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

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.

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Publication Details

Journal
Sustainability
Published
2024-09-19
DOI
https://doi.org/10.3390/su16188178
Citations
12
Primary Topic
Water Quality Monitoring Technologies
Type
article
Field-Weighted Citation Impact
2.42

Funders

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article

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

Taeho Im, Sang‐Hyun Lee, Seung-Gyu Kim
12 citations
Sustainability
Water Quality Monitoring Technologies
2.42
article

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

Taeho Im, Sang‐Hyun Lee, Seung-Gyu Kim
article en
12 citations

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.

SustainabilityVol. 16(18)
Hoseo University (KR)
Ministry of Oceans and Fisheries, Korea Institute of Marine Science and Technology promotion, Ministry of Science and ICT, South Korea, Institute for Information and Communications Technology Promotion, Division of Human Resource Development
Life below water
Openalex Percentile: Top 12%
Water Quality Monitoring Technologies
2.42
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AI-RCAS: A Real-Time Artificial Intelligence Analysis System for Sustainable Fisheries Management — Taeho Im, Sang‐Hyun Lee, et al. · Sustainability (2024) | TGRS Research Map | TGRS