{"id":"https://openalex.org/W2887529570","doi":"https://doi.org/10.23919/wac.2018.8430428","title":"Data-Driven Fault Detection of Un-Manned Aerial Vehicles Using Supervised Learning Over Cloud Networks","display_name":"Data-Driven Fault Detection of Un-Manned Aerial Vehicles Using Supervised Learning Over Cloud Networks","publication_year":2018,"publication_date":"2018-06-01","ids":{"openalex":"https://openalex.org/W2887529570","doi":"https://doi.org/10.23919/wac.2018.8430428","mag":"2887529570"},"language":"en","primary_location":{"id":"doi:10.23919/wac.2018.8430428","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wac.2018.8430428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 World Automation Congress (WAC)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://figshare.com/articles/conference_contribution/Data-Driven_Fault_Detection_of_Un-Manned_Aerial_Vehicles_Using_Supervised_Learning_over_Cloud_Networks/20595246","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5043356210","display_name":"Parsa Yousefi","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Parsa Yousefi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5008284047","display_name":"Hamid Fekriazgomi","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Hamid Fekriazgomi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5033567692","display_name":"Mevl\u00fct Demir","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mevlut A. Demir","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090986184","display_name":"John J. Prevost","orcid":"https://orcid.org/0000-0002-2303-599X"},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"John J. Prevost","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5113537394","display_name":"Mo Jamshidi","orcid":null},"institutions":[{"id":"https://openalex.org/I45438204","display_name":"The University of Texas at San Antonio","ror":"https://ror.org/01kd65564","country_code":"US","type":"education","lineage":["https://openalex.org/I45438204"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mo Jamshidi","raw_affiliation_strings":["Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA"],"affiliations":[{"raw_affiliation_string":"Department of Electrical and Computer Engineering, The University of Texas at San Antonio, San Antonio, Texas, USA","institution_ids":["https://openalex.org/I45438204"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5043356210"],"corresponding_institution_ids":["https://openalex.org/I45438204"],"apc_list":null,"apc_paid":null,"fwci":1.523,"has_fulltext":false,"cited_by_count":23,"citation_normalized_percentile":{"value":0.87166699,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9979000091552734,"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":0.9979000091552734,"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/T12597","display_name":"Fire Detection and Safety Systems","score":0.9968000054359436,"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/T14257","display_name":"Advanced Measurement and Detection Methods","score":0.9908999800682068,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7312124967575073},{"id":"https://openalex.org/keywords/drone","display_name":"Drone","score":0.6474317312240601},{"id":"https://openalex.org/keywords/fault-detection-and-isolation","display_name":"Fault detection and isolation","score":0.6388007402420044},{"id":"https://openalex.org/keywords/reliability","display_name":"Reliability (semiconductor)","score":0.6016943454742432},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5974230170249939},{"id":"https://openalex.org/keywords/linear-discriminant-analysis","display_name":"Linear discriminant analysis","score":0.5512632727622986},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.48224931955337524},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46034860610961914},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.45227155089378357},{"id":"https://openalex.org/keywords/fault","display_name":"Fault (geology)","score":0.4428296685218811},{"id":"https://openalex.org/keywords/discriminant","display_name":"Discriminant","score":0.42321568727493286},{"id":"https://openalex.org/keywords/actuator","display_name":"Actuator","score":0.3635326027870178},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3491663932800293},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32560181617736816},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.24239769577980042},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.12195223569869995}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7312124967575073},{"id":"https://openalex.org/C59519942","wikidata":"https://www.wikidata.org/wiki/Q650665","display_name":"Drone","level":2,"score":0.6474317312240601},{"id":"https://openalex.org/C152745839","wikidata":"https://www.wikidata.org/wiki/Q5438153","display_name":"Fault detection and isolation","level":3,"score":0.6388007402420044},{"id":"https://openalex.org/C43214815","wikidata":"https://www.wikidata.org/wiki/Q7310987","display_name":"Reliability (semiconductor)","level":3,"score":0.6016943454742432},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5974230170249939},{"id":"https://openalex.org/C69738355","wikidata":"https://www.wikidata.org/wiki/Q1228929","display_name":"Linear discriminant analysis","level":2,"score":0.5512632727622986},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.48224931955337524},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46034860610961914},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.45227155089378357},{"id":"https://openalex.org/C175551986","wikidata":"https://www.wikidata.org/wiki/Q47089","display_name":"Fault (geology)","level":2,"score":0.4428296685218811},{"id":"https://openalex.org/C78397625","wikidata":"https://www.wikidata.org/wiki/Q192487","display_name":"Discriminant","level":2,"score":0.42321568727493286},{"id":"https://openalex.org/C172707124","wikidata":"https://www.wikidata.org/wiki/Q423488","display_name":"Actuator","level":2,"score":0.3635326027870178},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3491663932800293},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32560181617736816},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.24239769577980042},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.12195223569869995},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","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},{"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/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"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},{"id":"https://openalex.org/C165205528","wikidata":"https://www.wikidata.org/wiki/Q83371","display_name":"Seismology","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.23919/wac.2018.8430428","is_oa":false,"landing_page_url":"https://doi.org/10.23919/wac.2018.8430428","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 World Automation Congress (WAC)","raw_type":"proceedings-article"},{"id":"pmh:oai:figshare.com:article/20595246","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Data-Driven_Fault_Detection_of_Un-Manned_Aerial_Vehicles_Using_Supervised_Learning_over_Cloud_Networks/20595246","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"}],"best_oa_location":{"id":"pmh:oai:figshare.com:article/20595246","is_oa":true,"landing_page_url":"https://figshare.com/articles/conference_contribution/Data-Driven_Fault_Detection_of_Un-Manned_Aerial_Vehicles_Using_Supervised_Learning_over_Cloud_Networks/20595246","pdf_url":null,"source":{"id":"https://openalex.org/S4377196282","display_name":"Figshare","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210132348","host_organization_name":"Figshare (United Kingdom)","host_organization_lineage":["https://openalex.org/I4210132348"],"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":"","raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.5899999737739563},{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.4300000071525574}],"awards":[],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320332201","display_name":"Office of the Secretary of Defense","ror":"https://ror.org/00q4sx826"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W108857541","https://openalex.org/W1502922572","https://openalex.org/W1596324102","https://openalex.org/W1970784519","https://openalex.org/W1984059976","https://openalex.org/W1991519797","https://openalex.org/W2001619934","https://openalex.org/W2011082138","https://openalex.org/W2019400639","https://openalex.org/W2040514520","https://openalex.org/W2046219409","https://openalex.org/W2064975748","https://openalex.org/W2100668822","https://openalex.org/W2101234009","https://openalex.org/W2119821739","https://openalex.org/W2120163187","https://openalex.org/W2129476886","https://openalex.org/W2130973592","https://openalex.org/W2137630789","https://openalex.org/W2165632323","https://openalex.org/W2477930117","https://openalex.org/W2529077967","https://openalex.org/W2544691384","https://openalex.org/W2560844049","https://openalex.org/W2562193524","https://openalex.org/W2565699500","https://openalex.org/W2588361740","https://openalex.org/W2756873776","https://openalex.org/W2762221204","https://openalex.org/W2773425841"],"related_works":["https://openalex.org/W2146076056","https://openalex.org/W2159118812","https://openalex.org/W2025991752","https://openalex.org/W2891847116","https://openalex.org/W2134472250","https://openalex.org/W2350891938","https://openalex.org/W1844323538","https://openalex.org/W4221088574","https://openalex.org/W1975056068","https://openalex.org/W2612560359"],"abstract_inverted_index":{"Modern":[0],"applications":[1],"of":[2,11,73,106,126,147],"Unmanned":[3],"Aerial":[4],"Vehicles":[5],"are":[6],"increasingly":[7],"attracting":[8],"the":[9,42,53,97,107,131,145],"attention":[10],"traditional":[12],"safety":[13],"and":[14,69,99,128],"reliability":[15],"fields.":[16],"There":[17],"exist":[18,30],"many":[19],"standard":[20],"approaches":[21,88],"for":[22,52,86],"determining":[23],"UAV":[24,54,78,108],"fault":[25],"detection.":[26],"However,":[27],"there":[28],"doesn't":[29],"a":[31,117],"method":[32],"that":[33,114],"is":[34],"not":[35,49],"only":[36],"model":[37,133],"independent":[38],"but":[39],"also":[40],"has":[41,83],"ability":[43],"to":[44,76,103,122],"detect":[45],"faults":[46],"which":[47,82],"have":[48],"been":[50,84],"predefined":[51],"system.":[55],"In":[56,110],"this":[57],"research":[58],"we":[59,112],"present":[60],"two":[61],"supervised":[62],"machine":[63],"learning":[64],"algorithms":[65],"implementing":[66],"Logistic":[67],"Regression":[68],"Linear":[70],"Discriminant":[71],"Analysis":[72],"Algorithms,":[74],"respectively,":[75],"predict":[77],"faults.":[79],"The":[80],"data":[81],"used":[85],"these":[87],"comes":[89],"from":[90],"discrete-sampled,":[91],"de-noised":[92],"analog":[93],"signals":[94],"based":[95],"on":[96],"voltage":[98],"current":[100],"inputs":[101],"belonging":[102],"four":[104],"actuators":[105],"drones.":[109],"addition,":[111],"demonstrate":[113],"by":[115],"using":[116],"five-fold":[118],"cross":[119],"validation":[120],"process":[121],"generate":[123],"different":[124],"types":[125],"training":[127],"test":[129],"datasets,":[130],"optimized":[132],"can":[134],"be":[135],"selected.":[136],"We":[137],"verify":[138],"our":[139,148],"results":[140],"through":[141],"an":[142],"analysis":[143],"describing":[144],"accuracies":[146],"proposed":[149],"model.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":6},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":5},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}
