@inproceedings{28db3aefea694fedbb2169a9f68d68bf,
title = "Dynamic data-driven sensor network adaptation for border control",
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.",
author = "Doina Bein and Madan, {Bharat B.} and Shashi Phoha and Sarah Rajtmajer and Anna Rish",
year = "2013",
doi = "10.1117/12.2027359",
language = "English (US)",
isbn = "9780819495020",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII",
note = "Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII ; Conference date: 29-04-2013 Through 01-05-2013",
}