Enhance the Efficiency and Safety of Intelligent Coal Transportation Ports with AI and Big Data
Lin Li, Jiapeng Yan, Lei Meng, Huashi Liu, Chenxu Hao, Delin Zhao, Yongnian Huang · 2024
This research addresses the challenges of large data volume, low utilization efficiency, and insufficient analysis and processing in the study and practice of intelligent ports. Focusing on a port for coal transportation, the study employs artificial intelligence processing algorithms as its core. It leverages existing advanced equipment and management systems to enhance the value of big data. The research establishes a framework for distributed data collection, heuristic production scheduling, and efficient anomaly detection. Based on this technology, the system achieves the goal of comprehensively and accurately reflecting the port's operational situation, avoiding the safety hazards of spontaneous coal combustion and significantly improving operational efficiency.