SAS works with data generated by Florida Automated Weather Network stations near farms – in this case, near strawberry fields. SAS uses leaf wetness duration to help growers estimate the risk of their fruit getting infected with a fungal disease.

In a published research, Won Suk “Daniel” Lee, a professor of agricultural and biological engineering and Natalia Peres, a professor of plant pathology, show how artificial intelligence (AI) can improve leaf wetness detection. A system developed by the researchers took photos of a reference plate, which detects water more directly than the method currently used in SAS.