What question did this study set out to answer?

The aim is to create a framework that evaluates maritime system health through independent subsystems using AI techniques.

June 2, 2026Open Access

MARISENSE — Maritime Systems Intelligence: Independent Subsystem Modeling and AI-Assisted Maritime System Health Index (MSHI)

Key Points

The aim is to create a framework that evaluates maritime system health through independent subsystems using AI techniques.
Developed a framework that integrates five subsystems: VTS, POS, OES, MSS, and CIS.
Applied AI-assisted calibration and anomaly detection to assess system health.
Created a composite Maritime System Health Index (MSHI) based on aggregated outputs of the subsystems.
Established an AI-enhanced index significantly improves real-time monitoring and operational decision-making.
Demonstrated effective anomaly detection, leading to timely risks mitigation in maritime operations.
Supported by real-time maritime governance applications, enhancing overall safety and efficiency.

Abstract

MARISENSE is a Maritime Systems Intelligence framework that evaluates overall maritime system health through five independent subsystems: Vessel Traffic System (VTS), Port Operations System (POS), Ocean Environmental System (OES), Maritime Safety System (MSS), and Coastal Infrastructure System (CIS). The framework preserves subsystem independence while applying AI-assisted calibration, anomaly detection, and dynamic weighting to aggregate subsystem outputs into a composite Maritime System Health Index (MSHI). MARISENSE supports real-time maritime governance, operational monitoring, risk assessment, anomaly detection, and decision support for ports, coastal authorities, and maritime safety organizations.

MARISENSE — Maritime Systems Intelligence: Independent Subsystem Modeling and AI-Assisted Maritime System Health Index (MSHI)

Key Points

Abstract

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