Abstract: In this research, a novel system that uses machine learning-recognized hand gestures to ease file transfer and computer control between two nearby PCs is displayed. By the use of gestures like "catch" and "throw," users may transfer files between computers and handle fundamental PC functions like media control, file browsing, and cursor movement. Bluetooth PAN (Personal Area Network) is used to establish communication between devices, allowing easy data sharing without the need for cable connections or difficult file browsing. The system uses a trained machine learning model for classification, OpenCV for image processing, and a standard webcam for gesture detection. Within an 8–10 m range, experimental results showcase reliable file transfer capability and accurate gesture detection. The goal of this initiative is to enhance computer-human interaction.
Keywords: Machine Learning, Gesture Recognition, File Transfer, Bluetooth PAN, Human-Computer Interaction, Computer Vision.
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DOI:
10.17148/IJARCCE.2025.141153
[1] Prathamesh Tupe, Sakshi Pawar, Atharva Pagale, Neenad Jadhav, Prof. Suchitra Deokate, "Gestural Interface for Networked Kinesthetic Operations (G.I.N.K.O.)," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141153
