SOURCE-LINKED INTELLIGENCE
Emergent soil, plant and food onsite digital services on chemical and biological contaminants
of heavy metals & micronutrients, and iv) UVC LED -based nutrient analysers for soil water content in-situ and real time monitoring. The AI-driven onsite digital tools will be model calibrated using machine learning algorithms to improve error distribution of a predictive model, ensuring reliability. Also, E-SPFdigit brings an edge-based remote sensing framework via a robust autonomous mobile robot self-navigating and a heavy-duty unmanned aerial vehicle for in-field detection of soil parameters regarding the aforementioned chemical and biological stressors. Finally, to predict pesticide and fertiliser and other chemical contaminants impacts on crop-soil-microbiome nexus, the project will use on-field real-time digital ground sensors combined with Earth Observation data and causal machine learning. All the onsite digital tools will be interconnected with a Decision Support Systems with blockchain and cybersecurity mechanisms enabling informed decisions and automated decision making for IPM and INM, enhanced with automated decision making for immediate soil management practices. Onsi
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- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 5033127.5
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T02:21:08.944Z. This is not the publication date.