AI Vision Board-Vision Board Human Computer Interaction for Smart Education using Open CV and Media Pipe Framework

The rapid advancement of Artificial Intelligence has enabled the development of more natural and intuitive Human-Computer Interaction (HCI) systems. This project, AI Vision Board, proposes a smart education interface that utilizes computer vision techniques to create a touchless, gesture-based interaction system. The objective is to enhance user accessibility in modern digital learning environments. The proposed system employs OpenCV for real-time image processing and the MediaPipe framework for accurate hand landmark detection and tracking. By analyzing hand gestures captured through a webcam, the system enables users to interact with a virtual vision board without relying on traditional input devices such as a mouse or keyboard. The system processes visual input in real time, ensuring low latency and smooth interaction. Gesture recognition algorithms are designed to be robust under varying lighting conditions and user environments. This approach not only improves usability but also supports hygienic, contactless interaction, which is increasingly important in shared or public learning spaces. Furthermore, the proposed solution can be integrated into smart classrooms, e-learning platforms, and assistive technologies, making learning more interactive and inclusive. The AI Vision Board demonstrates the potential of combining computer vision and HCI principles to build immersive educational tools. The system is scalable and can be extended with additional features such as voice commands and augmented reality, paving the way for future intelligent learning systems.