Digital Twin System

This project is a digital twin system that integrates various components for simulation, data integration, and machine learning. It is built using FastAPI for the backend and a frontend dashboard.

Project Structure

backend/
	.env
	api/
		rest/
		v1/
	auth/
		jwt.py
	core/
		auth.py
		config.py
	data_integration/
		collectors/
		pipeline/
		storage/
	db/
		crud.py
		database.py
		init_db.py
	Dockerfile

	main.py

	middleware/

	compliance.py

	ml/
		pipeline.py
	modeling/
		physiological/
	models/
	schemas/
	security/
	simulation/
digital-twin-system/
	backend/
	frontend/

docker-compose.yml

frontend/
	.env
	dashboard/
	package.json
	src/

report.md

requirements.txt

venv/
	bin/
	include/
	lib/
	lib64
	pyvenv.cfg

Backend

The backend is built using FastAPI and includes various modules for handling authentication, data integration, machine learning, and simulation.

Key Components

• Authentication: JWT-based authentication is implemented in jwt.py and auth.py.
• Data Integration: Collects and processes data from various sources. Key files include:
  • collectors
  • pipeline
  • storage
• Machine Learning: Handles ML model pipelines in pipeline.py.
• Modeling: Physiological models are implemented in physiological.
• Simulation: Simulation engine and endpoints are in simulation.
• Middleware: Compliance middleware for security headers and logging in compliance.py.

API Endpoints

• Simulation: Run simulations for patients.

  • simulation.py

• Data Integration: Collect and retrieve patient data.

  • data_integration.py

Configuration

Configuration settings are managed in config.py.

Database

Database initialization and CRUD operations are handled in:

• init_db.py
• crud.py
• database.py

Running the Backend

To run the backend, use Docker:

docker-compose up --build

Alternatively, you can run it locally:

cd backend
pip install -r requirements.txt
uvicorn main:app --host 0.0.0.0 --port 8000 --reload

Frontend

The frontend is a dashboard built with modern web technologies.

Running the Frontend

To run the frontend, navigate to the frontend directory and use npm:

cd frontend
npm install
npm start

Virtual Environment

Activate the virtual environment using the provided script:

source venv/bin/activate

For PowerShell:

.\venv\bin\Activate.ps1

Health Check

Check the health of the backend service:

curl http://localhost:8000/health

License

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

Contributing

Contributions are welcome! Please see the CONTRIBUTING file for more information.

Contact

For any inquiries, please contact the project maintainers.

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This README provides an overview of the project structure, key components, and instructions for running the backend and frontend services.