Code Repository for: "Characterization of Industrial Smoke Plumes from Remote Sensing Data", presented at Tackling Climate Change with Machine Learning workshop at NeurIPS 2020.
Zephyr is a platform which provides users with the predicted Air Quality Index levels of air pollution for 39 cities of India with daily, monthly and yearly trends. It also provides some of the statistics observed for AQI over these cities and various latest articles and blogs related to air pollution.
Used Tensorflow Object Detection API to detect different vehicles in a picture and predict pollution levels.
Command-line application providing some information about air quality in Poland. Tested using Mockito and JUnit
Research Paper on the prediction of pollutants concentration in Lille using Machine Learning Methods
Tools 🧰 to preprocess and post process data for air quality assessment.
Build an iOS Application to Predict Air Pollution Using a Random Forest Regressor
Creation of an ecological carpooling app with the possibility of doing stopovers
Using long short term memory networks to analysis the pollution of Beijing, China.
Prediction of PM 2.5 using transfer learning approaches.
Time series prediction models, exploratory data analysis and clustering on air pollution data
Python tool to sense, predict and push pollution data to Firebase Realtime Database
a platform which provides users with the predicted Air Quality Index levels of air pollution for 39 cities of India with daily, monthly and yearly trends. It also provides some of the statistics observed for AQI over these cities and various latest articles and blogs related to air pollution.
A Python notebook that aims to analyze the change in air quality index (AQI) for 4 major pollutants (Nitrogen Dioxide, Sulphur Dioxide, Carbon Monoxide, Ozone) that cover all 50 states of the United States from 2000 to 2016.
自强不吸——基于上海市天气与交通状况的空气质量分析报告
Aeolus: Air Pollution Assistant
SCMPM: An open source and efficient calibration and mapping approach based on real-time spatial model that calibrates measurements from low-cost sensor in an environment with high relative humidity. The model provides spatial calibration of low cost PM2.5 sensors
Deep Neural Network for the prediction of NO2 level in the air, using two different satellite images of a specific zone.
Python script that allows to modify dates of input files of modules of CALMET/CALPUFF model
Add a description, image, and links to the pollution-prediction topic page so that developers can more easily learn about it.
To associate your repository with the pollution-prediction topic, visit your repo's landing page and select "manage topics."