Facing the complex environment of urban rail transit train operations, technologies such as IoT, digital twins, big data, cloud computing, and artificial intelligence are utilized to achieve interconnectivity between trains and equipment. By effectively integrating scenario-based onboard data, trackside detection data, and maintenance business data, the system deeply analyzes the vehicle status characteristics and operational mechanisms of urban rail transit. This forms an intelligent system with capabilities including train status perception and tracking, fault diagnosis and early warning, remaining life prediction, intelligent maintenance decision-making, and automated operations, ensuring safe and reliable train operations, improving efficiency, saving energy, and enabling precise train maintenance management.