Catalogue of Services

Data analysis

Data augmentation

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

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 and LoRaWAN, other communication technologies could be supported, like NB-IoT.

Test design

Fondazione Bruno Kessler (FBK)

Test setup

Assessment of AI performance and software optimisation on edge computing devices

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.

Test design

RISE - Research Institutes of Sweden

Test setup

Assessment of conformity roadmap for an innovation

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.

Lukasiewicz Poznanski Instytut Technologiczny (L-PIT)

ELSA assessment

Assisting in Testing and Data Collection of AI-Driven Robotic Solutions

Our service provides end-to-end support for testing and data collection processes involving robotic or AI-driven systems. We assist in planning and conducting tests to ensure compliance with defined methodologies and objectives. Services include verifying system configurations, monitoring operations, managing technical infrastructure, and ensuring seamless data exchange. If necessary, we can provide access to modern agricultural machinery, such as advanced tractors or field robots equipped with Agriculture 4.0 systems, various sensors, and data recording systems. Additionally, we supply skilled operators to facilitate testing. Our service can also leverage our specialised physical infrastructure, including carrier frames, measurement wheels, and components for rapid prototyping and servicing, ensuring smooth testing operations. Collected data can be processed, documented, and provided in formats suitable for further analysis, enabling you to optimise your solutions effectively.

Provision of datasets

Test design

Università degli Studi di Napoli (UNINA)

Test setup

Blockchain in agriculture traceability systems

The service focuses on testing and developing blockchain technologies to enhance traceability in the agri-food sector. By integrating blockchain with IoT devices, the service ensures a transparent and immutable record of transactions across the entire supply chain. This enables agri-food companies to improve transparency, accountability, and trust while ensuring the integrity and safety of food products. Additionally, it drives efficiency and sustainability throughout the supply chain.

AI model training

Business modelling

Cybersecurity

Data analysis

Laboratoire National de Meterologie et d'Essais (LNE)

Certification of AI processes by LNE

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

Laboratoire National de Meterologie et d'Essais (LNE)

LCA assessment

Certification of Artificial Intelligence Management System (AIMS) of ISO/IEC 42001

The ISO/IEC 42001 is a global standard that provides a robust framework and structure within which AI systems can be developed, deployed and used responsibly. It sets out requirements and recommendations for establishing, implementing, maintaining and continuously improving an AI management system within the context of an organisation. Key controls included in the standard are risk management, AI impact assessment, system lifecycle management, performance optimisation, and supplier management. Its aim is to help organisations: Develop or use AI responsibly, Meet applicable regulatory requirements, and * Meet stakeholders' obligations and expectations. In this way, it provides concrete support to companies in optimising the use of AI by guaranteeing a level of control and confidence in the systems developed. Customers concerned: consulting firms; solution or application developers; integrators; companies integrating AI solutions purchased on the market or developed in-house into your offerings; competent authorities (decision-makers, regulators). Webinar: https://www.lne.fr/fr/webinars/iso-42001-certification-ia-lne-s Technical documentation (FR): https://www.lne.fr/sites/default/files/bloc-telecharger/FTC-ISO-42001-LNE.pdf

Certification

Conformity assessment

Desk assessment

LCA assessment

Cold chain monitoring

Università degli Studi di Napoli (UNINA)

The service focuses on developing and testing devices that ensure proper temperature conditions during the conservation and transportation of agri-food products. These devices capture and store temperature data throughout the process, offering reliable validation of temperature control. Additionally, the service provides advanced data analysis and reporting to help farmers and agri-food operators assess compliance, identify areas for improvement, and meet regulatory requirements.

Business modelling

Data analysis

Collection of datasets of images and sensor data using ground robots

The possibility to autonomously gather images and generic sensor data means a quantum leap in the creation of multispectral datasets in an automated and efficient way. A ground robot deployment occurs based on agreed requirements such as study area, measurement granularity, and data type so that it automatically captures all the information needed to generate a rich dataset. This not only makes data collection easy but also reduces human interference, hence reducing the chances of error, thus making the information obtained more valid. After the operation, the data is processed and tidied up to enable further analysis. In that respect, it can deliver faster and more accurate results for the customer, well-treated datasets according to each customer's needs, and at standards that can be further used in artificial intelligence models. With such information, customers will be better informed during the optimisation of their operations by using advanced technologies.

Politecnico di Milano (POLIMI)

Provision of datasets

Collection of test data during physical testing

Università degli Studi di Milano (UMIL)

Through this service, we offer dedicated technical systems (hardware and software) and expertise for the collection of relevant data during testing.

The scope of data collected can range from data generated by the AgrifoodTEF technical infrastructure (e.g., through the installation of IoT sensors) to the collection of data generated by the system under test to the generation of ground truth for evaluating the system. If necessary, service S00111 may be leveraged to take care of the interconnection between AgrifoodTEF data collection systems and the customer’s systems.

In addition to the raw collected data, we will also provide customers with complete documentation describing the logged features and conditions of the testing environment at the time of testing, as well as any parameter values, variation ranges and specifics required for reproducibility purposes.

Where necessary, data collection and documentation activities can require the involvement of field experts (e.g., engineers, agronomists).

Note: annotation and labelling of collected data, if needed, can be provided via service S00115.