AgriTwin has completed its Deploy phase, marking a key step in the validation of the Agricultural Digital Solution in a real farming environment.
Following the Develop phase, where the core prototype was designed, implemented and internally tested, the Deploy phase focused on installation, operational validation and user feedback. The system was deployed at the pilot farm in Salamanca to evaluate how the AgriTwin Decision Support System and Environmental Digital Twin perform under real-world conditions.
The deployed solution integrates several technical layers. The IoT and edge layer collects and buffers field data, including soil moisture, micro-climate and operational measurements. The cloud analytics layer processes these inputs together with weather data, Earth Observation and OpenAgri services. The Decision Support System generates advisory outputs related to irrigation, pest risk and fertilisation. The Environmental Digital Twin provides a visual spatial interface for understanding field conditions, assets and recommendations.
A central aspect of the Deploy phase was the comparison between two Agricultural Digital Solution configurations: a cloud-only version and a mixed edge-cloud version. The cloud version supports heavier analytics and centralised processing. The mixed version provides additional resilience by allowing local data buffering, lightweight inference and synchronisation when connectivity becomes available.
The validation work considered data continuity, dashboard usability, latency, data transmission requirements, computing resource use, energy consumption and farmer feedback. This evidence will support the project’s final assessment of how open, interoperable and connectivity-tolerant digital farming tools can be deployed in rural agricultural environments.
The conclusion of the Deploy phase prepares AgriTwin for the next step: Scale. During the final phase, the team will assess replication potential, business model validation, impact evidence and the preparation of open-source components for wider reuse.
This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101134083.
