementations of the wireless radio and their protocols are available in
integrated circuits. The low cost of these short-range wireless technologies
enables using them directly within sensors.
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range—from a few meters to a few hundred meters. If the data needs to
go further, the short-range communication typically is sent to a gateway
that then connects to the servers using cellular, cable, or some other IP
network transport.
For medium-range wireless transports, typical implementations of IoT
solutions use cellular for communication to a nearby tower (generally within a
few miles) that then backhauls the data into the internet or a remote server.
When cellular is not available, such as on ocean-bound ships or remote
geographies with low human presence, long-range satellite data services
provide a global reach for devices to communicate to a distant server program
for that IoT application.
Chapter 9 IoT Scalability and Alternative Technologies
These short-range wireless technologies generally are quite limited in
Whichever of these two categories the implementation falls into, fixed or
mobile, will drive the selection of the network and communications path for
the application.
Wired Data Connections
Wired connections typically are used for fixed location IoT applications. For
reaching a server, the cost of the transport is “shared” with general internet
access. For many device deployments, this is a very low-cost solution, since
the ISP generally does not charge a metered rate—i.e., the often fairly low
amount of data sent by the devices at a fixed location does not trigger a high
transport cost.
With wired connections, the overall service requires an ISP service or another
LAN. The quality of the service and general network availability also depends
on the ISP. If it is not able to provide continuous service, some mission-critical
applications may experience problems with outages.
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Service coverage and availability for cellular and satellite generally are
excellent. Even in developing countries, cellular service usually is available
wherever people live and along major highways.
If cellular is not available, as in truly remote locations such as an ocean-bound
ships or in mountain regions, the coverage from satellite data services is
excellent, although some of the satellite services may have relatively higher
latencies (the time for a data packet to traverse end-to-end) than other
technologies. Coverage inside “urban canyons” with tall buildings usually is
difficult for satellite data services, but this is where cellular services can excel.
If required, a hybrid cellular / satellite device, with multiple radios, can provide
truly global data access.
Chapter 9 IoT Scalability and Alternative Technologies
Cellular and Satellite Connectivity
In both cellular and satellite, the cost of the radio can be high relative to the
rest of the device, and the radios generally consume substantially more electrical
energy to transmit—the communications range is relatively long. For example,
it would not be practical to equip low-cost sensors or simple IoT application
devices with cellular or satellite transports. These would be far better served
by short-range wireless technologies, such as Bluetooth or Wi-Fi.
There is one other concern with cellular technologies―the longevity of
deployment is driven by smartphone users. Thus, the technologies evolve
relatively rapidly and devices using cellular services must be replaced after
some period of time—longer than typical smartphone user turnover, but less
than older traditional wired technologies.
123
In many IoT applications, short-range wireless data technologies, such as
Bluetooth, Wi-Fi, or ZigBee, are in common use. For certain consumer IoT
applications (such as fitness application devices) that only transmit to a
nearby smartphone, using Bluetooth and low-power Wi-Fi are common
choices. These allow the users to gather data via applications on their
smartphone. The need to further transmit the data to central servers for
processing is not a paramount requirement but can be done with ease from
the smartphone, if necessary.
Short-range wireless is relatively low-energy, so battery-powered devices
are designed and deployed easily. In some low-use applications, the battery
may last for months or years before it needs to be replaced. This is a key
advantage over cellular and satellite applications that require far more
Chapter 9 IoT Scalability and Alternative Technologies
Short-Range Wireless
frequent energy replacements (for example, using rechargeable batteries that
might last a few days).
For many home and business applications, a gateway that provides one or
more short-range wireless technologies for deployed sensors and low-power,
low-cost, data transmitters are ideal for a number of IoT applications. The
gateway communicates to the application servers using cellular or wired
ISP connections.
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Chapter 9 IoT Scalability and Alternative Technologies
Coverage inside
urban canyons
with tall buildings
usually is difficult
for satellite data
services, but this
is where cellular
services can excel.
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Chapter 9 IoT Scalability and Alternative Technologies
Low-Power Wide Area Network (LPWAN)
Recently, the need for low-cost, low-power applications that offer longer
transmission ranges (between 2 to 20 miles) has seen the development of
a number of new technologies and services competing for the large-scale
deployment of consumer and industrial IoT devices and applications.
Some of these are the proprietary LPWAN technologies and include the
commercial data service networks by Sigfox and its licensees in some
countries in Europe and elsewhere (and some cities in the U.S. as of this
writing). Similar (but not identical) data transports for IoT include the
technologies developed and deployed by Ingenu and Nwave.
The open standards effort by the LoRa Alliance primarily is geared to private
network deployments rather than public data networks, although companies
also are engaged in deploying LoRa for public access. A number of cellular
operators have opted to deploy LPWAN technologies for public access by
A number
IoT applications.
of cellular
The proprietary LPWAN technologies currently use unlicensed wireless
operators
spectrum at various standard frequencies. Thus, they may experience
congestion and interference, and have technology and data rate limitations
that are solved in different ways. For some transports, the data rate and
message sizes are low enough that a simple approach to overcome the
congestion problems is possible, although the data mostly is one-way (from
have opted to
deploy LPWAN
technologies
the device) for low-power use. Others provide more complex data encoding
for public
to reach the tower networks, leading to more expensive radio solutions that
may work for some IoT solutions, but not necessarily for all.
access by IoT
Finally, the International Telecommunications Union (ITU) has developed,
applications.
through 3GPP, a set of cellular standards that extend 4G LTE technology
for use with low-power, power-efficient, and low-cost IoT radios. The first
technology is LTE-M (also called CAT-M), which competes well with the
proprietary LPWAN technologies being deployed today.
The 3GPP standards body also ratified the NB-IoT standard for use with
IoT applications. Devices and networks using NB-IoT are expected to be
deployed in the next few years and will provide alternatives to the services
offered by SigFox, Ingenu, Nwave, and LoRa.
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The first draft of 5G specifications were released in December 2017 but,
even before that, work already was underway. The official final 5G standards
are not due out till 2020. However, some point releases have been created,
particularly for fixed wireless and for the New Radio standards. When
finalized, the official standards for 5G services will include a requirement to
accommodate large-scale deployments of IoT applications and devices.
Overall, 5G requirements will provide:
The transport of 1000x more data volumes than smartphone
users are using today.
More than 10x to 100x the number of connected devices
5G
Chapter 9 IoT Scalability and Alternative Technologies
Fifth Generation (5G) Cellular
in use today.
Dramatically lower latency (for end-to-end data packets)
below a few milliseconds.
Projected 10x longer battery life for low-power
devices―up to 10 years.
The 5G specifications incorporate various LPWAN network capabilities for
IoT devices. Furthermore, carriers have begun testing in a few markets with
a deployment of fixed 5G gateway modems for internet access by home
and business owners who now have a wireless alternative to traditional
ISP services. These gateways are pre-standards units that may require
modification later, once official ITU and 3GPP standards are ratified.
In time, 5G and the IoT cellular LPWAN technologies will be the cellular
transports of choice for these low-power applications, along with a base of
unlicensed spectrum devices deployed by the proprietary technology providers.
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CHAPTER 10
130
13 3
13 3
13 5
137
141
142
SECURITY, PRIVACY,
AND THE INTERNET
OF THINGS
PRIVACY AND SECURITY
INTERNATIONAL DATA TRANSPORT
SECURITY OBJECTIVES
SECURITY ISSUES FOR IoT
RISK MANAGEMENT AND ASSESSING
THE IMPACT OF BREACHES
ENCRYPTION AS AN IoT TOOL
CHOICE OF ENCRYPTION
ALGORITHM
Chapter 10 Security, Privacy, and the Internet of Things
SECURITY, PRIVACY,
AND THE INTERNET
OF THINGS
In her keynote speech at the Consumer Electronics Show in January 2015, former
U.S. Federal Trade Commission Chairperson Edith Ramirez noted, “Any device that is
connected to the internet is at risk of being hijacked.”
Whether that device is a smartphone, an automobile infotainment system, an automated diabetes monitor, or
a GPS-guided farm tractor, specific protections for the security of that IoT device and application must be built
into the entire solution.
Traditionally, companies in the financial and consumer markets have been targets for misuse of information
stored on their systems—including personal credit information, identify theft, misuse of credit cards by
unauthorized persons, personal privacy violations, and loss of corporate intellectual property. The financial
losses sustained by these security breaches are in the billions of dollars. While attempts have been made to
criminalize such nefarious activities, they continue to occur with increasing frequency and are a serious problem
for governments, businesses, and individuals.
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being held responsible for protecting data and devices, as well as corporate
proprietary information. Recent media reports of security compromises in
the medical and automotive industries have shown that aspects of such IoT
deployments can be used for purposes other than the applications for which
they originally were designed.
This chapter covers the basic requirements of security implementations and
the different methods commonly used to increase the overall security of IoT
data and applications.
Chapter 10 Security, Privacy, and the Internet of Things
Businesses deploying IoT solutions for their customers and themselves are
PRIVACY AND SECURITY
In the context of IoT, privacy is concerned with ensuring
that data access is limited to appropriate and authorized
parties only.
While using tools, such as data encryption, is an important part of this data
securing process, it is just one part of the puzzle. There are other mechanisms
and methods to protect privacy (although not just for IoT applications):
*****
Physical access security (for example, secured entrances to
data centers).
Security training (for employees on how to secure computers and
devices, as well as to understand data safety).
Intrusion detection (for systems that process and store the data) and
applying ML / AI techniques to continuously learn the ever-changing
intrusion patterns.
Software updates (to implement the latest versions of software for
security fixes).
Regular security auditing (helps identify the gaps).
Individuals have an expectation of privacy with regard to their personal data,
and it is crucial for businesses to implement relevant security methods.
In particular, financial and medical industries have specific governmental
regulations that govern their products and services in their respective
markets. The new IoT implementations that companies in these industries
are deploying may have special testing and certification requirements—
particularly in regard to security and privacy issues.
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Regulations for Privacy
Many governments are implementing new regulations that require companies
to protect the privacy of personal data of individuals in their jurisdictions, with
material consequences for mishandling such data. These regulations may
require consent from individuals, limitation on downstream use and processing
of data, or even specific security standards for handling and storage.
The most notable of these initiatives is the General Data Protection
Regulation (GDPR), which was adopted by the European Union (EU) and
went into full effect on May 25, 2018. GDPR creates a uniform set of data
privacy laws to protect all persons in member states. While it is well beyond
the scope of this book to discuss GDPR thoroughly, it should be noted that
the penalties for non-compliance can be severe and have the potential to
Chapter 10 Security, Privacy, and the Internet of Things
GDPR and Data Privacy
create serious business impacts.
Data will be considered “personal data” if it reveals important information
about a natural, identifiable, living person. In many cases, this is obvious.
But in the IoT area, other data, such as location data, also may be protected.
Many businesses are choosing to design their products, processes, and
systems to meet a single set of privacy requirements and are selecting
GDPR as their global standard since it is a stricter set of rules than those
in effect in many countries, including the United States.
Companies providing IoT services in the EU must be mindful of how local
laws, such as GDPR, apply to them. Services should be designed from the
ground up to comply with its requirements, which will necessitate close
collaboration between product, engineering, marketing, and legal teams.
Large Territorial Scope
GDPR applies to all companies in the EU that collect or process any personal
data of individuals in the EU, regardless of where the data is stored or
processed. It also may apply to companies located outside the EU if such
companies offer goods and services to persons in the EU (whether or not
payment is required) or use personal data of individuals in the EU to monitor
their activity or to make automated decisions about them.
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GDPR states that collection and processing of personal data of EU data
subjects is lawful only if it is fair and transparent. Processing is fair only if the
collection follows the principles of “Privacy by Design”, the data is protected
at each step and kept no longer than required, the individual data subject
has the opportunity to give unambiguous and informed consent to the
processing, and the data controller only uses the data for the disclosed and
agreed purpose. It is transparent only if the data controller, when requesting
consent, tells the individual what data is collected, who will have access to or
process the data, and what the data will be used for. The consent also must
say whether the data will be transferred outside the EU. Companies will
need to use clear and plain language in their consent forms, and they cannot
condition access to the service on receipt of consent to uses of the data
Data is
protected
at each step
and kept no
longer than
required.
Chapter 10 Security, Privacy, and the Internet of Things
Lawful Processing
beyond what is absolutely necessary to provide the service. Data subjects
also need to be provided with a way to withdraw their consent, to ask that
incorrect personal data be corrected, or to ask not to be contacted in the future.
Services that allow for public searching of data also must provide a way, in
certain circumstances, to “erase” data about an individual upon their request.
Privacy by Design
GDPR obligates companies to follow a “Privacy by Design” approach
in building their services and systems. The core concepts are data
minimization, meaning collecting and processing the minimum data set
necessary for the service, and securing the data against known risks of
unauthorized access, deletion, alteration, or loss of availability.
Security and Breach Notification
GDPR requires that companies holding and processing personal data take
appropriate measures to protect the data. This may include encryption in
transit or at rest, use of firewalls or intrusion monitoring tools, and allowing
access only to employees or service providers who have a clear need and
who have undergone training. Security also requires the data controller to
either securely delete personal data from production systems when no longer
needed, or thoroughly “de-identify” it so that it is no longer personal data.
In the event of a breach that could impact the rights and freedoms of EU
citizens, the data controller must notify their local authority within 72 hours
of first becoming aware of the breach and must notify the affected data
subjects without undue delay.
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Along with regulations, such as GDPR, enterprises
may need to conform to national regulations in certain
countries that prohibit the transport of data beyond their
national boundaries for processing and analytics. This data
includes the privacy concerns of individuals and companies
described above, but also includes other data as well.
Thus, enterprises deploying IoT applications in these countries must
understand whether the data must be analyzed in-country, using local
servers or commercial cloud facilities, rather than being sent to servers
Chapter 10 Security, Privacy, and the Internet of Things
INTERNATIONAL DATA TRANSPORT
outside national borders.
Today, it is unclear if these requirements consistently include “control plane”
messaging that is used to manage the devices (such as cellular registration
for roaming units with a home database server) rather than the actual content
of the data that they transmit during normal operations. The regulations
often are all-inclusive and could lead to operational difficulties if they are
violated. It is best to clearly obtain and follow the rules for the country where
the IoT devices are deployed. If exemptions are possible (perhaps through
anonymization of the data), they should be described, in writing, by the
national regulators in order to avoid future issues.
SECURITY OBJECTIVES
There are four basic security objectives that must be met
for all IoT security implementations:
• Authenticated sender and receiver
• Sender and receiver accessible
• Trust in the data content
• Confidentiality of information
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In any data connection, it is important for the sender and receiver of
information to be authenticated to each other, regardless of whether the
device is the sender (for remote data gathering and transmission) or the
receiver (for data and control messages from the server). As a general
security principle for transmitting data, the device must ensure that it is
sending its information to the correct server, and when receiving data
and control messages, it must ensure that the information is coming from
the correct server.
Sender and Receiver Accessible
In any network, the sender and receiver always must be accessible when
needed. If the network is not functional, or the server is not executing the
correct programs and processes to receive the data, the purpose of the
Chapter 10 Security, Privacy, and the Internet of Things
Authenticated Sender and Receiver
application may be lost. Mission-critical applications, such as automatic crash
notification or medical alerts, may fail to work properly if the connection is not
reliable. The lack of communication itself means a lack of security.
Trust in the Data Content
The accuracy in the content of the transmitted data is essential. If a device
does not encode and transmit data correctly, or if the connection is not errorfree, the quality and accuracy of the data becomes suspect. Even good data
becomes unreliable, and business actions that are taken on the content of
the data may not be appropriate.
Mission-critical information is particularly important to keep as error-free
as possible. The cost of business actions taken on receipt of incorrect data
may be high.
Confidentiality of Information
Finally, the confidentiality of the information must be maintained. Only the
correct recipient should have access to the transmitted data because it may
contain proprietary or confidential information. Indeed, privacy laws in many
countries require extra care with information regarding individual citizens. For
example, in the U.S., the Health Insurance Portability and Accountability Act
(HIPAA) provides specific rules for individually identifiable medical information.
And, of course, the GDPR requirements mentioned earlier are extremely
important for applications that operate in the EU or interact with its citizens.
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Security risks generally can be recognized and understood,
and the implementation of security methods should be
incorporated in the IoT device and software associated
with that application during the design phase. The concept
of “Security by Design” is essential. The nature of these
new deployments brings new complexities to creating
secure solutions.
Most obvious holes in security can be resolved quickly and efficiently. In
general, the potential for problems can be managed with confidence with
Chapter 10 Security, Privacy, and the Internet of Things
SECURITY ISSUES FOR IoT
the chosen security methods. However, it is vital to recognize that risks can
never be completely eliminated, and there is no single security solution for all
possible security requirements for all applications.
Thus, it is critical to assess the level of security implementations that are
appropriate for different kinds of data. It is imperative that this assessment
be done early—during the design of the application and devices, not as an
afterthought once many devices have been deployed.
Before choosing how to secure the application, there are a number of issues
to be considered:
• Authenticating presence on multiple data transport networks.
• Authorization for multiple types of services.
• Scaling to manage the large number of devices in IoT solutions.
• Automation for application functionality.
• Long lifecycles for deployed devices and applications.
• Implementing security updates in remote devices.
Multiple Networks
Some IoT devices operate in more than one transport network or technology
for redundancy or hybrid solutions. In these devices and solutions, security
may be more of a concern in one particular network compared to the others.
For example, a short-range wireless technology, such as Wi-Fi, can have
quite a different security threat vector and potential for breaches compared to
a long-range cellular service.
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Applications and devices may use multiple services, where the required
authorizations for allowing a device access to a particular service may
differ from one application to another. The authentication mechanisms also
may differ, and developers must minimize the risk of a less secure service
authentication system from allowing a device to be compromised.
Scaling Growth
In IoT deployments, there are predictions of explosive growth in the near
future—billions of potential devices within the next 5 to 10 years.
Thus, in any application where a security issue exists, the overall problem
could be magnified greatly by the large numbers of devices that may be
affected. This could result in network and data security issues that are difficult
to solve, since replacing all the compromised devices could be extremely
Chapter 10 Security, Privacy, and the Internet of Things
Multiple Types of Services
difficult, perhaps impossible.
Automated Functionality
In many IoT applications, the data is acted upon by automated programs
that process the received data and take business actions based on the
content. If the transmitted data is compromised, any simplistic responses or
automated functions to that compromised data could cascade into greater
difficulty. If some set of devices transmit excessively due to a program error,
the servers processing that incoming data could overload and not provide a
timely response to the device transmissions. Simplistic retry algorithms in the
devices may create a data storm as a result.
Long Lifecycles
Unlike handsets used by people who change them every few years, IoT
devices—particularly in industrial applications—may be deployed for many
years and operate continuously over that time. Often, the devices use
electrical power rather than batteries (unlike handsets that shut down when
battery energy is depleted), and the IoT devices could continue to use the
networks for years. Devices with compromised security could stay operational
for lengthy periods.
Remote Updates
Therefore, it is essential to plan and design for device updates via overthe-air (OTA) notifications—not just for application feature updates, but
also to update the security implementations within the devices. When a
device security breach is sufficiently critical that the device firmware must
be updated, the ability to reprogram the functionality remotely is vital. The
devices may be in inaccessible locations or a large number of devices must
be modified rapidly. However, the ability to perform OTAs also introduces
additional risks.
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For some data, the issue of security may not be as critical.
For example, if an IoT device is collecting temperature
information from a residence for monitoring (not controlling)
purposes, the security needs for this data to be protected
is not as stringent as a device that collects and transmits
credit card information for financial transactions.
Thus, the effort and level of security implementations, as well as the methods,
Chapter 10 Security, Privacy, and the Internet of Things
RISK MANAGEMENT AND
ASSESSING IMPACT OF BREACHES
necessarily differ for these two examples. One may require anonymizing the
data source for simplicity and privacy, and the other may require strong data
encryption to prevent unauthorized access to the data.
It is important to remember that even if we could determine all possible threat
vectors, the cost of designing preventative measures to counter every threat
might be prohibitively expensive. In all IoT deployments, it is important to
assess the potential for damage caused by a security breach and implement
security solutions accordingly.
To start, ask the following questions:
• If a single device is compromised, can it be used to compromise other
devices? The data transport used by that application? The remote
application servers? That entire application?
• If an application is compromised and misused, what impact does that
security event have? Is it life threatening to one individual? To more than
one individual? An entire population in a region?
• Can a data content breach cause financial harm to an individual? More
than one individual? The entire set of people depending on a particular IoT
application to function well?
• How quickly can the specific breach or intrusion be detected? Is it using
a well-known target mechanism (such as might exist in a widely used
cellular device operating system)?
• Can a compromised device, or set of devices, be isolated from the
application rapidly?
• If the data is personal information, does the breach violate the GDPR
(or similar regulation) and necessitate the need for timely and proper
compliant handling of that breach?
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The Definitive Guide | The Internet of Things for Business, 3rd Edition
Chapter 10 Security, Privacy, and the Internet of Things
In all IoT deployments,
it is important to
assess the potential
for damage caused by
a security breach and
implement security
solutions accordingly.
138
different points, with differing capabilities, in the IoT data chain. Developers
should assess the opportunity for implementing security best practices
(authentication, encryption, breach detection, etc.) at every point of that chain
during the design of the application—adhering to Security by
Design principles.
For example, the source of data could be a sensor. These are not likely to be
compromised easily, since they are very specific to their function, but they still
need protection. However, because of the simplicity of such sensors, it often
is difficult to implement a security solution for them.
Regardless, a compromised sensor could be used to inject false data into
the application, where an incorrect action might be taken by a server or
Chapter 10 Security, Privacy, and the Internet of Things
The opportunities for implementing security best practices occur at
human at the remote end of the chain. Data analytics systems are useful to
appropriately deal with false data.
A more complex source device, such as a multi-technology gateway
connecting to multiple types of sensors, or a cellular modem, offers more
opportunity—both for breaches to occur, as well as a location in the chain
for implementing a good security solution. For example, a gateway device
could have the compute capacity to implement encryption algorithms,
thereby securing the content further along the chain to the servers that
receive the data.
In general, the “closer to the device” that security best practices can be
implemented, the less impact a security breach can have on the overall
application. Indeed, it could be possible to isolate a subset of devices (or
applications) that are breached if the impact might be significant to the entire
application (or network) as a whole.
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assessment to determine the relevant security needs. And organizations have
to understand the trade-offs they make up-front. It is simply impossible to
determine all possible methods by which all such IoT data applications could
be compromised.
Even if we could determine all possible threat vectors for a particular
application, the cost of designing detection and preventative measures to
counter every threat might be prohibitively expensive for that application.
The best we can do is understand and minimize the risk as best as we can
up-front, then design the devices and application processes to be as easily
updatable as possible.
While server programs and accessible elements of the data chain can be
Chapter 10 Security, Privacy, and the Internet of Things
Each business and its IoT application implementations will require its own risk
updated more easily, the ability to re-program devices using OTA updates
is key to ensuring that the impacts of security breaches can be contained
and repaired. All device developers should look to implement OTA updates if
possible and practical, even if it potentially increases the cost of the device—
for example, adding on-board memory to support multiple “images” of
firmware for updates.
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One of the most basic technological tools to secure the
content and data in an IoT deployment is to encode the
data so that only the authorized recipient (whether it is a
program or human) can decode the data.
After the data is gathered and transmitted by the remote device (or is sent by
the server to the device), the content can be encrypted at various points along
the network, as well as when the data is stored.
The basic goals of encryption are to provide:
Chapter 10 Security, Privacy, and the Internet of Things
ENCRYPTION AS AN IoT TOOL
• Proof that the sender is valid—Encryption can make the data’s source
relatively irrefutable. Techniques such as electronic signatures on a
document can be a sign of irrefutability. Proof of who sent data is crucial
so that a hacker doesn’t steal a session and then pretend to be that user,
which is called spoofing.
• Proof that data was not altered—Encryption functions can be used to
ensure that a change to the data renders the content unusable to an
unauthorized recipient.
• Proof that data cannot be read by a third party—Encryption protects
data from being read in transit or upon receipt, except by someone (or a
process) with the correct decryption method.
Data encryption can protect the content in each of these areas to different
levels, depending on the need and the specific type of encryption that is used.
Weaknesses in Encryption
No encryption method is perfect. Depending on the computing power
available at a particular location, or the processing time used by the encryption
method, the algorithm may be weak or strong. In some low-cost sensors, it
may be impossible to implement encryption if the processor within the sensor
simply cannot perform the task—the developers must look for opportunities
further up the data transmission chain to implement the encryption.
Strong encryption may seem impossible to break but applying enough
compute resources to the task could reveal weaknesses that allow the data to
be decrypted by unauthorized systems or people. Additionally, future advances
in quantum computing will make breaking the encryption even easier.
Indeed, bugs may be discovered in the method itself, or in the particular
software implementation. A recent example is the Heartbleed security bug in
OpenSSL discovered in 2014. This affected about 17% of the world’s web
servers and, potentially, allowed encrypted data to be read. Patches were
made to OpenSSL, and a majority of web servers have since been updated.
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It is beyond the scope of this book to describe or
recommend a particular encryption algorithm. The specific
requirements of the IoT application or the computing
power available at a place in the data chain may drive a
preference for a particular algorithm.
Security experts can provide guidance for selecting an approach and should
be consulted during the design of the application.
Chapter 10 Security, Privacy, and the Internet of Things
CHOICE OF ENCRYPTION
ALGORITHM
The Information Technology (IT) departments at each company may have
specific encryption and security requirements, as in the use of Virtual Private
Networks (VPN) to transport data into its servers for processing and storage.
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CHAPTER 11
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146
149
152
154
IoT
USE CASES
RENEWABLE SOLAR ENERGY
AUTOMOTIVE
HEALTHCARE
SMART CITIES
FINANCIAL / INSURANCE
Chapter 11 IoT Use Cases
IoT USE CASES
We are a connected world. We now communicate with machines, with systems,
with people. That instantaneous connection, driven by real-time data, opens up
opportunities for businesses and individuals in ways not even imagined just a few
years ago. With IoT, the opportunities are endless. Below, we outline just some of the
use cases in which IoT can influence outcomes, enhance business efficiencies and
opportunities, and improve lives.
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Companies operating in the most remote locations, with
products purpose-built for off-grid, rural, and often hostile
environments, require a reliable global mobile network
that provides consistent connectivity worldwide to enable
effortless remote monitoring of solar energy systems. To
overcome these many life-critical, energy-delivery issues,
there is significant need for reliable GSM and CDMA
connectivity to deliver functional, energy saving solutions.
Chapter 11 IoT Use Cases
RENEWABLE SOLAR ENERGY
The World Energy Outlook estimated that 1.2 billion people, equivalent to
16% of the global population, do not have current access to electricity, with
many more people living with an electricity supply described as poor quality
or unreliable. More than 95% of those living without electricity are in SubSaharan Africa and developing Asia, 80% of which live in rural areas.
For example, BBOXX, a UK-based solar energy provider, using IoT
technologies, has developed solutions to provide affordable, clean energy to
off-grid communities in the developing world.
To address these issues, the solar-powered BBOXX system is deployed on
a simple plug-and-play basis, without the need to reconfigure to use local
network settings. By working with a carrier-agnostic and technology-agnostic
partner, BBOXX installed a global Subscriber Identity Module (SIM) at the
point of manufacture, reducing both supply chain costs and deployment time.
Advanced IoT connectivity enables energy provider
networks to overcome critical issues, such as
interrupted services, security breaches, and high
implementation and maintenance costs.
Within the residential and commercial solar sectors, SolarEdge, an Israeli
company with headquarters in the United States, provides solar solutions for
homes and businesses. Company products include power optimizers, solar
inverters (DC to AC inversion), and cloud-based monitoring solutions.
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Chapter 11 IoT Use Cases
With a presence in 13 countries, all with somewhat different connectivity
options and providers, secure and reliable connectivity was integral to the
company’s success. SolarEdge chose a carrier-agnostic and technologyagnostic IoT partner for deploying cellular connectivity, as well as for the
corresponding management solution. In dealing with a seasoned, professional
connectivity solution provider, SolarEdge was able to secure instant global
connectivity and management oversight; advanced revenue-grade metering;
and robust, real-time troubleshooting. Visibility into devices improved,
operational efficiency rose, customer service radically upgraded, and
inventory and loss management became transparent and easy to administer.
AUTOMOTIVE
Fleet
Fleet managers need real-time intelligence to solve transportation
issues before they become costly mistakes. They require a connected
data transport solution, combined with IoT analytics, to reduce
time-to-market processes, resolve troubleshooting issues, and bring
down the total cost of ownership. It is only with real-time business
intelligence data that retailers and manufacturers can acquire a
comprehensive view of their transportation ecosystem.
The fleet
The global trucking industry is undergoing enormous change. Older vehicles
management
are being replaced with “smart trucks” using IoT systems with cellular and
satellite communications technologies to transmit essential information for
solutions
management of fleet operations.
sector will rise
Commercial fleet programs are becoming more complex―beyond the
in valuation
original simple needs to manage inventory, location, routing, and fuel costs,
they now face requirements for mission-critical reliability, cross-region
from US$12.5
connectivity, and innovative market differentiation.
billion in 2015
Long-haul fleet management providers require onboard computing and fleet
to an expected
communications to deliver better business outcomes. On-board solutions
US$92 billion
require highly reliable, real-time, always-on cellular network connectivity,
which might require multiple carriers to meet the full-coverage needs of
by 2025.
fleet customers wherever they reside and drive.
The market for global fleet management solutions continues to expand
quickly. Data from Transparency Market Research estimates that the fleet
management solutions sector will rise in valuation from US$12.5 billion in
2015 to an expected US$92 billion by 2025, with a CAGR of 22.6% for
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to Berg Insight, connected fleet management will grow from 5.8 million rolling
units in operation to more than 12.7 million by 2020. Additionally, Berg Insights
see similar European growth in the sector, expanding from 5.3 million units in
2015 to an estimated 10.6 million by 2020.
As the commercial fleet sector becomes even more competitive, fleet owners
and operators are seeking more reliable connections―with flexible rate plans
Chapter 11 IoT Use Cases
the period between 2017 and 2025. In North and Latin America, according
and seamless coverage―across many geographic areas and remote locations.
In Europe, seamless cross-border operation for the trucking industry is an
essential requirement, as trucks continually traverse national boundaries.
Connected Car
Car makers have been honing in on the monetization of vehicle data. This
desire to monetize involves data from internal applications (diagnostics,
customer relationship management, marketing) and external applications
(usage-based insurance, traffic information). This requires more complex
systems for extracting, storing, normalizing, and preserving or deleting data.
Recent surveys estimate that 75% of all new cars shipped globally by 2024
will be equipped with wireless connections. Twenty years after General
Motors shipped its first connected Cadillacs, car companies have learned that
it is not enough to build a telecommunications module into the vehicle. The
entire system supporting that connection has to be properly designed and
maintained for the connected car proposition to be viable.
Today, connected cars are using IoT to connect everything from engine
diagnostics, to GNSS location data, to actual driving behaviors, to
infotainment systems. Modern connected car systems are expected to be
always-on and, increasingly, will be asked to support autonomous driving
and safety applications, such as collision avoidance. A reactive system, like
OnStar’s original offering, is no longer sufficient. Today, 80% of connected
cars are using technology that is more than a decade old and hardly suited to
automakers’ rapidly changing needs, let alone those of the customer.
Wireless connectivity, today and into the future, will be expected to maintain
continuous connections with increasing demands on the communication
of vehicle data and software updates; secure both real-time and historical
vehicle data; provide customizable end-user dashboards so as to share data
from the vehicle tracking system with end users and customers; and greater
insights leading to a safer and more efficient driving experience.
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technologies in development to make this a practical reality. While the
requirements of instantaneous action, such as accident avoidance, means
that the cars must process sensor data extremely rapidly―local to the
vehicle―other capabilities will be enabled by faster cellular technologies,
such as 5G.
For example, updates for general traffic conditions beyond the range of
Chapter 11 IoT Use Cases
The future of fully autonomous driving is interwoven with the communication
vehicle-to-vehicle (V2V) radio technology, as well as dynamic updates for
road changes (repair work, hazards), can be enabled by the advent of faster
cellular technologies.
Leasing / Ride Sharing / Asset Management
In many parts of the world, transportation is a huge hurdle. Traffic, costs,
and vehicle availability all come into play. To alleviate some of these issues,
ride-sharing companies are rapidly expanding globally, trying to fill the need
of moving people in urban areas. In fact, revenue from the global ride-sharing
sector is approaching US$57 billion and is expected to show an annual growth
rate of 16.5%, resulting in a market volume of US $106 billion by 2022.
In many countries, drivers want to lease vehicles so they can create their own
ride-sharing business driving for a specific brand. This creates a significant
risk of loss of the leased asset due to theft, lack of payment, or hijacking.
Additional loss can come from misuse of the vehicle.
In order to protect their investments, ride sharing companies need to track all
their vehicles, many of which are leased to individual drivers. Companies need
data on driver performance and access to vehicle metrics regarding whether
the leased vehicle is being used for another service or whether the driver
is paying leasing fees. In such cases, ride-sharing companies also need the
ability to remotely disable the vehicle before harm can be done to a company
or its reputation.
Key to all this is reliable monitoring and tracking connectivity so that data is
collected in a timely manner. Poor quality of IoT devices and slow response
times to problem management scenarios are situations that also need attention.
Today, ride-sharing companies can install a tracking device in their vehicles,
which ensures constant monitoring of vehicle location; insights to driver
performance metrics; vehicle metrics; auto-immobilize functionality if the
driver is late paying leasing charges or if the vehicle is reported stolen
or tampered with; or to halt activities if the driver is using the vehicle for
unauthorized purposes. This comprehensive IoT asset management solution
allows ride-sharing enterprises to retrieve any vehicle operating outside of
company guidelines and to protect its investment in a costly asset.
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The healthcare industry shows great promise as
IoT-driven systems and applications are improving
access to care, increasing the quality of care, while, at
the same time, reducing its overall cost. Today, it is one
of the fastest growing IoT sectors, with a large number of
startups developing new medical sensors, transporting
the data to care providers, and achieving the desired
health improvement outcomes.
Chapter 11 IoT Use Cases
HEALTHCARE
It has been estimated that 40% of the global economic impact of the IoT
revolution will occur in healthcare, more than any other sector. And
IoT-driven companies can gain a competitive edge in that sector—specifically
in areas such as user experience, operational costs and efficiencies, and
global expansion.
Cellular connectivity and IoT solutions enable medical device manufacturers
and healthcare providers to achieve the highest levels of patient engagement
and medical adherence, with the lowest TCO, regardless of global location.
Here we look at several use cases within the healthcare market in order to
show the progress, as well as the possibilities that exist going forward.
Patient Monitoring
Estimates show that more than 200 million people in the EU and the U.S.
suffer from one or several diseases that may benefit from some type
of home monitoring.
New IoT technologies are changing the way health services are delivered,
allowing recipients to remain in their homes to receive care and avoid costly
hospital stays. Companies are expanding in-home services, providing
solutions for independent living specifically tailored to serve aging and
disabled populations nationwide. With that in mind, more and more state
and federal healthcare agencies encourage in-home care programs as a vital
way to deliver efficiencies and reduce costs.
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healthcare-focused services. The company deploys a cost-effective IoT
cellular solution that provides connectivity for its services, regardless of the
patient’s location. Its systems proactively alert patients and caregivers to
changes in behavioral patterns by communicating with multiple sensors to
observe activities of daily living.
Chapter 11 IoT Use Cases
SimplyHome designs and installs wireless technology products and related
Text, email, or phone alerts can be generated by a single event, an intersection
of multiple events, or by inactivity. Components, such as motion-sensors,
door / window contacts, and bed pressure pads, alert caretakers to falls,
wandering, or changes in sleep patterns. The IoT-enabled SimplyHome
system helps residents remain independent with environmental controls that
operate beds, lights, TVs, doors, and more via tablet or voice activation.
Medical Adherence
According to research by the World Health Organization (WHO), the benefits
of medications used to fight disease are not fully realized because close to
50% of patients do not adhere to medicinal intake guidelines. Reasons for
not taking medicines on a regularly needed basis are plentiful, running from
lack of funds to sub-optimal healthcare literacy to communication / language
barriers to just plain forgetfulness.
As another example of IoT serving the healthcare sector, Wisepill is a leading
provider of medical adherence management solutions and the creator of the
Wisepill dispenser, a pillbox that uses cellular and IoT technologies to provide
real-time medical management solutions. The pillbox, designed to work in
diverse environments, has a rechargeable, longer-life battery, which allows
the device to be used for extended periods without the need of an external
power source.
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easily to far-off clinics. Additionally, many places have a severe shortage
Wisepill
of medical professionals. With IoT connectivity, Wisepill enables clients,
enables clients,
pharmaceutical businesses, doctors, and healthcare organizations around the
pharmaceutical
world to improve medication adherence management. The combination of
an experienced IoT solution provider and Wisepill provides patients with the
businesses,
peace of mind from knowing that if they miss taking their medications, there
doctors, and
would be a reminder to maintain their medicinal intake schedule.
By continuing to apply new cost-saving IoT technologies, and leveraging
economies of scale, Wisepill is providing affordable adherence solutions,
healthcare
organizations
assisting millions of people, regardless of where they live.
around the
Blood Banks
world to
Blood units represent a critical aspect of healthcare. Yet, blood units often get
improve
wasted due to the inability to store them under appropriate conditions.
The principal goal of an IoT technology-driven blood bank management
medication
program is to optimize the effectiveness of a blood bank. A successful
adherence
program involves increasing awareness about best practices; reducing
management.
the likelihood of blood samples becoming unusable; minimizing blood
Chapter 11 IoT Use Cases
Patients in developing countries or in hard-to-reach rural areas cannot travel
loss; improving blood availability; continuously educating clinicians; and
standardizing operations through workflows.
For example, in India, the business case for an IoT-enabled blood bank
monitoring solution rests on the following goals:
• Monitoring blood bank refrigerators on a 24x7 basis and storing
relevant data.
• Alerts of temperature variance outside a set range.
• Use of transparent monitoring network (single pane of glass).
• Reduction of paperwork.
The IoT-based blood bank improvement program includes both a measurement
of how well the program meets its goals and also demonstrates a commitment
to data driven reporting. This, plus additional functionality, provides the
insights needed to initiate and preserve blood bank management that will
save many lives.
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Doctors and hospitals need a secure way to establish connectivity and
transmit data from automated external defibrillators to a cloud application.
Today, IoT-connected medical devices can monitor and analyze data coming
from the patient in real time. And should an event occur, IoT-enabled
defibrillators, for example, provide verbal and on-screen instructions in
Chapter 11 IoT Use Cases
Device Monitoring: Defibrillators / Heart
Monitors / Pacemakers
delivering chest compressions. Some advanced defibrillators even can
deliver an electrical shock to a patient’s heart. Heart monitors send alerts
to both wearer and doctor in case of irregularities. In all these cases, device
connectivity, with real-time data, literally, is a life and death issue.
With an IoT-enabled solution for healthcare devices, real-time data, along
with alerts and reports, can save lives.
SMART CITIES
Virtually every aspect of city operations can be made
smarter through IoT—from embedded roadway devices
to advanced lighting to waste management. That means
there is unlimited potential for IoT providers to deliver a
variety of solutions to meet the ever-increasing demands
for efficiency and cost reduction.
The human migration to cities now is a global trend that research indicates
will continue for the foreseeable future. While this shift has enhanced the
economic well-being of millions, it also has placed incredible demands on
infrastructure and threatens the quality of life of the inhabitants of large, evergrowing cities.
Compounding these problems is the fact that tax bases and budgets do
not match the ever-growing needs. This is where IoT solutions can have a
significant and immediate impact.
A “smart city” may sound futuristic, but at its heart, the idea is quite simple
and traditional—smart cities bring together current and new technologies,
infrastructure, and government to benefit people’s quality of life.
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Chapter 11 IoT Use Cases
Smart cities
bring together
current and new
technologies,
infrastructure, and
government to
benefit people’s
quality of life.
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municipalities the ability to remotely monitor, manage, and control devices
using IoT technology. These tools help citizens create new insights and
actionable information from massive streams of real-time data.
IoT enables traditional cities to become ‘smart’ by incorporating ecosystems
that offer remarkable efficiencies, cost savings, and advanced resource
Chapter 11 IoT Use Cases
Smart city solutions introduce tremendous new capabilities, giving
management via automation and connectivity.
FINANCIAL / INSURANCE
The old school vision for asset insurance still is prevalent,
but the IoT is changing the landscape in a most disruptive
way—all for the good.
In the recent past, for example, vehicle telematics that insurance companies
cared about involved risk assessment, vehicle performance, reports, mobile
apps, and APIs. Today’s insurance provides a multitude of new views into
driver and driving characteristics. With sensors and devices absorbing data
at an unprecedented rate, insurance now also covers accident reconstruction,
false claims identification, overall claims management, driver coaching, alerts
and notifications, actuarial support, vehicle immobilization, asset protection,
usage-based insurance (UBI), and a lot more.
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business expectations for insurance are evolving. A platform-based, highly
scalable solution enables insurers to offer value-added services that simplify
the insurance process and radically improve customer satisfaction.
• Claims Management: Quickly process claims and identify possible fraud.
Reduce fraud and claims while speeding up the entire claims process.
• Customer Management: Maximize customer value through targeted
up-sell, cross-sell opportunities. Attract more low-risk customers.
Chapter 11 IoT Use Cases
As our world becomes increasingly digital and connected, customer and
• Renewals Management: Identify customers with high propensity to lapse
for targeted collection. Increase customer retention.
• Sales Force Management: Identify agents with high potential.
• Pricing & Risk Management: Conduct risk-based pricing for better
profitability. Gain a higher percentage of low-risk drivers. Reduce
underwriting costs. Provide customer premium savings.
The IoT enhances the interaction frequency with customers and provides
value through information and knowledge creation.
Bottom line—IoT data usage can impact services by providing insights to risk
assessment, loss control, driver behavior, product pricing, and much more.
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CHAPTER 12
158
158
159
160
160
163
164
165
166
166
THE FUTURE
OF THE INTERNET
OF THINGS
IoT WILL POSITIVELY AFFECT ALL MARKETS
IoT WILL COME FIRST
HOMES WILL GET SMARTER―AND MORE CONNECTED
ENTERPRISES WILL SPEND MORE
STANDARDS WILL IMPROVE
SECURITY CONCERNS WILL CONTINUE
OVER-THE-AIR (OTA) UPDATES WILL BECOME
THE NORM
PRIVACY CONCERNS AND GOVERNMENT
REGULATIONS
IoT VALUE REALIZED THOUGH
DATA ANALYTICS
THE FUTURE IS NOW
Chapter 12 The Future of the Internet of Things
THE FUTURE OF THE
INTERNET OF THINGS
Imagine a future where enterprise customers and consumers will ask product
companies about the sensor capabilities accessible via a mobile app when
purchasing a new appliance or car. In the future, not only will cars talk to each other,
but people will wear clothes connected to the Internet, reading glasses will be
connected to provide additional context to enrich the user’s experience, and more
than one-half of the Internet traffic to homes will go to appliances and devices and
not to children’s video games.
Sound unlikely? We think this future may not be too far away. Given the tremendous growth and
change that is taking place in the IoT industry, the future certainly is hard to predict, but here is what
we see taking shape in the near future.
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IoT applications and solutions already are positively
impacting many industries. This trend will continue
in all markets as businesses and consumers find new
opportunities where the ability to measure remote
products, gather data, and analyze the transmitted
information can improve the overall success of the
product deployment.
Chapter 12 The Future of the Internet of Things
IoT WILL POSITIVELY AFFECT
ALL MARKETS
The return on investment for IoT solutions will be a combination of direct
operational cost savings of service revenue for products, better interaction
with end-users’ needs and requirements, visibility into operational product
issues, and eliminating the need for product recalls.
IoT WILL COME FIRST
The most competitive companies, products, and solutions
will be those built around the concept of “IoT First”. This
means products will be designed from the outset with
access to connectivity and data via the IoT as a primary
consideration, and enterprises will begin planning
projects and building systems with IoT foremost in mind.
Today’s typical approach of retro-fitting connectivity to an existing product or
service will continue to occur, but those initiatives will not generate as much
value as IoT-First projects.
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As the cost of sensors, processors, and networking goes
down with volume, and consumers are increasingly aware
of the benefits of the smart home, IoT home automation
will provide greater peace of mind through security
implementations.
Remote access is the greatest selling point for IoT technologies these days.
Chapter 12 The Future of the Internet of Things
HOMES WILL GET SMARTER,
AND MORE CONNECTED
Consumers can check the status of their home from their smartphone—for
example, consumers can ensure that the front door is locked or remotely view
security cameras.
Security systems can push alerts directly to consumers, as well as security
agencies, in the case of a break-in or abnormal activity inside the home.
Many people see the value of such systems if they often are away from
home. A quick check can provide a sense of control even if they are
thousands of miles away.
Another important aspect of the connected home of the future is in the area
of energy usage. Consumers can automate lighting, temperature, and home
irrigation systems remotely. Home automation devices and sensors identify
rooms that are occupied and adjust HVAC systems and lighting to ensure
energy conservation. Self-monitoring appliances with IoT technologies
can determine changes in operation due to potential maintenance issues.
Sensors in outdoor landscaping measure the current moisture saturation
level of the ground and adjust the sprinklers. Smart meters provide utilities
with information about energy usage patterns to assist in planning power
consumption across a designated area. Discounts and incentives are given to
consumers to change usage patterns to benefit a community. The end result
of the connected home is increased safety, convenience, and freedom from
mundane decisions that allow consumers to enjoy more of their life.
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Currently, many think of IoT primarily in terms of
consumer devices and applications, but industry growth
shows enterprises will be spending far more on IoT
than consumers.
McKinsey forecasts that of the $12 trillion in economic value generated by IoT
in 2025, the majority (70%) of this value generated from IoT will be from B2B
deployments.1 Furthermore, IDC expects that by 2021, more than 70% of the
Chapter 12 The Future of the Internet of Things
ENTERPRISES WILL SPEND
MORE ON IoT
top 2,000 global corporations will be investing in connectivity management
solutions. Within the same time frame, IDC also expects that 75% of
enterprises with a positive IoT ROI will use tactical analytics applications to
reduce operating costs, while about 25% of companies that invest in decision
architecture will increase their revenue share.2 Just about any way you view it,
IoT can make a significant impact on the bottom line.
IoT STANDARDS WILL IMPROVE
The IoT space has undergone rapid growth in a relatively
short amount of time, so it’s no surprise that standards
for IoT still are in active development and not yet widely
adopted. With the proliferation of devices, sensors,
connectivity technologies, and IoT platforms that need to
be integrated to organizational systems, it is challenging
to find technology- and vendor-agnostic solutions that
work well with each other.
However, interoperability is key to ensuring the long-term success of IoT
initiatives, so companies deploying solutions need to be careful when going
down the path of a vendor-specific implementation that may not play well
with other suppliers. A lack of standards can lead to issues, including legal
implications for the accuracy of data, safe harbor issues between nations, or
liability in accidents with autonomous vehicles.
1
The CD “The Internet of Things: Mapping the Value Beyond the Hype,” McKinsey Global Institute,
June 2015.
2
“IDC Futurescape, Worldwide Internet of Things,” IDC, 2018.
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a result of deficiencies in current standards. Beyond the consolidation in the
industry that is typical of any fast-growing, dynamic sector, IoT companies
will move to providing fully enabled solutions instead of just products and
basic services. Companies will see a shift from one-time hardware sales to
“Product-as-a-Service” sales, where end users rent (or hire) the capabilities
of the product without incurring a large initial expense. This provides an
opportunity for enterprises to receive stable, long-term revenues, increase the
contact with the end user for further up-sales, and maintenance services that
could add up to significantly larger revenues over time than a simple product
delivery and sale.
Additionally, we will see a shift in IoT from technology- and vendor-specific
Chapter 12 The Future of the Internet of Things
Vendors, solutions providers, and distributors also will undergo changes as
solutions to agnostic solutions. The primary driver for this change is to help
reduce the complexity of incorporating and integrating point solutions that
slow down the number of purchases but increases the value of the solutions
services provided to the customer.
In terms of defining standards, the good news is many organizations already
are taking leadership roles.
Here are just a few groups that are furthering education, standards,
and best practices for creating, integrating, deploying, and maintaining
an IoT program:
• Standards development efforts, like OneM2M,3 set the direction for the
technical requirements for IoT interoperability and architecture. As other
industries adopt IoT, they will add to their own unique standards the
requirements for data and analytics that IoT benefits can provide.
• The IoT M2M Council (IMC)4 is focused on proving the business case
of IoT technology to customers who adopt it. It aims to stand for IoT
applications and connectivity as its own global industry and not viewed
through the narrow lens of a technical standard or single vertical industry.
• The Healthcare Information and Management Systems Society (HIMSS)5 is
a healthcare-focused organization that leads global endeavors to optimize
health engagements and care outcomes through information technology.
Its large membership is representative of the healthcare industry and
the organization is helping shape interoperability standards that will be
successfully adopted.
3
4
5
www.onem2m.org
www.iotm2mcouncil.org
www.himss.org
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Chapter 12 The Future of the Internet of Things
Beyond the
consolidation in the
industry that is typical
of any fast-growing,
dynamic sector,
IoT companies will
move to providing
fully enabled
solutions instead
of just products and
basic services.
162
Security concerns could slow down IoT adoption if
they aren’t approached thoughtfully. Given the massive
amount of data generated from information-intensive IoT
applications, the ever-increasing number of connected
devices, and the need to provide secure connectivity,
enterprises must be careful not to risk the privacy and
security of individuals.
Chapter 12 The Future of the Internet of Things
SECURITY CONCERNS
WILL CONTINUE
Although defending against all sophisticated cyber-attacks is not entirely
possible for end users of IoT technologies on their own, following industryproven best practices and designing programs with security and privacy in
mind is vital to the successful adoption of IoT. Data security will become a
very significant part of the IoT budget for most businesses.
Additionally, if an enterprise keeps security in mind from the initial phase
of any product development effort (“Security by Design”) and incorporates
it at a level that is appropriate to the use case, then most concerns will be
mitigated. Security implementations must be relative to the IoT application
requirements, and must be affordable, scalable, and user friendly. With better
insight, businesses may find that not all IoT use cases require the most robust
of security measures.
For example, fitness trackers typically track activity such as the number
of steps, number of calories burned, etc., so the devices may not need to
activate or to be physically chained down. However, the complex, connected
machinery that builds the parts of an airplane warrants physical security in
addition to a series of virtual locks to prevent unauthorized access, as well as
vetting of individuals who are permitted to remotely operate that machinery.
And finally, the enterprise should look at security as an ongoing process.
Security should be about incremental changes and not pose a fundamental
challenge that is insurmountable for business. Don’t try to build security that
is bulletproof for the next 20 or 30 years. To aim for such a goal is impossible,
as we cannot anticipate what innovations will occur or how the market will
change in the future.
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As products incorporate more and more embedded
software, the need for remote updates without requiring
the attention of skilled technicians will be the new norm,
since consumers cannot be expected to reliably perform
manual updates.
Using over-the-air (OTA) updates to refresh code inside the product will
be increasingly critical—to add new features, fix product bugs, and repair
Chapter 12 The Future of the Internet of Things
OVER-THE-AIR UPDATES WILL
BECOME THE NORM
firmware that could be sources of security breaches that impact the networks
or application.
With the large number of IoT devices inherent in many applications, the
cost of technician dispatches to fix bugs that impact other devices or data
networks would be prohibitive. OTA update capability must become the
future norm in all deployed IoT units and applications. The added up-front
cost to support these OTA updates easily will be repaid many times over, at
the first occurrence of a need to update―for example, to fix a security breach
due to cyber-attacks.
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As data and information from IoT devices increases, the
need to protect individuals and companies from privacy
breaches will become paramount. In our complex world,
the ability for consumers to understand the implications
of privacy breaches is decreasing rapidly.
Enterprises deploying IoT applications must accept an essential obligation
Chapter 12 The Future of the Internet of Things
PRIVACY CONCERNS AND
GOVERNMENT REGULATIONS
to protect the personal information of consumers to avoid problems such as
identity theft and financial loss due to security breaches.
Government regulations to manage privacy concerns and enforce consistent
compliance already are being legislated. For example, the European Union
(EU) enacted the General Data Protection Regulation (GDPR) on May 25,
2018 to unify data privacy requirements across the entire geo-political
landscape. The use of information related to Euro-citizens, companies, and
employees comes with very specific expectations of privacy, and harsh
penalties for serious violations that, potentially, could cause companies to go
out of business if they are not compliant to the requirements of GDPR.
Other countries are exploring similar and related regulations, and companies
deploying IoT solutions must follow these national laws and regulations to do
business in those countries. For example, in many regions, data—regardless
of whether it is privacy related or not—must not cross “national boundaries”.
Thus, all processing of that data, including the business outcomes of that IoT
solution, must be processed by systems local to that country.
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As billions of devices, things, and processes become
interconnected, they will create a massive volume of data
that drives the need for IoT analytics to automatically deal
with the deluge. IDC predicts that 25 million applications
will be created, and 50 trillion gigabytes of data will be
generated, by 2020.
Chapter 12 The Future of the Internet of Things
IoT VALUE REALIZED THROUGH
DATA ANALYTICS
Multiple analysts predict that by 2019, IoT-created data will be stored,
processed, analyzed, and acted upon close to, or at the edge of the network,
thus relieving part of the data proliferation challenge.
The need for data analytics will be so great that it will drive demand for jobs
for individuals that specialize in data science. While the issue of how to get
data off devices and into back-end systems is increasingly being resolved
through edge computing, the challenge of who gets to monetize the data is
not yet resolved. Also, there isn’t clarity in who plays the role of the broker of
all that data and who manages the data repository. There might be multiple
roles or one. As the increasing demand for data scientists to help make sense
of the data is met, organizations will start to utilize the data for predictive
purposes so it drives better, more efficient organizational decisions rather
than as a passive activity of analyzing the data after the fact.
THE FUTURE IS NOW
2017 was the year where the number of connected
devices surpassed the number of humans living on the
planet. And, as with any new, fast-growing technology, the
Internet of Things is not without challenges. However, the
opportunities are vast, and those that navigate the waters
thoughtfully can find great success.
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GLOSSARY
168
178
DIRECTORY
OF IoT TERMS
ACRONYMS
GLOSSARY
#s
3GPP
3rd Generation Partnership Project
2G
Second generation (as in cellular technology)
3G
Third generation (as in cellular technology)
4G
Fourth generation (as in cellular technology)
5G
Fifth generation (as in cellular technology)
Glossary Directory of IoT Terms
ACRONYMS
A
ADAS
AES
Advanced Driver Assistance Systems
Advanced Encryption Standard
AMPS
Advanced Mobile Phone System
AMPQ
Advance Message Queuing Protocol
ANSI-41
American National Standards Institute Standard 41 (control signal
messaging on SS7)
ANSI-95
American National Standards Institute Standard 95 (for CDMA cellular)
ANSI-136
American National Standards Institute Standard 136 (for TDMA cellular)
ANSI-2000
American National Standards Institute Standard 2000 (for CDMA
200 cellular)
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ARP
AWS
Application Programming Interface
Address Resolution Protocol
Amazon Web Services
Glossary Directory of IoT Terms
API
B
BAN
Body Area Network
BLE
Bluetooth Low Energy
BSC
Base Station Controller
BTS
Base Transceiver Station
BYOC
Bring Your Own Carrier
C
CAN
CDMA
CoAP
Controller Area Network
Code Division Multiple Access
Constrained Application Protocol
D
DG
DL or D/L
Distributed Generation
Download data to end node from server / target address
DoF
Degrees of Freedom
DR
Demand Response
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EAN
European Article Number
ECU
Electronic Control Unit
EDGE
Enhanced Data rates for GSM Evolution
EPC
Electronic Product Code
ESD
Electrostatic Discharge
ESN
Electronic Serial Number
EV-DO
Glossary Directory of IoT Terms
E
Enhanced Voice Data Only (or Enhanced Voice Data Optimized)
F
FAKRA
FDMA
FOTA
Fachnormenausschuss Kraftfahrzeugindustrie
Frequency Division Multiple Access
Firmware Over-the-Air
G
GGSN
GIS
GLONASS
Gateway GPRS Support Node
Geographic Information System
Russian global navigation system
GNSS
Global Navigation Satellite System
GPRS
General Packet Radio Service
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U.S. Global Positioning System
GSM
Global System for Mobile communications
H
HDFS
HEM
HEMS
Hadoop Distributed File System
Home Energy Management
Home Energy Management System
HetNet
Heterogeneous Network
HLR
Home Location Register
HSDPA
HSPA
High-Speed Downlink Packet Access
High-Speed Packet Access
HSPA+
Enhanced or Evolved High-Speed Packet Access
HSUPA
High-Speed Uplink Packet Access
HVAC
Glossary Directory of IoT Terms
GPS
Heating, Ventilation, and Air Conditioning
I
I2C
IaaS
ICCID
ICS
Inter-Integrated Circuit
Infrastructure as a Service
Integrated Circuit Chip Identifier
Industrial Control System
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IETF
IIoT
Information and Communications Technologies
Internet Engineering Task Force
Industrial Internet of Things
IMEI
International Mobile Equipment Identifier
IMS
Intelligent Multi-Media System
IMSI
International Mobile Subscriber Identifier
IoE
Internet of Everything
IoT
Internet of Things
IPSEC
IPv6
Internet Protocol Security
Internet Protocol Version 6
IS-136
Interim Standard 136
IS-95
Interim Standard 95
ISDN
Integrated Services Digital Network
ISM Bands
Industrial, Scientific, and Medical Bands
ITS
Intelligent Transportation System
ITU
International Telecommunications Union
IVI
Glossary Directory of IoT Terms
ICT
In-Vehicle Infotainment
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JSON
JavaScript Object Notation
L
L2TP
Layer 2 Tunneling Protocol
LAN
Local Area Network
LED
Light Emitting Diode
LPWA
LPWAN
LTE
LTE-M
Glossary Directory of IoT Terms
J
Low Power Wide Area
Low Power Wide Area Network
Long-Term Evolution
LTE category M1
M
M2M
Machine-to-Machine
MAC
Media Access Control
MCU
Micro-Controller Unit
MDN
Mobile Directory Number
MEID
Mobile Equipment Identifier
MEMS
Micro-Electro-Mechanical Systems
MIMO
Multiple Input, Multiple Output (in regards to antennas)
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Multimedia Messaging Service
MNO
Mobile Network Operator
MQTT
MS
MSC
MSISDN
MVNO
Message Queue Telemetry Transport
Glossary Directory of IoT Terms
MMS
Mobile Station
Mobile Switching Center
Mobile Station ISDN
Mobile Virtual Network Operator
N
NB-IoT
NFC
Narrowband IoT
Near Field Communication
P
PaaS
Platform as a Service
PAN
Personal Area Network
PCB
Printed Circuit Board
PDU
Power Distribution Unit
PERS
PoE
PPTP
Personal Emergency Response System
Power over Ethernet
Point-to-Point Tunneling Protocol
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Preferred Roaming List
PXE
Preboot Execution Environment
Q
QoS
Glossary Directory of IoT Terms
PRL
Quality of Service
R
RADIUS
REST
RF
RFC
RFID
RPMA
Remote Authentication Dial-In User Service
Representational State Transfer
Radio Frequency
Request for Comment
Radio Frequency Identification
Random Phase Multiple Access
S
SaaS
SBC
SCADA
Software as a Service
Single Board Computer
Supervisory Control and Data Acquisition
SDN
Software-Defined Network
SDO
Standards Development Organization
SGSN
Serving GPRS Support Node (also see GGSN)
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Subscriber Identity Module
SMA
Sub-Miniature version A
SMS
Short Message Service
SMSC
Short Message Service Center
SOAP
Simple Object Access Protocol
SoC
System on a Chip
SS7
Signaling System 7
STOMP
Glossary Directory of IoT Terms
SIM
Simple (or Streaming) Text-Oriented Message Protocol
T
TCP / IP
TDMA
TETRA
Transmission Control Protocol / Internet Protocol
Time Division Multiple Access
Terrestrial Trunked Radio
U
UART
UBI
UL or U/L
UMTS
Universal Asynchronous Receiver / Transmitter
Usage-Based Insurance
Uplink or Upload
Universal Mobile Telecommunications System
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Uniform Resource Identifier
URL
Uniform Resource Locator
V
V2I
Glossary Directory of IoT Terms
URI
Vehicle-to-Infrastructure
V2V
Vehicle-to-Vehicle
V2X
Shorthand for combining vehicle-to-vehicle (V2V), vehicle-to-infrastructure
(V2I), and vehicle to anything
VLR
Visitor Location Register
VPN
Virtual Private Network
W
WAN
Wide Area Network
WAP
Wireless Application Protocol
WAVE
Wi-Fi
Wireless Access in Vehicular Environments
Wireless Fidelity
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#s
1xEV-Do
1xRTT
1 times Evolution Data Optimized (used in ANSI-2000 CDMA).
Glossary Directory of IoT Terms
GLOSSARY
1 times Radio Transmission Technology (used in
ANSI-2000 CDMA).
2.4 GHz
Wireless band commonly used in technologies such as Wi-Fi,
Bluetooth, and ZigBee. This unlicensed band also is used by some
LPWA technologies.
2G
Second-generation cellular technology. This technology is starting
to be sunset in U.S. and elsewhere.
3G
Third-generation cellular technology offering improved data
transfer rates over 2G. Increased capacity and data speeds with
additional protocols.
3GPP
3rd Generation Partnership Project (3GPP) is a collaborative project
aimed at developing globally acceptable specifications for thirdgeneration (3G) mobile systems (GSM).
3GPP2
3rd Generation Partnership Project (3GPP2) is a collaborative
project aimed at developing globally acceptable specifications for
third-generation (3G) mobile systems (CDMA).
4G
Fourth-generation cellular technology and the latest upgrade to the
GSM network, providing greater data transfer speeds. Also known
as LTE.
5G
6LoWPAN
Fifth-generation cellular technology.
Communication protocol that compresses lvp6 packages for small,
low-power devices so as to let them communicate within the IoT.
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Wi-Fi protocol that uses sub-1 GHz license-exempt bands
(as opposed to conventional Wi-Fi that operates in the 2.4 GHz
and 5 GHz bands).
868 MHz
License-free RF band mostly used for short-range applications,
such as thermostats, security alarms, and industrial uses.
92 MHz
Glossary Directory of IoT Terms
802.11ah
License-free RF band used for short-range applications. The low
frequency allows for better penetration through walls and obstacles.
Has a low data transfer rate.
A
Acceleration Sensing
A MEMS concept referring to the increase in movement of an object
from one point to another along a straight line or axis. Applications
include remote control, pointing devices, gesture recognition, fitness
monitoring equipment.
Accelerometer
Tool that measures changes in acceleration in the unit in which it is
installed. Used to measure acceleration, tilt, vibrations.
Access Control
A system that determines who, when, and where people can enter
or exit a facility or area. Used for electrical systems, wireless locks,
cybersecurity, etc.
Access Point
Active Sensor
A Wi-Fi node that allows users entry to a network, typically a LAN.
A sensing device that requires an external source of power
to operate.
Actuator
A device that introduces motion by converting electrical energy into
mechanical energy in an electromechanical system. An actuator also
may stop motion by clamping or locking.
Address Resolution Protocol
(ARP)
Communication protocol used to convert an IP address into a
physical address. This way, computers can communicate with each
other, despite only knowing each other’s IP addresses, by sending
an ARP request that informs them about the other computer’s
MAC address.
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Systems (ADAS)
Digital features incorporated into vehicles to enhance driver safety.
ADAS functionality includes digital vision for lane departure
warnings, blind spot detection, radar for collision avoidance, and
V2V communications for multiple vehicles operating near
each other.
Advanced Message Queuing
Protocol (AMQP)
An open-source standard for business messaging communications.
Glossary Directory of IoT Terms
Advanced Driver Assistance
Main features include message orientation, queuing, routing,
reliability, security.
Advanced Metering
Infrastructure
Advanced Mobile Phone
System (AMPS)
Amazon Web Services
(AWS)
Architecture for automated, two-way communications between a
smart utility meter with an IP address and a utility company.
An analog cellular mobile system using FDMA. Analog AMPS has
been supplanted by digital.
The name given to a collection of remote computing services,
offered by Amazon.com, that combine to make a cloud
computing platform.
Anomaly Detection
Statistical technique that determines the patterns that are normal
and then identifies items that do not conform to those patterns.
Unlike simple classification where classes are known in advance, in
anomaly detection, the users don’t know what they are looking for
in the data.
Application Programming
Interface (API)
A collection of commands and protocols used to interact with an
operating system, device, or software component. In IoT, an API lets
the developer access the functionality of a device or sensors.
Application Software
Programs that enable specific end-user actions. The software uses
the given potential provided by computers to form an application.
Arduino
A single-board micro-controller used for prototyping without having
to deal with breadboards or soldering. Software is free and
open source.
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Attention commands are used to set data connections. The set
of short string commands allow developers to set up calls with a
modem, as well as perform far more complex tasks.
Audio Profile
Hardware profile used with Bluetooth applications that include
custom AT commands and functionality dedicated to wireless
streaming of audio. Examples include A2DP, which allows for
Glossary Directory of IoT Terms
AT Commands
streaming of audio to devices such as speakers, where an audio
gateway profile allows for two-way audio communications used in
devices such as headsets.
Augmented Entity
A physical entity is represented by a virtual entity on the digital
level. An augmented entity combines the two and stands for any
combination of the two entities.
B
Band
A range of frequencies used by a technology for communications
purposes. For example, the 2.4 GHz band is used for Wi-Fi and
Bluetooth communications.
Bandwidth
In signal processing, the measure of the width of a range of
frequencies.
Base Station
The radios and other equipment at the cell sites that are used to
communicate with cellular devices.
Beacons
Low-cost devices that communicate with smartphone apps indoors.
Beacons use Bluetooth and are key enablers for the smart retail
category, triggering messages as consumers pass through locations
or near products.
Big Data
Data sets so large that they cannot be used with traditional
database tools. Big Data often requires massively parallel
computing resources to access, curate, and analyze.
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Short-range wireless technology standard that operates on the 2.4
GHz band. Bluetooth can be used for sending both data and audio.
Bluetooth devices can be set up with different hardware profiles to
help perform specific tasks, such as with an audio adapter, an audio
headset, or keyboard profiles.
Bluetooth LE
Bluetooth Low Energy (also known as Bluetooth 4.0). Offers lower
Glossary Directory of IoT Terms
Bluetooth
power usage for devices.
Body Area Network (BAN)
A wireless network of wearable computing devices and sensors,
which may be embedded inside the body. A BAN also may be
called a WBAN, as in wireless body area network. Key use case is
for healthcare applications.
Bring Your Own Device
(BYOD)
Enterprise term recognizing that people are bringing their own
Wi-Fi-enabled devices into the corporate network.
Broadband
A high-speed, always-on data communications channel.
Brownfeild
Describes the problem and the process of having to consider
already existing systems when implementing new
software systems.
Business Logic
Describes the processes that are necessary to enable or execute
communication between an end user and a database or server.
These processes describe how data is transmitted, transformed,
or calculated.
C
CAN Bus
A message-based, multi-master serial protocol for transmitting
and receiving vehicle data within a CAN. The CAN Bus connects
multiple Electronic Control Units (ECUs), also known as nodes.
Initially designed for automotive, the CAN Bus can be adapted to
aerospace, commercial vehicles, industrial automation, and
medical equipment.
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Cellular Modem
A company that provides telecommunications services.
Allows a device to access the Internet using cellular mobile
networks. Devices can be configured to remotely connect to a
server or device to enable off-site access and data collection.
Cellular Router
Glossary Directory of IoT Terms
Carrier
Allows connected devices to access servers and other devices
by making an IP connection through the cellular mobile network.
Routers allow for multiple devices to be connected and controlled,
while offering extra device and data transfer security.
Chief IoT Officer (CIoT)
The CIoT coordinates the integration of IoT into the enterprise.
Successful CIoTs will break down silos between disciplines, such as
big data, data analytics, security, communications protocols, etc.
Class 1 Bluetooth
Offers a greater wireless data transfer distance (more than 100m,
up to 1km) with greater power consumption (100mW).
Class 2 Bluetooth
Short-range wireless data transmission (10-20m), which has low
power consumption of about 2.5mW.
Cloud
Cloud computing is an information technology paradigm that enables
ubiquitous access to shared pools of configurable system resources
and higher-level services that can be provisioned rapidly with
minimal management effort, via the internet. Cloud computing relies
on sharing of resources to achieve coherence and economy of scale.
Cloud Communications
Communication services provided by third parties that can be
accessed and used through the internet.
Cloud Computing
An approach where information technology capacities (such as
storage or applications) are separated from the individual computer
and are supplied through the internet at the user’s demand. The
“as-a-Service” moniker is sometimes used for cloud computing
services, such as Software-as-a-Service, Platform-as-a-Service,
and Infrastructure-as-a-Service. The backend for many IoT devices
may be delivered via the cloud.
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Access (CDMA)
Communications method used by many cell phone companies.
CDMA is an example of multiple access, where several transmitters
can send information simultaneously over a single communication
channel. This allows several users to share a band of frequencies
(see bandwidth). To permit this without interference between users,
CDMA employs spread spectrum technology and a special coding
scheme (where each transmitter is assigned a code).
Communication Model
Glossary Directory of IoT Terms
Code Division Multiple
Communication models try to capture, explain, simplify, and then
model communication. One of the oldest and most famous models,
the Shannon and Weaver Model, was created in 1949.
Companion Device
In wearables, a companion device requires a parent device, such as
a smartphone, to fully operate. The opposite would be a standalone
device that can do everything on its own.
Connected Healthcare
Connected health encompasses all advancements in the medical
industry that relate to IoT communication and remote sensing.
Connected Home
A connected home is networked to enable the interconnection and
interoperability of multiple devices, services, and apps, ranging
from communications and entertainment to healthcare, security,
and home automation. These services and apps are delivered over
multiple interlinked and integrated devices, sensors, tools, and
platforms. Related to Smart Home.
Constrained Application
Protocol (CoAP)
Controller Area Network
(CAN)
This software protocol is used in small electronics devices and
serves as the data encoding protocol between those devices.
A controller area network (CAN) is a serial bus network of
microcontrollers that connects devices, sensors, and actuators
in a system or sub-system for real-time control applications. In
automobiles, a CAN connects Electronic Control Units (ECUs) using
a multi-master serial bus (the CAN bus) to control actuators or
receive feedback from sensors. ECUs can be sub-systems, such
as airbags, transmission, antilock brakes, or engine control. The
standard consists of ISO 11898-1 and ISO 11898-2.
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A network of nodes that collectively monitors, senses, and controls
or enables control of an environment for a specific purpose. A home
appliance network is a one example of a control network.
D
Dashboard
Glossary Directory of IoT Terms
Control Network
A user interface that presents key data in a summarized form, often
as graphs or other widgets. Derived from the classic automobile
dashboard, the design of the interface depends on what data needs
to be monitored or measured.
Data Center
A collective term for the physical site, network elements, systems,
etc. that supports computing and network services.
Data Lake
A data lake is a massive data repository, designed to hold raw data
until it is needed and to retain data attributes so as not to preclude
any future uses or analysis. The data lake is stored on relatively
inexpensive hardware, and Hadoop can be used to manage the
data, replacing OLAP as a means to answer specific questions.
Sometimes referred to as an “enterprise data hub,” the data lake and
its retention of native formats sits in contrast to the traditional data
warehouse concept.
Degrees of Freedom (DoF)
A concept used in MEMS to describe the directions in which an
object can move and the number of independent variables in a
dynamic system.
De-identification
The stripping away of personally identifiable information from data
prior to its use. The process must include the removal of both direct
identifiers (name, email address, etc.) and the proper handling of
quasi-identifiers (sex, marital status, profession, postal code, etc.).
Demand Response
Demand response can reduce electrical price volatility during peak
demand periods and help avoid system emergencies.
Device Attack
An exploit that takes advantage of a vulnerable device to gain
network access.
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Distributed Generation (DG)
Metal rail used for mounting electrical equipment and racks
Decentralized, modular, and flexible power generation located close
to the serviced loads. Distributed micro-grids can control smaller
areas of demand with distributed generation and storage capacity.
DNP3 Protocol
Glossary Directory of IoT Terms
DIN Rail
An open, standards-based protocol for the electric utility industry
with interoperability between substation computers, remote
terminal units, intelligent electronic devices, and master stations.
Groups of enabled things are organized into namespaces.
Domain Model
A model that contains all areas and terms related to a certain field
of interest. It includes attributes, relations, constrains, acts, etc., that
are relevant for a certain task.
Downlink (DL or D/L)
The process of downloading data onto an end node from a server
/ target address. In a cellular network, this would be seen as data
being sent from a cellular base station to a mobile handset.
E
eHealth
Telemedicine, telehealth. Related to mHealth. Medical processes
and applications through information and computer technologies.
Electronic Control Unit (ECU)
Also known as a node, an Electronic Control Unit is a device, such
as a sensor or actuator, that is connected to other devices via a
CAN Bus. A vehicle can contain dozens of ECUs for functions
such as mirror adjustment, window power, airbags, cruise control,
entertainment, and, most significantly, engine control. To form a
CAN, two or more ECUs are needed.
Electronic Serial Number
(ESN)
Electrostatic Discharge (ESD)
Unique identification numeral for mobile devices in CDMA.
Replaced by the MEID.
This sudden flow of electricity can occur if two electrical objects,
with different electrical charges, come in contact with each other.
The difference in charge often is due to friction. Sometimes, the
short process is accompanied by sparks, as can be seen with
lightning. ESD can lead to severe damage to electrical devices.
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The flash memory chip that stores specialized software running in
a chip in an embedded device to control its functions. (Firmware =
software for hardware.)
Embedded System Security
The reduction of vulnerabilities and protection against threats in
software running on embedded devices.
Energy-Harvesting
Technologies
Glossary Directory of IoT Terms
Embedded Firmware
Technologies that use small amounts of energy from close proximity
to power small wireless devices. Applications can be found in
wireless sensor networks or wearable tech. Energy sources include
sun, wind, or kinetic energy.
Enhanced Data Rates for
GSM Evolution (EDGE)
An enhancement made to 2G GSM networks to improve data
transfer speeds and provide downlink speeds of up to 1 Mbit/s
and uplink speeds of up to 400 Kbit/s. It builds on available GSM or
GPRS standards and is integrated easily into existing networks.
Enhanced Voice Data Only
Enhanced Voice Data Only (or Enhanced Voice Data Optimized).
(EV-DO)
EPCglobal
Joint venture set up to achieve worldwide adoption and
standardization of Electronic Product Code (EPC) technology.
EtherCAT
A fieldbus system that allows for real-time Ethernet. It helps to
achieve short data update times, accurate synchronization, and
low hardware costs, so it can be used specifically for automated
or control systems. (CAT stands for Controller and
Automation Technology.)
European Article Number
Used to mark and identify products. Since 2009, it also is called
(EAN)
Global Trade Item Number (GTIN). The number usually is found
beneath barcodes and consists of up to 13 digits (EAN 13 barcode).
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Fachnormenausschuss
This is a type of SMB connector used in the automotive industry for
Kraftfahrzeugindustrie
connecting coaxial RF connectors.
(FAKRA)
Fast Data
Glossary Directory of IoT Terms
F
This is the application of Big Data analytics to smaller data sets in near
real time or in real time to solve a problem or create business value.
Firmware
Programming that is written to the read-only memory (ROM)
of a computing device. Firmware, which is added at the time of
manufacturing, is used to run user programs on the device.
Firmware Over-the-Air
(FOTA)
The process of updating an operating system and software over
the network, rather than having the consumer come into a service
center for updates.
Fitness Band
Activity tracker worn on the wrist, with sensors specifically related
to exercise and activity measuring. In contrast to a smartwatch that
may include fitness / activity tracking features, a fitness band is
dedicated to fitness.
Fleet Management
A broad term referencing a range of solutions for vehicle-related
applications. A fleet management solution typically is a vehiclebased system that incorporates data logging, satellite positioning,
and data communication to a back-office application.
Fog Computing
A distributed computing infrastructure in which some application
services are handled at the network edge in a smart device and some
application services are handled in a remote data center—in the cloud.
Form Factor
The physical size, pin-out, and configuration of a component. A
family range of modules, for example, may include 2G, 3G, and 4G
variants to allow PCB designers to design in one module but allow
for future upgrades through the product family’s road map.
Frequency Division Multiple
Access (FDMA)
The division of the frequency band allocated for wireless cellular
telephone communication into channels, each of which can carry a
voice conversation or digital data.
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Gateway
A link between two computer systems or programs, which allows
them to share information with each other. The router for your home
internet is one type of gateway.
Gateway GPRS Support
Node (GGSN)
Glossary Directory of IoT Terms
G
A main component of a GPRS network that supports the
networking between the GPRS network and external packetswitched networks. See also SGSN.
General Packet Radio Service
(GPRS)
A wireless communications standard on 2G and 3G cellular
networks, which supports a number of bandwidths and provides
theoretical data rates of 56-114 kbps. As cellular companies move
to more advanced networks, GPRS networks may be more costeffective for IoT networks.
Geofence
A virtual border applied to a physical space. For example,
geofencing might be defined around a nursery, and when a
mobile device crosses the nursery boundary, an alert is generated.
Geofences may be dynamically created and, in a telematics
application, can encompass entire neighborhoods or cities.
Geographic Information
System (GIS)
The combination of hardware, software, and data that captures,
manages, analyzes, and presents many kinds of geographic data.
GIS and location intelligence applications can be the foundation for
location-enabled services.
Global Navigation Satellite
System (GNSS)
Global Positioning System
(GPS)
General term for the multiple constellations of satellite
navigation systems.
A U.S. system of satellites and radio transmissions that is used to
locate GPS‐enabled hardware anywhere on the planet, with a very
high degree of accuracy.
Global System for Mobile
Communication (GSM)
The most widely used digital cellular network and the basis for
mobile communications, such as phone calls and short message
services (SMS).
Greenfield
In contradiction to brownfield, a greenfield project is one where no
consideration of previous systems is needed.
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Hadoop
A Java-based distributed programming framework for processing
large data sets. An application can be broken down into numerous
small parts, called fragments or blocks, that can be run on any node
in the cluster. Hadoop is part of the Apache Project, sponsored by
the Apache Software Foundation.
Hadoop Distributed File
System (HDFS)
Glossary Directory of IoT Terms
H
The primary distributed storage used by Hadoop applications.
A HDFS cluster has a NameNode that manages the file system
metadata and DataNodes to store the actual data.
Handoff
The transfer of a wireless call in progress from one transmission site
to another site without disconnection.
Haptic Technology or Haptics
Haptic technology (Haptics or touch feedback) applies tactile
sensations to human interactions with machines. The simplest
example is the actuator that vibrates a cell phone, but more
advanced haptics can detect the pressure applied to a sensor,
affecting the response.
Heating, Ventilation, and Air
Conditioning (HVAC)
Heterogeneous Network
(HetNet)
High-Speed Downlink Packet
Access (HSDPA)
High-Speed Packet Access
(HSPA)
These systems cover both vehicular and indoor building
comfort control.
Small cell networks using both macro and small cells. HetNets allow
mobile operators to better utilize their data networks’ capacity.
Increases the capacity of UMTS / 3G bandwidth to allow for faster
download speeds for connected devices.
An improvement made to data speeds over 3G technology through
the addition of two new protocols; HSDPA and HSUPA. It offers
potential downlink speeds of 14 Mbit/s and downlink of 5.76 Mbit/s.
High-Speed Uplink Packet
Access (HSUPA)
An improvement made to UMTS to enable faster uploading of data
from devices.
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The automation of certain activities within a household. This can
include automated control of lights, doors, and air conditioning,
for example.
Home Energy Management
(HEM)
Home Energy Management refers to technology that helps
homeowners improve home energy efficiency while also giving
them access to household products, such as tablets, smartphones,
Glossary Directory of IoT Terms
Home Automation
and computers.
Home Energy Management
Systems (HEMS)
Any hardware and / or software system that can monitor and
provide feedback about a home’s energy usage and / or enable
advanced control of energy-using systems and devices in the home.
Home Location Register
(HLR)
Host
Main database of permanent subscriber information for
a mobile network.
Computers that provide (or host) certain services or resources
within a network that other participants within the network can
then access and use. Hosts are the hardware basis for servers,
as servers are run on hosts. Often, hosts are the central point in a
company’s data processing process.
Hybrid Cloud
A mix of public and private cloud. The distribution of services
through private or public channels is decided upon by the users.
I
iBeacon
A technology introduced by Apple that uses sensors to locate iOS
or Android devices indoors and can send them notifications via
Bluetooth Low Energy (BLE). This also can be used in stores or
museums to give further information about nearby items.
Identifier
Also just ID, this marks objects for clear identification. Identifiers
usually are letters, words, symbols, or numbers that can be used to
create a code that reveals a definite identity after it is decoded.
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Recognizable attributes that are linked to an object, a person, etc.
Those attributes expose the entity and allow for clear identification.
If two things have the exact same attributes, they usually have the
same identity, and they can’t be distinguished from each other.
Industrial Control System
Computer hardware and software that monitor and control
(ICS)
industrial processes that exist in the physical world, where
Glossary Directory of IoT Terms
Identity
operator-driven supervisory commands can be pushed to remote
station devices. Industries such as electrical, water, oil, and gas are
typical ICS users.
Industrial Internet of Things
(IIoT)
A sub-discipline of IoT, encompassing connected large-scale
machinery and industrial systems, such as factory-floor monitoring,
HVAC, smart lighting, and security. Equipment can send real-time
information to an application so operators can better understand
how efficiently that equipment is running. Also referred to as
Industrial IoT.
Industrial, Scientific, and
Medical (ISM) Bands
An unlicensed part of the RF spectrum used for general purpose
data communications. In the U.S., the ISM bands are 915 MHz,
2.4 GHz, and 5.5 GHz, whereas 2.4 GHz is the global unlicensed
frequency, which has increasing amounts of interference.
Industrie 4.0
Invoking a fourth Industrial Revolution, Industrie 4.0 creates
intelligent manufacturing networks where decentralized smart
factories can communicate and react to each other autonomously.
The term, also known as Industry 4.0, was first used at the
Hannover Messe in 2011.
Industry 4.0
Industry 4.0 is a project introduced by the federal government
of Germany and refers to the fourth Industrial Revolution. It is a
strategy which aims to make better use of current and future ITcapacities in traditional industries.
Inertial Measurement Unit
(IMU)
A MEMS module that measures angular velocity and linear
acceleration using an accelerometer triad and an angular rate
sensor triad. Other IMU sensors may include magnetometers and
pressure sensors.
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Communication Technologies
(ICT)
The ICT industry provides access to information through
telecommunications. The communications technologies can
be items, such as the internet, VOIP, wireless networks,
or mobile phones.
Infrastructure as a Service
(IaaS)
An on-demand business model for IT capacities. Instead of owning
IT-infrastructure or server space, you rent and pay for it on a per-
Glossary Directory of IoT Terms
Information and
use basis. Those capacities usually are owned, maintained, and
provided by a cloud service.
Insurance Telematics
Vehicular tracking devices used by automobile insurance companies
to alter rates based on driver behavior. Tracks a multitude of driver
/ driving related items, including hard braking, mileage, speed, hard
turns, and much more.
Intelligent Device
Any type of equipment, instrument, or machine that has its own
computing capability. As computing technology becomes more
advanced and less expensive, it can be built into an increasing
diversity of devices. The list of uses includes personal and handheld
computers, cars, medical instruments, geological equipment, home
appliances, and more.
Intelligent Multimedia
Systems (IMS)
Intelligent Transportation
System (ITS)
Fundamental tools in the retrieval and dissemination of data, as well
as to enable face-to-face interaction across different geographies.
An application of advanced information and communications
technology for surface transportation enabling enhanced safety and
mobility while reducing environmental impacts.
Inter-Integrated Circuit (I2C)
I2C, pronounced I-squared-C, is a serial bus that provides
communication between sensors and microcontrollers, such
as the Arduino.
International Mobile
Equipment Identifier (IMEI)
The unique number used in GSM to identify mobile devices on
individual operator networks—conceptually similar to the MEID
in CDMA.
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Subscriber Identifier (IMSI)
International
Telecommunications Union
The unique number used in GSM, CDMA, and LTE to identify SIM
cards on their individual operator networks.
A specialized agency of the United Nations responsible for issues
concerning information and communication technologies.
(ITU)
Internet of Everything (IoE)
Glossary Directory of IoT Terms
International Mobile
The IoE amasses the technologies found in M2M and the IoT and
expands them with an even greater accumulation of data and
inferences. IoE is defined as a networked connection of four key
elements, including: People (social networks, health and fitness
sensors, and more); Things (physical sensors, measuring devices,
actuators, and other items generating or receiving data); Processes
(leveraging connectivity among data, things, and people to add
value, as in the use of smart fitness devices and social networks to
advertise healthcare offerings to prospective customers); and Data
(raw data analyzed and processed into useful information to enable
intelligent decisions and control mechanisms).
Internet of Things (IoT)
The Internet of Things moves beyond the scope of M2M,
encompassing and surpassing it in functionality by adding devices
and electronic equipment with embedding sensors, control systems,
and processors that enable communication across a multi-node,
open network of objects. The IoT includes any object, outfitted
with sensors, that has the ability to gather and transfer data
over a network.
Internet Protocol Security
(IPSEC)
A set of protocols that provide authentication and encryption to
Internet Protocol (IP) packets, adding an extra layer of security on IP
communications.
Interoperability
The ability of two or more systems or components to work together
and exchange and use information effectively.
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Systems integrated into automobiles that deliver both
entertainment and information content. Typical IVI applications
include managing audio, listening to or sending SMS, making
voice calls, navigating, and using rear-seat entertainment, as well
as interfacing with smartphone-enabled content, such as traffic
conditions, sports scores, and weather forecasts.
IoT Privacy
Glossary Directory of IoT Terms
In-Vehicle Infotainment (IVI)
Internet of Things privacy. The special considerations required to
protect the data of individuals from exposure in an IoT environment,
where almost any physical or logical entity or object can be given a
unique identifier and the ability to communicate autonomously over
the internet or similar IP network.
IoT Security
Internet of Things security. The area concerned with safeguarding
connected devices and networks in the Internet of Things.
IP Devices
All devices within a network that are labeled with an IP address.
IPv6
IP addresses serve to identify devices on the internet. IPv6 is the
newest internet address format, which provides more addresses
than the IPv4 address format.
IPv6 Address
A 128-bit alphanumeric string that identifies an endpoint device in
the Internet Protocol Version 6 (IPv6) addressing scheme.
IRIDIUM
A satellite communication constellation that provides global voice
and data coverage through its satellite network, operating on the
1618.85 to 1626.5 MHz frequencies.
J
JavaScript Object Notation
(JSON)
Used as a lightweight alternative to XML for organizing data, JSON
is text-based and human-readable. The format uses “name : object”
pairs to organize the data.
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Layer 2 Tunneling Protocol
(L2TP)
A tunneling protocol used to support virtual private networks
(VPNs) or as part of the delivery of services by ISPs. It does not
provide any encryption or confidentiality by itself, relying on
an encryption protocol that it passes within the tunnel to
provide privacy.
Light-Emitting Diode (LED)
Glossary Directory of IoT Terms
L
A semiconductor that generates light via electroluminescence.
Infrared LEDs can be used for the remote control units for many
consumer electronics.
Link Budget
An accounting of all of the losses in a wireless communication
system. In order to “close the link,” enough RF energy has to make it
from the transmitter to the receiver.
Local Area Network (LAN)
A network of devices in relatively close proximity. The two most
common communications technologies used in LANs are Ethernet
and Wi-Fi.
Long-Term Evolution
(LTE) / 4G
LTE, often referred to as 4G, is a cellular network type offering
superior data transfer speeds than its predecessor, 3G. It is part of
the GSM upgrade path. Portable devices now can access data at
high broadband speeds through LTE.
LoRa
LoRa is a proprietary, chirp spread spectrum radio modulation
technology for LPWAN. LoRa uses license-free sub-gigahertz radio
frequency bands (such as 169 MHz, 433 MHz, 868 MHz (Europe)
and 915 MHz (North America).
LoRa Alliance
The LoRa Alliance is an open, non-profit organization dedicated to
promoting the interoperability and standardization of low-power
wide area network (LPWAN) technologies to drive implementation
of the IoT. LPWANs enable IIoT, civic, and commercial applications.
LPWANs have lower costs and power requirements and longer
range than mobile networks. Those advantages mean they can
enable a much wider range of IoT applications, which have been
constrained by budgets and power issues.
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LoRaWAN is a media access control layer protocol for managing
communication between LPWAN gateways and end-node
devices, maintained by the LoRa Alliance. LoRaWAN defines
the communication protocol and system architecture for the
network while the LoRa physical layer enables the long-range
communication link.
Low-Power Wide Area
(LPWA)
Glossary Directory of IoT Terms
LoRaWAN
LPWA networks are designed for IoT applications that have low
data transmission rates, need long battery lives, can provide
low-cost services, sometimes operate in remote or hard to reach
locations (underground or geographically dispersed), and be
easy to deploy across basically every business sector, including
manufacturing, automotive, energy, utilities, agriculture, healthcare,
wearables (for humans or animals), or transport.
Low-Power Wireless Sensor
Network
A group of spatially distributed, independent devices that collect
data by measuring physical or environmental conditions with
minimal power usage.
M
Machine Authentication
The authorization of an automated human-to-machine or machineto-machine communication through verification of a digital
certificate or digital credentials. Unlike user authentication, the
process does not involve any action on the part of a human.
Machine Data
Also known as machine-generated data, this is digital information
created by the activity of computers, mobile phones, embedded
systems, and other networked devices.
Machine-to-Machine (M2M)
A term describing technology that allows for one connected device
to communicate and exchange information with another connected
device or sensor—without the assistance of a human.
MapReduce
A parallel processing model for handling extremely large data sets.
First, a map process runs to reduce a data set to key value pairs (in
sequence), and then a second reduce process combines those pairs
into a smaller set of tuples (ordered lists).
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The “layer 2” in a network that allows the physical medium (radio
waves or wire signals) to be organized to pass data back and
forth. For low-rate data wireless applications, the MAC has many
implications on performance.
Mesh Networking or Mesh
Network Topology
An ad hoc, local area network infrastructure where nodes
communicate directly with each other without the need to pass
Glossary Directory of IoT Terms
Media Access Control (MAC)
through a central structure, such as an ISP. The only way to shut
down a mesh network is to eliminate every node. Their adaptability
makes them ideal for IoT applications.
Message Broker
A middleware program that translates a message from the
messaging protocol of the sender into the messaging protocol of
the receiver. This makes it much easier for two applications
to communicate.
Message-Oriented
Middleware that allows for synchronous, as well as asynchronous
Middleware (MOM)
(queue), messaging between distributed systems.
Message Queuing Telemetry
Transport (MQTT)
mHealth or Mobile Health
An open, lightweight IoT communications protocol for the transfer
of telemetry messages.
This is the practice of medicine using mobile devices,
particularly physiological sensors. Sensors may be enabled to
communicate with a user’s mobile phone in a Body Area Network
(BAN) configuration.
MicroController Unit (MCU)
A full computer on a single chip. The chip contains a CPU, a clock,
non-volatile memory for the program (ROM or flash), volatile
memory for input and output (RAM), and an I/O control unit.
Micro-Electro-Mechanical
Systems (MEMS)
Miniaturized mechanical and electro-mechanical elements,
typically used for measurements, such as accelerometers and
gyroscopes. Systems-on-a-chip technology is used to embed
mechanical devices, such as fluid sensors, mirrors, actuators,
pressure and temperature sensors, and vibration sensors, on to
semiconductor chips.
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(MDN)
Mobile Equipment Identifier
(MEID)
Mobile Network Operator
(MNO)
Mobile Station (MS)
Mobile Station International
Subscriber Directory Number
The number a user would dial to reach a specific mobile phone.
Used in CDMA—conceptually similar to the MSISDN in GSM.
Unique identification numeral for mobile devices used in CDMA—
conceptually similar to the IMEI in GSM and LTE..
Glossary Directory of IoT Terms
Mobile Directory Number
Companies that operate traditional mobile
communications networks.
A cellular radio handset or cellular IoT device.
The telephone number to the SIM card in a mobile phone. Used in
GSM—conceptually similar to the MDN in CDMA.
(MSISDN)
Mobile Switching Center
(MSC)
The center of a network switching subsystem, associated with
communications switching functions, routing SMS messages, and
interfacing with other networks.
Mobile Virtual Network
Operator (MVNO)
Modbus
A wireless communications provider that leases the infrastructure
over which it provides services.
A communication protocol mainly used to connect electronic
devices. The Modbus Master (for example, a computer) requests
information from the Modbus Slaves (for example, electronic
thermometers). Up to 247 Slaves can transmit data to one Master.
Multimedia Messaging
Service (MMS)
A feature of mobile devices that allows transmission of images,
video, or audio in addition to short text messages via standardized
communications protocols. See Short Messaging Service (SMS).
Multiple-Input and MultipleOutput (MIMO)
A radio technology using multiple antennas at both the transmitter
and receiver to improve communication performance.
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Narrowband-IoT
(NB-IoT)
Narrowband-IoT is a LPWAN radio technology standard developed
to enable a wide range of devices and services to be connected
using cellular telecommunications bands. NB-IoT focuses
specifically on indoor coverage, low cost, long battery life, and
enabling a large number of connected devices.
Near Field Communications
(NFC)
Glossary Directory of IoT Terms
N
Short-range wireless communication between devices, used
in applications such as contactless mobile payments, transport
ticketing, and phone-as-key.
O
On-Board Equipment (OBE)
Components of a Vehicle-to-Infrastructure (V2I) implementation
located in a moving vehicle, communicating wirelessly with
roadside equipment. OBE applications may interface with other
vehicle systems via a CAN Bus.
Open Source
Software where the source code is available and can be modified
and freely redistributed. Open source is the opposite of closed,
proprietary systems.
Open VPN
Open-source software application that implements virtual private
network (VPN) techniques for creating secure point-to-point or siteto-site connections in routed or bridged configurations and remote
access facilities.
Operational Technology
As opposed to Information Technology (IT), this refers to
technologies associated with control and automation.
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Part 90 Licenses
Small parts of the RF spectrum that are made available in small
areas to businesses for data or voice communications. Many smart
grid providers use Part 90 licenses for wireless data.
Passive Sensor
Glossary Directory of IoT Terms
P
A device that detects and responds to input from
physical environments.
Penetration Testing, Pen
A method of evaluating the security of a network or system from
Testing, or Pentest
internal or external threats. This is part of a full security audit and
typically exploits a combination of weaknesses to gain access and
then evaluates the capability of the network’s defenders to detect
and respond to the penetration.
Personal Area Network
(PAN)
Interconnected devices operating in the range of a single person,
typically 10 meters. PANS are (mostly or exclusively) wireless, making
the term basically indistinguishable from Wireless PANs (WPAN).
Personal Emergency
Response System (PERS)
A mobile duress panic alarm component of a monitoring system,
typically for the residential market. Modern PERS devices go
beyond their origins as a mere push button to include MEMS
and various other sensors.
Pervasive Computing
Physical Web
Another term for ubiquitous computing.
Google’s open standard to allow IoT devices to communicate via
web addresses. By using HTTP, users can walk up and access
any smart device (such as parking meters and vending machines)
without the overhead of dedicated mobile apps.
Platform as a Service (PaaS)
Platform as a Service is a category of cloud computing services
that provides a platform allowing customers to develop, run,
and manage applications without the complexity of building and
maintaining the infrastructure typically associated with developing
and launching an app.
Point-to-Point Tunneling
A method for implementing virtual private networks (VPNs).
Protocol (PPTP)
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(PDU)
A physical device with multiple outlets that connects electrical
power to recipient devices. PDUs can be simple, such as a mounted
power strip, or more complex by having power filtering, UPS, load
balancing, or intelligent monitoring incorporated in the device.
Power over Ethernet (PoE)
The capability to deliver enough power to operate a device over
an Ethernet connection. PoE is useful in certain low-voltage
Glossary Directory of IoT Terms
Power Distribution Unit
applications, such as passive IP cameras.
Preboot Execution
The ability to manage power over a network connection.
Environment (PXE)
A PXE-enabled device can be shut down or restarted via
a network connection.
Preferred Roaming List (PRL)
A database (especially in a CDMA-based wireless device) that tells
how to find and connect to locally available wireless network(s). The
function of the PRL is most important when a device is outside its
home network and must seek out an alternate network.
Printed Circuit Board (PCB)
Mechanically supports and electrically connects electronic and
electrical components using conductive tracks, pads, and other
features etched from one or more sheet layers of copper laminated
onto or between sheet layers of a non-conductive substrate.
Private Cloud
Information technology services supplied via the cloud but only
within a single organization, for example, one company.
Public Cloud
Information technology services supplied via a cloud that are public
and made available for everyone.
Python
A widely used open-source programming language that can
be implemented in variety of ways, including in embedded
applications. There is a large library base that can be used by
Python applications, helping to minimize coding while speeding up
development time.
Python Script Interpreter
A tool that lets you run Python code, something that now is being
embedded directly into devices, such as cellular modules.
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Quality of Service (QoS)
Different services that regulate data transfer priorities to identify
and control the quality with which a service can be accessed by
users. This is especially important if a certain quality (for example,
bandwidth) has to be guaranteed to ensure the functionality
of a service.
Glossary Directory of IoT Terms
Q
R
Radio Fingerprinting
An electronic process that identifies each individual wireless
handset by examining its unique radio transmission characteristics.
Radio Frequency (RF)
Radio waves. This term generally means “wireless communication”
when referred to in IoT discussions.
Radio Frequency
Identification (RFID)
Generally speaking, this is the use of strong radio waves to “excite”
enough current in a small tag to send a radio transmission back.
Random Phase Multiple
Random Phase Multiple Access LPWAN technology was designed
Access (RPMA)
from the bottom up to optimize wide area connectivity for IoT devices.
Raspberry Pi
Raspberry Pi is a series of small, single-board computers developed
in the UK by the Raspberry Pi Foundation to promote the teaching
of basic computer science in schools and in developing countries.
The original model became far more popular than anticipated,
selling outside its target market for uses such as robotics.
Remote Authentication
Dial-In User Service
(RADIUS)
Remote Monitoring
and Control
A type of server responsible for receiving user connection requests,
authenticating the user, and returning all configuration information
necessary for the client to deliver service.
The increasingly automated monitoring and control of devices,
technologies, or processes. Wireless devices that send information
gathered directly to control centers often are used to achieve this.
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The use of various technologies to make observations and
measurements at a target that usually is at a distance or on a scale
beyond those observable to the naked eye.
Representational State
Transfer (REST)
An architecture for web standards, especially for the HTTP protocol.
It simplifies design of network applications compared to, for
example, SOAP.
RESTful Web Services
Glossary Directory of IoT Terms
Remote Sensing
Web services that are realized within the REST architecture are
called RESTful Web Services.
RF Sensitivity
The minimum magnitude of input signal you need based on a
specified signal-to-noise ratio to achieve a minimum error rate.
RFID Tagging
A system using small radio frequency identification devices for
tracking purposes. An RFID tagging system includes the tag itself,
a read / write device, and a host application for data collection,
processing, and transmission.
Roaming
Using a wireless device in an area outside its home coverage area.
S
Sensor
A device used to measure a specific characteristic of the
surrounding environment, such as temperature. The use of sensors
and actuators to connect things to the physical world is a key
component of IoT.
Sensor Analytics
Statistical analysis of data that is created by wired or
wireless sensors.
Sensor Hub
A technology that connects sensor data and then processes
the data. This way, the hub does part of a processor’s
data-processing job.
Serial Port Profile (SPP)
A hardware profile used with Bluetooth applications that includes
custom AT commands and functionality dedicated to wireless data
connections and serial cable replacement.
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A MEMS concept referring to the detection of sudden impacts at a
predetermined level. Typical applications include shut-off sensing,
condition monitoring, and tap detection for data entry.
Short Message Service
Center (SMSC)
Short Message Service (SMS)
The network element in a mobile telephone network that stores,
forwards, converts, and delivers SMS messages.
Glossary Directory of IoT Terms
Shock Sensing
A feature of mobile devices that allows transmission of short text
messages via standardized communications protocols.
Sigfox
A low-bandwidth, proprietary, wireless protocol that offers excellent
range and obstacle penetration for short messages, giving a new
low-powered and cost-effective wireless transmission transport for
IoT technologies.
Simple (or Streaming) Text
A protocol designed for working with message-oriented
Oriented Message Protocol
middleware, similar to HTTP. It allows clients to communicate with
(STOMP)
Simple Object Access
Protocol (SOAP)
Single Board Computer
(SBC)
most of the message brokers, making it language agnostic.
A protocol specification for exchanging structured information in the
implementation of web services in computer networks.
A complete, functioning computer with all functions (I/O, processor,
memory) located on one board. Popularized by the Raspberry
Pi system, SBCs are constructed in direct contrast to traditional
motherboards with plug-in cards for functions such as graphics
and Ethernet.
Smart Buildings
Buildings that try to minimize costs and environmental impact.
This is achieved by connected systems and efficient use of energy
through new, automated technology that intelligently responds
to certain aspects (available solar energy, temperature inside the
building, etc.).
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An automobile that uses technology to support the driver and
create a safer traffic environment. Different systems (inside and
outside of car) are connected and communicate with each other
to allow intelligent intervention in dangerous situations. Additional
functionality includes (but not limited to) full stack telematics, as
well as comprehensive global device, connectivity, and
services delivery.
Smart Cities
Glossary Directory of IoT Terms
Smart Car
Smart cities are defined by more intelligent city infrastructure
using modern information and communication technologies. Smart
cities propose a more flexible adaptation to certain circumstances,
more efficient use of resources, higher quality of life, more fluid
transportation, and more. This is achieved via networking and
integrated data exchange between humans and things.
Smart Grid
A term referring to the application of networking capabilities and
computer systems to the electric grid. For example, a smart grid
would include smart meters at the point of delivery, allowing for
real-time monitoring of usage and the adjustment of power settings
on some appliances.
Smart Home
The networking of household devices and systems through
information and communication technology. This way, processes
within a home can be monitored and controlled automatically to
optimize quality of life, costs, security, and environmental impact.
Related to Connected Home.
Smart Label
A type of identification tag that contains more advanced
technologies than conventional barcode data. Some common types
of smart labels are QR codes, Electronic Article Surveillance (EAS)
tags, and RFID tags.
Smart Meter
An electronic device that measures and displays resource
consumption (of water, gas, electricity, etc.) and communicates this
information to the resource distributors and managers (such as
utilities and municipalities) and even to consumers. This allows for a
more efficient distribution, usage, pricing, and control of resources.
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A subscription-based model where a monthly fee is charged for
using software, rather than an upfront purchase. SaaS and cloud
computing can give cash-strapped enterprises and startups access
to applications that might otherwise be too expensive to purchase
outright.
Software-Defined Network
(SDN)
Standards Development
Organization (SDO)
An approach to networking that decouples control of information
Glossary Directory of IoT Terms
Software as a Service (SaaS)
flow from the hardware and gives it to a software controller.
An organization whose primary activities are developing,
coordinating, revising, amending, interpreting, or otherwise
producing technical standards.
Structure Attenuation
The loss in intensity of radio waves through a medium (like radio
waves through a brick wall).
Subscriber Identity Module
(SIM)
A piece of hardware (the “smart card”) containing account
information for a user on a cellular network. The SIM is inserted into
a SIM holder in cellular devices.
Supervisory Control and Data
Acquisition (SCADA)
An industrial control system typically used for geographically
dispersed assets, often scattered over large distances. SCADA is
applied to electrical utilities to monitor substations, transformers,
and other electrical assets.
System on a Chip (SoC)
A single integrated-circuit technology that contains all the
necessary circuits and parts for a complete system. A single
microchip in a wearable device, for example, could contain an
analog-to-digital converter, memory, logic control, I/O, etc.
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Telematics
An IT concept regarding the long-distance transmission of data.
In vehicles on the move, telematics refers to the integrated use of
telecommunications and informatics, such as dashboard screens
that show the vehicle’s current position on a map or in centralized
tracking applications. Telematics is an interdisciplinary field that
Glossary Directory of IoT Terms
T
can encompass telecommunications, vehicular technologies,
road transportation, road safety, electrical engineering (sensors,
instrumentation, wireless communications, etc.), and computer
science (multimedia, internet, etc.).
Terrestrial Trunked Radio
(TETRA)
This operates as a two-way transceiver and is used by emergency
services, as well as on transport, such as rail and marine vessels.
It operates on low frequencies split over four channels (ranging
between 380 and 400 MHz for emergency services and higher
for civilian use). The use of low frequencies allows for far greater
transmission distances but lower data transfer rates.
Thread
A simplified IPv6-based mesh networking protocol geared to the
smart home sector. Developed on low-cost 802.15.4 chipsets,
Thread is designed for extremely low-power consumption.
Time Division Multiple
A channel access method for shared medium networks.
Access (TDMA)
Transceiver
Short for transmitter-receiver. A transceiver both transmits and
receives analog or digital signals. It normally is built into a network
interface card.
Transmission Control Protocol /
Core standard protocol for IP network communications.
Internet Protocol (TCP / IP)
Transponder
A wireless communications device that picks up and automatically
responds to an incoming signal. The term is a combination of the
words transmitter and responder. Transponders can be either
passive or active.
TV Whitespace
A new FCC program that makes unused TV station bands available
for temporary and controlled use in a small geographic area.
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Ubiquitous Computing
The concept of embedding microprocessors in everyday things so
they can communicate information continuously. Ubiquitous devices
are expected to be connected constantly. Utility smart meters are an
example of ubiquitous computing, replacing manual meter readers
with devices that can report usage and modify power settings on
Glossary Directory of IoT Terms
U
machines, panels, etc.
Uniform Resource Identifier
(URI)
The unique identifier makes content addressable on the
internet by uniquely targeting items, such as text, video, images,
and applications.
Uniform Resource Locator
A particular type of URI that targets web pages so that when a
(URL)
browser requests them, they can be found and served to users.
Universal Asynchronous
A microchip controlling a computer’s interface to serial devices.
Receiver / Transmitter
(UART)
Universal Authentication
It converts the bytes it receives from the computer along parallel
circuits into a serial bit stream.
A network identity verification method that allows users to move
from site to site securely without having to enter identifying
information multiple times.
Universal Mobile
Telecommunications System
Also referred to as 3G cellular technology, this is the third iteration
of the GSM. It achieves improved data transfer speeds over 2G.
(UMTS)
Uplink (UL or U/L)
This is the process of sending data from your device / computer to a
server or target address. In a cellular network, this would be seen as
data sent from a mobile handset to a cellular base station.
Usage-Based Insurance (UBI)
UBI bases insurance rates on pre-defined variables, including
distance, driving behavior, time, and place.
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Vehicle-to-Infrastructure
(V2I)
Vehicle-to-Vehicle (V2V)
The communication of smart cars and commercial vehicles with
surrounding sensors.
V2V systems allow vehicles to communicate with each other.
Networks of vehicles can help avoid congestion, find better routes,
Glossary Directory of IoT Terms
V
and aid law enforcement.
Vehicle-to-Vehicle
The wireless transmission of data between motor vehicles.
Communication
(V2V Communication)
Vibration Sensing
A MEMS concept referring to the detection of periodic acceleration
and deceleration. Typical applications include structural health
monitoring, acoustic event triggering, and seismic equipment.
Virtual Private Network
(VPN)
A secure system for users to send and receive data across shared
or public networks. This is accomplished through encryption or
protocols that act as if the user’s devices were connected directly to
the private network.
Virtual Sensor
Virtual sensors gather information that would not be measurable by
a single device. This way, they can attain information that can’t be
measured directly.
Visited Location Register
(VLR)
The database containing information about a subscriber’s roaming
within a mobile switching center’s location area.
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Wearable Technology
Technologies or computers integrated into articles of clothing or
accessories that can be worn. Often, the wearable tech is used to
quantify a physical process (such as heartbeat monitoring) or to
augment human capabilities. Because of the impracticality of wires
to transmit sensor data, wearables are almost universally wireless,
Glossary Directory of IoT Terms
W
using a variety of communication protocols, such as BLE.
Wide Area Network (WAN)
A telecommunications network or computer network that extends
over a large geographical distance.
Wireless Application Protocol
(WAP)
A protocol for wireless devices allowing the user to view and
interact with data services. Often used to support internet access
and Web browsing on mobile phones.
Wireless Fidelity (Wi-Fi)
A common form of local area network that operates on the 2.4 GHz
band. Its popularity has led to a wide variety of devices to become
Wi-Fi enabled, including smartphones, cameras, vehicles, and
household appliances.
Z
ZigBee
Small-range wireless networking protocol that operates primarily on
the 2.4 GHz frequency spectrum. ZigBee devices connect in a mesh
topology, forwarding messages from controlling nodes to slaves,
which repeat commands to other connected nodes. Due to its low
power consumption and low data rate, ZigBee has been used in
applications such as traffic management, wireless light switches,
and industrial device monitoring.
Z-Wave
Wireless communication technology used in security systems,
businesses, and home automation.
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ABOUT THE AUTHOR
Syed Zaeem Hosain | Chief Technical Officer
Mr. Hosain is responsible for the architecture and future direction of Aeris’ networks
and technology strategy. He joined Aeris in 1996 as Vice President, Engineering and is a
member of the founding executive team of Aeris. Mr. Hosain has more than 38 years of
experience in the semiconductor, computer, and telecommunications industries,
including product development, architecture design, and technical management.
Prior to joining Aeris, he held senior engineering and management positions at Analog
Devices, Cypress Semiconductor, CAD National, and ESS Technology. Mr. Hosain is
Chairman of the International Forum on ANSI‐41 Standards Technology (IFAST) and
Chairman of the IoT M2M Council (IMC). He holds a Bachelor of Science degree in
Computer Science and Engineering from the Massachusetts Institute of Technology,
Cambridge, MA.
ABOUT AERIS
Aeris is a global technology partner with a proven history of helping companies unlock the value of IoT. For more
than a decade, we’ve powered critical projects for some of the most demanding customers of IoT services. Aeris
strives to fundamentally improve businesses by dramatically reducing costs, accelerating time-to-market, and
enabling new revenue streams. Built from the ground up for IoT and road tested at scale, Aeris IoT Services are
based on the broadest technology stack in the industry, spanning connectivity up to vertical solutions. As
veterans of the industry, we know that implementing an IoT solution can be complex, and we pride ourselves
on making it simpler.