Implementation of an IoT-Based Camera Imaging System for an Autonomous Tennis Ball Collecting Robot

Collecting tennis balls manually is tiring and time-consuming, reducing the effectiveness of training sessions. This study designs and implements an autonomous tennis ball collecting robot equipped with a dual vision camera system, a conveyor-based ball intake mechanism, and Internet of Things (IoT) connectivity. A long-range camera scans the court to detect ball positions for navigation, while a short-range camera verifies precise ball alignment just before collection, improving detection reliability under varying distances and partial occlusions. Detected balls are then transported via a conveyor into a storage basket, addressing failure modes common in simple sweeping mechanisms. The integrated IoT system enables real-time remote monitoring, control, and data transmission on robot status and ball collection progress through mobile or web interfaces. Experimental results indicate long-range and short-range ball recognition accuracies of 87% and 93%, respectively, with the robot able to collect up to 15 balls in 8 minutes. These results demonstrate that combining dual-camera vision, conveyor mechanisms, and IoT-based control significantly enhances the efficiency, practicality, and intelligence of tennis training activities.