Real Time Queue Management System

Authors: Ahire Ayush Pravin, Pawar Aakash Pralhad, Nagare Pallavi Bansilal, Karad Shrirang Karad, R. M. Gawande

Country: India

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Abstract: The increasing number of visitors in government offices often leads to long waiting times, overcrowding, and inefficient service management. Traditional queue systems lack real-time updates and proper communication, causing inconvenience for both citizens and staff. This paper presents a Real-Time Queue Management System designed to improve service efficiency using an Android-based application and a Python-Django backend. The system enables users to book queue tokens digitally, track their position, and receive real-time notifications about their turn. A Linear Regression algorithm is used to predict waiting times based on current queue data, enhancing accuracy and user convenience. Additionally, a chatbot module is integrated to assist users with common queries, and a dedicated section provides information about government schemes and eligibility criteria. The system ensures better organization, reduces physical crowding, and improves overall user experience. Experimental outcomes indicate improved efficiency, reduced waiting time, and enhanced service transparency, making the system suitable for modern government offices and public service environments.

Keywords: Queue Management System, Real-Time Prediction, Linear Regression, Android Application, Django Framework, Notification System, Chatbot, Government Services, Waiting Time Prediction, Smart Governance.

Paper Id: 233157

Published On: 2026-06-15

Published In: Volume 14, Issue 3, May-June 2026

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