{"id":"https://openalex.org/W4405699118","doi":"https://doi.org/10.1061/jccee5.cpeng-6249","title":"Multimodal Data Fusion and Deep Learning for Occupant-Centric Indoor Environmental Quality Classification","display_name":"Multimodal Data Fusion and Deep Learning for Occupant-Centric Indoor Environmental Quality Classification","publication_year":2024,"publication_date":"2024-12-23","ids":{"openalex":"https://openalex.org/W4405699118","doi":"https://doi.org/10.1061/jccee5.cpeng-6249"},"language":"en","primary_location":{"id":"doi:10.1061/jccee5.cpeng-6249","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6249","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-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/A5103211719","display_name":"Min Jae Lee","orcid":"https://orcid.org/0009-0009-4017-3209"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Min Jae Lee","raw_affiliation_strings":["Virginia Polytechnic Institute and State Univ"],"raw_orcid":"https://orcid.org/0009-0009-4017-3209","affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State Univ","institution_ids":["https://openalex.org/I859038795"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068080488","display_name":"Ruichuan Zhang","orcid":"https://orcid.org/0000-0001-8421-1996"},"institutions":[{"id":"https://openalex.org/I859038795","display_name":"Virginia Tech","ror":"https://ror.org/02smfhw86","country_code":"US","type":"education","lineage":["https://openalex.org/I859038795"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ruichuan Zhang","raw_affiliation_strings":["Virginia Polytechnic Institute and State Univ"],"raw_orcid":"https://orcid.org/0000-0001-8421-1996","affiliations":[{"raw_affiliation_string":"Virginia Polytechnic Institute and State Univ","institution_ids":["https://openalex.org/I859038795"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I859038795"],"apc_list":null,"apc_paid":null,"fwci":0.9275,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.69608347,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":"39","issue":"2","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12120","display_name":"Air Quality Monitoring and Forecasting","score":0.9916999936103821,"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":0.9916999936103821,"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/T11002","display_name":"Indoor Air Quality and Microbial Exposure","score":0.9857000112533569,"subfield":{"id":"https://openalex.org/subfields/2307","display_name":"Health, Toxicology and Mutagenesis"},"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/T11692","display_name":"Noise Effects and Management","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/3616","display_name":"Speech and Hearing"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5603412389755249},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5410441756248474},{"id":"https://openalex.org/keywords/quality","display_name":"Quality (philosophy)","score":0.5359362363815308},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4591500163078308},{"id":"https://openalex.org/keywords/data-quality","display_name":"Data quality","score":0.4248150885105133},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41385582089424133},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.3614404797554016},{"id":"https://openalex.org/keywords/construction-engineering","display_name":"Construction engineering","score":0.3358931541442871},{"id":"https://openalex.org/keywords/operations-management","display_name":"Operations management","score":0.08879068493843079}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5603412389755249},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5410441756248474},{"id":"https://openalex.org/C2779530757","wikidata":"https://www.wikidata.org/wiki/Q1207505","display_name":"Quality (philosophy)","level":2,"score":0.5359362363815308},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4591500163078308},{"id":"https://openalex.org/C24756922","wikidata":"https://www.wikidata.org/wiki/Q1757694","display_name":"Data quality","level":3,"score":0.4248150885105133},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41385582089424133},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3614404797554016},{"id":"https://openalex.org/C107053488","wikidata":"https://www.wikidata.org/wiki/Q2674423","display_name":"Construction engineering","level":1,"score":0.3358931541442871},{"id":"https://openalex.org/C21547014","wikidata":"https://www.wikidata.org/wiki/Q1423657","display_name":"Operations management","level":1,"score":0.08879068493843079},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C176217482","wikidata":"https://www.wikidata.org/wiki/Q860554","display_name":"Metric (unit)","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1061/jccee5.cpeng-6249","is_oa":false,"landing_page_url":"https://doi.org/10.1061/jccee5.cpeng-6249","pdf_url":null,"source":{"id":"https://openalex.org/S176637136","display_name":"Journal of Computing in Civil Engineering","issn_l":"0887-3801","issn":["0887-3801","1943-5487"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315747","host_organization_name":"American Society of Civil Engineers","host_organization_lineage":["https://openalex.org/P4310315747"],"host_organization_lineage_names":["American Society of Civil Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Computing in Civil Engineering","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":45,"referenced_works":["https://openalex.org/W1539811621","https://openalex.org/W1991680538","https://openalex.org/W2002753823","https://openalex.org/W2039887695","https://openalex.org/W2065504936","https://openalex.org/W2075351671","https://openalex.org/W2081849299","https://openalex.org/W2087298138","https://openalex.org/W2327557979","https://openalex.org/W2346141405","https://openalex.org/W2602420730","https://openalex.org/W2626841833","https://openalex.org/W2766318212","https://openalex.org/W2779744026","https://openalex.org/W2884990684","https://openalex.org/W2891670944","https://openalex.org/W2912696304","https://openalex.org/W2922504779","https://openalex.org/W2965460638","https://openalex.org/W2989894222","https://openalex.org/W2990889364","https://openalex.org/W2995201943","https://openalex.org/W2998919931","https://openalex.org/W3010849353","https://openalex.org/W3015817510","https://openalex.org/W3022291028","https://openalex.org/W3047631327","https://openalex.org/W3097360695","https://openalex.org/W3131847845","https://openalex.org/W3175200815","https://openalex.org/W4205767436","https://openalex.org/W4206747810","https://openalex.org/W4211094330","https://openalex.org/W4283276216","https://openalex.org/W4310604641","https://openalex.org/W4310664318","https://openalex.org/W4323316882","https://openalex.org/W4365812644","https://openalex.org/W4386509496","https://openalex.org/W4386838435","https://openalex.org/W4388018300","https://openalex.org/W4388802439","https://openalex.org/W4390569198","https://openalex.org/W4390849481","https://openalex.org/W4392359807"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2611989081","https://openalex.org/W2731899572","https://openalex.org/W4230611425","https://openalex.org/W4294635752","https://openalex.org/W4304166257","https://openalex.org/W4383066092","https://openalex.org/W3215138031","https://openalex.org/W2390428730","https://openalex.org/W1970865845"],"abstract_inverted_index":{"Amidst":[0],"the":[1,5,26,52,108],"growing":[2],"recognition":[3],"of":[4,7,30,78,177],"impact":[6],"indoor":[8,31,151,180],"environmental":[9,32,79,89],"conditions":[10,123,176],"on":[11,25,125],"buildings":[12],"and":[13,17,28,44,59,68,81,90,101,112,129,153,165,182,185,190],"occupant":[14,57,82,91,126,167],"comfort,":[15],"health,":[16],"well-being,":[18],"there":[19],"has":[20],"been":[21],"an":[22],"increasing":[23],"focus":[24],"assessment":[27,71],"modeling":[29,40],"quality":[33],"(IEQ).":[34],"Despite":[35],"considerable":[36],"advancements,":[37],"existing":[38],"IEQ":[39,70,122,163,175],"methodologies":[41],"often":[42],"prioritize":[43],"limit":[45],"to":[46,132,148],"singular":[47],"comfort":[48,58,128,152,189],"metrics,":[49],"potentially":[50],"neglecting":[51],"comprehensive":[53],"factors":[54],"associated":[55],"with":[56,144],"health.":[60],"There":[61],"is":[62],"a":[63,75,117,140],"need":[64],"for":[65,120],"more":[66],"inclusive":[67],"occupant-centric":[69],"models":[72,85],"that":[73],"cover":[74],"broader":[76],"spectrum":[77],"parameters":[80],"needs.":[83],"Such":[84],"require":[86],"integrating":[87,157],"diverse":[88,158],"data,":[92],"facing":[93],"challenges":[94],"in":[95,173,188],"leveraging":[96],"data":[97,159,164],"across":[98],"various":[99],"modalities":[100],"time":[102],"scales":[103],"as":[104,106],"well":[105],"understanding":[107],"temporal":[109],"patterns,":[110],"relationships,":[111],"trends.":[113],"This":[114],"paper":[115],"proposes":[116],"novel":[118],"framework":[119,138,170],"classifying":[121,174],"based":[124],"self-reported":[127],"health":[130,154],"levels":[131,155],"address":[133],"these":[134],"challenges.":[135],"The":[136,169],"proposed":[137],"leverages":[139],"multimodal":[141,166],"data-fusion":[142],"approach":[143],"Transformer-based":[145],"models,":[146],"aiming":[147],"accurately":[149],"predict":[150],"by":[156],"sources,":[160],"including":[161],"multidimensional":[162],"feedback.":[168],"was":[171],"evaluated":[172],"selected":[178],"public":[179],"spaces":[181],"achieved":[183],"97%":[184],"96%":[186],"accuracy":[187],"health-based":[191],"classifications,":[192],"outperforming":[193],"several":[194],"baselines.":[195]},"counts_by_year":[{"year":2026,"cited_by_count":6},{"year":2025,"cited_by_count":1}],"updated_date":"2026-08-06T08:24:18.245995","created_date":"2025-10-10T00:00:00"}