Facility security reasoning in a hybrid intelligent tracking system

Author

Elling, John W. ; Johnson, Chris

Author_Institution

Los Alamos Nat. Lab., NM, USA

Volume

3

fYear

1997

fDate

12-15 Oct 1997

Firstpage

2579

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on

Conference_Location

Orlando, FL

ISSN

1062-922X

Print_ISBN

0-7803-4053-1

Type

conf

DOI

10.1109/ICSMC.1997.635323

Filename

635323