At present, the number of electric bicycles in China is still increasing rapidly, with the risk of fire still exceeding 300 million. This paper designs an electric vehicle monitoring system based on deep learning. The system uses the image real-time transmission system and deep learning platform to identify and detect the relevant behaviors of electric vehicles in real time. Infrared cameras are set in the areas with high fire risk such as the centralized parking point and charging point of electric vehicles. The captured infrared image is based on the smoke removal processing method of histogram equalization to improve the contrast of the image. It is convenient for the upper computer to identify the high-temperature point, find the fire point in time, and nip the danger in the bud.

Changle Wang, Pei Yu, Guochen Zhang. Intelligent detection system of community electric vehicle based on visual deep learning. Academic Journal of Computing & Information Science (2022), Vol. 5, Issue 4: 1-3. https://doi.org/10.25236/AJCIS.2022.050401.

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