{"id":"https://openalex.org/W3130804234","doi":"https://doi.org/10.1109/access.2021.3060338","title":"Advances Toward the Next Generation Fire Detection: Deep LSTM Variational Autoencoder for Improved Sensitivity and Reliability","display_name":"Advances Toward the Next Generation Fire Detection: Deep LSTM Variational Autoencoder for Improved Sensitivity and Reliability","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3130804234","doi":"https://doi.org/10.1109/access.2021.3060338","mag":"3130804234"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3060338","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3060338","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09357405.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/9312710/09357405.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5015681681","display_name":"Zhaoyi Xu","orcid":"https://orcid.org/0000-0002-8498-3483"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Zhaoyi Xu","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-8498-3483","affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5006516776","display_name":"Yanjie Guo","orcid":"https://orcid.org/0000-0002-1115-7383"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Yanjie Guo","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0002-1115-7383","affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5045699117","display_name":"Joseph H. Saleh","orcid":"https://orcid.org/0000-0001-7590-9399"},"institutions":[{"id":"https://openalex.org/I130701444","display_name":"Georgia Institute of Technology","ror":"https://ror.org/01zkghx44","country_code":"US","type":"education","lineage":["https://openalex.org/I130701444"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Joseph Homer Saleh","raw_affiliation_strings":["School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA"],"raw_orcid":"https://orcid.org/0000-0001-7590-9399","affiliations":[{"raw_affiliation_string":"School of Aerospace Engineering, Georgia Institute of Technology, Atlanta, GA, USA","institution_ids":["https://openalex.org/I130701444"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I130701444"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":3.5846,"has_fulltext":true,"cited_by_count":31,"citation_normalized_percentile":{"value":0.92327308,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":"9","issue":null,"first_page":"30636","last_page":"30653"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T12597","display_name":"Fire Detection and Safety Systems","score":0.9998999834060669,"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"}},{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9940000176429749,"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/T11317","display_name":"Fire dynamics and safety research","score":0.9796000123023987,"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/computer-science","display_name":"Computer science","score":0.8126689195632935},{"id":"https://openalex.org/keywords/cusum","display_name":"CUSUM","score":0.7350423336029053},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.6897927522659302},{"id":"https://openalex.org/keywords/nist","display_name":"NIST","score":0.6322306990623474},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5385030508041382},{"id":"https://openalex.org/keywords/fire-detection","display_name":"Fire detection","score":0.5375601053237915},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.5285552740097046},{"id":"https://openalex.org/keywords/sensitivity","display_name":"Sensitivity (control systems)","score":0.5165702104568481},{"id":"https://openalex.org/keywords/ewma-chart","display_name":"EWMA chart","score":0.47682541608810425},{"id":"https://openalex.org/keywords/control-chart","display_name":"Control chart","score":0.4662666916847229},{"id":"https://openalex.org/keywords/false-alarm","display_name":"False alarm","score":0.4653416872024536},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.44838500022888184},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.438009649515152},{"id":"https://openalex.org/keywords/change-detection","display_name":"Change detection","score":0.42554694414138794},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.37487006187438965},{"id":"https://openalex.org/keywords/reliability-engineering","display_name":"Reliability engineering","score":0.33985841274261475},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.33854958415031433},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.15341287851333618},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.10146275162696838},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.09378194808959961}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8126689195632935},{"id":"https://openalex.org/C178518018","wikidata":"https://www.wikidata.org/wiki/Q1024555","display_name":"CUSUM","level":2,"score":0.7350423336029053},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.6897927522659302},{"id":"https://openalex.org/C111219384","wikidata":"https://www.wikidata.org/wiki/Q6954384","display_name":"NIST","level":2,"score":0.6322306990623474},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5385030508041382},{"id":"https://openalex.org/C2780836893","wikidata":"https://www.wikidata.org/wiki/Q19922674","display_name":"Fire detection","level":2,"score":0.5375601053237915},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.5285552740097046},{"id":"https://openalex.org/C21200559","wikidata":"https://www.wikidata.org/wiki/Q7451068","display_name":"Sensitivity (control systems)","level":2,"score":0.5165702104568481},{"id":"https://openalex.org/C74746147","wikidata":"https://www.wikidata.org/wiki/Q5324652","display_name":"EWMA chart","level":4,"score":0.47682541608810425},{"id":"https://openalex.org/C196985124","wikidata":"https://www.wikidata.org/wiki/Q1369242","display_name":"Control chart","level":3,"score":0.4662666916847229},{"id":"https://openalex.org/C2776836416","wikidata":"https://www.wikidata.org/wiki/Q1364844","display_name":"False alarm","level":2,"score":0.4653416872024536},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.44838500022888184},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.438009649515152},{"id":"https://openalex.org/C203595873","wikidata":"https://www.wikidata.org/wiki/Q25389927","display_name":"Change detection","level":2,"score":0.42554694414138794},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.37487006187438965},{"id":"https://openalex.org/C200601418","wikidata":"https://www.wikidata.org/wiki/Q2193887","display_name":"Reliability engineering","level":1,"score":0.33985841274261475},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.33854958415031433},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.15341287851333618},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.10146275162696838},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.09378194808959961},{"id":"https://openalex.org/C24326235","wikidata":"https://www.wikidata.org/wiki/Q126095","display_name":"Electronic engineering","level":1,"score":0.0},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"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/C97355855","wikidata":"https://www.wikidata.org/wiki/Q11473","display_name":"Thermodynamics","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"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/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"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/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3060338","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3060338","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09357405.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:35a697f09d0d401eb3017a528313a9aa","is_oa":true,"landing_page_url":"https://doaj.org/article/35a697f09d0d401eb3017a528313a9aa","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":"IEEE Access, Vol 9, Pp 30636-30653 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3060338","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3060338","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09357405.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320306101","display_name":"National Aeronautics and Space Administration","ror":"https://ror.org/027ka1x80"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3130804234.pdf","grobid_xml":"https://content.openalex.org/works/W3130804234.grobid-xml"},"referenced_works_count":56,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1528387358","https://openalex.org/W1985690171","https://openalex.org/W2017874056","https://openalex.org/W2024336827","https://openalex.org/W2044836500","https://openalex.org/W2045638068","https://openalex.org/W2069451827","https://openalex.org/W2101109743","https://openalex.org/W2122646361","https://openalex.org/W2123372707","https://openalex.org/W2128038346","https://openalex.org/W2151803712","https://openalex.org/W2166481425","https://openalex.org/W2296267969","https://openalex.org/W2321847991","https://openalex.org/W2371625969","https://openalex.org/W2402302915","https://openalex.org/W2461729787","https://openalex.org/W2467604901","https://openalex.org/W2502276222","https://openalex.org/W2548252014","https://openalex.org/W2740696094","https://openalex.org/W2786827964","https://openalex.org/W2789894922","https://openalex.org/W2793947836","https://openalex.org/W2883525675","https://openalex.org/W2888728157","https://openalex.org/W2919974312","https://openalex.org/W2964121744","https://openalex.org/W2969882235","https://openalex.org/W2970971581","https://openalex.org/W2995751392","https://openalex.org/W3005874793","https://openalex.org/W3019740599","https://openalex.org/W3021818594","https://openalex.org/W3022657898","https://openalex.org/W3036604424","https://openalex.org/W3083853617","https://openalex.org/W3106543020","https://openalex.org/W3126272279","https://openalex.org/W3138192619","https://openalex.org/W3139214261","https://openalex.org/W3196620053","https://openalex.org/W4247756218","https://openalex.org/W4255375128","https://openalex.org/W4285719527","https://openalex.org/W4295312788","https://openalex.org/W6631190155","https://openalex.org/W6712909570","https://openalex.org/W6720208624","https://openalex.org/W6742066070","https://openalex.org/W6766978945","https://openalex.org/W6767190027","https://openalex.org/W6782509707","https://openalex.org/W6792109256"],"related_works":["https://openalex.org/W1990746329","https://openalex.org/W4232974465","https://openalex.org/W2931607628","https://openalex.org/W2096733066","https://openalex.org/W2085977497","https://openalex.org/W3006471751","https://openalex.org/W2900112507","https://openalex.org/W1966132454","https://openalex.org/W3176858885","https://openalex.org/W2769959759"],"abstract_inverted_index":{"Fire":[0],"detection":[1,56,80,116,162,187],"is":[2],"a":[3,7,53,191],"critical":[4],"component":[5],"of":[6,35,86,112,185],"building":[8,30],"safety":[9],"monitoring":[10,46],"system":[11],"and":[12,32,41,66,76,93,100,108,134,146,152,176,189],"remains":[13],"an":[14],"important":[15],"research":[16],"area":[17],"with":[18,117],"weighty":[19],"practical":[20],"relevance.":[21],"Significant":[22],"advances":[23],"have":[24],"occurred":[25],"in":[26,29],"recent":[27],"years":[28],"automation,":[31],"the":[33,84,110,121,144,147,156,160],"operation":[34],"buildings":[36],"has":[37],"become":[38],"more":[39,44],"complex":[40],"requires":[42],"ever":[43],"effective":[45],"systems.":[47],"In":[48],"this":[49],"work,":[50],"we":[51,89,94],"develop":[52,90],"novel":[54],"fire":[55,79,99,115],"method":[57],"using":[58,143],"deep":[59],"Long-Short":[60],"Term":[61],"Memory":[62],"(LSTM)":[63],"neural":[64],"networks":[65],"variational":[67],"autoencoder":[68],"(VAE)":[69],"to":[70],"meet":[71],"these":[72],"increasingly":[73],"stringent":[74],"requirements":[75],"outperform":[77],"existing":[78],"methods.":[81],"To":[82],"evaluate":[83],"effectiveness":[85],"our":[87,113],"method,":[88],"high-fidelity":[91],"simulations,":[92],"use":[95],"datasets":[96],"from":[97],"real-world":[98,148],"non-fire":[101],"experiments":[102,149],"provided":[103],"by":[104],"NIST.":[105],"We":[106],"compare":[107],"discuss":[109],"performance":[111],"proposed":[114],"alternative":[118],"methods,":[119],"including":[120],"standard":[122],"LSTM,":[123],"cumulative":[124],"sum":[125],"control":[126],"chart":[127],"(CUSUM),":[128],"exponentially":[129],"weighted":[130],"moving":[131],"average":[132],"(EWMA),":[133],"two":[135],"currently":[136],"used":[137],"fixed-temperature":[138],"heat":[139],"detectors.":[140],"The":[141,180],"results":[142,181],"simulation-based":[145],"are":[150],"complementary,":[151],"they":[153],"indicate":[154,190],"that":[155],"LSTM-VAE":[157],"robustly":[158],"outperforms":[159],"other":[161,186],"methods":[163,188],"with,":[164],"for":[165],"example,":[166],"statistically":[167],"significant":[168],"shorter":[169],"alarm":[170],"time":[171],"lags,":[172],"no":[173,177],"missed":[174],"detection,":[175],"false":[178],"alarms.":[179],"also":[182],"identify":[183],"shortcomings":[184],"clear":[192],"ranking":[193],"among":[194],"them":[195],"(LSTM-VAE>-EWMA":[196],">LSTM>-CUSUM).":[197]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":10},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
