Heal Kathon Web
A real-time patient monitoring and fall-risk detection system that helps healthcare staff monitor patients and receive instant alerts. Demo Account: admin@admin.com | Password: 123456
Screenshots
A visual tour of the application
Features
Key features and functionalities
Real-time patient monitoring dashboard
Fall-risk detection using ESP32-C3 sensor devices
Live updates via Socket.IO WebSocket connections
Patient management with PostgreSQL and Prisma
Dockerized deployment for easy scalability
Architecture
System architecture and design
Challenge
The main problem I solved
Developing a reliable real-time monitoring system capable of processing sensor data from multiple patients simultaneously while delivering low-latency alerts to healthcare staff.
Solution
How I addressed the challenge
Built a full-stack application with Next.js, Socket.IO, Prisma, and PostgreSQL to enable real-time communication between IoT devices and the dashboard. ESP32-C3 devices collect patient movement data, which is analyzed to identify fall-risk events and instantly notify medical staff. Docker was used to simplify deployment and improve scalability.
Lessons Learned
Key takeaways from this project
Strengthened my skills in real-time web applications, WebSocket communication, IoT integration, database design with Prisma, Docker deployment, and building scalable healthcare systems.