{"id":585133,"date":"2019-05-07T11:58:58","date_gmt":"2019-05-07T18:58:58","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=585133"},"modified":"2020-11-17T12:09:33","modified_gmt":"2020-11-17T20:09:33","slug":"demo-video-analytics-killer-app-for-edge-computing","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/demo-video-analytics-killer-app-for-edge-computing\/","title":{"rendered":"Demo: Video Analytics – Killer App for Edge Computing"},"content":{"rendered":"
The world is witnessing an unprecedented increase in camera deployment. The USA and UK, for instance, have one camera for every 8 people. Video analytics from these cameras are becoming more and more pervasive, exerting important functions on a wide range of verticals including manufacturing, transportation, and retails. While vision techniques have seen considerable advancement, they have come at the expense of compute and network cost.<\/p>\n
As an alternative to the centralized, in-the-cloud compute paradigm, edge computing offers the promise of near real-time insights, faster localized actions, and cost reduction because of efficient data management and operations. We believe video analytics may represent the \u201ckiller application\u201d for edge computing due to its demanding requirements on compute, bandwidth and latency. In this demo, we showcase a live video analytics system that spans across the cloud and edge, with low cost, and produces results with high accuracy.<\/p>\n","protected":false},"excerpt":{"rendered":"
The world is witnessing an unprecedented increase in camera deployment. The USA and UK, for instance, have one camera for every 8 people. Video analytics from these cameras are becoming more and more pervasive, exerting important functions on a wide range of verticals including manufacturing, transportation, and retails. While vision techniques have seen considerable advancement, […]<\/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":[246574],"research-area":[13547],"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-585133","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-highlight-award","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2019-6-17","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":"MobiSys Best Demo Runner-up Award","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":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/05\/MobiSys19demo_EVA.pdf","id":"585136","title":"mobisys19demo_eva","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[{"id":585136,"url":"https:\/\/www.microsoft.com\/en-us\/research\/uploads\/prod\/2019\/05\/MobiSys19demo_EVA.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Ganesh Ananthanarayanan","user_id":31834,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ganesh Ananthanarayanan"},{"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"},{"type":"user_nicename","value":"Landon Cox","user_id":37527,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Landon Cox"},{"type":"user_nicename","value":"Alex Crown","user_id":30817,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Alex Crown"},{"type":"user_nicename","value":"Shadi Noghabi","user_id":37760,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Shadi Noghabi"},{"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"}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[144899],"msr_project":[382664,212082],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":382664,"post_title":"Microsoft Rocket for Live Video Analytics","post_name":"live-video-analytics","post_type":"msr-project","post_date":"2017-05-15 08:28:48","post_modified":"2020-11-22 08:59:49","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/live-video-analytics\/","post_excerpt":"Project Rocket's goal is to democratize video analytics: build a system for real-time, low-cost, accurate analysis of live videos. This system will work across a geo-distributed hierarchy of intelligent edges and large clouds, with the ultimate goal of making it easy and affordable for anyone with a camera stream to benefit from video analytics.","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/382664"}]}},{"ID":212082,"post_title":"Edge Computing","post_name":"edge-computing","post_type":"msr-project","post_date":"2020-02-23 16:44:03","post_modified":"2020-11-12 19:40:46","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/edge-computing\/","post_excerpt":"Industries ranging from manufacturing to healthcare are eager to develop real-time control systems that use machine learning and artificial intelligence to improve efficiencies and reduce cost. 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