- Rice identification and forecasting models were developed using satellite data and artificial intelligence (AI)
- Record number of 13,000+ participants submitted more than 7,500 AI models
- CarbonFarm to leverage winning models for use by agribusinesses and governments
The EY organization today announced the winners of the 2023 EY Open Science Data Challenge – an annual competition for university students, early career professionals and EY people to find tangible solutions for global sustainability issues using satellite data, AI and other technologies. This year’s topic focused on food security by identifying rice fields in Vietnam and estimating yields. The program is part of the EY organization’s broader strategic commitment to innovate using data and AI for good.
According to the UN annual Human Development Report, 820 million people go to bed hungry. The UN Food and Agriculture Organization predicts that the agriculture industry will need to produce 70% more food while only being able to use 5% more land. The EY organization is working together with NGOs, governments and scientists to help find ways to make this a reality, and this year’s competition will help provide tangible ways for improving predictions of crop yields and using land more efficiently.
The 2023 Challenge saw a record number of participants with more than 13,000 registrations; more than 7,500 submitted models; from more than 110 countries and 632 universities. Participants identified where rice could be cultivated and estimated crop yields based on factors such as climate. They gained skills in understanding and interpreting radar and optical satellite data, coding and testing machine learning (ML) techniques including classification and prediction algorithms.
The 2023 winners hail from across the world: Bangladesh, India, Canada and Poland. They were selected by a panel of judges from Microsoft, Cornell University, University of California’s Disaster Resilience Network, Tierra Foods and the EY organization. Winners were announced at the awards ceremony in New York where finalists gathered to celebrate, network and share their collective passion for sustainability. The winners are:
Team Nông dân trồng lúa, Macquarie University and Vin University
- Tuo Kai
- Vi Hieu Nguyen
- Gary Chen
- Tien Duong
Team 2XX, EY Malaysia
- Xin Dee Tan
- Kristin Lee
- Lai Yi Tian
- Shahirah Shalihan
Team Crop Dusters, University of British Columbia
- Reza Mursalin
- Advitja Hajela
- Nirvaan Rohira
- Divyadarshan Punjabi
Team Maciej Wylężek, EY Poland
The winning models are available free of charge for non-commercial purposes. One recipient of the models is CarbonFarm, an organization focused on keeping global warming below 1.5 Celsius.
Vassily Carantino, CarbonFarm Cofounder and CEO, says:
“While we focus on quantifying greenhouse gas emissions from rice to help farmers claim carbon credits, monitoring yields is also a very important dimension as carbon projects should not decrease farmers’ yields. We will leverage the models and put them in the hands of agribusinesses and project developers in the region.”
This year’s collaboration partners included Microsoft, which provided participants with access to satellite datasets, learning courses and credits; as well as Cornell University, which provided a scientific backbone to the design of the challenge, helped identify the topic and formulate the problem statement, and provided the necessary rice cropping datasets.
Beatriz Sanz Sáiz, EY Global Consulting Data and AI Leader, says:
“This program is an excellent example of how AI can be used to help change the world for the better. The technology has the potential to revolutionize the way we work and now is the time for the public and private sectors to come together and use AI in a way that is not only responsible but makes a real difference too. This year’s entrants, finalists and winning teams have been a real inspiration to us all and I would like to say a huge congratulations to all of them for their incredible hard work and dedication.”
Today, the EY organization is also announcing the 2024 EY Open Science Data Challenge topic is focused on “building coastal resilience.” Some of the most vulnerable areas to climate change are low-lying coastal zones in developing countries and small island states. Teams will be set with the challenge of helping save lives by helping coastal communities become better at preparing for and responding to disasters caused by climate change. Teams will review land classification models; use satellite data combined with climate, topographic, population and socioeconomic data; and apply ML algorithms and generative AI in the development of their models.
Find out more information here.
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