Ship AIS data will be integrated with both static information (ship metadata, traffic infrastructures, pilot data, etc.) and dynamic conditions (traffic flow, ocean environment, schedules, etc.) by developing data fusion methods, to describe more precisely multi-dimensional marine traffic environments. Based on the AIS fused marine traffic data, feature engineering, data analytics and AI techniques will be developed and organized as a systematical AI-architecture to detect both real-time and historical ship sailing anomalies. Then, innovative visualization techniques are researched and developed to store and present the large volume of multi-dimensional marine traffic flow and detected anomalies in an interactive manner, which can be exploited and fast cross-check specific anomalies for practical maritime applications.