{"id":766744,"date":"2021-08-12T11:16:09","date_gmt":"2021-08-12T18:16:09","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=766744"},"modified":"2023-03-30T07:28:43","modified_gmt":"2023-03-30T14:28:43","slug":"indoor-location-competition-2-0-dataset","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/indoor-location-competition-2-0-dataset\/","title":{"rendered":"Indoor Location Competition 2.0 Dataset"},"content":{"rendered":"

Microsoft sponsored and co-organized Indoor Location Competition 2.0 in 2021. 1446 contestants from more than 60 countries making up 1170 teams participated in this unique global event. In this competition, a first-of-its-kind large-scale indoor location benchmark dataset was released. The dataset for this competition consists of dense indoor signatures of WiFi, geomagnetic field, iBeacons etc., as well as ground truth (waypoint) (locations) collected from hundreds of buildings in Chinese cities. The data found in path trace files (*.txt) corresponds to an indoor path between position p_1 and p_2 walked by a site-surveyor.<\/p>\n

During the walk, an Android smartphone is held flat in front of the surveyors body, and a sensor data recording app is running on the device to collect IMU (accelerometer, gyroscope) and geomagnetic field (magnetometer) readings, as well as WiFi and Bluetooth iBeacon scanning results. A detailed description of the format of trace file is shown, along with other details and processing scripts, at this GitHub link (opens in new tab)<\/span><\/a>. In addition to raw trace files, floor plan metadata (e.g., raster image, size, GeoJSON) are also included for each floor.<\/p>\n

More details on the competition including winning solutions can be found on our Kaggle competition site (opens in new tab)<\/span><\/a>.<\/p>\n

Download from<\/strong><\/span> Kaggle (opens in new tab)<\/span><\/a><\/p>\n

\"graphical<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"

Microsoft sponsored and co-organized Indoor Location Competition 2.0 in 2021. 1446 contestants from more than 60 countries making up 1170 teams participated in this unique global event. In this competition, a first-of-its-kind large-scale indoor location benchmark dataset was released. The dataset for this competition consists of dense indoor signatures of WiFi, geomagnetic field, iBeacons etc., […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":null,"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"","msr_organization":"","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2021-1-1","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13556,13547],"msr-publication-type":[193724],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-766744","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2021-1-1","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/aka.ms\/location20dataset","label_id":"243109","label":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Yuanchao Shu","user_id":35079,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Yuanchao Shu"},{"type":"text","value":"Qiang Xu","user_id":0,"rest_url":false},{"type":"text","value":"Jie Liu","user_id":0,"rest_url":false},{"type":"text","value":"Romit Roy Choudhury","user_id":0,"rest_url":false},{"type":"text","value":"Niki Trigoni","user_id":0,"rest_url":false},{"type":"user_nicename","value":"Victor Bahl","user_id":31167,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Victor Bahl"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144899],"msr_project":[389828],"publication":[],"video":[],"msr-tool":[766738],"msr_publication_type":"miscellaneous","related_content":{"projects":[{"ID":389828,"post_title":"Path Guide: Plug-and-play Indoor Navigation","post_name":"path-guide-plug-play-indoor-navigation","post_type":"msr-project","post_date":"2017-06-11 00:32:41","post_modified":"2019-01-15 15:51:15","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/path-guide-plug-play-indoor-navigation\/","post_excerpt":"Path Guide is a completely plug-and-play indoor navigation service that does not require maps or any additional equipment. 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