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🚑 DisasterTriageNet

DisasterTriageNet is an AI-powered emergency management system designed to optimize disaster response. It combines real-time victim health telemetry, machine learning-based triage scoring, and geospatial clustering to coordinate medical resources efficiently during mass-casualty events.


🚀 Getting Started

We've recently overhauled the project documentation! For complete instructions on setting up your development environment, initializing the database, and running the real-time simulation, please refer to our new guide:

👉 View the Professional Setup Guide


🔥 Key Features

  • 🧠 AI Triage Scoring: Predicts medical severity (Low to Critical) using a LightGBM model.
  • 📍 Geospatial Hotspots: Dynamic DBSCAN clustering of victims to identify major incident zones.
  • ⚡ Real-Time Coordination: Instant dashboard updates via Socket.io for victim ingestion and hospital bed status.
  • 📅 Incident Management: Multi-incident support to manage separate disaster episodes.
  • 🚗 ETA Estimator: Real-time calculation of ambulance arrival times to hospitals.
  • 📱 Field QR Access: Generates unique QR codes for victims for scanning by field responders.

🛠️ Tech Stack

  • Frontend: React 19, Vite, Leaflet, Recharts, Tailwind CSS, Socket.io-client.
  • Backend: Python 3.13, Flask, Flask-SocketIO, SQLite, Scikit-learn, LightGBM.
  • Communication: WebSockets (Real-time), REST API (State management).
  • Security: JWT Authentication, Bcrypt password hashing, Role-Based Access Control.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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A fully software-based intelligent disaster response system integrating mobile health inputs, AI-based severity scoring, geospatial clustering, and dynamic rescue coordination.

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