Maritime Policy & Management

AI-Driven in Maritime Management

Port and Maritime Security Management

• Risk identification and classification of port operations based on deep learning
• Safety risk identification and emergency decision-making under extreme conditions
• Conflict resolution for responsibility and authority between autonomous berthing systems and traditional pilotage regimes
• Maritime safety supervision based on computer vision and vessel big data
• Multimodal transport risk intelligent identification and anomaly detection

Intelligent Operation and Collaborative Governance of Port and Maritime Systems

• Intelligent collaborative operation strategies for large-scale heterogeneous fleets
• Intelligent scheduling and collaborative control of port production systems
• Resilience of port and shipping networks under emergency events
• Analysis of shipper behavior preferences based on machine learning algorithms

Investment decision-making and risk management in shipping

• Investment decision-making for ship emission control under policy constraints
• Coupled modeling of shipping derivatives pricing and market sentiment
• Shipping price index prediction driven by large language model
• Intelligent pricing strategies for multimodal transport
• Impact of extreme weather events on shipping insurance actuarial analysis

Emissions and Intelligent Regulation of Port and Maritime Systems

• Intelligent optimization of routes for fleets considering integrated energy systems
• UAV-based sniffing and deep learning-based source attribution of emission components
• Data-driven modeling and cost prediction of ship fuel consumption
• Emission reduction pathways and policy design for ports and shipping under multi-agent collaboration and multi-policy coupling

Crew Management and Nautical Education

• AI-driven educational pathway for crew skill transformation in autonomous shipping scenarios
• Edge computing and fatigue driving intervention mechanisms for EEG monitoring of seafarers
• Legal adaptability of crew manning standards and AI-assisted scheduling systems
• Text mining of social media for the identification of mental health risks among seafarers and early intervention

AI Ethics and Institutional Innovation

• Detection and correction policies for racial and cultural biases in maritime AI systems
• Intellectual property allocation and revenue sharing mechanisms for AI training data in the port and shipping sector
• Equity assessment of the diffusion of AI technologies in ports and shipping in developing countries
• Legal standards for algorithmic explainability in determining liability for autonomous vessel accidents
• Application boundaries of AI-assisted legislative tools in the revision of international maritime conventions