Title :
Facility security reasoning in a hybrid intelligent tracking system
Author :
Elling, John W. ; Johnson, Chris
Author_Institution :
Los Alamos Nat. Lab., NM, USA
Abstract :
A hybrid intelligent expert system is being developed for the adaptive multisensor integrated security system (AMISS) to identify threatening patterns of behavior in a nuclear facility. The focus of this paper is the sensor fusion strategy used to create the input to the rule-based and neural network reasoning systems. The sensor fusion components of the AMISS system use a number of data processing techniques to accomplish its mission of combining disparate sensor data types in a noisy and uncertain environment
Keywords :
adaptive signal processing; expert systems; inference mechanisms; neural nets; object-oriented methods; pattern recognition; security; sensor fusion; target tracking; tracking; adaptive multisensor integrated security system; expert system; intelligent tracking system; neural network reasoning systems; object oriented reasoning; rule-based systems; sensor fusion; threatening pattern recognition; Computer science; Data security; Hybrid intelligent systems; Information security; Insulation life; Laboratories; National security; Neural networks; Personnel; Sensor fusion;
Conference_Titel :
Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-4053-1
DOI :
10.1109/ICSMC.1997.635323
