Build an AI-powered Agricultural Assistant

Contact: James Hodson,

Short Description: SDG02 aims to achieve food security, improved nutrition and promote sustainable agriculture. Build an AI model that identifies patterns, similarities and differences in agriculture between developing and developed communities around the world.

Detailed Description: World hunger is on the rise, affecting 11 percent of people globally. There were an estimated 775 million undernourished people in 2014, and that number increased to 815 million by 2016. Family farming is part of the solution to the hunger problem. More than 90% of farms are run by an individual or a family and they produce about 80% of the world’s food, occupying around 70-80% of farmland. The objective of this project is to model patterns, similarities and differences in grain growth, agricultural practices and soil/climate conditions among the most hunger stricken areas of the world. The results will be used for effective decision-making at multiple levels across the agricultural value chain and to develop solutions for optimized agricultural practices of small scale farming. Projects will include Machine Learning models, data management platforms, and visualization engines to allow communities to interact with the data and assist in decision making. Successful projects will have the opportunity to present their products in front of community leaders, researchers, and policy-makers at the AI for Good Foundation Global Conference in 2019!


Possible Data Sets:


Sustainable World:

Open Data Charter:


Africa Information Highway:

The World Bank:



Open Climate Data:

Africa Climate:


NASA World Wind:

Svalbard Global See Vault:


Global Nutrition Report:

Grain Growth:

More data…