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Automatic fire detection based on soft computing techniques: review from 2000 to 2010

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Abstract

Automatic fire detection system is a system that is capable of assessing environmental factors and their effects on the environment as well as predicting the occurrence of fire in the early stages and even before the outbreak. There are two perspectives in fire detection: fire detection in forests or jungles and fire detection in occupied or residential areas. Automatic fire detection has attracted increased attention due to its importance in decreasing fire damage. There are many studies that have considered appropriate techniques for early fire detection. In recent years researches have been studying technical developments in this field aimed at exploiting wireless communications networks, detection systems and fire prediction systems design. In this paper the automatic fire detection researches using intelligent techniques from 2000 to 2010 is reviewed. We could classify researches to four categories: fire detectors, reduce false alarms systems, fire data analysis and fire predictors. We also classify the intelligent techniques outlined in the researches for each category.

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  1. K. N. Toosi University of Technology, Tehran, Iran

    Elham Mahdipour & Chitra Dadkhah

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Mahdipour, E., Dadkhah, C. Automatic fire detection based on soft computing techniques: review from 2000 to 2010. Artif Intell Rev 42, 895–934 (2014). https://doi.org/10.1007/s10462-012-9345-z

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