Bayesian proprioceptor for forest fire observer network

Authors:
Ljiljana Šerić;Maja Štula;Darko Stipaničev;Maja Braović
Affiliations:
Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia;Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia;Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia;Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Split, Croatia
Venue:
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
Year:
2012

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Abstract

The paper describes design and implementation of Bayesian proprioceptor for forest fire observer network. The proprioceptor, sometimes also referred to as network observer has task of syintactical and semantical sensor and data validation in advanced sensor network Multi agent Bayesian network is used for cooperative data analysis and data understanding having false alarm reduction as final goal. A multi agent system for data sampling and data analysis is described. The proprioceptor is deployed as a part of intelligent forest fire monitoring system (iForestFire).