System For Real Time Fire And Smoke Intensity Detection

Main Article Content

Vikas Maheshkar Vikas Maheshkar
Ayush Singh
Huny Dahiya
Vansh

Abstract

Fire poses a significant threat to daily life, causing both economic and social harm. To
mitigate these damages, early detection of fire and smoke is crucial, and this paper introduces a model
employing vision-based techniques. The proposed model utilizes image processing and convolutional
neural networks to detect fire and smoke, providing insights into their intensity and any changes in a
video. The model comprises two units for fire and smoke detection, each employing image preprocessing
techniques, including rule-based color detection and motion detection, along with CNN. The calculated
percentages of fire and smoke in the processed images offer detailed information about the severity of
the hazards in a specific area. The model detects whether the intensity of fire and smoke is increasing,
decreasing or constant.

Article Details

How to Cite
Vikas Maheshkar, V. M., Ayush Singh, Huny Dahiya, & Vansh. (2024). System For Real Time Fire And Smoke Intensity Detection. INFOCOMP Journal of Computer Science, 23(1). Retrieved from https://infocomp.dcc.ufla.br/index.php/infocomp/article/view/3514
Section
Computer Graphics, Image Processing, Visualization and Virtual Reality

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