Dynamic data-driven sensor network adaptation for border control

Doina Bein; Bharat B. Madan; Shashi Phoha; Sarah Rajtmajer; Anna Rish

doi:10.1117/12.2027359

6 June 2013 Dynamic data-driven sensor network adaptation for border control

Doina Bein, Bharat B. Madan, Shashi Phoha, Sarah Rajtmajer, Anna Rish

Proceedings Volume 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII; 87110J (2013) https://doi.org/10.1117/12.2027359
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

Given a specific scenario for the border control problem, we propose a dynamic data-driven adaptation of the associated sensor network via embedded software agents which make sensor network control, adaptation and collaboration decisions based on the contextual information value of competing data provided by different multi-modal sensors. We further propose the use of influence diagrams to guide data-driven decision making in selecting the appropriate action or course of actions which maximize a given utility function by designing a sensor embedded software agent that uses an influence diagram to make decisions about whether to engage or not engage higher level sensors for accurately detecting human presence in the region. The overarching goal of the sensor system is to increase the probability of target detection and classification and reduce the rate of false alarms. The proposed decision support software agent is validated experimentally on a laboratory testbed for multiple border control scenarios.

Citation Download Citation

Doina Bein, Bharat B. Madan, Shashi Phoha, Sarah Rajtmajer, and Anna Rish "Dynamic data-driven sensor network adaptation for border control", Proc. SPIE 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII, 87110J (6 June 2013); https://doi.org/10.1117/12.2027359

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