{"id":"https://openalex.org/W2991082611","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909729","title":"MEED: An Unsupervised Multi-Environment Event Detector for Non-Intrusive Load Monitoring","display_name":"MEED: An Unsupervised Multi-Environment Event Detector for Non-Intrusive Load Monitoring","publication_year":2019,"publication_date":"2019-10-01","ids":{"openalex":"https://openalex.org/W2991082611","doi":"https://doi.org/10.1109/smartgridcomm.2019.8909729","mag":"2991082611"},"language":"en","primary_location":{"id":"doi:10.1109/smartgridcomm.2019.8909729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909729","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/A5018930556","display_name":"Daniel Jorde","orcid":"https://orcid.org/0000-0003-2511-8817"},"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":true,"raw_author_name":"Daniel Jorde","raw_affiliation_strings":["Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046920192","display_name":"Matthias Kahl","orcid":"https://orcid.org/0000-0002-6354-2646"},"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":"Matthias Kahl","raw_affiliation_strings":["Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5072791865","display_name":"Hans\u2010Arno Jacobsen","orcid":"https://orcid.org/0000-0003-0813-0101"},"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":"Hans-Arno Jacobsen","raw_affiliation_strings":["Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany"],"affiliations":[{"raw_affiliation_string":"Chair for Application and Middleware Systems, Technische Universit\u00e4t M\u00fcnchen, Germany","institution_ids":["https://openalex.org/I62916508"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5018930556"],"corresponding_institution_ids":["https://openalex.org/I62916508"],"apc_list":null,"apc_paid":null,"fwci":0.8346,"has_fulltext":false,"cited_by_count":12,"citation_normalized_percentile":{"value":0.7469313,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"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":0.9997000098228455,"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":0.9997000098228455,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9869999885559082,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T14011","display_name":"Elevator Systems and Control","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/computer-science","display_name":"Computer science","score":0.7621477842330933},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.6917121410369873},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5971853733062744},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5763298273086548},{"id":"https://openalex.org/keywords/energy","display_name":"Energy (signal processing)","score":0.4833904802799225},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4820009768009186},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47824373841285706},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.45123088359832764},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4265488088130951},{"id":"https://openalex.org/keywords/unsupervised-learning","display_name":"Unsupervised learning","score":0.419695109128952},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41184481978416443},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.35169151425361633},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.1880263388156891},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10763251781463623},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.0720260739326477}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7621477842330933},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.6917121410369873},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5971853733062744},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5763298273086548},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.4833904802799225},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4820009768009186},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47824373841285706},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.45123088359832764},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4265488088130951},{"id":"https://openalex.org/C8038995","wikidata":"https://www.wikidata.org/wiki/Q1152135","display_name":"Unsupervised learning","level":2,"score":0.419695109128952},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41184481978416443},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.35169151425361633},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.1880263388156891},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10763251781463623},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.0720260739326477},{"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/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/smartgridcomm.2019.8909729","is_oa":false,"landing_page_url":"https://doi.org/10.1109/smartgridcomm.2019.8909729","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","score":0.5699999928474426,"display_name":"Affordable and clean energy"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1272474793","https://openalex.org/W1522301498","https://openalex.org/W1533861849","https://openalex.org/W1972312492","https://openalex.org/W2000132463","https://openalex.org/W2043279449","https://openalex.org/W2067113445","https://openalex.org/W2078921071","https://openalex.org/W2101521385","https://openalex.org/W2122646361","https://openalex.org/W2123910460","https://openalex.org/W2131774270","https://openalex.org/W2162855079","https://openalex.org/W2274317587","https://openalex.org/W2291326641","https://openalex.org/W2328118626","https://openalex.org/W2345639291","https://openalex.org/W2545189634","https://openalex.org/W2559922179","https://openalex.org/W2620772283","https://openalex.org/W2741144289","https://openalex.org/W2794835514","https://openalex.org/W2795087227","https://openalex.org/W2795358293","https://openalex.org/W2807936141","https://openalex.org/W2964121744","https://openalex.org/W6631190155","https://openalex.org/W6631943919","https://openalex.org/W6667177350","https://openalex.org/W6704800599","https://openalex.org/W6738771346","https://openalex.org/W6936597892"],"related_works":["https://openalex.org/W3013693939","https://openalex.org/W2159052453","https://openalex.org/W2566616303","https://openalex.org/W3131327266","https://openalex.org/W2734887215","https://openalex.org/W4297051394","https://openalex.org/W2997921738","https://openalex.org/W2806873178","https://openalex.org/W2770818364","https://openalex.org/W2965146396"],"abstract_inverted_index":{"The":[0,101,122],"accurate":[1],"detection":[2],"of":[3,38,47,75,103,131],"transitions":[4],"between":[5],"appliance":[6,39],"states":[7,40],"in":[8,156],"electrical":[9],"signals":[10],"is":[11,93,105],"the":[12,76,128,132,136,157],"fundamental":[13],"step":[14],"that":[15,92,125],"numerous":[16],"energy":[17],"conserving":[18],"applications,":[19],"such":[20],"as":[21,69],"Non-Intrusive":[22],"Load":[23],"Monitoring,":[24],"rely":[25],"on.":[26],"So":[27],"far,":[28],"domain":[29],"experts":[30],"define":[31],"rules":[32],"and":[33,41,60,134,143,152],"patterns":[34],"to":[35,42,62,110],"detect":[36],"changes":[37],"extract":[43],"detailed":[44],"consumption":[45],"information":[46],"individual":[48],"appliances":[49],"subsequently.":[50],"Such":[51],"event":[52,88],"detectors":[53],"are":[54],"specifically":[55],"designed":[56],"for":[57,66],"certain":[58],"environments":[59],"need":[61],"be":[63],"tediously":[64],"adapted":[65],"new":[67,85],"ones,":[68],"they":[70],"require":[71],"in-depth":[72],"expert":[73],"knowledge":[74],"environment.":[77],"To":[78],"overcome":[79],"this":[80],"limitation,":[81],"we":[82],"propose":[83],"a":[84,96,140],"unsupervised,":[86],"multi-environment":[87],"detector,":[89],"called":[90],"MEED,":[91],"based":[94],"on":[95,114,139],"bidirectional":[97],"recurrent":[98],"denoising":[99],"autoencoder.":[100],"performance":[102],"MEED":[104,126],"evaluated":[106],"by":[107],"comparing":[108],"it":[109],"two":[111,115],"state-of-the-art":[112],"algorithms":[113,138],"publicly":[116],"available":[117],"datasets":[118],"from":[119],"different":[120],"environments.":[121,159],"results":[123],"show":[124],"improves":[127],"current":[129],"state":[130],"art":[133],"outperforms":[135],"reference":[137],"residential":[141],"(BLUED)":[142],"an":[144],"office":[145],"environment":[146],"(BLOND)":[147],"dataset":[148],"while":[149],"being":[150],"trained":[151],"used":[153],"fully":[154],"unsupervised":[155],"heterogeneous":[158]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}