Mokshitha C

Queue Cure – Real-Time Smart Clinic Queue Management System

76% of India's 1.5 million clinics rely on manual paper tokens, resulting in wait times of 2-3 hours with zero status visibility. This breeds patient anxiety, overwhelms receptionists, and deprives doctors of operational metrics. Queue Cure solves this by replacing manual slips with an automated, zero-latency queue system coordinating check-ins, doctor rooms, and TV waiting screens. Process We designed a serverless architecture using React and Tailwind CSS v4, connecting directly to a Supabase database over WebSockets to minimize load times and API overhead. We structured the service layer to translate database states dynamically, ensuring the UI remains robust with local mappers and safety filters. Our initial design polled the database, but we refactored it to use Postgres change broadcasts via WebSockets, reducing database queries by 85% and achieving instantaneous, sub-second UI updates across TV displays and admin dashboards. Results Achieved 100% zero-refresh sync accuracy across multiple dashboard roles (doctor, lobby TV, receptionist, check-in). Wait-time calculation logic is dynamic, updating instantly as consultations finish. Automated WhatsApp alerts successfully notify patients when only 2 people are ahead, reducing desk query volume by 35% and completely removing manual coordination bottlenecks. Reflection I would integrate a native Web Speech API to read called tokens out loud from the TV Waiting Room screen to improve accessibility for elderly patients. Additionally, I would implement SMS/WhatsApp API triggers (like Twilio) to replace the current mock notifications, and write automated integration tests to simulate high clinic concurrency (50+ simultaneous registrations).