Design of Edge Cloud Computing Recognition System for Intelligent Needs from the Perspective of Sports Psychology

This paper intends to meet society’s demand for intelligent recognition system design and improve the performance of the behavioral action recognition system. Based on the previous research, the behavior recognition system is optimized. The edge Cloud Computing (CLO) technology is introduced. Also, the idea of sports psychology is integrated. The overall scheme of the behavior recognition system is designed. The accuracy, precision, and recall of the recognition system in different behaviors are analyzed by training the data set. In addition, the cloud-based behavior recognition design model is compared with other algorithms to analyze the algorithm advantages. Finally, the training and validation tests are performed on the training set of expression images using the behavior recognition system mode. It is found that the behavior recognition system model can show high accuracy in different environments, all above 80%. The results show that the edge CLO recognition system that meets intelligence needs has good accuracy, precision, and recall in both action recognition and image expression recognition. The recognition effect is the best. This paper aims to provide some ideas for the research on intelligent behavior recognition and put forward some references for the field expansion of edge CLO technology applications. Besides, the intelligence level of the behavior recognition system is improved through software design.