{"id":166675,"date":"2014-09-01T00:00:00","date_gmt":"2014-09-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/indoor-air-quality-monitoring-system-for-smart-buildings\/"},"modified":"2018-10-16T20:41:48","modified_gmt":"2018-10-17T03:41:48","slug":"indoor-air-quality-monitoring-system-for-smart-buildings","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/indoor-air-quality-monitoring-system-for-smart-buildings\/","title":{"rendered":"Indoor Air Quality Monitoring System for Smart Buildings"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Many developing countries are suffering from air pollution, especially the Particulate Matter with diameter of 2.5 micrometers or less (PM2.5). While quite a few air quality monitoring stations have been built by governments in a city\u2019s public areas, the indoor PM2.5 has not yet been monitored and dealt with effectively. Though many office buildings have a HVAC (heating, ventilation, and air conditioning) system, PM2.5 is not considered as a factor when the system circulates fresh air from outdoors. This paper introduces a real system that we have deployed in the offices of five Microsoft Campuses in China. This system instantly monitors indoor air quality on different floors of a building (including office areas, gyms, garages, and restaurants), enabling Microsoft employees to enquiry the air quality of a place by using a mobile phone or checking a website. The information can guide a user\u2019s decision making, e.g., finding the right time to work out in the gym or turn on individual air filters in her own office. Through analyzing the indoor and outdoor air quality data collected over a long period, our system can even offer actionable and energy-efficient suggestion to HVAC systems, e.g., automatically turning on the system only a few hours earlier than usual if it is a heavily polluted day, or identifying the filters in HVAC system that should be renewed.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Many developing countries are suffering from air pollution, especially the Particulate Matter with diameter of 2.5 micrometers or less (PM2.5). While quite a few air quality monitoring stations have been built by governments in a city\u2019s public areas, the indoor PM2.5 has not yet been monitored and dealt with effectively. Though many office buildings have [&hellip;]<\/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":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-166675","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"Proceedings of the 16th ACM International Conference on Ubiquitous Computing (UbiComp 2014)","msr_affiliation":"","msr_published_date":"2014-09-01","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":"204670","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"Indoor%20air%20quality%20monitoring%20for%20smart%20building.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Indoor20air20quality20monitoring20for20smart20building.pdf","id":204670,"label_id":0},{"type":"file","title":"Indoor%20air%20quality-UbiComp2014-Zheng.pptx","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Indoor20air20quality-UbiComp2014-Zheng.pptx","id":204669,"label_id":0},{"type":"file","title":"Data.zip","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Data-2.zip","id":204668,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":204670,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Indoor20air20quality20monitoring20for20smart20building.pdf"},{"id":204669,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Indoor20air20quality-UbiComp2014-Zheng.pptx"},{"id":204668,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/Data-2.zip"}],"msr-author-ordering":[{"type":"text","value":"Xuxu Chen","user_id":0,"rest_url":false},{"type":"user_nicename","value":"yuzheng","user_id":35088,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=yuzheng"},{"type":"text","value":"Yubiao Chen","user_id":0,"rest_url":false},{"type":"user_nicename","value":"qiwjin","user_id":33314,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=qiwjin"},{"type":"text","value":"Weiwei Sun","user_id":0,"rest_url":false},{"type":"user_nicename","value":"echang","user_id":31709,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=echang"},{"type":"user_nicename","value":"wyma","user_id":34861,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=wyma"}],"msr_impact_theme":[],"msr_research_lab":[199560],"msr_event":[],"msr_group":[],"msr_project":[171316,170824],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":171316,"post_title":"Urban Air","post_name":"urban-air","post_type":"msr-project","post_date":"2014-03-24 02:17:14","post_modified":"2018-04-02 19:26:10","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/urban-air\/","post_excerpt":"Using a diversity of big data to infer and predict fine-grained air quality throughout a city, and finally tackle air pollutions. \u00a0 http:\/\/urbanair.msra.cn\/\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 \u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0Install Mobile Apps Many countries are suffering from air pollutions. Many cities have built a few\u00a0air quality monitoring stations to inform people urban air quality every hour. Influenced by multiple complex factors, however,\u00a0urban air quality is\u00a0highly skewed in a city, varying by locations significantly and changing over time differently in different places.&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/171316"}]}},{"ID":170824,"post_title":"Urban Computing","post_name":"urban-computing","post_type":"msr-project","post_date":"2016-07-03 10:26:01","post_modified":"2018-04-07 17:32:40","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/urban-computing\/","post_excerpt":"Concept\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0\u00a0 (\u4e2d\u6587\u4e3b\u9875) Urban computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face, e.g. air pollution, increased energy consumption and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing technologies, advanced data management and analytics models, and novel visualization methods, to create win-win-win solutions that improve&hellip;","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/170824"}]}}]},"_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166675"}],"collection":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item"}],"about":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/types\/msr-research-item"}],"version-history":[{"count":1,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166675\/revisions"}],"predecessor-version":[{"id":432963,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-item\/166675\/revisions\/432963"}],"wp:attachment":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/media?parent=166675"}],"wp:term":[{"taxonomy":"msr-content-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-content-type?post=166675"},{"taxonomy":"msr-research-highlight","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-research-highlight?post=166675"},{"taxonomy":"msr-research-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/research-area?post=166675"},{"taxonomy":"msr-publication-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-publication-type?post=166675"},{"taxonomy":"msr-product-type","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-product-type?post=166675"},{"taxonomy":"msr-focus-area","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-focus-area?post=166675"},{"taxonomy":"msr-platform","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-platform?post=166675"},{"taxonomy":"msr-download-source","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-download-source?post=166675"},{"taxonomy":"msr-locale","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-locale?post=166675"},{"taxonomy":"msr-post-option","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-post-option?post=166675"},{"taxonomy":"msr-field-of-study","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-field-of-study?post=166675"},{"taxonomy":"msr-conference","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-conference?post=166675"},{"taxonomy":"msr-journal","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-journal?post=166675"},{"taxonomy":"msr-impact-theme","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-impact-theme?post=166675"},{"taxonomy":"msr-pillar","embeddable":true,"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-pillar?post=166675"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}