Deep Learning-Powered Vessel Trajectory Prediction for Improving Smart Traffic Services in Maritime Internet of Things

• Published in: IEEE transactions on network science and engineering Vol. 9; no. 5; pp. 3080 - 3094
• Main Authors: Liu, Ryan Wen, Liang, Maohan, Nie, Jiangtian, Lim, Wei Yang Bryan, Zhang, Yang, Guizani, Mohsen
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.09.2022; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 6G mobile communication; Artificial intelligence; Artificial neural networks; automatic identification system; Collision avoidance; Deep learning; Hidden Markov models; Internet of Things; Machine learning; Maritime Internt of Things; Navigation; Predictive models; Sea vessels; Traffic conflicts; Traffic models; Trajectory; trajectory prediction; vessel traffic services

The maritime Internet of Things (IoT) has recently emerged as a revolutionary communication paradigm where a large number of moving vessels are closely interconnected in intelligent maritime networks. However, the tremendous growth of vessel trajectories, collected from the combined satellite-terres...