Please use this identifier to cite or link to this item: https://doi.org/10.1109/TVT.2007.891480
Title: Energy efficient multiple target tracking in wireless sensor networks
Authors: Yeow, W.-L.
Tham, C.-K. 
Wong, W.-C. 
Keywords: Distributed tracking
Intelligent sensors
Minimum energy control
Neurodynamic programming
Prediction methods
Issue Date: Mar-2007
Source: Yeow, W.-L., Tham, C.-K., Wong, W.-C. (2007-03). Energy efficient multiple target tracking in wireless sensor networks. IEEE Transactions on Vehicular Technology 56 (2) : 918-928. ScholarBank@NUS Repository. https://doi.org/10.1109/TVT.2007.891480
Abstract: Energy awareness is a crucial component in the design of wireless sensor networks at all layers. This paper looks into efficient energy utilization of a target-tracking sensor network by predicting a target's trajectory through experience. While this is not new, the chief novelty comes in conserving energy through both dynamic spatial and temporal management of sensors while assuming minimal locality information. We adapted our target trajectory model from the Gauss-Markov mobility model, formulated the tracking problem as a hierarchical Markov decision process (HMDP), and solved it through neurodynamic programming. Our HMDP for target-tracking (HMTT) algorithm conserves energy by reducing the rate of sensing (temporal management) but maintains an acceptable tracking accuracy through trajectory prediction (spatial management) of multiple targets. We derived some theoretical bounds on accuracy and energy utilization of HMTT. Simulation results demonstrated the effectiveness of HMTT in energy conservation and tracking accuracy against two other predictive tracking algorithms, with accuracy of up to 47% higher and energy savings of up to 200%. © 2007 IEEE.
Source Title: IEEE Transactions on Vehicular Technology
URI: http://scholarbank.nus.edu.sg/handle/10635/55869
ISSN: 00189545
DOI: 10.1109/TVT.2007.891480
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