Virtual Booth

This project focuses on the development of a gesture-based video control system using the ESP32 microcontroller, targeting users with physical disabilities who face difficulty using conventional input devices like keyboards and mice. The study falls under the field of human-computer interaction (HCI) specifically touchless interfaces and assistive technology. The main problem addressed is the lack of accessible control systems for individuals with limited mobility. The proposed solution enables users to control video playback functions such as play, pause, volume adjustment, and navigation through simple hand gestures. The system utilizes an MPU6050 Inertial Measurement Unit (IMU) sensor to capture real-time motion data which is processed by the ESP32. The recognized gesture is then transmitted via MQTT over Wi-Fi to a Python script running on a laptop. The script interprets the gesture and simulates keyboard input using the pyautogui library to control media playback. The development process includes sensor calibration, threshold tuning for gesture recognition and system testing under different conditions. The prototype is built using Arduino IDE for firmware development and Python for client-side processing. Results show that the system can reliably detect and respond to gestures such as tilt up/down and swipe left/right with minimal latency. The integration of MQTT and gesture recognition techniques demonstrates a practical and low-cost approach to hands-free control. This project not only highlights the potential of ESP32-based IoT applications in accessibility but also contributes to the growing field of inclusive design in digital interaction.