Smart Health Monitoring Dashboard — collect, visualize, and alert on vital sign data in (near) real time.

• Real-time data ingestion of physiological metrics (heart rate, SpO₂, temperature, etc.)
• Trend charts and historical views
• Alerts / thresholds (notify when values go out of safe bounds)
• User management & authentication (if implemented)
• Configurable via environment variables
• Extensible — add new metrics, sensors, alert types

monitor-health/
├── backend/
│ ├── controllers/
│ ├── models/
│ ├── routes/
│ ├── server.js (or app.js)
│ └── package.json
├── frontend/
│ ├── src/
│ ├── public/
│ └── package.json
├── .gitignore
└── README.md

Follow these steps to get the project running locally. (Yes, I insist you read this.)

• Node.js (v14 or newer is safe)
• npm or yarn
• A running MongoDB instance (local or hosted)

1. Clone the repo

   git clone https://github.com/shaikhhabib001/monitor-health.git
   cd monitor-health
   

2. Install dependencies

   cd backend
   npm install
   cd ../frontend
   npm install

3. Set environment variables

   In backend/, create a .env file. Example contents:

   MONGO_URI=your_mongodb_connection_string
   PORT=5000
   

   Adjust names and values according to how your code reads them.

4. Run in development mode

   In one terminal:

   cd backend
   npm run dev    # or `node server.js` if dev script not present

   In another terminal:

   cd frontend
   npm start

   • Frontend usually lives at http://localhost:3000
   • Backend at http://localhost:5000 (or your chosen port)

• Create an account / log in (if authentication is included)
• Send metric data over API endpoints or via sensor integration
• View dashboard: current values, historical charts
• Receive alerts when values exceed configured thresholds

• Add new environment variables to .env
• Extend backend routes, controllers, or models
• Tweak frontend UI, chart styles, new metrics
• Add alert channels (email, SMS, push)

• Use a cloud-hosted MongoDB (Atlas, etc.)
• Deploy backend and frontend as separate services (e.g. Heroku, Vercel + Node server)
• Set environment variables accordingly in production
• Use SSL / HTTPS
• Secure your API (auth, rate limits, validation)

• Validate sensor / input data carefully
• Rate-limit or batch data ingestion
• Use logging & error tracking (Sentry, Winston, etc.)
• Back up your database
• Monitor performance as data grows

This project is licensed under the MIT License — you’re free to use, modify, share, as long as you include attribution.

• Open an issue to discuss feature ideas or bugs
• Fork the repo, make changes, submit a pull request
• Follow code style, add documentation & tests

Feel free to reach out via GitHub issues / PRs. Let’s make health data more actionable (and less opaque).