{"id":"https://openalex.org/W4323566429","doi":"https://doi.org/10.3390/s23062913","title":"Proactive Fault Prediction of Fog Devices Using LSTM-CRP Conceptual Framework for IoT Applications","display_name":"Proactive Fault Prediction of Fog Devices Using LSTM-CRP Conceptual Framework for IoT Applications","publication_year":2023,"publication_date":"2023-03-08","ids":{"openalex":"https://openalex.org/W4323566429","doi":"https://doi.org/10.3390/s23062913","pmid":"https://pubmed.ncbi.nlm.nih.gov/36991624"},"language":"en","primary_location":{"id":"doi:10.3390/s23062913","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23062913","pdf_url":"https://www.mdpi.com/1424-8220/23/6/2913/pdf?version=1678353047","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj","pubmed"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/1424-8220/23/6/2913/pdf?version=1678353047","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007445687","display_name":"H. Sabireen","orcid":null},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Sabireen H","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India","institution_ids":["https://openalex.org/I876193797"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071238732","display_name":"V. Neelanarayanan","orcid":"https://orcid.org/0000-0001-9206-0251"},"institutions":[{"id":"https://openalex.org/I876193797","display_name":"Vellore Institute of Technology University","ror":"https://ror.org/00qzypv28","country_code":"IN","type":"education","lineage":["https://openalex.org/I876193797"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Neelanarayanan Venkataraman","raw_affiliation_strings":["School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Vellore Institute of Technology, Chennai 600127, India","institution_ids":["https://openalex.org/I876193797"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5071238732"],"corresponding_institution_ids":["https://openalex.org/I876193797"],"apc_list":{"value":2400,"currency":"CHF","value_usd":2598},"apc_paid":{"value":2400,"currency":"CHF","value_usd":2598},"fwci":3.4575,"has_fulltext":true,"cited_by_count":18,"citation_normalized_percentile":{"value":0.92850955,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"23","issue":"6","first_page":"2913","last_page":"2913"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9997000098228455,"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"}},"topics":[{"id":"https://openalex.org/T10273","display_name":"IoT and Edge/Fog Computing","score":0.9997000098228455,"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/T12079","display_name":"IoT Networks and Protocols","score":0.9850000143051147,"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"}},{"id":"https://openalex.org/T12697","display_name":"Water Quality Monitoring Technologies","score":0.9805999994277954,"subfield":{"id":"https://openalex.org/subfields/2312","display_name":"Water Science and Technology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.7713730335235596},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6013137102127075},{"id":"https://openalex.org/keywords/scalability","display_name":"Scalability","score":0.5994997620582581},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.5538976788520813},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.5447250008583069},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.49883389472961426},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.4954112768173218},{"id":"https://openalex.org/keywords/edge-device","display_name":"Edge device","score":0.4903881549835205},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4757494628429413},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46555501222610474},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46492600440979004},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.44786494970321655},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.4209796190261841},{"id":"https://openalex.org/keywords/distributed-computing","display_name":"Distributed computing","score":0.4197099804878235},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3642429709434509},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.29831385612487793},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1492886245250702},{"id":"https://openalex.org/keywords/cloud-computing","display_name":"Cloud computing","score":0.13261201977729797},{"id":"https://openalex.org/keywords/database","display_name":"Database","score":0.12056928873062134}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7713730335235596},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6013137102127075},{"id":"https://openalex.org/C48044578","wikidata":"https://www.wikidata.org/wiki/Q727490","display_name":"Scalability","level":2,"score":0.5994997620582581},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.5538976788520813},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.5447250008583069},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.49883389472961426},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.4954112768173218},{"id":"https://openalex.org/C138236772","wikidata":"https://www.wikidata.org/wiki/Q25098575","display_name":"Edge device","level":3,"score":0.4903881549835205},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4757494628429413},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46555501222610474},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46492600440979004},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.44786494970321655},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.4209796190261841},{"id":"https://openalex.org/C120314980","wikidata":"https://www.wikidata.org/wiki/Q180634","display_name":"Distributed computing","level":1,"score":0.4197099804878235},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3642429709434509},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.29831385612487793},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1492886245250702},{"id":"https://openalex.org/C79974875","wikidata":"https://www.wikidata.org/wiki/Q483639","display_name":"Cloud computing","level":2,"score":0.13261201977729797},{"id":"https://openalex.org/C77088390","wikidata":"https://www.wikidata.org/wiki/Q8513","display_name":"Database","level":1,"score":0.12056928873062134},{"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/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","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/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.3390/s23062913","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23062913","pdf_url":"https://www.mdpi.com/1424-8220/23/6/2913/pdf?version=1678353047","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},{"id":"pmid:36991624","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/36991624","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors (Basel, Switzerland)","raw_type":null},{"id":"pmh:oai:pubmedcentral.nih.gov:10054027","is_oa":true,"landing_page_url":"https://www.ncbi.nlm.nih.gov/pmc/articles/10054027","pdf_url":"https://pmc.ncbi.nlm.nih.gov/articles/PMC10054027/pdf/sensors-23-02913.pdf","source":{"id":"https://openalex.org/S2764455111","display_name":"PubMed Central","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors (Basel)","raw_type":"Text"},{"id":"pmh:oai:doaj.org/article:e7a53bf9bf84419583945390da21fc54","is_oa":true,"landing_page_url":"https://doaj.org/article/e7a53bf9bf84419583945390da21fc54","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors, Vol 23, Iss 6, p 2913 (2023)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/1424-8220/23/6/2913/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/s23062913","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Sensors; Volume 23; Issue 6; Pages: 2913","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/s23062913","is_oa":true,"landing_page_url":"https://doi.org/10.3390/s23062913","pdf_url":"https://www.mdpi.com/1424-8220/23/6/2913/pdf?version=1678353047","source":{"id":"https://openalex.org/S101949793","display_name":"Sensors","issn_l":"1424-8220","issn":["1424-8220"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Sensors","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4323566429.pdf"},"referenced_works_count":46,"referenced_works":["https://openalex.org/W1494581921","https://openalex.org/W1837982953","https://openalex.org/W1900331253","https://openalex.org/W1969359541","https://openalex.org/W2003663690","https://openalex.org/W2012753837","https://openalex.org/W2018058497","https://openalex.org/W2060204338","https://openalex.org/W2064675550","https://openalex.org/W2111619626","https://openalex.org/W2114623221","https://openalex.org/W2136848157","https://openalex.org/W2142812297","https://openalex.org/W2148508494","https://openalex.org/W2160821994","https://openalex.org/W2341925029","https://openalex.org/W2463062468","https://openalex.org/W2567327791","https://openalex.org/W2753452557","https://openalex.org/W2755009304","https://openalex.org/W2756139420","https://openalex.org/W2765776605","https://openalex.org/W2781420345","https://openalex.org/W2790957846","https://openalex.org/W2795237059","https://openalex.org/W2807972111","https://openalex.org/W2810084952","https://openalex.org/W2893503005","https://openalex.org/W2901849107","https://openalex.org/W2917153503","https://openalex.org/W2929092969","https://openalex.org/W2944851425","https://openalex.org/W2972192263","https://openalex.org/W2980506400","https://openalex.org/W2982661883","https://openalex.org/W2984881398","https://openalex.org/W2988015189","https://openalex.org/W2997421118","https://openalex.org/W3012463771","https://openalex.org/W3046557892","https://openalex.org/W3081547323","https://openalex.org/W3120126734","https://openalex.org/W3164721774","https://openalex.org/W4242598204","https://openalex.org/W6665630473","https://openalex.org/W6761565887"],"related_works":["https://openalex.org/W2979760315","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W3189674571","https://openalex.org/W4322761281","https://openalex.org/W2914646191","https://openalex.org/W4238233472","https://openalex.org/W4313339048","https://openalex.org/W4386004629","https://openalex.org/W2942586735"],"abstract_inverted_index":{"Technology":[0],"plays":[1],"a":[2,34,49,106,127,203,213,241,262,276],"significant":[3,263],"role":[4],"in":[5,116,122,265,292],"our":[6],"daily":[7],"lives":[8],"as":[9,15],"real-time":[10],"applications":[11],"and":[12,19,80,133,137,174,212,229,284,301],"services":[13,185],"such":[14],"video":[16],"surveillance":[17],"systems":[18],"the":[20,29,67,95,117,147,156,162,168,178,193,197,209,217,223,234,266,285],"Internet":[21],"of":[22,31,37,97,100,119,150,167,180,206,225,247,253,268,271,288],"Things":[23],"(IoT)":[24],"are":[25,71,91],"rapidly":[26],"developing.":[27],"With":[28],"introduction":[30],"fog":[32,43,50,60,101,123,181,254,272],"computing,":[33],"large":[35],"amount":[36],"processing":[38,280],"has":[39],"been":[40],"done":[41],"by":[42,56,274],"devices":[44,124],"for":[45],"IoT":[46,68,187],"applications.":[47,69,188],"However,":[48],"device's":[51],"reliability":[52],"may":[53,63],"be":[54],"affected":[55],"insufficient":[57,120],"resources":[58,99,121,270],"at":[59],"nodes,":[61],"which":[62,220],"fail":[64],"to":[65,112,153,186,294],"process":[66],"There":[70],"obvious":[72],"maintenance":[73],"challenges":[74],"associated":[75],"with":[76,196,240],"many":[77],"read-write":[78],"operations":[79],"hazardous":[81],"edge":[82],"environments.":[83],"To":[84,145],"increase":[85],"reliability,":[86],"scalable":[87],"fault-predictive":[88],"proactive":[89,114,238],"methods":[90],"needed":[92],"that":[93,192],"predict":[94,113],"failure":[96,151,286],"inadequate":[98,154],"devices.":[102],"In":[103],"this":[104],"paper,":[105],"Recurrent":[107],"Neural":[108],"Network":[109],"(RNN)-based":[110],"method":[111,201,236],"faults":[115,239],"event":[118],"based":[125],"on":[126,208,216],"conceptual":[128,169],"Long":[129],"Short-Term":[130],"Memory":[131,136],"(LSTM)":[132],"novel":[134],"Computation":[135],"Power":[138],"(CRP)":[139],"rule-based":[140],"network":[141,199],"policy":[142,200],"is":[143,159],"proposed.":[144],"identify":[146],"precise":[148],"cause":[149],"due":[152],"resources,":[155],"proposed":[157,258],"CRP":[158,198],"built":[160],"upon":[161],"LSTM":[163,194],"network.":[164],"As":[165],"part":[166],"framework":[170,259],"proposed,":[171],"fault":[172,175],"detectors":[173],"monitors":[176],"prevent":[177],"outage":[179],"nodes":[182,273],"while":[183],"providing":[184,249],"The":[189,257],"results":[190],"show":[191,261],"along":[195],"achieves":[202],"prediction":[204,252,267,289],"accuracy":[205,215],"95.16%":[207],"training":[210],"data":[211],"98.69%":[214],"testing":[218],"data,":[219],"significantly":[221],"outperforms":[222],"performance":[224],"existing":[226],"machine":[227],"learning":[228,231],"deep":[230],"techniques.":[232],"Furthermore,":[233],"presented":[235],"predicts":[237],"normalized":[242],"root":[243],"mean":[244],"square":[245],"error":[246],"0.017,":[248],"an":[250],"accurate":[251],"node":[255],"failure.":[256],"experiments":[260],"improvement":[264],"inaccurate":[269],"having":[275],"minimum":[277],"delay,":[278],"low":[279],"time,":[281],"improved":[282],"accuracy,":[283],"rate":[287],"was":[290],"faster":[291],"comparison":[293],"traditional":[295],"LSTM,":[296],"Support":[297],"Vector":[298],"Machines":[299],"(SVM),":[300],"Logistic":[302],"Regression.":[303]},"counts_by_year":[{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":5}],"updated_date":"2026-05-21T06:26:12.895304","created_date":"2025-10-10T00:00:00"}
