What if we already gather all the data we need to help us prepare for disasters, better plan our urban environments and protect our food supply? What if we lack the tools to effectively analyze all the data we already collect?
A doctoral student at Arizona State University is on the front lines of artificial intelligence, or AI, research designed to help us act on what we know.
This June, top data science researchers and graduate students convened on the campus of Dedan Kimathi University of Technology in Nyeri, Kenya to tackle some of the planet’s most pressing problems — food insecurity, environmental conservation and climate change.
Data Science Africa, or DSA, hosted its annual Summer School, attracting hundreds of students, industry professionals and academics from all over the world to collaborate on the event’s theme of “Data Science for Social Good in the Age of Generative AI.”
Gedeon Muhawenayo, a doctoral student in the School of Computing and Augmented Intelligence, part of the Ira A. Fulton Schools of Engineering at ASU, attended the event on behalf of the Kerner Lab, discussing the team’s work as part of the NASA Harvest program. NASA Harvest is a consortium of leading scientists and agricultural stakeholders who combine their expertise to ensure food security.
Hannah Kerner, an assistant professor of computer science and engineering in the Fulton Schools, is developing tools to analyze huge sets of Earth observational data to inform actionable plans. In her laboratory, her team is using a type of AI called machine learning to process massive sets of information.
One aspect of the group’s work involves supplying satellite imagery to banks of computers and tasking AI systems with learning to recognize what type of crop is being grown in the images. Once the AI can identify the crops, it can build meaningful maps when it receives new images. This process enables experts to know how much food is being produced in a region and whether it will be enough to feed the population.
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