Dynamic data-driven sensor network adaptation for border control

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationSensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII
DOIs
StatePublished - Aug 9 2013
EventSensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII - Baltimore, MD, United States
Duration: Apr 29 2013May 1 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume8711
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Other

OtherSensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense XII
CountryUnited States
CityBaltimore, MD
Period4/29/135/1/13

All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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