QueueCure – Smart Clinic Queue Management System

76% of India's 1.5 million clinics still run on paper token slips and shouting. Patients wait 2-3 hours with zero visibility into their position. Receptionists juggle paper and verbal announcements. Doctors have no dashboard. Built for Queue Cure '26 Hackathon by Wooble × Unstop, with the core requirement: both receptionist and patient screens must update instantly when "Call Next" is clicked, with zero refresh. Process I chose Socket.io over polling because the requirement demanded sub-second updates across multiple screens. I designed the wait-time calculation as position × avgConsultationTime, computed live and never hardcoded — receptionists can adjust consultation time at any moment and all wait times recalculate instantly across every connected screen. For the receptionist UI, I prioritized mistake-proofing: confirmation dialogs for destructive actions, disabled states when the clinic is closed, and toast feedback on every action. I separated "Skip" from "Remove" as distinct actions to prevent accidental data loss. I documented concurrency explicitly — Node.js processes Socket.io events on a single thread, so multiple receptionists clicking "Call Next" simultaneously cannot race condition; events Results Live sync confirmed at under 50ms across all connected screens in production testing. Successfully deployed full-stack: backend on HuggingFace Spaces (Docker), frontend on Netlify, with GitHub auto-deploy CI/CD. Built and shipped a working AI chatbot, voice announcement system, and live analytics dashboard beyond the hackathon's core requirements — demonstrating both speed and depth under a 9-day timeline. Reflection I'd add MongoDB persistence so queue data survives server restarts — currently it's in-memory, which resets if the HuggingFace Space restarts. I'd also add SMS notifications via Twilio so patients don't need to keep the browser tab open to know when they're called.