Digital Twins voor akkerbouw en melkveehouderij

Evert, Frits van


In precision agriculture, farmers need precise, real-time information about the status of crops, soils and livestock, as well as information about the likely outcome of management decisions. We present the Digital Future Farm (DFF), a digital twin for arable farming and for dairy farming. The DFF consists of dynamic models of arable crops, grass, and livestock, as well as a method to use real-time data from sensors to keep the models synchronized with the real-world object that is simulated. In this way the DFF provides a comprehensive real-time view of the system and can thus be used to monitor crops, soils, and livestock. The DFF can also be used to predict the future state of the system (by using forecast weather). Finally, the DFF can be used to investigate the expected outcome of alternative management scenarios, for example with respect to fertilization, irrigation, and grazing management. We discuss how the DFF can possibly serve as inspiration for similar applications in (peri-)urban management and planning.