Platform for Testing Precision Agriculture Concepts
SoilQI is an academic web platform developed within the Precision Agriculture course at the University of Porto. It was designed to integrate, within a single working environment, the different data sources that support site-specific crop management. The platform combines robotic field monitoring through a mobile PWA, data from IoT soil sensors — including electrical conductivity, pH, temperature, and moisture — CSV survey imports, multispectral satellite imagery from Sentinel-1, Sentinel-2, and Sentinel-3, and manual georeferenced annotations. This enables students to gain practical experience of the complete cycle of agronomic data collection, visualisation, and spatial analysis.
The outcome of this cycle is materialised in prescription maps generated through spatial interpolation methods, including IDW, Kriging, and TPS, as well as AI-assisted semantic analysis. These maps can be exported to variable-rate technology (VRT) equipment, whether conventional agricultural machinery or autonomous robots.
In this context, SoilQI integrates natively with ViField’s ORIOOS agricultural robotics system and with the VineShield-DT vineyard monitoring platform. It can also import data from QGIS and the John Deere Operations Center, creating a bridge between academic tools and precision agriculture ecosystems already used in the field.
As an academic project, SoilQI is not intended to replace commercial solutions. Instead, it provides an advanced learning and experimentation environment in which students and researchers can explore the full precision agriculture pipeline, from soil sensing to site-specific actuation.