Combined AI Capabilities for Enhancing Maritime Safety in a Common Information Sharing Environment
The complexity of maritime traffic operations indicates an unprecedented necessity for joint introduction and exploitation of artificial intelligence (AI) technologies, that take advantage of the vast amount of vessels’ data, offered by disparate surveillance systems to face challenges at sea. This paper reviews the recent Big Data and AI technology implementations for enhancing the maritime safety level in the common information sharing environment (CISE) of the maritime agencies, including vessel behavior and anomaly monitoring, and ship collision risk assessment. Specifically, the trajectory fusion implemented with InSyTo module for soft information fusion and management toolbox, and the Early Notification module for Vessel Collision are presented within EFFECTOR Project. The focus is to elaborate technical architecture features of these modules and combined AI capabilities for achieving the desired interoperability and complementarity between maritime systems, aiming to provide better decision support and proper information to be distributed among CISE maritime safety stakeholders.
Paladin, Zdravko; Kapidani, Nexhat; Lukšić, Žarko; Mihailović, Andrej; Scrima, Piero; Jacobé de Naurois, Charlotte; Laudy, Claire; Rizogiannis, Constantinos; Astyakopoulos, Alkiviadis; and Blum, Alexis, "Combined AI Capabilities for Enhancing Maritime Safety in a Common Information Sharing Environment" (2022). Bled 2022 Proceedings. 31.