Intelligent decision support for marine safety and security operation centres

Surveillance of large volume traffic demands robust and scalable network architectures for distributed information fusion. Operating in an uncertain environment and the ability to flexibly adapt to dynamic changes in resource availabilities are critical for the success of surveillance and rescue missions. In this thesis the architectural design of a decision support system for a Marine Safety and Security Operation Centre (MSOC) is presented. The goal of this system is to improve coordination in emergency response services. The system design emphasizes robustness and scalability through its decentralized control structure, automated planning, dynamic resource configuration management and task execution management under uncertainty. The proposed model is described in abstract functional and operational terms based on the Abstract State Machine (ASM) paradigm and the CoreASM open source tool environment for modeling dynamic properties of the system. An example scenario from the marine operations domain is described in detail, and afterwards, an experimental analysis which evaluates the validity of our system under various scenarios are presented at the end.