Research on video classification method of key pollution sources based on deep learning

Abstract

China's environmental problems are not only related to the fundamental interests of the broad masses of the people, but also to China's national security and international image. At present, China's environmental protection work is facing a complex situation. Pollution sources can be divided into natural pollution sources and man-made pollution sources. Natural sources of pollution refer to places where nature releases harmful substances or causes harmful effects to the environment, such as active volcanoes. Man-made pollution source refers to the pollution source formed by human activities, and is also the main object of environmental protection research and control. Among the man-made pollution sources, air pollution sources, water pollution sources and soil pollution sources can be classified according to the main objects of pollution. Among them, air pollution sources and water pollution sources have the greatest impact on human life. Therefore, it has become an important subject worthy of in-depth discussion to take automatic and electronic measures for potential environmental pollution incidents, discover environmental pollution problems in time, reduce the probability of environmental pollution incidents, and even put some major environmental pollution incidents in their infancy. In this paper, deep learning method is used to classify the existing key pollution source video. Water pollution experiments show that the accuracy of video counting reaches 93.1%, which is better than other video processing schemes. The operation time of the system reaches acceptable range, and a solution to meet the real-time requirement is put forward.