[NLP] Analysis of reviews from mobile apps related to air quality

Python application to get Air Quality Index of your nearest city

Made with Flutter ❤️

Air Quality Index project for Proximity Labs

🛺 😷 A visual and statistical exploration of several years of air quality data for Dhaka, Bangladesh.

Mono-repo to Maintain Source Codes of SEM VI IoT Project

A program that sends emails when the AQI has passed a configurable threshold. Compatible with an sds011 air quality sensor on a raspberry pi.

This project predicts the Air Quality Index (AQI) using machine learning techniques. By analyzing historical air quality data and relevant environmental factors, it provides accurate forecasts to help raise awareness and promote healthier living conditions in urban areas.

Custom Air Quality Index Calculator

Django + React application to forecast Air Quality Index (AQI) using a Long Short-Term Memory (LSTM) neural network

Delhi Air Quality Index calculation, EDA and Regression models

esphome board to interface with a few air quality (PM) sensors

A relation between Air Quality Index & Healthcare Ranking of 52 states in USA to determine which state is good for living

Air quality checking app for getting the air quality by entering the city

This repo consist of predicting Air quality values like relative humidity, absolute humidity or any other features I have used forecasting method to analyze and predict

An app that looks up weather data from OpenWeatherMap.org's API. Users have the ability to view current data of weather, air quality, temperature, and humidity.

This project aims to design and develop a user-friendly website that provides real-time Air Quality Index (AQI) data, forecasts, and alerts to help individuals, communities, and organizations make informed decisions about their health and environmental sustainability. Project Includes Source Code, PPT, Synopsis, Report, Documents, Base Research pap

This project analyzes air quality trends in Kathmandu, Nepal, using machine learning and time-series forecasting. It predicts AQI levels in real time using Random Forest and forecasts future pollution levels (24/48/72 hours) with Facebook Prophet. An interactive Streamlit dashboard allows users to visualize trends and forecast AQI

Time series forecasting project to predict hourly air pollutant concentrations for the next 48 hours using models like ARIMA and Facebook Prophet. Includes data preprocessing, feature engineering, RMSE-based model comparison, and a complete notebook with visual analysis.