Surya Saravanan

SyncX - Realtime Smart Queue Management System

Many clinics still use manual queue systems, causing confusion, long waits, and repeated interruptions at reception desks. Patients often don’t know their token status or estimated waiting time, while receptionists struggle to manage queues and emergency cases efficiently. To solve this, we built SyncX — a realtime smart queue management system with live token tracking, dynamic waiting-time estimation, emergency prioritization, and separate dashboards for patients and reception staff using Socket.IO for instant updates. Process We studied how local clinics manage queues and identified key issues like repeated patient inquiries, lack of real-time waiting updates, and poor handling of emergency cases. Our initial static queue system failed due to manual refresh requirements and no real-time sync. We then redesigned the system using Socket.IO for instant updates, MongoDB for dynamic queue storage, and React with Tailwind for a responsive UI. We refined the wait-time estimation multiple times to improve accuracy. The final solution delivers a simple, real-time system that enhances efficiency, reduces confusion, and improves overall clinic workflow. Results The system improved queue efficiency by enabling real-time updates and reducing patient confusion. Testing showed sub-second sync latency and improved wait-time accuracy after multiple iterations. Users reported better clarity of queue position and smoother experience. Reception workload was reduced due to automation. Future work includes predictive emergency handling, analytics dashboards, and large-scale real-world testing for scalability. Reflection Next time, I would start with a real-time architecture from the beginning instead of building a static prototype first, to save iteration time. I’d also involve clinic staff earlier in testing to refine wait-time logic based on real scenarios. Adding predictive analytics for patient flow and emergency prioritization would improve accuracy further. Finally, I would focus more on scalability and deploy pilot versions across multiple clinics to validate performance under real-world load.