Fleet AI Simulation

Fleet AI Simulation uses historical vessel tracks, inspection logs, and synthetic risk scenarios to train robust decision‑making policies via deep reinforcement learning. It accelerates model convergence and improves adaptability in real maritime operations.

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Maritime Digital Twin

Maritime Digital Twin builds a real-time virtual representation of vessels and ports using sensor data, operational logs, and satellite inputs. It enables predictive maintenance, scenario simulation, and compliance tracking, advancing operational efficiency and environmental responsibility.

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Marine Robotics

Marine Robotics explores advanced mechatronics, AI, and control systems to design next-generation autonomous vehicles for marine missions. These include drones and crawlers capable of vertical surface navigation, deep-sea maneuvering, and operations in extreme conditions such as strong currents, confined spaces, or hazardous environments.

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Ocean Data Fusion

Ocean Data Fusion integrates satellite, sonar, drone, sensor, and historical data streams to build real-time ocean intelligence systems. By harmonizing disparate formats and timelines, it supports decision-making across navigation, environmental protection, and maritime operations with high-resolution, predictive insights.

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ESG-AI Models

ESG-AI Models leverage AI to automate compliance checks, assess environmental and social impact, and streamline sustainability reporting for maritime stakeholders. These models analyze operational, sensor, and regulatory data to provide actionable ESG metrics aligned with global standards like IMO, EU MRV, and Poseidon Principles.

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