Shri Adhithya . T

QueueSolved - Clinic Queue Management System

Neighbourhood clinics often manage patient queues using paper token slips, manual registers, and verbal announcements. This creates long and uncertain waiting times, frequent confusion about token order, extra workload for receptionists, and no real-time visibility for patients or doctors. Patients and guardians must physically stand in line just to register, while receptionists manually assign tokens, track consultations, handle skipped patients, and identify emergencies. In critical cases, delays in recognizing symptoms and prioritizing patients can affect care. Process We built QUEUE SOLVED with fixed consultation times and a basic TV display, but manual refreshes and hardcoded timings caused inaccurate ETAs. We solved this using WebSockets for real-time updates across all screens. MongoDB stores consultation history to calculate dynamic, disease-based averages, improving ETA accuracy. Patients can self-register via QR from the TV, and emergency cases are flagged and prioritized with receptionist approval, supported by voice alerts. Results QUEUE SOLVED replaces paper tokens and manual queue calling with a live digital clinic queue system. Receptionists can register patients, generate tokens, manage consultations, and prioritize emergency cases. Patients can self-register through a QR code and track their queue status. The receptionist dashboard, TV display, and patient queue update instantly without refresh. ETAs use stored consultation history instead of fixed timings, improving accuracy over time. The result is reduced receptionist workload, better patient visibility, and faster response to urgent cases. Reflection Future development will add multilingual voice guidance in Tamil, Hindi, and English; WhatsApp/SMS alerts when a patient’s token is near; doctor-specific ETA prediction using consultation patterns; appointment booking with no-show detection; offline queue mode for low-connectivity clinics; and a smart triage assistant that asks follow-up symptom questions before flagging emergencies. We also plan a multi-clinic dashboard so hospital groups can monitor queues, patient flow, and emergency load across branches.