Real Time State Monitoring Simulation of Image Recognition Based on Infrared Light Sensors and Wireless Networks in High-Intensity Training

Abstract

The traditional real-time condition monitoring methods of high-intensity training often rely on complex hardware equipment or manual observation, which has the problem of insufficient real-time and accuracy. The system uses infrared light sensor to acquire athletes' physiological data, and transmits it to the central processing unit combined with wireless network. Image recognition technology is used to analyze sensor data and images of training scenes to monitor the status of athletes in real time. A prototype system is designed and tested, and its performance is evaluated by experiments. The experimental results show that the designed system is efficient and accurate in real-time condition monitoring of high-intensity training. The application of wireless network significantly improves the speed and stability of data transmission and ensures the real-time performance of the system. Image recognition algorithm can effectively identify and analyze the key actions and state changes in the training process. The image recognition system based on infrared light sensor and wireless network developed in this research can significantly improve the real-time condition monitoring ability of high-intensity training. The system has advantages in real-time, accuracy and data transmission stability, and has a wide application prospect.