{"id":"https://openalex.org/W4405194878","doi":"https://doi.org/10.1002/itl2.622","title":"Multisensor\u2010Driven Lightweight Networks for Intelligent Sports Training System: Design and Research","display_name":"Multisensor\u2010Driven Lightweight Networks for Intelligent Sports Training System: Design and Research","publication_year":2024,"publication_date":"2024-12-09","ids":{"openalex":"https://openalex.org/W4405194878","doi":"https://doi.org/10.1002/itl2.622"},"language":"en","primary_location":{"id":"doi:10.1002/itl2.622","is_oa":true,"landing_page_url":"https://doi.org/10.1002/itl2.622","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/itl2.622","source":{"id":"https://openalex.org/S4210238311","display_name":"Internet Technology Letters","issn_l":"2476-1508","issn":["2476-1508"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet Technology Letters","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"bronze","oa_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/itl2.622","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5115065231","display_name":"Jibao Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Jibao Xing","raw_affiliation_strings":["Jilin Animation Institute  Jilin China","Jilin Animation Institute, Jilin, China"],"affiliations":[{"raw_affiliation_string":"Jilin Animation Institute  Jilin China","institution_ids":[]},{"raw_affiliation_string":"Jilin Animation Institute, Jilin, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5115065231"],"corresponding_institution_ids":[],"apc_list":{"value":2630,"currency":"USD","value_usd":2630},"apc_paid":null,"fwci":0.2475,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56167277,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"8","issue":"5","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9973000288009644,"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9973000288009644,"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/T10444","display_name":"Context-Aware Activity Recognition Systems","score":0.9955000281333923,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9868000149726868,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7157946825027466},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.640245795249939},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5452471375465393},{"id":"https://openalex.org/keywords/training","display_name":"Training (meteorology)","score":0.5063849687576294},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.49267178773880005},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.46730709075927734},{"id":"https://openalex.org/keywords/edge-computing","display_name":"Edge computing","score":0.46031591296195984},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.4500933587551117},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.38769668340682983},{"id":"https://openalex.org/keywords/real-time-computing","display_name":"Real-time computing","score":0.3805757164955139},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3747010827064514}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7157946825027466},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.640245795249939},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5452471375465393},{"id":"https://openalex.org/C2777211547","wikidata":"https://www.wikidata.org/wiki/Q17141490","display_name":"Training (meteorology)","level":2,"score":0.5063849687576294},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.49267178773880005},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.46730709075927734},{"id":"https://openalex.org/C2778456923","wikidata":"https://www.wikidata.org/wiki/Q5337692","display_name":"Edge computing","level":3,"score":0.46031591296195984},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.4500933587551117},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.38769668340682983},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.3805757164955139},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3747010827064514},{"id":"https://openalex.org/C153294291","wikidata":"https://www.wikidata.org/wiki/Q25261","display_name":"Meteorology","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1002/itl2.622","is_oa":true,"landing_page_url":"https://doi.org/10.1002/itl2.622","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/itl2.622","source":{"id":"https://openalex.org/S4210238311","display_name":"Internet Technology Letters","issn_l":"2476-1508","issn":["2476-1508"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet Technology Letters","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1002/itl2.622","is_oa":true,"landing_page_url":"https://doi.org/10.1002/itl2.622","pdf_url":"https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/itl2.622","source":{"id":"https://openalex.org/S4210238311","display_name":"Internet Technology Letters","issn_l":"2476-1508","issn":["2476-1508"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310320595","host_organization_name":"Wiley","host_organization_lineage":["https://openalex.org/P4310320595"],"host_organization_lineage_names":["Wiley"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Internet Technology Letters","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/7","display_name":"Affordable and clean energy","score":0.8999999761581421}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4405194878.pdf"},"referenced_works_count":13,"referenced_works":["https://openalex.org/W2080873731","https://openalex.org/W2559085405","https://openalex.org/W2963163009","https://openalex.org/W3006898026","https://openalex.org/W3088302081","https://openalex.org/W3102969100","https://openalex.org/W3176249739","https://openalex.org/W3193938635","https://openalex.org/W4360584650","https://openalex.org/W4375951626","https://openalex.org/W4385767864","https://openalex.org/W4386230936","https://openalex.org/W4392514192"],"related_works":["https://openalex.org/W230091440","https://openalex.org/W4306904969","https://openalex.org/W2233261550","https://openalex.org/W2810751659","https://openalex.org/W258997015","https://openalex.org/W4324372666","https://openalex.org/W4225706866","https://openalex.org/W2914646191","https://openalex.org/W3023564924","https://openalex.org/W2942586735"],"abstract_inverted_index":{"ABSTRACT":[0],"Edge":[1],"computing":[2],"and":[3,18,28,49,102,117,138],"multisensor":[4,37],"integration":[5],"have":[6],"revolutionized":[7],"sports":[8,31,144],"training":[9,32,63,145],"technologies,":[10],"yet":[11],"many":[12],"existing":[13],"systems":[14],"remain":[15],"computationally":[16],"intensive":[17],"complex":[19,78],"for":[20],"everyday":[21],"use.":[22],"This":[23,128],"study":[24],"introduces":[25],"an":[26],"efficient":[27],"user\u2010friendly":[29],"intelligent":[30],"system":[33,45,72,109],"that":[34,70,131],"leverages":[35],"edge\u2010based":[36],"data":[38],"processing":[39],"with":[40,90,121],"lightweight":[41],"neural":[42],"networks.":[43],"The":[44,108],"utilizes":[46],"low\u2010latency":[47],"activity":[48],"real\u2010time":[50,112],"pose":[51],"estimation":[52],"data,":[53],"powered":[54],"by":[55],"a":[56],"modified":[57],"MobileNetV2":[58],"model,":[59],"to":[60,105,111],"generate":[61],"personalized":[62,143],"plans":[64],"through":[65],"reinforcement":[66],"learning.":[67],"Tests":[68],"show":[69],"the":[71,74],"matches":[73],"accuracy":[75,92],"of":[76],"more":[77,146],"models":[79],"while":[80],"significantly":[81],"reducing":[82],"computational":[83],"needs.":[84],"Compression":[85],"techniques":[86],"further":[87],"enhance":[88],"efficiency":[89],"minimal":[91],"loss.":[93],"User":[94],"studies":[95],"revealed":[96],"notable":[97],"improvements":[98],"in":[99],"fitness":[100],"levels":[101],"adherence":[103],"compared":[104],"traditional":[106],"methods.":[107],"adapts":[110],"user":[113],"performance,":[114],"offering":[115],"feedback":[116],"dynamically":[118],"adjusting":[119],"plans,":[120],"low":[122],"energy":[123],"consumption":[124],"across":[125],"mobile":[126],"devices.":[127],"research":[129],"shows":[130],"our":[132],"developed":[133],"system,":[134],"which":[135],"integrates":[136],"multisensors":[137],"artificial":[139],"intelligence,":[140],"can":[141],"make":[142],"accessible.":[147]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}
