Risk Control Analysis of Digital Financial Engineering Based on 6G Physical Information System

被引:0
|
作者
Zhou, Jia [1 ]
Shi, Yabin [2 ]
机构
[1] Guangzhou Huali Coll, Guangzhou 510000, Guangdong, Peoples R China
[2] Guangzhou Coll Commerce, Guangzhou 510000, Guangdong, Peoples R China
关键词
Sensors; Sports data; Deep leaning; Cloud computing; Prediction;
D O I
10.1007/s11277-024-11240-x
中图分类号
TN [电子技术、通信技术];
学科分类号
0809 ;
摘要
Small sensors may now be used to analyze and evaluate sports and physical activities via communication with smart tools and ubiquitous computing devices. Digital Financial support is the extensive motive of this research where smart monitoring reduces the cost of players paying to extra labors. Also, accurate engineering solutions are achieved for sports monitoring using 6G network. Through the use of the underlying framework and these sensors, we are able to gather data from a variety of physical activities from any place at any time. That being said, a lot of data is produced by these gadgets. In order to evaluate a sportsperson's physical activity, it is thus essential to have as much data as possible. Sports physical activity analysis is now done at a level that might be changed by wearable devices with small sensors, edge and cloud computing, and artificial intelligence with deep learning technology. In order to improve the athlete's profile by forecasting their physique and suggesting specific training, this research attempts to integrate the three pillars of physical activity based on these attributes. We can create a dataset from the genuine ecological settings thanks to a unique framework that is offered for this aim. We have read a great deal of material on sports and physical activity to guarantee the effectiveness of our job. The limits of the sensors, data gathering, and processing methods from the literature were highlighted. We conjecture that with the aid of edge and cloud computing devices that let the data to stream without limitation, the collection of data, continuous measurement, and analysis of various processes will result in a more dependable model. The swimming athletes in this article are trained using personalized programmes and profile-type techniques. Based on the trial findings, the proposed integrated system offers coaches and players important data that facilitates targeted training, enhanced athlete healthcare, and performance optimization.
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页数:24
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