Mining ship spatial trajectory patterns from AIS database for maritime surveillance

Abstract

With the development of AIS (Automatical Identification System), more and more ships are equipped with AIS. The messages transmitted by AIS have thus become an abundant and inexpensive source of information for maritime surveillance. In view of this, this paper applied Electronic Chart System (ECS), database management, Data Warehouse (DW) and Data Mining (DM) technologies to facilitate the discovery of hidden and valuable information in a huge amount of AIS data. With enlighten of business intelligence, Association Rules Algorithm is applied to deal with discovering the ship trajectory pattern. The results show that the knowledge mined by this paper is interesting to maritime safety administration. The application domain can range from current Vessel Traffic Service (VTS), maritime surveillance, marine traffic engineering, ship's behavior and traffic flow study to homeland security.