{"id":"https://openalex.org/W7165169684","doi":"https://doi.org/10.1145/3744256.3812594","title":"Load-as-a-sensor? Sensing indoor conditions at scale with system identification models of HVAC loads","display_name":"Load-as-a-sensor? Sensing indoor conditions at scale with system identification models of HVAC loads","publication_year":2026,"publication_date":"2026-06-19","ids":{"openalex":"https://openalex.org/W7165169684","doi":"https://doi.org/10.1145/3744256.3812594"},"language":null,"primary_location":{"id":"doi:10.1145/3744256.3812594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812594","pdf_url":null,"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 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3744256.3812594","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5087099867","display_name":"Yufei Zhang","orcid":"https://orcid.org/0009-0001-8574-3473"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Yufei Zhang","raw_affiliation_strings":["ETHOS Lab, EPFL, Fribourg, Switzerland"],"raw_orcid":"https://orcid.org/0009-0001-8574-3473","affiliations":[{"raw_affiliation_string":"ETHOS Lab, EPFL, Fribourg, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012658940","display_name":"Vasantha Ramani","orcid":"https://orcid.org/0000-0001-8438-6403"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Vasantha Ramani","raw_affiliation_strings":["ETHOS Lab, EPFL, Fribourg, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-8438-6403","affiliations":[{"raw_affiliation_string":"ETHOS Lab, EPFL, Fribourg, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056589095","display_name":"Andrew Sonta","orcid":"https://orcid.org/0000-0001-9021-0842"},"institutions":[{"id":"https://openalex.org/I5124864","display_name":"\u00c9cole Polytechnique F\u00e9d\u00e9rale de Lausanne","ror":"https://ror.org/02s376052","country_code":"CH","type":"education","lineage":["https://openalex.org/I2799323385","https://openalex.org/I5124864"]}],"countries":["CH"],"is_corresponding":false,"raw_author_name":"Andrew Sonta","raw_affiliation_strings":["ETHOS Lab, EPFL, Fribourg, Switzerland"],"raw_orcid":"https://orcid.org/0000-0001-9021-0842","affiliations":[{"raw_affiliation_string":"ETHOS Lab, EPFL, Fribourg, Switzerland","institution_ids":["https://openalex.org/I5124864"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":6.2611,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.97234264,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"35","last_page":"45"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10534","display_name":"Structural Health Monitoring Techniques","score":0.19210000336170197,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10534","display_name":"Structural Health Monitoring Techniques","score":0.19210000336170197,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural 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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.17949999868869781,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.07819999754428864,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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/hvac","display_name":"HVAC","score":0.5561000108718872},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5218999981880188},{"id":"https://openalex.org/keywords/system-identification","display_name":"System identification","score":0.42250001430511475},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.41839998960494995},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.26739999651908875}],"concepts":[{"id":"https://openalex.org/C122346748","wikidata":"https://www.wikidata.org/wiki/Q1798773","display_name":"HVAC","level":3,"score":0.5561000108718872},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5218999981880188},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.5001000165939331},{"id":"https://openalex.org/C119247159","wikidata":"https://www.wikidata.org/wiki/Q1366192","display_name":"System identification","level":3,"score":0.42250001430511475},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.41839998960494995},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.38280001282691956},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.3125},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.26739999651908875},{"id":"https://openalex.org/C152588345","wikidata":"https://www.wikidata.org/wiki/Q6498959","display_name":"Scale model","level":2,"score":0.257099986076355},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3744256.3812594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812594","pdf_url":null,"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 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3744256.3812594","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3744256.3812594","pdf_url":null,"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 13th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Affordable and clean energy","score":0.5211192965507507,"id":"https://metadata.un.org/sdg/7"},{"display_name":"Climate action","score":0.4273689389228821,"id":"https://metadata.un.org/sdg/13"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W2085874418","https://openalex.org/W2093447280","https://openalex.org/W2289455364","https://openalex.org/W2727832219","https://openalex.org/W2842089854","https://openalex.org/W2988485369","https://openalex.org/W3156755729","https://openalex.org/W3158049794","https://openalex.org/W4221157442","https://openalex.org/W4362633747","https://openalex.org/W4365451997","https://openalex.org/W4388327809","https://openalex.org/W4405176482","https://openalex.org/W4407568684","https://openalex.org/W4408726584","https://openalex.org/W4410351908","https://openalex.org/W4415339824","https://openalex.org/W7124301473"],"related_works":[],"abstract_inverted_index":{"The":[0],"transition":[1],"toward":[2],"renewable-powered":[3],"grids":[4],"has":[5],"intensified":[6],"the":[7,66,185,224,231,243],"need":[8],"for":[9,43,235,245],"building":[10,15,50,237,250],"demand-side":[11],"flexibility,":[12],"yet":[13],"unlocking":[14],"thermal":[16,70,238],"flexibility":[17],"potential":[18],"requires":[19],"accurate":[20],"and":[21,40,95,103,120,129,156,214,228,248],"scalable":[22],"dynamic":[23],"models.":[24,99],"Current":[25],"data-driven":[26,236],"approaches":[27],"face":[28],"a":[29,55,136],"critical":[30],"scalability":[31,225],"challenge:":[32],"they":[33],"predominantly":[34],"rely":[35],"on":[36,148,174],"indoor":[37,171],"temperature":[38,172,182,194],"measurements":[39],"intrusive":[41],"experiments":[42],"training,":[44],"preventing":[45],"massive":[46],"deployment":[47],"across":[48],"heterogeneous":[49],"stocks.":[51],"This":[52],"paper":[53],"proposes":[54],"physics-informed":[56,232],"load-to-temperature":[57],"transformation":[58,203],"(LTT)":[59],"framework":[60,88],"to":[61],"bridge":[62],"this":[63,85,202,240],"gap,":[64],"enabling":[65],"identification":[67,98],"of":[68,92,187],"comprehensive":[69],"models":[71,107,166,190],"using":[72],"only":[73],"ubiquitous":[74],"HVAC":[75,251],"load":[76],"metering":[77],"under":[78],"regular":[79],"operation":[80,252],"conditions.":[81],"We":[82,100,144],"demonstrate":[83,200],"that":[84,201],"inference":[86,173,197],"methodology":[87],"broadly":[89,227],"allows":[90],"integration":[91],"existing":[93],"classical":[94,117],"differentiable":[96,123,139,233],"system":[97],"selected,":[101],"adapted,":[102],"developed":[104,138],"four":[105],"candidate":[106,165],"following":[108],"two":[109],"modeling":[110],"paradigms:":[111],"(1)":[112],"State-Space":[113,126],"models,":[114],"considering":[115],"both":[116,152],"RC":[118],"networks":[119],"an":[121],"adapted":[122],"Physics-Constrained":[124,140],"Neural":[125],"Model":[127],"(PC-NSSM),":[128],"(2)":[130],"Transfer":[131],"Functions,":[132],"comparing":[133],"ARMAX":[134],"with":[135,192],"newly":[137],"ARX":[141],"model":[142],"(PC-ARX(1)).":[143],"validated":[145],"our":[146,163],"approach":[147],"real-world":[149],"datasets":[150],"covering":[151],"linear":[153],"thermostatic":[154],"control":[155],"non-linear":[157,215],"weather-compensated":[158],"radiator":[159,216],"control.":[160],"After":[161],"LTT,":[162],"best":[164],"achieve":[167],"2\u20135%":[168],"MAPE":[169],"in":[170,230],"unseen":[175],"operating":[176],"modes":[177],"without":[178],"\"seeing\"":[179],"any":[180],"explicit":[181,193],"data,":[183],"approximating":[184],"accuracy":[186],"ideal":[188],"baseline":[189],"trained":[191],"sensors.":[195],"Beyond":[196],"accuracy,":[198],"we":[199],"successfully":[204],"identifies":[205],"physical":[206],"invariants\u2014including":[207],"time":[208],"constants,":[209],"steady-state":[210],"heat":[211],"loss":[212],"factors,":[213],"exponents\u2014while":[217],"providing":[218],"robust":[219],"uncertainty":[220],"quantification.":[221],"By":[222],"resolving":[223],"challenge":[226],"advancing":[229],"learning":[234],"modeling,":[239],"work":[241],"paves":[242],"way":[244],"credible,":[246],"occupant-centric":[247],"energy-flexible":[249],"at":[253],"scale.":[254]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-06-20T20:08:15.867695","created_date":"2026-06-19T00:00:00"}