Abstract: As a traditional high-risk industry, mining faces severe challenges to safe production arising from its complex working environment. Although the establishment of a dual-prevention mechanism combining risk classification and control with hazard identification and remediation has led to a declining trend in the total number of accidents, the existing safety management model still faces prominent bottlenecks, including insufficient accuracy in risk identification and assessment, inadequate depth and breadth in hazard identification and remediation, and technology application lagging behind the requirements of the management system. To address these issues, this study develops a mine safety intelligent-control dual-system platform based on the deep integration of intelligent technology and the safety management system. The platform integrates advanced technologies such as the Internet of Things, big data analytics, and artificial intelligence. Through the digital reengineering of core business processes such as risk classification and control as well as hazard identification and remediation, the platform enables dynamic assessment and precise classification of mine safety risks, as well as intelligent identification and closed-loop remediation of hazards. The results overcome the limitations of traditional management approaches, address the problems of inadequate implementation of safety responsibilities and delayed risk control, and provide scientific and efficient technical support and a decision-making basis for mining enterprises to achieve intrinsic safety and intelligent transformation and upgrading.