Smart Golf Equipment with SVM Algorithm for Real-Time Analysis of Swing Metrics and Feedback

This research introduces a novel method for improving golf performance with smart golf equipment incorporating Support Vector Machine (SVM) algorithms. The proposed approach captures swing characteristics in real time by processing data from sensors integrated into golf clubs and wearable devices. The SVM algorithm evaluates data, including swing speed, angle, and trajectory, to provide prompt feedback to players. This feedback enables players to evaluate strengths and flaws in their swing technique, promoting focused improvements. The system is designed for user accessibility, allowing golfers of varying proficiency to get performance metrics and personalized coaching advice. Furthermore, mobile apps enable effortless data visualization and longitudinal progress monitoring. Experimental findings indicate that the proposed smart golf equipment using SVM achieves an accuracy of 94.2%, providing real-time feedback and accurate swing analysis, enhancing players' performance via improved motion classification and consistency. It advances sports technology by providing a practical solution for golfers aiming to improve their abilities using data-driven analysis and feedback systems.