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CYBELE · Project

Big Data Platform That Helps Farms and Food Companies Make Smarter Decisions Faster

foodPilotedTRL 7
cybele-project.eu

Imagine farming generates mountains of data — weather, soil sensors, animal health monitors, satellite images — but most of it just sits there unused because regular computers can't crunch it fast enough. CYBELE built a supercomputer-powered platform that pulls all that scattered farm data together, cleans it up, and runs massive calculations to find patterns humans would miss. Think of it like giving farmers and food companies a turbocharged search engine for their own operations — one that can spot which field needs water, which animals are getting sick, or where the supply chain is leaking money. The platform was tested with real agricultural and livestock cases across Europe.

By the numbers
32
consortium partners across Europe
16
countries represented in the project
14
industry partners in the consortium
11
SMEs participating in development and testing
44%
industry participation ratio
41
total deliverables produced
The business problem

What needed solving

Farms and food companies generate enormous volumes of data from sensors, satellites, IoT devices, and operational systems — but most of it goes unused because standard computing infrastructure cannot process it fast enough or combine it meaningfully. This leads to poor sourcing decisions, wasted resources, missed early warnings on crop or animal health, and an inability to implement circular-economy practices in the food chain.

The solution

What was built

CYBELE built a distributed big data management platform powered by high-performance computing (HPC), delivering working software packages including Data Exploration and Brokerage Services and Data Management and Curation Services — both released in two versions with full API documentation. The platform provides data discovery, cleaning, harmonization, semantic enrichment, processing, and visualization capabilities for large-scale agricultural and livestock datasets, totaling 41 deliverables.

Audience

Who needs this

Agri-tech companies building precision farming products that need to process large-scale sensor and satellite dataLivestock technology providers looking for HPC-grade analytics for animal health and feeding optimizationFood supply chain operators seeking data-driven sourcing and waste reduction toolsAgricultural cooperatives wanting to combine data from multiple farms into a single analytics platformFarm management software companies needing a scalable backend for multi-source data integration
Business applications

Who can put this to work

Precision Agriculture
mid-size
Target: Agri-tech companies and large farming cooperatives

If you are a farming cooperative or agri-tech provider struggling to combine data from dozens of sensors, drones, and weather stations into actionable insights — CYBELE developed a high-performance data platform with built-in data cleaning, harmonization, and analytics services. It processes large-scale agricultural datasets that would overwhelm standard cloud setups, and was tested across real-life industrial cases with 32 partners from 16 countries.

Livestock Management
enterprise
Target: Livestock technology companies and large-scale animal farming operations

If you are a livestock operation dealing with fragmented animal health data from IoT sensors, feeding systems, and environmental monitors — CYBELE built data management and curation services specifically for precision livestock farming. The platform handles data discovery, processing, and visualization so you can detect health issues earlier and optimize feeding regimes using supercomputer-grade analytics.

Food Supply Chain
any
Target: Food processing and distribution companies

If you are a food supply chain company trying to reduce waste and improve sourcing decisions — CYBELE developed a virtual experimentation environment where you can run multi-parameter impact models on large-scale datasets. The platform supports circular-economy solutions in the food chain and was built with input from 14 industry partners and 11 SMEs across Europe.

Frequently asked

Quick answers

What would it cost to access or license CYBELE's platform?

The project did not publish specific pricing or licensing fees. As a publicly funded Innovation Action with 32 partners, the platform components and APIs were developed as open deliverables. Contact the coordinator at South East Technological University (Ireland) to discuss licensing terms for the software packages and services.

Can this handle the data volumes of a real commercial farming operation?

Yes — the platform was specifically designed for large-scale datasets and built on high-performance computing (HPC) infrastructure. It was validated through real-life industrial cases in precision agriculture and livestock farming, processing data from multiple distributed sources simultaneously.

Who owns the intellectual property and can I use the software?

IP is shared among the 32 consortium partners according to Horizon 2020 rules. The project produced 41 deliverables including documented software packages with APIs. Licensing arrangements would need to be discussed with the coordinator or the specific partner that developed the component you need.

Does this comply with agricultural data regulations in the EU?

CYBELE built data integrity and provenance features directly into its data management services. The platform includes data cleaning, curation, and semantic enrichment — designed with security and controlled access in mind. Specific regulatory compliance details should be verified with the consortium.

How long would it take to integrate this with our existing farm management systems?

The platform was built with interoperability as a core feature, offering documented APIs for data exploration, brokerage, and management services. Based on available project data, the modular architecture with separate data management and analytics layers suggests integration can be done component by component rather than requiring a full system overhaul.

Is there ongoing support or has the project ended?

CYBELE officially ended in March 2022. However, South East Technological University in Ireland coordinated the project and 14 industry partners were involved. Several partners may offer commercial support or continued development of specific platform components.

What makes this different from existing precision agriculture platforms?

CYBELE's distinguishing feature is supercomputer-grade processing power applied to agricultural data. While most farm platforms run on standard cloud infrastructure, CYBELE's HPC-enabled environment can handle multi-parametric experiments and massive datasets that conventional platforms cannot process efficiently. It was validated across multiple real agricultural and livestock use cases.

Consortium

Who built it

CYBELE has one of the larger Horizon 2020 consortia with 32 partners spanning 16 countries — a strong signal of broad European validation. The 44% industry ratio (14 industry partners, including 11 SMEs) means this was not an ivory-tower research exercise; nearly half the partners were companies with commercial skin in the game. The coordinator is South East Technological University in Ireland (a higher education institution), with the consortium balanced across 7 universities, 8 research organizations, and 3 other entities. Countries represented include major agricultural economies (France, Spain, Italy, Germany, Poland, Denmark, Finland) alongside tech hubs (Netherlands, Belgium), giving the platform exposure to diverse farming conditions and data environments across Europe.

How to reach the team

South East Technological University, Ireland — formerly Waterford Institute of Technology. Reach out to their research office or the CYBELE project lead for licensing and collaboration inquiries.

Order a report on this consortiumSee SOUTH EAST TECHNOLOGICAL UNIVERSITY profile →
Next steps

Talk to the team behind this work.

Want to know if CYBELE's big data platform fits your farming or food supply chain operation? SciTransfer can arrange a direct introduction to the right consortium partner for your specific use case.

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