Track: Research Track |
| Secure platform for remote medical learning using WebRTC and facial recognition authentication |
| This article introduces an innovative distance medical learning platform designed to address the challenges of medical training in poorly equipped regions. Using WebRTC technology, this solution gives final-year medical students access to advanced teaching resources, such as real-time observation of surgical operations. Security is ensured by a dual authentication system, combining AI-based facial recognition (utilizing DeepFace) with traditional password identification. The architecture incorporates WebRTC, Socket.io, and the Internet of Things (IoT) to facilitate real-time communication and the dissemination of medical content. Uvicorn/Gunicorn servers are used to ensure a robust and scalable infrastructure. The platform aims to overcome geographical barriers and provide practical and interactive learning opportunities while guaranteeing the confidentiality of sensitive medical data. This approach represents a significant advancement in democratizing access to quality medical education, opening new perspectives for medical education in the digital age. |
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| Presentation Video |
| Presentation Notes |
| WebRTC_ZABOLO.pptx |
Real Time Communications Conference & Expo at Illinois Tech
IEEE International Conference
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