{"id":"https://openalex.org/W2952589828","doi":"https://doi.org/10.1109/access.2019.2921912","title":"Anomaly Detection, Analysis and Prediction Techniques in IoT Environment: A Systematic Literature Review","display_name":"Anomaly Detection, Analysis and Prediction Techniques in IoT Environment: A Systematic Literature Review","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2952589828","doi":"https://doi.org/10.1109/access.2019.2921912","mag":"2952589828"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2921912","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2921912","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08733806.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08733806.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Muhammad Fahim","orcid":"https://orcid.org/0000-0001-7863-5311"},"institutions":[{"id":"https://openalex.org/I4210116741","display_name":"Innopolis University","ror":"https://ror.org/02b7jh107","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210116741"]}],"countries":["RU"],"is_corresponding":true,"raw_author_name":"Muhammad Fahim","raw_affiliation_strings":["Institute of Information Systems, Innopolis University, Innopolis, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Information Systems, Innopolis University, Innopolis, Russia","institution_ids":["https://openalex.org/I4210116741"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090153909","display_name":"Alberto Sillitti","orcid":null},"institutions":[{"id":"https://openalex.org/I4210116741","display_name":"Innopolis University","ror":"https://ror.org/02b7jh107","country_code":"RU","type":"education","lineage":["https://openalex.org/I4210116741"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Alberto Sillitti","raw_affiliation_strings":["Institute of Information Systems, Innopolis University, Innopolis, Russia"],"affiliations":[{"raw_affiliation_string":"Institute of Information Systems, Innopolis University, Innopolis, Russia","institution_ids":["https://openalex.org/I4210116741"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210116741"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":9.3933,"has_fulltext":true,"cited_by_count":214,"citation_normalized_percentile":{"value":0.98295785,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"7","issue":null,"first_page":"81664","last_page":"81681"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":1.0,"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":1.0,"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":0.998199999332428,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9947999715805054,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7998105883598328},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.7913517355918884},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5957323312759399},{"id":"https://openalex.org/keywords/downtime","display_name":"Downtime","score":0.5185818672180176},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.48718470335006714},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4848812520503998},{"id":"https://openalex.org/keywords/data-stream-mining","display_name":"Data stream mining","score":0.4724964201450348},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.46788233518600464},{"id":"https://openalex.org/keywords/wireless-sensor-network","display_name":"Wireless sensor network","score":0.4556586444377899},{"id":"https://openalex.org/keywords/systematic-review","display_name":"Systematic review","score":0.4527107775211334},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4196079969406128}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7998105883598328},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.7913517355918884},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5957323312759399},{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.5185818672180176},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.48718470335006714},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4848812520503998},{"id":"https://openalex.org/C89198739","wikidata":"https://www.wikidata.org/wiki/Q3079880","display_name":"Data stream mining","level":2,"score":0.4724964201450348},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.46788233518600464},{"id":"https://openalex.org/C24590314","wikidata":"https://www.wikidata.org/wiki/Q336038","display_name":"Wireless sensor network","level":2,"score":0.4556586444377899},{"id":"https://openalex.org/C189708586","wikidata":"https://www.wikidata.org/wiki/Q1504425","display_name":"Systematic review","level":3,"score":0.4527107775211334},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4196079969406128},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0},{"id":"https://openalex.org/C2779473830","wikidata":"https://www.wikidata.org/wiki/Q1540899","display_name":"MEDLINE","level":2,"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/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2921912","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2921912","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08733806.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:ed58cfcc8ae54c46b50be4097a3992a2","is_oa":true,"landing_page_url":"https://doaj.org/article/ed58cfcc8ae54c46b50be4097a3992a2","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 81664-81681 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2921912","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2921912","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08733806.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2952589828.pdf","grobid_xml":"https://content.openalex.org/works/W2952589828.grobid-xml"},"referenced_works_count":81,"referenced_works":["https://openalex.org/W122923078","https://openalex.org/W1423966491","https://openalex.org/W1515008182","https://openalex.org/W1584308190","https://openalex.org/W1737989768","https://openalex.org/W1824651852","https://openalex.org/W1917413620","https://openalex.org/W1979370046","https://openalex.org/W1980070248","https://openalex.org/W1986202539","https://openalex.org/W1987019926","https://openalex.org/W2007556941","https://openalex.org/W2011778831","https://openalex.org/W2021583824","https://openalex.org/W2023290212","https://openalex.org/W2023840804","https://openalex.org/W2032860265","https://openalex.org/W2034239152","https://openalex.org/W2038819732","https://openalex.org/W2045946501","https://openalex.org/W2051803334","https://openalex.org/W2054608156","https://openalex.org/W2056702017","https://openalex.org/W2058118558","https://openalex.org/W2059745508","https://openalex.org/W2071763130","https://openalex.org/W2073523114","https://openalex.org/W2084512860","https://openalex.org/W2091319256","https://openalex.org/W2120096192","https://openalex.org/W2120236791","https://openalex.org/W2122646361","https://openalex.org/W2126868529","https://openalex.org/W2131739422","https://openalex.org/W2134255060","https://openalex.org/W2142889610","https://openalex.org/W2148173149","https://openalex.org/W2151054033","https://openalex.org/W2161029186","https://openalex.org/W2165743104","https://openalex.org/W2185125590","https://openalex.org/W2241984682","https://openalex.org/W2308071406","https://openalex.org/W2323758128","https://openalex.org/W2342518110","https://openalex.org/W2406523001","https://openalex.org/W2464284844","https://openalex.org/W2528199750","https://openalex.org/W2533835508","https://openalex.org/W2534428265","https://openalex.org/W2551502590","https://openalex.org/W2554061044","https://openalex.org/W2556077447","https://openalex.org/W2557877271","https://openalex.org/W2559446181","https://openalex.org/W2560792524","https://openalex.org/W2600859289","https://openalex.org/W2607361017","https://openalex.org/W2740720967","https://openalex.org/W2743189459","https://openalex.org/W2744316982","https://openalex.org/W2762208441","https://openalex.org/W2765884627","https://openalex.org/W2766807000","https://openalex.org/W2807164734","https://openalex.org/W2814079182","https://openalex.org/W2898604056","https://openalex.org/W2899789068","https://openalex.org/W2899895429","https://openalex.org/W2901588159","https://openalex.org/W4239954780","https://openalex.org/W6605003677","https://openalex.org/W6635269506","https://openalex.org/W6645462788","https://openalex.org/W6682188055","https://openalex.org/W6686152136","https://openalex.org/W6698240980","https://openalex.org/W6736862581","https://openalex.org/W6744986105","https://openalex.org/W6755923150","https://openalex.org/W6756663677"],"related_works":["https://openalex.org/W2046276983","https://openalex.org/W2954002293","https://openalex.org/W2078264086","https://openalex.org/W2892741875","https://openalex.org/W2164372000","https://openalex.org/W3190734578","https://openalex.org/W1595351371","https://openalex.org/W91065195","https://openalex.org/W3191523773","https://openalex.org/W2964556660"],"abstract_inverted_index":{"Anomaly":[0],"detection":[1,105],"has":[2],"attracted":[3],"considerable":[4],"attention":[5],"from":[6,119],"the":[7,11,17,41,70,96,116,124,151,154,166,192],"research":[8,73,111,147,172],"community":[9],"in":[10,28,85,123,174,178],"past":[12],"few":[13,171],"years":[14],"due":[15],"to":[16,54,80,121,150,164,197,204],"advancement":[18],"of":[19,37,69,98,127,146,156,161],"sensor":[20],"monitoring":[21,40],"technologies,":[22],"low-cost":[23],"solutions,":[24],"and":[25,44,66,78,87,138,170,186,212],"high":[26],"impact":[27],"diverse":[29],"application":[30,125],"domains.":[31,90],"Sensors":[32],"generate":[33],"a":[34,99,144],"huge":[35,47,167],"amount":[36],"data":[38,49,152],"while":[39],"physical":[42],"spaces":[43],"objects.":[45],"These":[46],"collected":[48],"streams":[50],"can":[51,188],"be":[52],"analyzed":[53],"identify":[55],"unhealthy":[56],"behaviors.":[57],"It":[58],"may":[59],"reduce":[60],"functional":[61],"risks,":[62],"avoid":[63],"unseen":[64],"problems,":[65,200],"prevent":[67],"downtime":[68],"systems.":[71,140],"Many":[72],"methodologies":[74],"have":[75,142],"been":[76],"designed":[77],"developed":[79],"determine":[81],"such":[82],"anomalous":[83],"behaviors":[84],"security":[86],"risk":[88],"analysis":[89,155],"In":[91],"this":[92],"paper,":[93],"we":[94],"present":[95],"results":[97],"systematic":[100],"literature":[101],"review":[102],"about":[103],"anomaly":[104,209],"techniques":[106,207],"except":[107],"for":[108,208],"these":[109],"dominant":[110],"areas.":[112],"We":[113,141],"focus":[114],"on":[115,182],"studies":[117],"published":[118],"2000":[120],"2018":[122],"areas":[126],"intelligent":[128],"inhabitant":[129],"environments,":[130],"transportation":[131],"systems,":[132,135],"health":[133],"care":[134],"smart":[136],"objects,":[137],"industrial":[139],"identified":[143],"number":[145],"gaps":[148],"related":[149],"collection,":[153],"imbalanced":[157],"large":[158],"datasets,":[159],"limitations":[160],"statistical":[162],"methods":[163],"process":[165],"sensory":[168],"data,":[169],"articles":[173],"abnormal":[175],"behavior":[176],"prediction":[177],"real":[179,199],"scenarios.":[180],"Based":[181],"our":[183],"analysis,":[184],"researchers":[185],"practitioners":[187],"acquaint":[189],"themselves":[190],"with":[191],"existing":[193],"approaches,":[194],"use":[195],"them":[196],"solve":[198],"and/or":[201],"further":[202],"contribute":[203],"developing":[205],"novel":[206],"detection,":[210],"prediction,":[211],"analysis.":[213]},"counts_by_year":[{"year":2026,"cited_by_count":8},{"year":2025,"cited_by_count":38},{"year":2024,"cited_by_count":53},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":29},{"year":2021,"cited_by_count":25},{"year":2020,"cited_by_count":9},{"year":2019,"cited_by_count":2}],"updated_date":"2026-04-11T08:14:18.477133","created_date":"2025-10-10T00:00:00"}
