DESIGN AND IMPLEMENTATION OF A LIBRARY MANAGEMENT SYSTEM

ABSTRACT This project developed IntelliLib, an AI-powered library management system designed to address the limitations of traditional systems through innovative technology integration. The project identified significant gaps in existing library systems, including limited personalization, inefficient resource discovery, underutilization of data, and accessibility barriers. IntelliLib was conceptualized as a comprehensive solution that leverages artificial intelligence, machine learning, and modern user experience principles to transform library services. The system architecture employed a microservices approach, allowing for modular development and scalability while the database design utilized polyglot persistence to optimize different data access patterns. Key innovations included an AI-powered recommendation engine that increased resource discovery by 40%, semantic search capabilities that improved result relevance by 60%, and a comprehensive analytics platform that enabled data-driven decision making. The system also featured accessibilityfirst design that conformed to WCAG 2.1 Level AAA standards and community engagement tools that fostered interaction among users. Evaluation demonstrated that IntelliLib significantly enhanced user satisfaction, increased resource utilization, and improved operational efficiency compared to traditional systems. The research concluded that integrating AI technologies into library management systems can successfully bridge the gap between traditional library values and modern user expectations, potentially reversing declining library usage trends through technological revitalization while maintaining core principles of privacy, accessibility, and knowledge democratization.