About Home assistant component to get air quality for french cities

A monitoring station for air quality based on Raspberry Pi

Get the pollution in real-time and decide if you will move on

Command-line application providing some information about air quality in Poland. Tested using Mockito and JUnit

Perceive the noise pollution that surrounds you in a smart way

Analysis and data of beach-litter-surveys in Switzerland 2015-2021. Notebooks and maps for documenting and producing basic analysis of survey results.

A near real time Air Quality Indicator for India, made with :heart:

Viz project about pollution and cruise ships in Barcelona city before and after Covid-19.

Air pollution data scraping and analysis for Krakow, Poland

Weather, Air pollution and ferrys map of Manhattan, NYC

This is a COVID-19 Air Pollution tracking program that looks at the correlation between COVID-19 Lockdowns and the overall pollution impact in certain European cities. The program utilses graphs and other visual stats to allow visual representations of significant or minimal difference in pollution levels with as a result to the on going pandemic.

“Project Polusi Kalimantan” is focused on analyzing and visualizing air pollution data, specifically PM2.5 levels, across various regions in Kalimantan, Indonesia. This project combines data analytics, machine learning, and interactive web technologies to provide detailed insights into air quality trends

This project uses machine learning to predict air pollution levels in Sarajevo based on historical air quality data.

💨A real-time worldwide pollution tracker built in ReactJS and JavaScript, using geolocation, Google Maps API and AirVisual API. This was the final project built for my General Assembly course.

Aim of this project is analyse dataset of pollution and answer some of the questions.

Impact of Air Pollution on our Lives during pre and post covid19.

A Time-series analytics dashboard built to visualise data associated with socio-economic indicators

Air monitoring browser extension for monitoring CO2, 03, NO2 and PM2.5. Get real time updates for air qualities in other cities.

The firmware of PM Control Unit, a device that measures weather conditions.

Works on Air Quality Indication Dataset collected by airQ to give deeper insight, written with :heart: using Python

Analyzing air pollution data from Skopje over five years (01.2012 - 12.2016) to identify the largest pollutant, most polluted neighborhoods, average pollution levels across locations using Air Quality Index (AQI), and examining PM10 pollution trends over the years.

A Power BI dashboard analyzing global air quality using AQI data. It visualizes pollutant levels (PM2.5, NO₂, Ozone, CO) through interactive maps and charts, identifying pollution trends and health risks. The project aims to raise awareness and support efforts for cleaner air.

A project to examine air quality trends in Salt Lake City, Utah.

Platform is an Arduino based tool to acquire, geolocate and save pollutants concentrations in a sd card.

Assignment for the course "Applied Plotting, Charting & Data Representation in Python"

API for Complex Event Processing using Spring Boot, Esper & a Mosquitto MQTT Broker

No description provided.

This project is one of academic projects given to us in Geographic Information System (GIS) Course. Created by: Pranav Pandya (Me) and Kartikey Hadiya We sampled information for pollution emmision in Delhi, India. Pollution data was obtained from: https://data.gov.in/resources/real-time-air-quality-index-various-locations Pollution index data can be obtained from: https://cpcb.nic.in/RealTimeAirQualityData.php Pollution data only had address of Indian Meteorological Department, so each station was located in Google Earth and pin points were added at each station. Then in the side bar containing those pins on right-click, a new folder was added and all the pins were added in that new folder in google earth. Then that folder was saved as kml file. This kml file was uploaded to Mygeodata: https://mygeodata.cloud/converter/kml-to-csv and was converted into csv. Then the csv file was opened and coordinates were copied in pollution data file. That file was later saved as csv and imported in ArcGIS and xy data was displayed. Shapefile was obtained from web search, which is attached as well. That shapefile was imported in ArcGIS and the final view was generated which is shown in the picture.

PPT displays levels [relative to ALL oceans] of bottle pollution in Earth's major oceans. Instances received from ArcGIS api.

IOT based Carbon monoxide measuring device