Flame detection system based on wavelet analysis of PIR sensor signals with an HMM decision mechanism
Author
Ug̃ur Töreyin, B.
Soyer, E. Birey
Urfaliog̃lu, Onay
Çetin, A. Enis
Date
2008-08Source Title
16th European Signal Processing Conference, 2008
Publisher
IEEE
Pages
[1] - [5]
Language
English
Type
Conference PaperItem Usage Stats
86
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32
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Abstract
In this paper, a flame detection system based on a pyroelectric (or passive) infrared (PIR) sensor is described. The flame detection system can be used for fire detection in large rooms. The flame flicker process of an uncontrolled fire and ordinary activity of human beings and other objects are modeled using a set of Hidden Markov Models (HMM), which are trained using the wavelet transform of the PIR sensor signal. Whenever there is an activity within the viewing range of the PIR sensor system, the sensor signal is analyzed in the wavelet domain and the wavelet signals are fed to a set of HMMs. A fire or no fire decision is made according to the HMM producing the highest probability. copyright by EURASIP.
Keywords
Decision mechanismFire detection
Flame detection
Flame flicker
Human being
Sensor signals
Sensor systems
Wavelet domain
Hidden Markov models
Wavelet analysis
Sensors