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Automating Fire Detection and Suppression with Computer Vision: A Multi-Layered Filtering Approach to Enhanced Fire Safety and Rapid Response

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Abstract

A computer vision-based integrated fire detection and automated suppression device capable of real-time functioning is proposed to enhance the fire safety. The developed multilayered algorithm considers color based clue detection and thereafter incorporates three filtration stages ‘Centroid Analysis’, ‘Histogram Analysis’ and ‘Variance Analysis’ for successful fire detection. Results from the proposed algorithm has been compared and validated against standard video datasets and was found to have an overall accuracy of 95.26% with 91.61% true positive detection rate, only 8.39% of false detection in positive fire videos and true negative rate of 98.91% with only 1.09% of false detection in negative nonfire videos. Additionally, our algorithm showed an average improvement of 7.95% in accuracy and 9.43% in precision over existing algorithms, demonstrating its sensitivity and reliability for effective fire detection and suppression. The algorithm also includes unique fire localization techniques to locate the detected fire, which was integrated with an Arduino based suppression unit to provide a real- time autonomous fire suppression. Laboratory-scale experimental validation has shown practical significance of the proposed system for any kind of personal, industrial, indoor, or outdoor environmental applications with a high precision value of 99.51% and a recall value of 95.93%.

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Acknowledgements

We would like to thank Dr. Pranibesh Mandal, assistant professor of mechanical engineering department at Jadavpur University, and Mr. Kanchan Sadhu of Bharat Petroleum Corporation Limited for their valuable insights and technical assistance throughout the project.

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Authors and Affiliations

  1. Department of Mechanical Engineering, Jadavpur University, Kolkata, 700032, India

    Md Safwan Mondal, Nilendu Saha, Saumadeep Guha, Achintya Mukhopadhyay & Sourav Sarkar

  2. Department of Instrumentation and Electronics Engineering, Jadavpur University (Salt Lake Campus), Kolkata, 700106, India

    Varun Prasad, Ramendra Kumar & Ratna Ghosh

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  1. Md Safwan Mondal
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Mondal, M.S., Prasad, V., Kumar, R. et al. Automating Fire Detection and Suppression with Computer Vision: A Multi-Layered Filtering Approach to Enhanced Fire Safety and Rapid Response. Fire Technol 59, 1555–1583 (2023). https://doi.org/10.1007/s10694-023-01392-w

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