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Enhancing the function of the aids to navigation by practical usage of the deep learning algorithm

Published online by Cambridge University Press:  13 January 2025

Yoontae Sim Open the ORCID record for Yoontae Sim [Opens in a new window]  and
Chong-Ju Chae
Yoontae Sim*
Affiliation:
Division of Navigation safety system, Mopko Maritime University, Mokpo, Korea
Chong-Ju Chae
Affiliation:
Maritime Safety & Environmental Administration (MSEA), World Maritime University, Malmo, Sweden
*
*Corresponding author: Yoontae Sim; Email: 12188@naver.com
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Abstract

Information is provided to navigators through advanced onboard navigation equipment, such as the electronic chart display and information system (ECDIS), radar and the automatic identification system (AIS). However, maritime accidents still occur, especially in coastal and inland water where many navigational dangers exist. The recent artificial intelligence (AI) technology is actively applied in navigation fields, such as collision avoidance and ship detection. However, utilising the aids to navigation (AtoN) system requires more engagement and further exploration. The AtoN system provides critical navigation information by marking the navigation hazards, such as shallow water areas and wrecks, and visually marking narrow passageways. The prime function of the AtoN can be enhanced by applying AI technology, particularly deep learning technology. With the help of this technology, an algorithm could be constructed to detect AtoN in coastal and inland waters and utilise the detected AtoN to create a safety function to supplement watchkeepers using recent navigation equipment.

Keywords

artificial intelligencedeep learning algorithmobject detectionAtoN detection
Type
Research Article
Information
The Journal of Navigation , First View , pp. 1 - 12
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Copyright
Copyright © The Author(s), 2025. Published by Cambridge University Press on behalf of The Royal Institute of Navigation

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