{"id":"https://openalex.org/W4388320652","doi":"https://doi.org/10.1145/3600100.3623718","title":"Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy Detection","display_name":"Overcoming Data Scarcity through Transfer Learning in CO2-Based Building Occupancy Detection","publication_year":2023,"publication_date":"2023-11-03","ids":{"openalex":"https://openalex.org/W4388320652","doi":"https://doi.org/10.1145/3600100.3623718"},"language":"en","primary_location":{"id":"doi:10.1145/3600100.3623718","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3623718","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3623718","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3623718","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5006438674","display_name":"Manuel Weber","orcid":"https://orcid.org/0000-0001-9488-7877"},"institutions":[{"id":"https://openalex.org/I174004417","display_name":"Munich University of Applied Sciences","ror":"https://ror.org/012k1v959","country_code":"DE","type":"education","lineage":["https://openalex.org/I174004417"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Manuel Weber","raw_affiliation_strings":["Munich University of Applied Sciences (HM), Germany"],"raw_orcid":"https://orcid.org/0000-0001-9488-7877","affiliations":[{"raw_affiliation_string":"Munich University of Applied Sciences (HM), Germany","institution_ids":["https://openalex.org/I174004417"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5047498936","display_name":"Farzan Banihashemi","orcid":"https://orcid.org/0000-0001-5661-275X"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Farzan Banihashemi","raw_affiliation_strings":["Technical University of Munich, Germany"],"raw_orcid":"https://orcid.org/0000-0001-5661-275X","affiliations":[{"raw_affiliation_string":"Technical University of Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042685867","display_name":"Peter Mandl","orcid":"https://orcid.org/0000-0003-4508-7667"},"institutions":[{"id":"https://openalex.org/I174004417","display_name":"Munich University of Applied Sciences","ror":"https://ror.org/012k1v959","country_code":"DE","type":"education","lineage":["https://openalex.org/I174004417"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Peter Mandl","raw_affiliation_strings":["Munich University of Applied Sciences (HM), Germany"],"raw_orcid":"https://orcid.org/0000-0003-4508-7667","affiliations":[{"raw_affiliation_string":"Munich University of Applied Sciences (HM), Germany","institution_ids":["https://openalex.org/I174004417"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5072791865","display_name":"Hans\u2010Arno Jacobsen","orcid":"https://orcid.org/0000-0003-0813-0101"},"institutions":[{"id":"https://openalex.org/I185261750","display_name":"University of Toronto","ror":"https://ror.org/03dbr7087","country_code":"CA","type":"education","lineage":["https://openalex.org/I185261750"]}],"countries":["CA"],"is_corresponding":false,"raw_author_name":"Hans-Arno Jacobsen","raw_affiliation_strings":["University of Toronto, Canada"],"raw_orcid":"https://orcid.org/0000-0003-0813-0101","affiliations":[{"raw_affiliation_string":"University of Toronto, Canada","institution_ids":["https://openalex.org/I185261750"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060499098","display_name":"Ruben Mayer","orcid":"https://orcid.org/0000-0001-9870-7466"},"institutions":[{"id":"https://openalex.org/I54009628","display_name":"University of Bayreuth","ror":"https://ror.org/0234wmv40","country_code":"DE","type":"education","lineage":["https://openalex.org/I54009628"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Ruben Mayer","raw_affiliation_strings":["University of Bayreuth, Germany"],"raw_orcid":"https://orcid.org/0000-0001-9870-7466","affiliations":[{"raw_affiliation_string":"University of Bayreuth, Germany","institution_ids":["https://openalex.org/I54009628"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":3.1164,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.92854099,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"10"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9955999851226807,"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9800000190734863,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/occupancy","display_name":"Occupancy","score":0.9428926706314087},{"id":"https://openalex.org/keywords/transfer-of-learning","display_name":"Transfer of learning","score":0.8543925881385803},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7675280570983887},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.6037775874137878},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5628934502601624},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5402353405952454},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5196822285652161},{"id":"https://openalex.org/keywords/labeled-data","display_name":"Labeled data","score":0.5122846364974976},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.5043016672134399},{"id":"https://openalex.org/keywords/data-modeling","display_name":"Data modeling","score":0.500436544418335},{"id":"https://openalex.org/keywords/transfer","display_name":"Transfer (computing)","score":0.4462491273880005},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.4411832094192505},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.10901135206222534},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10583555698394775}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.9428926706314087},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.8543925881385803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7675280570983887},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.6037775874137878},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5628934502601624},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5402353405952454},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5196822285652161},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.5122846364974976},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.5043016672134399},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.500436544418335},{"id":"https://openalex.org/C2776175482","wikidata":"https://www.wikidata.org/wiki/Q1195816","display_name":"Transfer (computing)","level":2,"score":0.4462491273880005},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.4411832094192505},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.10901135206222534},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10583555698394775},{"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/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"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/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C173608175","wikidata":"https://www.wikidata.org/wiki/Q232661","display_name":"Parallel computing","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1145/3600100.3623718","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3623718","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3623718","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},{"id":"pmh:oai:mediatum.ub.tum.de:node/1726075","is_oa":false,"landing_page_url":"https://mediatum.ub.tum.de/1726075","pdf_url":null,"source":{"id":"https://openalex.org/S4377196330","display_name":"mediaTUM  (Technical University of Munich)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I62916508","host_organization_name":"Technical University of Munich","host_organization_lineage":["https://openalex.org/I62916508"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"ConferencePaper"}],"best_oa_location":{"id":"doi:10.1145/3600100.3623718","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3600100.3623718","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3600100.3623718","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 10th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321394","display_name":"Aalto-Yliopisto","ror":"https://ror.org/020hwjq30"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4388320652.pdf","grobid_xml":"https://content.openalex.org/works/W4388320652.grobid-xml"},"referenced_works_count":34,"referenced_works":["https://openalex.org/W1978118650","https://openalex.org/W2003726679","https://openalex.org/W2005514768","https://openalex.org/W2053154970","https://openalex.org/W2061656867","https://openalex.org/W2085852460","https://openalex.org/W2131353345","https://openalex.org/W2133667298","https://openalex.org/W2165698076","https://openalex.org/W2182886880","https://openalex.org/W2554207730","https://openalex.org/W2594899909","https://openalex.org/W2615843269","https://openalex.org/W2621226175","https://openalex.org/W2626675958","https://openalex.org/W2738662141","https://openalex.org/W2753362299","https://openalex.org/W2797286629","https://openalex.org/W2896283615","https://openalex.org/W2902043212","https://openalex.org/W2933773907","https://openalex.org/W2983410907","https://openalex.org/W3023461866","https://openalex.org/W3035040013","https://openalex.org/W3110615623","https://openalex.org/W3190238878","https://openalex.org/W4206564475","https://openalex.org/W4214656940","https://openalex.org/W4224224459","https://openalex.org/W4289515924","https://openalex.org/W4297969478","https://openalex.org/W4381114317","https://openalex.org/W6637618735","https://openalex.org/W6963232140"],"related_works":["https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W2140186469","https://openalex.org/W4388320652","https://openalex.org/W3193920202","https://openalex.org/W4318813552","https://openalex.org/W2576964996","https://openalex.org/W3171384686","https://openalex.org/W4389518428"],"abstract_inverted_index":{"Knowing":[0],"indoor":[1],"occupancy":[2,20,103,126],"states":[3],"is":[4,28],"crucial":[5],"for":[6,33,124],"energy":[7],"optimization":[8],"in":[9,99],"buildings.":[10],"While":[11],"neural":[12],"networks":[13],"can":[14,159],"effectively":[15,133],"be":[16,160],"used":[17],"to":[18,108],"detect":[19],"based":[21],"on":[22,148],"carbon":[23],"dioxide":[24],"measurements,":[25],"their":[26],"application":[27],"impeded":[29],"by":[30,162],"the":[31,43,93,100,115,135,163],"need":[32],"sufficient":[34],"labeled":[35],"training":[36],"data.":[37,141,170],"In":[38],"this":[39],"study,":[40],"we":[41,91,154],"analyze":[42],"prediction":[44,104],"performance":[45,158],"of":[46,97,102,119,138,167],"three":[47],"different":[48],"transfer":[49],"learning":[50],"(TL)":[51],"methods":[52,64],"leveraging":[53,168],"target":[54,139],"room":[55,89,140],"data":[56,59,78],"jointly":[57],"with":[58,150],"from":[60,79,105],"other":[61],"rooms.":[62],"The":[63],"include":[65],"(1)":[66],"pretraining":[67,149],"and":[68,73,83,117],"fine-tuning,":[69],"(2)":[70],"layer":[71],"freezing,":[72],"(3)":[74],"domain-adversarial":[75],"learning.":[76],"Using":[77],"five":[80],"real-world":[81,152],"rooms":[82],"one":[84],"simulated":[85,169],"room,":[86],"including":[87],"multiple":[88],"types,":[90],"provide":[92],"most":[94],"extensive":[95],"evaluation":[96],"TL":[98,132],"field":[101],"environmental":[106],"variables":[107],"date.":[109],"This":[110],"work\u2019s":[111],"contribution":[112],"further":[113],"includes":[114],"architecture":[116],"hyperparameters":[118],"a":[120],"deep":[121],"CNN-LSTM":[122],"model":[123],"CO2-based":[125],"detection.":[127],"Our":[128],"results":[129],"indicate":[130],"that":[131,156],"reduces":[134],"required":[136],"amount":[137],"Moreover,":[142],"while":[143],"previous":[144],"literature":[145],"was":[146],"focused":[147],"related":[151],"data,":[153],"show":[155],"similar":[157],"achieved":[161],"more":[164],"practical":[165],"approach":[166]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2}],"updated_date":"2026-08-01T09:00:35.917206","created_date":"2025-10-10T00:00:00"}