Jaya Nikhilesh Ravichandran

QueueCure AI – Real-Time Smart Clinic Queue Management System

Many clinics in India still depend on paper tokens and manual announcements for patient queues. This leads to long waiting times, poor transparency, and increased workload for receptionists. Patients often wait for hours without knowing their position in the queue, while staff manually track and call tokens. There is no accurate wait-time prediction or real-time communication. QueueCure AI solves this by digitizing queue management with live updates, voice-assisted operations, and intelligent wait-time estimation. Process I developed a real-time clinic queue management system to eliminate manual tracking for patients, receptionists, and administrators. I designed two synchronized interfaces: a Receptionist Dashboard for patient registration and a Patient Waiting Room display showing tokens, queue positions, and estimated wait times. Powered by Socket.IO and MongoDB, the system features Tamil and English voice recognition for hands-free operations and leverages historical consultation records for dynamic wait-time predictions. To ensure a reliable, scalable solution, I engineered robust handling for edge cases like emergency patients, skipped tokens, duplicate actions, and network interruptions. Results 100% real-time queue synchronization using Socket.IO Dynamic wait-time prediction based on consultation history Reduced manual receptionist workload through voice commands Emergency patient prioritization without disrupting queue integrity Improved patient transparency with live queue visibility Scalable MERN-stack architecture supporting multiple users simultaneously Reflection Unlike traditional systems, QueueCure AI unifies real-time sync, Tamil/English voice commands, voice announcements, and AI wait-time predictions in one platform. Built for actual clinic deployment, it enables hands-free receptionist management via speech recognition, emergency prioritization, dynamic recalculations, and queue analytics. The architecture is engineered to robustly handle critical real-world edge cases, including simultaneous updates, skipped tokens, and network interruptions.