Ship trajectory prediction based on Automatic Identification System (AIS) data has attracted
increasing interest as it helps prevent collision accidents and eliminate potential …

The growing availability of maritime IoT traffic data and continuous expansion of the
maritime traffic volume, serving as the driving fuel, propel the latest Artificial Intelligence (AI) …

Maritime transport faces new safety challenges in an increasingly complex traffic
environment caused by large-scale and high-speed ships, particularly with the introduction …

This paper presents a deep learning method for the prediction of ship motions in 6 Degrees
of Freedom (DoF). Big data streams of Automatic Identification System (AIS), now-cast, and …

In order to improve the navigation ability of vessels and ensure the safety of maritime traffic,
vessel trajectory prediction plays a crucial role in the intelligent navigation and collision …

The revolutionary progress of deep learning and data mining technology has greatly
contributed to the rapid development of maritime Internet of Things. In order to advance …

The extraction of ship behavior patterns from Automatic Identification System (AIS) data and
the subsequent prediction of travel routes play crucial roles in mitigating the risk of ship …

With multi-dimensional exploration toward oceans, enormous sensing data has been
generated with significant volume, velocity, variety, and heterogeneity. The resulting big …

In a world increasingly interconnected by advanced technologies, we have become reliant
on the ubiquitous networks that bind our devices, our services, and, indeed, our lives. As …

This thesis proposes an approach to predict vessel tracks in waterways using a Bidirectional
Long Short-Term Memory (Bi-LSTM) model as well as a transformer model. For this purpose …