영농형 태양광 시스템에서의 스마트 농업을 위한 의사결정지원시스템A Decision Support System for Smart Farming in Agrophotovoltaic Systems
- Other Titles
- A Decision Support System for Smart Farming in Agrophotovoltaic Systems
- Authors
- 김영진; 소준용; 온영재; 이재윤; 김소정
- Issue Date
- Dec-2022
- Publisher
- 한국산업경영시스템학회
- Keywords
- Agrophotovoltaic; Decision support system; Internet of things; Smart farming
- Citation
- 산업경영시스템학회지, v.45, no.4, pp 180 - 186
- Pages
- 7
- Indexed
- KCI
- Journal Title
- 산업경영시스템학회지
- Volume
- 45
- Number
- 4
- Start Page
- 180
- End Page
- 186
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/22579
- DOI
- 10.11627/jksie.2022.45.4.180
- ISSN
- 2005-0461
2287-7975
- Abstract
- Agrophotovoltaic (APV) system is an integrated system producing crops as well as solar energy. Because crop production underneath Photovoltaic (PV) modules requires delicate management of crops, smart farming equipment such as real-time remote monitoring sensors (e.g., soil moisture sensors) and micro-climate monitoring sensors (e.g., thermometers and irradiance sensors) is installed in the APV system. This study aims at introducing a decision support system (DSS) for smart farming in an APV system. The proposed DSS is devised to provide a mobile application service, satellite image processing, real-time data monitoring, and performance estimation. Particularly, the real-time monitoring data is used as an input of the DSS system for performance estimation of an APV system in terms of production yields of crops and monetary benefit so that a data-driven function is implemented in the proposed system. The proposed DSS is validated with field data collected from an actual APV system at the Jeollanamdo Agricultural Research and Extension Services in South Korea. As a result, farmers and engineers enable to efficiently produce solar energy without causing harmful impact on regular crop production underneath PV modules. In addition, the proposed system will contribute to enhancement of the smart farming technology in the field of agriculture.
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Collections - College of Engineering > Department of Industrial and Systems Engineering > 1. Journal Articles

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