{"id":"https://openalex.org/W4317927913","doi":"https://doi.org/10.1145/3560905.3567767","title":"Simultaneous Sporadic Sensor Anomaly Detection for Smart Homes","display_name":"Simultaneous Sporadic Sensor Anomaly Detection for Smart Homes","publication_year":2022,"publication_date":"2022-11-06","ids":{"openalex":"https://openalex.org/W4317927913","doi":"https://doi.org/10.1145/3560905.3567767"},"language":"en","primary_location":{"id":"doi:10.1145/3560905.3567767","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3560905.3567767","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3560905.3567767","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3560905.3567767","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5023601697","display_name":"Hyunwoo Jung","orcid":"https://orcid.org/0000-0001-9711-2233"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":true,"raw_author_name":"Hyunwoo Jung","raw_affiliation_strings":["Seoul National University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038388758","display_name":"Wootack Kim","orcid":"https://orcid.org/0000-0001-7139-683X"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Wootack Kim","raw_affiliation_strings":["Seoul National University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5040238073","display_name":"Hyuna Seo","orcid":"https://orcid.org/0000-0001-5255-3131"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Hyuna Seo","raw_affiliation_strings":["Seoul National University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114626700","display_name":"Youngki Lee","orcid":"https://orcid.org/0000-0002-1319-7071"},"institutions":[{"id":"https://openalex.org/I139264467","display_name":"Seoul National University","ror":"https://ror.org/04h9pn542","country_code":"KR","type":"education","lineage":["https://openalex.org/I139264467"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Youngki Lee","raw_affiliation_strings":["Seoul National University, Republic of Korea"],"affiliations":[{"raw_affiliation_string":"Seoul National University, Republic of Korea","institution_ids":["https://openalex.org/I139264467"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5023601697"],"corresponding_institution_ids":["https://openalex.org/I139264467"],"apc_list":null,"apc_paid":null,"fwci":0.1326,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.55645259,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"1061","last_page":"1066"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T12222","display_name":"IoT-based Smart Home Systems","score":0.9976000189781189,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.8314253091812134},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.7309580445289612},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6660366058349609},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.659720778465271},{"id":"https://openalex.org/keywords/outlier","display_name":"Outlier","score":0.6003597378730774},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47274717688560486},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.441878080368042},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.43024110794067383},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4244634807109833},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3911905884742737},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.15638765692710876}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8314253091812134},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7309580445289612},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6660366058349609},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.659720778465271},{"id":"https://openalex.org/C79337645","wikidata":"https://www.wikidata.org/wiki/Q779824","display_name":"Outlier","level":2,"score":0.6003597378730774},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47274717688560486},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.441878080368042},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.43024110794067383},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4244634807109833},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3911905884742737},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.15638765692710876},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3560905.3567767","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3560905.3567767","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3560905.3567767","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3560905.3567767","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3560905.3567767","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3560905.3567767","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 20th ACM Conference on Embedded Networked Sensor Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.46000000834465027}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4317927913.pdf","grobid_xml":"https://content.openalex.org/works/W4317927913.grobid-xml"},"referenced_works_count":11,"referenced_works":["https://openalex.org/W1503337758","https://openalex.org/W2021361613","https://openalex.org/W2025361447","https://openalex.org/W2032924581","https://openalex.org/W2053587358","https://openalex.org/W2078712147","https://openalex.org/W2162543538","https://openalex.org/W2469385864","https://openalex.org/W2900248151","https://openalex.org/W2987793235","https://openalex.org/W3021789177"],"related_works":["https://openalex.org/W2499612753","https://openalex.org/W3111802945","https://openalex.org/W2806741695","https://openalex.org/W2946096271","https://openalex.org/W2295423552","https://openalex.org/W3107369729","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259"],"abstract_inverted_index":{"Dissemination":[0],"of":[1,46,49,118],"sensors":[2],"and":[3,20],"advances":[4],"in":[5],"techniques":[6],"(e.g.,":[7],"network)":[8],"has":[9],"led":[10],"to":[11,74,123,129],"the":[12,76,93,116,119],"opportunity":[13],"for":[14,32,79],"smart":[15,33,108],"home.":[16],"However,":[17],"sensor":[18,25,47,59,110],"malfunctions":[19],"difficult-to-diagnose":[21],"characteristics":[22],"hinder":[23],"robust":[24],"system":[26],"operation.":[27],"Sensor":[28],"anomaly":[29,60],"detection":[30,61],"systems":[31],"home":[34,109],"have":[35],"been":[36],"proposed,":[37],"but":[38],"they":[39],"target":[40],"only":[41],"a":[42,50,58,106],"few":[43],"specific":[44],"types":[45],"anomalies":[48,82],"single":[51],"sensor.":[52],"In":[53],"this":[54],"work,":[55],"we":[56],"propose":[57],"method":[62,104],"based":[63],"on":[64,105],"Deep":[65],"Neural":[66],"Network":[67],"(DNN),":[68],"which":[69],"automatically":[70],"extracts":[71],"critical":[72],"features":[73],"detect":[75],"anomalies,":[77],"even":[78],"simultaneous":[80],"sporadic":[81],"with":[83],"complex":[84],"data":[85],"patterns.":[86],"We":[87,100],"leverage":[88],"Hypersphere":[89],"Classification":[90],"(HSC)":[91],"[14],":[92],"state-of-the-art":[94],"DNN-based":[95],"supervised":[96],"outlier":[97],"exposure":[98],"method.":[99],"evaluate":[101],"our":[102],"proposed":[103],"public":[107],"dataset.":[111],"Our":[112],"results":[113],"show":[114],"that":[115],"performances":[117],"baselines":[120],"drop":[121],"up":[122,128],"54.4%":[124],"while":[125],"ours":[126],"drops":[127],"1.1%.":[130]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
