Study of Multi-Classification of Advanced Daily Life Activities on SHIMMER Sensor Dataset

Today the field of wireless sensors have the dominance in almost every person’s daily life. Therefore researchers are exasperating to make these sensors more dynamic, accurate and high performance computational devices as well as small in size, and also in the application area of these small sensors. The wearable sensors are the one type which are used to acquire a person’s behavioral characteristics. The applications of wearable sensors are healthcare, entertainment, fitness, security and military etc. Human activity recognition (HAR) is the one example, where data received from wearable sensors are further processed to identify the activities executed by the individuals. The HAR system can be used in fall detection, fall prevention and also in posture recognition. The recognition of activities is further divided into two categories, the un-supervised learning and the supervised learning. In this paper we first discussed some existing wearable sensors based HAR systems, then briefly described some classifiers (supervised learning) and then the methodology of how we applied the multiple classification techniques using a benchmark data set of the shimmer sensors placed on human body, to recognize the human activity. Our results shows that the methods are exceptionally accurate and efficient in comparison with other classification methods. We also compare the results and analyzed the accuracy of different classifiers

A Novel Protocol For Barrier K-Coverage In Wireless Sensor Networks

One of major problems in the wireless sensor networks is the barrier coverage problem. This problem deals with the ability to minimizing the probability of undetected penetration through the barrier (sensor network). The reliability and fault tolerance problems are very important for long strip barrier coverage sensor networks. Also, another design challenge in sensor networks is to save limited energy resources to prolong the lifetime of wireless sensor network. In this paper we propose the fault tolerant k-barrier coverage protocol, called APBC. The proposed protocol maintains a good balance in using nodes energy, in order to prolong the network lifetime. The proposed protocol presents a proper way to provide the k-barrier coverage at nodes fails without reexecuting the algorithm. The simulation results show that this method prolongs the lifetime of the network in comparison with RIS method

A Hybrid Scheme based on Alternative Scalar Leader Election (HS-ASLE) for Redundant Data Minimization in Multi-event Occurrence Scenario for WMSNs

The current paper reports a hybrid approach namely “Hybrid Scheme based on Alternative Scalar Leader Election (HS-ASLE)” for camera sensor actuation in multi-event occurrence scenario. In the proposed approach, the whole monitored zone gets segregated into multiple virtual sub-compartments and in each of the sub-compartments, one and three scalar leaders are elected alternatively that behave as the representatives of scalars to report event information. During the event occurrence, the event information gets trapped through the scalar leaders in lieu of scalars and the leaders convey the event occurrence information to the respective camera sensors. Pervasive experiment and observation have been ordained to mark the impact of varying the number of deployed scalar sensors and camera sensors individually on various performance parameters in multi-event occurrence ambience. Further, the numerical outcomes attained in terms of number of cameras actuated, coverage ratio, redundance ratio and energy expenditure for camera activation proclaim the effectiveness of our proposed HS-ASLE over the other two existing approaches in literature. Moreover, it is marked that our proposed approach attains maximal event region coverage with least camera activation, least redundant data transmission and lowest energy expenditure for camera sensor actuation as compared to two other approaches, which justify the precedence of our proposition over the other existing approaches

Intelligent Sensor Networks

In the last decade, wireless or wired sensor networks have attracted much attention. However, most designs target general sensor network issues including protocol stack (routing, MAC, etc.) and security issues. This book focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on their world-class research, the authors present the fundamentals of intelligent sensor networks. They cover sensing and sampling, distributed signal processing, and intelligent signal learning. In addition, they present cutting-edge research results from leading experts

Real-time human ambulation, activity, and physiological monitoring:taxonomy of issues, techniques, applications, challenges and limitations

Automated methods of real-time, unobtrusive, human ambulation, activity, and wellness monitoring and data analysis using various algorithmic techniques have been subjects of intense research. The general aim is to devise effective means of addressing the demands of assisted living, rehabilitation, and clinical observation and assessment through sensor-based monitoring. The research studies have resulted in a large amount of literature. This paper presents a holistic articulation of the research studies and offers comprehensive insights along four main axes: distribution of existing studies; monitoring device framework and sensor types; data collection, processing and analysis; and applications, limitations and challenges. The aim is to present a systematic and most complete study of literature in the area in order to identify research gaps and prioritize future research directions

Effective Node Clustering and Data Dissemination In Large-Scale Wireless Sensor Networks

The denseness and random distribution of large-scale WSNs makes it quite difficult to replace or recharge nodes. Energy efficiency and management is a major design goal in these networks. In addition, reliability and scalability are two other major goals that have been identified by researchers as necessary in order to further expand the deployment of such networks for their use in various applications. This thesis aims to provide an energy efficient and effective node clustering and data dissemination algorithm in large-scale wireless sensor networks. In the area of clustering, the proposed research prolongs the lifetime of the network by saving energy through the use of node ranking to elect cluster heads, contrary to other existing cluster-based work that selects a random node or the node with the highest energy at a particular time instance as the new cluster head. Moreover, a global knowledge strategy is used to maintain a level of universal awareness of existing nodes in the subject area and to avoid the problem of disconnected or forgotten nodes. In the area of data dissemination, the aim of this research is to effectively manage the data collection by developing an efficient data collection scheme using a ferry node and applying a selective duty cycle strategy to the sensor nodes. Depending on the application, mobile ferries can be used for collecting data in a WSN, especially those that are large in scale, with delay tolerant applications. Unlike data collection via multi-hop forwarding among the sensing nodes, ferries travel across the sensing field to collect data. A ferry-based approach thus eliminates, or minimizes, the need for the multi-hop forwarding of data, and as a result, energy consumption at the nodes will be significantly reduced. This is especially true for nodes that are near the base station as they are used by other nodes to forward data to the base station. MATLAB is used to design, simulate and evaluate the proposed work against the work that has already been done by others by using various performance criteria

High resilience wireless mesh networking characteristics and safety applications within underground mines

The work presented in this thesis has investigated the feasibility, characteristics and potential applications of low power wireless networking technology, particularly aimed at improving underground mine safety. Following an initial review, wireless technology was identified as having many desirable attributes as a modern underground data transmission medium. Wireless systems are mobile, flexible, and easily scalable. Installation time can be reduced and there is scope for rapid deployment of wireless sensor networks following an emergency incident such as a mine explosion or roof rock fall. Low power mesh technology, relating to the Zigbee and IEEE 802.15.4 LR-WPAN (low-rate wireless personal area network) standards, has been of particular interest within this research project. The new breed of LR-WPAN technology is specifically designed for low power, low data rate wireless sensor applications. The mesh networking characteristics of the technology significantly increase network robustness and resilience. The self-healing, self-organising, multiple pathway redundancy, and highly scalable attributes of mesh networks are particularly advantageous for underground, or confined space, high-integrity safety and emergency applications. The study and potential use of this type of technology in an underground mine is a novel aspect of this thesis. The initial feasibility and review examined the current and future trends of modern underground data transmission systems, with particular focus on mine safety. The findings following the review determined the ideal requirements of an underground data transmission in terms of robustness, integrity, interoperability, survivability and flexibility; with wireless mesh networking meeting many of these requirements. This research has investigated underground wireless propagation characteristics at UHF and microwave frequencies in tunnels. This has involved examining electromagnetic (EM) waveguide theory, in particular the lossy dielectric tunnel waveguide model e.g. (Emslie et al., 1975 and Delogne, 1982). Extensive tests have been carried out in three different underground locations (railway tunnel, hard rock mine, coal mine test facility) using continuous wave (CW), or ‘pure’ transmission at 2.3GHz and 5.8GHz, along with a range of throughput performance tests using various wireless technologies: IEEE 802.11b, 802.11g, SuperG, SuperG (plus BeamFlex antennas), 802.11pre-n. 802.11draft-n, and Bluetooth. The results of these practical tests have been compared with the lossy dielectric tunnel waveguide model showing good agreement that tunnels will in fact enhance the EM propagation through the waveguide effect. Building on previous research during the last 30 years into high frequency underground radio transmission, this work presents a novel investigation into the performance of modern underground wireless technologies operating in underground mines and tunnels. 4 The feasibility and performance of low power wireless mesh networking technology, relating to Zigbee/IEEE 802.15.4, operating in various underground and confined space environments has been investigated through a series of practical tests in different locations including: a hard rock test mine, a coal mine and a fire training centre (confined space built infrastructure). The results of these tests are presented discussing the significant benefits in employing ‘mesh’ topologies in mines and tunnels. Following this, key applications were identified for potential development. Distributed smart sensor network e.g. environmental monitoring, machine diagnostics or remote telemetry, applications were developed to a proof-of-concept stage. A remote 3D surveying telemetry application was also developed in conjunction with the ‘RSV’ (remote surveying vehicle) project at CSM. Vital signs monitoring of personnel has also been examined, with tests carried out in conjunction with the London Fire Service. ‘Zonal location information’ was another key application identified using underground mesh wireless networks to provide active tracking of personnel and vehicles as a lower cost alternative to RFID. Careful consideration has also been given to potential future work, ranging from ‘mine friendly’ antennas, to a ‘hybrid Zigbee’, such as, optimised routing algorithms, and improved physical RF performance, specifically for high-integrity underground safety and emergency applications. Both the tests carried out and key safety applications investigated have been a novel contribution of this thesis. In summary, this thesis has contributed to furthering the knowledge within the field of subsurface electromagnetic wave propagation at UHF and microwave frequencies. Key characteristics and requirements of an underground critical safety data transmission system have been identified. Novel aspects of this work involved investigating the application of new wireless mesh technology for underground environments, and investigating the performance of modern wireless technologies in tunnels through practical tests and theoretical analysis. Finally, this thesis has proved that robust and survivable underground data transmission, along with associated mine safety applications, can feasibly be achieved using the low power wireless mesh networking technology. Robust underground wireless networking also has potential benefits for other industrial and public sectors including tunnelling, emergency services and transport

Doctor of Philosophy

dissertationLow-cost wireless embedded systems can make radio channel measurements for the purposes of radio localization, synchronization, and breathing monitoring. Most of those systems measure the radio channel via the received signal strength indicator (RSSI), which is widely available on inexpensive radio transceivers. However, the use of standard RSSI imposes multiple limitations on the accuracy and reliability of such systems; moreover, higher accuracy is only accessible with very high-cost systems, both in bandwidth and device costs. On the other hand, wireless devices also rely on synchronized notion of time to coordinate tasks (transmit, receive, sleep, etc.), especially in time-based localization systems. Existing solutions use multiple message exchanges to estimate time offset and clock skew, which further increases channel utilization. In this dissertation, the design of the systems that use RSSI for device-free localization, device-based localization, and breathing monitoring applications are evaluated. Next, the design and evaluation of novel wireless embedded systems are introduced to enable more fine-grained radio signal measurements to the application. I design and study the effect of increasing the resolution of RSSI beyond the typical 1 dB step size, which is the current standard, with a couple of example applications: breathing monitoring and gesture recognition. Lastly, the Stitch architecture is then proposed to allow the frequency and time synchronization of multiple nodes' clocks. The prototype platform, Chronos, implements radio frequency synchronization (RFS), which accesses complex baseband samples from a low-power low-cost narrowband radio, estimates the carrier frequency offset, and iteratively drives the difference between two nodes' main local oscillators (LO) to less than 3 parts per billion (ppb). An optimized time synchronization and ranging protocols (EffToF) is designed and implemented to achieve the same timing accuracy as the state-of-the-art but with 59% less utilization of the UWB channel. Based on this dissertation, I could foresee Stitch and RFS further improving the robustness of communications infrastructure to GPS jamming, allow exploration of applications such as distributed beamforming and MIMO, and enable new highly-synchronous wireless sensing and actuation systems