When Hela and Azer, both data scientists, saw the AirQo Low-Cost Air Quality Monitor Calibration Challenge on the Zindi Africa Platform, they immediately knew what their next hackathon challenge would be.
“I was fascinated by the challenge, it was going to be my first time working on real challenges to solve real-world problems,” Hela said.
As for Azer, a seasoned participant in the air quality data challenges he knew he had to test his skills.
For a little over one month, Hela and Azer joined over 280 data scientists from across the world, to work on a once in a lifetime opportunity to improve the air quality monitoring gap in Uganda.
The challenge was to develop a model that would allow us to improve the accuracy of data from our low-cost devices across the country and transform it to as close as possible to the reference value.
“We are empowering young data scientists in Africa and harnessing their power to solve our own African challenges,” Lillian Muyama, our Data scientist noted.
The Data Fest challenge held in partnership with Pollicy and Zindi Africa was aimed at improving the accuracy of our low-cost air quality monitors built in order to provide accurate air quality data insights to citizens and governments alike.
“The AirQo’s air quality challenge was very popular on the Zindi platform,” Amy Bray the Zindi Africa Data Scientist and Competitions Lead noted. “It was geared towards solving actual real challenges that affect us, and this is the reason it attracted a lot of participation and conversation from data scientists from all over the globe.”
Zindi Africa is a science competition platform that allows data scientists to hone their skills on real datasets and problems relevant to the African market, while Pollicy improves government service delivery through civic engagement and participation.
“The DataFest is a platform for young data scientists to compete and uncover meaning and insight in a large and complicated data set.”Gilbert Beyemba, Head of Programs at Pollicy noted. “We are empowering young people and getting them to appreciate careers in the data science field. It was inspiring to see young people collaborate, learn from each other, and work on emerging challenges like data in air quality in Africa,"
After one month of calibrating data, Azer and Hela emerged winners and will be implementing their solution with us.
“I have never had an opportunity to implement my solution and I am excited that AirQo has given me the opportunity to actually see my solution come to life,” Hela said “I am also looking forward to discovering and using machine learning algorithms to solve real problems.” As for Azer, he is looking forward to acquiring new skills and learning how to deploy a successful model. “I am interested in working in the machine learning space and deploying the models.”