Advanced International Journal for Research

E-ISSN: 3048-7641     Impact Factor: 9.11

A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal

Call for Paper Volume 7, Issue 2 (March-April 2026) Submit your research before last 3 days of April to publish your research paper in the issue of March-April.

Smart Queue Management

Author(s) Mr. S. Gunasekaran, B. Gowtham, K. Gowdham, B. C. Gopish, B. Elamathi
Country India
Abstract The Smart Queue Management is software that is implemented online in hospitals. Long waiting in the Queue is the common problems in this generation. It will create overcrowded in hospital lobbies, leads to frustration and insufficient space. We use digital tokens to prevent this and handle the order of service. The Smart Queue Management System is based on digital token allocation. The facility allows users to sign up and sign in. After joining, they can monitor their token in real time. They may choose the hospital they like best. The system also Notifies the members when their time is near or at least 30 minutes ahead through SMS, e-by mail or push notification. They will no longer queue. They will be able to produce payment via online. The system is more convenient in helping the service providers in Regulate the customer flow with an interactive dashboard. The system enables the staffs monitor wait times. The system is developed utilizing Java- based backend including token management database. It is also appropriate in banks and other service environment. Finally, the future work seeks to revolutionize the experience of queuing by eliminating unnecessary wait, stress, and enhancing the overall Efficiency in the delivery of services. The Smart Queue Management System introduces up-to-date, environmentally friendly and efficient means of dealing with the daily issue in the waiting line.
Keywords Smart queue management, intelligent scheduling, quality of service (QoS), congestion control, resource allocation, queue optimization, network performance, adaptive queue systems, and machine learning in networking.
Field Computer Applications
Published In Volume 7, Issue 2, March-April 2026
Published On 2026-03-02

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