{"metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00219803","sets":["6164:6165:6640:11008"]},"path":["11008"],"owner":"44499","recid":"219803","title":["複数Wi-Fi機器のCSIを用いた行動推定手法の評価"],"pubdate":{"attribute_name":"公開日","attribute_value":"2022-07-06"},"_buckets":{"deposit":"27e6ab62-fc54-4153-9e40-cd1c628ed83c"},"_deposit":{"id":"219803","pid":{"type":"depid","value":"219803","revision_id":0},"owners":[44499],"status":"published","created_by":44499},"item_title":"複数Wi-Fi機器のCSIを用いた行動推定手法の評価","author_link":["573672","573674","573673","573671","573669","573670","573668"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"複数Wi-Fi機器のCSIを用いた行動推定手法の評価"}]},"item_type_id":"18","publish_date":"2022-07-06","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":"静岡大学情報学部"},{"subitem_text_value":"NTTドコモ"},{"subitem_text_value":"日本電信電話株式会社"},{"subitem_text_value":"NTTドコモ"},{"subitem_text_value":"静岡大学情報学部"},{"subitem_text_value":"愛知工業大学情報科学部"},{"subitem_text_value":"静岡大学情報学部"}]},"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/219803/files/IPSJ-DICOMO2022229.pdf","label":"IPSJ-DICOMO2022229.pdf"},"date":[{"dateType":"Available","dateValue":"2024-07-06"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-DICOMO2022229.pdf","filesize":[{"value":"1.7 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":"5790ecdf-952b-4099-8a68-e5e12407b54f","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2022 by the Information Processing Society of Japan"}]},"item_18_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"寺本, 京祐"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"斎藤, 隆仁"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"池田, 大造"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"太田, 賢"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"西村, 雅史"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"水野, 忠則"}],"nameIdentifiers":[{}]},{"creatorNames":[{"creatorName":"峰野, 博史"}],"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":"近年のスマートホーム化や IoT などの発展によって，日常行動のセンシングが注目されている．行動推定手法として人が映らないことによるプライバシー保護やコスト削減が図れる Wi-Fi CSI ベースの手法が研究されている．先行研究においては，屋内における簡単な人の動きを CSI で推定可能であることが報告されている．しかし，先行研究では一度に推定可能な行動数は限られており，収集可能な行動範囲についても非常に狭いという課題がある．そこで，本研究では 2 台の CSI 受信機から日常生活で想定される行動を推定することを目標とする．提案手法では，2 台の CSI 受信機を用いて CSI を収集し，ノイズ除去を実施する．また，推定精度を上げるため，ノイズ除去による信号の歪みが抑えられるスペクトログラムによる画像化を行う．使用する学習モデルは画像認識分野で使用されている CNN と近年画像認識分野で注目されている ViT を用いて性能比較を行った．結果，人の有無を推定する基礎実験において，CNN モデルの交差検証の精度が 92% となった．","subitem_description_type":"Other"}]},"item_18_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"1658","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2022論文集"}],"bibliographicPageStart":"1651","bibliographicIssueDates":{"bibliographicIssueDate":"2022-07-06","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"2022"}]},"relation_version_is_last":true,"weko_creator_id":"44499"},"id":219803,"updated":"2025-01-19T14:46:31.321816+00:00","links":{},"created":"2025-01-19T01:19:51.762279+00:00"}