J Sowbarnikaa
Featured project
QueueCure Smart Room Display
### Project Statement **QueueCure Live** is a real-time, full-stack queue management platform built with Node.js and Socket.io to eliminate chaotic manual loops in clinical OPDs. By leveraging a centralized server-side state architecture, the system guarantees zero-latency (<50ms) sync between receptionist entries and public monitors. It automates patient-placement pacing, replaces paper tokens, and removes waiting-room blind spots to deliver complete operational transparency. Process Problem Discovery: Researched OPD bottlenecks, identifying paper token losses and manual calling as key sources of patient anxiety and administrative friction. Architecture Design: Designed a lightweight Node.js/Express server using a single state object as the undisputed source of truth to guarantee complete data integrity. Real-time Pipeline: Implemented bidirectional WebSockets with Socket.io, engineering a zero-latency (<50 ms) push network to sync reception updates with patient screens. UI Refinement: Created responsive dual portals using HTML5 and Tailwind CSS, embedding HTML escaping to secure patient displays against XSS injection risks. Results Replaced slow database polling with lightweight WebSocket state broadcasts, resulting in instantaneous data reflection across all displays. Unified all screens under a server-side "Single Source of Truth," eliminating status mismatches or desync bugs. Shifted OPD tracking from a blind-spot to a predictive model (2Hr -> Instant visibility), drastically lowering patient anxiety. Eliminated paper waste and manual shouting, streamlining staff workflows. Reflection Move from volatile server memory to a Redis/MongoDB layer to retain queue states across unexpected server restarts. Integrate Twilio or WhatsApp Business APIs to ping patients when they are "3 tokens away," allowing them to wait outside safely. Replace static average consultation times with an ML model that predicts wait times based on doctor specialty, time of day, and patient case complexity. Refactor code to support multiple rooms and doctors simultaneously.