{"id":179003,"updated":"2025-01-20T04:54:23.132802+00:00","links":{},"created":"2025-01-19T00:48:17.381789+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00179003","sets":["1164:4061:9092:9142"]},"path":["9142"],"owner":"11","recid":"179003","title":["階層認識の高度化とシームレス測位の効率化"],"pubdate":{"attribute_name":"公開日","attribute_value":"2017-05-18"},"_buckets":{"deposit":"36084974-8d74-4bc6-bb87-80bfd5bfe326"},"_deposit":{"id":"179003","pid":{"type":"depid","value":"179003","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"階層認識の高度化とシームレス測位の効率化","author_link":["385001","384999","385003","385000","384997","385002","384998","385004"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"階層認識の高度化とシームレス測位の効率化"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"測位・センシング技術","subitem_subject_scheme":"Other"}]},"item_type_id":"4","publish_date":"2017-05-18","item_4_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"立命館大学大学院情報理工学研究科"},{"subitem_text_value":"立命館大学総合科学技術研究機構"},{"subitem_text_value":"立命館大学情報理工学部"},{"subitem_text_value":"立命館大学情報理工学部"}]},"item_4_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"Graduate 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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":"2188-8698","subitem_source_identifier_type":"ISSN"}]},"item_4_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"スマートフォンなどの携帯端末のセンサを活用した位置情報サービスやコンテキストアウェアサービスの提供が期待されている.本研究では屋内外シームレスな測位手法において GPS の無駄な動作の削減を目的として,スマートフォンに搭載された Wi-Fi や GPS,気圧センサなどのデバイスを組み合わせることにより,建物の階層間の高さや Wi-Fi 基地局設置階層が既知の建物では高精度な階層推定手法を,未知の建物では屋外と接続された階層かどうかを学習 ・ 推定する手法を提案する.既知の建物における階層推定手法では Wi-Fi と気圧センサを組み合わせることで平均 96% の精度で階層を推定できることを示した.未知の建物における屋外と接続された階層かどうかを学習 ・ 推定する手法では,同一階層に設置された Wi-Fi 基地局を学習し GPS 受信状態からラベル付けを行うことで推定が行えることを示した.","subitem_description_type":"Other"}]},"item_4_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"8","bibliographic_titles":[{"bibliographic_title":"研究報告ユビキタスコンピューティングシステム(UBI)"}],"bibliographicPageStart":"1","bibliographicIssueDates":{"bibliographicIssueDate":"2017-05-18","bibliographicIssueDateType":"Issued"},"bibliographicIssueNumber":"11","bibliographicVolumeNumber":"2017-UBI-54"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}