Sports Training Assistance system using Dynamic Data Processing System based Improved Cat Optimization Algorithm

In recent years, the field of Artificial Intelligence (AI) and sports applications, computer vision is quickly evolving as a technology. However, the existing models required precise information to be delivered, and it was a crucial task to have several sensor devices. Therefore, a Dynamic Data Processing System (DDPS - ICOA) incorporating an Improved Cat Optimization method is developed in this research for the purpose of recognizing human posture. The model initially integrated the auxiliary teaching system and adjust the standard motion database. The trainers are presented with data that is visually appealing of user movements are related with the conventional actions. With the ability to identify and show video files, the system's overall performances component provides educators with an intelligent teaching platform. According to the results. it illustrated that suggested DDPS - ICOA method achieved better performances in terms accuracy of 99.84%, Efficiency ratio of 98.58% and Error range of 20.27%. which is comparatively higher when compared to existing models such as Hidden Markov Model (HMM), Intelligent Controller System (ICS) and Decision Support Systems (DSS).