Agriculture and Environment: Sensory Intelligence for Certified Production and Resource Stewardship

About

We invite European agri-tech research centers, certification bodies, and AI specialists on environmental monitoring to co-develop a full-cycle “from soil to certificate” sensory intelligence system, enhanced by localized Artificial Intelligence. This project aims to deploy affordable IoT networks for continuous monitoring of agricultural plots (including livestock welfare) and critical natural reservoirs (e.g., water, forests), transforming raw environmental data into automated certifications, premium market access, and AI-powered early warnings for ecosystem threats and disasters.

OUR APPROACH AND VALUE ADDED:

Our approach is “Precision for Purpose, Augmented by Local Intelligence.” We leverage our deep territorial embeddedness with smallholder and pastoralist communities to design sensor networks that capture critical parameters for productivity, sustainability, and market access. This includes soil moisture and sensors, livestock biometric monitors (activity, temperature), water reservoir level and quality trackers, and forest acoustic and temperature sensors. Our value lies in integrating this dense data layer with Small Language Models (SLMs) and AI fine-tuned on local conditions. This enables: 1) Automated, Intelligent Certification: Generating sophisticated, data-backed proofs for organic practices, animal welfare, or carbon sequestration. 2) Predictive Resource Security & Disaster Prevention: Creating hyper-local models for water availability, irrigation needs and abuse, detection of anomalies indicative of pollution events, fire risk, and flood prediction, generating actionable environmental hazard indicators.

EXPECTED RESULT AND NEED FOR COOPERATION:

The expected result is a democratized, intelligent environmental system that turns stewards into data-empowered beneficiaries and protectors. Farmers receive AI-generated advisories and automated audit reports. Communities gain predictive insights into natural resource risks. To achieve this, we need European partners who contribute with:

• Advanced expertise in sensor fusion, AI/ML models for agriculture, animal health, and environmental anomaly detection for disaster prevention.

• Experience in developing or fine-tuning Small Language Models (SLMs) for local context analysis and in integrating IoT data with international certification standards to create digital audit trails.

• Knowledge in developing low-cost, field-deployable, local-first sensor packages and the edge-computing frameworks needed to support localized AI analysis for comprehensive ecosystem monitoring (water, soil, bioacoustics).

• Capacity for co-submission to Horizon Europe Cluster 6 as a primary anchor, with strong links to Cluster 4 (Data, AI & Robotics) and Cluster 5 (Climate Action), and partnerships with European certification and AI ethics entities.

PROFILE OF THE EUROPEAN PARTNER SOUGHT:

We seek collaborations with leading agri-tech institutes, AI research groups focused on edge computing and SLMs, organizations like the Joint Research Centre (JRC), and companies specializing in sustainable supply chain tech. Partners should have a practical vision for making high-value certifications and advanced predictive analytics accessible to small-scale producers via appropriate, localized technology.