Illegal ship identification system based on trajectory similarity measurement

Abstract

The Automatic Identification System (AIS) relies on the identification code (MMSI) of a vessel to identify it and records its trajectory data, which is an important technical means for modern maritime management. However, there are some vessels that violate regulations by opening multiple AIS transponders, resulting in multiple location trajectory records for the same vessel. This behavior is difficult to distinguish through traditional means and has a negative impact on the accuracy and effectiveness of maritime management, thereby threatening the safety of navigation. This system uses big data processing tool Spark to efficiently process and analyze large amounts of AIS data and detects the similarity of vessel trajectories to automatically identify the violating vessels that open multiple AIS transponders. In this way, the system not only improves the detection efficiency of violations, but also provides more reliable evidence for maritime management departments to ensure the safety and order of navigation routes.