Services

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 predetermined 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 [...]

The service focuses on utilising artificial intelligence (AI) and visual recognition technology to enhance quality assurance, consistency, and efficiency in the agri-food industry. Its AI-driven quality assessment solutions ensure that products meet industry standards, regulatory requirements, and consumer expectations. By identifying deviations from quality standards, the service enables proactive quality control, reducing the risk of product recalls or rejections.

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 [...]

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.

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.

One of the key activities during digital testing is the collection of data concerning the progression and the final outcome of the tests. Such data enable the evaluation of system performance by the customer or – if needed – by agrifoodTEF (via Service S00184). This service manages the collection of data relevant to performance evaluation produced during the tests by both the system under test and the computational environment where the tests take place. Examples of collected data comprise [...]

Collection of data relevant to the performance of a physical system (e.g., a machine) during the execution of experimental activities and preparation of such data for analysis and interpretation.

The service focuses on developing customised holographic technology to fight the counterfeiting of agricultural products. It provides a tailored security system using advanced holograms that strengthens product integrity, builds consumer trust, and supports the broader goal of safeguarding the agri-food sector from fraud.

This service consists of deploying a modular sensor payload (equipped with Lidar, inertial motion units, GNSS, Radar, stereo cameras, and ultra-wideband technology) to agricultural environments such as vineyards and orchards to collect and annotate high-fidelity datasets tailored to customer needs. Data are systematically labelled and can be delivered to agrifoodTEF customers as structured datasets for AI-driven agricultural solutions.

This service concerns the curation of ground truth annotations for testing and experimentation data. More specifically, data labelling concerns the association of portions of data (e.g., image regions) to descriptions that provide information about the significance of those portions. In particular, labelling is required whenever the data are meant to be used for model training. We also provide labelling services for domain-specific data attributes, such as disease indicators and their [...]

Validation (e.g., check for technical quality) and/or processing (e.g., transcoding, formatting, association with ground truth) of datasets.

This service involves the design of a digital testing environment, either deployed on the agrifoodTEF digital infrastructure or on-site, to support the execution of user-customised tests.