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Sensors 2017, 17(2), 361; doi:10.3390/s17020361

A Continuous Object Boundary Detection and Tracking Scheme for Failure-Prone Sensor Networks

Department of Computer Engineering, Ajou University, Suwon 443749, Korea
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Author to whom correspondence should be addressed.
Academic Editor: Wendong Xiao
Received: 23 December 2016 / Revised: 5 February 2017 / Accepted: 10 February 2017 / Published: 13 February 2017
(This article belongs to the Section Sensor Networks)
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Abstract

In wireless sensor networks, detection and tracking of continuous natured objects is more challenging owing to their unique characteristics such as uneven expansion and contraction. A continuous object is usually spread over a large area, and, therefore, a substantial number of sensor nodes are needed to detect the object. Nodes communicate with each other as well as with the sink to exchange control messages and report their detection status. The sink performs computations on the received data to estimate the object boundary. For accurate boundary estimation, nodes at the phenomenon boundary need to be carefully selected. Failure of one or multiple boundary nodes (BNs) can significantly affect the object detection and boundary estimation accuracy at the sink. We develop an efficient failure-prone object detection approach that not only detects and recovers from BN failures but also reduces the number and size of transmissions without compromising the boundary estimation accuracy. The proposed approach utilizes the spatial and temporal features of sensor nodes to detect object BNs. A Voronoi diagram-based network clustering, and failure detection and recovery scheme is used to increase boundary estimation accuracy. Simulation results show the significance of our approach in terms of energy efficiency, communication overhead, and boundary accuracy. View Full-Text
Keywords: continuous object detection and tracking; node failure; wireless sensor network continuous object detection and tracking; node failure; wireless sensor network
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Imran, S.; Ko, Y.-B. A Continuous Object Boundary Detection and Tracking Scheme for Failure-Prone Sensor Networks. Sensors 2017, 17, 361.

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