Abhirishitha Naraharisetti

QueueCure – AI Powered Hospital Queue Management System

Hospitals often struggle with long waiting queues, manual token handling, and lack of real-time communication between patients and staff. Patients are uncertain about their queue position and waiting time, while receptionists spend significant effort managing appointments and consultations manually. QueueCure was developed to digitize hospital queue management through real-time tracking, appointment booking, token generation, and role-based dashboards, improving operational efficiency and enhancing the patient experience. Process The project started by analyzing common hospital queue management challenges and identifying key user roles: Patient, Receptionist, Doctor, and Admin. A role-based system architecture was designed to provide dedicated dashboards for each user. React.js was used for the frontend, Node.js and Express.js for backend services, and MongoDB for data storage. Socket.IO was integrated to enable real-time queue updates without page refreshes. JWT authentication secured user access, while Nodemailer handled password recovery. Additional features such as appointment booking, QR token generation, analytics dashboards, and live queue monitoring were implemented and tested to ensure a smooth user experience. Results QueueCure provides a centralized platform for managing hospital queues and appointments efficiently. The system enables real-time queue tracking, appointment scheduling, QR-based token generation, and live updates using Socket.IO. Role-based dashboards for Patients, Doctors, Receptionists, and Admins improve workflow management and communication. Additional features include secure JWT authentication, email-based password recovery, and analytics monitoring. The project demonstrates how digital queue management can reduce manual effort, improve operational efficiency. Reflection Given more time, I would extend QueueCure with AI-powered waiting time prediction based on historical consultation data and patient volume. I would also add SMS and WhatsApp notifications, doctor availability forecasting, multi-hospital support, and advanced analytics for operational insights. Future improvements would include mobile app support, multilingual interfaces, and cloud deployment with automated scaling to support larger healthcare organizations.