Title: A Study for Development of Route Prediction Method for Vessel using Machine Learning

Issue Number: Vol. 9, No. 4
Year of Publication: Dec - 2019
Page Numbers: 203-207
Authors: Jumpei MATSUE, Kotetsu KAWAKAMI, Ryota ISOZAKI, Shunsuke INADA, Masashi SUGIMOTO, Shinji TSUZUKI, Kazuhiko NAGAO
Journal Name: International Journal of Digital Information and Wireless Communications (IJDIWC)
- Hong Kong

Abstract:


Nowadays, vessels such as cargo vessels, ferries, and fishing boats are constantly coming and going on all over the sea. On the other hands, unfortunately, collisions among vessels account for about one-quarter of the total accidents. In this paper, small boats such as fishing boats and pleasure boats that is not required to mount Automatic Identification System (AIS) has been focused on. In detail, a module for LoRa (Long Range) wireless, which is one of the LPWA (Low Power, Wide Area) standards, and a GPS module are mounted on a small vessel. Moreover, machine learning is used to determine by predicting the navigation route, a system to avoid collisions between ships has been considered.