{"id":"https://openalex.org/W2172191795","doi":"https://doi.org/10.1109/sahcn.2011.5984896","title":"Inferring mobile trajectories using a network of binary proximity sensors","display_name":"Inferring mobile trajectories using a network of binary proximity sensors","publication_year":2011,"publication_date":"2011-06-01","ids":{"openalex":"https://openalex.org/W2172191795","doi":"https://doi.org/10.1109/sahcn.2011.5984896","mag":"2172191795"},"language":"en","primary_location":{"id":"doi:10.1109/sahcn.2011.5984896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2011.5984896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5086254784","display_name":"Eunjoon Cho","orcid":null},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Eunjoon Cho","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010361523","display_name":"Kevin Bing-Yung Wong","orcid":"https://orcid.org/0009-0000-3411-8726"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kevin Wong","raw_affiliation_strings":["Department of Electrical Engineering, University of Stanford, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5056178417","display_name":"Omprakash Gnawali","orcid":"https://orcid.org/0000-0003-2649-6035"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Omprakash Gnawali","raw_affiliation_strings":["Department of Computer Science, University of Stanford, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5080764662","display_name":"Martin Wicke","orcid":null},"institutions":[{"id":"https://openalex.org/I95457486","display_name":"University of California, Berkeley","ror":"https://ror.org/01an7q238","country_code":"US","type":"education","lineage":["https://openalex.org/I95457486"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Wicke","raw_affiliation_strings":["Department of Electrical Engineering and Computer Science, University of California Berkeley, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Electrical Engineering and Computer Science, University of California Berkeley, USA","institution_ids":["https://openalex.org/I95457486"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065368881","display_name":"Leonidas Guibas","orcid":"https://orcid.org/0000-0002-8315-4886"},"institutions":[{"id":"https://openalex.org/I97018004","display_name":"Stanford University","ror":"https://ror.org/00f54p054","country_code":"US","type":"education","lineage":["https://openalex.org/I97018004"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leonidas Guibas","raw_affiliation_strings":["Department of Computer Science, University of Stanford, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, University of Stanford, USA","institution_ids":["https://openalex.org/I97018004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4475,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.64153405,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"1","issue":null,"first_page":"188","last_page":"196"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.996999979019165,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/timestamp","display_name":"Timestamp","score":0.8957840800285339},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.778988242149353},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.607785701751709},{"id":"https://openalex.org/keywords/binary-number","display_name":"Binary number","score":0.6071823835372925},{"id":"https://openalex.org/keywords/path","display_name":"Path (computing)","score":0.5418210625648499},{"id":"https://openalex.org/keywords/trajectory","display_name":"Trajectory","score":0.5263782143592834},{"id":"https://openalex.org/keywords/position","display_name":"Position (finance)","score":0.482754647731781},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.423667848110199},{"id":"https://openalex.org/keywords/volume","display_name":"Volume (thermodynamics)","score":0.42126908898353577},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.41540732979774475},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3595830798149109},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.2132682204246521},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09586471319198608}],"concepts":[{"id":"https://openalex.org/C113954288","wikidata":"https://www.wikidata.org/wiki/Q186885","display_name":"Timestamp","level":2,"score":0.8957840800285339},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.778988242149353},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.607785701751709},{"id":"https://openalex.org/C48372109","wikidata":"https://www.wikidata.org/wiki/Q3913","display_name":"Binary number","level":2,"score":0.6071823835372925},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.5418210625648499},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.5263782143592834},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.482754647731781},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.423667848110199},{"id":"https://openalex.org/C20556612","wikidata":"https://www.wikidata.org/wiki/Q4469374","display_name":"Volume (thermodynamics)","level":2,"score":0.42126908898353577},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.41540732979774475},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3595830798149109},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.2132682204246521},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09586471319198608},{"id":"https://openalex.org/C94375191","wikidata":"https://www.wikidata.org/wiki/Q11205","display_name":"Arithmetic","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/sahcn.2011.5984896","is_oa":false,"landing_page_url":"https://doi.org/10.1109/sahcn.2011.5984896","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2011 8th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","display_name":"Sustainable cities and communities","score":0.44999998807907104}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1563879233","https://openalex.org/W1578078765","https://openalex.org/W1995903777","https://openalex.org/W2070377940","https://openalex.org/W2094636498","https://openalex.org/W2095187583","https://openalex.org/W2107482124","https://openalex.org/W2117520883","https://openalex.org/W2122182186","https://openalex.org/W2126141220","https://openalex.org/W2126829907","https://openalex.org/W2128445255","https://openalex.org/W2133336070","https://openalex.org/W2138309709","https://openalex.org/W2139995290","https://openalex.org/W2141218915","https://openalex.org/W2147855783","https://openalex.org/W2156072601","https://openalex.org/W2160343401","https://openalex.org/W2166698530","https://openalex.org/W2170240475","https://openalex.org/W2797746357","https://openalex.org/W4245685877","https://openalex.org/W6633660136","https://openalex.org/W6678956196","https://openalex.org/W6679757172","https://openalex.org/W6680640338","https://openalex.org/W6680892813","https://openalex.org/W6681697924","https://openalex.org/W6683181385"],"related_works":["https://openalex.org/W2060561905","https://openalex.org/W1417711376","https://openalex.org/W1986883493","https://openalex.org/W2469862403","https://openalex.org/W2166378262","https://openalex.org/W2035891203","https://openalex.org/W4379524643","https://openalex.org/W2011027677","https://openalex.org/W2367807705","https://openalex.org/W4285233590"],"abstract_inverted_index":{"Understanding":[0],"human":[1],"mobility":[2],"in":[3,9,82,171],"an":[4],"environment":[5],"can":[6,31,74,119,160],"be":[7],"approached":[8],"many":[10],"forms,":[11],"one":[12],"of":[13,21,35,58,67,70,99,106,148],"which":[14],"is":[15,166],"to":[16,39,169],"recover":[17],"the":[18,68,79,83,100,104,121,126,146,152,163],"underlying":[19,122],"structure":[20],"user":[22],"movement.":[23],"In":[24],"our":[25,132,158],"work,":[26],"we":[27,30,73,118],"show":[28,53,113],"that":[29,54,114,124],"use":[32,170],"a":[33,76,86,135,172],"network":[34,140],"binary":[36,60],"proximity":[37],"sensors":[38],"detect":[40,162],"paths":[41],"between":[42,78,90],"nodes":[43],"and":[44,109,137,165],"also":[45,96],"extract":[46],"highly":[47],"popular":[48],"trajectories":[49,123,164],"users":[50],"take.":[51],"We":[52,111,129,142],"with":[55,63,115,155],"sufficient":[56],"amount":[57],"these":[59,71],"data,":[61],"even":[62],"no":[64],"prior":[65],"knowledge":[66],"location":[69],"sensors,":[72],"capture":[75],"correlation":[77],"detection":[80],"timestamps":[81,156],"case":[84],"where":[85],"physical":[87],"path":[88],"exists":[89],"any":[91],"two":[92,138],"nodes.":[93],"Our":[94],"algorithm":[95,133,159],"generates":[97],"characteristics":[98],"path,":[101],"such":[102],"as":[103],"distribution":[105],"transition":[107],"times":[108],"volume.":[110],"further":[112],"sampling":[116],"techniques":[117],"estimate":[120],"generated":[125],"time":[127],"stamps.":[128],"have":[130],"tested":[131],"on":[134],"simulator":[136],"sensor":[139,153],"deployments.":[141],"found":[143],"that,":[144],"despite":[145],"lack":[147],"position":[149],"information":[150],"about":[151],"nodes,":[154],"alone":[157],"accurately":[161],"robust":[167],"enough":[168],"real-world":[173],"office":[174],"building.":[175]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2017,"cited_by_count":3},{"year":2016,"cited_by_count":1},{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}