Description:

The Air Quality Monitoring & Prediction Dashboard is a web-based platform that collects real-time air quality data from IoT sensors and public APIs, then uses data analytics and machine learning models to monitor pollution levels and forecast future Air Quality Index (AQI) values.

It helps citizens, environmental agencies, and policymakers understand current pollution levels, identify sources of poor air quality, and take preventive measures before pollution peaks. The system also integrates historical AQI trends, weather conditions, and seasonal patterns to improve prediction accuracy.

Key Features:

1. Real-Time AQI Data Collection – Integrates with IoT air quality sensors and open APIs (e.g., OpenAQ, AQICN).

2. Pollutant-Level Monitoring – Tracks PM2.5, PM10, CO, NO₂, SO₂, and O₃ concentrations.

3. AQI Calculation & Visualization – Displays AQI with WHO or local government standards using color-coded alerts.

4. Predictive Analytics – Uses models like ARIMA, Prophet, or LSTM to forecast AQI for the next few hours or days.

5. Weather Data Integration – Includes temperature, wind speed, and humidity for better prediction accuracy.

6. Heatmap & Map-Based Visualization – Shows pollution levels across different city locations.

7. Historical Data Insights – Provides trend analysis over weeks, months, and years.

8. Mobile & Web Access – Responsive design for public awareness and easy accessibility.

9. Alert Notifications – Sends SMS/Email/Push alerts when AQI exceeds safe limits.

Technology Stack:

• Backend: PHP / Java / Node.js (REST APIs for handling sensor data and predictions)

• Frontend: HTML, CSS, Bootstrap, JavaScript (Leaflet.js / Google Maps API for geo-visualization, Chart.js for graphs)

• Database: MySQL / MongoDB (to store historical AQI and weather data)

• Data Science Layer: Python (pandas, NumPy, scikit-learn, TensorFlow, Prophet for forecasting)

• IoT Integration: Air quality sensors (e.g., MQ135, PMS5003) connected via Arduino or Raspberry Pi

Example Use Case:

• A city municipal body installs air quality sensors in 50 locations.

• The system collects real-time data every 5 minutes, calculates AQI, and predicts pollution peaks during rush hours.

• Citizens receive alerts to avoid outdoor activities when AQI exceeds 150 (unhealthy).

• Policymakers use the dashboard to enforce traffic control measures on high-pollution days.