This paper presents the design, fabrication, and testing of a sensor-driven training device for table tennis that provides real-time feedback and improves training efficacy. To identify ball trajectory and validate shots, the device uses infrared and sound sensors in combination with ESP32 microcontrollers in a master-slave arrangement. A goal-like structure attached to the table collects balls, while sensors assess whether a shot is valid, which is defined as a ball that bounces on the table before entering the goal. Visual feedback is provided via LED strips and an LCD display, guaranteeing that players receive immediate and intuitive performance information. Testing was done under three different conditions: infrared sensor only, infrared plus sound sensor in a quiet area, and infrared plus sound sensor in a noisy environment. The results demonstrated that, while a single infrared sensor reliably identified ball entry, it could not distinguish between valid and invalid shots. Combining infrared and sound sensors yielded complete accuracy in calm situations but dropped to 40% accuracy in noisy environments due to sound interference. The prototype highlights the ability of multi-sensor systems to serve both rookie and advanced players, while emphasizing the necessity for greater noise filtering or alternate sensors for reliable real-world applications.
Sahertian et al. (2026) studied this question.