NextGen: An AI-Integrated Library Management System

Abstract

Traditional library management in Indian academic institutions continues to rely on paper registers, standalone desktop tools, and manual workflows that fail to meet the expectations of a digitally connected student community. This paper presents NextGen, a full-stack AI-integrated Library Management System (LMS) developed using the MERN technology stack (MongoDB, Express.js, React 18, Node.js 20). The system supports three distinct user roles — Student/Member, Librarian, and Administrator — with privilege separation enforced through JSON Web Token (JWT) authentication and server-side Role-Based Access Control (RBAC) middleware. Students can discover, reserve, and track borrowed books from any browser-enabled device while receiving personalised book recommendations generated by a content-based filtering engine built on TF-IDF vector representations and cosine similarity. Librarians benefit from an automated loan lifecycle, real-time fine calculation executed by a scheduled cron job, and a live dashboard displaying overdue items and pending reservations. Administrators access collection analytics exportable as CSV and PDF reports. Performance benchmarking against a dataset of ten thousand books and five hundred members under fifty concurrent users demonstrates that 95% of API responses complete within 200 milliseconds, full-text catalogue searches resolve in under 100 milliseconds, and the recommendation engine achieves a mean cosine similarity score of 0.74. The system is containerised with Docker Compose, enabling single-command deployment without specialised DevOps knowledge. A user study with fifteen MCA volunteers yielded an average recommendation relevance rating of 3.8 out of 5, compared to 2.1 for a random baseline, confirming measurable discovery improvement over traditional browsing.

Introduction

The text discusses the limitations of traditional academic library systems, which still rely on outdated manual processes such as physical records, manual fine calculation, and limited accessibility. These systems create inefficiencies for students, librarians, and administrators, especially in modern digital environments where real-time access and automation are expected.

To address these issues, the proposed system NextGen is a web-based, AI-powered library management platform built using the MERN stack (MongoDB, Express.js, React, Node.js). It leverages cloud technologies and modern web architecture to provide a fully accessible, scalable, and efficient solution.

The system solves key problems in existing library systems, including:

• Lack of remote access to library services
• Manual and error-prone fine management
• Absence of intelligent book recommendations
• Weak authentication and role control
• Limited reporting and analytics capabilities

NextGen introduces several improvements:

• Full web accessibility through any browser and device
• AI-based book recommendations using TF-IDF and cosine similarity
• Real-time fine calculation and display
• Secure authentication with role-based access control (RBAC)
• Automated reporting and notifications
• Easy deployment using Docker

Compared to existing systems like Koha, Evergreen, and OpenBiblio, NextGen offers a modern user interface, mobile responsiveness, integrated AI features, and simplified deployment.

The system follows a three-tier architecture with a React frontend, Node.js backend, and MongoDB database. It supports different user roles (students, librarians, administrators) with specific functionalities.

Overall, NextGen modernizes library management by combining web technology, automation, and AI, improving accessibility, efficiency, and user experience while enabling data-driven decision-making in academic libraries.

Conclusion

This paper presented NextGen, an AI-integrated Library Management System built on the MERN stack that modernises the complete library operational workflow for Indian academic institutions. The system achieves its core technical objectives: a multi-role, JWT-secured React 18 frontend delivers distinct privilege-controlled dashboards for Members, Librarians, and Administrators; a Node.js Express REST API with Mongoose ODM manages the complete loan lifecycle with atomic MongoDB transactions; an automated fine calculation system with daily cron job execution eliminates manual fine management; and a content-based TF-IDF recommendation engine delivers personalised reading suggestions that measurably improve catalogue discovery compared to traditional browsing. Empirical validation confirms consistent performance and reliability: all 50 unit tests pass, all 12 integration test scenarios return expected responses, and performance benchmarking confirms 95% of API operations complete within 200ms under 50 concurrent users. NextGen makes a practical contribution to library technology in the Indian academic context by demonstrating that a full-featured, AI-enriched LMS can be delivered using freely available open-source technology, deployed with minimal infrastructure expertise through Docker Compose, and operated without recurring software licensing costs.

References

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Copyright

Copyright © 2026 Mr. Siriki Durga Venkat, Mr. Dulam JayaSurya, Mr. Shaik Riyaz, Ms. Thoram Harshitha. This 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.