Catalogue of Services

AI hardware performance assessment

Fondazione Bruno Kessler

Location

Italy

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service is designed to test products that run complex applications, often utilising multiple microservices and heavy AI algorithms, in field conditions with limited or no connectivity to the cloud. 

We offer tailored benchmarking to identify bottlenecks within the solution's architecture, helping TEF customers enhance the efficiency and reliability of their products. 

The service can also incorporate virtual elements, such as enriched datasets and virtual machines hosting containerised modules, alongside physical sensors and infrastructure deployed either in our test field or directly at the client's premises for the duration of the experimentation.

ARPA 1 - Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)

INRAE

Location

France

Arable farming

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

INRAE offers a comprehensive testing service to validate robot's safety functions in line with ISO 18497:2018. 

Our tests assess robot's ability to detect and stop when encountering obstacles using a high-precision laser tracker for accuracy. These tests, conducted at our Montoldre site in France, will help ensure robot's compliance with industry safety standards. 

A representative from the team must be present to assist in configuring and monitoring the system during testing.

Assessment and evaluation of applied natural language processing

Research Institutes of Sweden

Location

Sweden

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service explores the potential of implementing applied Natural Language Processing (NLP) systems, rigorously evaluating them to ensure high quality and performance while identifying and addressing any limitations. It includes developing improvements to resolve issues uncovered during evaluation and ensures the NLP systems remain up-to-date.

By integrating NLP technology, businesses can enhance customer interactions through automated yet personalized responses. NLP also enables the analysis of large volumes of text data to uncover trends, identify opportunities, and provide valuable insights.

In the context of agricultural AI and robotics, NLP can significantly improve decision-making, operational efficiency, and communication.

Assessment of conformity roadmap for an innovation

Research Institutes of Sweden

Location

Sweden

At user's premises

Arable farming

Food processing

Horticulture

Livestock farming

Tree Crops

Are you ready to launch your innovative product with complete confidence in its compliance and market success? Our service offers a thorough assessment of all necessary steps to ensure your product meets the latest standards, laws, and directives. We will guide you through the regulatory landscape, identifying the specific rules applicable to your product and providing tailored advice on how to adapt your innovation to meet these requirements.

Unsure if current laws cover your groundbreaking idea? We will also investigate whether new regulations are needed to support your innovation's potential.

In addition to compliance, we provide a comprehensive range of supplementary services that AgrifoodTEF can offer to further accelerate your success. From testing and validation to expert guidance on market strategy, we are here to support you every step of the way.

Collection of test data during physical testing

Provider name

Location

Italy

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Through this service, we provide specialised technical systems (both hardware and software) and expertise for collecting relevant data during testing.

The scope of the data collected can vary, encompassing information generated by the agrifoodTEF technical infrastructure (e.g., through the installation of IoT sensors), data from the system under test, and ground truth data for system evaluation. If needed, this service can facilitate the interconnection between agrifoodTEF's data collection systems and the customer's systems.

In addition to the raw data collected, we will supply customers with comprehensive documentation detailing the logged features, conditions of the testing environment at the time of testing, and any parameter values, variation ranges, and specifics necessary for reproducibility.

When required, data collection and documentation activities may involve field experts such as engineers and agronomists.

Please note that annotation and labeling of collected data, if necessary, can be provided through service S00115. 

Compliance assessment for robotic machines

Research Institutes of Sweden

Location

At user's premises

Sweden

Arable farming

Food processing

Horticulture

Livestock farming

Tree Crops

Ensure your company develops robotic machinery that complies with all relevant regulations, standards, and directives with the support of expert guidance. Beyond meeting existing requirements, expert assistance is provided in areas where the rules are unclear or undefined. For situations with ambiguous or missing guidelines, practical solutions are offered based on extensive experience in functional safety.

Autonomous robotic machinery often relies on complex sensor technologies, such as radar, LIDAR, and cameras, to detect nearby individuals. Demonstrating how these advanced sensors can be integrated into safety functions is challenging, as it involves considering not only traditional functional safety aspects but also emerging factors like AI and Safety of the Intended Functionality (SOTIF).

Support includes performing comprehensive risk assessments, identifying relevant safety functions, and establishing high-level safety requirements for each. Depending on the project's focus, further guidance can be provided to ensure the selected safety concept aligns with applicable functional safety standards.

Computer Vision for automated food quality assessment

Universitat de Lleida

Location

Spain

Remote

Food processing

The service provides validation of existing automated food quality assessment solutions thanks to artificial intelligence, in particular through computer vision techniques. 

We help solution providers to check the solution performance using a controlled testing infrastructure, including our Food Processing Pilot Plant. The service might also include the generation of reference datasets of food samples and expected quality measures, which can be used both for validation and training of the AI solution based on Computer Vision. 

Data and media labelling for AI training

Institut de l‘Elevage - IDELE

Location

Remote

Tree Crops

This service specializes in accurately annotating and labeling datasets or multimedia content, including photos, videos, and audio, specifically for training Artificial Intelligence algorithms in the ruminant livestock sector. By meticulously tagging key features such as animal behavior, physical conditions, environmental factors, and health indicators, we provide high-quality datasets that enhance the precision of AI models used in livestock monitoring, health assessment, and farm management solutions.

Our service ensures that AI solutions for ruminant farming are trained with contextually rich, well-labeled data, enabling the development of advanced tools for animal welfare, productivity optimization, and predictive analytics in the livestock industry.

Data valorisation and dataspace integration assessment

Fondazione Bruno Kessler

Location

Remote

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

We provide an analysis of collected data in the context of developing AI-driven agricultural products and services, identifying opportunities for data-value extraction through integration within the agrifoodTEF DataSpace.

Our goal is to help customers understand both the monetary and non-monetary value of their data, as well as the channels through which they can offer it to potential users and buyers.

By analysing supply and demand in relevant Data Spaces, we recommend optimal strategies for describing metadata and adopting the appropriate technological solutions to enhance data visibility, ensuring data owners maintain control over who accesses their information.

Our services include consulting customers on enriching their data systems to adopt data sovereignty and trust solutions, aligning with the European data space strategy.

Design of computational environments for digital testing

Politecnico di Milano

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Test activities involve three key components: the environment (where the tests are conducted), the protocol (defining what tests are performed and how), and evaluation metrics (used to assess the test results). Through this service, we assist customers in designing a computational environment tailored to running the digital tests required for their software components. Specifically, this service:

• Defines the data (and metadata) requirements needed to support the test
• Identifies the necessary software environment (e.g., operating system, libraries)
• Selects an appropriate simulator and defines simulated environments, if required
• Chooses remote access tools, if applicable.

As a result, we deliver a comprehensive design of the testing environment, including specifications such as memory requirements, GPU/TPU acceleration, and necessary libraries. This environment can be deployed on either the agrifoodTEF digital infrastructure or the customer's computing infrastructure (i.e., on premises).

Design of testing protocols for physical testing

Politecnico di Milano

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Any physical testing activity comprises three main components:

• the environment (where the tests are conducted),
• the protocol (which defines the tests to be executed and their methodology),
• and the evaluation metrics (used to assess the test results).

This service focuses on the protocol, while the environment and metrics can be designed as needed through services S00106 and S00108.

In the context of testing customer solutions within physical facilities, this service aims to create a suitable testing protocol based on the use cases specified by the customer. The components of the testing protocol defined in this phase may include:

• Defining the different phases of the protocol and their duration
• Outlining the operations to be executed in each phase
• Quantifying the effort required for each phase, including the number and qualifications of personnel involved
• Distributing testing operations over time, considering seasonal and daily variations, as well as weather conditions
• Establishing acceptable and desired variation ranges for each configurable element in the testing environment
• Determining the number of test repetitions required and their distribution across the variation ranges

To ensure a comprehensive approach to protocol design, this service involves a collaborative team of both engineers and agronomists.

Evaluation of AI-based optimal pesticide dosage in tree crops

Universitat de Lleida

Location

Spain

At user's premises

Tree Crops

The service offers systems performance evaluation based on AI to optimize the dosage of pesticides for tree crops. 

The service includes comparing the optimized treatment performance versus the standard procedure, measuring the pesticide and economic savings, assessing drift reduction to the environment and improvements in environmental and biodiversity impact or the CO2 footprint of the treatment.