{"id":"https://openalex.org/W2045484711","doi":"https://doi.org/10.1145/2809695.2817882","title":"Poster","display_name":"Poster","publication_year":2015,"publication_date":"2015-11-01","ids":{"openalex":"https://openalex.org/W2045484711","doi":"https://doi.org/10.1145/2809695.2817882","mag":"2045484711"},"language":"en","primary_location":{"id":"doi:10.1145/2809695.2817882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2809695.2817882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"type":"article","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/A5056718303","display_name":"Yang Zhao","orcid":"https://orcid.org/0000-0001-5252-658X"},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Yang Zhao","raw_affiliation_strings":["GE Global Research, Niskayuna, NY, USA"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023785451","display_name":"Ting Yu","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ting Yu","raw_affiliation_strings":["GE Global Research, Niskayuna, NY, USA"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5111740361","display_name":"Jeff Ashe","orcid":null},"institutions":[{"id":"https://openalex.org/I4210134512","display_name":"GE Global Research (United States)","ror":"https://ror.org/03e06qt98","country_code":"US","type":"company","lineage":["https://openalex.org/I4210134512"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Jeff Ashe","raw_affiliation_strings":["GE Global Research, Niskayuna, NY, USA"],"affiliations":[{"raw_affiliation_string":"GE Global Research, Niskayuna, NY, USA","institution_ids":["https://openalex.org/I4210134512"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5056718303"],"corresponding_institution_ids":["https://openalex.org/I4210134512"],"apc_list":null,"apc_paid":null,"fwci":0.1841,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.57363237,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"397","last_page":"398"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991000294685364,"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"}},"topics":[{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9991000294685364,"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/T10326","display_name":"Indoor and Outdoor Localization Technologies","score":0.9987000226974487,"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/T10080","display_name":"Energy Efficient Wireless Sensor Networks","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/granularity","display_name":"Granularity","score":0.7021817564964294},{"id":"https://openalex.org/keywords/radio-frequency","display_name":"Radio frequency","score":0.6960499286651611},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6892880201339722},{"id":"https://openalex.org/keywords/doppler-effect","display_name":"Doppler effect","score":0.5884540677070618},{"id":"https://openalex.org/keywords/breathing","display_name":"Breathing","score":0.4809695780277252},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.48061078786849976},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3479260206222534},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33262282609939575},{"id":"https://openalex.org/keywords/electronic-engineering","display_name":"Electronic engineering","score":0.3304482102394104},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.24342772364616394},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.18657609820365906},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.10679012537002563}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.7021817564964294},{"id":"https://openalex.org/C74064498","wikidata":"https://www.wikidata.org/wiki/Q3396184","display_name":"Radio frequency","level":2,"score":0.6960499286651611},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6892880201339722},{"id":"https://openalex.org/C142757262","wikidata":"https://www.wikidata.org/wiki/Q76436","display_name":"Doppler effect","level":2,"score":0.5884540677070618},{"id":"https://openalex.org/C39300077","wikidata":"https://www.wikidata.org/wiki/Q9530","display_name":"Breathing","level":2,"score":0.4809695780277252},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.48061078786849976},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3479260206222534},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33262282609939575},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.3304482102394104},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.24342772364616394},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18657609820365906},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.10679012537002563},{"id":"https://openalex.org/C1276947","wikidata":"https://www.wikidata.org/wiki/Q333","display_name":"Astronomy","level":1,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2809695.2817882","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2809695.2817882","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 13th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":3,"referenced_works":["https://openalex.org/W2047539221","https://openalex.org/W2137494381","https://openalex.org/W2544371467"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072"],"abstract_inverted_index":{"This":[0,22],"paper":[1],"presents":[2],"a":[3,10,15,35,63,74,99],"non-invasive":[4],"human":[5,53],"activity":[6],"monitoring":[7],"system":[8,24,47,69],"with":[9],"low-cost":[11],"Doppler":[12,36,101],"sensor":[13,37],"and":[14,38,70],"pair":[16],"of":[17,28,50],"radio":[18],"frequency":[19],"(RF)":[20],"sensors.":[21],"radio-based":[23],"combines":[25],"the":[26,68,89],"strengths":[27],"two":[29],"sensing":[30,40],"modalities:":[31],"fine":[32],"granularity":[33],"from":[34,42],"large":[39,64],"coverage":[41],"an":[43],"RF":[44],"link.":[45],"The":[46],"is":[48,93],"capable":[49],"detecting":[51],"subtle":[52],"motion":[54],"such":[55],"as":[56,58,60],"breathing,":[57],"well":[59],"walking":[61],"in":[62,73],"area.":[65],"We":[66],"deploy":[67],"perform":[71],"experiments":[72],"5.5":[75],"m":[76,79],"by":[77],"7.5":[78],"room":[80],"to":[81],"classify":[82],"four":[83],"activities.":[84],"Experimental":[85],"results":[86],"show":[87],"that":[88],"average":[90],"classification":[91],"rate":[92],"90%,":[94],"31%":[95],"more":[96],"accurate":[97],"than":[98],"single":[100],"system.":[102]},"counts_by_year":[{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1},{"year":2017,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2016-06-24T00:00:00"}