{"id":"https://openalex.org/W3042026052","doi":"https://doi.org/10.1109/wf-iot48130.2020.9221098","title":"Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach","display_name":"Predictive Maintenance for Edge-Based Sensor Networks: A Deep Reinforcement Learning Approach","publication_year":2020,"publication_date":"2020-06-01","ids":{"openalex":"https://openalex.org/W3042026052","doi":"https://doi.org/10.1109/wf-iot48130.2020.9221098","mag":"3042026052"},"language":"en","primary_location":{"id":"doi:10.1109/wf-iot48130.2020.9221098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wf-iot48130.2020.9221098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 6th World Forum on Internet of Things (WF-IoT)","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.03313","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5042242910","display_name":"Kevin Shen Hoong Ong","orcid":"https://orcid.org/0000-0002-1611-7612"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Kevin Shen Hoong Ong","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University Singapore","Nanyang Technological University, Singapore School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore School of Computer Science and Engineering","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091266202","display_name":"Dusit Niyato","orcid":"https://orcid.org/0000-0002-7442-7416"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Dusit Niyato","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University Singapore","Nanyang Technological University, Singapore School of Computer Science and Engineering"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University Singapore","institution_ids":["https://openalex.org/I172675005"]},{"raw_affiliation_string":"Nanyang Technological University, Singapore School of Computer Science and Engineering","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5060020877","display_name":"Chau Yuen","orcid":"https://orcid.org/0000-0002-9307-2120"},"institutions":[{"id":"https://openalex.org/I152815399","display_name":"Singapore University of Technology and Design","ror":"https://ror.org/05j6fvn87","country_code":"SG","type":"education","lineage":["https://openalex.org/I152815399"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Chau Yuen","raw_affiliation_strings":["Engineering Product Development, Singapore University of Technology and Design","Singapore University of Technology and Design Engineering Product Development"],"affiliations":[{"raw_affiliation_string":"Engineering Product Development, Singapore University of Technology and Design","institution_ids":["https://openalex.org/I152815399"]},{"raw_affiliation_string":"Singapore University of Technology and Design Engineering Product Development","institution_ids":["https://openalex.org/I152815399"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5042242910"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":0.7419,"has_fulltext":false,"cited_by_count":9,"citation_normalized_percentile":{"value":0.70890457,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10876","display_name":"Fault Detection and Control Systems","score":0.993399977684021,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems 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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9932000041007996,"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/T10780","display_name":"Reliability and Maintenance Optimization","score":0.9909999966621399,"subfield":{"id":"https://openalex.org/subfields/2213","display_name":"Safety, Risk, Reliability and Quality"},"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/downtime","display_name":"Downtime","score":0.8231735229492188},{"id":"https://openalex.org/keywords/predictive-maintenance","display_name":"Predictive maintenance","score":0.8229906558990479},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.7247591614723206},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.60718834400177},{"id":"https://openalex.org/keywords/preventive-maintenance","display_name":"Preventive maintenance","score":0.5789492130279541},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5475238561630249},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.5310848951339722},{"id":"https://openalex.org/keywords/corrective-maintenance","display_name":"Corrective maintenance","score":0.5298832654953003},{"id":"https://openalex.org/keywords/proactive-maintenance","display_name":"Proactive maintenance","score":0.48654189705848694},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.4355516731739044},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3692249059677124},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3336145281791687},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2977522611618042}],"concepts":[{"id":"https://openalex.org/C180591934","wikidata":"https://www.wikidata.org/wiki/Q1253369","display_name":"Downtime","level":2,"score":0.8231735229492188},{"id":"https://openalex.org/C70452415","wikidata":"https://www.wikidata.org/wiki/Q3182448","display_name":"Predictive maintenance","level":2,"score":0.8229906558990479},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.7247591614723206},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.60718834400177},{"id":"https://openalex.org/C24090081","wikidata":"https://www.wikidata.org/wiki/Q1043452","display_name":"Preventive maintenance","level":2,"score":0.5789492130279541},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5475238561630249},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.5310848951339722},{"id":"https://openalex.org/C129529059","wikidata":"https://www.wikidata.org/wiki/Q2291518","display_name":"Corrective maintenance","level":3,"score":0.5298832654953003},{"id":"https://openalex.org/C141417316","wikidata":"https://www.wikidata.org/wiki/Q3278390","display_name":"Proactive maintenance","level":3,"score":0.48654189705848694},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.4355516731739044},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3692249059677124},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3336145281791687},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2977522611618042},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1109/wf-iot48130.2020.9221098","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wf-iot48130.2020.9221098","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE 6th World Forum on Internet of Things (WF-IoT)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.03313","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.03313","pdf_url":"https://arxiv.org/pdf/2007.03313","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"mag:3042026052","is_oa":true,"landing_page_url":"http://export.arxiv.org/pdf/2007.03313","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"arXiv (Cornell University)","raw_type":null},{"id":"doi:10.48550/arxiv.2007.03313","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2007.03313","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.03313","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.03313","pdf_url":"https://arxiv.org/pdf/2007.03313","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/17","display_name":"Partnerships for the goals","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3042026052.pdf"},"referenced_works_count":20,"referenced_works":["https://openalex.org/W1757796397","https://openalex.org/W2032301033","https://openalex.org/W2120841219","https://openalex.org/W2126773300","https://openalex.org/W2155968351","https://openalex.org/W2201581102","https://openalex.org/W2415594836","https://openalex.org/W2591055632","https://openalex.org/W2623491082","https://openalex.org/W2744067593","https://openalex.org/W2746553466","https://openalex.org/W2801175696","https://openalex.org/W2895851557","https://openalex.org/W2911048887","https://openalex.org/W4251052400","https://openalex.org/W6637967152","https://openalex.org/W6687681856","https://openalex.org/W6739193204","https://openalex.org/W6754973754","https://openalex.org/W6758527398"],"related_works":["https://openalex.org/W3094457271","https://openalex.org/W2401307145","https://openalex.org/W2898789964","https://openalex.org/W2979583465","https://openalex.org/W2594075068","https://openalex.org/W3055205275","https://openalex.org/W1510288078","https://openalex.org/W2904280798","https://openalex.org/W2048808031","https://openalex.org/W2027986351","https://openalex.org/W1972966992","https://openalex.org/W2944342107","https://openalex.org/W2324099498","https://openalex.org/W2882121747","https://openalex.org/W2804474080","https://openalex.org/W1558159398","https://openalex.org/W2095327910","https://openalex.org/W2848262145","https://openalex.org/W2087621891","https://openalex.org/W2491304571"],"abstract_inverted_index":{"Failure":[0],"of":[1,13,23,34,40,131],"mission-critical":[2],"equipment":[3,15,42,58,74,94,132],"interrupts":[4],"production":[5],"and":[6,31,47,92,115],"results":[7,124],"in":[8],"monetary":[9],"loss.":[10],"The":[11],"risk":[12],"unplanned":[14],"downtime":[16],"can":[17],"be":[18],"minimized":[19],"through":[20],"Predictive":[21],"Maintenance":[22],"revenue":[24],"generating":[25],"assets":[26],"to":[27],"ensure":[28],"optimal":[29,112],"performance":[30],"safe":[32],"operation":[33],"equipment.":[35,121],"However,":[36],"the":[37,41,93,107,126],"increased":[38],"sensorization":[39],"generates":[43],"a":[44,64,85],"data":[45],"deluge,":[46],"existing":[48],"machine-learning":[49],"based":[50],"predictive":[51,73],"model":[52],"alone":[53],"becomes":[54],"inadequate":[55],"for":[56,72,99,119,128],"timely":[57],"condition":[59],"predictions.":[60],"In":[61],"this":[62],"paper,":[63],"model-free":[65],"Deep":[66],"Reinforcement":[67],"Learning":[68],"algorithm":[69,109],"is":[70,97],"proposed":[71,108],"maintenance":[75,113,133],"from":[76],"an":[77,111,136],"equipment-based":[78],"sensor":[79,86,90],"network":[80],"context.":[81],"Within":[82],"each":[83,120],"equipment,":[84],"device":[87],"aggregates":[88],"raw":[89],"data,":[91],"health":[95],"status":[96],"analyzed":[98],"anomalous":[100],"events.":[101],"Unlike":[102],"traditional":[103],"black-box":[104],"regression":[105],"models,":[106],"self-learns":[110],"policy":[114],"provides":[116],"actionable":[117],"recommendation":[118],"Our":[122],"experimental":[123],"demonstrate":[125],"potential":[127],"broader":[129],"range":[130],"applications":[134],"as":[135],"automatic":[137],"learning":[138],"framework.":[139]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":4}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2025-10-10T00:00:00"}