Advanced human-machine teaming could transform maritime operations through holonic human cyber-physical systems. By creating digital counterparts for crew, equipment and processes, cooperative autonomous elements enable richer decision support and human-condition monitoring. The concept reveals how smarter collaboration between people and technology may enhance safety, performance and operational effectiveness at sea.

AMARIS is pioneering joint maritime and aviation emergency training by connecting previously separate ship and helicopter simulation environments into a shared operational scenario. Combining cross-domain simulation with human factors research, the initiative enhances communication, coordination and decision-making, offering a scalable, cost-effective approach to improving preparedness for complex search and rescue operations

Autonomous SWATH vessels could transform offshore wind farm maintenance by combining hybrid fuel cell-battery propulsion with highly stable hull designs optimised for harsh operating environments. Through numerical modelling and Shetland-based case studies, the research demonstrates superior operational availability, stability and ROV deployment performance versus conventional monohulls, supporting safer, more sustainable offshore operations.

Maritime cybersecurity is becoming a strategic imperative as digital dependence grows across critical waterways. Combining bridge simulators, eye-tracking technology and AI-driven risk assessment, this research explores human and technical responses to cyber-attacks in the Turkish Straits. The findings aim to strengthen resilience, improve training and inform future maritime security policy.

Human-centred design is emerging as a critical enabler of next-generation maritime systems. Using divergent and convergent thinking across the design lifecycle, researchers demonstrate how deeper understanding of user needs and human-system interactions can improve safety, functionality and operational effectiveness, offering a practical framework for more resilient maritime innovation overall today.

As maritime systems grow more complex through automation, alternative fuels and advanced mission requirements, understanding vessel-wide impacts of failures becomes increasingly challenging. This research introduces an AI-enabled decision support system that leverages functional architectures to assess mission feasibility, guide recovery actions and enhance situational awareness, offering a powerful tool for safer, more resilient naval operations.

Digital twins are transforming maritime engineering by connecting virtual ship models with real-world operational data. Drawing on advances in simulation, IoT, AI and cloud technologies, this research traces the evolution from virtual prototyping to lifecycle-wide digital twins, revealing new opportunities to enhance design, training, maintenance, operational performance and long-term asset management.

Predictive motion analysis is advancing the safe deployment of crewed and uncrewed air and sea vehicles at sea. By combining real-time ship motion forecasting, deck-condition sensing and integrated simulation, new approaches improve launch and recovery operations, support autonomous systems, and enable predictive maintenance, enhancing safety, reliability and operational effectiveness.

Predictive motion analysis is advancing the safe deployment of crewed and uncrewed air and sea vehicles at sea. By combining real-time ship motion forecasting, deck-condition sensing and integrated simulation, new approaches improve launch and recovery operations, support autonomous systems, and enable predictive maintenance, enhancing safety, reliability and operational effectiveness.

Digital collaboration is becoming essential to the future of European shipbuilding. As specialist shipyards increasingly rely on partnerships and subcontracting, interoperable digital twins and shipbuilding-specific lifecycle management technologies are enabling secure information sharing, reducing collaboration risks and strengthening competitiveness in the delivery of complex, innovation-driven maritime programmes.

Advanced defect detection techniques are enhancing maritime reliability by transforming operational time-series data into machine-learning-ready visual representations. Combining Gramian Angular Fields, Recurrence Plots and Markov Transition Fields with convolutional neural networks, the approach improves fault classification accuracy, demonstrating how AI-driven analytics can strengthen quality assurance, maintenance strategies and operational safety.

Shipbuilding organisations are increasingly turning to Product Lifecycle Management to manage growing design complexity, traceability requirements and supplier networks. Drawing on implementation experience, this perspective outlines practical foundations for shipbuilding-specific PLM adoption, highlighting how integrated digital processes can improve collaboration, visibility and lifecycle control while reducing reliance on fragmented tools and expertise.