{"id":159944,"date":"2010-05-01T00:00:00","date_gmt":"2010-05-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/home-heating-using-gps-based-arrival-prediction-2\/"},"modified":"2018-10-16T20:02:32","modified_gmt":"2018-10-17T03:02:32","slug":"home-heating-using-gps-based-arrival-prediction-2","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/home-heating-using-gps-based-arrival-prediction-2\/","title":{"rendered":"Home Heating Using GPS-Based Arrival Prediction"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Home heating is a major factor in worldwide energy use. We describe two experiments aimed at reducing the amount of time heating systems need to be on, without compromising occupants&#8217; comfort. The first resulted in a machine learning algorithm based on GPS data to predict when an occupant will arrive at home. The second examined how long it takes to heat homes based on temperature measurements, telling us how far in advance arrival predictions are needed. Our findings suggest that GPS-based prediction has the potential to reduce home energy consumption compared to existing methods.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Home heating is a major factor in worldwide energy use. We describe two experiments aimed at reducing the amount of time heating systems need to be on, without compromising occupants&#8217; comfort. The first resulted in a machine learning algorithm based on GPS data to predict when an occupant will arrive at home. The second examined [&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":[13562,13552],"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-159944","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-computer-vision","msr-research-area-hardware-devices","msr-locale-en_us"],"msr_publishername":"Microsoft Research","msr_edition":"Proceedings of Pervasive 2010 Workshop on Energy Awareness and Conservation through Pervasive Applications","msr_affiliation":"","msr_published_date":"2010-05-01","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":"207142","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"home_heating_with_gps_Pervasive09workshop_submitted.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/home_heating_with_gps_Pervasive09workshop_submitted.pdf","id":207142,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":207142,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2016\/02\/home_heating_with_gps_Pervasive09workshop_submitted.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"jws","user_id":32459,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=jws"},{"type":"user_nicename","value":"jckrumm","user_id":32203,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=jckrumm"},{"type":"user_nicename","value":"brianme","user_id":31299,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=brianme"},{"type":"user_nicename","value":"ajbrush","user_id":30886,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=ajbrush"},{"type":"user_nicename","value":"akapoor","user_id":30903,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=akapoor"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144794,144633,144767],"msr_project":[170664],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":170664,"post_title":"PreHeat: Controlling Home Heating With Occupancy Prediction","post_name":"preheat-controlling-home-heating-with-occupancy-prediction","post_type":"msr-project","post_date":"2011-03-02 12:43:04","post_modified":"2023-11-28 10:06:40","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/preheat-controlling-home-heating-with-occupancy-prediction\/","post_excerpt":"Home heating uses more energy than any other residential energy expenditure, making increasing the efficiency of home heating an important goal for saving money and protecting the environment. We have built a home-heating system, PreHeat, that automatically programs your thermostat based on when you are home. PreHeat\u2019s goal is to reduce the amount of time a household\u2019s thermostat needs to be on without compromising the comfort of household members. 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