{"id":"https://openalex.org/W2994803408","doi":"https://doi.org/10.1145/3368926.3369661","title":"Sensor-based Abnormal Behavior Detection Using Autoencoder","display_name":"Sensor-based Abnormal Behavior Detection Using Autoencoder","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2994803408","doi":"https://doi.org/10.1145/3368926.3369661","mag":"2994803408"},"language":"en","primary_location":{"id":"doi:10.1145/3368926.3369661","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","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/A5100734815","display_name":"Seungjin Lee","orcid":"https://orcid.org/0000-0003-1034-1098"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Seungjin Lee","raw_affiliation_strings":["Sejong University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sejong University, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5107967381","display_name":"Dongil Shin","orcid":"https://orcid.org/0000-0002-8621-715X"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongil Shin","raw_affiliation_strings":["Sejong University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sejong University, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008353224","display_name":"Dongkyoo Shin","orcid":"https://orcid.org/0000-0002-2665-3339"},"institutions":[{"id":"https://openalex.org/I28777354","display_name":"Sejong University","ror":"https://ror.org/00aft1q37","country_code":"KR","type":"education","lineage":["https://openalex.org/I28777354"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Dongkyoo Shin","raw_affiliation_strings":["Sejong University, Seoul, Korea"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sejong University, Seoul, Korea","institution_ids":["https://openalex.org/I28777354"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5100734815"],"corresponding_institution_ids":["https://openalex.org/I28777354"],"apc_list":null,"apc_paid":null,"fwci":0.2903,"has_fulltext":false,"cited_by_count":6,"citation_normalized_percentile":{"value":0.68286908,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"111","last_page":"117"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9995999932289124,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.972100019454956,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9639000296592712,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/autoencoder","display_name":"Autoencoder","score":0.8924865126609802},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6179215908050537},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5573027729988098},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44857582449913025},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3342931270599365},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.17388811707496643}],"concepts":[{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.8924865126609802},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6179215908050537},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5573027729988098},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44857582449913025},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3342931270599365},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.17388811707496643}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3368926.3369661","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3368926.3369661","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Tenth International Symposium on Information and Communication Technology  - SoICT 2019","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":13,"referenced_works":["https://openalex.org/W1546449802","https://openalex.org/W1959608418","https://openalex.org/W2004099281","https://openalex.org/W2112831159","https://openalex.org/W2124658620","https://openalex.org/W2126868529","https://openalex.org/W2137019369","https://openalex.org/W2145094598","https://openalex.org/W2164489414","https://openalex.org/W2181347294","https://openalex.org/W2193564998","https://openalex.org/W2312556800","https://openalex.org/W2422305492"],"related_works":["https://openalex.org/W4220775285","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2772917594","https://openalex.org/W2775347418","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747"],"abstract_inverted_index":{"The":[0,174,190],"population":[1],"of":[2,10,23,30,70,185,207,217,239],"elderly":[3,34,91,231],"people":[4,24,35,48,92,96],"is":[5,42,64,137,160,224],"increasing,":[6],"with":[7,97,200],"the":[8,16,21,68,119,129,171,183,186,237],"development":[9],"an":[11,79,149,157,205],"aging":[12],"society":[13],"all":[14],"over":[15],"world.":[17],"As":[18],"a":[19,107,122,144,161,168,215],"result,":[20],"number":[22],"who":[25],"need":[26],"to":[27,66,89,124,133,140,166,226],"take":[28],"care":[29],"themselves,":[31],"such":[32,105,127,147],"as":[33,106,128,148],"living":[36,93],"alone":[37,94],"or":[38,112,132,232],"suffering":[39],"from":[40,170],"dementia,":[41],"also":[43,55,138],"increasing.":[44],"Caring":[45],"for":[46,72,241],"these":[47],"requires":[49,121],"not":[50],"only":[51],"social":[52],"burdens":[53],"but":[54,151],"economic":[56],"costs.":[57],"A":[58],"system":[59],"that":[60],"manages":[61],"their":[62],"behavior":[63,81,142,172,180,188,202,213],"essential":[65],"reduce":[67,236],"cost":[69,238],"caring":[71,240],"them.":[73,242],"In":[74],"this":[75,153,194],"study,":[76,154],"we":[77,155],"propose":[78],"abnormal":[80,179,212],"detection":[82],"model":[83,110,146,176,223],"using":[84,143],"smart":[85],"home":[86],"sensor":[87],"data":[88],"manage":[90],"and":[95,198,235],"dementia.":[98],"Previous":[99],"studies":[100],"have":[101],"used":[102,156,192],"probability":[103],"models":[104,191],"hidden":[108],"Markov":[109],"(HMM)":[111],"support":[113],"vector":[114],"machine":[115],"(SVM)":[116],"model.":[117],"However,":[118],"HMM":[120],"process":[123],"estimate":[125],"values":[126],"initial":[130],"probability,":[131],"define":[134],"states.":[135],"It":[136],"possible":[139],"detect":[141,178],"classification":[145],"SVM,":[150],"in":[152,193,228],"autoencoder,":[158],"which":[159],"representative":[162],"unsupervised":[163],"learning":[164],"model,":[165],"obtain":[167],"pattern":[169],"data.":[173,189],"autoencoder":[175],"can":[177],"by":[181],"extracting":[182],"characteristics":[184],"normal":[187,201],"study":[195],"were":[196],"trained":[197],"tested":[199],"data,":[203,214],"showing":[204],"accuracy":[206],"more":[208],"than":[209],"99%.":[210],"For":[211],"loss":[216],"about":[218],"10-30%":[219],"was":[220],"observed.":[221],"This":[222],"expected":[225],"assist":[227],"effectively":[229],"managing":[230],"demented":[233],"patients":[234]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2021,"cited_by_count":2}],"updated_date":"2026-04-29T09:16:38.111599","created_date":"2025-10-10T00:00:00"}