{"updated":"2025-01-19T17:51:14.530663+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00211281","sets":["1164:3865:10488:10574"]},"path":["10574"],"owner":"44499","recid":"211281","title":["電波強度に基づく位置推定モデルの再学習方式"],"pubdate":{"attribute_name":"公開日","attribute_value":"2021-05-20"},"_buckets":{"deposit":"61e344a0-bb87-4111-bc23-205c27c96d64"},"_deposit":{"id":"211281","pid":{"type":"depid","value":"211281","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"電波強度に基づく位置推定モデルの再学習方式","author_link":["536507","536506","536511","536510","536508","536509"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"電波強度に基づく位置推定モデルの再学習方式"},{"subitem_title":"Retraining method of signal strength based model for indoor positioning","subitem_title_language":"en"}]},"item_type_id":"4","publish_date":"2021-05-20","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"株式会社日立製作所研究開発グループ"},{"subitem_text_value":"株式会社日立製作所研究開発グループ"},{"subitem_text_value":"株式会社日立製作所研究開発グループ "}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Hitachi, Ltd., Research & Development Group","subitem_text_language":"en"},{"subitem_text_value":"Hitachi, Ltd., Research & Development Group","subitem_text_language":"en"},{"subitem_text_value":"Hitachi, Ltd., Research & Development Group","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"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/211281/files/IPSJ-MBL21099001.pdf","label":"IPSJ-MBL21099001.pdf"},"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-MBL21099001.pdf","filesize":[{"value":"2.3 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"35"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_login","version_id":"76e6c414-cee3-4794-b85c-f0eae64e90d5","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2021 by the Institute of Electronics, Information and Communication Engineers This SIG report is only available to those in membership of the SIG."}]},"item_4_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"山本, 正明"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"栗山, 裕之"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"永松, 健司"}],"nameIdentifiers":[{}]}]},"item_4_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Masaaki, Yamamoto","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Hiroyuki, Kuriyama","creatorNameLang":"en"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"Kenji, Nagamatsu","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_4_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA11851388","subitem_source_identifier_type":"NCID"}]},"item_4_textarea_12":{"attribute_name":"Notice","attribute_value_mlt":[{"subitem_textarea_value":"SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc."}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_18gh","resourcetype":"technical report"}]},"item_4_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"2188-8817","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"近年，COVID-19 (新型コロナウィルス感染症) の感染拡大に伴い，感染拡大防止と業務継続の両立に向けてオフィスワーカーの勤務場所が多様化した．そこで，在宅勤務であるかどうか，出社勤務であればどの座席を利用したかを自動記録する技術に注目が集まっている．これらの状況を鑑みて，従業員が利用した座席を推定する位置推定システムを開発した．そして，機械学習を使った位置推定モデルを簡便に再学習する方法を検討し，オフィスでの有効性検証を実施した．具体的には，スマートフォンの機種と保持状態に起因した位置推定誤りを低減するため，従業員毎のスマートフォンの機種と保持状態に合わせて位置推定モデルを更新する方法を提案した．そし て，オフィスでの実験により，提案方式の位置推定誤差は 2.6～3.0m であり，機種による位置推定誤差を 3.1～3.3m 低減し，保持状態による位置推定誤差を 0.9～1.0m 低減可能であることを明らかにした．","subitem_description_type":"Other"}]},"item_4_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"Covid-19 is continuing to spread around the world. Office workers therefore work in several sites to balance work and prevetation of its. A positioning system for estimating worker’s positions is attracting considerable attention. Given this background, we propose a machine-learning based positioning method. In this method, a positioning model is generated from the training data measured by smartphones. The model estimates a worker’s position from the test data measrured by worker’s smartphone. When the training data and the test data were measured by using different types of smartphones, a positioning error increased. In addition, a different holding state of smartphone increased the error, too. To reduce the error, we propose a method to update the training data according to the holding states and the types of smartphones.The evaluation of the proposed method was done with RMSE (Root Mean Square Error) as a metric. When using different holding states and the type of smartphone, RMSE of the method was reduced to 2.6 to 3.0m.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"4","bibliographic_titles":[{"bibliographic_title":"研究報告モバイルコンピューティングと新社会システム（MBL）"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2021-05-20","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"1","bibliographicVolumeNumber":"2021-MBL-99"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"created":"2025-01-19T01:12:27.962278+00:00","id":211281,"links":{}}