Mathematics Seminar - 08/26/26

Abstract: Remote sensing is a core technology of precision agriculture, which has been evolved into AI-driven smart agriculture. This talk will focus on developing AI-driven multisource (space-borne, airborne and ground-based) remote sensing for agricultural applications, and present the use of multisource remote sensing imagery, especially unmanned aerial vehicle-based remote sensing, for single field/farm monitoring and control through crop growth phenology reinforcement learning and multiple privacy-reserved fields/farms through crop growth phenology federated learning. This work highlights the efforts of my team to develop AI-driven multisource remote sensing data and model management infrastructure to provide new agricultural cybernetics insight for the research community and data and model management tools for farmers and stakeholders to promptly adapt to rapidly changing field conditions. In the presentation some theoretical models and mathematical perspectives will be described and discussed as well.