2020 Fiscal Year Final Research Report
Development of mini pipe greenhouse cultivation support systems to hand down ventilation judgment of diligent farmers.
| Project/Area Number |
17K08024
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Agricultural environmental engineering/Agricultural information engineering
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| Research Institution | Anan National College of Technology |
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Principal Investigator |
Yoshida Susumu 阿南工業高等専門学校, 創造技術工学科, 教授 (10607310)
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| Co-Investigator(Kenkyū-buntansha) |
白石 和章 鳥羽商船高等専門学校, その他部局等, 准教授 (40442454)
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| Project Period (FY) |
2017-04-01 – 2021-03-31
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| Keywords | フィールドモニタリング / 独立電源 / 農業ICT |
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| Outline of Final Research Achievements |
In the carrot cultivation for the shipment of the Tokushima special product in the spring and summer, I developed the perforator amount of ventilation judgment support system for farmers using the environmental data and growth information in mini pipe greenhouses.
The result of this study, I developed the remote camera system for the growth judgment in the greenhouse and tested the temperature environment judgment proof in the greenhouse by the AI from the photograph of the leaf. Furthermore, I developed the system which displayed quantity of temperature, humidity and sunlight data measured using the low-priced environmental sensor for the mini pipe greenhouse by a Web browser. In addition, I developed the system which put “an estimated multiplication temperature graph at the standard cultivation” on “the multiplication temperature graph by measurements” and could display. Therefore, cultivation farmers became able to conjugate in the amount of ventilation judgment of greenhouses.
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| Free Research Field |
農業情報工学
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| Academic Significance and Societal Importance of the Research Achievements |
電源の無い圃場での簡易施設であるミニパイプハウス栽培において，生育状況と栽培環境をモニタリングできる独立電源を含めた低価格モニタリングシステムを開発した. 生育状況リモートカメラシステムと画像強化学習によりハウス内温度環境判断を可能とした．また，農研機構「メッシュ農業気象データ」と，NEDO「年間月別日射量データベース」を用いて，試験圃場での栽培実績から作成したハウス内気温推定モデルより，播種日からの標準栽培時の推定ハウス内日積算気温データを算出しグラフ化，環境センサで測定した温度・日射量データからハウス内日積算気温グラフと重ねて確認でき，ハウス温度管理判断支援可能なシステムを開発した．
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