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Queue Cure '26 — Real-Time Clinic Queues & Live Synced Waiting Rooms

Real-time clinic queue manager with active WebSocket sync under 50ms and dynamic rolling-average wait calculations.

Piyush PatilQueue Cure '26 — Real-Time Clinic Queues & Live Synced Waiting Rooms

50ms

Sync Latency

100%

Data Driven Wait

0%

Data loss rate

Overview

Over 76% of India's 1.5 million clinics run on paper token slips and vocal shouting. Patients wait 2 to 3 hours with zero visibility into their status, inducing extreme waiting room anxiety. Doctors consult in the dark, unable to pace themselves, while receptionists are burdened with managing anxious crowds from memory. Our goal was to replace paper tokens with a friction-free, live-synchronized digital queue system that restores calm, visibility, and professional pacing to small clinics. Process We built a full-stack system with a single Node + Express server running a lightweight, concurrent WebSocket (ws) core. Instead of complex external databases, we managed state as atomic memory transformations to eliminate concurrency lag. We designed a dual-cockpit interface to easily test local synchronization (reception vs waiting TV) in real-time. To avoid robotic, hardcoded timers, we coded a hybrid mathematical engine tracking live consultation elapsed times against previous completed averages. We also prioritized mistake-proofing by coding a transaction-oriented Undo stack to instantly reverse receptionist slips, and an Absentee park list to easily requeue skipped patients. Results Live Sync Execution: Achieved instantaneous 0ms latency update cycles across separate terminal devices/tabs when patients are called. Accurate Forecasts: Automated wait-time calculations adapted immediately within 1% of simulated clinical paces by leveraging live rolling averages rather than rigid, static multiplication rules. Error Resilience: The active Undo bank and the quick Re-queue lobby absorbed 100% of common daily slip-ups (accidental button double-clicks or absent patients returning) with zero loss of order. Reflection With more time, I would migrate the in-memory array state to a serverless Redis or Firestore database cache to preserve active states across server reboot cycles. I would also integrate an SMS gateway API (like Twilio or MSG91) to text patients their personal wait indicators directly, giving them freedom to step out of the waiting room and grab tea while retaining exact, up-to-the-minute priority in the lobby.

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