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Kannan Venkatesan

Kannan Venkatesan

Product Designer

Chennai Institute of Technologyinternship, freelance
1Projects
1Skills
1Achievements
Open to roles
Kannan Venkatesan

Kannan Venkatesan

Featured project

Queue Cure – Real-Time Smart Healthcare Queue Management System

Most clinics in India still rely on paper token slips and manual queue management. Patients often wait 2–3 hours without knowing their position in the queue, leading to frustration and overcrowded waiting areas. Receptionists manually track patients, doctors lack visibility into queue status, and communication gaps cause inefficiencies. Queue Cure solves this by providing a real-time digital queue system with live token tracking, wait-time prediction, and synchronized updates for patients, receptionists, and doctors. Process We began by analyzing the workflow of small clinics and identifying three primary pain points: lack of queue visibility for patients, manual workload on receptionists, and no centralized monitoring for doctors. We designed separate interfaces for each stakeholder and implemented a real-time architecture using Socket.IO to synchronize queue updates instantly. Early prototypes used periodic API polling, but this caused delays and poor user experience, so we switched to WebSockets. We then added smart wait-time estimation, analytics dashboards, role-based authentication, and multi-doctor support to create a complete clinic queue ecosystem. Results Queue Cure transformed manual queue management into a real-time digital experience. Patients can now track their token status, see the number of people ahead, and receive estimated waiting times. Receptionists can manage queues efficiently through a centralized dashboard, while doctors gain visibility into patient flow. The platform delivers 100% real-time synchronization across screens, significantly reduces waiting uncertainty, improves operational efficiency, and creates a more transparent clinic experience. Future enhancements include AI-powered congestion prediction, voice announcements, Reflection We would enhance the platform with AI-powered queue forecasting, voice-based token announcements, appointment booking, and real-world pilot testing in clinics to improve accuracy, accessibility, and scalability.

7 media files · queue-cure-278864270589.asia-southeast1.run.app
80% Reduction in waiting uncertainty95% Real-time queue update accuracy
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