Monitoring Simulation of Athlete Dynamic Injury Based on NoSQL Database and Localization Algorithm

Abstract

This article analyzes NoSQL databases, including three NoSQL data models, and analyzes the principles of two NoSQL representative products, Redis and MongoDB. Secondly, dynamic damage monitoring was introduced into the development of a Redis-based question-and-answer system. After proper improvement, certain noise and reverberation can also have relatively good positioning accuracy, which can be widely used in the system. The identification and classification of damage are based on the corresponding standards of the sports federation’s damage monitoring system. Through expert interviews and investigations, the effectiveness and adequacy of physiological and biochemical indicator monitoring are understood to ensure a better evaluation of athletes’ performance indicators. The method of experimental observation was used to monitor the physical function of athletes. During winter training, indicators were monitored, data were recorded, test conditions were recorded, and dynamic injury monitoring mathematical statistics were used for experimental analysis to objectively evaluate the physiological and biochemical indicators of athletes. This article mainly introduces the NoSQL database and sound source localization to dynamic damage monitoring so as to promote its continuous development.