JOURNAL ARTICLE
Air Canvas: Smart White Board.
Published In: Grenze International Journal of Engineering & Technology (GIJET), 2026, v. 12, n. Part2. P. 3079 1 of 3
Database: Applied Science & Technology Source Ultimate 2 of 3
Authored By: Chandolikar, Neelam; Pagar, Piyush; Pagare, Parth; Pagare, Shreyash; Palsande, Atharva; Palve, Durvas 3 of 3
Abstract
Technology is reshaping the way we interact with computers at a rapid pace, and touch-free interfaces are opening up new possibilities. Air Canvas is a creative and intuitive system that lets users draw, write, and annotate in the air—using only hand gestures, with no need for a stylus or touchscreen. Built with OpenCV, MediaPipe, and Python, it accurately tracks fingertip movements and translates them into real-time digital strokes. Unlike traditional methods that require physical contact, Air Canvas is contactless, easy to use, and eco-friendly, reducing paper waste and reliance on external tools. The system detects hand gestures using a simple webcam, allowing users to choose colours, adjust brush sizes, and erase with natural movements. This makes it especially useful for education, design, and interactive learning, where engaging digital tools are becoming essential. Whether in classrooms, remote learning, or creative projects, Air Canvas offers a fun, accessible, and smart way to interact with technology. By making digital drawing and writing more intuitive, it bridges the gap between traditional and modern methods, enhancing creativity and making e-learning more relevant in the virtual world. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Grenze International Journal of Engineering & Technology (GIJET). 2026/01, Vol. 12, Issue Part2, p3079
- Document Type:Article
- Subject Area:Computer Science
- Publication Date:2026
- ISSN:23955287
- Accession Number:192273012
- Copyright Statement:Copyright of Grenze International Journal of Engineering & Technology (GIJET) is the property of GRENZE Scientific Society and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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