{"created":"2026-01-09T02:19:15.311428+00:00","links":{},"updated":"2026-01-15T01:47:01.255661+00:00","id":2006758,"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:02006758","sets":["581:1765244505933:1765245307659"]},"path":["1765245307659"],"owner":"80578","recid":"2006758","title":["Keypoint検出を用いた萎れ定量化によるエッジ型自動灌水制御の提案"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2026-01-15"},"_buckets":{"deposit":"863e1cd3-bd0f-4631-9b4b-494bfb6c510d"},"_deposit":{"id":"2006758","pid":{"type":"depid","value":"2006758","revision_id":0},"owner":"80578","owners":[80578],"status":"published","created_by":80578},"item_title":"Keypoint検出を用いた萎れ定量化によるエッジ型自動灌水制御の提案","author_link":[],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Keypoint検出を用いた萎れ定量化によるエッジ型自動灌水制御の提案","subitem_title_language":"ja"},{"subitem_title":"Proposal for Edge-based Automatic Irrigation Control by Quantification of Wilting Using Keypoint Detection","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"[一般論文（推薦論文）] スマート農業，自動灌水制御，深層学習，YOLO，Keypoint検出","subitem_subject_scheme":"Other"}]},"item_type_id":"2","publish_date":"2026-01-15","item_2_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"静岡大学大学院総合科学技術研究科"},{"subitem_text_value":"静岡大学情報学部"},{"subitem_text_value":"株式会社Happy Quality"},{"subitem_text_value":"サンファーム中山株式会社"},{"subitem_text_value":"株式会社Happy Quality"},{"subitem_text_value":"静岡大学学術院情報学領域／静岡大学グリーン科学技術研究所"}]},"item_2_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate School of Integrated Science and Technology, Shizuoka University","subitem_text_language":"en"},{"subitem_text_value":"Faculty of Informatics, Shizuoka University","subitem_text_language":"en"},{"subitem_text_value":"Happy Quality Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Sun Farm Nakayama Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"Happy Quality Co., Ltd.","subitem_text_language":"en"},{"subitem_text_value":"College of Informatics, Academic Institute, Shizuoka University / Research Institute of Green Science and Technology, Shizuoka University","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/2006758/files/IPSJ-JNL6701012.pdf","label":"IPSJ-JNL6701012.pdf"},"date":[{"dateType":"Available","dateValue":"2028-01-15"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-JNL6701012.pdf","filesize":[{"value":"2.8 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"660","billingrole":"5"},{"tax":["include_tax"],"price":"330","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"8"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"7a6fa02c-d3f6-403a-a19a-5ac62a85b74e","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2026 by the Information Processing Society of Japan"}]},"item_2_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"大沼,理巧"}]},{"creatorNames":[{"creatorName":"小池,誠"}]},{"creatorNames":[{"creatorName":"古田,祐樹"}]},{"creatorNames":[{"creatorName":"玉井,大悟"}]},{"creatorNames":[{"creatorName":"宮地,誠"}]},{"creatorNames":[{"creatorName":"峰野,博史"}]}]},"item_2_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Riku Ohnuma","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Makoto Koike","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Yuki Furuta","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Daigo Tamai","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Makoto Miyachi","creatorNameLang":"en"}]},{"creatorNames":[{"creatorName":"Hiroshi Mineno","creatorNameLang":"en"}]}]},"item_2_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AN00116647","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_2_publisher_15":{"attribute_name":"公開者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"item_2_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-7764","subitem_source_identifier_type":"ISSN"}]},"item_2_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，農作物の品質向上や安定供給を実現するため，熟練農家の高度な栽培技術をICTで再現・自動化する研究が進められている．トマト栽培においては，土壌水分量や茎径変化量の測定値に基づく自動灌水制御が提案されているが，これらのセンサは高価であり，普及の課題となっている．そこで，著者らは安価なカメラを用いて植物の動画を収集し，動画から葉の動きをトラッキングすることで植物体の萎れを定量化し自動灌水制御を実現する研究に取り組んできたが，計算コストが高くクラウド型でしか実現できないという課題が残っていた．本研究では，Keypoint検出を用いた軽量な萎れ定量化手法を組み込んだ，エッジ型自動灌水制御システムを提案する．動画データが必要な物体追跡モデルではなく，画像データを入力とするKeypoint検出に基づく葉の萎れ定量化モデルを構築することにより，エッジデバイス上での動作を可能とした．提案手法を組み込んだ自動灌水制御システムを圃場に設置して動作させた結果，平均12.9秒で萎れ指標を算出できることを確認した．加えて，提案手法の有効性を実証するための栽培実験を実施し，熟練農家が栽培した果実と同程度の廃棄割合で栽培できたことに加え，実験開始前の果実と比較して0.77Brixの糖度向上が確認できた．","subitem_description_type":"Other"}]},"item_2_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In recent years, research has been conducted to reproduce and automate the advanced cultivation techniques of skilled farmers using ICT in order to improve the quality of agricultural products and realize a stable supply. In tomato cultivation, automatic irrigation control based on measurements of soil moisture and stem diameter change has been proposed, but these sensors are expensive, and their widespread use has been a challenge. The authors proposed a method to estimate the amount of water in a plant by tracking leaves and quantifying wilting to perform automatic irrigation, but it is computationally expensive and can only be implemented in a cloud-based system. In this study, we propose an edge-type automatic irrigation control system that incorporates a lightweight wilt quantification method using keypoint detection. Instead of an object tracking model that requires video data, a leaf wilting estimation model based on keypoint detection is constructed using image data as input, enabling the system to operate on edge devices. We installed and operated an automatic irrigation system incorporating the proposed method in a field, and confirmed that the system was able to calculate the wilting index in 12.9 seconds on average. Furthermore, we conducted a demonstration experiment in which tomatoes were cultivated using the proposed automatic irrigation control method. As a result of the experiment, it was confirmed that the fruits could be grown with the same level of waste ratio as those grown by experienced farmers, and that the sugar content increased by 0.77 Brix compared to the fruits before the experiment started, suggesting the effectiveness of the proposed method.","subitem_description_type":"Other"}]},"item_2_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"104","bibliographic_titles":[{"bibliographic_title":"情報処理学会論文誌"}],"bibliographicPageStart":"92","bibliographicIssueDates":{"bibliographicIssueDate":"2026-01-15","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"67"}]},"relation_version_is_last":true,"item_2_identifier_registration":{"attribute_name":"ID登録","attribute_value_mlt":[{"subitem_identifier_reg_text":"10.20729/0002006758","subitem_identifier_reg_type":"JaLC"}]},"weko_creator_id":"80578"}}