Soil moisture detection in crops is vital information for optimizing irrigation, ensuring adequate water supply to plants and maximizing crop efficiency. Soil moisture detection also helps prevent wastage of water resources and reduce production costs, contributing to more sustainable and productive agriculture.

Radaz carried out artificial intelligence training to detect soil moisture in sugarcane plantations. It is possible to apply it to other types of cultivation through artificial intelligence training.

Below is a soil moisture map, in which it is possible to read that the area flown over (represented in the photo) had bare soil moisture less than 20% and the soil covered with sugar cane had moisture greater than 20%.

Photo of the flight location

Soil moisture map

This application was validated through the FAPESP-IBM-PITE project (2019), in cooperation with Unicamp and Usina São Martinho.