Multisensor data fusion for fire detection

Fire is a common disastrous phenomenon that constitutes a serious threat. The SCIER (Sensor and Computing Infrastructure for Environmental Risks is partially funded by the European Community through the FP6 IST Program. The work presented in this paper expresses the ideas of the authors and not necessarily the whole SCIER consortium.) project envisages the deployment of Wireless Sensor Networks at the ''Urban-Rural-Interface'' (URI) aiming to the detection, monitoring and crisis management of such natural hazards. One of its primary objectives is the development of an advanced multisensor data fusion scheme which feeds a CUSUM sequential test used in the early detection of fires. Reasoning about the probability of fire in a geographical area covered by temperature, humidity and vision sensors is achieved through Evidential Reasoning (Dempster-Shafer theory).

[1]  Hong Bao,et al.  A fire detecting method based on multi-sensor data fusion , 2003, SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems, Man and Cybernetics. Conference Theme - System Security and Assurance (Cat. No.03CH37483).

[2]  R. Yager On the dempster-shafer framework and new combination rules , 1987, Inf. Sci..

[3]  Frederick W. Williams,et al.  Multi-criteria fire detection systems using a probabilistic neural network , 2000 .

[4]  E. S. Page CONTINUOUS INSPECTION SCHEMES , 1954 .

[5]  A. Walter Notes on the utilization of records from third order climatological stations for agricultural purposes , 1967 .

[6]  David M. Doolin,et al.  Wireless sensors for wildfire monitoring , 2005, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[7]  J. Cihlar,et al.  Satellite-based detection of Canadian boreal forest fires: Development and application of the algorithm , 2000 .

[8]  Philippe Smets,et al.  Varieties of ignorance and the need for well-founded theories , 1991, Inf. Sci..

[9]  Robert H. Fraser,et al.  Automatic Detection of Fire Smoke Using Artificial Neural Networks and Threshold Approaches Applied to AVHRR Imagery , 2001 .

[10]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[11]  Frederick W. Williams,et al.  Early Warning Fire Detection System Using a Probabilistic Neural Network , 2003 .

[12]  Edit Gombay,et al.  An adaptation of Page’s CUSUM test for change detection , 2005, Period. Math. Hung..

[13]  P. Erdös,et al.  A limit theorem for the maximum of normalized sums of independent random variables , 1956 .

[14]  José Ramón González Olabarria,et al.  Integrating fire risk into forest planning , 2006 .

[15]  Philippe Smets,et al.  The Transferable Belief Model , 1994, Artif. Intell..

[16]  J. Casanova,et al.  Fire detection and monitoring using MSG Spinning Enhanced Visible and Infrared Imager (SEVIRI) data , 2006 .