Revolutionizing Marine Traffic Management: A Comprehensive Review of Machine Learning Applications in Complex Maritime Systems
Irmina Durlik, Tymoteusz Miller, Lech Dorobczyński, Polina Kozlovska, Tomasz Kostecki
Abstract
This review article explores the applications and impacts of Machine Learning (ML) techniques in marine traffic management and prediction within complex maritime systems. It provides an overview of ML techniques, delves into their practical applications in the maritime sector, and presents an in-depth analysis of their benefits and limitations. Real-world case studies are highlighted to illustrate the transformational impact of ML in this field. The article further provides a comparative analysis of different ML techniques and discusses the future directions and opportunities that lie ahead. Despite the challenges, ML’s potential to revolutionize marine traffic management and prediction, driving safer, more efficient, and more sustainable operations, is substantial. This review article serves as a comprehensive resource for researchers, industry professionals, and policymakers interested in the interplay between ML and maritime systems.