Green city air detection and healthy exercise based on the Internet of Things and cloud platform embedded system

Abstract

With the continuous development of science and technology, the improvement of industrialization level and the continuous improvement of network platform functions, people have higher and higher expectations for cloud platform embedded system, and also face many problems that need to be solved, such as difficult matching, difficult replacement and consumption of a lot of money in the process of replacing parts. Combined with a large number of research reports and data, we can conclude that China’s environmental problems have been very serious, solving environmental pollution is imminent. This paper uses a detailed detection method, that is, by collecting the mass concentration of PM2.5 in an area to analyze the environmental pollution problems in the area, and puts forward solutions, and discusses the characteristics and changes of air pollution in areas that have been seriously affected by air pollution and in special periods, and then analyzes them. Aerobic exercise is a gentle and moderate way of physical fitness. A large number of clinical studies have shown that long-term participation in aerobic exercise can not only consume body fat, regulate body weight, enhance cardiopulmonary function, but also regulate and improve mental health. It is the main way for modern people to carry out physical fitness exercise. With the continuous development of artificial intelligence technology, aerobic exercise is gradually developing in the direction of intelligence. This report combines somatosensory technology and tracking technology, targeted to solve the problem to provide intelligent demand, to achieve the accuracy of the motion system. • China’s environmental problems have been very serious, solving environmental pollution is imminent. • Collecting the mass concentration of PM2.5 in an area to analyze the environmental pollution problems. • Long-term participation in aerobic exercise can not only consume body fat. • This report combines somatosensory technology and tracking technology.