The automatic identification system of maritime accident risk using rule-based reasoning

Abstract

Current maritime traffic monitoring systems are not sufficiently adapted to the identification of maritime accident risk. It is very difficult for operators responsible for monitoring traffic to identify which vessels are at risk among all the shipping traffic displayed on their screen. They are overwhelmed by huge amount of kinematic ship data to be decoded. To improve this situation, this paper proposes a system for the automatic identification of maritime accident risk. The system consists of two modules. The first automates expert knowledge acquisition through the computerized exploration of historical maritime data, and the second provides a rule-based reasoning mechanism.