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.

Execution of physical testing

Politecnico di Milano (POLIMI)

Location

Italy

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

Any physical test activity involves three main components: environment (where the tests take place), protocol (defining what tests are executed and how), and evaluation metrics (used to assess the results of the tests). The execution of physical testing, i.e., the object of this service, corresponds to supporting the customer in executing with the system(s) under test the procedures specified by the protocol in the specified environment and identifying and solving any issues that may negatively affect the tests. In most cases, support by AgrifoodTEF involves assistance by both agronomists (for agricultural aspects) and engineers (for aspects related to the technological infrastructure supporting the tests). Beside the object of this service, i.e., test execution, AgrifoodTEF can, if requested, support the customer along any other aspect and phase of the physical experimentation pipeline. For instance, for the design of the environment and protocol to be used for the test, the customer can either proceed autonomously or exploit services S00106 and S00107. Similarly, preparation of the test environment can be done either by the customer or by AgrifoodTEF via service S00110; in both cases, assistance in interconnecting the system under test with AgrifoodTEF’s test infrastructure is available via service S00111. Finally, data collection during the test or data processing and performance evaluation after the conclusion of the test, if needed, can be provided by AgrifoodTEF via services S00113 and S00114, respectively.

Expand training datasets by using synthetic data based on existing datasets

RISE - Research Institutes of Sweden

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.

Experimentation implementing robotics in agricultural processes

HISPATEC

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This pilot service focuses on the integration of robotic systems into agricultural processes, enabling the automation of key tasks such as planting, harvesting, and crop monitoring. By combining robotics with advanced software, this service improves operational efficiency, reduces labor costs, and enhances the precision of agricultural tasks. The integration ensures that robotic systems work seamlessly within existing workflows and provide consistent, high-quality performance.

Experimentation with Artificial Intelligence for Agricultural Optimisation

HISPATEC

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service applies artificial intelligence (AI) algorithms to process and analyse large datasets collected from agricultural operations. By leveraging machine learning and data analytics, the service generates predictive insights about crop needs, such as water, fertilizer, and pest control, allowing for more accurate and efficient resource use. The AI-driven approach helps farmers and agribusinesses optimise their production processes, reduce waste, and improve yields by making data-driven decisions.

Experimentation with synthetic data generation and data augmentation techniques

Lukasiewicz Poznanski Instytut Technologiczny

Location

Poland

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service involves expanding training datasets using synthetic data and data augmentation techniques. This will use algorithms capable of generating synthetic data simulating certain aspects of existing datasets. Such an approach will lead to the enrichment of the existing training material. The service includes the creation of synthetic replicas based on real data, the combining of real and synthetic data, and also, for example, the creation of digital terrain maps based on ground data, which can be further enriched with synthetically generated details. As a result, we offer a comprehensive solution for more reliable development of datasets.

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

Josephinum Research (JR)

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.

Field Spectrometer Measurements

Instituut voor Landbouw-, Visserij- en Voedingsonderzoek (ILVO)

Location

At user's premises

Belgium

France

Germany

Netherlands

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service utilises field spectrometers to measure the spectral properties of physical environments, such as barns, greenhouses, or outdoor fields. By capturing detailed spectral data, we help you develop, improve, or validate your agri-food solutions, whether for monitoring plant health, optimising lighting conditions, or enhancing environmental control systems. The measurements provide insights into how different wavelengths of light interact with the environment, enabling fine-tuned adjustments for better crop growth, energy efficiency, or precision farming applications. Additionally, this service can serve as a follow-up to lab-scale measurements where hyperspectral technology is used to conduct pilot tests to determine which wavelengths provide valuable information. In this service, we then perform field tests on these specific wavelengths.

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.

Generation and provision of labelled datasets for benchmarking purposes

Lukasiewicz Poznanski Instytut Technologiczny

Location

Poland

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The service provides the ability to deliver to the client model training data sets with labels and metadata, which will later be used to conduct comparative analyses of AI algorithms by the target groups using the technologies under study. The datasets delivered to the client will be configured or customised in advance, as appropriate, according to the requirements and needs of the client of the service. Customisation processes will include configuring and adjusting the data and labelling according to the scopes of field operations, technological processes or communications to which the transferred data assets relate. These data sets include, but are not limited to, satellite and spatial data for remote sensing, phenological data for different crops, or synthetic data to expand training opportunities.

Generation of datasets using network-connected sensors

GRADIANT

Location

At user's premises

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service focuses on the collection and processing of data from sensors connected to a 5G network. Leveraging the high-speed, low-latency capabilities of 5G, it facilitates efficient data transmission, ensuring comprehensive coverage and timely data collection across various environments. The collection and processing methods yield high-quality datasets that are essential for training AI models and developing decision-making algorithms, supporting diverse applications. Additionally, the scalable environment developed allows for adaptability across different sensors, use cases, locations, and even communication technologies, like LoRa. 

Generation of quality terrain datasets over autonomous ground robots

GRADIANT

Location

At user's premises

Spain

Arable farming

Horticulture

Livestock farming

Tree Crops

Viticulture

This service specialises in generating high-quality terrain datasets using sensor-equipped UGVs (unmanned ground vehicles). By employing autonomous UGVs, the service streamlines the data collection process, ensuring efficiency and accuracy in gathering crucial parameters like humidity, pH, temperature, etc. This equipped UGV navigates diverse terrains, autonomously collecting data in specific locations planned by the user. The automated data collection not only enhances the speed of information gathering but also facilitates the generation of comprehensive datasets. This information is invaluable for professionals seeking to make AI models, make data-driven decisions, and analyse the impact of different strategies on the lands.