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{202822,
        author = {P. Janani and S. Dhanushya and K. Kavyadharshini and Mrs. R. Sudha},
        title = {Smart Lost and Back To Me: An Intelligent Lost and Found Management System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {10001-10007},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=202822},
        abstract = {Lost items such as identity cards, ATM cards, access cards, and official documents are frequently misplaced in educational institutions, offices, and public environments. Traditional lost-and-found systems rely heavily on manual processes, which are time-consuming, inefficient, and prone to human error. This paper proposes “Back To Me: Smart Lost and Found Box”, an intelligent and automated system integrating Internet of Things (IoT), Machine Learning, and web technologies to efficiently manage lost items. The proposed system consists of a smart physical box equipped with multiple slots and embedded camera modules. When a found item is deposited, the system automatically captures its image. The captured image is processed using Python based Machine Learning algorithms, specifically the YOLO (You Only Look Once) object detection model for real-time identification and classification. A web application developed using HTML and CSS enables users to register and report lost items. The system compares captured images with stored database records to verify ownership. Upon successful identification, a secure One-Time Password (OTP) is sent to the registered email ID, allowing authorized access to retrieve the item. The proposed system significantly reduces manual effort, enhances security, improves accuracy, and provides a scalable solution suitable for campuses, offices, and smart public infrastructures.},
        keywords = {},
        month = {May},
        }