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Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking

Alonshia S. Elayaraja
Copyright: © 2019 |Pages: 14
ISBN13: 9781522555223|ISBN10: 1522555226|ISBN13 Softcover: 9781522586517|EISBN13: 9781522555230
DOI: 10.4018/978-1-5225-5522-3.ch001
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MLA

Elayaraja, Alonshia S. "Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking." Modeling Methods for Business Information Systems Analysis and Design, edited by Selin Erben, IGI Global, 2019, pp. 1-14. https://doi.org/10.4018/978-1-5225-5522-3.ch001

APA

Elayaraja, A. S. (2019). Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking. In S. Erben (Ed.), Modeling Methods for Business Information Systems Analysis and Design (pp. 1-14). IGI Global. https://doi.org/10.4018/978-1-5225-5522-3.ch001

Chicago

Elayaraja, Alonshia S. "Bayesian Localized Energy Optimized Sensor Distribution for Efficient Target Tracking." In Modeling Methods for Business Information Systems Analysis and Design, edited by Selin Erben, 1-14. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-5522-3.ch001

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Abstract

Many applications in wireless sensor networks perform localization of nodes over an extended period of time. Optimal selection algorithm poses new challenges to the overall transmission power levels for target detection, and thus, localized energy optimized sensor management strategies are necessary for improving the accuracy of target tracking. In this chapter, a proposal plan to develop a Bayesian localized energy optimized sensor distribution scheme for efficient target tracking in wireless sensor network is designed. The sensor node localization is done with Bayesian average, which estimates the sensor node's energy optimality. Then the sensor nodes are localized and distributed based on the Bayesian energy estimate for efficient target tracking. The sensor node distributional strategy improves the accuracy of identifying the targets to be tracked quickly. The performance is evaluated with parameters such as accuracy of target tracking, energy consumption rate, localized node density, and time for target tracking.

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