The invention relates to a fire smog detection method based on motion characteristics and the convolutional neural network. Through reading a video file, a first image is stored as an original image,and smog detection on each frame of the video is carried out; firstly, the original image is added to background update as reference, a background model is further established, secondly, a foregroundimage is extracted through a difference method, the foreground image is filtered through a dark channel threshold image to acquire candidate smog areas, lastly, a depth convolutional neural network model after training is loaded to automatically extract high-level characteristics of the candidate smog areas, and whether the candidate smog areas are smog areas is determined according to extracted characteristic vectors. The method is advantaged in that the channel prior knowledge is added to motion foreground detection, common interference is effectively filtered, environment adaptability of adetection method is improved, the convolutional neural network is used for carrying out characteristic extraction of smog images, and detection efficiency is substantially improved.