Published June 23, 2022 | Version v1
Conference paper Open

Combined AI Capabilities for Enhancing Maritime Safety in a Common Information Sharing Environment

  • 1. Administration for Maritime Safety and Port Management of Montenegro
  • 2. King College London, United Kingdom
  • 3. Engineering I.I., S.p.A., ENG, Italy
  • 4. Thales Group, France
  • 5. Center for Security Studies, Ministry of Citizen Protection, Greece
  • 6. Secrétariat général de la mer - SGMER, France


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 et al_Bled Conference Paper_Combining AI for mar. safety in CISE_v3.1.pdf

Additional details


EFFECTOR – An End to end Interoperability Framework For MaritimE Situational Awareness at StrategiC and TacTical OpeRations 883374
European Commission