Catalogue of Services

Evaluation of AI-based optimal pesticide dosage in tree crops

Universitat de Lleida

Location

At user's premises

Spain

Tree Crops

Evaluation of the performance of systems to optimise the dosage of pesticides based on artificial intelligence for tree crops. The service includes comparing the optimised 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.

Evaluation of readiness for testing

Research Institutes of Sweden

Location

At user's premises

Remote

Sweden

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Customers are often unaware of the best way to conduct testing and may require support and coaching to reach a state of test-readiness and proceed to purchase a testing service from TEF. 
Service S00248 is designed to help customers understand and navigate the various steps involved in testing. The service offers clear and straightforward guidance to ensure customers are fully prepared for testing. By collaborating with RISE experts, customers can be confident that they are receiving the appropriate advice to achieve their goals. 
The aim of the service is to make the testing process more accessible and understandable, allowing customers to focus on their core activities.
 

Field Spectrometer Measurements

Instituut voor Landbouw-, Visserij- en Voedingsonderzoek

Location

At user's premises

Belgium

France

Germany

Netherlands

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service utilises field spectrometers to measure the spectral properties of physical environments, such as barns, greenhouses, or outdoor fields. By capturing detailed spectral data, we help you develop, improve, or validate your agri-food solutions, whether for monitoring plant health, optimising lighting conditions, or enhancing environmental control systems. The measurements provide insights into how different wavelengths of light interact with the environment, enabling fine-tuned adjustments for better crop growth, energy efficiency, or precision farming applications. Additionally, this service can serve as a follow-up to lab-scale measurements where hyperspectral technology is used to conduct pilot tests to determine which wavelengths provide valuable information. In this service, we then perform field tests on these specific wavelengths.

Generation of datasets using network-connected sensors

GRADIANT

Location

At user's premises

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service focuses on the collection and processing of data from sensors connected to a 5G network. Leveraging the high-speed, low-latency capabilities of 5G, it facilitates efficient data transmission, ensuring comprehensive coverage and timely data collection across various environments. The collection and processing methods yield high-quality datasets that are essential for training AI models and developing decision-making algorithms, supporting diverse applications. Additionally, the scalable environment developed allows for adaptability across different sensors, use cases, locations, and even communication technologies, like LoRa. 

Generation of quality terrain datasets over autonomous ground robots

GRADIANT

Location

At user's premises

Spain

Arable farming

Horticulture

Livestock farming

Tree Crops

Viticulture

This service specialises in generating high-quality terrain datasets using sensor-equipped UGVs (unmanned ground vehicles). By employing autonomous UGVs, the service streamlines the data collection process, ensuring efficiency and accuracy in gathering crucial parameters like humidity, pH, temperature, etc. This equipped UGV navigates diverse terrains, autonomously collecting data in specific locations planned by the user. The automated data collection not only enhances the speed of information gathering but also facilitates the generation of comprehensive datasets. This information is invaluable for professionals seeking to make AI models, make data-driven decisions, and analyse the impact of different strategies on the lands. 

Life Cycle Assessment (LCA) for Agriculture Robots

Danish Technological Institute

Location

At user's premises

Denmark

Remote

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Life Cycle Assessment (LCA) for Agriculture Robots is a comprehensive evaluation method that assesses environmental impacts at every stage of a robot’s lifecycle—starting from raw material extraction, manufacturing, utilization, and ending with disposal or recycling. This service provides valuable insights into energy consumption, waste generation, and other environmental factors, helping customers identify key areas for improvement. By promoting sustainability and eco-efficiency, LCA supports decision-making for reducing ecological footprints and ensuring compliance with sustainability standards such as Frugal AI requirements. The service is tailored to meet diverse customer needs, enabling them to understand and optimize the environmental performance of their robotic technologies.

Performance and sustainability testing of robotic or AI-driven solutions

Lukasiewicz - Poznanski Instytut Technologiczny

Location

At user's premises

Poland

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service provides a comprehensive assessment of the performance of systems, focusing on sustainability indicators such as energy consumption and input usage per hectare. It evaluates the impact of artificial intelligence (AI) or robotic solutions on the performance and sustainability of the associated equipment. The service includes tests such as functional testing, accelerated durability testing, and assessments of the system’s resilience to environmental factors and electromagnetic interference (EMI). By identifying potential design flaws or manufacturing defects, the service supports the development and optimisation of tested solutions, contributing to sustainable technological advancements.

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.

Provision of general-purpose datasets via multisensory ground robot

National Institute for Research in Digital Science and Technology  - INRIA

Location

At user's premises

France

Arable farming

Food processing

Greenhouse

Horticulture

Tree Crops

Viticulture

General-purpose datasets serve two primary objectives: (i) evaluating mobility algorithms and (ii) developing and assessing general-purpose AI applications. In the context of mobility algorithms, this pertains to classical robotics tasks such as mapping, localisation, SLAM (Simultaneous Localisation and Mapping), and navigation. Meanwhile, general-purpose AI applications focus on advancing algorithms and feeding decision support systems (DSS) for tasks such as, but not limited to, weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas like arable farming, horticulture, food processing, forestry, and tree management. A significant challenge in developing AI solutions for agricultural robotics lies in the dynamic nature of agricultural environments, which fluctuate with different seasons and weather conditions. To address this, acquiring consistent and periodic data is essential for monitoring these changes effectively. This real-time data collection, often facilitated by ground robots, is crucial for developing efficient algorithms and AI solutions. Such datasets can support the development of sensor-specific techniques or be leveraged to create multisensory algorithms, enabling more accurate and adaptable systems for agricultural applications.

Provision of general-purpose datasets via a multisensory aerial robot.

National Institute for Research in Digital Science and Technology  - INRIA

Location

At user's premises

France

Arable farming

Food processing

Greenhouse

Horticulture

Tree Crops

Viticulture

We provide general-purpose datasets that can be used by customers to evaluate mobility algorithms and to develop and assess general-purpose AI applications. In the context of mobility algorithms, this pertains to classical robotics tasks such as mapping, localisation, and SLAM (Simultaneous Localisation and Mapping). Meanwhile, general-purpose AI applications focus on advancing algorithms and feeding decision support systems (DSS) for tasks including, but not limited to, weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas such as arable farming, horticulture, food processing, forestry, and tree management. A significant challenge in developing AI solutions for agricultural robotics lies in the dynamic nature of agricultural environments, which fluctuate with different seasons and weather conditions. To address this, acquiring consistent and periodic data is essential for effectively monitoring these changes. This real-time data collection, often facilitated by aerial robots, is crucial for developing efficient algorithms and AI solutions. Such datasets can support customers in the development of sensor-specific techniques or be leveraged to create multisensory algorithms, enabling more accurate and adaptable systems for agricultural applications.

Provision of general-purpose datasets with user-specified sensor(s)

National Institute for Research in Digital Science and Technology  - INRIA

Location

At user's premises

France

Arable farming

Food processing

Greenhouse

Horticulture

Tree Crops

Viticulture

General-purpose datasets serve two primary objectives: (i) evaluating mobility algorithms and (ii) developing and assessing general-purpose AI applications. In the context of mobility algorithms, this includes classical robotics tasks such as mapping, localisation, SLAM (Simultaneous Localisation and Mapping), and navigation. Meanwhile, general-purpose AI applications focus on advancing algorithms and supporting decision support systems (DSS) for tasks such as, but not limited to, weed detection, health monitoring, growth and maturity assessment, and yield estimation in areas like arable farming, horticulture, food processing, forestry, and tree management. A significant challenge in developing AI solutions for agricultural robotics lies in the dynamic nature of agricultural environments, which fluctuate with different seasons and weather conditions. To address this, acquiring consistent and periodic data is essential for effectively monitoring these changes. This real-time data collection, often facilitated by aerial and/or ground robots equipped with user-specified sensors, is crucial for developing efficient algorithms and AI solutions. Such datasets can support the development of sensor-specific techniques or be leveraged to create multisensory algorithms, enabling more accurate and adaptable systems for agricultural applications.