Urban Air Pollution Hackathon by AI+ Club UI
Can you predict air quality in cities around the world using satellite data?
53 data scientists enrolled, 33 on the leaderboard
SafetyPredictionStructuredSDG15
Nigeria
22 July—26 July
5 days

This is a private hackathon whose primary purpose is for the members of the DSN Ai+ Club Ibadan to apply what they have learnt. If you are part of Ai+ Club Ibadan contact the club leader for the secret code.

You may have seen recent news articles stating that air quality has improved due to COVID-19. This is true for some locations, but as always the truth is a little more complicated. In parts of many African cities, air quality seems to be getting worse as more people stay at home. For this challenge we’ll be digging deeper into the data, finding ways to track air quality and how it is changing, even in places without ground-based sensors. This information will be especially useful in the face of the current crisis, since poor air quality makes a respiratory disease like COVID-19 more dangerous.

We’ve collected weather data and daily observations from the Sentinel 5P satellite tracking various pollutants in the atmosphere. Your goal is to use this information to predict PM2.5 particulate matter concentration (a common measure of air quality that normally requires ground-based sensors to measure) every day for each city. The data covers the last three months, spanning hundreds of cities across the globe.

About DSN Ai+ Club Ibadan (twitter.com/dsn_ui):

DSN Ai+ Club Ibadan (University of Ibadan, Nigeria) is a branch of Data Science Nigeria Community aimed at building and sustaining Ai talents at the university with the vision #1millionAiTalentsIn10Years.