Two-Hand Gesture Recognition for User Information Interaction based on Internet of Educational Things

With the increasing prevalence of computer technology, interaction through the computer has become a significant challenge for certain groups, such as the elderly, disabled, and students. Hand sign recognition has emerged as a promising solution in recent years, as it offers a natural and adaptable means of human-machine interaction, particularly in educational contexts. However, real-time hand gesture recognition is a complex system development task that requires advanced technology and expertise. To address this issue, we propose a system architecture and software configuration for developing hand sign recognition based on the internet of things (IoT). In the experiment, a Raspberry Pi with a camera, Python programming, and Open-Source Computer Vision (OpenCV) software were used to develop an accurate system for detecting, recognizing, and interpreting two-hand gesture recognition in the context of human-IoT interaction. The project's primary focus is improving the accuracy of hand sign gesture recognition in real-time systems. The proposed system contributes to facilitating friendly and adaptable human-computer interaction, especially in educational services. In addition, the research result enables better computer interactions for the elderly and disabled, thus promoting greater inclusivity and accessibility in the technology industry.