Things that affects sleep quality among athletes and predicting their fitness through Internet of Things

Abstract

The purpose of this study was to look at the link between sleep quality and sports performance of athletes. Here physical fitness among athletes’ also can be predicted using Internet-of-Things (IoT) environment. The IoT has the potential to make people's live style different and easy to work. Now-a-days people are connected with Internet, where the entire human beings and living communities are getting transformed because of different Network protocols. By investigating the causes for sleep quality, its goal was to make coaches and players aware of the necessity of sleeping in order to improve training and competition performance. This study is conducted for twelve female and male athletes of 22 to 27 age group. The associations between sleep quality and other variables were investigated using a one-way ANCOVA model, three main factors are Consuming caffeine or alcohol, sleeping environment and extreme moods such as shocks or being exited before sleep are important reason for poor sleep quality. Here Athletes who are suffering due to inadequate sleep owing to poor characteristics of sleep, which has resulted in negative physical and psychological effects, as well as negative consequences on training and competition performance. And it is proposed that hygiene of sleep be pushed to trainers or coaches and players in order to increase their understanding on how to have healthier sleeping habits. And also in this paper we create procedures for predicting athletes' physical fitness using an IoT context, laying a solid basis for associated athlete index improvement applications. The findings of this study demonstrate that the professional group's wellness prediction accuracy rate using the athletes' model of physical fitness prediction and indexing optimization in an Internet of Things environment is greater than the control groups’, with a difference of p<001.