Zambian Student Builds Machine Learning System to Help African Farmers Adapt to Climate Change
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A Zambian graduate student in the United States is developing a machine learning system designed to help African farmers decide what to plant, when to plant
Share Facebook Twitter Email Pinterest LinkedIn Tumblr VKontakte WhatsAppA Zambian graduate student in the United States is developing a machine learning system designed to help African farmers decide what to plant, when to plant it and how much yield to expect — addressing a growing challenge as climate change disrupts the generational knowledge that has long guided African agriculture.Mwansa Phiri, a student in the Katz School’s master’s program in artificial intelligence, is leading a project called Smart Farming: A Machine Learning Approach to Crop Growth Prediction. The project aims to support food security across Africa by giving farmers better data on which to base planting decisions, particularly as drought, flooding and tightening regulations on water and fertilizer use put traditional farming methods under strain.Phiri said the project was inspired in part by Zambian agritech entrepreneur Nchimunya Munyama, whose own AI-focused startup grew out of the challenges his grandfather faced as a farmer. “Since we’re in the United States, we don’t really get to hear what’s going on back home,” Phiri said. “Nchimunya came to visit us in the States and told us how difficult it is for farmers to know what to grow. They rely on generational knowledge — what their parents always planted — but climate conditions are changing.”Phiri collaborated with fellow AI students Jelidah Nayingwa and Esparance Tuyishime, who helped train, test and refine the machine learning models. “We a...
