Efficient Deep CNN-Based Fire Detection and Localization in Video Surveillance Applications

Computer Engineering

For reducing the loss of life and various industries from fire, an early warning is an important. Accidents caused by undiscovered fires have cost the globe a lot of money. The demand for effective fire detection systems is on the rise. Because of the system\'s inefficiency, existing fire and smoke detectors are failing. Analyzing live camera data allows for real-time fire detection. The fire flame features are investigated, and the fire is recognized using edge detection and thresholding methods, resulting in the creation of a fire detected model. It detects hazardous fires identified on the size, velocity, volume and the texture. In this paper we are proposing an emerging fire detection system based on Convolutional Neural Network. The model\'s experimental results on our dataset reveal that it has good fire detection capability and ability of detecting multi-scale fire in real-time

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