An interactive R Shiny dashboard that visualizes air quality trends and provides short-term forecasts (PM2.5, PM10, NO₂) for urban locations using time-series data.
📌 Project Overview
This project aims to:
Analyze air pollution data from global cities
Visualize key pollutants and weather conditions over time
Forecast short-term air quality using time-series models
Provide an intuitive, interactive interface for exploration and insights
✅ Interactive dashboard (Shiny) ✅ Daily trends of PM2.5, PM10, and NO₂ ✅ Location-wise filtering ✅ 7-day forecast using ARIMA models ✅ Clean, responsive UI with dynamic charts
🧰 Tools & Technologies
Language: R
Libraries:
shiny, forecast, ggplot2, dplyr, lubridate, plotly, readr
Visualization: ggplot2, plotly
Time Series Modeling: forecast::auto.arima()
🗃️ Dataset
The dataset includes:
Air pollutant levels: PM2.5, PM10, NO₂
Weather indicators: temperature, wind, humidity, UV index
Date and location metadata
📁 Sample data included: sample_air_quality_data.csv
🚀 How to Run Install required libraries
install.packages(c("shiny", "ggplot2", "dplyr", "lubridate", "forecast", "readr", "plotly"))
Run the app
shiny::runApp('path_to_your_project_folder')
📊 Sample Screenshot
Add hourly forecasts and AQI calculation
Integrate map-based pollutant visualization
Enable historical comparisons and downloadable reports