Virtual Hand Gesture and Voice Command Control System Using Computer Vision and Artificial Intelligence

  • Unique Paper ID: 207506
  • Volume: 13
  • Issue: 3
  • PageNo: 1273-1275
  • Abstract:
  • Human–Computer Interaction (HCI) has evolved significantly with advancements in Artificial Intelligence (AI) and Computer Vision. Traditional input devices such as keyboards, mice, and touchscreens often limit interaction in smart environments, robotics, healthcare, and assistive technologies. This paper presents a Virtual Hand Gesture and Voice Command Control System that enables users to interact with computers and IoT devices using natural hand gestures and speech commands. The proposed system employs MediaPipe for real-time hand landmark detection, OpenCV for image processing, TensorFlow-based gesture classification, and speech recognition for voice-controlled operations. The multimodal approach enhances usability by combining gesture recognition with voice commands, thereby improving accuracy and accessibility. Experimental results demonstrate an average gesture recognition accuracy of 97.8% and voice recognition accuracy of 96.5% under normal environmental conditions. The proposed system provides an efficient, touchless, and intuitive interface suitable for smart homes, healthcare, industrial automation, and assistive technologies.

Copyright & License

Copyright © 2026 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{207506,
        author = {purnima and Basavarajappa Sedam and Dr. Sripal Reddy},
        title = {Virtual Hand Gesture and Voice Command Control System Using Computer Vision and Artificial Intelligence},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {13},
        number = {3},
        pages = {1273-1275},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=207506},
        abstract = {Human–Computer Interaction (HCI) has evolved significantly with advancements in Artificial Intelligence (AI) and Computer Vision. Traditional input devices such as keyboards, mice, and touchscreens often limit interaction in smart environments, robotics, healthcare, and assistive technologies. This paper presents a Virtual Hand Gesture and Voice Command Control System that enables users to interact with computers and IoT devices using natural hand gestures and speech commands. The proposed system employs MediaPipe for real-time hand landmark detection, OpenCV for image processing, TensorFlow-based gesture classification, and speech recognition for voice-controlled operations. The multimodal approach enhances usability by combining gesture recognition with voice commands, thereby improving accuracy and accessibility. Experimental results demonstrate an average gesture recognition accuracy of 97.8% and voice recognition accuracy of 96.5% under normal environmental conditions. The proposed system provides an efficient, touchless, and intuitive interface suitable for smart homes, healthcare, industrial automation, and assistive technologies.},
        keywords = {Computer Vision, Hand Gesture Recognition, Voice Recognition, Artificial Intelligence, MediaPipe, OpenCV, Human Computer Interaction, IoT.},
        month = {August},
        }

Cite This Article

purnima, , & Sedam, B., & Reddy, D. S. (2026). Virtual Hand Gesture and Voice Command Control System Using Computer Vision and Artificial Intelligence. International Journal of Innovative Research in Technology (IJIRT), 13(3), 1273–1275.

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