Work

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

Year: 2024

Type: article

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.

Source: Sustainability

DOI: 10.3390/su16188178

Authors: Seung-Gyu Kim, Sang-Hyun Lee, Tae-Ho Im

Institution: Hoseo University

Language: English

Topic: Water Quality Monitoring Technologies

Subfield: Water Science and Technology

Field: Environmental Science

Domain: Physical Sciences

SDG: Life below water

Open Access status: gold

Estimated APC paid: $2,728