Fostering Precision Agriculture and Livestock Farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable Big Data analytics

Project Details


Main research question/goal

CYBELE is a 3-year project to demonstrate how high performance computing (HPC) and Big Data analysis can help revolutionize agriculture and boost precision farming in order to create social, economic and environmental benefits. CYBELE aims to ensure that the stakeholders have a secure access to large-scale datasets and have the processing power available to analyse and process this data, generate value and extract useful insights. The project is coordinated by the Waterford Institute of Technology (WIT) and involving 31 international partners. The 14-million-euro CYBELE project is financed under Horizon 2020 (H2020) - The EU Framework Programme for Research and Innovation.

Research approach

After an analysis and design phase, development of the CYBELE integrated platform will take place. This will include all the necessary mechanisms, tools, services and algorithms to work with the HPC infrastructure. Nine demonstrators in the precision agriculture and precision livestock farming fields have been selected to showcase and evaluate the potential of the HPC infrastructure. ILVO is WP leader of the precision livestock farming demonstrators and is also involved in the work of two of these demonstrators. One is about “Sustainable pig production”, together with Vion Food Group, and will focus on a better usage of the vast amounts of data collected in a slaughterhouse, hyperspectral imaging for meat quality and the usage of sensor data to alert for pig diseases on-farm. The other demonstrator is about “Open sea fishing” and will focus on better monitoring of fish prevalence and the marine ecosystem of the North Sea, improvement of fisheries management via multiple sensors on the ship, and the automatic detection of fish species through image analysis.


The impact of CYBELE will be that (a) an HPC-enabled environment supporting the execution of agrifood related experiments optimizing the processing of large scale datasets will be developed; and (b) several demonstrators in precision agriculture and precision livestock farming will have tested, used and improved the HPC environment through iterative feedback. The CYBELE solution will be built to persist after the end of the project, and input of external stakeholders will also be taken into account. Overall, this project leads to a more easily accessible HPC environment, with features adapted to the agrifood sector and which enables more advanced analysis for researchers and policy-makers, increased responsiveness and decision-making for companies and stakeholders and the ability to use available data in the chain in a more effective way. The solutions built on top of the environment in turn lead to more responsible use of natural resources, improved farm management, less waste and losses, etc.

Funding provider(s)
EU Horizon2020
Effective start/end date1/01/1931/03/22