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Test and validate intelligent solutions based on sensors to optimise livestock farming

Centre d'Estudis Porcins

The service validates that the tested solution performs as expected by the vendor or manufacturer. The objective is to detect potential mistakes in the sensor readings, the processing of the signal gathered by the sensor or in the intelligent component deriving the final information to be provided to the user to optimize livestock farming . The test can be performed at sensor or application level. The tests and validation can be performed in a laboratory or in an experimental pig farm equipped with automatic and manual measures of different variables (feed, water, CO2, NH3, temperature, ventilation, liveweight, etc.)

Collection of test data

Testbed preparation

Łukasiewicz - Poznański Instytut Technologiczny

Testbed preparation will enable costumers to execute physical tests of their technology/machines/algorithms in line with their expectations.

Within this service, costumers might get a well prepared flat/slopped arable lands or permanent grasslands.

We can also prepare a land with "controlled rain conditions" or a dump ground. There is also a possibility of providing and preparation of apiary or a sprinkler for software testing. We can help costumers run physical experiments by preparing a cultivated/non-cultivated fields or run tests on test plots, specially designed for testing. Within the latter, we will take care of such elements like: soil preparation, seed/plant procurement, seeding/planting, plant growth management, preparation of technical infrastructure. All this to meet your needs to ensure optimal conditions for conducting and monitoring tests.

This service can be executed in fields with various area with system of weather stations, phenological stations and ICT infrastructure. We can also prepare costumers sets of data collected for these areas like archive cultivated plants, treatments, crops, etc.

Testing and evaluation of mobility algorithms with ground robot

National Institute for Research in Digital Science and Technology  - INRIA

The sophia infrastructure offers the possibility to test and evaluate the mobility algorithms embedded on a ground robot.

Mobility Algorithms concerns the classical robotics functionalities of Mapping, Localization, SLAM, and Navigation. The ground robot is equipped with an array of sensors, including Camera, LiDAR, IMU, and RTK-GPS (for the ground truth evaluation).

The service consists of three main steps:

First of all, the algorithm is evaluated using representative datasets.
After that, the algorithm is integrated in a ROS2 architecture and evaluated with the local agrifoodTEF test infrastructure (different areas are possible). The performance of different attributes of the algorithm is evaluated with quantitative and qualitative metrics. A possibility of benchmarking will be proposed as a complementary option in order to position the performance of the proposed algorithm regarding the current state of the art.
Finally, the last step will be to perform the field testing in real condition and in a particular end-user or customer site using the mobile living lab (it consists of a mobile laboratory going to the field connected with the real robot for monitoring and evaluation purposes).

AI model training

Collection of test data

Data analysis

Desk assessment

People training

Performance evaluation

Provision of datasets

Test design

Test setup

Test execution

Testing and evaluation of mobility algorithms with aerial robot

National Institute for Research in Digital Science and Technology  - INRIA

The sophia infrastructure will offer the possibility to test and evaluate the mobility algorithms embedded on a ground robot. M

obility Algorithms concerns the classical robotics functionalities of Mapping, Localization, SLAM, and Navigation.

The aerial robot is equipped with an array of sensors, including Camera, LiDAR, IMU, and RTK-GPS (for the ground truth evaluation). The service consists of three main steps:

First of all, the algorithm is evaluated using representative datasets.
After that, the algorithm is integrated in a ROS2 architecture and evaluated with the local agrifoodTEF test infrastructure (different areas are possible). The performance of different attributes of the algorithm is evaluated with quantitative and qualitative metrics. A possibility of benchmarking will be proposed as a complementary option in order to position the performance of the proposed algorithm regarding the current state of the art.
Finally, the last step will be to perform the field testing in real condition and in a particular end-user or customer site using the mobile living lab (it consists of a mobile laboratory going to the field connected with the real robot for monitoring and evaluation purposes).

AI model training

Collection of test data

Data analysis

Desk assessment

People training

Performance evaluation

Provision of datasets

Test design

Test setup

Test execution

Testing of plant detection

Our digital test helps you evaluate how well your model identifies different types of plants. Your model can be delivered in a docker container or the inference results are collected in real time from your device in the field. We focus on key performance metrics like accuracy, precision, recall, Intersection over Union (IoU), and F1 score to give you a clear picture of your model's effectiveness. Crucial to this process is the ground truth data, which can be either specially prepared for this test or sourced from an existing benchmark dataset.

Testing of spot spraying performance

Our spot spraying test service precisely checks how well your spraying system works under real-world conditions. The innovative approach allows for immediate documentation of the spray distribution without altering the spraying process. After application, we document the spread pattern and analyse this data to assess how effectively and precisely the liquid targets the intended areas. This enables you to fine-tune application techniques and evaluate herbicide effects, ensuring your spraying strategies are both efficient and environmentally conscious.

Collection of test data

Performance evaluation

Test design

Test execution

Test setup

Testing of weeding performance

Our service offers comprehensive field trials to test the performance of your AI-based weeding system. Before the system operates, we record essential environmental data such as soil conditions and weather. We assess the crops and weeds either manually or with automated tools, and re-evaluate them post-weeding to measure the system's effectiveness. Our trials can be conducted on fields provided by us or at external locations of your choosing. This testing gives you clear, objective insights into your system’s performance and helps identify any potential issues under real-world conditions.

Collection of test data

Performance evaluation

Test design

Test execution

Test setup

Usability & UX testing

Our service evaluates both, the physical components and user interface of your product to ensure they meet high usability and user experience standards. Participants from a representative test group perform specific tasks that reflect the product's application, followed by a questionnaire to gather their insights. We analyse these responses to provide you with both qualitative and quantitative feedback in a detailed report. This process helps you fine-tune your product to better meet user needs.

Collection of test data

Performance evaluation

Test design

Test execution

Test setup

User Experience (UX) Evaluation

Universitat de Lleida

This service is offered by the UsabiliLAB, which specialises in advancing the usability and accessibility of interactive products and services. The service helps companies, particularly SMEs, develop AI and robotics solutions that are not only innovative but also more efficient, effective, and user-friendlier, while considering their accessibility.

The UsabiliLAB offers assessments, including conformity regarding relevant standards, and provides actionable insights to enhance usability and accessibility across various platforms, including:

Web Pages: We evaluate and refine agricultural web platforms to make them more intuitive and accessible.
Mobile Applications: Our detailed assessments help improve the usability of mobile apps, making them more user-friendly and accessible to a wider audience.
Other Interactive Products: from software interfaces to agricultural machinery, we analyse and improve any product with a user interface, ensuring that they are easy to use and meet the needs of your target audience.

Collection of test data

Conformity assessment

User Experience (UX) Evaluation

Universitat de Lleida

This service is offered by the UsabiliLAB, which specializes in advancing the usability and accessibility of interactive products and services. The service helps companies, particularly SMEs, develop AI and robotics solutions that are not only innovative but also more efficient, effective and user-friendly, while considering their accessibility.

The UsabiliLAB offers assessments and provides actionable insights to enhance usability and accessibility across various platforms, including:

Web Pages: we evaluate and refine agricultural web platforms to make them more intuitive and accessible.
Mobile Applications: our detailed assessments help improve the usability of mobile apps, making them more user-friendly and accessible to a wider audience.
Other Interactive Products: from software interfaces to agricultural machinery, we analyze and improve any product with a user interface, ensuring that they are easy to use and meet the needs of your target audience.

Conformity assessment

Performance evaluation

Test design

Test execution

Test setup

Validation of AI-based models of crop fields

Universitat de Lleida

We provide experimentation fields for herbaceous crops (like wheat, barley, maize, soybean, sunflower, pea, rapeseed, camelina, and more), along with sample laboratory analysis or crop characterisation if required.

All combined are used as testbeds for data acquisition throughout the crops’ growth cycle for training predictive models or helping the company’s development and improvement of their AI-based algorithms for agronomy applications, such as automatic weed detection for precision spraying solutions, biomass and yield estimation, phenological characterisation, etc.

This service also helps the validation of agricultural technology solutions based on, but not limited to, systems that require physical testing, such as proximal remote sensing technologies, including UAVs (unmanned aerial vehicles, or drones), computer vision systems for weeding machines, spraying applicators, etc.

AI model training

Collection of test data

Data analysis

Performance evaluation

Provision of datasets

Test execution

Validation of AI- or robotic-based solutions for vineyard management: provision of dedicated and private experimentation facilities on a real vineyard

Institut Français de la Vigne et du Vin - IFV

Location

France

Viticulture

Install your robotic or AI solution on a real vineyard to assess its performance or to foster its development with storage and workshop facilities. Benefit from our accompaniment and our guidance to find the better spots in the vineyard according to your experimental needs. We define the requirements together before you arrive and book for you the parcels and the workshop. We give you detailed information about the soil and all operations in the vineyard so you can choose the best spot to conduct your developments. You will be advised and get feedback on how your solution works.

Performance evaluation

Catalogue of Services

All agrifoodTEF services can be customised!