Title :
Research of Fire Detection Method Based on Multi-Sensor Data Fusion
Author :
Xiaojuan Chen ; Leping Bu
Author_Institution :
Coll. of Electr. & Inf. Eng., Naval Univ. of Eng., Wuhan, China
Abstract :
In order to reduce false alarm and alarm failure of fire detection system, a research of fire detection method based on multi-sensor data fusion was conducted. In this research, probabilistic neural networks (PNN) data fusion algorithm was employed to detect fire based on texture features from fire scene. Information of temperature and smoke concentration were processed by trend algorithm separately. Results from the above three fire detection algorithms were processed through decision level data fusion to accomplish fire detection and automatic fire alarm. It has been demonstrated that fire detection platform based on this method can detect fire faster and more accurately and discard nuance disturbances from florescent light or alcohol burner, thus providing a brighter future in applications.
Keywords :
fires; sensor fusion; PNN; alarm failure; alcohol burner; false alarm; fire detection method; fire scene; florescent light; multisensor data fusion; probabilistic neural networks; smoke concentration; temperature concentration; texture features; trend algorithm; Artificial neural networks; Detection algorithms; Feature extraction; Fires; Smoke detectors; Temperature sensors; Training;
Conference_Titel :
Computational Intelligence and Software Engineering (CiSE), 2010 International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5391-7
Electronic_ISBN :
978-1-4244-5392-4
DOI :
10.1109/CISE.2010.5677271