Abstract: In the realm of online education and artistry, the limitations of conventional mice for digital drawing and illustration have posed challenges for educators, students, and artists. The impracticality of a mouse hinders the fluidity and precision crucial for effective teaching and learning, particularly in visually dependent subjects. Additionally, the high cost of specialized drawing tablets has restricted access, limiting creative expression in the digital realm. The "AirInk Studio" project addresses these challenges by introducing an innovative desktop application. Powered by Python, OpenCV, Mediapipe, and Tkinter, it utilizes computer vision and hand tracking for a seamless drawing experience. Boasting diverse brush styles, an undo feature, and an extensive color palette, the project caters to varied artistic preferences. Not only does it redefine online education, but it also empowers artists with an affordable and versatile digital canvas, democratizing creativity in the virtual space. Furthermore, the project expands its capabilities with features like drawing shapes, including circles, rectangles, and lines, as well as a text box feature for annotations and labels. The integration of a chat web application, developed with React.js and Firebase, enables real-time collaboration and connection among users. Moreover, a community showcase web app, leveraging React.js and Firebase, provides users with a platform to share and exhibit their creations, fostering a vibrant digital art community. Together, these enhancements elevate the "AirInk Studio" project, enriching the digital art experience and promoting collaboration and creativity among users.

Keywords: Python, OpenCV, Mediapipe, Tkinter, Computer vision, Hand tracking, React.js and Firebase.

Cite: Shreyas Shinde, Vedant Ingale, Mandar Terkhedkar, Amey Ashtankar, Prof. Archana Dirgule, "Literature Survey on AirInk Studio: A Visual Drawing Model", IARJSET International Advanced Research Journal in Science, Engineering and Technology, vol. 11, no. 3, 2024, Crossref https://doi.org/10.17148/IARJSET.2024.11357.

| DOI: 10.17148/IARJSET.2024.11357