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.
| Original language | English |
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| Journal | European Signal Processing Conference |
| Publication status | Published - 2008 |
| Externally published | Yes |
| Event | 16th European Signal Processing Conference, EUSIPCO 2008 - Lausanne, Switzerland Duration: 25 Aug 2008 → 29 Aug 2008 |