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

Abstract

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.

Maritime information sharing environment deployment using the advanced multilayered Data Lake capabilities

“…The proposed methodological framework derives from previously conducted research on advancing and optimizing information sharing processes in the maritime domain, mostly concerning the EU CISE Initiative and developing disruptive technologies in the field of Big Data, Analytics and AI, that support modern business processes and data management ([1], [2], [3]). For this purpose, the overall architecture of the framework is composed of three structural aspects: CISE Model for international maritime collaborations, Big Data Infrastructure for hosting, storing, distribution, and analytics of large data sets, and comprehensive Data Lake architecture with intelligent layers for data processing, querying and retrieval of relevant information to support data exchanges between maritime authorities within CISE Network, as illustrated on Figure 1.…”

Enhancing Maritime Cybersecurity through Operational Technology Sensor Data Fusion: A Comprehensive Survey and Analysis

“…Trajectory-based ML-dynamic algorithms [43,49,50,60,74,82,88,97,123,131,138,140,164,171,174,176,[179][180][181][182]184,186,188,190,191,197,198,200,201,214,228,231,233,235,252] 8.…”