Detection of sports energy consumption based on IoTs and cloud computing

In the fields of sports training, nutrition, labour physiology, etc., the research of exercise volume and energy consumption has received great attention. However, many current methods for detecting exercise energy consumption are not low-precision, and their operation and realization are relatively difficult. Through cloud services and Internet of Things (IoTs), it can directly provide sports training athletes with monitoring of sports energy consumption. Establishing an effective data model can realize rapid query and accurate response of largescale complex sports energy consumption data. Therefore, according to the current survey of exercise energy consumption detection, this research studied the use of new technologies, that is, IoTs and cloud computing to detect sports energy consumption, proposed the IoTs architecture model and cloud computing model for sports energy consumption detection, and the method of data collection in the process of exercise energy consumption detection was given. Moreover, this study also studied the accuracy of the system's exercise energy consumption detection results. The research results showed that the sports energy consumption detection system in view of IoTs and cloud computing designed in this research had an error of less than 2%, which has high accuracy.