The Digital Twin is a smart simulator that digitizes your specific growing facilities with your specific crop. It is programmed to provide real-time insight into your growing environment beyond what physical sensors can measure.
The digital twin uses physics-informed machine learning to compute how climate variables and crop growth variables will interact. This makes the invisible crop growth metrics, such as transpiration and photosynthetic rate, visible for growers to analyze as
Gain more data and insight without installing additional hardware
The crop metrics provided by Digital Twin include transpiration, photosynthesis, leaf area index, fresh weight, and dry weight.
Visualize how different growing strategies affect predicted crop growth
With the ability of smart sensors to “predict” given sensor value and control setpoints, growers have a better understanding of how strategies influence crop metrics.
Effectively plan labor around an accurate harvest prediction
With this information, growers are better informed about the state of the crop, which leads to better operational decisions, such as growth strategy and harvest time.
The digital twin is a stepping stone that helps power our final product, focused on autonomous climate control: the λutopilot