Abstract

Sensors are being deployed to improve border security generating enormous collections of data and databases. Unfortunately these sensors can respond to a variety of stimuli, sometimes reacting to meaningful events and sometimes triggered by random events which are considered false alarms. The intent of this project is to supplement human intelligence in a sensor network framework that can assist in filtering and real-time decision making from the large volume of data generated. Our conceptual design of a human-computer system is to use off-line learning to identify the important patterns. The critical real-time system uses the identified patterns from off-line learning in a system that relates the risks of false alarms with the length of patterns and the time interval distributions between sensors in the patterns to allow the human to generate intervention decisions. The human would supplement the computer information with the current threat levels and the available resources for reactions.

Original languageEnglish (US)
Title of host publication2010 3rd International Conference on Human-Centric Computing, HumanCom 2010
DOIs
StatePublished - Oct 28 2010
Event2010 3rd International Conference on Human-Centric Computing, HumanCom 2010 - Cebu, Philippines
Duration: Aug 11 2010Aug 13 2010

Publication series

Name2010 3rd International Conference on Human-Centric Computing, HumanCom 2010

Other

Other2010 3rd International Conference on Human-Centric Computing, HumanCom 2010
CountryPhilippines
CityCebu
Period8/11/108/13/10

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Human-Computer Interaction
  • Software

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