Near Infrared Spectral Imaging Based on Cloud Data and Wireless Network Sensing in Big Data Sports and Fitness Detection

Abstract

Because of its non-invasive and rapid response, NIR imaging has shown great potential in the field of biological information acquisition and analysis. This study aims to explore the application of near infrared spectral imaging technology based on cloud data and wireless network sensing in big data sports fitness detection, aiming to improve the collection efficiency and analysis accuracy of sports data, so as to provide scientific basis for personal health management. In this study, near infrared spectral imaging instrument was used to collect real-time physiological data during exercise through wireless network sensing equipment. The collected data is transmitted to the cloud platform through the mobile network, and big data analysis technology is used to conduct in-depth analysis of physiological characteristics and athletic performance. Through the design of monitoring system based on the Internet of Things, the efficient collaboration between multiple devices is realized. The experimental results show that the constructed system can monitor users' physiological parameters in real time, such as blood oxygen saturation, muscle oxygenation, etc., and organize and analyze the data through the cloud platform. Compared with the traditional monitoring method, the system greatly improves the data transmission rate and processing efficiency, and effectively improves the accuracy and timeliness of physical fitness detection.