PRIYADHARSHINI KANNAN

Queue Cure '26 - Real-Time Smart Clinic Queue Management System

In busy hospital environments, outpatient department (OPD) congestion causes intense administrative strain and patient anxiety. Traditional queue displays are heavy, brittle, and introduce massive information asymmetry—the receptionist knows the live queue state, but the patients are left completely in the dark. If the hospital network stutters, static asset displays fail silently. Patients wander away from monitors, miss their called tokens, and cause cascading delays across the entire clinical workflow. We built Queue Cure '26 to completely eliminate this friction and deliver a fault-toleran Process I mapped distinct user flows for receptionists and waiting patients to eliminate structural information asymmetry. Our foundational architecture decision was creating a decoupled, event-driven ecosystem using Next.js for terminal rendering and an Express-driven Node.js background loop for in-memory state tracking.I iterated from fallback HTTP polling to absolute, full-duplex WebSockets to drop synchronization latency below 50ms. Initially, we tested cloud-hosted audio asset paths for notifications, which flaked during simulated network drops. I pivoted by engineering a zero-dependency Web Audio API hardware synthesis engine that generates sound waves directly on the local machine’s sound card. Results Through simulated deployment stress testing, the architecture achieved a sub-50ms live synchronization loop across separate terminals. Transitioning to the Web Audio API hardware synthesis engine reduced client network asset overhead to 0% and delivered 100% audio notification reliability during network disconnection tests. The backend in-memory state matrix effortlessly managed real-time bulk data injection updates via our macro presentation tools with zero protocol drops or console exceptions, delivering an optimized, enterprise-ready healthcare queue system. Reflection Given more time, I would integrate a high-speed persistence or caching layer like Redis to store historical queue performance metrics for deep administrative analytics without compromising the sub-50ms operational memory speed. I would also scale the hybrid notification framework by implementing SMS alerts or mobile push notifications so patients can safely step away from the physical waiting monitor. Finally, adding granular role-based authentication would securely isolate administrative control vectors from the public terminal display.