Simulation of Optical Sensors in IoT Motion Training Systems in Wireless Sensor Networks and Cloud Technology Environments

Abstract

With the rapid development of Internet of Things (IoT) technology, optical sensors, as an important data acquisition tool, can accurately monitor the physiological state and athletic performance of athletes, and provide data support for personalized training. This study aims to explore the simulation effect of optical sensors in the Internet of Things sports training system combined with wireless sensor network and cloud technology, so as to improve the science and effectiveness of sports training. This paper uses simulation model to build a wireless sensor network-based motion training system for the Internet of Things, and focuses on analyzing the performance of optical sensors in the process of data acquisition. Through the three stages of sensor deployment, data transmission and cloud processing, the accuracy and reliability of the sensors in real-time monitoring of athletes’ athletic ability and physical status are evaluated. The simulation results show that the optical sensor can effectively collect motion data in the system and quickly transmit it to the cloud for analysis through wireless network. The response time of the system is significantly reduced, the stability and accuracy of data transmission are improved, and the real-time feedback of athletes during training is realized. The combination of wireless sensor network and cloud technology provides a new solution for sports training, and the effective application of optical sensor can significantly improve the training effect.