Dynamic data processing system for sports training system using internet of things.
Background: The Internet of Things (IoT) has recently become a prevalent technological culture in the sports training system. Although numerous technologies have grown in the sports training system domain, IoT plays a substantial role in its optimized health data processing framework for athletes du...
| Publicado en: | Technology & Health Care Vol. 29; no. 6; pp. 1305 - 1319 |
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| Autores principales: | , , |
| Formato: | Journal Article |
| Publicado: |
Sage Publications Inc.
2021
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=153965052&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 153965052 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09287329 3QT jtl: Technology & Health Care issn: 09287329 maglogo: N pubinfo: dt: 2021 vid: 29 iid: 6 pid: 344 pub: Sage Publications Inc. place: Thousand Oaks, California artinfo: ui: 153965052 150630582 153965052 NLM34092678 10.3233/THC-213008 NLM34092678 153965052 ppf: 1305 ppct: 14 formats: tig: atl: Dynamic data processing system for sports training system using internet of things. aug: au: Fang, Zhi Mahapatra, Rajendra Prasad Selvaraj, P. affil: Department of Physical Education, Southeast University, Nanjing, Jiangsu, China sug: ab: Background: The Internet of Things (IoT) has recently become a prevalent technological culture in the sports training system. Although numerous technologies have grown in the sports training system domain, IoT plays a substantial role in its optimized health data processing framework for athletes during workouts.Objective: In this paper, a Dynamic data processing system (DDPS) has been suggested with IoT assistance to explore the conventional design architecture for sports training tracking.Method: To track and estimate sportspersons physical activity in day-to-day living, a new paradigm has been combined with wearable IoT devices for efficient data processing during physical workouts. Uninterrupted observation and review of different sportspersons condition and operations by DDPS helps to assess the sensed data to analyze the sportspersons health condition. Additionally, Deep Neural Network (DNN) has been presented to extract important sports activity features.Results: The numerical results show that the suggested DDPS method enhances the accuracy of 94.3%, an efficiency ratio of 98.2, less delay of 24.6%, error range 28.8%, and energy utilization of 31.2% compared to other existing methods. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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