{"updated":"2025-01-19T20:57:17.101263+00:00","links":{},"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00202278","sets":["6164:6165:6640:10055"]},"path":["10055"],"owner":"44499","recid":"202278","title":["ニューラルネットワークを用いた大規模イベント向けBLE屋内位置推定の比較評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2019-06-26"},"_buckets":{"deposit":"0f2d35c0-fe42-4ca2-b8e9-709af06f7830"},"_deposit":{"id":"202278","pid":{"type":"depid","value":"202278","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"ニューラルネットワークを用いた大規模イベント向けBLE屋内位置推定の比較評価","author_link":["496193","496192","496190","496191"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"ニューラルネットワークを用いた大規模イベント向けBLE屋内位置推定の比較評価"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"位置情報システム","subitem_subject_scheme":"Other"}]},"item_type_id":"18","publish_date":"2019-06-26","item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"jpn"}]},"item_18_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"名古屋大学大学院工学研究科"},{"subitem_text_value":"名古屋大学大学院工学研究科"},{"subitem_text_value":"名古屋大学大学院工学研究科"},{"subitem_text_value":"名古屋大学大学院工学研究科／名古屋大学未来社会創造機構"}]},"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/202278/files/IPSJ-DICOMO2019006.pdf","label":"IPSJ-DICOMO2019006.pdf"},"date":[{"dateType":"Available","dateValue":"2021-06-26"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2019006.pdf","filesize":[{"value":"3.4 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":"44"}],"accessrole":"open_date","version_id":"e18ecb35-b879-4a58-bdac-05cb5bbda02f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2019 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"浦野, 健太"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"廣井, 慧"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"米澤, 拓郎"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"河口, 信夫"}],"nameIdentifiers":[{}]}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_5794","resourcetype":"conference paper"}]},"item_18_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"本稿では，移動する BLE タグからのパケットを環境内の複数のスキャナで受信し，受信信号強度を使う BLE 屋内位置推定において，ニューラルネットワークを用いた手法を考える．無線電波を使う位置推定では，受信信号強度の不安定さが精度に影響する．そこで，Fingerprint や三点測位に代わり，ニューラルネットワークの利用が試みられており，精度の改善が報告されている．一方で，多数の人がいる実環境への対応可能性は十分検証されていない．そこで本稿では，(1)デノイジングオートエンコーダと既存手法を組み合わせた位置推定と，(2)ニューラルネットワークによる End-to-end の位置推定を比較し，高精度に推定できる手法を検討する．(1) では，受信信号強度からノイズ除去や欠損値の補完を行い既存手法で位置推定を行う．(2) は全結合層と LSTM 層からなり，受信信号強度の時系列を用いて位置推定を行う．ネットワークの学習時は，単純なシミュレーションで生成したデータでの学習の後，実環境で収集したデータで追加の学習を行う．大規模展示会での実験データでの評価では，デノイジングオートエンコーダと既存手法の組合わせは精度で劣り，End-to-end のニューラルネットワークのほうが良い精度で推定を行えた．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"35","bibliographic_titles":[{"bibliographic_title":"マルチメディア,分散協調とモバイルシンポジウム2019論文集"}],"bibliographicPageStart":"29","bibliographicIssueDates":{"bibliographicIssueDate":"2019-06-26","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2019"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":202278,"created":"2025-01-19T01:04:51.132391+00:00"}