{"id":"https://openalex.org/W2989756061","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909725","title":"Exploiting Breadth in Energy Datasets for Automated Device Identification","display_name":"Exploiting Breadth in Energy Datasets for Automated Device Identification","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2989756061","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909725","mag":"2989756061"},"language":"en","primary_location":{"id":"doi:10.1109/smartgridcomm.2019.8909725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","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/A5043080680","display_name":"Sean Barker","orcid":"https://orcid.org/0000-0003-3844-7687"},"institutions":[{"id":"https://openalex.org/I135474949","display_name":"Bowdoin College","ror":"https://ror.org/03gh96r95","country_code":"US","type":"education","lineage":["https://openalex.org/I135474949"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Sean Barker","raw_affiliation_strings":["Bowdoin College, Brunswick, ME, USA"],"affiliations":[{"raw_affiliation_string":"Bowdoin College, Brunswick, ME, USA","institution_ids":["https://openalex.org/I135474949"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051073108","display_name":"Kyle Morrison","orcid":null},"institutions":[{"id":"https://openalex.org/I135474949","display_name":"Bowdoin College","ror":"https://ror.org/03gh96r95","country_code":"US","type":"education","lineage":["https://openalex.org/I135474949"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Kyle Morrison","raw_affiliation_strings":["Bowdoin College, Brunswick, ME, USA"],"affiliations":[{"raw_affiliation_string":"Bowdoin College, Brunswick, ME, USA","institution_ids":["https://openalex.org/I135474949"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5017825338","display_name":"Tucker Williams","orcid":null},"institutions":[{"id":"https://openalex.org/I135474949","display_name":"Bowdoin College","ror":"https://ror.org/03gh96r95","country_code":"US","type":"education","lineage":["https://openalex.org/I135474949"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tucker Williams","raw_affiliation_strings":["Bowdoin College, Brunswick, ME, USA"],"affiliations":[{"raw_affiliation_string":"Bowdoin College, Brunswick, ME, USA","institution_ids":["https://openalex.org/I135474949"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043080680"],"corresponding_institution_ids":["https://openalex.org/I135474949"],"apc_list":null,"apc_paid":null,"fwci":0.3577,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.62009499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"52","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10603","display_name":"Smart Grid Energy Management","score":0.9998999834060669,"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/T10121","display_name":"Building Energy and Comfort Optimization","score":0.9904999732971191,"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/T11954","display_name":"Energy Efficiency and Management","score":0.9873999953269958,"subfield":{"id":"https://openalex.org/subfields/2105","display_name":"Renewable Energy, Sustainability and the Environment"},"field":{"id":"https://openalex.org/fields/21","display_name":"Energy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7682411670684814},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.6897410750389099},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.5367644429206848},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.505526065826416},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4983546733856201},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4763346314430237},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.45763400197029114},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4556875228881836},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4429195523262024},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.42733532190322876},{"id":"https://openalex.org/keywords/efficient-energy-use","display_name":"Efficient energy use","score":0.41755905747413635},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.12088415026664734}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682411670684814},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.6897410750389099},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.5367644429206848},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.505526065826416},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4983546733856201},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4763346314430237},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45763400197029114},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4556875228881836},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4429195523262024},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.42733532190322876},{"id":"https://openalex.org/C2742236","wikidata":"https://www.wikidata.org/wiki/Q924713","display_name":"Efficient energy use","level":2,"score":0.41755905747413635},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.12088415026664734},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartgridcomm.2019.8909725","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909725","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":24,"referenced_works":["https://openalex.org/W1479651931","https://openalex.org/W1504694836","https://openalex.org/W1509579154","https://openalex.org/W1575597416","https://openalex.org/W1972602829","https://openalex.org/W1996944908","https://openalex.org/W2032924581","https://openalex.org/W2033435309","https://openalex.org/W2043279449","https://openalex.org/W2046682591","https://openalex.org/W2123910460","https://openalex.org/W2125055259","https://openalex.org/W2151729265","https://openalex.org/W2164577899","https://openalex.org/W2255051834","https://openalex.org/W2279379996","https://openalex.org/W2943271466","https://openalex.org/W3099873379","https://openalex.org/W3102977103","https://openalex.org/W6630488282","https://openalex.org/W6634499289","https://openalex.org/W6661243264","https://openalex.org/W6695076252","https://openalex.org/W6936597892"],"related_works":["https://openalex.org/W4375867731","https://openalex.org/W2012531322","https://openalex.org/W2402761219","https://openalex.org/W2611989081","https://openalex.org/W2785900585","https://openalex.org/W2353730437","https://openalex.org/W2490303674","https://openalex.org/W2609066826","https://openalex.org/W2810752900","https://openalex.org/W2365677836"],"abstract_inverted_index":{"The":[0],"recent":[1],"explosion":[2],"of":[3,14,19,73,85,98,125],"interest":[4],"in":[5,28,40],"smart":[6,46],"building":[7,47],"energy-efficiency":[8],"has":[9],"led":[10],"to":[11,34,122],"a":[12,29,37,70],"proliferation":[13],"public":[15],"energy":[16],"datasets.":[17,53],"Most":[18],"these":[20],"datasets":[21,106],"focus":[22],"on":[23,51,95,103,134],"depth":[24],"(i.e.,":[25],"many":[26,41],"devices":[27,39],"few":[30,38],"buildings)":[31],"as":[32],"opposed":[33],"breadth":[35,59,128],"(e.g.,":[36],"buildings),":[42],"and":[43,109,113,120],"thus":[44],"most":[45],"algorithms":[48],"are":[49,64],"evaluated":[50],"depth-oriented":[52],"We":[54],"argue":[55],"that":[56,63,132],"increasing":[57],"data":[58,118],"conveys":[60],"important":[61],"benefits":[62,115],"not":[65],"easily":[66],"achieved":[67],"by":[68],"even":[69],"large":[71],"quantity":[72],"deep":[74],"data.":[75],"As":[76],"an":[77,91],"illustrative":[78],"case":[79],"study,":[80],"we":[81],"consider":[82],"the":[83,123],"problem":[84],"classifying":[86],"previously":[87],"unseen":[88],"appliances":[89],"using":[90],"off-the-shelf":[92],"classifier":[93],"trained":[94],"known":[96],"instances":[97],"other":[99],"devices.":[100],"Our":[101],"experiments":[102],"multiple":[104],"real-world":[105],"(both":[107],"depth-":[108],"breadth-oriented)":[110],"demonstrate":[111],"significant":[112],"sustained":[114],"from":[116],"increased":[117],"breadth,":[119],"point":[121],"importance":[124],"incorporating":[126],"greater":[127],"into":[129],"similar":[130],"techniques":[131],"rely":[133],"generalized":[135],"electrical":[136],"load":[137],"models.":[138]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}