Introduction

The COVID-19 pandemic has fundamentally changed the way we interact with public and shared surfaces. With heightened awareness of hygiene and the need to reduce the spread of pathogens, there is an increased demand for touchless interaction technologies, Gesture recognition systems enable users to interact with devices and interfaces without physical contact, enhancing safety and user experience in various environments such as hospitals, retail stores, airports, and public kiosks. This case study outlines the development and deployment of a gesture recognition system for touchless interfaces, emphasizing the critical need for such solutions in the post-COVID era. The project leverages advanced computer vision techniques and machine learning models to interpret human gestures in real-time, providing seamless and hygienic user interaction.