Rural AI: Serverless-Powered Federated Learning for Remote Applications

—With increasing connectivity to support digital ser- vices in urban areas, there is a realization that demand for offering similar capability in rural communities is still limited. To unlock the potential of Artiﬁcial Intelligence (AI) within rural economies, we propose Rural AI—the mobilization of serverless computing to enable AI in austere environments. Inspired by problems observed in New Zealand, we analyze major challenges in agrarian communities and deﬁne their requirements. We demonstrate a proof-of-concept Rural AI system for cross-ﬁeld pasture weed detection that illustrates the capabilities serverless computing offers to traditional federated learning.