Current Volume 10
Libraria: An Intelligent Smart Library Management System Using Machine Learning, R Analytics, and IoT-Based QR Verification
Abstract
The Libraria Smart Library Management System is an integrated digital platform developed to automate and modernize traditional library operations using Web Development, Machine Learning, R Analytics, Mobile Application Development, and IoT-based QR verification technologies. Conventional library systems often depend on manual processes for maintaining records, verifying borrow requests, calculating fines, and tracking inventory, leading to inefficiency and increased administrative workload. The proposed system addresses these limitations by providing an intelligent, secure, and user-friendly smart library platform. The system enables students and administrators to access library services through both web and Android mobile applications. The frontend was developed using HTML, CSS, and JavaScript, while Supabase was used as the cloud backend for authentication, database management, and real-time synchronization. The system supports functionalities such as secure login, book searching, borrow request management, QR-based verification, fine tracking, analytics generation, and personalized recommendations. Machine Learning techniques such as TF-IDF and Cosine Similarity were implemented to generate intelligent book recommendations based on user borrowing history and preferences. R programming was used to generate statistical insights including borrow trend analysis, overdue risk prediction, correlation analysis, and fine statistics. QR code technology was integrated to automate borrowing verification and improve security through contactless authentication. The project demonstrates the practical integration of multiple modern technologies into a single unified platform capable of improving automation, accessibility, analytics, and user experience in educational institutions. Overall, Libraria provides a scalable and efficient smart library solution suitable for modern digital learning environments.
Keywords
Smart Library Management System, Machine Learning, TF-IDF, Cosine Similarity, R Analytics, QR Verification, Supabase, Android WebView, Web Application, IoT.
Citations
IRE Journals:
Dr. J. Narendra Babu, Dr. Deepak S Sakkari, Harshitha V, G Yogeendra; Goutham S, Hemanth H ; Deekshith A. E "Libraria: An Intelligent Smart Library Management System Using Machine Learning, R Analytics, and IoT-Based QR Verification" Iconic Research And Engineering Journals Volume 9 Issue 12 2026 Page 3084-3087 https://doi.org/10.64388/IREV9I12-1719236
IEEE:
Dr. J. Narendra Babu, Dr. Deepak S Sakkari, Harshitha V, G Yogeendra; Goutham S, Hemanth H ; Deekshith A. E
"Libraria: An Intelligent Smart Library Management System Using Machine Learning, R Analytics, and IoT-Based QR Verification" Iconic Research And Engineering Journals, 9(12) https://doi.org/10.64388/IREV9I12-1719236
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