Big Data Sports Fitness Detection based on Cloud Storage-Oriented Data System

Abstract

Abstract Nowadays, there are more and more motor vehicles in cities, and with the deteriorating world environment and depletion of resources, low-carbon travel has become a new trend, and green fitness has become a link of sustainable and healthy development. Information data has increased rapidly, and the application of cloud storage has become more widespread. However, current cloud storage still has various problems, especially user information security issues. Therefore, in order to protect users' confidential information and data, information can be stored in the cloud in the form of cipher text. So if you want users to be able to retrieve the information they want in a large amount of data, you need to design a full-text ciphertext retrieval program. Another important function of cloud storage services is that each user can safely share data, which requires the existence of a safe and effective access control scheme. The current national fitness boom symbolizes that the people's pursuit of health is already a fashion, and outdoor hiking is a healthy, low-carbon and environmentally friendly fitness method. Walking in the city can not only promote the improvement of urban public facilities and the further optimization of the urban environment, but also promote the development of urban characteristic culture. Because hiking in the city has the dual effects of national fitness and environmental protection, it is very important for the rationalization and humanization of urban hiking. This paper selects and recognizes the open and shared city data, takes the path data of the hikers' movement as the research basis and research object, and organizes and analyzes the relevant data on the Google Earth data sharing platform.