Integration of OneNet IoT platform improves accuracy in physiological monitoring for athletes, highlighting safety.
This paper used the photoplethysmographic method to collect and extract training information data of a large number of sports personnel and preprocessed the collected data, including removing outlier and carrying out standardization processing. A non-contact network model was used to train the preprocessed data, and the physical fitness of the athletes was reflected from the following three indicators: heart rate, respiratory rate, and body temperature. This article selected 10 volunteers who love sports and compared traditional sports physiological health monitoring technology with sports physiological health monitoring technology based on the OneNet Internet of Things (IoT) cloud platform. The results show that the application of a sports physiological health monitoring system based on the IoT cloud platform can significantly improve the accuracy of physical fitness monitoring, which is of great significance for preventing safety accidents for sports personnel and improving people's body values.
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Wang et al. (2025) studied this question.
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