- The system provides precise insights into global shipping operations, enabling better port management and sustainable resource planning.
- An AI model accurately detects illegal fishing by analyzing vessel trajectories, offering a cost-effective alternative to traditional patrols.
- Advanced data integration and machine learning improve vessel behavior classification, emissions monitoring, and navigation safety.
- These innovations enhance operational efficiency and support Hong Kong’s role as a major international maritime center.
Researchers at The Hong Kong Polytechnic University (PolyU) have developed new technologies to improve the global maritime industry. Led by the Maritime Data and Sustainable Development Centre (PMDC), these innovations use artificial intelligence and big data. They apply machine learning, computer vision, and real-time data analysis to tackle challenges in vessel monitoring, port congestion, and maritime regulation, as reported by OpenGov Asia – CIO Network Pte Ltd.
Advanced AI and Data Technologies for Maritime Operations
The center has developed an AI system to estimate supply and demand for typhoon shelter berths in Hong Kong. Typhoon shelters protect vessels during severe weather, making accurate planning essential. The system utilizes drones to capture images of vessels, which are then analyzed by deep learning computer vision with 98.6% accuracy. This allows automatic ship identification and classification, predicting berth usage from 2022 to 2035. The tool improves berth management and emergency response by providing real-time shelter occupancy data. It reduces manual monitoring time and supports digital maritime infrastructure. The Hong Kong Marine Department has adopted this system to enhance facility planning and regulation.
Another key innovation is a maritime data analytics platform that processes AIS data to deliver real-time port congestion and shipping connectivity indicators. Unlike traditional methods, this platform uses big data algorithms to provide detailed, up-to-date insights into port operations. Developed with Tsinghua University, it aids both broad trade analysis and detailed vessel tracking, enabling timely and informed decision-making.
Improving Maritime Operations and Enforcement with AI and Big Data
The system uses a multi-level global shipping database to provide accurate insights into port turnover and connectivity. This digital platform helps maritime stakeholders monitor operations and quickly address logistics issues. It supports better resource management and long-term sustainable development in shipping.
In maritime enforcement, researchers developed an AI model to detect illegal fishing with up to 90% accuracy. The model uses vessel trajectory data and a semi-supervised machine learning approach to recognize abnormal fishing behavior. This method improves upon traditional patrols, offering a scalable and cost-effective monitoring solution.
The trajectory analysis distinguishes vessel behaviors across navigation states without extensive manual labeling. It also aids emissions monitoring and risk assessment. In partnership with local authorities, the team used AIS, radar, and CCTV data to study cruise ship movements. Applying graph neural networks, they improved vessel trajectory forecasting for better real-time navigation safety.
These advancements demonstrate the value of AI and big data in automating analysis, improving accuracy, and boosting efficiency. PolyU’s research supports Hong Kong’s strategic maritime goals and strengthens its position as a leading international maritime hub.
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Source: OpenGovAsia
