air-quality-prediction

This project has applied Machine Learning and Deep Learning techniques to analyse and predict the Air Quality in Beijing.

Machine Learning model which uses closed-form solution of Locally Weighted Regression (LOWESS) Algorithm to predict the Quality of Air

PurpleAirSF: datasets for realistic air quality forecasting

This repository contains codes, datasets, results, and reports of a machine learning project on air quality prediction.

REST API for real-time air quality index (AQI) and pollutant data. Query by city name or GPS coordinates.

This project aims at forecasting the PM2.5 concentration using the other environmental factors.

Automated MLOps for Urban Air Quality is a serverless AI system forecasting PM2.5 levels for Karachi, Pakistan. It automates the entire machine learning lifecycle from hourly data ingestion to daily model retraining, predicting air quality for 24, 48, and 72 hour horizons.

Machine Learning based Air Quality Index (AQI) prediction system for Indian cities with real-time user inputs, pollutant analysis, AQI classification, and an interactive Streamlit web application.

Predicting PM10 air particles using recurrent neural networks (RNN, GRU, LSTM)

Exploring Machine Learning Models to forecast daily PM2.5 concentration using meteorological parameters in Hetauda, Nepal.

Air Quality Prediction for Smart Cities Using Multi-Layer Perceptron

Air quality prediction using Machine Learning and Bidirectional LSTM models for environmental forecasting.

ML-based system predicting Air Quality Index (AQI) using PM2.5, NO2, and CO data, with a Flask web app showing health category insights.

Multi-strategy deep ensembles for 48-hour urban PM2.5 forecasting

Indoor Air Quality Predictions and Monitoring

RAME: a residual-augmented meta-ensemble for 24-hour urban ozone forecasting