AI vs World Hunger

In 20 years, our world population will surpass nine billion, making food scarcity an increasingly pressing issue. Today, one in every nine people goes to bed hungry. And ninety-eight percent of the world's hungry live in developing countries.

What if I said that Artificial Intelligence technology could end world hunger? Farmers in developing countries face issues such as unpredictable weather, crop diseases, and scarcity of resources like water. Researchers at the Stanford Sustainability and AI lab are working on predicting crop yields months before harvest using remote sensing data to aid in planting decisions and identifying low yield areas. Others at Carnegie Mellon University are developing a system using drones, robots, and stationary sensors. The data is then analyzed by machine learning algorithms to increase the yield of heat and drought-resistant crops.

I wish to innovate the way farmers in developing countries grow crops by providing them low-cost intelligence to help them succeed. Based on the weather patterns, soil conditions, and available water resources, we can develop a Machine Learning algorithm to suggest which plants would be most successful in an area (e.g., hybrid seeds). We could make this application available to farmers on low-cost smartphone devices- which they may even share. Based on precipitation data and soil conditions, the app would predict the water needed to sustain the farm. Using computer vision algorithms, we can provide the ability to detect plant diseases based on photographs uploaded by the farmer. The application would then suggest the remediation steps that the farmer could employ. The knowledge and support such an app could provide to the farmers would be invaluable, and by putting this in the hands of the farmers, I want to equip them to make smart decisions that can eventually eliminate world hunger, one farm at a time!