Pages: 1-5

Ranjana S. Dhiwar, Santosh Koditka

DOI: https://adypsoe.in/adypjiet-journal/Artical-21-2025-9-30

This study presents the design, implementation, and evaluation of an artificial intelligence (AI)-enabled radio frequency identification (RFID)-based tracking bookshelf system aimed at improving library management efficiency. By integrating passive ultra-high frequency RFID tags with machine learning algorithms and real-time analytics, the proposed system enables continuous item localization, automated inventory auditing, anomaly detection, and improved circulation workflows. A prototype was deployed in a mid-sized academic library and tested using a controlled dataset of 500 books. Experimental findings indicate 95% localization accuracy, a 40% reduction in average search time, and substantial improvements in audit efficiency. User feedback from librarians and patrons further supports the usability of the system. The results demonstrate that AI-enhanced RFID infrastructure can significantly improve operational visibility and enable data-driven library management.