{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/132feef0699943d2820907ca9412747d\" frameborder=\"0\" width=\"1920\" height=\"1440\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1440,"width":1920,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1440,"thumbnail_width":1920,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/132feef0699943d2820907ca9412747d-6d371ffc140076a6.gif","duration":305.167,"title":"AI Real Time Hospital Queue Management Demo","description":"This Loom demonstrates QQ26, an AI-powered real-time hospital queue management system. The speaker explains how the web app helps receptionists generate and track tokens, while patients see their live token status and estimated waiting times without asking staff. During the demo, the receptionist advances from token 10 to token 13, calls the next patient, sets an average consultancy time of 10 minutes, and shows today’s analysis: 5 patients, 2 completed, average waiting time 15 minutes, and efficiency 40%. The AI wait-time prediction is shown for token 13 as 10 minutes, using FastAPI, Scikit-learn, and WebSocket-based real-time updates with a MySQL database."}