AI-RCAS: A Real-Time Artificial Intelligence Analysis System for Sustainable Fisheries Management
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.
BibTeX
@article{park2024,
title = {AI-RCAS: A Real-Time Artificial Intelligence Analysis System for Sustainable Fisheries Management},
author = {Park, Jeonghwan and Lee, Seung-Woo and Kim, Jinyoung},
journal = {Sustainability},
volume = {16},
number = {18},
pages = {8178},
year = {2024},
publisher = {MDPI},
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.},
}