MUMBAI, India, May 1 -- Intellectual Property India has published a patent application (202641047792 A) filed by Mani Deep Karumanchi; P Bhanuchand; Mathi Pujitha; Sakkurthi Pushpalatha; Motamarri Rakesh; and Yamana Adithya Reddy, Bapatla, Andhra Pradesh, on April 15, for 'ai-powered hand tracking system for virtual mouse and keyboard applicants.'
Inventor(s) include Mani Deep Karumanchi; P Bhanuchand; Mathi Pujitha; Sakkurthi Pushpalatha; Motamarri Rakesh; and Yamana Adithya Reddy.
The application for the patent was published on May 1, under issue no. 18/2026.
According to the abstract released by the Intellectual Property India: "The rapid advancement of technology has significantly transformed the way humans interact with computers, creating a demand for more natural, intuitive, and touchless interfaces beyond traditional input devices such as the mouse and keyboard. This project, titled AI-Enhanced Gesture Controlled Virtual Mouse and Keyboard, presents an innovative solution that enables users to perform computer operations using hand gestures without the need for physical hardware. The system utilizes a standard webcam to capture real-time video input and applies computer vision techniques to detect, track, and interpret hand movements. By identifying specific hand landmarks and finger positions, the system translates gestures into corresponding commands such as cursor movement, left and right clicking, scrolling, and virtual typing. The integration of artificial intelligence enhances the accuracy, efficiency, and adaptability of the system, allowing it to function effectively under different lighting conditions and for various users. Unlike conventional systems that rely solely on predefined rules, the proposed approach incorporates intelligent processing to improve gesture recognition and reduce errors. The system is designed to operate in real time, ensuring smooth and responsive interaction between the user and the computer. This touchless interaction method not only improves user convenience but also promotes hygiene, making it particularly useful in environments where physical contact with devices is limited or undesirable, such as healthcare facilities, public systems, and smart environments. Additionally, the solution offers accessibility benefits for individuals with physical disabilities, enabling them to interact with computers more easily. The project is developed using Python and integrates powerful libraries such as OpenCV for image processing, MediaPipe for hand tracking, and PyAutoGUI for controlling mouse and keyboard functions. The implementation focuses on simplicity, cost-effectiveness, and usability, as it does not require any specialized hardware apart from a basic webcam. Despite certain limitations such as dependency on lighting conditions and camera quality, the system demonstrates strong potential as an alternative to traditional input devices. Furthermore, the project opens pathways for future enhancements, including integration with voice commands, advanced deep learning models for improved accuracy, and expansion into applications such as virtual reality and augmented reality systems."
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