Catalogue of Services

Execution of digital testing

Politecnico di Milano (POLIMI)

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service assists customers in executing digital tests using agrifoodTEF’s digital infrastructure. Tests can either be defined by the customer or designed through agrifoodTEF services (e.g., S00176, S00177, S00178). If specific activities are required to properly interface the system under test with the digital infrastructure, these can be handled by either the customer or agrifoodTEF (via Service S00180).

Support provided by this service includes general assistance during the test execution phase, such as monitoring to ensure compliance with the testing protocol or offering immediate help in identifying and resolving issues. Additionally, the service provides technical support during the test execution of the system under test, including ensuring that all necessary processes are correctly configured and running, as well as helping the customer address any unforeseen challenges that may arise when complex digital systems interact.

Finally, through this service, agrifoodTEF manages the technical infrastructure for test execution, ensuring smooth data exchange between the system under test and the agrifoodTEF infrastructure, and verifying that all testing requirements—potentially identified during the desk assessment phase (Service S00179)—are met during the actual test runs.

Expand training datasets by using synthetic data based on existing datasets

Research Institutes of Sweden (RISE)

Location

Remote

Sweden

Arable farming

Food processing

Horticulture

Livestock farming

Tree Crops

This service can, together with the company, expand training datasets with synthetic data. If required or appropriate, methodology and expanded data sets will also be a part of the service. By deploying synthetic data, companies can overcome some of the limitations of their existing datasets, leading to improved model performance, reduced costs, and enhanced operational efficiency. The service empowers businesses to innovate and adapt in an increasingly competitive landscape.

Feasibility analysis of a selected AI or robotics use case in agriculture

Josephinium Research

Location

Austria

Remote

Arable farming

Livestock farming

This follow-up service supports clients who, based on a prior assessment or internal selection, want to explore a specific AI or robotics use case in greater depth. It focuses on understanding the conditions under which the selected use case could be applied in agriculture. Our team performs a structured feasibility analysis considering technical, organisational, and sector-specific factors. This includes evaluating compatibility with agricultural processes, identifying potential barriers to adoption, and estimating the expected added value. The goal is to provide the client with a clearer picture of what successful implementation would require and which factors might influence success or failure. The deliverable is a detailed report with insights, risks, and recommendations, supporting further internal evaluation and strategic planning.

Functional safety testing of machines

Lukasiewicz Poznanski Instytut Technologiczny

Location

Austria

Poland

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Within the framework of this service, we offer the possibility of carrying out functional safety tests of objects in the form of, for example, autonomous vehicles, robots, machines, agricultural equipment and components, etc. The service provides opportunities to test these devices with measurements of their mechanical, physical, acoustic, electrical parameters and electromagnetic compatibility to assess the overall safety of the user of the tested vehicles, machines, equipment and components for agriculture, horticulture, forestry and food. Verification of the tested parameters is based on the requirements of standards and directives declared by the manufacturer as compatible with its product and general normative safety regulations. Initial evaluation of an object is carried out based on its provided design documentation and/or measurements made on a prototype based on harmonized and non-harmonized standards with relevant EU and sector regulations. In the case of autonomous vehicles, we also offer tests of the correctness of response and operation of safety devices built into their structures in standardized cases of hazardous situations. The results obtained can be used in the further process of product labelling, declaration of conformity to place the CE mark on the device.

Lab gold-standard evaluation

Universidad de Córdoba

Location

Remote

Spain

Food processing

This service provides a lab-based evaluation for AI classification models, contrasting their results with a gold-standard analysis to assess accuracy and reliability. Focused on applications in food processing, such as beekeeping and pollen counting, this service ensures that AI models meet high standards of precision, which is essential for fields requiring validated data accuracy.

Labelling and Data Augmentation Framework Support

ILVO

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service provides essential support for creating a robust framework to label, store, and manage data effectively for AI training purposes. Proper labelling is crucial, as deep learning models rely on consistent, high-quality data to detect complex patterns. Within this service, we do not label data ourselves but rather offer training guidelines to ensure that data is labelled accurately and consistently across large datasets. Please refer to other services if you wish for your data to be labelled by us. In addition, we help set up the necessary digital infrastructure for storing and maintaining this data. Our support streamlines the labelling and data augmentation process, laying the foundation for successful AI development in applications such as crop monitoring, pest detection, and yield prediction in the agri-food sector.

Life Cycle Assessment (LCA) for Agriculture Robots

Danish Technological Institute (DTI)

Location

At user's premises

Denmark

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Life Cycle Assessment (LCA) for Agriculture Robots is a comprehensive evaluation method that assesses environmental impacts at every stage of a robot’s lifecycle—starting from raw material extraction, manufacturing, utilization, and ending with disposal or recycling. This service provides valuable insights into energy consumption, waste generation, and other environmental factors, helping customers identify key areas for improvement. By promoting sustainability and eco-efficiency, LCA supports decision-making for reducing ecological footprints and ensuring compliance with sustainability standards such as Frugal AI requirements. The service is tailored to meet diverse customer needs, enabling them to understand and optimize the environmental performance of their robotic technologies.

Life cycle assessment (LCA) of agrifood products with and without AI, Robotic & DIGitalisation (AIRDIG) services

Research Institutes of Sweden (RISE)

Location

Remote

Sweden

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

LCA of agrifood products provides a clear comparison of the environmental impacts associated with food production using advanced technologies like AI, robotics, and digital tools versus traditional methods. By examining every stage of the production process—from resource extraction to processing, packaging, and distribution—this assessment highlights how these innovative technologies can lead to significant reductions in energy consumption, waste generation, and overall environmental footprints. For example, AI can optimise crop management, while robotics can streamline harvesting, both contributing to more efficient resource use. This information empowers businesses to understand the tangible benefits of adopting AIRDIG services, enabling them to make informed decisions that not only enhance environmental sustainability but also improve operational efficiency and reduce costs. Ultimately, the LCA serves as a valuable tool for stakeholders looking to implement greener practices in their agrifood operations.

Life cycle assessment (LCA) of AI, Robotic & Digitalisation (AIRDIG) services in the agrifood sector

Research Institutes of Sweden (RISE)

Location

Remote

Sweden

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

This service helps you understand how AIRDIG technologies impact the environment throughout their use in food production. From building the tech infrastructure to using and eventually discarding AI and robotic systems, this assessment pinpoints key areas like energy use, electronic waste, and resource consumption. It also explores how smart farming tools—like automated machines and precision farming—can improve environmental sustainability by reducing waste, conserving resources, and boosting efficiency. This approach offers a clear roadmap for making agrifood innovations more environmentally friendly.

Model training of AI agrifood-related algorithms

GRADIANT

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The AI model training service in TEF infrastructure offers a powerful platform for developing cutting-edge artificial intelligence solutions in the agrifood sector. Leveraging high-performance computing resources, this service enables innovators to train AI models using diverse tabular data types. These include sensor readings (such as soil moisture, temperature, and nutrient levels), machine-generated data (from agricultural equipment and IoT devices), crop yield statistics, weather patterns, and supply chain metrics. Users can either provide their own datasets or utilise existing data within the TEF infrastructure (see Related Services). The service supports a wide range of AI frameworks and model architectures, allowing for flexible experimentation and rapid iteration. From predictive maintenance of farming equipment to optimising crop management practices, this platform accelerates the development of AI-driven solutions that address critical challenges in agriculture and food science, fostering innovation and efficiency in the industry. 

Monitoring of deployed AI models for agrifood applications

Gradiant Technologies

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Our monitoring service provides comprehensive visibility into your own current model deployments. Through an intuitive dashboard interface, stakeholders can track and analyse their model's performance in real-time. The service continuously monitors three critical aspects: computational resource utilisation (such as processing power and memory usage), incoming data streams and patterns, and the model's output results and accuracy. This visibility allows teams to proactively identify potential bottlenecks, optimise resource allocation, and ensure the model performs as expected. The dashboard presents complex technical metrics in an easy-to-understand visual format, enabling both technical and non-technical team members to make informed decisions about their deployment. By providing these monitoring capabilities, the service helps maintain optimal performance and reliability of your model within the test environment while reducing the time needed to identify and resolve potential issues. The deployment of an AI model for testing purposes could also be done by Gradiant on another service (see related services) and then be monitored through this service.

People training services

Politecnico di Milano (POLIMI)

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The AgrifoodTEF consortium comprises a set of testing and experimentation facilities and targeted services aimed at supporting customers in the testing and validation of systems and devices based on advanced technologies. Given the technical complexity of these facilities and services and the associated complexity of many activities making use of them, many customers can benefit from a preliminary training activity. The goal of such training is to make best use of the facilities and services and fully exploit the allotted time when actual testing/experimentation occurs. Customer training – involving both technical and procedural aspects – can either be sought by the customer autonomously leveraging the documentation provided by AgrifoodTEF or directly supported by AgrifoodTEF via this service; a combination of both approaches is also possible. This service does not limit its applicability to customers that already know what they require from AgrifoodTEF. The service also provides an opportunity for customers to discuss their specific needs and requirements with our team and be directed towards the set of services in the catalogue that best suit their needs. Especially where the customer envisages an articulate testing campaign, exploring their idea together with AgrifoodTEF via this service can be very beneficial in planning subsequent activities. This service can, if needed, be integrated with services S00109 (desk assessment activities for physical systems) or S00179 (desk assessment activities for digital systems or data) to anchor its operation and possible further testing activities more closely to the specific features of the system(s) developed by the customer.