LAUSR

With the development of modern Internet technology, the health assessment model based on computer technology has gradually become a research hotspot. In the process of studying the health level of residents, exercise status and diet nutrition are important factors affecting their health. Therefore, based on the idea of the genetic algorithm, this paper establishes a resident sports nutrition data monitoring system. In this system, the data feature selection method of the genetic algorithm, which simulates the process of biological evolution, is used in the key technology of real-time motion data processing of residents, and it is improved to interfere with the data cross process of the genetic algorithm, to seek the local optimal solution. Two different types of data sets and different data classifiers are selected to verify the system's performance. It is proved that compared with the traditional filter class feature selection method, this method can achieve more effective data feature recognition. In addition, some samples are selected to test the residents' sports nutrition data monitoring system, mainly through the analysis and quantification of the exercise process, eating habits, physique, and other data of the athletes; to evaluate the impact of their sports and eating habits on physical health; and to obtain the best sports guidance scheme, to guide the adjustment and improvement of their later sports and eating plans. Through the analysis of the existing residents' health status, the monitoring and management strategies of residents' health status are summarized, which provides a certain reference for the improvement of residents' physical health under the background of artificial intelligence.