Time Series Analysis of Air Pollutants(PM2.5) using LSTM model

Welcome to quote our published papers, and the codes have been uploaded.

The present project aims to predict air pollution in Beijing, China, using the data set "Beijing Multi-Site Air-Quality Data Data Set"

In this project work, the main motive is to build a deep learning model to detect air pollution from real-time images. In order to achieve that goal, we have collected data from different sources and then enhanced the low-quality images using the Image enhancement technique. Our next step was to train a CNN (Convolutional Neural Network) on the …

Time series analysis to predict AQI in Delhi, dataset collated from Indian Meteorological department of India.

Air pollution prediction using linear regression

Routeco - Your Route Comrade

This problem statement focused on building machine learning models that would assist create city-level air pollution susceptibility maps with a 5-meter spatial resolution for milan city in Italy. This city has unique challenges of dealing with pollution levels due to its unique topographic features.

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.

End-to-end Machine Learning project classifying air pollution levels (High/Low) in China. Compares performance of SVM, Logistic Regression, and Decision Trees, deployed with an interactive Streamlit dashboard.

Air Quality Analysis and Prediction System