The Critical Nature of Data Science in the Development and Utilization of Agricultural Autonomy

Visiting scholar Craig Baillie will define and give examples of the meaning of agricultural autonomy, which includes sensing, analytics and autonomous actuation (i.e., robotics). Data science is essential to the development and use of sensors and data in the agricultural context. This includes analytical technologies, such as traditional statistics and spatiotemporal statistics, which are required for precision agriculture, and even machine learning and artificial intelligence. Issues related to data volume (e.g., big data) will be considered along with the need for adequate wireless connectivity to transmit data and/or enable edge computing.