QUEUE CURE '26

In hospitals, clinics, and service centers, long waiting queues and lack of real-time updates caused frustration for users and inefficient crowd management for staff. Patients had no visibility on waiting time or queue status, leading to unnecessary physical waiting and poor experience. The goal of Queue Cure was to digitize queue management and provide real-time tracking and smart queue updates. Process We started by analyzing real-world queue problems in hospitals and service centers. We identified key pain points like uncertainty in waiting time, lack of token tracking, and manual queue handling. We then designed a simple digital flow where users can join queues online and track their position in real time. We built the frontend using a modern web stack and focused on a clean, mobile-friendly UI. During development, we faced issues with setup and server connection, which we resolved by debugging Node.js configuration and project structure. We iterated the UI multiple times to make it more intuitive and reduce user confusion. Results Queue Cure successfully demonstrated a working prototype for digital queue management. The system improved clarity in queue tracking and reduced uncertainty for users. The interface allowed users to understand their position in the queue easily and reduced dependency on physical waiting. Judges appreciated the practical problem-solving approach and clean UI flow. Reflection I would implement full real-time backend synchronization (WebSockets/Firebase) for live queue updates instead of simulated updates. I would also add analytics for hospitals to predict peak hours and optimize staffing. More user testing with real hospital scenarios would further improve system accuracy and usability.