{"_buckets": {"deposit": "a30b3516-f58b-438a-bb5f-2f1e9c76b0cc"}, "_deposit": {"id": "13541", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "13541"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00013541", "sets": ["322"]}, "author_link": ["42733", "42734", "42735", "42736", "42737", "42738"], "item_10_alternative_title_19": {"attribute_name": "その他のタイトル", "attribute_value_mlt": [{"subitem_alternative_title": "A Wireless LAN Location Estimation Method Based on Gaussian Mixture Model", "subitem_alternative_title_language": "en"}]}, "item_10_biblio_info_6": {"attribute_name": "書誌情報", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-03-15", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "3", "bibliographicPageEnd": "1081", "bibliographicPageStart": "1069", "bibliographicVolumeNumber": "52", "bibliographic_titles": [{"bibliographic_title": "情報処理学会論文誌", "bibliographic_titleLang": "ja"}]}]}, "item_10_description_4": {"attribute_name": "抄録", "attribute_value_mlt": [{"subitem_description": "モバイル端末の普及や,家庭や公共施設などへの無線LAN アクセスポイントの設置個所の増加にともない,屋内・屋外を問わず電波を受信可能な無線LAN情報を利用した位置推定手法が注目されている.一般に屋内における位置推定のアプリケーションでは屋外に比べて高い精度が細かい時間幅で要求される.しかし従来の無線LAN位置推定手法では,推定精度を向上させるためには非常に大規模なデータベースが必要であり,かつ膨大な計算量が必要であるという課題がある.そこで本研究では,まず大規模な無線LANデータベースをGaussian Mixture Model(GMM)によって表現することで,無線LAN情報のデータ量を従来の95%以上削減する手法を提案する.次に,計算量を調整可能な Particle Filterを用いた位置推定手法を提案する.評価実験を実施した環境では,本手法により6〜10m程度の精度でのリアルタイム位置推定が可能であった. ", "subitem_description_language": "ja", "subitem_description_type": "Abstract"}, {"subitem_description": "Recently, location estimation systems using WLAN are getting popular, because WLAN access points are widely introduced to general houses and public facilities. We can receive the signal of WLAN regardless of indoor and outdoor, so that WLAN is available for indoor location estimation. Conventional researches of location estimation have a problem that needs a huge WLAN database and a large computation. In this paper, we propose a modeling method of WLAN database using Gaussian Mixture Model (GMM) and a location estimation method using particle filter. Consequently, we succeeded in reducing the amount of WLAN data to about 5%. In this time\u0027s experiment environment, accuracy of realtime location estimation was about 6〜10m.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/15440"}]}, "item_10_publisher_32": {"attribute_name": "出版者", "attribute_value_mlt": [{"subitem_publisher": "一般社団法人情報処理学会", "subitem_publisher_language": "ja"}]}, "item_10_rights_12": {"attribute_name": "権利", "attribute_value_mlt": [{"subitem_rights": "ここに掲載した著作物の利用に関する注意 本著作物の著作権は（社）情報処理学会に帰属します。本著作物は著作権者である情報処理学会の許可のもとに掲載するものです。ご利用に当たっては「著作権法」ならびに「情報処理学会倫理綱領」に従うことをお願いいたします。 Notice for the use of this material The copyright of this material is retained by the Information Processing Society of Japan (IPSJ). This material is published on this web site with the agreement of the author (s) and the IPSJ. Please be complied with Copyright Law of Japan and the Code of Ethics of the IPSJ if any users wish to reproduce, make derivative work, distribute or make available to the public any part or whole thereof. All Rights Reserved, Copyright (C) Information Processing Society of Japan. Comments are welcome. Mail to address editj\u003cat\u003eipsj.or.jp, please.", "subitem_rights_language": "ja"}]}, "item_10_select_15": {"attribute_name": "著者版フラグ", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "0387-5806", "subitem_source_identifier_type": "PISSN"}]}, "item_1615787544753": {"attribute_name": "出版タイプ", "attribute_value_mlt": [{"subitem_version_resource": "http://purl.org/coar/version/c_970fb48d4fbd8a85", "subitem_version_type": "VoR"}]}, "item_access_right": {"attribute_name": "アクセス権", "attribute_value_mlt": [{"subitem_access_right": "open access", "subitem_access_right_uri": "http://purl.org/coar/access_right/c_abf2"}]}, "item_creator": {"attribute_name": "著者", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "藤田, 迪", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "42733", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "梶, 克彦", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "42734", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "河口, 信夫", "creatorNameLang": "ja"}], "nameIdentifiers": [{"nameIdentifier": "42735", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Fujita, Susumu", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "42736", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Kaji, Katsuhiko", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "42737", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "Kawaguchi, Nobuo", "creatorNameLang": "en"}], "nameIdentifiers": [{"nameIdentifier": "42738", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "ファイル情報", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-20"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "fujita-ipsjjournal2010.pdf", "filesize": [{"value": "2.7 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_note", "mimetype": "application/pdf", "size": 2700000.0, "url": {"label": "fujita-ipsjjournal2010.pdf", "objectType": "fulltext", "url": "https://nagoya.repo.nii.ac.jp/record/13541/files/fujita-ipsjjournal2010.pdf"}, "version_id": "0d08e930-d5bb-47d7-a167-93b62e9fb872"}]}, "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": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "Gaussian Mixture Model を用いた無線LAN位置推定手法", "item_titles": {"attribute_name": "タイトル", "attribute_value_mlt": [{"subitem_title": "Gaussian Mixture Model を用いた無線LAN位置推定手法", "subitem_title_language": "ja"}]}, "item_type_id": "10", "owner": "1", "path": ["322"], "permalink_uri": "http://hdl.handle.net/2237/15440", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2011-09-06"}, "publish_date": "2011-09-06", "publish_status": "0", "recid": "13541", "relation": {}, "relation_version_is_last": true, "title": ["Gaussian Mixture Model を用いた無線LAN位置推定手法"], "weko_shared_id": -1}