AgAI: Building tech for small holder farmers in NigeriaPermalink
Pavlos Protopapas (pavlos@seas.harvard.edu) and MarcAntonio Awada (mawada@hbs.edu)
This project will utilize data from Babban Gona, a Nigerian-based company that works with nearly 100,000 smallholder farmers to improve their farming practices, increase agricultural productivity, and enhance farmer financial health. The company has collected data on historical farm yields, field agent visit logs with notes, millions of images of crop growth and development, and a smaller dataset of tens-of-thousands of labeled crop images.
This project will utilize this data to develop image-based AI farming tools that can run on low-cost mobile phones, optimization algorithms to improve the routing of field agents to farmers, and accessible apps for farmers and field agents to improve their productivity. The project will involve working with Babban Gona to help them collect additional data that can improve farmer outcomes. Also, it will analyze existing data to improve the performance of the routing of field agents and develop image-based AI farming tools that can run on low-cost mobile phones.
This project is a collaboration between Babban Gona's data science team and the Tech for All Lab at the Digital, Data, and Design (D3) Institute. This collaboration is led by Tarun Khanna (Jorge Paulo Lemann Professor at Harvard Business School), Rembrand Koning (Assistant Professor at Harvard Business School), and MarcAntonio Awada (Head of Research and Data Science at the D3 Institute).
Pavlos Protopapas (pavlos@seas.harvard.edu) and MarcAntonio Awada (mawada@hbs.edu)
This project will utilize data from Babban Gona, a Nigerian-based company that works with nearly 100,000 smallholder farmers to improve their farming practices, increase agricultural productivity, and enhance farmer financial health. The company has collected data on historical farm yields, field agent visit logs with notes, millions of images of crop growth and development, and a smaller dataset of tens-of-thousands of labeled crop images.
This project will utilize this data to develop image-based AI farming tools that can run on low-cost mobile phones, optimization algorithms to improve the routing of field agents to farmers, and accessible apps for farmers and field agents to improve their productivity. The project will involve working with Babban Gona to help them collect additional data that can improve farmer outcomes. Also, it will analyze existing data to improve the performance of the routing of field agents and develop image-based AI farming tools that can run on low-cost mobile phones.
This project is a collaboration between Babban Gona's data science team and the Tech for All Lab at the Digital, Data, and Design (D3) Institute. This collaboration is led by Tarun Khanna (Jorge Paulo Lemann Professor at Harvard Business School), Rembrand Koning (Assistant Professor at Harvard Business School), and MarcAntonio Awada (Head of Research and Data Science at the D3 Institute).