Information Collection, Analysis, and Monitoring System of Children's Physical Training Based on Multisensor

In order to obtain more children's physical training information and improve the accuracy of children's physical training monitoring, a multisensor-based children's physical training information collection, analysis, and monitoring system is proposed. In the process of physical training and sports training, people's physical training information collection is directly related to the level and effectiveness of physical training. With the combination of multisensor concept and sports training information collection, it can collect the key index data of sports mobilization in real time with the help of multiple sensors and information technology. Taking children's physical training as the object, this paper designs a multisensor physical training data information acquisition terminal, collects different training characteristic data with the help of multisensor equipment, and then comprehensively analyzes and monitors the physical information with the help of certain fusion technology, so as to construct a human posture recognition algorithm based on children's physical training information acquisition. Support vector machine and decision tree are used to classify children's different physical exercise states, and a relatively perfect algorithm architecture of human posture recognition is constructed. The results show that for two decision trees, each decision tree is trained with a total of 675 groups of data, and a total of 342 groups of data are verified and pruned. The two decision trees take 7.17 s and 7.32 s to complete the training process, respectively. It can be seen that when the number of training groups is equal, the training time of the two placement methods is close, so it can be considered that the two placement methods have little effect on the training speed of decision tree. The experimental data show that the design of children's physical training monitoring system in this paper has a certain market value.