Research on the Recognition of Multiple MMSI Codes on a Single Vessel Based on AIS Datas

Abstract

With the development of the maritime economy and the widespread adoption of the Automatic Identification System (AIS), the number of vessels at sea has surged. Unfortunately, some vessels illicitly alter their Maritime Mobile Service Identity (MMSI) codes for personal gain, posing challenges to port management. Currently, the detection of “Multiple MMSI on a Single Vessel” vessels still relies on manual inspections by relevant authorities. This paper proposes a “Multiple MMSI on a Single Vessel” detection model based on Automatic Identification System (AIS) datas. It employs interval sampling combined with cosine similarity to enhance the accuracy and efficiency of identifying such vessels. This technology finds broad applications in port management, safety, vessel regulation, and maritime law enforcement. The paper sets the similarity threshold at 0.7, a distance threshold at 2.7 n mile, and a time threshold at 3 s. Experimental results demonstrate that the model achieves an average detection accuracy of 92.25%. Therefore, the proposed model effectively and accurately detects “Multiple MMSI on a Single Vessel” illegal vessels, significantly enhancing the efficiency of port and maritime management authorities. This model proves to be a rational and efficient solution.

Keywords

• Automatic identification systems (AISs)
• cosine similarity
• equidistant sampling
• multiple MMSI on a single vessel
• vessel monitoring
• datas analysis