๐ฑ Air Quality Dashboard - Real Data for a Sustainable Future
Advanced air quality monitoring using real environmental data to support sustainability and environmental science

๐ Live Demo
๐ Main Dashboard: https://civcell.github.io/air-quality-dashboard/
๐ค Advanced Features: https://civcell.github.io/air-quality-dashboard/ml_showcase.html
๐ About This Project
Iโm passionate about sustainability and environmental science. This dashboard uses real air quality data that I collect from environmental monitoring stations, government APIs, and weather services around the world. Itโs not fake data - itโs actual pollution measurements that help us understand our environment better!
โป๏ธ Why Air Quality Matters for Sustainability
- ๐ฑ Health Impact: Clean air means healthier communities
- ๐ Climate Connection: Pollution affects global warming
- ๐ญ Industry Monitoring: Track pollution from factories and transportation
- ๐ณ Green Solutions: Measure how parks and trees clean the air
- ๐ Policy Making: Data helps create better environmental laws
๐ Real Data Sources
๐ Where the Data Comes From
- EPA AirNow: Official US air quality data
- World Air Quality Index: Global pollution monitoring
- OpenWeatherMap: Weather and atmospheric conditions
- Local Environmental Agencies: City and state monitoring stations
- Government APIs: Real-time environmental data feeds
๐ Data Collection Process
- Automated Scraping: Collect data every hour from multiple sources
- Data Validation: Check for accuracy and consistency
- Real-time Updates: Keep information current and relevant
- Quality Control: Ensure reliable measurements
๐ง Smart Analysis Features
๐ฎ Predictive Analytics
- AI Forecasting: Predict air quality for the next 24 hours
- Weather Integration: Understand how weather affects pollution
- Pattern Recognition: Identify pollution trends and cycles
- Smart Alerts: Warn about bad air quality before it happens
๐จ Anomaly Detection
- Automatic Monitoring: Find unusual pollution patterns
- Early Warning System: Detect problems before they become dangerous
- Source Identification: Help locate pollution sources
- Real-time Alerts: Immediate notifications of air quality issues
๐ฏ Data Insights
- Factor Analysis: Understand what causes bad air quality
- Geographic Patterns: See where pollution is worst
- Temporal Trends: Track changes over time
- Correlation Studies: Find connections between different factors
Backend & Data Processing
- Python 3.8+: Core programming language
- Web Scraping: Collect real-time environmental data
- Data APIs: Connect to government and environmental services
- Database Management: Store and organize large datasets
Smart Analysis (AI/ML)
- Scikit-learn: Machine learning algorithms
- Random Forest: Best performing prediction model
- Anomaly Detection: Find unusual patterns automatically
- Feature Engineering: Understand what drives air quality
Visualization & Web Interface
- Interactive Charts: Plotly.js for dynamic graphs
- Interactive Maps: Leaflet.js for geographic data
- Responsive Design: Works on all devices
- Real-time Updates: Live data visualization
๐ Project Structure
air-quality-dashboard/
โโโ ๐ static_dashboard.html # Main dashboard (GitHub Pages)
โโโ ๐ค ml_showcase.html # Advanced AI features
โโโ ๐ ml_enhanced_dashboard.py # Full Python dashboard
โโโ ๐ requirements_ml.txt # Python dependencies
โโโ ๐ launch_dashboard.py # Quick launch script
โโโ ๐ README.md # Project documentation
โโโ ๐ DEPLOYMENT.md # How to deploy
๐ Quick Start
1. View Online (Easiest)
Simply visit: https://civcell.github.io/air-quality-dashboard/
2. Run Locally (For Developers)
# Clone the project
git clone https://github.com/civcell/air-quality-dashboard.git
cd air-quality-dashboard
# Setup Python environment
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
pip install -r requirements_ml.txt
# Run the dashboard
python ml_enhanced_dashboard.py
๐ What Youโll See
๐ก๏ธ Real-time Monitoring
- Live air quality data from actual monitoring stations
- Weather conditions that affect pollution levels
- Pollution metrics (PM2.5, PM10, CO, NO2, O3, SO2)
- Hourly updates throughout the day
๐บ๏ธ Geographic Visualization
- Interactive maps showing pollution across cities
- Location-based analysis for different areas
- Station monitoring with real-time data
- Spatial patterns in air quality
๐ Smart Analysis
- AI predictions for future air quality
- Pattern detection in pollution data
- Correlation analysis between factors
- Trend identification over time
๐ฑ Sustainability Applications
๐ฅ Public Health
- Health Alerts: Warn people about bad air quality
- Activity Planning: Help plan outdoor activities on clean air days
- Medical Research: Support studies on air quality and health
- Community Awareness: Educate people about environmental health
๐ญ Environmental Monitoring
- Industrial Compliance: Track factory emissions
- Transportation Impact: Measure how cars affect air quality
- Green Infrastructure: Evaluate the effectiveness of parks and trees
- Policy Support: Provide data for environmental regulations
๐ Urban Planning
- Smart City Development: Plan cities with better air quality
- Green Space Planning: Design parks and gardens strategically
- Traffic Management: Optimize routes to reduce pollution
- Building Placement: Choose healthy locations for schools and hospitals
๐ Climate Research
- Pollution Patterns: Understand how pollution affects climate
- Seasonal Analysis: Study how seasons impact air quality
- Global Trends: Track environmental changes worldwide
- Sustainability Metrics: Measure progress toward environmental goals
๐ฏ Who This Helps
๐ฅ General Public
- Daily Planning: Check air quality before going outside
- Health Awareness: Understand environmental health risks
- Education: Learn about air quality and sustainability
- Community Engagement: Get involved in environmental issues
๐๏ธ Policy Makers
- Data-Driven Decisions: Use real data for environmental policies
- Regulation Development: Create better environmental laws
- Resource Allocation: Invest in areas that need improvement
- Progress Tracking: Monitor environmental improvement over time
๐ฌ Researchers
- Environmental Studies: Access real-time air quality data
- Climate Research: Study pollution and climate connections
- Health Research: Investigate air quality and health relationships
- Technology Development: Test new environmental monitoring tools
๐ข Businesses
- Environmental Compliance: Monitor pollution levels
- Sustainability Reporting: Track environmental impact
- Risk Management: Identify environmental risks
- Green Marketing: Demonstrate environmental commitment
๐ My Sustainability Goals
๐ Environmental Awareness
- Make air quality data accessible to everyone
- Help people understand their environmental impact
- Support community environmental initiatives
- Promote sustainable living practices
๐ฌ Scientific Research
- Use real data to understand pollution patterns
- Support environmental science research
- Develop better environmental monitoring tools
- Contribute to climate change understanding
โป๏ธ Sustainable Solutions
- Help communities make better environmental decisions
- Support green technology development
- Promote renewable energy and clean transportation
- Encourage sustainable urban planning
๐ฑ Green Technology
- Develop tools that support sustainability
- Create accessible environmental monitoring
- Support clean energy initiatives
- Promote environmental education
๐ Learning Resources
๐ฑ Sustainability & Environment
๐ฌ Air Quality Science
๐ป Technology & Data
๐ค Contributing
I welcome contributions from anyone interested in sustainability and environmental science!
How You Can Help
- Report Issues: Find bugs or suggest improvements
- Add Data Sources: Help collect more environmental data
- Improve Visualizations: Make the dashboard more user-friendly
- Documentation: Help explain complex concepts simply
- Sustainability Ideas: Suggest new environmental features
Getting Started
- Fork the repository
- Create a feature branch (
git checkout -b feature/amazing-feature
)
- Make your changes and test them
- Commit with a clear message (
git commit -m 'Add amazing feature'
)
- Push to your branch (
git push origin feature/amazing-feature
)
- Open a Pull Request
๐ License
This project is open source and available under the MIT License - see the LICENSE file for details.
๐ Acknowledgments
- Environmental Agencies: EPA, WHO, and local monitoring stations
- Open Source Community: Python, Scikit-learn, Plotly, and Bootstrap
- Data Providers: AirNow, World Air Quality Index, OpenWeatherMap
- Sustainability Advocates: Everyone working toward a greener future
๐ Show Your Support
If this project helps you understand air quality and sustainability better, please give it a โญ๏ธ star on GitHub!
๐ Sustainability Commitment
This project is built with sustainability in mind:
- โป๏ธ Real Data: Uses actual environmental measurements
- ๐ฑ Green Focus: Designed to support environmental goals
- ๐ฌ Scientific Approach: Based on real environmental science
- ๐ Global Impact: Helps communities worldwide
**Built with โค๏ธ by civcell |
๐ฑ Committed to Sustainability |
๐ Real Data for a Better Future** |