Composite Event Recognition for Maritime Monitoring
This work addresses maritime safety and security for shipping authorities and monitoring systems, but it is incremental as it applies an existing event recognition method to a specific domain with new patterns.
The paper tackled the problem of detecting dangerous and illegal vessel activities in maritime monitoring by developing a system using the Run-Time Event Calculus and a library of maritime patterns, achieving effective recognition as evaluated with real-world datasets for predictive accuracy and computational efficiency.
Maritime monitoring systems support safe shipping as they allow for the real-time detection of dangerous, suspicious and illegal vessel activities. We present such a system using the Run-Time Event Calculus, a composite event recognition system with formal, declarative semantics. For effective recognition, we developed a library of maritime patterns in close collaboration with domain experts. We present a thorough evaluation of the system and the patterns both in terms of predictive accuracy and computational efficiency, using real-world datasets of vessel position streams and contextual geographical information.