SCHOOL MANAGEMENT SYSTEM 4: LIBRARY MANAGEMENT SYSTEM “AUTOMATED CATALOGING AND IMPROVED ONLINE PUBLIC ACCESS CATALOG SERVICES USING A.I DRIVEN TOOL”

Abstract

School libraries serve a vital function in academic institutions by providing access to essential learning resources. However, many still rely on outdated systems, characterized by inefficient manual cataloging, disorganized inventories, and limited Online Public Access Catalog (OPAC) capabilities. These challenges hinder accessibility, reduce user satisfaction, and compromise operational effectiveness. This study proposes the development of an AI-driven Library Management System (LMS) that automates cataloging processes and enhances OPAC functionalities, aiming to significantly improve the user experience and overall library efficiency. To ensure adaptive development and active stakeholder involvement, the system was built following the Agile Scrum methodology, which supported iterative progress and regular feedback cycles. A microservices architecture was adopted to promote modularity, scalability, and efficient system maintenance. Key system functionalities include AI-driven automated cataloging, smart classification of books, metadata generation through ISBN lookup, real-time availability tracking, personalized search suggestions, and a user-friendly, responsive OPAC interface. Development and deployment were streamlined through the application of DevOps principles, including Continuous Integration (CI) and Continuous Deployment (CD), enabling rapid, reliable software delivery. The implementation of the system resulted in substantial improvements in both the speed and accuracy of cataloging processes. The integration of AI tools significantly minimized manual data entry and reduced the likelihood of human error. The enhanced OPAC system became more intuitive and responsive, offering features such as real-time book availability, personalized recommendations, and faster, more accurate search functionality. Surveys and user feedback from librarians and students reflected a marked increase in satisfaction and engagement, demonstrating the system's positive impact on overall library service delivery. This project underscores the transformative potential of artificial intelligence in modern library management. The automation of key tasks, intelligent search capabilities, and enhanced user interfaces collectively contributed to a more efficient, accessible, and user-centered library system. The adoption of a microservices framework ensured seamless integration, system scalability, and simplified maintenance. Overall, the developed Library Management System (LMS) presents a forward-thinking solution for academic institutions seeking to modernize and optimize their resource management processes.