Pankaj Raut

🏥 QueueCure – AI-Powered Smart Hospital Queue Management System with Real-Time Queue Tracking

Many clinics and hospitals still use paper tokens and manual queue management. Patients often do not know their queue position or expected waiting time, which leads to frustration and overcrowded waiting areas. Receptionists spend a lot of time answering the same questions about queue status, while doctors have limited visibility into the patient flow. QueueCure was built to solve this problem by creating a real-time digital queue management system. The goal was to reduce waiting uncertainty, improve hospital workflow, and provide live queue updates without requiring any page refresh. Process I started by analyzing the problems in traditional hospital queue systems, such as manual tokens, no wait-time visibility, and poor communication between patients and staff. I then designed the system architecture using Node.js, Express.js, MongoDB, and Socket.IO. I first built patient registration and queue management, followed by the patient portal, doctor dashboard, and live display screen. To achieve real-time updates, I implemented Socket.IO so that all connected screens stay synchronized instantly. Finally, I added wait-time prediction, analytics, PDF reports, history management, and tested different edge cases Results QueueCure successfully digitizes hospital queue management with real-time updates across the Receptionist Dashboard, Patient Portal, Doctor Dashboard, and Live Display Screen. The system provides live queue tracking, dynamic wait-time prediction, emergency queue handling, analytics, and PDF reporting. It improves queue visibility for patients and reduces manual workload for hospital staff. Reflection If I continue developing QueueCure, I would add user authentication, role-based access control, SMS and WhatsApp notifications, and appointment booking features. I would also improve the analytics system using machine learning to predict waiting times more accurately. For scalability, I would migrate the system to a cloud-native architecture and support multiple hospitals and branches from a single platform. I would also conduct real user testing in clinics to gather feedback and further improve the user experience.