Catalogue of Services

AI model evaluation and verification

Research Institutes of Sweden

Location

Remote

Sweden

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Evaluating or verifying AI solutions is technically challenging and imposes specific requirements on the application, which can vary from setting internal benchmarks to establishing safety conditions. Evaluation and verification are performed using a broad set of tools ranging from straightforward performance evaluation metrics to formal methods for the verification of safety requirements. Formal methods can also be used to evaluate requirement fulfilment and systematically discover scenarios showing that AI systems need further improvements. Alternatively, customers can receive technical assistance and advice on improving AI systems that do not meet requirements.

AI model training

Politecnico di Milano

Location

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service concerns training AI models on behalf of the customer for a specific task and optimisation objective, e.g., improving accuracy on crop classification from image data. The target model is the solution provided by the customer that needs to be enhanced with respect to a set of pre-determined features to reach the desired performance level. However, if required, the training can also be applied to additional state-of-the-art models available in the market for benchmarking purposes. If not defined by the customer, some features of the training process can be identified via service S00179 (desk assessment activities for digital systems and/or data): for instance, model features to improve, reference model baselines to include in the performance comparison, as well as benchmark datasets. The data used for training the model can be either provided by the customer or annotated ad hoc as a preparatory activity to model training (via service S00290 - Data Labelling); another possibility is that data are retrieved among reference benchmark datasets that are openly available. We will also agree with customers on the level of hardware acceleration required, based on the considered AI models: e.g., GPU acceleration via connection to a remote server vs. on-device training.

AI model training for computer vision tasks in TEF infrastructure

GRADIANT

Location

Remote

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The service allows training an AI model to be used for computer vision tasks, like object detection, segmentation, or classification tasks. The training is run on the TEF infrastructure, thus providing a powerful platform for developing cutting-edge artificial intelligence solutions in the agrifood sector. By leveraging high-performance computing resources, CPUs, and GPUs within the TEF infrastructure, this service enables innovators to train AI models using datasets based on images or videos. Users can either provide their own datasets or utilise existing data within the TEF infrastructure (see Related Services). The model training supports various architectures for the computer vision tasks, allowing the selection of the most appropriate one depending on the use case.

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 agricultural equipment connectivity through private 5G/NB-IoT network deployment

GRADIANT

Location

At user's premises

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The service provides a comprehensive assessment of the connectivity of agricultural equipment, such as sensors and actuators, through private networks. By offering in-depth visibility into the network’s operation, it enables accurate troubleshooting, ensuring optimal connectivity for these kinds of devices. The service can handle the connection of multiple devices, making it suitable for validating the development of custom connectivity modules or testing agricultural equipment with built-in commercial modules. This allows for early detection of connectivity issues, fine-tuning module and network configurations, and ensuring smooth equipment operation. By deploying private networks, it is possible to implement configurations that simulate adverse conditions in deployment, such as successive outages, excessive packet loss, remote access failures to access the hardware, and more; practices that would be unthinkable in public networks. Furthermore, although the preference is for the deployment of cellular networks like 5G, 4G, or 3G, other communication technologies could be supported, like NB-IoT.

Assessment of agricultural potential for emerging technologies in AI & robotics

Josephinum Research

Location

Austria

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Our service is designed to assist clients in identifying and evaluating potential agricultural applications for AI or robotics technologies originally developed for other sectors. Clients can provide detailed information about their technology, including its current applications and technical specifications. Our expert team will conduct extensive research to identify possible use cases related to the agricultural and food production sector, analysing factors such as feasibility, potential benefits, and relevance to current agricultural challenges. The tools used for this work will depend on the use case and may include, for example, online research as well as expert interviews. The customer will receive the results as a comprehensive report outlining the identified potential applications, adoptions needed and an assessment of their relevance and impact within the agricultural sector. This service enables clients to explore new markets and adapt their technologies to meet the evolving needs of modern agriculture.

Assessment of AI performance and software optimisation on edge computing devices

Fondazione Bruno Kessler

Location

At user's premises

Italy

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The tests in this service are aimed at products that run complex apps (based on a multitude of microservices, including heavy AI algorithms) in the fields, with limited to no connectivity to the cloud. In these cases, we propose a benchmarking designed to understand what the bottlenecks are in the implemented solution architecture to help TEF customers improve the efficiency and reliability of such products/solutions. The service may also encompass virtual facility elements (enriched datasets, virtual machines hosting containerised modules) blended with physical sensors and infrastructure in our test field or directly installed at the client's premises if need be for the duration of the experimentation.

Assessment of conformity roadmap for an innovation

Research Institutes of Sweden

Location

At user's premises

Sweden

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.

Assessment of dataset quality

Laboratoire National de Métrologie et d’Essais - LNE

Location

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

With the development of AI models in most sectors of society, the importance of the data used to train and test these models has been an important concern for the AI supplier. Understanding the quality of the datasets used, especially in sectors such as the agricultural and agrifood domains where data can be rare, is thus a prerequisite to ensure the correct development of AI models and build trust regarding these approaches for society. This service aims to answer this challenge by assessing the quality of datasets provided by the client. The features of the datasets that will be analyzed are based on agreed definition by the AI community: completeness, balance, diversity, accuracy... The dataset's quality assessment will begin by establishing the list of the system's influencing factors necessary for the constitution of a database. These factors will be identified both by using LNE expertise and outside sources, such as agrifood-relevant experts. Using these factors, LNE will analyse the distribution (or weight) of the various influencing factors in the databases and compare it to that under normal conditions of use in order to assess the representativity and balance of the dataset.

Assistance for Identifying AI Technologies for Agricultural Robotics, Drones, and Precision Machinery

Danish Technological Institute

Location

Denmark

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Our service is tailored to support AI technology providers, particularly in robotics and drone sectors, focusing on agricultural applications. We identify AI technologies that boost agricultural efficiency and productivity and offer integration support for embedding AI into agricultural robotics, drones, and precision machinery. Our guidance includes selecting effective AI tools and algorithms for specific agricultural challenges. Additionally, we offer comprehensive screening of AI technologies for agricultural relevance, which supports the company’s seamless integration of AI into existing equipment.

Benchmarking & Testing Suite for Edge Hardware Systems

Lukasiewicz - Poznanski Instytut Technologiczny

Location

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

The Benchmarking & Testing Suite for Edge Hardware Systems delivers a set of tests designed to evaluate the performance, reliability, and functionality of edge hardware and its components under various operational conditions. 

The tests can be compared to specific industry standards or the performance of other solutions available on the market. Examples of tests offered as part of the service: 

- Environmental tests: Assessing devices' resistance to extreme conditions, such as temperature, humidity, and vibrations. 

- Signal tests: Evaluating devices using GNSS signal generators, testing their resilience to interference or false signals. 

- Network tests: Evaluate device performance within a prototype 5G network infrastructure.

 - Functional tests: Assessing the capability of devices, such as remote PTZ (pan, tilt, zoom) cameras, to perform operational tasks in field conditions. 

- Integration tests: Examining the cooperation of edge devices with sensors, AI systems, and their responses to data input failures. - Accuracy tests: Measuring the precision of sensors and control systems. Test results can be compared to specified standards or the performance of competitive solutions, enabling customers to better understand their devices' capabilities.

Certification of AI processes by LNE

Laboratoire National de Métrologie et d’Essais - LNE

Location

At user's premises

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Today’s AI suppliers and AI users need to stand out from the competition, guarantee the performance of their algorithms or systems, and prepare to comply with the future European "AI Act" regulation, particularly with the obligation of transparency. With its dual expertise in certification and evaluation of AI algorithms, LNE has created a voluntary certification that meets this need. The aim of this certification standard is to define common requirements for the design, development, evaluation, and maintenance processes of all types of AI functionalities based on machine learning. It therefore covers all business sectors in which AI is used in order to guarantee the application of best practices that promote trustworthiness in AI. Website: https://www.lne.fr/en/service/certification/certification-processes-ai Webinar: https://www.lne.fr/fr/webinars/matinee-information-ia-act-certification-ia-l Technical documentation (FR): https://www.lne.fr/sites/default/files/bloc-telecharger/FTC-ISO-42001-LNE.pdf