How can students connect soil measurements with decisions in the field? SoilQI, developed within the University of Porto's Precision Agriculture course, offers an academic environment for exploring that journey.
Bringing field data together
According to its official overview, SoilQI combines mobile PWA-based robotic monitoring, soil sensors, CSV surveys, satellite observations and georeferenced notes. Measurements include electrical conductivity, pH, temperature and moisture, supporting practical work on agricultural data visualisation and spatial analysis.
From measurements to prescription maps
The platform describes map generation using IDW, Kriging and TPS interpolation, alongside AI-assisted semantic analysis. Prescription maps can be exported for variable-rate machinery and autonomous robots.
Connecting learning with agricultural robotics
Reported integrations include ViField's ORIOOS robotics system and VineShield-DT vineyard monitoring, with imports from QGIS and John Deere Operations Center.
SoilQI's focus is education and experimentation: helping students and researchers explore the sequence from sensing to localised action. Its academic scope makes it a useful project to discover when studying how data and robotics meet in precision agriculture.
Explore the platform and its description at SoilQI.com.