An Integrated Maritime Safety and Security Monitoring System Using IoT, Geofencing, and Artificial Intelligence

Abstract

Maritime operations require timely and accurate information to deal with navigation hazards, equipment problems, route deviations and unauthorized vessel movements. The study proposes a comprehensive maritime safety and security monitoring system that integrates Internet of Things (IoT) sensors, GPS-based geofencing and artificial intelligence to monitor vessel position and sensor data, track the safe navigation and maritime zones and use an AI model to detect and categorize abnormal events. The system provides a central dashboard that displays vessel status, alerts and historical incident history for human decision making. The research design is based on a development process for requirements analysis and system development, prototype development, testing and final evaluation by an expert team. The technical performance was evaluated based on functional success rate, geofence accuracy, false-alert rate, missed-event rate and alert response time. The AI component is evaluated by accuracy, precision, recall, F1-score and confusion matrix and the software quality is evaluated based on the characteristics of ISO/IEC 25010:2023. As per the literature of the last few years, the baseline performance of the system was 96.67% functional success, 95.00% geofence accuracy and 93.50% AI classification accuracy. This standard is set as an assessment benchmark to compare the results to the real prototype testing. As a practical solution to enhance maritime situational awareness, propose to integrate real-time sensing, location monitoring and intelligent risk analysis were done. It is intended as an additional tool for decision-making and not as an alternative to navigation systems or professional maritime judgment.