Development of an integrated and visualized platform for railway freight information management in support of intelligent transportation management

With the continuous growth of railway freight volumes and the rapid evolution of logistics systems, traditional railway freight management models face numerous challenges such as data silos, information opacity, and low scheduling efficiency. To address the urgent need for information integration and visualization in intelligent transportation management, this paper proposes and develops an integrated and visualized platform for railway freight information management tailored to intelligent transportation management. The platform is based on multi-source heterogeneous data fusion technology, integrating key business information such as railway transportation, scheduling, and equipment status to build a unified data integration middleware. This enables the collection, processing, and sharing of information throughout the entire railway freight process. Building on this foundation, the platform combines big data analysis and intelligent decision-making models to provide core functions such as freight flow prediction, congestion identification, and transportation optimization, supporting scientific scheduling and emergency response. The system integrates visualization tools such as GIS maps and dynamic charts to comprehensively display transportation status and business indicators, providing managers with intuitive and efficient decision-making support tools. The platform has been piloted in actual business scenarios, verifying its significant effects in enhancing the intelligent management level of railway freight transportation, optimizing transportation processes, and enhancing system visibility, providing strong support for the future construction of a smart logistics system.