PulseQ — AI-Powered Real-Time Clinic Queue & Patient Flow System

Many clinics in India still rely on paper token slips and manual queue management. Patients often wait for hours without knowing when they'll be called, while receptionists manage everything from memory. Existing processes provide no visibility, no real-time updates, and no accurate wait-time estimates. The goal of PulseQ was to transform traditional paper-based queues into a real-time, intelligent patient flow system that improves transparency for patients and efficiency for clinics. I started by identifying the minimum requirements: receptionist dashboard, patient view, and live synchronization. I designed the system around Socket.IO so that queue updates propagate instantly across all screens without refresh. To avoid hardcoded estimates, I calculated waiting times from actual consultation durations. I then extended the solution with OCR-based paper token digitization, QR token tracking, priority queues, analytics, and AI-assisted recommendations. The architecture follows a modular MVC structure using React, Node.js, Express, Mo PulseQ transformed manual paper-token workflows into a digital real-time queue system. Patients can track their position and estimated wait times without repeatedly asking receptionists. Live synchronization ensures all screens update instantly, while historical consultation data enables accurate wait prediction. Additional capabilities like OCR migration, QR tracking, analytics, and AI recommendations make PulseQ closer to a clinic operating system than a simple queue manager, improving transparency and reducing operational overhead. Given more time, I would add multi-doctor support, WhatsApp notifications, appointment scheduling, offline synchronization for unstable networks, and deeper AI capabilities through Pulse Companion and Pulse Guardian. I would also improve prediction accuracy using historical traffic patterns and consultation trends. Finally, I would conduct user testing with clinics to validate usability and refine the experience based on real-world workflows and feedback.