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Sensors 2017, 17(5), 1028;

Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks

College of Mechanical and Electronic Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China
Author to whom correspondence should be addressed.
Academic Editors: Cheng-Ying Yang and Min-Shiang Hwang
Received: 16 February 2017 / Revised: 19 April 2017 / Accepted: 2 May 2017 / Published: 4 May 2017
(This article belongs to the Special Issue Mobile Sensing Applications)
Full-Text   |   PDF [6325 KB, uploaded 4 May 2017]   |  


Target detection is a widely used application for area surveillance, elder care, and fire alarms; its purpose is to find a particular object or event in a region of interest. Usually, fixed observing stations or static sensor nodes are arranged uniformly in the field. However, each part of the field has a different probability of being intruded upon; if an object suddenly enters an area with few guardian devices, a loss of detection will occur, and the stations in the safe areas will waste their energy for a long time without any discovery. Thus, mobile wireless sensor networks may benefit from adaptation and pertinence in detection. Sensor nodes equipped with wheels are able to move towards the risk area via an adaptive learning procedure based on Bayesian networks. Furthermore, a clustering algorithm based on k-means++ and an energy control mechanism is used to reduce the energy consumption of nodes. The extended Kalman filter and a voting data fusion method are employed to raise the localization accuracy of the target. The simulation and experimental results indicate that this new system with adaptive energy-efficient methods is able to achieve better performance than the traditional ones. View Full-Text
Keywords: wireless sensor network; alarm; intrusive detection; energy control; data fusion wireless sensor network; alarm; intrusive detection; energy control; data fusion

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Zou, T.; Li, Z.; Li, S.; Lin, S. Adaptive Energy-Efficient Target Detection Based on Mobile Wireless Sensor Networks. Sensors 2017, 17, 1028.

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