{"id":153074,"date":"2007-06-04T00:00:00","date_gmt":"2007-06-04T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/location-and-mobility-in-a-sensor-network-of-mobile-phones\/"},"modified":"2018-10-16T20:43:44","modified_gmt":"2018-10-17T03:43:44","slug":"location-and-mobility-in-a-sensor-network-of-mobile-phones","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/location-and-mobility-in-a-sensor-network-of-mobile-phones\/","title":{"rendered":"Location and Mobility in a Sensor Network of Mobile Phones"},"content":{"rendered":"<div class=\"asset-content\">\n<p>Mobile phones have two sensors: a camera and a microphone. Our goal in this position paper it to explore the use of these sensors for building an audio-visual sensor network that exploits the deployed base of millions of mobile phones worldwide. Among the several salient features of such a sensor network, we focus on mobility. Mobility is advantageous since it yields significant advantage in spatial coverage. However, due to the uncontrolled nature of device motion, it is difficult to sample a required region with a given device. We propose a data based abstraction to deal with this difficulty. Rather than treating the physical devices as our sensor nodes, we introduce a layer of static virtual sensor nodes corresponding to the sampled data locations. The virtual nodes corresponding to the required region to be sensed can be queried directly to obtain data samples for that region. We discuss how the locations of the virtual sensor nodes can be enhanced, and sometimes derived, using the visual data content itself. Experiments with real data are presented to expose some of the practical considerations for our design approach.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Mobile phones have two sensors: a camera and a microphone. Our goal in this position paper it to explore the use of these sensors for building an audio-visual sensor network that exploits the deployed base of millions of mobile phones worldwide. Among the several salient features of such a sensor network, we focus on mobility. [&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":"","msr-author-ordering":[{"type":"user_nicename","value":"kansal"},{"type":"user_nicename","value":"zhao"}],"msr_publishername":"Association for Computing Machinery, Inc.","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"ACM SIGMM 17th International workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV), ","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"MSR-TR-2007-26","msr_organization":"","msr_pages_string":"15","msr_page_range_start":"15","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"Copyright \u00a9 2007 by the Association for Computing Machinery, Inc. Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific permission and\/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212) 869-0481, or permissions@acm.org. The definitive version of this paper can be found at ACM's Digital Library --http:\/\/www.acm.org\/dl\/.","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":"Microsoft Research","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":"2007-06-04","msr_highlight_text":"","msr_notes":"ACM SIGMM 17th International workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV),","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":2007,"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":[13547],"msr-publication-type":[193718],"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-153074","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-systems-and-networking","msr-locale-en_us"],"msr_publishername":"Association for Computing Machinery, Inc.","msr_edition":"ACM SIGMM 17th International workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV),","msr_affiliation":"","msr_published_date":"2007-06-04","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"15","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"MSR-TR-2007-26","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"ACM SIGMM 17th International workshop on Network and Operating Systems Support for Digital Audio & Video (NOSSDAV),","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":"226525","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"kansal_NOSSDAV07.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2007\/06\/kansal_NOSSDAV07.pdf","id":226525,"label_id":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":[{"id":226525,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2007\/06\/kansal_NOSSDAV07.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"kansal","user_id":32485,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=kansal"},{"type":"user_nicename","value":"zhao","user_id":35103,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=zhao"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[170109],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"techreport","related_content":{"projects":[{"ID":170109,"post_title":"SenseWeb","post_name":"senseweb","post_type":"msr-project","post_date":"2008-12-10 10:52:54","post_modified":"2017-06-16 11:08:28","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/senseweb\/","post_excerpt":"SenseWeb is a peer produced sensor network that consists of sensors deployed by contributors across the globe. 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