Volume 2 - Issue 2, March - April 2026

Inefficient queue management in secured banking and healthcare sectors often leads to prolonged waiting times, overcrowding, and reduced service quality. Traditional token systems lack predictive capabilities and real-time user engagement, resulting in poor time utilization and operational inefficiencies. This paper presents a Smart Queue Management and Token Prediction System designed to optimize customer flow through a secured web-based platform. The proposed system enables users to generate secured digital tokens remotely and receive timely notifications regarding their service status. A historical data-driven prediction mechanism is integrated to estimate waiting time by analysing past service durations and real-time queue length. The system dynamically adjusts predictions based on service patterns, improving accuracy during peak and non-peak hours. Experimental evaluation demonstrates that the proposed solution reduces uncertainty in waiting time estimation and minimizes physical crowding in service environments. The architecture is scalable, cost-effective, and adaptable for deployment in banking, healthcare, and other high-density service sectors. .

Rajasuriaa R, Dr.Sreejith Vignesh B P, "Smart Queue Management and Token Prediction System for Secured Banking and Healthcare Sectors" International Journal of Advanced Multidisciplinary Research and Educational Development, V2(2): Page(300-303) Mar-Apr 2026. ISSN: 3107-6513. www.ijamred.com. Published by Scientific and Academic Research Publishing.