Anushka Nikam

Queue Cure AI – Smart Healthcare Queue Management System

Problem Statement Many clinics still use paper tokens and manual queue management, causing long waiting times, poor transparency, and patient frustration. Patients often do not know their queue status or expected consultation time, while receptionists struggle with manual tracking and emergency prioritization. Queue Cure AI solves this by providing real-time queue tracking, smart wait-time prediction, emergency patient handling, and a digital queue system that improves efficiency for patients, doctors, and clinic staff. Process Our Process We researched common challenges in clinic queue management, including long waiting times, lack of transparency, and manual token systems. Using a user-centered approach, we designed separate views for receptionists and patients, implemented real-time updates using LocalStorage and Storage Events, and added smart wait-time prediction with emergency patient prioritization. Through multiple iterations, we simplified the interface and focused on creating a fast, transparent, and easy-to-use healthcare queue management solution. Results Queue Cure AI successfully transformed traditional paper-based queue management into a real-time digital solution. The platform provides live queue tracking, smart wait-time prediction, and emergency patient prioritization, helping patients stay informed while improving clinic efficiency. By reducing waiting uncertainty and streamlining queue operations, Queue Cure AI creates a faster, more transparent, and patient-friendly healthcare experience. Reflection If given more time, we would conduct real-world testing with clinics and patients to gather direct feedback and improve usability. We would also integrate a cloud-based backend for multi-device synchronization, implement AI-powered wait-time prediction using historical data, and add appointment booking and notification features. These enhancements would make Queue Cure AI more scalable, accurate, and deployment-ready.