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Utilizing AI and IoT technologies for identifying risk factors in sports

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成果类型:
期刊论文
作者:
Chen, Zhiling;Dai, Xinghong
通讯作者:
Dai, XH
作者机构:
[Chen, Zhiling] Univ South China, Sch Phys Educ, Hengyang, Hunan, Peoples R China.
[Dai, Xinghong; Dai, XH] Hunan Univ, Sch Phys Educ, Changsha, Hunan, Peoples R China.
通讯机构:
[Dai, XH ] H
Hunan Univ, Sch Phys Educ, Changsha, Hunan, Peoples R China.
语种:
英文
关键词:
AI;Athlete safety;IoT;Performance optimization;Risk factor identification;Scaled conjugate gradient algorithm;Sports analytics
期刊:
Heliyon
ISSN:
2405-8440
年:
2024
卷:
10
期:
11
页码:
e32477
基金类别:
General Research Project of Humanities and Social Sciences of the Ministry of Education [20YJC890002]; Hunan Provincial Education Planning Project [XJK23CTW007]; Scientific Research project of Hunan Provincial Department of Education; Teaching Reform Project of the University of South China [2022ZD-XJG21]
机构署名:
本校为第一机构
院系归属:
体育学院
摘要:
A dynamic cooperation is poised to redefine the limits of athlete safety and performance optimization in the dynamic field of sports science. A new age in sports analysis is promised by the combination of artificial intelligence (AI) and the internet of things (IoT), one in which data-driven insights not only improve our comprehension of athletic performance but also aid to reduce hazards. This academic work explores the complex interactions between AI and IoT in the context of sports. The IoT and AI integration appear to be a strong mix that has the potential to redefine the standards for ath...

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