Precision Agriculture
This use case will provide a real-life demonstration of the benefits of the DS2 IDT solution and tangible benefits to the precision agriculture community.
Demo site: Greece
Description
At its core is AgroNIT, a digital platform primarily used to provide farmers with direct access to monitoring tools to inspect field conditions, track crop development, needs or imminent threats, and view localized weather forecasts. It currently offers limited services customization and minimal structured interaction among its users (farmers, agronomists, analysts, etc.). Within DS2, AgroNIT is being re-architected to function as a federated marketplace. Within it, data and services are published, discovered, and consumed. Farmers receive tailored recommendations. Agronomists offer predictive tools. Analysts contribute models. Services are exchanged securely and transparently.
Challenge
Precision agriculture depends on data that is high-quality, real-time, and context. This use case demonstrates how such data, originating from fields, satellites, weather models, and AI services, is shared, processed, and used to support smarter, more sustainable farming in Northern Greece.
Purpose
This use case addresses the integration of real-time agricultural data, AI services, and cross-sector collaboration within a federated digital environment. It focuses on precision farming in Northern Greece, where diverse actors, such as farmers, agronomists, researchers, service providers, and the agri-food industry, interact through a shared infrastructure. The scope is intentionally broad in technological reach yet specific in its application context: improving crop productivity, resource efficiency, and decision-making, while maintaining full control over data assets.
Requirements Co-creation and Architecture Validation
Precision agriculture delivers IoT-intensive requirements with sensor and satellite data, creating the most datarich validation environment.
Offered Service
The service supports precision farming by offering AI-driven recommendations on irrigation, crop monitoring, and sourcing logistics. It helps farmers, agronomists, and cooperatives make real-time, data-informed decisions to boost productivity and sustainability. Delivered through the AgroNIT web platform, the service combines dashboards, AI models, and a federated data marketplace. Core data products include IoT sensor data, high-res crop images, weather forecasts, and satellite indices. These are processed across two dataspaces: DigiAgro data space (run by UTH) and AgroScience data space (run by CROWNEST).
Dataspaces
Two distinct dataspaces support this system: DigiAgro DS and AgroScience DS. AgroScience DS, which is operated by CROWNEST SA, delivers analytics, decision support tools, and consultancy services by integrating external datasets, such as satellite imagery, short-term forecasts, agronomic baselines, and making them actionable. The DigiAgro DS, operated by the University of Thessaly, serves as a dedicated infrastructure for the acquisition, management, and controlled sharing of agricultural field data.
Complex Data Lifecycle and Regulatory Compliance Testing
Precision Agriculture creates federated learning scenarios requiring distributed data control across agricultural cooperatives.
Non-functional Properties
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Data sovereignty: Farmers retain ownership and control over their data at all times.
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Privacy preservation: Sensitive and proprietary data is not shared unless explicitly permitted; Federated Learning reduces exposure.
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Compliance: All operations align with GDPR and European data governance frameworks (IDSA, GAIA-X).
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Scalability: The system architecture supports increased data volume, additional farms, and new service providers.
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Interoperability: Based on open standards and modular integration, supporting future cross-sector extensions.
Functional Properties
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Real-time monitoring of environmental and crop conditions via IoT sensors and cameras.
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Visualization of weather forecasts, field metrics, and crop imagery.
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Discovery, publication, and consumption of datasets and digital services within a federated marketplace.
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Secure data exchange between independently operated dataspaces (DigiAgro DS and AgroScience DS).
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Role-based access and dynamic policy enforcement for data usage and service invocation.
Modules Used in the Use Case and Their Added Value
DS2 modules (e.g., ORC, PAE, RET, DRM) ensure data control, policy enforcement, and secure cross-dataspace interaction.
Before DS2
High-quality agricultural data from field sensors, satellites, and weather models remained fragmented across isolated systems, restricting farmers and agronomists from accessing the integrated, real-time insights needed for sustainable precision farming.
After DS2
A secure federated marketplace called AgroNIT seamlessly connects distinct agricultural dataspaces, empowering stakeholders to exchange real-time IoT data and edge-trained AI models to make smarter, data-informed crop management decisions.
Use Case Participants
DigiAgro
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Farmers / Cooperatives (Central & Northern Greece)
AgroScience
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CROWNEST SA
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Agronomists/Agricultural Scientists
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Third-party data providers (Weather forecasts, Satellite imagery)
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Kronos SA (Food Industry)