Queue Cure AI Platform

Problem: Patients in clinics often wait for 45–90 minutes without knowing when their turn will arrive. Traditional token systems only announce numbers and provide no visibility into queue progress. This leads to uncertainty, frustration, and overcrowded waiting areas. User Pain: Patients repeatedly ask for updates, waste time waiting unnecessarily, and risk missing their turn if they leave the waiting area. Business Need: Clinics need a better way to manage patient flow, reduce receptionist workload, minimize crowding, and improve patient satisfaction through transparent queue management. Process Researched queue management practices in small and medium-sized clinics. Identified the main problem: patients have no visibility into queue progress or expected waiting time. Analyzed the workflow of patients, receptionists, and doctors to understand pain points. Defined three objectives: transparency, reduced waiting uncertainty, and improved operational efficiency. Explored a basic token display system but found it insufficient as it only showed token numbers. Tested a manual refresh approach, which resulted in delayed and outdated information. Decided to implement real-time synchronization to provide instant queue updates. Designed and iterated multiple UI layouts to ensure queue information was clear and easy to understand. Results Tested the system with sample clinic queues and verified that token updates were reflected instantly across all screens. Reduced the need for patients to repeatedly ask receptionists about their turn. Improved queue visibility by showing the current token, patients ahead, and estimated waiting time. Made the process easier to understand and follow for both patients and staff. Feedback indicated that users found the system simple, clear, and helpful. If given more time, we would add appointment booking, SMS/WhatsApp notifications, multilingual support, and detailed analytics to further improve Reflection The current version focuses on core queue management features and real-time updates, but it does not yet support online appointment booking. Estimated waiting times are calculated using average consultation duration and may not always reflect unexpected delays. The system currently targets a single clinic workflow; future versions could support multiple doctors and departments. We would improve accessibility by adding support for multiple languages and voice-based announcements. Notifications are currently limited and could be enhanced through SMS or WhatsApp alerts. More extensive testing wit