{"id":"https://openalex.org/W3182792505","doi":"https://doi.org/10.1109/access.2021.3094243","title":"Internet of Things and Deep Learning Enabled Elderly Fall Detection Model for Smart Homecare","display_name":"Internet of Things and Deep Learning Enabled Elderly Fall Detection Model for Smart Homecare","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3182792505","doi":"https://doi.org/10.1109/access.2021.3094243","mag":"3182792505"},"language":"en","primary_location":{"id":"doi:10.1109/access.2021.3094243","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3094243","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09471869.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/ielx7/6287639/9312710/09471869.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5053107720","display_name":"Thavavel Vaiyapuri","orcid":"https://orcid.org/0000-0001-5494-5278"},"institutions":[{"id":"https://openalex.org/I142608572","display_name":"Prince Sattam Bin Abdulaziz University","ror":"https://ror.org/04jt46d36","country_code":"SA","type":"education","lineage":["https://openalex.org/I142608572"]}],"countries":["SA"],"is_corresponding":true,"raw_author_name":"Thavavel Vaiyapuri","raw_affiliation_strings":["College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia"],"raw_orcid":"https://orcid.org/0000-0001-5494-5278","affiliations":[{"raw_affiliation_string":"College of Computer Engineering and Sciences, Prince Sattam Bin Abdulaziz University, Al-Kharj, Saudi Arabia","institution_ids":["https://openalex.org/I142608572"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041429943","display_name":"E. Laxmi Lydia","orcid":"https://orcid.org/0000-0002-6788-7051"},"institutions":[{"id":"https://openalex.org/I188963388","display_name":"International Institute of Information Technology","ror":"https://ror.org/02dernx73","country_code":"IN","type":"education","lineage":["https://openalex.org/I188963388"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"E. Laxmi Lydia","raw_affiliation_strings":["Department of Computer Science and Engineering, Vignan&#x2019;s Institute of Information Technology (Autonomous), Visakhapatnam, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Engineering, Vignan&#x2019;s Institute of Information Technology (Autonomous), Visakhapatnam, India","institution_ids":["https://openalex.org/I188963388"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5063103313","display_name":"Mohamed Yacin Sikkandar","orcid":"https://orcid.org/0000-0002-7971-1504"},"institutions":[{"id":"https://openalex.org/I195631090","display_name":"Majmaah University","ror":"https://ror.org/01mcrnj60","country_code":"SA","type":"education","lineage":["https://openalex.org/I195631090"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Mohamed Yacin Sikkandar","raw_affiliation_strings":["Department of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majma&#x2019;ah, Saudi Arabia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Medical Equipment Technology, College of Applied Medical Sciences, Majmaah University, Al Majma&#x2019;ah, Saudi Arabia","institution_ids":["https://openalex.org/I195631090"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046440892","display_name":"Vicente Garc\u00eda\u2010D\u00edaz","orcid":"https://orcid.org/0000-0003-2037-8548"},"institutions":[{"id":"https://openalex.org/I165339363","display_name":"Universidad de Oviedo","ror":"https://ror.org/006gksa02","country_code":"ES","type":"education","lineage":["https://openalex.org/I165339363"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Vicente Garc\u00eda D\u00edaz","raw_affiliation_strings":["Department of Computer Science, School of Computer Science Engineering, University of Oviedo, Oviedo, Spain"],"raw_orcid":"https://orcid.org/0000-0003-2037-8548","affiliations":[{"raw_affiliation_string":"Department of Computer Science, School of Computer Science Engineering, University of Oviedo, Oviedo, Spain","institution_ids":["https://openalex.org/I165339363"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039361880","display_name":"Irina V. Pustokhina","orcid":null},"institutions":[{"id":"https://openalex.org/I103031861","display_name":"Plekhanov Russian University of Economics","ror":"https://ror.org/04pbtsc74","country_code":"RU","type":"education","lineage":["https://openalex.org/I103031861"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Irina V. Pustokhina","raw_affiliation_strings":["Department of Entrepreneurship and Logistics, Plekhanov Russian University of Economics, Moscow, Russia"],"raw_orcid":"https://orcid.org/0000-0001-5480-8871","affiliations":[{"raw_affiliation_string":"Department of Entrepreneurship and Logistics, Plekhanov Russian University of Economics, Moscow, Russia","institution_ids":["https://openalex.org/I103031861"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5090218287","display_name":"Denis A. Pustokhin","orcid":"https://orcid.org/0000-0002-8138-8494"},"institutions":[{"id":"https://openalex.org/I111567634","display_name":"State University of Management","ror":"https://ror.org/00nxz6d14","country_code":"RU","type":"education","lineage":["https://openalex.org/I111567634"]}],"countries":["RU"],"is_corresponding":false,"raw_author_name":"Denis A. Pustokhin","raw_affiliation_strings":["Department of Logistics, State University of Management, Moscow, Russia"],"raw_orcid":"https://orcid.org/0000-0002-8138-8494","affiliations":[{"raw_affiliation_string":"Department of Logistics, State University of Management, Moscow, Russia","institution_ids":["https://openalex.org/I111567634"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5053107720"],"corresponding_institution_ids":["https://openalex.org/I142608572"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":6.4009,"has_fulltext":true,"cited_by_count":90,"citation_normalized_percentile":{"value":0.9756936,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":"9","issue":null,"first_page":"113879","last_page":"113888"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10114","display_name":"Balance, Gait, and Falls Prevention","score":0.9829000234603882,"subfield":{"id":"https://openalex.org/subfields/3612","display_name":"Physical Therapy, Sports Therapy and Rehabilitation"},"field":{"id":"https://openalex.org/fields/36","display_name":"Health Professions"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.965399980545044,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical 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":0.7730597257614136},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6793107986450195},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.621733546257019},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.6035188436508179},{"id":"https://openalex.org/keywords/autoencoder","display_name":"Autoencoder","score":0.5897149443626404},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5312222242355347},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4999713897705078},{"id":"https://openalex.org/keywords/wearable-computer","display_name":"Wearable computer","score":0.4762551784515381},{"id":"https://openalex.org/keywords/home-automation","display_name":"Home automation","score":0.4495035409927368},{"id":"https://openalex.org/keywords/wearable-technology","display_name":"Wearable technology","score":0.4328889846801758},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4286848306655884},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.42723849415779114},{"id":"https://openalex.org/keywords/internet-of-things","display_name":"Internet of Things","score":0.4192194938659668},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.32673847675323486},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.2977364957332611},{"id":"https://openalex.org/keywords/embedded-system","display_name":"Embedded system","score":0.19376105070114136},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.10620328783988953}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7730597257614136},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6793107986450195},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.621733546257019},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.6035188436508179},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.5897149443626404},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5312222242355347},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4999713897705078},{"id":"https://openalex.org/C150594956","wikidata":"https://www.wikidata.org/wiki/Q1334829","display_name":"Wearable computer","level":2,"score":0.4762551784515381},{"id":"https://openalex.org/C507571656","wikidata":"https://www.wikidata.org/wiki/Q848436","display_name":"Home automation","level":2,"score":0.4495035409927368},{"id":"https://openalex.org/C54290928","wikidata":"https://www.wikidata.org/wiki/Q4845080","display_name":"Wearable technology","level":3,"score":0.4328889846801758},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4286848306655884},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.42723849415779114},{"id":"https://openalex.org/C81860439","wikidata":"https://www.wikidata.org/wiki/Q251212","display_name":"Internet of Things","level":2,"score":0.4192194938659668},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.32673847675323486},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.2977364957332611},{"id":"https://openalex.org/C149635348","wikidata":"https://www.wikidata.org/wiki/Q193040","display_name":"Embedded system","level":1,"score":0.19376105070114136},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.10620328783988953}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2021.3094243","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3094243","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09471869.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:d7eb2ab3edae4031ae5bfbc9fbc3a263","is_oa":true,"landing_page_url":"https://doaj.org/article/d7eb2ab3edae4031ae5bfbc9fbc3a263","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 113879-113888 (2021)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2021.3094243","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2021.3094243","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/9312710/09471869.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":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3182792505.pdf","grobid_xml":"https://content.openalex.org/works/W3182792505.grobid-xml"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W1982500163","https://openalex.org/W2021002687","https://openalex.org/W2121062110","https://openalex.org/W2128814754","https://openalex.org/W2140943894","https://openalex.org/W2610979719","https://openalex.org/W2733439154","https://openalex.org/W2764242840","https://openalex.org/W2765510333","https://openalex.org/W2767165810","https://openalex.org/W2800342439","https://openalex.org/W2901658644","https://openalex.org/W2912258320","https://openalex.org/W2913797540","https://openalex.org/W2955543943","https://openalex.org/W2956143643","https://openalex.org/W2963166639","https://openalex.org/W2985684113","https://openalex.org/W2998692113","https://openalex.org/W3006415409","https://openalex.org/W3026359008","https://openalex.org/W3033176519","https://openalex.org/W3037456657","https://openalex.org/W3045678992","https://openalex.org/W3108544423","https://openalex.org/W3135062470","https://openalex.org/W3157039972"],"related_works":["https://openalex.org/W3090300519","https://openalex.org/W3161928361","https://openalex.org/W2514492205","https://openalex.org/W4250401876","https://openalex.org/W2943851981","https://openalex.org/W2566526749","https://openalex.org/W3047461507","https://openalex.org/W3126390843","https://openalex.org/W4245880644","https://openalex.org/W4312415459"],"abstract_inverted_index":{"Recently,":[0,96],"the":[1,86,90,97,144,159,164,168,173,208,212,218,241,255,261,270,289,293,297,301,309],"techniques":[2],"of":[3,5,24,31,69,75,89,99,143,161,211,243,251,269,292,304],"Internet":[4],"Things":[6],"(IoT)":[7],"and":[8,17,27,33,151,184,245,263,280,306,313],"mobile":[9],"communications":[10],"have":[11],"been":[12],"developed":[13],"to":[14,44,51,84,110,148,157,198,260],"gather":[15],"human":[16],"environment":[18],"information":[19],"data":[20],"for":[21,67,115,138,203,240],"a":[22,64,194],"variety":[23],"intelligent":[25,152],"services":[26],"applications.":[28],"Remote":[29],"monitoring":[30],"elderly":[32,58,76,127],"disabled":[34],"people":[35,77],"living":[36],"in":[37,79,163,178,249],"smart":[38,80,116,139,165],"homes":[39,81],"is":[40,61,82,147,176,191,238],"highly":[41],"challenging":[42],"due":[43,50],"probable":[45],"accidents":[46],"which":[47],"might":[48],"occur":[49],"daily":[52],"activities":[53],"such":[54],"as":[55,63,193],"falls.":[56],"For":[57],"people,":[59],"fall":[60,112,128,204,244,252,277,283,312,315],"considered":[62],"major":[65],"reason":[66],"death":[68],"post-traumatic":[70],"complication.":[71],"So,":[72],"early":[73],"identification":[74],"falls":[78,162],"needed":[83],"increase":[85],"survival":[87],"rate":[88],"person":[91],"or":[92],"offer":[93],"required":[94],"support.":[95],"advent":[98],"artificial":[100],"intelligence":[101],"(AI),":[102],"IoT,":[103],"wearables,":[104],"smartphones,":[105],"etc.":[106],"makes":[107],"it":[108],"feasible":[109],"design":[111],"detection":[113,129,278,316],"systems":[114],"homecare.":[117,140],"In":[118,206],"this":[119,121],"view,":[120],"paper":[122],"presents":[123],"an":[124,258],"IoT":[125,174],"enabled":[126],"model":[130,146,190,214,272,295],"using":[131,217],"optimal":[132],"deep":[133,153],"convolutional":[134],"neural":[135],"network":[136],"(IMEFD-ODCNN)":[137],"The":[141,266,285],"goal":[142],"IMEFD-ODCNN":[145,271,294],"enable":[149],"smartphones":[150],"learning":[154],"(DL)":[155],"algorithms":[156],"detect":[158],"occurrence":[160],"home.":[166],"Primarily,":[167],"input":[169],"video":[170],"captured":[171],"by":[172],"devices":[175],"pre-processed":[177],"different":[179],"ways":[180],"like":[181],"resizing,":[182],"augmentation,":[183],"min-max":[185],"based":[186,236],"normalization.":[187],"Besides,":[188],"SqueezeNet":[189,213],"employed":[192,239],"feature":[195,201],"extraction":[196],"technique":[197],"derive":[199],"appropriate":[200],"vectors":[202],"detection.":[205],"addition,":[207],"hyperparameter":[209],"tuning":[210],"takes":[215,273],"place":[216,274],"salp":[219],"swarm":[220],"optimization":[221,227],"(SSO)":[222],"algorithm.":[223],"Finally,":[224,248],"sparrow":[225],"search":[226],"algorithm":[228],"(SSOA)":[229],"with":[230,300],"variational":[231],"autoencoder":[232],"(VAE),":[233],"called":[234],"SSOA-VAE":[235],"classifier":[237],"classification":[242],"non-fall":[246],"events.":[247],"case":[250],"event":[253],"detected,":[254],"smartphone":[256],"sends":[257],"alert":[259],"caretakers":[262],"hospital":[264],"management.":[265],"performance":[267,291],"validation":[268],"on":[275,308],"UR":[276,314],"dataset":[279],"multiple":[281,310],"cameras":[282,311],"dataset.":[284,317],"experimental":[286],"outcomes":[287],"highlighted":[288],"promising":[290],"over":[296],"recent":[298],"methods":[299],"maximum":[302],"accuracy":[303],"99.76%":[305],"99.57%":[307]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":20},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":21},{"year":2022,"cited_by_count":13},{"year":2021,"cited_by_count":2}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
