A line in the sand: a wireless sensor network for target detection, classification, and tracking

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A line in the sand: a wireless sensor network for target detection, classification, and tracking (2004)

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by A. Arora , P. Dutta , S. Bapat , V. Kulathumani , H. Zhang , V. Naik, V. Mittal , H. Cao , M. Demirbas , M. Gouda , Y. Choi , T. Herman , et al.

Venue:	COMPUTER NETWORKS
Citations:	272 - 41 self

BibTeX

@ARTICLE{Arora04aline,
    author = {A. Arora and P. Dutta and S. Bapat and V. Kulathumani and H. Zhang and V. Naik and V. Mittal and H. Cao and M. Demirbas and M. Gouda and Y. Choi and T. Herman and et al.},
    title = {A line in the sand: a wireless sensor network for target detection, classification, and tracking},
    journal = {COMPUTER NETWORKS},
    year = {2004},
    volume = {46},
    pages = {605--634}
}

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Abstract

Intrusion detection is a surveillance problem of practical import that is well suited to wireless sensor networks. In this paper, we study the application of sensor networks to the intrusion detection problem and the related problems of classifying and tracking targets. Our approach is based on a dense, distributed, wireless network of multi-modal resource-poor sensors combined into loosely coherent sensor arrays that perform in situ detection, estimation, compression, and exfiltration. We ground our study in the context of a security scenario called ‘‘A Line in the Sand’ ’ and accordingly define the target, system, environment, and fault models. Based on the performance requirements of the scenario and the sensing, communication, energy, and computation ability of the sensor network, we explore the design space of sensors, signal processing algorithms, communications, networking, and middleware services. We introduce the influence field, which can be estimated from a network of binary sensors, as the basis for a novel classifier. A contribution of our work is that we do not assume a reliable network; on the contrary, we quantitatively analyze the effects of network unreliability on application performance. Our work includes multiple experimental deployments of over 90

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