Recent research developed within the ALIANCE project, a Czech-funded initiative focused on AI-driven integration of weather forecasts, satellite data and sensor networks for climate adaptation in agriculture, has been published in the international peer-reviewed journal Sensors (MDPI), confirming the technological maturity of AI-based weather data integration for precision agriculture.
The study introduces a methodology combining artificial intelligence, multi-source data fusion and spatial modelling to refine short-term near-surface air temperature forecasts at field level. The workflow connects outputs from the Global Forecast System (GFS), agricultural meteorological stations, terrain data and machine learning models. The result is a set of high-resolution, spatially continuous temperature maps ready for operational deployment.
The research was developed in collaboration with experts from Plan4all, partner in Agri-Digital Growth, WirelessInfo, the Czech Technical University in Prague, Help Service – Remote Sensing and Lesprojekt-služby.
Beyond its scientific contribution, the publication marks a structural shift underway in European agriculture, where decision-making increasingly depends on the integration of meteorological forecasts, sensor networks, geospatial data and AI-driven modelling embedded in operational agricultural decision-support infrastructures.
With AI-driven systems now increasingly part of the daily infrastructure of agricultural decision-making, the sector faces a new challenge: updating professional roles and qualification frameworks to keep pace with this operational transformation, a transition that sits at the core of Agri-Digital Growth’s work on vocational education and structured digital competences across Europe.
The full article is available on the publisher’s website:
https://www.mdpi.com/1424-8220/26/4/1297