Catalogue of Services

Performance testing of deep learning solutions

Universidad de Córdoba

Location

Remote

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service evaluates the performance of deep learning algorithms to determine their efficiency and feasibility for migration to embedded devices. By leveraging high-performance computing (HPC) and GPU resources, this testing helps developers understand how well their algorithms perform in terms of speed, accuracy, and resource consumption. The service is particularly beneficial for applications in food processing, such as beekeeping and pollen counting, where real-time data processing is essential.

Performance Testing of Robotic Systems and AI Solutions

Lukasiewicz Poznanski Instytut Technologiczny

Location

At user's premises

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

We provide physical testing services, under both laboratory and field conditions, to assess the proper performance of the object under test, the level of quality, and the performance achieved. These tests focus on evaluating the performance of an object under laboratory and operational (field) conditions while maintaining its proper functionality. Our testing process helps identify potential weaknesses in the design of the device, offering insights that can inform adjustments to algorithms or hardware. This service aims to ensure that systems perform reliably under a variety of conditions, helping to prevent failures and maintain optimal performance in real-world applications.

Physical Testing of Endurance & Reliability

Lukasiewicz Poznanski Instytut Technologiczny

Location

At user's premises

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

We provide physical testing services, both in laboratory and field environments, to evaluate the endurance and reliability of devices and their components. These tests focus on the ability of components to withstand external conditions while maintaining proper functionality. Our testing process helps identify potential weaknesses in device design, offering insights that can inform adjustments to algorithms or hardware. The service is designed to ensure your systems can perform reliably under a variety of conditions, helping to prevent failures and maintain optimal performance in real-world applications.

Preparation of computational test environment

Politecnico di Milano (POLIMI)

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

To successfully conduct a digital testing campaign, preparatory activities are usually required to set up the computational environment used for testing. This service performs activities such as: - setting up the hardware resources needed to run the tests - configuring and initialising the virtual environments used for testing (e.g., Docker images, private “data rooms” for safe data sharing) - installation and configuration of required software packages and dependencies - Setting up authentication layers, user roles and credentials as needed- Migration and/or exchange of required data and ground truth annotations - installation and configuration of a simulator - importing and configuring a previously defined simulated environment - executing dry runs to check that all elements of the test environment operate as required Environment preparation is done according to an environment design provided by the customer. If needed, such design can be done by AgrifoodTEF for the customer via Service S00176. Interested customers can get support from AgrifoodTEF for the entire pipeline involved in digital testing, from the design of its other elements beside the environment (namely, the testing protocol via service S00177 and the evaluation metrics via service S00178) to test execution (service S00182) and data collection (service S00183) and evaluation (S00184). Support in interconnecting the systems under test to the digital testing environment, if needed, is available via service S00181.

Preparation of physical test environment

Politecnico di Milano (POLIMI)

Location

Italy

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

Testing a system in a physical environment requires an environment that has been prepared and set up to support the specific testing activities to be executed. This service supports the customer in the execution of the tests by taking care of such preparation and setup. The service involves: - agronomic preparation: e.g., providing the required soil conditions, making sure that a given in-field configuration of specific plants at a given growth stage is available at the time of testing, and so on; - Technical preparation: e.g., setting up infrastructure elements such as RTK GPS base stations, environmental sensors, power and networking, as well as the computational environment required to interface with the system under test to acquire and possibly pre-process experimental data. If AgrifoodTEF facilities are involved in the experimental activities, the service also includes configuring the testing facility accordingly. Environment preparation is done according to an environment design provided by the customer. If needed, such a design can be done by AgrifoodTEF for the customer via Service S00106. Interested customers can get support from AgrifoodTEF for the entire pipeline involved in experimental testing, from the design of its other elements beside the environment (namely, the testing protocol via service S00107 and the evaluation metrics via service S00108) to test execution (service S00113), data collection (service S00113), and evaluation (S00114). The output of Service S00110 is the environment ready for the execution of the testing campaign at the time requested by the customer.

Providing demonstration testing on the test field of robotic or AI-driven solutions

Lukasiewicz Poznanski Instytut Technologiczny

Location

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

As part of the service, a testbed will be provided for product demonstration of robotic machines along with AI systems. The polygon will be configured and prepared to meet the customer's individual needs in terms of field operations, technological processes, and communication. The service provider will provide polygons with a variety of surfaces according to the customer's specifications, e.g., meadow, ploughed field. The service will include soil moisture control, continuous monitoring of the field, and all activities carried out on it. The service providers will provide the necessary assistance and infrastructure needed to support the fieldwork carried out by the surveyed sites. The service may also involve demonstration of AI systems used in apiaries.

Provision of a phenotyping greenhouse with extensive sensor set - NPEC

Wageningen University WUR

Location

Netherlands

Arable farming

Greenhouse

Horticulture

NPEC will enable you to make accurate, high-throughput studies of plant performance possible in relation to relevant biotic (diseases, bacteria) and abiotic (light quantity and quality, nutrients, temperature, moisture, soil pH and atmospheric CO2 level) factors across a range of scales. 

The experiments can be performed in a greenhouse compartment with an extensive set of sensors to measure the plant and it’s environment. In growth rooms smaller scale experiments can be performed, with a special chamber for studying the roots of plants using transparent growth media. In the open field crop measurements can be performed using the Traitseeker for RGB, spectral and 3D measurements. 

Provision of a virtual playground for robots

Wageningen University WUR

Location

Netherlands

Remote

Greenhouse

Horticulture

The service consists of a photorealistic digital greenhouse environment, built in a game engine. 

The greenhouse is configurable to different sizes, light conditions (sun, supplementary lighting) or row spacing. In the greenhouse different crops can be placed to either test AI detection networks or complete robotic systems, as there is a ROS2 integration available. The environment is made in a way that physical properties of the objects have influence on other components or robot interactions. 

Provision of dataset for agricultural applications

Laboratoire National de Métrologie et d’Essais - LNE

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Our service offers a comprehensive collection of high-quality datasets tailored for agricultural applications, specifically designed to facilitate the testing and training of AI systems. These datasets encompass a wide range of data types, such as RGB or infrared images, 3D scans of LiDAR, or tabular data, ensuring that users have access to the relevant information needed for effective model development. By providing clean, well-structured, and annotated data, we empower agricultural businesses, researchers, and developers to enhance their AI solutions, driving innovation and efficiency in the industry. With our datasets, users can accelerate their projects, improve decision-making, and ultimately contribute to more sustainable agricultural practices.

Provision of datasets

Fondazione Bruno Kessler

Location

Remote

Arable farming

Horticulture

Tree Crops

Viticulture

FBK is developing its own datasets based on its experience in the robotics and agricultural sector. These datasets can be used for training and testing of the solution proposed by the customer. Different kinds of datasets can be provided (raw, unprocessed, or processed data) according to the customer's specific needs. This service is often an essential first step for the validation process of a new product.

Provision of datasets

Josephinum Research

Location

Remote

Arable farming

Horticulture

Tree Crops

Viticulture

Our service offers a comprehensive dataset tailored for training or testing your solutions in the technology and agricultural sectors. Whether you're looking to enhance existing models or build new ones, our versatile data can be adapted to fit your specific needs. For those requiring an even more robust solution, our service seamlessly integrates with our data augmentation and labelling service (S00172), ensuring that you have access to well-organized and precisely labelled data. This flexibility allows us to support a variety of sensors and use cases, utilizing both existing data records and capturing new data in your application area. Optimize your agricultural technology solutions with our data services, designed to propel your projects forward efficiently and effectively.

Provision of datasets

Politecnico di Milano (POLIMI)

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

During the development of systems based on AI and/or robotics, tailored data are needed to support the realisation, validation and optimisation of systems and subsystems. This service aims at providing such data. AI models are a noteworthy example of systems that require data to be trained; more generally, any system which processes data produced via artificial perception (such as images, videos, LiDAR, ultrasound, radar...) requires suitable data to be built, tested and fine-tuned. This service allows a customer to define together with AgrifoodTEF the specific features of the data that the customer’s activities require and to receive datasets precisely matching such features. Among the features to be defined are the type, number and specifications of the data streams comprised in the datasets (e.g., when multi-sensor data are required) and the range of variations encompassed by the data (e.g., variety of environmental conditions represented in a sensor stream); lower-level features to be defined concern formatting and packaging of the data.