# Multi platform Computer Vision System to Support Physical Fitness Assessments in Schoolchildren
## 4 Discussion  
This study has demonstrated the feasibility and effectiveness of computer vision technology as a tool for monitoring and promoting physical activity among schoolchildren. This technology's ability to provide accurate, real-time data on physical activity represents a significant advance in promoting healthy lifestyles in young populations. Analyzing and contrasting the results with different investigations [24] shows a favorable percentage of success. In these investigations, a trend of percentage of success more significant than 85% is observed. In the case of the research presented, a percentage of success that is more important than 90% is obtained in three of the four tests taken for field environments and greater than 90% in two tests in a laboratory environment. In comparison, in the mobile version, a success rate greater than 85% is obtained in three tests. It should be noted that these investigations developed their computer vision models and that the nature of the tests significantly affects the accuracy percentage. We also highlight that broad agreement is observed between both methods in the four physical tests. This shows that computer vision technology is comparable to traditional methods in terms of precision and offers additional advantages in accessibility and efficiency. The agreement between methods suggests that implementing these technologies in school settings could revolutionize how physical fitness is assessed and promoted, facilitating more continuous and accurate monitoring among schoolchildren. This study's four physical fitness tests with computer vision evaluation help establish schoolchildren's health and general well-being because they could facilitate the work of physical education teachers by allowing them to evaluate large groups of schoolchildren quickly and accurately. Computer vision can offer many advantages in evaluating schoolchildren's physical activities [25]. It can make a more accurate evaluation, which cannot be achieved with the traditional method. Computer vision can also provide feedback on the assessment, allowing readjustment and improvement of decision-making [26]. These results have also been demonstrated in Latin American countries, such as in the study [27], with applications that can analyze the biomechanics of movement, responding quickly and accurately to execution errors, as well as user satisfaction and interest in using the application in the future. In addition, evidence was provided on computer vision techniques for the automated evaluation of physical activity, such as what was performed by [8]. This supports our statement about the usefulness of this technology for personalized activities for those who require it. The agile development of the software with previously developed and validated models and the nature of the tests allowed the research to obtain results comparable to higher-level research. However, the sit-ups flexibility test accepts the worst percentage of success, less than 85% on average. This last point must be considered when evaluating this research compared to other reviewed research. Finally, this research improves on the previous research by two authors [28]. Implementing computer vision technologies in school contexts provides critical practical considerations. It allows schoolteachers to effectively monitor students' physical activity and develop specific programs based on needs, motivating them to perform physical activities for a healthy life. Theoretically, this study provides a deeper understanding of how technological innovations can be effectively applied to school health. This study not only provides an advanced technological tool for assessing the physical condition of schoolchildren with high precision but also has the potential to transform physical education, promoting a healthier and more active life among young people. Implementing computer vision technologies in school contexts is necessary. This would allow teachers to monitor students' physical fitness during physical education classes effectively.