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논문 기본 정보

자료유형
학술대회자료
저자정보
Moonsun Shin (Konkuk University) Seonmin Hwang (Bizforce) Kyeongja Jeong (Chungcheong University) Seongwon Lee (Chungbuk National University)
저널정보
한국정보통신학회 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING 2024 INTERNATIONAL CONFERENCE ON FUTURE INFORMATION & COMMUNICATION ENGINEERING Vo.15 No.1
발행연도
2024.1
수록면
217 - 220 (4page)

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초록· 키워드

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The domestic and international smart farm market is showing a growth rate of more than 10% every year, and the smart farm market in the livestock sector is also expected to grow significantly. The smart agriculture based on ICT convergence technology is entering the stage of basic technology development and growth. In various applications, there is entering the stage of basic technology development and growth. In various applications, there is an increasing number of cases where deep learning, machine learning, big data, etc. are used to achieve results such as maximizing productivity and improving management efficiency. It is necessary to build an intelligent livestock management system by incorporating cutting-edge ICT convergence to improve productivity, reduce costs, and secure quality competitiveness. In this paper, we propose a smart livestock farming monitoring framework applying deep learning technologies for intelligent livestock management system.

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Abstract
Ⅰ. INTRODUCTION
Ⅱ. SMART MONITORING FRAMEWORK
Ⅲ. AI-based MONITORING of LIVESTOCK BEHAVIOR STATUS
Ⅳ. CONCLUSIONS
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