SmartCare - AI-Powered Smart Wound Dressing Monitoring System

SmartCare is an innovative healthcare monitoring system that combines AI technology with smart wound dressings to provide real-time patient monitoring and analysis. The system helps healthcare providers track wound healing progress, detect potential infections, predict healing times, and receive AI-powered recommendations for patient care.

Features

• Real-time Monitoring: Track wound dressing sensor data in real-time
• AI Analysis:
  • Infection detection
  • Healing time prediction
  • Patient status analysis
• GenAI Integration: Provides intelligent recommendations and suggestions
• Patient Management: Add and manage patient records
• Secure Authentication: JWT-based secure authentication system

Technology Stack

Frontend

• Vue.js 3 with TypeScript
• Pinia for state management
• Tailwind CSS for styling
• Vue Router for navigation
• Chart.js for data visualization
• Vite as build tool

Backend

• Python with Flask framework
• JWT for authentication
• MongoDB for database
• Scikit-Learn for machine learning models
• Google's Gemini API for AI features

Prerequisites

• Node.js (v16 or higher)
• Python 3.8 or higher
• MongoDB
• Google Cloud account (for Gemini API)

Installation

Backend Setup

1. Navigate to the server directory:

cd server

2. Create and activate a virtual environment:

python -m venv venv  # On Mac: python3 -m venv venv
venv/bin/activate  # On Mac: source venv\Scripts\activate

3. Install dependencies:

pip install -r requirements.txt  # On Mac: pip3 install -r requirements.txt

4. Create a .env file in the server directory with the following variables:

DB_NAME = "smartcare"
MONGO_URI = "mongodb+srv://<username>:<password>@<cluster>.mongodb.net"
SECRET_KEY = "<some_secret_value>"
GENAI_API_KEY = "<your_api_key>"
PORT = 5000

Frontend Setup

1. Navigate to the client directory:

cd client

2. Install dependencies:

npm install

3. Create a .env file in the client directory with the following variables:

VITE_API_URL = "http://localhost:5000"

Running the Application

Backend

1. Activate the virtual environment (if not already activated):

cd server
venv/bin/activate  # On Mac: source venv\Scripts\activate

2. Start the Flask server:

python app.py # On Mac: python3 app.py

The backend server will run on http://localhost:5000

Frontend

1. In a new terminal, navigate to the client directory:

cd client

2. Start the development server:

npm run dev

The frontend application will be available at http://localhost:5173

Building for Production

Frontend

1. Build the frontend application:

cd client
npm run build

The built files will be in the dist directory.

Backend

The backend is ready for production deployment. Make sure to:

1. Set appropriate environment variables
2. Use a production-grade WSGI server (e.g., Gunicorn)
3. Configure proper security measures

Deployment

Frontend Deployment

• Build the frontend using npm run build
• Deploy the contents of the dist directory to your web server or cloud platform (e.g., Netlify, Vercel, or AWS S3)
• Set up environment variables in your deployment platform

Backend Deployment

• Deploy the Flask application to a cloud platform (e.g., Render.com, Heroku, AWS, or Google Cloud)
• Set up environment variables in your deployment platform
• Configure MongoDB connection
• Set up proper CORS settings for production

Contributing

1. Fork the repository
2. Create a feature branch
3. Commit your changes
4. Push to the branch
5. Create a Pull Request

License

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

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Made with ❤️ by Mohamed Bakour