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AI-RCAS: A Real-Time Artificial Intelligence Analysis System for Sustainable Fisheries Management

Author

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  • Seung-Gyu Kim

    (Department of Information and Communication Engineering, Hoseo University, 20, Hoseo-ro79beon-gil, Baebang-eup, Asan-si 31499, Republic of Korea)

  • Sang-Hyun Lee

    (Department of Information and Communication Engineering, Hoseo University, 20, Hoseo-ro79beon-gil, Baebang-eup, Asan-si 31499, Republic of Korea)

  • Tae-Ho Im

    (Department of Information and Communication Engineering, Hoseo University, 20, Hoseo-ro79beon-gil, Baebang-eup, Asan-si 31499, Republic of Korea)

Abstract

This study proposes an Artificial Intelligence-based Real-time Catch Analysis System (AI-RCAS) for sustainable fisheries management. The AI-RCAS, implemented on a Jetson board, consists of fish recognition using YOLOv10, tracking with a ByteTrack algorithm optimized for marine environments, and a counting module. Experiments in actual fishing environments showed significant improvements, with species recognition rates of 74–81%. The system supports the efficient operation of the total allowable catch (TAC) system through real-time analysis, addressing the limitations of the existing Electronic Monitoring (EM) systems. However, challenges remain, including object-tracking difficulties and performance issues in unstable marine environments. Future research should focus on optimizing the fishing process, improving video processing, and expanding the dataset for better generalization.

Suggested Citation

  • Seung-Gyu Kim & Sang-Hyun Lee & Tae-Ho Im, 2024. "AI-RCAS: A Real-Time Artificial Intelligence Analysis System for Sustainable Fisheries Management," Sustainability, MDPI, vol. 16(18), pages 1-17, September.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:18:p:8178-:d:1481288
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    References listed on IDEAS

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