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.

@article{192841,
        author = {Sarvesh Kadam and Gayatri Gangadhar Urmude and Samruddhi Vijay Bhor and Sakshi Dattatray Kandekar and Prof. Hole.P.P},
        title = {AI-Driven-Gesture-Controlled-Image-Capture-with-Cloud-Sharing-main},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {9},
        pages = {3079-3084},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=192841},
        abstract = {The rapid adoption of touchless technologies has increased the demand for contactless documentation systems in academic and industrial environments. This paper presents a Smart AI-based Contactless Documentation System that utilizes real-time hand gesture recognition to automate image capture and securely synchronize data with cloud storage. Unlike traditional systems requiring manual interaction, the proposed solution integrates a deep learning-based hand landmark detection model with automated cloud authentication and secure sharing mechanisms. The system enhances workflow efficiency, minimizes physical contact, and ensures data accessibility through encrypted cloud links. Experimental evaluation demonstrates high gesture recognition accuracy (above 95%) with minimal latency. The proposed framework is scalable and suitable for smart laboratories, digital documentation centers, and industrial inspection systems.},
        keywords = {},
        month = {February},
        }