Abstract: In order to overcome the shortcomings of the existing mountain fire early warning technology in transmission and transformation corridor and improve the anti- interference ability of mountain fire identification, a method of mountain fire early warning based on edge computing is proposed. Based on the analytic hierarchy process (AHP), an analysis model of influencing factors for the location selection of edge monitoring nodes is established. The weight of each element is determined by the discriminant matrix, and the location of edge monitoring node is determined according to the optimal solution. Aiming at the mountain fire identification environment in the transmission and transformation corridor, the edge computing architecture is designed in detail to improve the level of mountain fire early warning in the transmission and transformation corridor. In order to reduce the computational cost of edge convolution calculation, the Mobilenet-SSD model is established to train the fire image recognition data of edge monitoring nodes, and anti-interference measures are added to verify the model effect. The experimental results show that the training model is suitable for the edge computing architecture and can effectively identify the fire in the transmission and transformation corridor. 

Key words:  , power transmission and transformation corridor, mountain fire early warning, edge computing, Mobilenet