Abstract: The video analysis and identification technology of coal mine safety production is the core technical support to ensure the intelligent construction of our country's coal mines and the high-quality development of the coal industry. In order to carry out real-time monitoring and early warning for potential safety hazards in coal mines, the key technologies of video AI (Artificial Intelligence) identification have become the research hotspot in the field of safety production in coal mines. In this paper, the development status of safety monitoring in the process of intelligent construction of coal mines are first expounded. Then, the problems of low efficiency, slow response and poor effect of the current mine video monitoring and safety hazard identification as well as early warning system are concluded. Combined with advanced technologies such as computer vision, edge computing, big data processing, cloud services, and intelligent terminals, the top-level design of AI recognition for coal mine safety production video is carried out. Furthermore, the “cloud-edge-terminal” collaborative computing system architecture of “human-machine-environment” global video AI perception in coal mines is also proposed, followed with a video recognition end node sensor, edge computing equipment, and video recognition scene cloud service application system constructed. By this way, the intelligent identification and early warning linkage control response mechanism are clarified, and the “cloud-edge-terminal” information interactive perception and linkage control data chain has been dredged, resulting with data sharing linkage and early warning coordination. At the same time, around the construction of the “human-machine-environment” global AI visual information intelligent perception and holographic generalized scene platform, the technical processing process of visual perception and identification and early warning of mine safety hazards has been sorted out. What’s more, the characteristic of the processing-enhancement-reconstruction-detection-recognition method are also summarized, and the mainstream direction and trend of the key technology development of coal mine safety production video AI recognition are also pointed out. Secondly, based on the application cases of representative mines such as Wangjialing Coal Mine and Baodian Coal Mine, the author demonstrates the latest progress and application effects of typical application scenarios in the process of coal mine safety production. Finally, according to the key technology characteristics of coal mine safety production video AI recognition, it is concluded that the existing coal mine safety production video AI recognition system has weak technical theory, different specifications of intelligent terminals, confusing application scenarios, poor data compatibility and linkage closed-loop ability, weak database security, inconsistent evaluation mechanism as well as imperfect application standards, etc. Subsequently, this paper pointed out that the future development direction is to strengthen the research on key technologies and theories of video AI recognition, establish and improve intelligent terminal hardware specifications and applicable systems and build a new coal mine information multi-dimensional active perception model and industrial internet application platform with unified standards, perfect mechanism, real-time interconnection, dynamic prediction, collaborative control, safety and reliability, which gradually form a high-precision intelligent perception field of holographic generalization in the whole mine, so as to realize the precise perception of the underground "human-machine-environment" global video information and the coordinated control of danger sources.