Recently, trial operation of Material Monitoring Self-diagnosis System has been launched in Shendong Coal.
This system is developed by the AI R&D Taskforce of Software R&D Department of Shendong Coal Intelligent Technology Center. Through AI intelligence image recognition technology, and a series of steps, such as initial material collection, machine learning, model training, algorithm research and optimization, fuzzy scenario analysis model of surveillance camera is finally formed. This system has access to the video monitoring sites of material areas of various units through the security platforms, and automatically diagnoses the current status of monitoring cameras through trained model. In case of abnormal status of cameras, alarm from WeCom will be noticed to the designated monitoring administrators of various units so as to facilitate immediate check and response. This will form a closed loop in the system feedback and keep the material monitoring under real-time and efficient operation.
According to Zhang Peng from the Intelligent Information Office of Material Supply Center, “In order to unify and standardize the management of material monitoring in various units, we have developed a material monitoring self-diagnosis system. The system adopts AI analysis on the current status of monitoring cameras, and is able to send alarm notices on abnormal status to urge the personnel in charge to check and take reasonable responding measures, minimizing the risk of material management loopholes caused by abnormal monitoring”.
