Designing Intelligent Coastal Surveillance based on Big Maritime Data

The ocean is classified into several territorial regimes that span from internal waters, archipelagic waters, territorial seas, contiguous zones, exclusive economic zones (EEZ), and high seas. The relevant state authorities must perform surveillance of all ships that navigate through their respective territories to ensure the ship safety and prevent them from carrying out illegal activities such as illegal unregulated and unreported (IUU) fishing, illegal firearms smuggling, and piracy. Currently, maritime domain surveillance is carried out using a combination of Automatic Identification System (AIS), Coastal Radar System (CRS), and Long Range Camera (LRC). The massive amount of incoming data from these surveillance systems produce big maritime data. However, big maritime data is useless without artificial intelligence intervention. This research proposed an intelligent system that provides and analyzes ship path planning, identifies suspicious ships, track ships, and approaches and attacks target ships using unmanned aerial vehicle (UAV) swarm. Artificial intelligence-based surveillance systems are developed in a single Integrated Coastal Marine Monitoring System, which is expected to perform quickly, precisely, and comprehensively.