{"created":"2023-06-20T16:50:41.702293+00:00","id":23257,"links":{},"metadata":{"_buckets":{"deposit":"22171d18-1a4c-45d2-b8f6-d50c1b3a248a"},"_deposit":{"created_by":3,"id":"23257","owners":[3],"pid":{"revision_id":0,"type":"depid","value":"23257"},"status":"published"},"_oai":{"id":"oai:kindai.repo.nii.ac.jp:00023257","sets":["14:2667:4819"]},"author_link":["30541"],"control_number":"23257","item_8_biblio_info_21":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2021","bibliographicIssueDateType":"Issued"},"bibliographicPageEnd":"10","bibliographicPageStart":"1","bibliographic_titles":[{"bibliographic_title":"科学研究費助成事業研究成果報告書 (2021)"}]}]},"item_8_description_25":{"attribute_name":"リンクURL","attribute_value_mlt":[{"subitem_description":"https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-19K06323/","subitem_description_type":"Other"}]},"item_8_description_33":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"研究成果の概要（和文）：園芸施設環境計測制御データの高度利用目的で，正常環境状態を学習した深層学習モデルを使い，施設の点検・保守に役立つ高度監視システムを開発した．学習済モデルを内蔵したRaspberry PiをUECSで環境制御された施設LANに接続し，正常状態の環境予測値を毎分出力させ，実測値との偏差から異常発生をリアルタイム検知可能にした．実証試験の結果，環境計測異常値や植物成育異常の観察だけで検知が難しい，計測制御異常の検出が可能であった．また，培養液高度管理を支援する深層学習応用システムの開発用学習データセット整備のため，生産作物の養水分吸収量を1分ごとに自動計測する自作可能UECSノードを開発した．\n研究成果の概要（英文）： For the advanced utilization of environmental measurement and control data, an intelligent monitoring system for inspection and maintenance of greenhouses using a deep learning (DL) model has been discussed. The DL model has learned normal greenhouse environment from the big-data record. A Raspberry Pi installed the learned DL model is attended to a greenhouse LAN with working the Ubiquitous Environment Control System (UECS), and compares predicted values by DL with measured real values every minute. The results of a demonstration tests confirmed that the system was able to detect delicate control abnormalities that are difficult to detect only by observing abnormal environmental measurement values and abnormal plant growth. A UECS node that automatically measures the amount of water and fertilizer absorbed by crops every minute was also designed and developed. The utilization as the training data sets for DL applications for advanced nutrient management in hydroponics is expected.","subitem_description_type":"Abstract"}]},"item_8_description_36":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"研究種目：基盤研究(C); 研究期間：2019～2021; 課題番号：19K06323; 研究分野：植物生産工学, 植物環境調節工学, 農業情報工学; 科研費の分化・細目：","subitem_description_type":"Other"}]},"item_8_description_37":{"attribute_name":"資源タイプ(WEKO2)","attribute_value_mlt":[{"subitem_description":"Research Paper","subitem_description_type":"Other"}]},"item_8_description_41":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_8_publisher_14":{"attribute_name":"出版者 名前","attribute_value_mlt":[{"subitem_publisher":"近畿大学"}]},"item_8_text_10":{"attribute_name":"著者 役割","attribute_value_mlt":[{"subitem_text_value":"研究代表者"}]},"item_8_text_7":{"attribute_name":"著者(英)","attribute_value_mlt":[{"subitem_text_language":"en","subitem_text_value":"Hoshi, Takehiko"}]},"item_8_text_8":{"attribute_name":"著者 所属","attribute_value_mlt":[{"subitem_text_value":"近畿大学生物理工学部; 教授"}]},"item_8_text_9":{"attribute_name":"著者所属(翻訳)","attribute_value_mlt":[{"subitem_text_value":"Kindai University"}]},"item_8_version_type_12":{"attribute_name":"版","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_be7fb7dd8ff6fe43","subitem_version_type":"NA"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"星, 岳彦"},{"creatorName":"ホシ, タケヒコ","creatorNameLang":"ja-Kana"}],"nameIdentifiers":[{},{}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2022-12-05"}],"displaytype":"detail","filename":"19K06323seika.pdf","filesize":[{"value":"1.1 MB"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"label":"19K06323seika.pdf","url":"https://kindai.repo.nii.ac.jp/record/23257/files/19K06323seika.pdf"},"version_id":"2f4013a2-06ee-48b6-8e45-60614af2be7e"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"培養液管理システム","subitem_subject_scheme":"Other"},{"subitem_subject":"エッジコンピューティング","subitem_subject_scheme":"Other"},{"subitem_subject":"保守管理","subitem_subject_scheme":"Other"},{"subitem_subject":"環境制御システム","subitem_subject_scheme":"Other"},{"subitem_subject":"高度異常監視","subitem_subject_scheme":"Other"},{"subitem_subject":"Raspberry Pi","subitem_subject_scheme":"Other"},{"subitem_subject":"深層学習モデル","subitem_subject_scheme":"Other"},{"subitem_subject":"UECS","subitem_subject_scheme":"Other"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"research report","resourceuri":"http://purl.org/coar/resource_type/c_18ws"}]},"item_title":"深層学習による園芸施設環境モニタリングデータからの高次情報の抽出","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"深層学習による園芸施設環境モニタリングデータからの高次情報の抽出","subitem_title_language":"ja"},{"subitem_title":"Extraction of high-order information by deep learning from environment monitoring data on greenhouses","subitem_title_language":"en"}]},"item_type_id":"8","owner":"3","path":["4819"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2022-12-05"},"publish_date":"2022-12-05","publish_status":"0","recid":"23257","relation_version_is_last":true,"title":["深層学習による園芸施設環境モニタリングデータからの高次情報の抽出"],"weko_creator_id":"3","weko_shared_id":-1},"updated":"2023-08-01T02:29:56.353362+00:00"}