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Conference Paper
Design and Implementation of an AI-Based Smart Aquaculture System for Feeding Optimization and Automated Farm Management
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- Authors
- Jaeyoung Kim, Dongseung Shin, Laekyoung Lee
- Issue Date
- 2026-07
- Citation
- International Conference on Embedded Technology and Artificial Intelligence (ICETA) 2026, pp.1-2
- Publisher
- 대한임베디드공학회
- Language
- English
- Type
- Conference Paper
- Abstract
- Smart aquaculture technologies are becoming increasingly important for improving productivity and reducing operational costs. This paper presents the design and implementation of an AI-based smart aquaculture system integrating fish monitoring, feeding optimization, and automated feeding control. The proposed system collects environmental data, aquaculture operation records, and fish-related information through a unified platform. An edge-based control system automatically manages feeding devices and tank facilities according to operational conditions. A prototype system was implemented and deployed in a commercial aquaculture environment. The results demonstrate the feasibility of integrating artificial intelligence, IoT sensing, and automated control technologies for practical aquaculture management.
- Keyword
- Smart Aquaculture, Artificial Intelligence, Edge Computing, Automated Feeding
- KSP Keywords
- Aquaculture system, Edge Computing, Edge-based, Environmental data, Operational costs, Prototype system, artificial intelligence, automated control, design and implementation, farm management, feeding control