Application of AIS data for monitoring and detecting anomalous vessel behavior at sea

Trà Văn Đồng; Nguyễn Thu Nguyệt Minh; Lý Hải Sơn

Issue: Số 23 - Tháng 8 - 2026 Khoa học - Kỹ thuật

Application of AIS data for monitoring and detecting anomalous vessel behavior at sea

Published: September 7, 2026

Abstract

This study develops a system for monitoring and detecting anomalous vessel behavior at sea using Automatic Identification System (AIS) data. The system continuously processes vessel position, speed, and course data and combines machine-learning, prediction, and DBSCAN clustering methods to identify deviations from normal navigation patterns and generate alerts. Actual vessel trajectories are compared with predicted trajectories according to predefined thresholds for position, speed, and heading. Experimental results show that the system achieves anomaly-detection accuracy of up to 95%, with an average detection time of less than five seconds. The application also supports real-time visualization, vessel-status classification, and comparison between actual and predicted routes. The findings demonstrate the potential of AIS-based analytics to support real-time maritime surveillance and early detection of abnormal vessel behavior.

Keywords

automatic identification system DBSCAN maritime surveillance anomaly detection

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