Centre for Data Science

This paper proposes a self-organizing, cluster based protocol-Multi-path, Multi-hop Hierarchical Routing (MuMHR) -for use in large scale, distributed Wireless Sensor Networks (WSN). With MuMHR, robustness is achieved by each node learning multiple paths and election of cluster-head backup node(s). Energy expenditure is reduced by shortening the distance between the node and its cluster-head and by reducing the setup communication overhead. This is done through incorporating the number-of-hops metric in addition to the back-off waiting time. Simulation results show that MuMHR performs better than LEACH, which is the most promising hierarchical routing algorithm to date; MuMHR reduces the total number of set-up messages by up to 65% and enhances the data delivery ratio by up to 0.83.

A computer model has been developed for analysing the deposition of inhaled electro-aerosols in human airways. The effect of electrostatic charges on the total aerosol deposition efficiency in the human respiratory tract has been investigated. Based on measured data, a computer prediction can be made of the site of deposition in human airways.

Wireless sensor networks typically gather data at a number of locations. However, it is desirable to be able to design applications and reason about the data in more abstract forms than points of data. This paper examines one way in which this can be done.

This paper describes Trove a physical game implemented on a wireless sensor network (WSN). Architecturally, the WSN is a decentralized system, exhibiting local node processing and information extraction, collaborative inter-node behaviour and local decision making capabilities. From the perspective of the players, Trove is a multi-player, real time, physical game. The user-centered narrative, configuration and game play of Trove are presented as well as its design and implementation.

The paper presents a thought experiment as to the feasibility of using large scale wireless sensor networks as a vehicle for high level scientific investigation. The discussion is framed by a demanding scenario, that of planetary exploration, and the assessment of feasibility is driven by the available micromachining technologies and recent advances in the areas of ad-hoc networking, communications and intelligent sensing. Following discussion on the development of the mission, the next question addressed is if and how MEMS and VLSI technologies could be integrated to provide a self-contained space probe, 40mm in length. A sensor payload is proposed, which includes means of seismic, chemical, temperature and visual exploration. The power and communications systems are also discussed, based on the needs of a mission profile which provides no special 'base station' nodes on the planet's surface, requiring each sensor package to be capable of information extraction, in-network collaboration and communication with an orbiting satellite. The outcome of the thought experiment described is a positive assertion of feasibility for the sensor node hardware, given current levels of MEMS and VLSI technologies. With respect to the wireless ad-hoc networking aspects of the proposed deployment, pointers are given to the issues which are still necessitating research work, mainly from the computer sciences community

Transducers represent a key component of medical instrumentation systems. In this paper, sensors that perform the task of measuring the physical quantity of acceleration are discussed. These sensors are of special significance since, by integrating their output signal, accelerometers can additionally provide a measure of velocity and position. Applications for such measurements and, thus, of accelerometers, range from early diagnosis procedures for tremor-related diseases (e.g., Parkinson's) to monitoring daily patterns of patient activity using telemetry systems. The system-level requirements in such applications are considered and two novel neural-network transducer designs developed by the authors are presented, which aim to satisfy such requirements. Both designs are based on a micromachined sensing element with capacitive signal pickoff. The first is an open-loop design utilizing a direct-inverse-control strategy, while the second is a closed-loop design, where electrostatic actuation is used as a form of feedback. Both transducers are nonlinearly compensated, capable of self-test, and provide digital outputs.

The paper develops a terminology to describe sensors which have been enhanced in some way by the integration of some additional processing circuitry. Several terms, current in the literature, including 'smart sensors' and 'intelligent sensors' are discussed and the 'cogent' sensor is introduced. This is followed by a brief review of existing and potential applications of Artificial Intelligence (AI) to microsystems, in terms of technology integration, device level performance enhancement and system level added functionality.

It is difficult to present new, complex ideas in ways that are informative and interesting in situations where a vast amount of information has to be delivered and understood quickly. Given short attention spans, boredom thresholds and limited capacity to assimilate new information, it is essential to use an effective conveyor of the message, which presents the content in a clear and unambiguous manner whilst helping the receiver to remain alert and focused and integrate the information with existing knowledge. This paper introduces a collaboration between computer scientists and artists to develop an effective, animation based information communication tool, in the form of an application scenario, to be used for communicating to students (and wider audiences) dry technical aspects of Pervasive Computing.

In enclosed suits, such as those worn by explosive ordnance disposal (EOD) experts, evaporative cooling through perspiration is less effective and, particularly in hot environments, uncompensable heat stress (UHS) may occur. Although some suits have cooling systems, their effectiveness during missions is dependent on the operative's posture. In order to properly assess thermal state, temperature-based assessment systems need to take posture into account. This paper builds on previous work for instrumenting EOD suits with regard to temperature monitoring and proposes to also monitor operative posture with MEMS accelerometers. Posture is a key factor in predicting how body temperature will change and is therefore important in providing local or remote warning of the onset of UHS. In this work, the C4.5 decision tree algorithm is used to produce an on-line classifier that can differentiate between nine key postures from current acceleration readings. Additional features that summarize how acceleration is changing over time are used to improve average classification accuracy to around 97.2%. Without such temporal feature extraction, dynamic postures are difficult to classify accurately. Experimental results show that training over a variety of subjects, and in particular, mixing gender, improves results on unseen subjects. The main advantages of the on-line posture classification system described here are that it is accurate, does not require integration of acceleration over time, and is computationally lightweight, allowing it to be easily supported on wearable microprocessors.

Greater availability and affordability of wireless technology has led to an increase in the number of wireless sensor network(WSN) applications where sense data is collected at a central user point, commonly outside (geographically and topologically) the network, for processing. Resource constraints on nodes in the network coupled with considerable redundancy in the data generated mean that applications have to be developed with an eye to maximising energy efficiency in order to extend network life. In-network computation, and in particular in-network information extraction from data, has been promoted as a technique for achieving this aim. In-network processing, however, has been limited to systems where at most, simple aggregate queries are evaluated, the results of which are communicated to the outside world. There is currently little research into how the idea of in-network processing can be extended and implemented to allow more complex queries to be resolved within the network. This paper examines key applicative query-based approaches that utilise in-network processing for query resolution, identifies their strengths and limitations and puts forward ideas for facilitating innetwork complex query processing in WSNs. Finally, preliminary results of experiments, where in-network attribute-based logical abstractions are used for processing complex queries, are presented.

Bomb disposal manned missions are inherently safetycritical. Wireless Sensor Network (WSN) technology potentially offers an opportunity to increase the safety of the operatives involved in such missions through detailed physiological parameters monitoring and fusion of "health" information.

The fundamental aim of monitoring is to identify abnormalities in the observed phenomena and allow inference of the likely cause. Faced with the common problems of spatially irregular sensor distribution and intermittent sensor measurement availability, key to fulfilling the monitoring aim is filling in the spatio-temporal gaps in the data. Whilst Wireless Sensor Networks (WSN) technology, combined with MEMS availability potentially offer sensing solutions for a variety of application domains, in the context of monitoring applications a conceptual shift is needed from currently available, point-measurement based "sense-and-send" systems towards the provision of phenomena field representations, in real-time, enabling effective visualisation of the spatio-temporal patterns.

Cancer prognostic prediction requires a classification system that is robust to the interaction and uncertainty of input factors, as well as being interpretable on the decision made. In this paper, a hybrid neuro-fuzzy classifier is applied to determine the long-term outcome of patients with bilharziasisrelated bladder cancer. The same data set is also analysed by a Multi-Layer Percepton Neural Network (MLPNN) and logistic regression, which are both widely used in the area of medical decision-making. In order to better assess the value of this neuro-fuzzy classifier, a benchmark data set used in this area of oncology, the Wisconsin Breast Cancer Data (WBCD), is examined by the above three methods. The study demonstrates that the hybrid neuro-fuzzy classifier is efficient in cancer data analysis and it yields a high classification rate of 97.1% for WBCD, and 84.9% for the bladder cancer data, respectively.

Finding solutions for the current period of climate change or “global warming” is possibly the most serious and pressing challenge faced by scientists and the wider community today. Although governments are beginning to act, a community wide approach is needed with a large proportion of individuals engaging to reduce energy consumption that depends on fossil fuels. The Passive House (or Passivhaus) standard is an ultra-low energy standard for building construction and design that aims at dramatically reducing energy consumption in the home. While appropriate for new builds, this standard may be difficult to achieve with existing buildings. In this work, Wireless Sensor Network (WSN) technology is examined as an enabling tool to support rapid progression to improved energy efficiency and increased comfort for existing buildings. As with participatory urban sensing, the home occupant could, in the future, take on the role of scientist; developing an awareness of trouble spots in the house would allow them to target problems thus reducing the need for heating and improving comfort. The paper reports on experiences and findings from several residential and commercial environmental monitoring WSN deployments using a WSN developed from off the shelf components. The sensors deployed measure temperature, relative humidity, CO2 concentration and light. Depending on the size and layout of the space to be monitored, added to the scope of deployment, between 12 and 20 nodes were deployed and the monitoring period was 7-14 days per location. The paper illustrates the value of using WSN technologies as enablers for the amateur eco-home scientist on the path towards reduced energy consumption and increased comfort. It evaluates the suitability of the system for both commercial and residential deployments and shows how large quantities of data can be reduced to meaningful high level information delivered to the user.

The development of MEMS devices has generally followed a bottom up methodology, reaching now a stage where the capabilities of the devices could be used much more effectively in systems designed from the top down to include them. A holistic view of the requirements of MEMS based systems and the capabilities of the microdevices must be taken if such systems are to deliver the promise that was expected. This paper presents an overview of the integrative perspective required for workers in all areas of the field, to enable them to appreciate the system level design issues leading to breakthrough cogent sensing applications.

Artificial intelligence techniques have found a number of applications in hypermedia, mostly in two specific areas, user interface, particularly adaptive ones and information search and retrieval. There have been fewer cases of application of these techniques to aid the authoring process. This paper studies the applicability of some AI techniques to the authoring process, in particular, helping designers understand and control the structure of a presentation.

During manned bomb disposal missions, the combination of the protective suit's weight (37kg), physical activity, high ambient temperatures, and restricted airflow can cause the operative's temperature to rise to dangerous levels during missions, impairing their physical and mental ability. This work proposes to use Body Sensor Networks (BSNs) to increase the safety of operatives in such missions through detailed physiological monitoring, fusion of health information, and remote alerts. Previous trials conducted by the authors have shown no correlation between the suit wearer's temperature at any single skin site and their core temperature, nor between single point temperature variations and subjective thermal sensation. This paper reports on the development of a wearable, wireless, networked sensing system suitable for integration within the suit and deployment in manned missions. A sensor fusion and modelling approach is proposed that estimates the overall thermal sensation of the suit wearer, in real-time, based on the multipoint temperature data. Zhang's thermal sensation model was used in this work. Modelling is performed locally to enable cooling system actuation, provide local feedback, and accommodate application specific constraints. Experimentation with the prototype confirms the importance of: multi-site skin measurement; timely cooling actuation; and monitoring the operative's thermal state. Evaluation of Zhang's model highlights the need for a bespoke model to account for suit and mission specific factors. The deployed BSN has been evaluated through experimental trials using a number of subjects in mission-like conditions and has been shown to be appropriate for the target application.

Centre as an applicative query language specifically designed to address the particular constraints imposed by sensor networks. A parser for the language and its formal specification were seen as an essential first step in being able to issue correct, purposeful queries to the network. A simple specification model that could be incrementally refined through to implementation was considered essential in accomplishing this goal. The purpose of this paper, therefore, is two-fold. First, to report the motivation for the formal specification of the ASQue parser, and second, to describe the construction of the parser from specification to implementation using the B-method.

The sciences often find it difficult to present complex ideas to audiences in ways that are informative and interesting. This is problematic, when the public needs to enter into a debate about new ideas, during conferences when vast amounts of information on diverse subjects are presented in a very short time, and in lectures when experts present fundamental principles to novices. Given our relatively short attention spans, boredom thresholds and limited capacity to assimilate new information, it is essential that the medium is an effective conveyor of the message, and in itself helps the receiver to remain alert and focused whilst also presenting information in a clear and unambiguous manner. The development of a new area of research, cogent computing, provided an opportunity to produce an effective, animation-based information communication tool, in the form of an application scenario, to be used for communicating to students, wider audiences and the design and development team itself, technical aspects of pervasive computing.