{"id":"https://openalex.org/W4286572030","doi":"https://doi.org/10.1109/metroind4.0iot54413.2022.9831517","title":"A TinyML approach to non-repudiable anomaly detection in extreme industrial environments","display_name":"A TinyML approach to non-repudiable anomaly detection in extreme industrial environments","publication_year":2022,"publication_date":"2022-06-07","ids":{"openalex":"https://openalex.org/W4286572030","doi":"https://doi.org/10.1109/metroind4.0iot54413.2022.9831517"},"language":"en","primary_location":{"id":"doi:10.1109/metroind4.0iot54413.2022.9831517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroind4.0iot54413.2022.9831517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Workshop on Metrology for Industry 4.0 &amp; IoT (MetroInd4.0&amp;IoT)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5072435713","display_name":"Mattia Antonini","orcid":"https://orcid.org/0000-0003-1685-0264"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Mattia Antonini","raw_affiliation_strings":["Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","institution_ids":["https://openalex.org/I2277624104"]},{"raw_affiliation_string":"OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073870729","display_name":"Miguel Pincheira","orcid":"https://orcid.org/0000-0002-5847-2145"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Miguel Pincheira","raw_affiliation_strings":["Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","institution_ids":["https://openalex.org/I2277624104"]},{"raw_affiliation_string":"OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027706529","display_name":"Massimo Vecchio","orcid":"https://orcid.org/0000-0003-4426-8220"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Massimo Vecchio","raw_affiliation_strings":["Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","institution_ids":["https://openalex.org/I2277624104"]},{"raw_affiliation_string":"OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044155942","display_name":"Fabio Antonelli","orcid":"https://orcid.org/0000-0001-5221-7752"},"institutions":[{"id":"https://openalex.org/I2277624104","display_name":"Fondazione Bruno Kessler","ror":"https://ror.org/01j33xk10","country_code":"IT","type":"facility","lineage":["https://openalex.org/I2277624104"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Fabio Antonelli","raw_affiliation_strings":["Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Fondazione Bruno Kessler,OpenIoT Research Unit, DI Center,Trento,Italy","institution_ids":["https://openalex.org/I2277624104"]},{"raw_affiliation_string":"OpenIoT Research Unit, DI Center, Fondazione Bruno Kessler, Trento, Italy","institution_ids":["https://openalex.org/I2277624104"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I2277624104"],"apc_list":null,"apc_paid":null,"fwci":3.2051,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":{"value":0.9347259,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"397","last_page":"402"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9998999834060669,"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":0.9998999834060669,"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/T12111","display_name":"Industrial Vision Systems and Defect Detection","score":0.9714000225067139,"subfield":{"id":"https://openalex.org/subfields/2209","display_name":"Industrial and Manufacturing 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/T12205","display_name":"Time Series Analysis and Forecasting","score":0.9710999727249146,"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/anomaly-detection","display_name":"Anomaly detection","score":0.8020883202552795},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7351976037025452},{"id":"https://openalex.org/keywords/downtime","display_name":"Downtime","score":0.6347244381904602},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5690216422080994},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.5363686084747314},{"id":"https://openalex.org/keywords/asset","display_name":"Asset (computer security)","score":0.4112872779369354},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3699643909931183},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.35112786293029785},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.24586239457130432},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.22673079371452332},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.1855936348438263},{"id":"https://openalex.org/keywords/operating-system","display_name":"Operating system","score":0.09704652428627014}],"concepts":[{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.8020883202552795},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7351976037025452},{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.6347244381904602},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5690216422080994},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.5363686084747314},{"id":"https://openalex.org/C76178495","wikidata":"https://www.wikidata.org/wiki/Q4808784","display_name":"Asset (computer security)","level":2,"score":0.4112872779369354},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3699643909931183},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.35112786293029785},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.24586239457130432},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.22673079371452332},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.1855936348438263},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.09704652428627014}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/metroind4.0iot54413.2022.9831517","is_oa":false,"landing_page_url":"https://doi.org/10.1109/metroind4.0iot54413.2022.9831517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Workshop on Metrology for Industry 4.0 &amp; IoT (MetroInd4.0&amp;IoT)","raw_type":"proceedings-article"},{"id":"pmh:oai:iris.uniecampus.it:11389/39798","is_oa":false,"landing_page_url":"https://hdl.handle.net/11389/39798","pdf_url":null,"source":{"id":"https://openalex.org/S4306400077","display_name":"IRIS eCampus Telematic University (Universit\u00e0 degli Studi eCampus)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I167322064","host_organization_name":"Universit\u00e0 degli Studi eCampus","host_organization_lineage":["https://openalex.org/I167322064"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/9","display_name":"Industry, innovation and infrastructure","score":0.5600000023841858}],"awards":[],"funders":[{"id":"https://openalex.org/F4320320300","display_name":"European Commission","ror":"https://ror.org/00k4n6c32"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2148922589","https://openalex.org/W2296719434","https://openalex.org/W2606084320","https://openalex.org/W2898468067","https://openalex.org/W2994001460","https://openalex.org/W2998789622","https://openalex.org/W3003257820","https://openalex.org/W3035965352","https://openalex.org/W3044495145","https://openalex.org/W3067862503","https://openalex.org/W3099878876","https://openalex.org/W3110142540","https://openalex.org/W3186677043","https://openalex.org/W3213478591"],"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/W2109143577","https://openalex.org/W2161582432","https://openalex.org/W1972812226","https://openalex.org/W4250391074","https://openalex.org/W1985537075"],"abstract_inverted_index":{"Unforeseen":[0],"failures":[1],"of":[2,59,123,167,176,190,196,202],"industrial":[3,107],"assets":[4,20,71],"may":[5],"lead":[6],"to":[7,30,50,65,69,87,92,172,182],"unexpected":[8],"downtime":[9],"with":[10],"a":[11,137,142,155,187],"huge":[12],"impact":[13,195],"on":[14,141],"critical":[15],"business":[16],"processes.":[17],"Therefore,":[18],"modern":[19],"usually":[21],"include":[22],"several":[23],"embedded":[24],"sensors":[25],"and":[26,53,99,113,144,204],"processing":[27,90],"units,":[28],"allowing":[29],"monitor":[31],"certain":[32],"operational":[33],"parameters,":[34],"i.e.,":[35],"Condition":[36,67],"Monitoring.":[37],"The":[38],"sensed":[39],"data":[40],"can":[41,61],"be":[42],"later":[43],"analyzed":[44],"using":[45],"Machine":[46],"Learning":[47],"(ML)":[48],"approaches":[49],"detect":[51],"anomalies":[52],"anticipate":[54],"failures.":[55],"Furthermore,":[56,171],"the":[57,63,85,93,101,119,152,164,168,174,177,194],"Internet":[58],"Things":[60],"provide":[62],"tools":[64],"extend":[66],"Monitoring":[68],"legacy":[70],"that":[72,135],"do":[73],"not":[74],"have":[75],"onboard":[76],"sensing":[77],"capabilities.":[78],"In":[79],"general,":[80],"these":[81],"IoT":[82,125,146],"devices":[83],"offer":[84],"opportunity":[86],"move":[88],"ML":[89],"closer":[91],"monitored":[94,169],"asset,":[95],"thus":[96],"reducing":[97],"costs":[98,203],"simplifying":[100],"anomaly":[102,132,158],"detection":[103,133,159],"system.":[104],"However,":[105],"extreme":[106],"environments":[108],"present":[109],"harsh":[110],"operating":[111],"conditions":[112],"limited":[114,150],"resources,":[115,151],"further":[116],"exacerbated":[117],"by":[118],"reduced":[120],"computation":[121],"capabilities":[122],"most":[124],"devices.":[126],"This":[127],"paper":[128],"proposes":[129],"an":[130],"ML-based":[131],"system":[134],"uses":[136],"retrofitting":[138],"kit":[139],"based":[140],"constrained":[143],"cost-effective":[145],"device.":[147],"Despite":[148],"its":[149],"latter":[153],"executes":[154],"state-of-the-art":[156],"unsupervised":[157],"algorithm":[160],"locally,":[161],"autonomously":[162],"learning":[163],"normality":[165],"behavior":[166],"asset.":[170],"improve":[173],"transparency":[175],"monitoring":[178],"process,":[179],"we":[180],"propose":[181],"leverage":[183],"blockchain":[184],"technology":[185],"as":[186],"non-repudiable":[188],"repository":[189],"information,":[191],"also":[192],"assessing":[193],"such":[197],"implementation":[198],"choice":[199],"in":[200],"terms":[201],"overhead.":[205]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
