AI-powered air quality prediction system using satellite data and machine learning

Monitoring Air Pollution from Space using Satellite Observations, Ground-Based Measurements, Reanalysis Data, and AI/ML Techniques

The following repository contains simple sets of code to clean, restructure and assess data downloaded from Central Pollution Control Board Data

BioWaste AI is an AI-powered web application that classifies biomedical waste and provides CPCB-compliant disposal guidance using natural language input

VasAQ: An air quality analytics platform using NMF for source identification and Random Forest Regression for 15-day AQI forecasting. Powered by CPCB (data.gov.in) and Visual Crossing data.

Predicting Water Quality Index (WQI) and categorical classification using Deep Learning Neural Networks on CPCB India environmental monitoring data (2019-2022).

Screening-level BOD-DO compliance modelling for the Wazirabad-Okhla reach of the Yamuna in Delhi: 1D Streeter-Phelps, 2000-run Latin Hypercube Monte Carlo, CPCB Class C compliance probabilities. Built from public CPCB station data 2018-2022.

Airpy is a tool to preprocess CPCB data, validated using vizualizations