{"id":"https://openalex.org/W4382119857","doi":"https://doi.org/10.1109/iotm.001.2200232","title":"Simple Heuristics as a Viable Alternative to Machine Learning-Based Anomaly Detection in Industrial IoT","display_name":"Simple Heuristics as a Viable Alternative to Machine Learning-Based Anomaly Detection in Industrial IoT","publication_year":2023,"publication_date":"2023-06-26","ids":{"openalex":"https://openalex.org/W4382119857","doi":"https://doi.org/10.1109/iotm.001.2200232"},"language":"en","primary_location":{"id":"doi:10.1109/iotm.001.2200232","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iotm.001.2200232","pdf_url":null,"source":{"id":"https://openalex.org/S4210201254","display_name":"IEEE Internet of Things Magazine","issn_l":"2576-3180","issn":["2576-3180","2576-3199"],"is_oa":false,"is_in_doaj":false,"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 Internet of Things Magazine","raw_type":"journal-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/A5092270158","display_name":"Balint Bicski","orcid":null},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Balint Bicski","raw_affiliation_strings":["Budapest University of Technology and Economics,Hungary","Budapest University of Technology and Economics, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Budapest University of Technology and Economics, Hungary","institution_ids":["https://openalex.org/I29770179"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023052225","display_name":"K\u00e1roly Farkas","orcid":"https://orcid.org/0000-0001-6965-2689"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Karoly Farkas","raw_affiliation_strings":["Budapest University of Technology and Economics,Hungary","Budapest University of Technology and Economics, Hungary","Gloster Infocommunications Plc, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Budapest University of Technology and Economics, Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Gloster Infocommunications Plc, Hungary","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086869190","display_name":"Adri\u00e1n Pek\u00e1r","orcid":"https://orcid.org/0000-0003-4511-8267"},"institutions":[{"id":"https://openalex.org/I29770179","display_name":"Budapest University of Technology and Economics","ror":"https://ror.org/02w42ss30","country_code":"HU","type":"education","lineage":["https://openalex.org/I29770179"]}],"countries":["HU"],"is_corresponding":false,"raw_author_name":"Adrian Pekar","raw_affiliation_strings":["Budapest University of Technology and Economics,Hungary","Budapest University of Technology and Economics, Hungary","ELKH-BME Information Systems Research Group, Hungary"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Budapest University of Technology and Economics,Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"Budapest University of Technology and Economics, Hungary","institution_ids":["https://openalex.org/I29770179"]},{"raw_affiliation_string":"ELKH-BME Information Systems Research Group, Hungary","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I29770179"],"apc_list":{"value":2995,"currency":"USD","value_usd":2995},"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.06160563,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"6","issue":"3","first_page":"104","last_page":"109"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9991999864578247,"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":0.9991999864578247,"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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9988999962806702,"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"}},{"id":"https://openalex.org/T11918","display_name":"Forecasting Techniques and Applications","score":0.973800003528595,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.86273193359375},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.7531360983848572},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7202852964401245},{"id":"https://openalex.org/keywords/heuristic","display_name":"Heuristic","score":0.7199438810348511},{"id":"https://openalex.org/keywords/heuristics","display_name":"Heuristics","score":0.7128767967224121},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6585270762443542},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6395118236541748},{"id":"https://openalex.org/keywords/simple","display_name":"Simple (philosophy)","score":0.5860257148742676},{"id":"https://openalex.org/keywords/anomaly","display_name":"Anomaly (physics)","score":0.5758081674575806},{"id":"https://openalex.org/keywords/autoregressive-model","display_name":"Autoregressive model","score":0.5336229205131531},{"id":"https://openalex.org/keywords/series","display_name":"Series (stratigraphy)","score":0.4631364643573761},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.4583633840084076},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.42869675159454346},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3987185060977936},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3425532877445221},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13135188817977905},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.12313085794448853}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.86273193359375},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.7531360983848572},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7202852964401245},{"id":"https://openalex.org/C173801870","wikidata":"https://www.wikidata.org/wiki/Q201413","display_name":"Heuristic","level":2,"score":0.7199438810348511},{"id":"https://openalex.org/C127705205","wikidata":"https://www.wikidata.org/wiki/Q5748245","display_name":"Heuristics","level":2,"score":0.7128767967224121},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6585270762443542},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6395118236541748},{"id":"https://openalex.org/C2780586882","wikidata":"https://www.wikidata.org/wiki/Q7520643","display_name":"Simple (philosophy)","level":2,"score":0.5860257148742676},{"id":"https://openalex.org/C12997251","wikidata":"https://www.wikidata.org/wiki/Q567560","display_name":"Anomaly (physics)","level":2,"score":0.5758081674575806},{"id":"https://openalex.org/C159877910","wikidata":"https://www.wikidata.org/wiki/Q2202883","display_name":"Autoregressive model","level":2,"score":0.5336229205131531},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.4631364643573761},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.4583633840084076},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.42869675159454346},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3987185060977936},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3425532877445221},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13135188817977905},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.12313085794448853},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","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/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C26873012","wikidata":"https://www.wikidata.org/wiki/Q214781","display_name":"Condensed matter physics","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/iotm.001.2200232","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/iotm.001.2200232","pdf_url":null,"source":{"id":"https://openalex.org/S4210201254","display_name":"IEEE Internet of Things Magazine","issn_l":"2576-3180","issn":["2576-3180","2576-3199"],"is_oa":false,"is_in_doaj":false,"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 Internet of Things Magazine","raw_type":"journal-article"},{"id":"pmh:oai:real.mtak.hu:174878","is_oa":false,"landing_page_url":"http://real.mtak.hu/174878/1/Simple_Heuristics_as_a_Viable_Alternative_to_Machine_Learning-Based_Anomaly_Detection_in_Industrial_IoT-2.pdf","pdf_url":"http://real.mtak.hu/174878/1/Simple_Heuristics_as_a_Viable_Alternative_to_Machine_Learning-Based_Anomaly_Detection_in_Industrial_IoT-2.pdf","source":{"id":"https://openalex.org/S4306400081","display_name":"Repository of the Academy's Library (Library of the Hungarian Academy of Sciences)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210140733","host_organization_name":"Library and Information Centre of the Hungarian Academy of Sciences","host_organization_lineage":["https://openalex.org/I4210140733"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.46000000834465027,"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320335908","display_name":"Nemzeti Kutat\u00e1si, Fejleszt\u00e9si \u00e9s Innovaci\u00f3s Alap","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W2336226252","https://openalex.org/W2511127197","https://openalex.org/W2743617586","https://openalex.org/W2768947629","https://openalex.org/W2786827964","https://openalex.org/W2794778778","https://openalex.org/W2954327103","https://openalex.org/W2955914832","https://openalex.org/W3014106621","https://openalex.org/W3043320740","https://openalex.org/W3094964338","https://openalex.org/W3106543020","https://openalex.org/W3111419800","https://openalex.org/W3117435741","https://openalex.org/W3198059351","https://openalex.org/W6927549558"],"related_works":["https://openalex.org/W3186512740","https://openalex.org/W4363671829","https://openalex.org/W2780476542","https://openalex.org/W2806741695","https://openalex.org/W4290647774","https://openalex.org/W3189286258","https://openalex.org/W3207797160","https://openalex.org/W3210364259","https://openalex.org/W4300558037","https://openalex.org/W2667207928"],"abstract_inverted_index":{"This":[0],"article":[1],"evaluates":[2],"the":[3,16,32,52,55,99,107,118,145,163],"efficacy":[4,33],"of":[5,20,34,57,67,113,165],"simple":[6],"heuristic":[7,96],"approaches":[8],"compared":[9],"to":[10,82,103,117,127,138,171],"sophisticated":[11,88,139],"machine":[12,58],"learning":[13,44,59],"by":[14,86,101],"quantifying":[15],"accuracy":[17],"and":[18,41],"timeliness":[19],"selected":[21],"multivariate":[22,140],"anomaly":[23,45,142],"detectors":[24],"on":[25,144],"industrial":[26],"time":[27,123],"series.":[28],"It":[29],"specifically":[30],"examines":[31],"two":[35],"probabilistic":[36],"detectors,":[37],"a":[38,42,65,84],"statistical":[39],"detector":[40],"deep":[43],"detector.":[46],"The":[47,70,93],"presented":[48],"work":[49],"stems":[50],"from":[51,157],"observation":[53],"that":[54,77,162],"application":[56,147],"methods":[60,89,132,168],"may":[61],"be":[62],"unfounded":[63],"in":[64,73,111],"variety":[66],"use":[68],"cases.":[69],"findings":[71],"made":[72],"this":[74],"study":[75],"imply":[76],"there":[78],"is":[79,125],"no":[80],"reason":[81],"over-engineer":[83],"solution":[85],"applying":[87],"without":[90],"genuine":[91],"grounds.":[92],"conventional":[94],"autoregressive":[95],"model":[97],"outperforms":[98],"autoencoder":[100,108],"up":[102,126],"7.2":[104],"percent.":[105],"Furthermore,":[106],"also":[109],"underperforms":[110],"terms":[112],"execution":[114],"time.":[115],"Compared":[116],"simpler":[119],"approaches,":[120],"its":[121],"computational":[122],"complexity":[124],"47":[128],"percent":[129],"higher.":[130],"Simple":[131],"thus":[133],"emerge":[134],"as":[135],"viable":[136],"alternatives":[137],"time-series":[141],"detection":[143],"evaluated":[146],"domain.":[148],"Our":[149],"conclusions":[150],"remained":[151],"valid":[152],"through":[153],"examining":[154],"datasets":[155],"originating":[156],"other":[158],"domains.":[159],"We":[160],"infer":[161],"performance":[164],"more":[166],"elaborated":[167],"requires":[169],"verification":[170],"justify":[172],"their":[173],"usage.":[174]},"counts_by_year":[],"updated_date":"2026-08-21T09:56:20.448147","created_date":"2025-10-10T00:00:00"}
