AI-ENABLED DIGITAL TWINS FOR SAFETY-CRITICAL MARITIME CYBER-PHYSICAL SYSTEMS

T
Dr.Chandrasekaran Venkatesan
Assistant Professor,
Department of Marine Engineering,
Vels Institute of Science, Technology and Advanced Studies,
Chennai, Tamil Nadu, India.
he maritime industry faces unprecedented challenges in maintaining
operational safety and efficiency as autonomous systems and digital
connectivity reshape shipping operations. This paper presents a
comprehensive survey of AI-enabled digital twin architectures for maritime
cyber-physical systems, with emphasis on safety-critical applications in autonomous and
highly automated vessels. Digital twins—virtual replicas of physical ships integrated with
real-time sensor data, AI algorithms, and predictive analytics—enable unprecedented
capabilities in predictive maintenance, route optimization, and dynamic risk management.
However, their deployment in safety-critical environments introduces novel cybersecurity
vulnerabilities, regulatory compliance gaps, and verification challenges. This paper
systematically reviews: (1) current digital twin technologies deployed in maritime
operations; (2) AI-driven decision-making frameworks for autonomous navigation and
propulsion systems; (3) cyber-physical security threats and mitigation strategies; (4) IMO
MASS Code and regulatory alignment; and (5) future research directions for assured
autonomy. Through case studies from leading port authorities (Rotterdam, Hamburg,
Amsterdam) and shipping operators, we identify architectural best practices, edge
computing integration, and safety verification methodologies. We propose a unified
framework for AI-enabled maritime cyber-physical systems that balances innovation with
safety assurance, regulatory compliance, and human oversight. This survey provides
researchers, maritime engineers, and policy makers with a comprehensive understanding of
digital twin technologies' transformative potential while highlighting critical gaps requiring
future investigation.