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https://github.com/deaneeth/aqi-monitoring-system

Real-time air quality monitoring system with interactive maps, role-based access control, and automated AQI data simulation. Built with Laravel, MySQL, and Leaflet.js.
https://github.com/deaneeth/aqi-monitoring-system

air-quality alerts-system data-visualization fullstack geospatial interactive-maps laravel leaflet mysql php phpunit simulation web-application

Last synced: 12 days ago
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Real-time air quality monitoring system with interactive maps, role-based access control, and automated AQI data simulation. Built with Laravel, MySQL, and Leaflet.js.

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README 

        
# 💨 Air Quality Monitoring Dashboard



A comprehensive web-based platform for monitoring air quality data in the Colombo Metropolitan Area. This system provides real-time Air Quality Index (AQI) visualization through interactive maps and role-based access control for different user types.



![Public Map Page with Sensors](assets/Public_map_page_with_sensors.png)



## 🌟 Features



### Core Functionality

- **Real-time AQI Monitoring**: Live air quality data visualization with automatic updates every 5 minutes

- **Interactive Map Interface**: Leaflet.js-powered map with color-coded markers representing AQI levels

- **Data Simulation Engine**: Automated AQI data generation with realistic patterns including random fluctuations, sine wave patterns, and peak-hour variations

- **Alert System**: Automatic notifications when AQI levels exceed unhealthy thresholds (>200)

- **CSV Data Import**: Bulk sensor data upload functionality



### User Management & Security

- **Role-Based Access Control**: Three distinct user roles with appropriate permissions

  - **Public Users**: Read-only access to public map

  - **Monitoring Admins**: Sensor management and AQI data monitoring

  - **System Admins**: Full system access including user management and diagnostics

- **Secure Authentication**: Laravel-based authentication with middleware protection

- **Session Management**: Secure session handling with CSRF protection



### Administrative Features

- **Sensor Management**: Create, edit, and deactivate air quality sensors

- **User Management**: Admin panel for user account creation and management

- **System Diagnostics**: Comprehensive system information dashboard

- **Alert Configuration**: Customizable AQI threshold settings



## 🛠 Tech Stack



### Backend

- **Framework**: Laravel (PHP)

- **Database**: MySQL

- **Testing**: PHPUnit for unit and integration testing

- **API**: RESTful API endpoints with JSON responses



### Frontend

- **Mapping**: Leaflet.js for interactive map visualization

- **UI/UX**: Responsive design with Bootstrap

- **Real-time Updates**: AJAX-based data fetching

- **Charts**: Historical AQI data visualization



### Development Tools

- **Version Control**: Git

- **API Testing**: Postman

- **Database Management**: phpMyAdmin

- **Code Editor**: VS Code



## 📋 Prerequisites



- PHP >= 7.4

- Composer

- MySQL >= 5.7

- Node.js & NPM

- Web server (Apache/Nginx)



## 🚀 Installation



1. **Clone the repository**

   ```bash

   git clone https://github.com/deaneeth/aqi-monitoring-system

   cd aqi-monitoring-system

   ```



2. **Install PHP dependencies**

   ```bash

   composer install

   ```



3. **Install JavaScript dependencies**

   ```bash

   npm install

   ```



4. **Environment configuration**

   ```bash

   cp .env.example .env

   php artisan key:generate

   ```



5. **Configure database**

   - Update `.env` file with your database credentials

   ```

   DB_CONNECTION=mysql

   DB_HOST=127.0.0.1

   DB_PORT=3306

   DB_DATABASE=aqi_monitoring

   DB_USERNAME=your_username

   DB_PASSWORD=your_password

   ```



6. **Run database migrations**

   ```bash

   php artisan migrate

   ```



7. **Seed the database (optional)**

   ```bash

   php artisan db:seed

   ```



8. **Build frontend assets**

   ```bash

   npm run dev

   ```



9. **Start the development server**

   ```bash

   php artisan serve

   ```



## 🧪 Testing



### Testing Coverage

![Unit Tests](assets/Unit_Test.png)

*Comprehensive PHPUnit testing suite ensuring code quality and reliability*



### Unit Tests

Run individual component tests:

```bash

php artisan test --testsuite=Unit

```



### Integration Tests

Test API endpoints and database interactions:

```bash

php artisan test --testsuite=Feature

```



### Manual Testing

- Use Postman collection for API endpoint testing

- Browser developer tools for frontend validation

- Cross-browser testing (Chrome, Firefox)



## 📊 Database Schema



### Main Tables

- **sensors**: Sensor location and configuration data

- **sensor_data**: Historical AQI measurements

- **users**: User accounts and role assignments

- **alerts**: System-generated alerts for threshold violations



## 🎯 Usage



### For Public Users

1. Navigate to the public map interface

2. View real-time AQI data through color-coded markers

3. Click markers to see detailed AQI information and historical charts



### For Monitoring Admins

1. Log in through the admin panel

2. Manage sensors (create, edit, deactivate)

3. Monitor real-time AQI data and alerts

4. Configure alert thresholds

5. Upload CSV data for bulk sensor management



### For System Admins

1. Access full system diagnostics

2. Manage user accounts and permissions

3. View system configuration and health metrics

4. Monitor application performance



## 🚨 AQI Alert System



The system automatically generates alerts based on standard AQI categories:

- **Good (0-50)**: Green markers

- **Moderate (51-100)**: Yellow markers

- **Unhealthy for Sensitive Groups (101-150)**: Orange markers

- **Unhealthy (151-200)**: Red markers

- **Very Unhealthy (201-300)**: Purple markers

- **Hazardous (301+)**: Maroon markers



Alerts are triggered when AQI levels exceed 200 (Unhealthy threshold).



## 🔧 Configuration



### AQI Simulation

Configure simulation parameters in the admin dashboard:

- Data generation intervals (default: 5 minutes)

- AQI value ranges and patterns

- Peak hour variations



### Alert Thresholds

Customize alert triggers through the configuration panel:

- Set custom AQI thresholds

- Configure notification preferences

- Manage alert recipients



## 📱 Responsive Design



The application is fully responsive and tested across:

- Desktop browsers (Chrome, Firefox, Safari)

- Tablet devices

- Mobile phones



## 🎓 Academic Context



This project was developed as part of the Software Development Tools and Practices module, demonstrating practical application of:

- Full-stack web development

- Real-time data simulation

- Geographic information systems

- Software testing methodologies

- Version control and collaborative development



## 📸 Screenshots



### Public Map Interface

![Public Map](assets/Public_map_page_with_sensors.png)

*Interactive map showing real-time AQI data with color-coded markers for different pollution levels*



### Admin Dashboard

![Admin Dashboard](assets/Admin_Dashboard.png)

*Comprehensive admin interface with system overview, alerts, and quick access to management tools*



### Sensor Management

![Sensor Management](assets/Sensor_Management_Page.png)

*Intuitive interface for managing air quality sensors, including location data and status monitoring*



### System Administration

![System Admin Dashboard](assets/System_Admin_Dashboard.png)

*Advanced system diagnostics and configuration panel for system administrators*



> 📋 **View all screenshots and detailed interface documentation in [SCREENSHOTS.md](SCREENSHOTS.md)**



## 🤝 Contributing



1. Fork the repository

2. Create a feature branch (`git checkout -b feature/amazing-feature`)

3. Commit your changes (`git commit -m 'Add amazing feature'`)

4. Push to the branch (`git push origin feature/amazing-feature`)

5. Open a Pull Request



## 📝 License



This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.



## 📞 Support



For questions or support, please open an issue on GitHub or contact the repository maintainer.



---



**Note**: This system uses simulated data for demonstration purposes. For production deployment with real sensor data, additional configuration and hardware integration would be required.