{"id":"https://openalex.org/W2933773907","doi":"https://doi.org/10.1145/3302505.3310077","title":"A domain adaptation technique for fine-grained occupancy estimation in commercial buildings","display_name":"A domain adaptation technique for fine-grained occupancy estimation in commercial buildings","publication_year":2019,"publication_date":"2019-03-25","ids":{"openalex":"https://openalex.org/W2933773907","doi":"https://doi.org/10.1145/3302505.3310077","mag":"2933773907"},"language":"en","primary_location":{"id":"doi:10.1145/3302505.3310077","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3302505.3310077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Internet of Things Design and Implementation","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/A5057389542","display_name":"Tianyu Zhang","orcid":"https://orcid.org/0000-0002-2508-1949"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Tianyu Zhang","raw_affiliation_strings":["University of Alberta, Edmonton, Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Alberta, Canada","institution_ids":["https://openalex.org/I154425047"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5079048464","display_name":"Omid Ardakanian","orcid":"https://orcid.org/0000-0002-6711-5502"},"institutions":[{"id":"https://openalex.org/I154425047","display_name":"University of Alberta","ror":"https://ror.org/0160cpw27","country_code":"CA","type":"education","lineage":["https://openalex.org/I154425047"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Omid Ardakanian","raw_affiliation_strings":["University of Alberta, Edmonton, Alberta, Canada"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Alberta, Edmonton, Alberta, Canada","institution_ids":["https://openalex.org/I154425047"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I154425047"],"apc_list":null,"apc_paid":null,"fwci":5.7193,"has_fulltext":false,"cited_by_count":21,"citation_normalized_percentile":{"value":0.97488609,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"148","last_page":"159"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9674000144004822,"subfield":{"id":"https://openalex.org/subfields/2215","display_name":"Building and Construction"},"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":0.9667999744415283,"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":0.96670001745224,"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/occupancy","display_name":"Occupancy","score":0.9170184135437012},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7616081237792969},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.7316403388977051},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.6489251255989075},{"id":"https://openalex.org/keywords/adaptation","display_name":"Adaptation (eye)","score":0.6220239996910095},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.5358074903488159},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.432101309299469},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4314798414707184},{"id":"https://openalex.org/keywords/test-data","display_name":"Test data","score":0.41994550824165344},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41728144884109497},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38660603761672974},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.17247095704078674},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12115532159805298}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.9170184135437012},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7616081237792969},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.7316403388977051},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.6489251255989075},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.6220239996910095},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.5358074903488159},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.432101309299469},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4314798414707184},{"id":"https://openalex.org/C16910744","wikidata":"https://www.wikidata.org/wiki/Q7705759","display_name":"Test data","level":2,"score":0.41994550824165344},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41728144884109497},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38660603761672974},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.17247095704078674},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12115532159805298},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"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/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3302505.3310077","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3302505.3310077","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Internet of Things Design and Implementation","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.6399999856948853,"id":"https://metadata.un.org/sdg/11"}],"awards":[{"id":"https://openalex.org/G3247444335","display_name":null,"funder_award_id":"530852-18","funder_id":"https://openalex.org/F4320334593","funder_display_name":"Natural Sciences and Engineering Research Council of Canada"}],"funders":[{"id":"https://openalex.org/F4320334593","display_name":"Natural Sciences and Engineering Research Council of Canada","ror":"https://ror.org/01h531d29"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":44,"referenced_works":["https://openalex.org/W6538360","https://openalex.org/W46086471","https://openalex.org/W167598277","https://openalex.org/W179875071","https://openalex.org/W1802825888","https://openalex.org/W1968359621","https://openalex.org/W1978039224","https://openalex.org/W1980884867","https://openalex.org/W1991724394","https://openalex.org/W1995400545","https://openalex.org/W2064675550","https://openalex.org/W2069962612","https://openalex.org/W2093434700","https://openalex.org/W2114117309","https://openalex.org/W2115873741","https://openalex.org/W2130772746","https://openalex.org/W2131953535","https://openalex.org/W2138484437","https://openalex.org/W2143612262","https://openalex.org/W2155566686","https://openalex.org/W2156692643","https://openalex.org/W2157331557","https://openalex.org/W2166331910","https://openalex.org/W2297891736","https://openalex.org/W2408842991","https://openalex.org/W2489292218","https://openalex.org/W2546724727","https://openalex.org/W2547405038","https://openalex.org/W2554207730","https://openalex.org/W2605216517","https://openalex.org/W2605287558","https://openalex.org/W2610623618","https://openalex.org/W2615977380","https://openalex.org/W2735604903","https://openalex.org/W2751969628","https://openalex.org/W2786808285","https://openalex.org/W2797286629","https://openalex.org/W2803766679","https://openalex.org/W2804327584","https://openalex.org/W2838829825","https://openalex.org/W2893522934","https://openalex.org/W2896283615","https://openalex.org/W2951939904","https://openalex.org/W2963500702"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W1968324288","https://openalex.org/W1540010871","https://openalex.org/W4394775207","https://openalex.org/W2028936140","https://openalex.org/W2043884319","https://openalex.org/W3195353062","https://openalex.org/W3186268266"],"abstract_inverted_index":{"Fine-grained":[0],"occupancy":[1,31,57,81],"information":[2,22],"is":[3,16,102,159,180],"essential":[4],"to":[5,19,24,54,78,92,125,192],"improve":[6],"human":[7],"experience":[8],"and":[9,33,71,120],"operational":[10],"efficiency":[11],"of":[12,27,129,170],"buildings,":[13],"yet":[14],"it":[15],"quite":[17],"challenging":[18],"obtain":[20],"this":[21,45],"due":[23],"the":[25,67,89,96,108,113,117,122,127,132,147,163,183,187],"lack":[26],"special-purpose":[28],"sensors":[29],"for":[30,37,186],"monitoring,":[32],"insufficient":[34],"training":[35],"data":[36,64,101,179],"developing":[38],"accurate":[39],"data-driven":[40],"models.":[41],"This":[42],"paper":[43],"addresses":[44],"challenge":[46],"by":[47],"(a)":[48],"utilizing":[49],"recurrent":[50],"neural":[51],"network":[52],"models":[53,82],"uncover":[55],"latent":[56],"patterns":[58],"in":[59,84,131,142],"individual":[60],"rooms":[61],"from":[62,137,182],"trend":[63],"available":[65],"through":[66],"building":[68],"management":[69],"system,":[70],"(b)":[72],"applying":[73],"a":[74,85,156,167],"domain":[75,165,185,189],"adaptation":[76,190],"technique":[77,191],"transfer":[79],"existing":[80],"trained":[83],"controlled":[86],"environment":[87,94],"(i.e.,":[88,95],"source":[90],"domain)":[91,98],"another":[93],"target":[97,133,164,184],"where":[99],"labelled":[100,171,178],"sparse":[103],"or":[104],"non-existent.":[105],"We":[106],"adjust":[107],"model":[109,124,149,157],"parameters":[110],"based":[111],"on":[112,162],"apparent":[114],"differences":[115],"between":[116],"two":[118,138,143],"environments":[119],"apply":[121],"adapted":[123,148],"estimate":[126],"number":[128],"occupants":[130],"domain.":[134],"Our":[135],"results":[136],"test":[139],"commercial":[140],"buildings":[141],"continents":[144],"indicate":[145],"that":[146,158],"yields":[150],"only":[151],"slightly":[152],"lower":[153],"accuracy":[154],"than":[155],"originally":[160],"built":[161],"given":[166],"large":[168],"amount":[169],"data.":[172],"Furthermore,":[173],"we":[174],"study":[175],"how":[176],"much":[177],"required":[181],"semi-supervised":[188],"achieve":[193],"promising":[194],"results.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":4},{"year":2019,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}