Localization in WSN

— L'intérêt pour les réseaux de capteurs sans fil s'est considérablement accru. Ils ont fait l'objet de plusieurs travaux de recherche ces dernières années. Néanmoins, ces réseaux sont confrontés à de multiples problèmes. Parmi ces problèmes nous trouvons celui de la localisation. Ce dernier, a reçu une attention importante car plusieurs applications ont besoin de l'information de localisation des capteurs. Ainsi, de nombreux systèmes et algorithmes de localisation ont été proposés pour ce type de réseaux. Dans ce papier nous avons effectué une étude comparative entre les deux protocoles de localisation AT-Free et HT-Refine. Nous avons évalué les performances et discuter les résultats obtenus par simulation.

Construction progress monitoring has been perceived as one of the key factors that prompt the achievement of a construction project. However, assessing the progress is time consuming, costly and obliges specialized personnel to reduce disagreements and approximate the actual performance to the original plan as close as possible. Image processing is a promising method that has been developed for automated monitoring of construction projects. It has attracted increasing attention for progress monitoring, quality assurance and work space analyses. Nonetheless, remarkable drawbacks still remain in image processing, particularly for outdoor environment such as construction progress monitoring. The principle downside of image processing goes back to the image resolution. Ambient lightning condition significantly affects the image quality which does affect the accuracy of data, extracted from related images. Much research strives to reduce the level of errors for data extraction but so far none has been able to deliver complete satisfactory and reliable result. In this research a novel approach based on thermal image analysis is presented. The new method consists of three phases: First, collecting the thermal and original images by utilizing Infrared-Camera. Second, estimating the position of captured images by the use of wireless sensor network implemented in the work space. Finally, the 3D plan will be updated automatically in the Building Information Modeling (BIM) software. The preliminary experimental results from an actual concrete building construction site show the feasibility of inferring the actual state of progress by the use of thermal images to overcome the limitation of vision monitoring. 

AUTOMATED CONSTRUCTION PROGRESS MONITORING USING THERMAL IMAGES AND WIRELESS SENSOR NETWORKS. Available from: https://www.researchgate.net/publication/275024236_AUTOMATED_CONSTRUCTION_PROGRESS_MONITORING_USING_THERMAL_IMAGES_AND_WIRELESS_SENSOR_NETWORKS#share [accessed Sep 11, 2015].

We will design a system based on WSNs and IoT technologies to manage real-time power at buildings. This system comprises of: a wireless sensor network (sensing node and base station) and a smart home gateway. A sensing node is utilized wireless sensors to measure voltage and current; to calculate power consumption of connected appliances, transmitted wirelessly to a base station via Zigbee node. A base station is designed to receive all data transmitted from the sensing node and display it through GUI available at the personal computer, with the possibility of controlling ON and OFF appliances according to consumer requirements; All of these readings will be stored at database for analysis. In addition, a smart home gateway will connect the system with internet to allow consumers to continuous monitoring and remote control the appliances via a smartphone application. The benefit of this system, that the appliances control mechanism can be done in different ways (manually, automatically, and remotely). Various household appliances were tested to verify the accuracy of the electrical parameters that measured at system and compare them with practical measurement, found the average error ratio between them (0.3%) was in voltage, (1.5%) in current, and (1.8%) in power.

Wireless sensor networks (WSNs) have boomed in this last decade. They are involved in all aspects of our daily lives and make it easier. Despite the great strides in these networks, several problems arose and are remained open. The localization of sensor networks nodes is one of the most challenging problem that has attracted many researches. Consequently, a lot of work has been carried out to provide accurate location information of sensors and sensing field. In this paper, we present a taxonomy of the most important localization technologies proposed for WSNs. We survey different published localization algorithms in the literature while giving an up-to-date with the most recent schemes. Then we highlight their characteristics and describe metrics used for their classification. A complete comparison will be given and also directions of future research will be discussed.

A wireless sensor network comprises of small sensor nodes each of which consists of a processing device, small amount of memory, battery and radio transceiver for communication. The sensor nodes are autonomous and spatially distributed in an area of investigation. Certain applications and protocols of wireless sensor networks require that the sensor nodes should be aware of their position relative to the sensor network. For it to be significant and to be of value, the data such as temperature, humidity and pressure, gathered by sensor nodes must be ascribed to the relative position from where it was collected. For this to happen, the sensor nodes must be aware of their relative positions. Traditional location finding solutions, such as Global Positioning System, are not feasible for wireless sensor nodes due to multiple reasons. Therefore, new methods, techniques and algorithms need to be developed to solve the problem of location and position estimation of wireless sensor nodes. A number of algorithms and techniques based upon different characteristics and properties of sensor nodes have already been proposed for this purpose. This chapter discusses the basic principles and techniques used in the localization algorithms, categories of these algorithms and also takes a more closer look at a few of the representative localization schemes.

In the recent years, there has been a huge advancement in wireless sensor computing technology. Today, wireless sensor network (WSN) has become a key technology for different types of smart environment. Nodes localization in WSN has arisen as a very challenging problem in the research community. Most of the applications for WSN are not useful without a priory known nodes positions. Adding GPS receivers to each node is an expensive solution and inapplicable for indoor environments. In this paper, we implemented and evaluated an algorithm based on multidimensional scaling (MDS) technique for three-dimensional (3D) nodes localization in WSN using improved heuristic method for distance calculation. Using extensive simulations we investigated our approach regarding various network parameters. We compared the results from the simulations with other approaches for 3D-WSN localization and showed that our approach outperforms other techniques in terms of accuracy.

It is often useful to know the location of nodes in wireless sensor network, but GPS enabled sensor nodes can be expensive. In this paper, we studied and analyzed Senelex (Sensor Network Localization Explorer). We have explored the self-localization performance for arbitrary sensor network based on Cramer-Rao bound. This Paper presents the analysis of range based schemes on the basis of few network parameters (Network Size, Anchor node Density, Array node density) with the metric Standard Deviation of localization error. Lesser the deviation greater the accuracy, thus all the network parameters show their own characteristics.

WLAN has lately been applied to the problem of mobility tracking and behavior analysis. To further the development of the studies in this direction the positioning system that can perform on the network side with minimal human participation is needed. One of the current limitations is the requirement on the number of reference signal available. Thus, methods that require fewer reference signals for positioning are needed. This paper provides the comparison of WLAN based positioning methods that can operate with a single AP.

This research article seeks to propose a Hilbert-Huang transform (HHT) based novel feature extraction approach for the analysis of multi-channel EEG signals using its local time scale features. The applicability of this recently developed HHT based new features has been investigated in the analysis of multi-channel EEG signals for classifying a small set of non-motor cognitive task. HHT is combination of multivariate empirical mode decomposition (MEMD) and Hilbert transform (HT). At the first stage, multi-channel EEG signals (6 channels per trial per task per subject) corresponding to a small set of non-motor mental task were decomposed by using MEMD algorithm. This gives rise to adaptive i.e. data driven decomposition of the data into twelve mono component oscillatory modes known as intrinsic mode functions (IMFs) and one residue function. These generated intrinsic mode functions (IMFs) are multivariate i.e. mode aligned and narrowband. From the generated IMFs, most sensitive IMF has been chosen by analysing their power spectrum. Since IMFs are amplitude and frequency modulated, the chosen IMF has been analysed through their instantaneous amplitude (IA) and instantaneous frequency (IF) i.e. local features extracted by applying Hilbert transform on them. Finally, the discriminatory power of these local features has been investigated through statistical significance test using paired t-test. The analysis results clearly support the potential of these local features for classifying different cognitive task in EEG based Brain –Computer Interface (BCI) system. Keywords-Electroencephalogram (EEG) signal, Hilbert-Huang transforms (HHT), Multivariate Empirical Mode Decomposition (MEMD), Intrinsic Mode Functions (IMFs), Brain-Computer Interface (BCI)

Indoor object localization can enable many ubicomp applications, such as asset tracking and object-related activity recognition. Most location and tracking systems rely on either battery-powered devices which create cost and maintenance issues or cameras which have accuracy and privacy issues. This paper introduces a system that is able to detect the 3D position and motion of a battery-free RFID tag embedded with an ultrasound detector and an accelerometer. Combining tags' acceleration with location improves the system's power management and supports activity recognition. We characterize the system's localization performance in open space as well as implement it in a smart wet lab application. The system is used to track real-time location and motion of the tags in the wet lab as well as recognize pouring actions performed on the objects to which the tag is attached. The median localization accuracy is 7.6cm -(3.1, 5, 1.9)cm for each (x, y, z) axis -with max update rates of 15 Sample/s using single RFID reader antenna.

Many Wireless Sensor Networks (WSNs) applications are new and their requirements may not be fully anticipated during the sensor networks design and development stage. We are presenting a sensor network infrastructure that support motes' with remote hardware and software modification to match the target applications need. Using the proposed infrastructure in next-generation WSNs will produce flexible infrastructures that will provide over-the-air remote design modification even after the deployment of WSNs on the sensing field. In this paper, we are presenting the design concept and challenges of such infrastructure. Also, we present the use of the infrastructure in one possible environmental monitoring application such as forest fire. The development of such infrastructure will have an impact on advances the research on the real-time remote sensing, heterogeneous WSN, and WSNs applications.

Urban Vehicular Ad Hoc Network (UVANET) provides non-safety applications like media sharing, Internet service, file transfer, gaming, and so on. To provide better services to the users in UVANET, routing plays an important role. In this paper, a novel routing protocol is proposed for UVANET to support the non-safety applications. We have considered a non-safety application where the drivers and passengers of different parking lots can play multi-player games with each other. To play the games smoothly, the game data should reach the destination in a minimum time. Simulation results show that, when the density of the vehicles in the city area is high, then the proposed protocol fulfills the end-to-end delay tolerance of 100 ms. At last, an experimental work is performed to validate the proposed routing protocol by running a simple puzzle game in a UVANET prototype designed in an indoor laboratory environment and outdoor environment.

"This thesis addresses the use of radio-frequency identification (RFID) for three fundamental tasks in mobile robotics: mapping, self-localization, and trajectory estimation. These topics have widely been studied in recent years, because they are regarded as key ingredients to autonomous robots. In particular, we investigate the application of long-range passive RFID in the work at hand. This RFID standard is expected to play a major role in the automation of identification processes in industry and commerce.

We present solutions to the automated inventory of RFID-tagged goods, which we interpret as mapping the locations of RFID transponders. In order to quickly provide the required model of the detection behavior of the RFID reader on board the mobile robot, we devise a semi-autonomous learning method for probabilistic sensor models. Moreover, we compare different techniques to self-localize in an RFID-tagged environment. In the last part, we show how the trajectory of the robot can be estimated in previously unknown surroundings by tailoring approaches from the field of simultaneous localization and mapping (SLAM)."

We consider the problem of navigating a flying robot to a specific sensor node within a wireless sensor network. This target sensor node periodically sends out beacons. The robot is capable of sensing the received signal strength of each received beacon (RSSI measurements). Existing approaches for solving the sensor spotting problem with RSSI measurements do not deal with noisy channel conditions and/or heavily depend on additional hardware capabilities. In this work we reduce RSSI fluctuations due to noise by continuously sampling RSSI values and maintaining an exponential moving average (EMA). The EMA values enable us to detect significant decrease of the received signal strength. In this case it is reasoned that the robot is moving away from the sensor. We present two basic variants to decide a new moving direction when the robot moves away from the sensor. Our simulations show that our approaches outperform competing algorithms in terms of success rate and flight time. In field experiments with real hardware, a flying robocopter successfully and quickly landed near a sensor placed in an outdoor test environment. Traces show robustness to additional environmental factors not accounted for in our simulations.

The areas of positioning and tracking through Wireless Sensor Network (WSN) have received considerable attention recently driven by the requirement to obtain high positioning accuracy with minimum cost possible. A wide range of proposed approaches regarding the positioning area have emerged, however most of them suffer from either requiring an
extra sensor, high power consumption, inaccessible indoors, or offer high positioning error. This paper presents a research and development of an adaptive positioning system for ZigBee WSN based on the Received Signal Strength (RSS) system. The proposed system is an efficient positioning system in both indoors and outdoors, where it offers reasonable positioning accuracy (0.1 – 0.6) meters, and achieves low power consumption. The proposed system has been validated through a number of real experiments using XBee modules.

This paper presentsa new simple mobile tracking system based on IEEE802.11 wireless signal detection, which can be used for analyzingthe movement of pedestrian traffic. Wi-Fi packets emitted by Wi-Fi enabled smartphones are received at a monitoring station and these packets contain date, time, MAC address, and other information. The packets are received at a number of stations, distributed throughout the monitoring zone, which can measure the received signal strength. Based on the location of stations and data collected at the stations, the movement of pedestrian traffic can be analyzed. This information can be used to improve the services, such as better bus schedule time and better pavement design. In addition, this paper presents a signal strength based localization method.

Energy efficiency is an essential issue to be reckoned in wireless sensor networks development. Since the low-powered sensor nodes deplete their energy in transmitting the collected information, several strategies have been proposed to investigate the communication power consumption, in order to reduce the amount of transmitted data without affecting the information reliability. Lossy compression is a promising solution recently adapted to overcome the challenging energy consumption, by exploiting the data correlation and discarding the redundant information. In this paper, we propose a hybrid compression approach based on two dimensions specified as horizontal (HC) and vertical compression (VC), typically implemented in cluster-based routing architecture. The proposed scheme considers two key performance metrics, energy expenditure, and data accuracy to decide the adequate compression approach based on HC-VC or VC-HC configuration according to each WSN application requirement. Simulation results exhibit the performance of both proposed approaches in terms of extending the clustering network lifetime.

Abstract—In many wireless sensor network applications, such
as warning systems or healthcare services, it is necessary to
update the captured data with location information. A promising
solution for statically deployed sensors is to benefit from mobile
beacon-assisted localization. The main challenge is to design and
develop an optimum path planning mechanism for a mobile
beacon to decrease the required time for determining location,
increase the accuracy of the estimated position, and increase
the coverage. In this paper, we propose a novel superior path
planning mechanism called Z-curve. Our proposed trajectory can
successfully localize all deployed sensors with high precision and
the shortest required time for localization. We also introduce
critical metrics, including the ineffective position rate for further
evaluation of mobile beacon trajectories. In addition, we consider
an accurate and reliable channel model, which helps to provide
more realistic evaluation. Z-curve is compared with five existing
path planning schemes based on three different localization
techniques such as weighted centroid localization and trilateration
with time priority and accuracy priority. Furthermore,
the performance of the Z-curve is evaluated at the presence of
obstacles and Z-curve obstacle-handling trajectory is proposed to
mitigate the obstacle problem on localization. Simulation results
show the advantages of our proposed path planning scheme over
the existing schemes.

We present a distributed localization algorithm for wireless sensor networks. Each sensor estimates its position by iteratively solving a set of local spatially-constrained programs. The constraints allow sensors to update their positions simultaneously and collaboratively using range and position estimates to those neighbors within their communications range. Moreover, the algorithm has been designed for implementation with resource-limited devices. Since the exchange of information among sensors is a key component for this method, we introduce a stopping criterion to monitor the wireless transmissions for the whole network in order to significantly reduce energy consumption with minimal impact on localization accuracy. Experimental results show that we can determine the best trade-off between wireless transmissions and accuracy. The performance of the proposed scheme is very competitive when compared with similar and more computationally demanding schemes.

This research presents a distributed and formula-based bilateration algorithm that can be used to provide initial set of locations. In this scheme each node uses distance estimates to anchors to solve a set of circle-circle intersection (CCI) problems, solved through a purely geometric formulation. The resulting CCIs are processed to pick those that cluster together and then take the average to produce an initial node location.
The algorithm is compared in terms of accuracy and computational complexity with a Least-Squares localization algorithm, based on the Levenberg–Marquardt methodology.
Results in accuracy vs. computational performance show that the bilateration algorithm is competitive compared with well known optimized localization algorithms.

7
th International Conference on Information Technology Convergence and Services (ITCSS
2021) will provide an excellent International forum for sharing knowledge and results in theory,
methodology and applications of Information Technology Convergence and Services. The aim of
the conference is to provide a platform to the researchers and practitioners from both academia
as well as industry to meet and share cutting-edge development in the field.

In mobile Ad-Hoc networks, each node of the network must contribute in the process of communication and routing. However, this contribution can expose the network to several types of attackers. The security of mobile ad hoc networks is an open research topic and a major in terms of their vulnerability to various attacks, such as black hole, Sybil ... etc. In this article, we analyze the attack black hole (black hole) in ad hoc networks using as AODV routing protocol. In a black hole attack, a malicious node impersonates a legitimate node, manufactures forged responses with a number of high sequence and thus forces the victim node to select it as a relay. We are interested in a first time to study the impact of dishonest nodes on the network, and then we will simulate black hole attack using two simulator NS2 and OPNET.

In this paper, we investigate the actual performance of some of the best known localization algorithms when deployed in realworld indoor environments. Among the plethora of possible localization schemes, we focus on those based on radio signal strength measurements only, since they do not require extra circuitry that would result in higher cost and energy consumption. For a fair comparison, we have first gathered thousands of radio signal strength measurements in two different indoor environments. To estimate the channel model parameters and to compare the different localization algorithms these data have been used.

As Wireless Sensor Network (WSN) has become a key technology for different types of smart environment, nodes localization in WSN has arisen as a very challengin g problem in the research community. Most of the applications for WSNs necessitate a priory known nodes positions. In this paper, we propose an algorithm for three dimensional (3D) nod es localization in surface WSN based on multidimension al scaling (MDS) technique. Using extensive simulations, we in vestigated in details our approach regarding different network topologies, various network parameters and performance issues. The results from simulations show that our algorithm produces small localization error and outperforms MDS-MAP in terms of accuracy. Keywords-wireless sensor networks; multidimensional scaling; 3D surface localization; nodes positioning.

In recent years, indoor localization has become a hot research topic with some sophisticated solutions reaching accuracy on the order of ten centimeters. While certain classes of applications can justify the corresponding costs that come with these solutions, a wealth of applications have requirements that can be met at much lower cost by accepting lower accuracy. This paper explores one specific application for monitoring patients in a nursing home, showing that sufficient accuracy can be achieved with a carefully designed deployment of low-cost wireless sensor network nodes in combination with a simple RSSI-based localization technique. Notably our solution uses a single radio sample per period, a number that is much lower than similar approaches. This greatly eases the power burden of the nodes, resulting in a significant lifetime increase. This paper evaluates a concrete deployment from summer 2012 composed of fixed anchor motes throughout one floor of a nursing home and mobile units carried by patients. We show how two localization algorithms perform and demonstrate a clear improvement by following a set of simple guidelines to tune the anchor node placement. We show both quantitatively and qualitatively that the results meet the functional and non-functional system requirements.

"One of the major challenges in the area of wireless sensor networks is simultaneously reducing energy consumption and increasing network lifetime. Efficient routing algorithms have received considerable attention in previous studies for achieving the required efficiency, but these methods do not pay close attention to coverage, which is one of the most important Quality of Service parameters in wireless sensor networks. Suitable route selection for transferring information received from the environment to the sink plays crucial role in the network lifetime. The proposed method tries to select an efficient route for transferring the information. This paper reviews efficient routing algorithms for preserving k-coverage in a sensor network and then proposes an effective technique for preserving k-coverage and the reliability of data with logical fault tolerance. It is assumed that the network nodes are aware of their residual energy and that of their neighbors. Sensors are first categorized into two groups, coverage and communicative nodes, and some are then re-categorized as clustering and dynamic nodes. Simulation results show that the proposed method provides greater efficiency energy consumption.
"

The continuous tracking of mobile systems via active or passive RFID is a desirable but difficult to achieve objective. In this paper, we present our experimental results of positioning techniques using passive UHF RFID, Bluetooth, and WLAN. We thereby employ three orthogonal measuring techniques: detection rates, signal strength, and round trip time. The orthogonality of the methods is designed to achieve robustness to noise and unforeseen changes in the surroundings. Moreover, due to their different read ranges, the technologies can complement each other at different scales of the environment.

A Wireless Sensor Network (WSN) consists of many sensors that communicate wirelessly to monitor a physical region. Location information is critical essential and indispensable for many applications of WSNs. A promising solution for localizing statically deployed sensors is to benefit from mobile location-aware nodes called beacons. However, the essential problem is to find the optimum path that the mobile beacon should travel in order to improve localization accuracy, time and success as well as energy efficiency. In this paper, we evaluate the performance of five mobile beacon trajectories; Random Way Point, Scan, Hilbert, Circles and Localization algorithm with a Mobile Anchor node based on Trilateration (LMAT) based on three different localization techniques such as Weighted Centroid Localization and trilateration with time priority and accuracy priority. This evaluation aims to find effective and essential properties that the trajectory should have. Our simulations show that a random movement cannot guarantee the performance of localization. The results also show the efficiency of LMAT regarding accuracy, success and collinearity while the Hilbert space filling curve has lower energy consumption. Circles path planning can help to localize unknown sensors faster than others at the expense of lower localization precision.

Underwater Wireless Sensor Networks (UWSNs) provide new opportunities to observe and predict the behavior of aquatic environments. In some applications like target tracking or disaster prevention, sensed data is meaningless without location information. In this paper, we propose a novel 3D centralized, localization scheme for mobile underwater wireless sensor network, named Reverse Localization Scheme or RLS in short. RLS is an event-driven localization method triggered by detector sensors for launching localization process. RLS is suitable for surveillance applications that require very fast reactions to events and could report the location of the occurrence. In this method, mobile sensor nodes report the event toward the surface anchors as soon as they detect it. They do not require waiting to receive location information from anchors. Simulation results confirm that the proposed scheme improves the energy efficiency and reduces significantly localization response time with a proper level of accuracy in terms of mobility model of water currents. Major contributions of this method lie on reducing the numbers of message exchange for localization, saving the energy and decreasing the average localization response time.

In recent years, indoor localization has become a hot research topic with some sophisticated solutions reaching accuracy on the order of ten centimeters. While certain classes of applications can justify the corresponding costs that come with these solutions, a wealth of applications have requirements that can be met at much lower cost by accepting lower accuracy. This paper explores one specific application for monitoring patients in a nursing home, showing that sufficient accuracy can be achieved with a carefully designed deployment of low-cost wireless sensor network nodes in combination with a simple RSSI-based localization technique. Notably our solution uses a single radio sample per period, a number that is much lower than similar approaches. This greatly eases the power burden of the nodes, resulting in a significant lifetime increase. This paper evaluates a concrete deployment from summer 2012 composed of fixed anchor motes throughout one floor of a nursing home and mobile ...

Wireless Sensor Networks (WSNs) is a strong candidate for smart grid applications, such as advanced metering infrastructure, demand response management, dynamic pricing, load control, electricity fraud detection, fault diagnostics, substation monitoring and control as well as automation of various elements of the power grid. The realization of these applications directly depends on efficiency of communication facilities among power grid elements. However, the harsh power grid environmental conditions with obstacles, noise, interference, and fading pose great challenges to reliability of these facilities to monitor and control the power grid. The purpose of this paper is to evaluate performance of WSNs in different power grid environments such as 500 kv substations, main power control room, and underground network transformer vaults. The power grid environments are modeled using a log-normal shadowing path loss model channel with realistic parameters. The network is simulated and performance is evaluated using packet delivery ratio, communication delay, and energy consumption. The simulation results have revealed that different environments have considerable impacts on performance of WSNs which make it suitable for most applications that need low data rate with low reliability requirements.

In this paper, we present a novel technique for localization of caption text in video frames based on noise inconsistencies. Text is artificially added to the video after it has been captured and as such does not form
part of the original video graphics. Typically, the amount of noise level is uniform across the entire captured video frame, thus, artificially embedding or overlaying text on the video introduces yet another segment of noise level. Therefore detection of various noise levels in the video frame may signify
availability of overlaid text. Hence we exploited this property by detecting regions with various noise levels to localize overlaid text in video frames. Experimental results obtained shows a great improvement in line with overlaid text localization, where we have performed metric measure based on Recall, Precision and fmeasure.

Abstract A Wireless Sensor Network (WSN) consists of
many sensors that communicate wirelessly to monitor a
physical region. Location information is critical essential
and indispensable for many applications of WSNs. A
promising solution for localizing statically deployed sensors
is to benefit from mobile location-aware nodes called
beacons. However, the essential problem is to find the
optimum path that the mobile beacon should travel in order
to improve localization accuracy, time and success as well
as energy efficiency. In this paper, we evaluate the performance
of five mobile beacon trajectories; Random Way
Point, Scan, Hilbert, Circles and Localization algorithm
with a Mobile Anchor node based on Trilateration (LMAT)
based on three different localization techniques such as
Weighted Centroid Localization and trilateration with time
priority and accuracy priority. This evaluation aims to find
effective and essential properties that the trajectory should
have. Our simulations show that a random movement
cannot guarantee the performance of localization. The
results also show the efficiency of LMAT regarding
accuracy, success and collinearity while the Hilbert space
filling curve has lower energy consumption. Circles path planning can help to localize unknown sensors faster than
others at the expense of lower localization precision.

Wireless sensor nodes positions perform a crucial role in various sensor network applications. Localization of sensor node in WSN includes security problems such as node re-authentication and movement tracing. Various techniques have been proposed in recent times to solve the location problems of usual sensors but poor to support hostile and dynamic environments as their blueprints are only for the static environments. In this paper, we propose the disciplined node authentication and key exchange protocol that clean downs the overhead in node re-authentication and also assists untraceability of localized nodes. The proposed protocol will be the professional solution to increase the lifetime of sensor network.

This work focuses on the development of relatively simple, low cost, autonomous and feasible wireless sensor network and related embedded system combination to be integrated with AMATEUR UAV and unmanned ground vehicle (UGV) management system both at inter and intra level communication and networking for different modules and different vehicles. What we describe here is our progress in a ongoing live project. We also make fresh implementable proposals to integrate autonomous Amateur UAV and share plans to implement it for vehicle management system using intelligent communication and networked system approach. We envision the capability of modern sensing network where communication between different sensors and embedded system combination enable user to have a closer view over larger area and provide potent capability of acting autonomously.

Sensors, coupled with transceivers, have quickly evolved from technologies purely confined to laboratory test beds to workable solutions used across the globe. These mobile and connected devices form the nuts and bolts required to fulfill the vision of the so-called internet of things (IoT). This idea has evolved as a result of proliferation of electronic gadgets fitted with sensors and often being uniquely identifiable (possible with technological solutions such as the use of Radio Frequency Identifiers). While there is a growing need for comprehensive modeling paradigms as well as example case studies for the IoT, currently there is no standard methodology available for modeling such real-world complex IoT-based scenarios. Here, using a combination of complex networks-based and agent-based modeling approaches, ​we present a novel approach to modeling the IoT. Specifically, the proposed approach uses the Cognitive Agent-Based Computing (CABC) framework to simulate complex IoT netwo...

The number of anchor nodes required for accurate localization is an important problem in the wireless sensor network research community. The error associated with localization is high when anchor nodes are not optimally placed in the network. No matter how the network is set up, the error associated with localization is inevitable. There are various sources for these errors, one of which is the unavailability of anchor nodes. These conditions arise due to stumpy deployment density or poor signal propagation owing to factors like multipath effects, fading effects and poor visibility. This paper proposes a method of determining the minimum number of anchor nodes required for a given sensor (smart energy meter) network dimension using triangulation as the localization process. The proposed method uses the sensitivity of the sensor nodes and various environmental conditions. Using the sensitivity of the sensor nodes and the environmental conditions, the minimum number of anchor nodes for a network dimension was determined through simulation. The minimum number of anchors required for a network with clear line of sight, suburban , residential and non-line of sight environments was achieved with this method.

Wireless Sensor Networks have highly scattered, self-organized nodes that can detect, compute, and transmit the information collected at different nodes in the network. These nodes spread over a specific topographical zone. They enhance the instantaneous formation of the network. Knowing the current location of a node is a crucial and cardinal requirement for any application promulgated in WSN. Once the locations of the sensor nodes can be precisely positioned, there are ample of probabilities for the data transmission of the network to be excelling inefficiency. Location responsiveness enables essential network features such as coverage, routing, deployment, topology control, clustering, boundary discovery, target tracking, rescue, and other location services. Hence, WSN localization has become a breath and backbone arena that ostentatiously attracted significant research interest. Our work traces a compilation of all the dynamic research in sensor networks on localization techniqu...

Wireless Sensor Networks have highly scattered, self-organized nodes that can detect, compute, and transmit the information collected at different nodes in the network. These nodes spread over a specific topographical zone. They enhance the instantaneous formation of the network. Knowing the current location of a node is a crucial and cardinal requirement for any application promulgated in WSN. Once the locations of the sensor nodes can be precisely positioned, there are ample of probabilities for the data transmission of the network to be excelling inefficiency. Location responsiveness enables essential network features such as coverage, routing, deployment, topology control, clustering, boundary discovery, target tracking, rescue, and other location services. Hence, WSN localization has become a breath and backbone arena that ostentatiously attracted significant research interest. Our work traces a compilation of all the dynamic research in sensor networks on localization techniques and emanates eminent understanding of it.