IET Wireless Sensor Systems
Volume 9, Issue 4, August 2019
Volumes & issues:
Volume 9, Issue 4
August 2019
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- Author(s): Devendra Kumar Yadav ; Singam Jayanthu ; Santos Kumar Das ; Suchismita Chinara ; Pragyan Mishra
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 167 –180
- DOI: 10.1049/iet-wss.2018.5197
- Type: Article
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p.
167
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Slope stability is one of the major geological concerns in open-cast mines. The mining area slopes needs to be regularly monitored to detect occurrence of any slope failure prior to any catastrophe. An early warning system solves this purpose preventing loss of significant mass of human lives as well as property. This is a critical scrutiny which renders various techniques and methodologies regarding slope monitoring of open-cast mine. Wireless sensor network (WSN) has been standing out as a productive competent tool for monitoring the tangible environmental structures by sensing the differences, processing this raw data and finally communicating the result to the web from where it can be referred for researches and predicting mechanisms. Internet of Things (IoT) comes into picture for communicating the sensed and processed data from the sensors to the application where it can be further analysed. In recent scenario, power issue is of great concern associated with deploying a real-time monitoring system. This review depicts how WSN can be adopted and preferred to any other technologies used in slope monitoring due to its advantages it brings. Moreover, collaborative operation of WSN with IoT results in a more systematic, robust, energy-efficient, cost-effective real-time monitoring approach.
Critical review on slope monitoring systems with a vision of unifying WSN and IoT
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- Author(s): Nitika Rai and Rohin Daruwala
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 181 –190
- DOI: 10.1049/iet-wss.2018.5048
- Type: Article
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p.
181
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Network coverage is a measure of efficiency that signifies the extent to which the deployed nodes collectively cover the network area. It is a fundamental and critical quality of service (QoS) parameter for designing wireless sensor networks (WSNs). Various sensing models are reported which can be used to predict the coverage fraction for a given number of nodes in a predetermined network area. However, each of these reported models consider a subset of parameters. In this study, a novel formulation and hence a new model, composite probabilistic sensing model (CPSM) is proposed which combines the cumulative effects of all the possible factors, thus resulting in a realistic study. Further, the model is revisited to estimate the optimal density of randomly deployed nodes required to attain the desired network area coverage. An exhaustive parametric study is carried out and the results obtained are used to empirically derive a formula based on regression analysis using least square polynomial curve fitting technique. The formulation can be readily and accurately used to design any practical WSN system.
- Author(s): Muhammad Safyan ; Zia Ul Qayyum ; Sohail Sarwar ; Muddesar Iqbal ; Raul Garcia Castro ; Anwer Al-Dulaimi
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 193 –200
- DOI: 10.1049/iet-wss.2018.5209
- Type: Article
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193
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Ontology-based knowledge-driven activity recognition (AR) models play a vital role in realm of Internet of Things (IoTs). However, these models suffer the shortcomings of static nature, inability of self-evolution, and lack of adaptivity. Also, AR models cannot be made comprehensive enough to cater all the activities and smart home inhabitants may not be restricted to only those activities contained in AR model. So, AR models may not rightly recognise or infer new activities. Here, a framework has been proposed for dynamically capturing the new knowledge from activity patterns to evolve behavioural changes in AR model (i.e. ontology based model). This ontology-based framework adapts by learning the specialised and extended activities from existing user-performed activity patterns. Moreover, it can identify new activity patterns previously unknown in AR model, adapt the new properties in existing activity models and enrich ontology model by capturing change representation to enrich ontology model. The proposed framework has been evaluated comprehensively over the metrics of accuracy, statistical heuristics, and Kappa coefficient. A well-known dataset named DAMSH has been used for having an empirical insight into the effectiveness of proposed framework that shows a significant level of accuracy for AR models.
- Author(s): Susan G. Varghese ; Ciji Pearl Kurian ; V.I. George ; Anupriya John ; Varsha Nayak ; Anil Upadhyay
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 201 –207
- DOI: 10.1049/iet-wss.2018.5065
- Type: Article
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201
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ZigBee standard is the popular communication protocol for wireless sensor networks (WSN) and Internet of Things (IoT) networks. An energy efficient WSN technology is a good choice for an IoT based lighting control technology. This article is a comparative analysis for finding the quality of service parameters provided by the different topologies of ZigBee for a wireless networked lighting control system. In order to estimate the energy consumption in ZigBee topologies for lighting automation, this work analyses the star, mesh, and tree topology-based WSN with two routing protocols Adhoc on-demand distance vector (AODV) and dynamic source routing (DSR). Lighting automation using wireless control networks with sensor-actuator nodes in a laboratory is considered as the test scenario. The applicability of ZigBee topologies for IoT-based lighting automation is discussed by the evaluation of performance parameters like average jitter, throughput, end-to-end delay, and energy model.
- Author(s): K Kaushik ; Deepak Mishra ; Swades De
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 208 –217
- DOI: 10.1049/iet-wss.2018.5009
- Type: Article
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208
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Self-sustainability of wireless sensor nodes is the need of the hour to realise ubiquitous wireless networks. To this end, the authors investigate practical feasibility of a sustainable green sensor network with solar-powered nodes. They propose simple-yet-efficient (i) analytical circuit model for solar-assisted supercapacitor charging and (ii) statistical model for characterising the solar intensity distribution. Combining these circuit and statistical models, they derive a novel solar charging rate distribution for supercapacitor. For analytical insights, they also propose an ideal diode-based tight approximation for the practical supercapacitor charging circuit model. Accuracy of these proposed analytical models are validated by extensive numerical simulations based on real-world solar intensity profile and panel characteristics. The derived solar charging rate distribution is used to investigate the energy outage probability of a sensor node for a given sensing rate. The results suggest that, for an energy outage probability of 0.1, at New Delhi, a 40 F supercapacitor and a 3 W solar panel can support the operation of Waspmote with six on-board gas sensors at a rate of 65 samples per day. Furthermore, they use the proposed models to estimate the practical supercapacitor and panel sizes for sustainable operation at different geographical locations with varying sensing rate.
- Author(s): Mohamed S. Abdalzaher ; Lotfy Samy ; Osamu Muta
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 218 –226
- DOI: 10.1049/iet-wss.2018.5114
- Type: Article
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Nowadays, trust models of wireless sensor networks (WSNs) security have flourished due to the day-to-day attack challenges, which are most popular for internet of things (IoT). This article proposes a trust model based on non-zero-sum game approach for clustered-WSNs (CWSNs) security to maximise the data trustworthiness transmission. The proposed model is developed for two different attack-defence scenarios. In the first scenario, the trust model is used to face a denial-of-service (DoS) attack in which the attacker is able to drop or partially drop the delivered acknowledgments (ACKs) from a cluster member (CM) to the cluster head (CH). In the second scenario, the model target is to protect CWSNs from ON–OFF attack where the attacker is capable to frequently infect the CMs. Simulation results show improved performance of protecting the CWSNs against DoS/ON–OFF attacks and maximising data trustworthiness represented by the CMs compliance of sending the ACKs to the CH. Consequently, this mechanism can attain the appropriate security and performance for WSN-based IoT systems.
- Author(s): Banafsj Khalifa ; Ahmed Khedr ; Zaher Al Aghbari ; Jemal Abawajy
- Source: IET Wireless Sensor Systems, Volume 9, Issue 4, p. 227 –235
- DOI: 10.1049/iet-wss.2018.5174
- Type: Article
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Using the internet of things paradigm for monitoring applications requires sufficient coverage of a monitored region to collect accurate data and observe events. The problem of a coverage hole arises when a sensor fails (loses connectivity with its neighbouring sensors) for reasons such as energy exhaustion or physical damage due to deployment in harsh environments. It is vital to detect and repair coverage holes as soon as they appear because they can have debilitating effects on network coverage and connectivity if left unattended. The authors propose a novel approach that employs a fuzzy inference system to select a neighbouring sensor that moves to recover the lost area. All neighbouring sensors communicate with each other to estimate the size and location of the coverage hole. Each sensor considers its own energy level, its distance from the approximated hole, and its redundancy ratio to evaluate its eligibility. The most eligible sensor is then selected to patch the coverage hole. Through extensive simulations, they analysed the performance of the proposed approach and compared it with baseline approaches in terms of coverage recovery effectiveness. The results show that the proposed approach is much more effective in repairing the holes as compared to the baseline approaches.
Node density optimisation using composite probabilistic sensing model in wireless sensor networks
Ontology evolution for personalised and adaptive activity recognition
Comparative study of zigBee topologies for IoT-based lighting automation
Stochastic solar harvesting characterisation for sustainable sensor node operation
Non-zero-sum game-based trust model to enhance wireless sensor networks security for IoT applications
Fuzzy logic approach to repair coverage holes in internet of things monitoring applications
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