Detection and Identification of Threat Potential of Ships using Satellite Images and AIS Data

This paper addresses the issue of vessel tracking using Automatic Identification Systems (AIS) and imagery data. In general, we depend on AIS data for the accurate tracking of the vessels, but there is often a gap between two consecutive AIS instances of any vessel. This is called as blind period or the inactivity period. In this period, we can not be sure about the location of the ship. The duration of inactivity period is quite variable due to various factors like weather, satellite connectivity and manual turn off. This makes tracking and identification of any threat difficult. In this paper, we propose a two-fold approach for tracking and identifying the potential threat using deep learning models and AIS data. In the first fold, the ships out of satellite imaging are identified while in the second fold. the corresponding AIS data is analysed to discover any potential threat or suspicious activity.