i-manager Publications

Fire and Smoke Detection with Deep Learning: A Review

Vinay Kumar Jain*, Chitrangad Jain**

* Shri Shankaracharya Technical Campus, Bhilai, India.

** Chhattisgarh Swami Vivekanand Technical University, Bhilai, India.

Periodicity:July - December'2022
DOI : https://doi.org/10.26634/jdp.10.2.19262

Abstract

This paper outlines a state-of-the-art method for smoke and fire detection utilizing Convolutional Neural Networks (CNNs). The current smoke detectors installed in buildings pose a challenge for effective fire detection. The inefficiency of traditional methods in terms of speed and cost led to the exploration of using Artificial Intelligence (AI) to identify and alert from Closed Circuit Television (CCTV) footage. In this paper, an analytical overview of AI is conducted by using a selfcreated dataset of video frames containing flames and smoke. The data undergoes pre-processing before being used to train a CNN-based machine learning model. The goal of this review study is to understand the available literature in the field and propose a highly accurate, cost-effective, and simple system for fire detection in various scenarios.

Keywords

Convolutional Neural Networks, Closed Circuit Television, Smoke, Artificial Intelligence and Detection, Machine Learning Model.

How to Cite this Article?

Jain, V. K., and Jain, C. (2022). Fire and Smoke Detection with Deep Learning: A Review. i-manager’s Journal on Digital Signal Processing, 10(2), 22-32. https://doi.org/10.26634/jdp.10.2.19262

References

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Fire and Smoke Detection with Deep Learning: A Review

Abstract

Keywords

How to Cite this Article?

References

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