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Proceedings Paper

Dynamic data-driven sensor network adaptation for border control
Author(s): Doina Bein; Bharat B. Madan; Shashi Phoha; Sarah Rajtmajer; Anna Rish
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Paper 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.

Paper Details

Date Published: 6 June 2013
PDF: 9 pages
Proc. SPIE 8711, Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII, 87110J (6 June 2013); doi: 10.1117/12.2027359
Show Author Affiliations
Doina Bein, The Pennsylvania State Univ. (United States)
Bharat B. Madan, Old Dominion Univ. (United States)
Shashi Phoha, The Pennsylvania State Univ. (United States)
Sarah Rajtmajer, The Pennsylvania State Univ. (United States)
Anna Rish, The Pennsylvania State Univ. (United States)


Published in SPIE Proceedings Vol. 8711:
Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII
Edward M. Carapezza, Editor(s)

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