CleanAir India

AI-driven AQI and weather insights with MongoDB and GCP.

Comment

Problem Analysis

  1. Climate change intensifies heatwaves, as seen in the extreme 2022 heatwave in India and Pakistan, with a significant increase in heatwave days compared to the previous year.
  2. Rising air pollution, including wildfires and stubble burning, exacerbates the air quality crisis, with 99% of the global population breathing air exceeding WHO limits.
  3. Build an AI/ML model to assist government authorities and citizens in predicting heatwave occurrences and the Air Quality Index (AQI) for Adilabad, Nizamabad, Warangal, Karimnagar, and Khammam on a monthly basis throughout 2023.

What does CleanAir India do?

  1. Dynamic Forecasting of AQI and Temperature Data: Our platform employs advanced algorithms to provide real-time and accurate predictions of the Air Quality Index (AQI) and temperature. These forecasts enable individuals and organizations to stay informed about the current and future air quality conditions, facilitating proactive measures and decision-making.
  2. Showcasing EDA, Statistical Analysis, and Visuals: We present a comprehensive collection of exploratory data analysis (EDA), statistical analysis, and visually captivating representations. These insights demonstrate the efficacy and scalability of our predictions, offering users a deeper understanding of the data patterns, trends, and potential correlations. Our goal is to empower users with valuable visualizations that enhance their knowledge and awareness of air quality dynamics.

Business Strategy

  1. We have devised a proactive approach by sending forecasted values, allowing individuals to receive advance notifications and take necessary precautions accordingly.
  2. Our comprehensive dashboard is designed to generate a multitude of key performance indicators (KPIs) and enlighten users about the statistical insights of their local areas.
  3. Upholding data integrity as a top priority, we offer premium, paid data source endpoints to access consistently reliable and meticulously maintained information. Ensuring high-quality data, we strive to empower users with accurate and dependable data sources.

Data Source - data.gov.in

We have sourced data for 5 different cities, namely:

  1. Adilabad
  2. Nizamabad
  3. Khammam
  4. Warangal
  5. Kharimanagar

Our MongoDB database AQI has the undermentioned collections: aqi_forecast_daily_collection, aqi_forecast_monthly_collection, AQI_history_daily_collection, AQI_history_monthly_collection, weather_forecast_daily_collection, weather_forecast_monthly_collection, weather_history_daily_collection, weather_history_monthly_collection

With the data that has been accumulated, we aim to find out various monthly predictions related to the weather and AQI considering these 5 cities.

Models

  1. LSTM model for predicting AQI
  2. Forecasting models for predicting Heatwaves

Usage of MongoDB and GCP

  1. MongoDB has been used to store the data we are utilising for our prediction models.
  2. Google Cloud Storage has been used and deployment of the app has been done on the Google App Engine.

Built With

Share this project:

Updates