스마트미디어저널 (Smart Media Journal)

  • 제13권2호
  • /
  • Pages.16-22
  • /
  • 2024
  • /
  • 2287-1322(pISSN)
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  • 2288-9671(eISSN)
한국스마트미디어학회 (THE KOREAN INSTITUTE OF SMART MEDIA)
권호 표지

Predicting Desired Fertigation for Rose Using Internet of Things Sensors and Time-Series Model

  • Mingle Xu (Department of Electronics Engineering, Jeonbuk National University) ;
  • Sook Yoon (Department of Computer Engineering, Mokpo National University) ;
  • Jongbin Park (Department of Electronics Engineering, Jeonbuk National University) ;
  • Jeonghyun Baek (Rural Development Administration) ;
  • Dong Sun Park (Department of Electronics Engineering, Jeonbuk National University)
  • 투고 : 2023.10.16
  • 심사 : 2023.12.21
  • 발행 : 2024.02.29
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초록

Greenhouse provides opportunities to have big yield effectively and efficiently. However, many resources are required, such as fertigation, a kind of solution of nutrient. Resources supply is essential to cultivate crops. Inadequate supply will hinder plant growth whereas the surplus results in waste. In this paper, we are especially interested in the fertigation supply. Further, excess fertigation leads to drainage which is difficult to purify and threatens the environment. To address this challenge, we aim to predict the desired amount of fertigation. To achieve this objective, we first establish a prototype to record the climate conditions inside a rose greenhouse using Internet of Things sensors. Simultaneously, the desired fertigation amount is obtained with the help of weight scale and historical data of fertigation supply and drainage. Second, a method is proposed to predict the desired fertigation by taking the sensors' data as input, with a time-series model. Extensive experimental results suggest the potential of our objective and method. To be specific, our method achieves an average MAE 0.032 in the validation datasets.

키워드

과제정보

This work was partially supported by the Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) and Korea Smart Farm R&D Foundation (KosFarm) through the Smart Farm Innovation Technology Development Program, funded by the Ministry of Agriculture, Food and Rural Affairs (MAFRA) and Ministry of Science and ICT (MSIT), Rural Development Administration (RDA) (1545027177). This research was partially supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (No. 2019R1A6A1A09031717). This work was partially supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (No. 2021R1A2C1012174).

참고문헌

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