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Setup for AI solution testing

Fondazione Bruno Kessler

Digital testing of an AI solution often requires action to obtain the proper configuration. This service contains all the required actions necessary to configure, integrate and execute the client AI solution with FBK test environment. Carrying out these preliminary activities, FBK will be able to have a working setup that will be the entry point for subsequent testing and validation services.

Test setup

Technology Setup and Integration for Agricultural Production Testing

This experimental service focuses on the initial setup and integration of new technologies within the client’s production environment. The process includes connecting hardware and software systems, configuring settings, and ensuring that the technology is fully operational and integrated with existing workflows. The integration is performed with minimal disruption to daily operations and includes tests to ensure compatibility and optimal performance from the start.

Collection of test data

Data analysis

Test execution

Test setup

Test and demonstration of (robotic sensor, implement, algorithm) solutions with end-users

Wageningen Research - WR

Accessing the end-user in a country takes a lot of time and effort. Wageningen Research - Field Crops has, through its regional experimental farms, access to farmer networks and dealers and can bring you in contact with them. The researchers in our department have a practical approach and know what is needed to implement new technologies in farms, therefore fulfilling a bridge between agronomy, technology, and ecology. By testing and demonstrating your product or service to our farm managers and farmers in the region (for example, farmers in https://www.proeftuinprecisielandbouw.nl), we gather valuable feedback to speed up the development of your prototype.

Market research

Test execution

Test and experimentation of robotic and AI solutions in field crops

Wageningen Research - WR

The core business of Wageningen Research - Field Crops is to design and create experimental plots (e.g. at the Farm of the Future) and to collect objective data on crops, weeds, diseases, pests and quality and effectiveness of robotic and AI solutions, in which we provide statistical reliable datasets. Examples of experiments are e.g. testing the accuracy and quality of handsfree harvesting solutions, weeding robots and path following of autonomous implement carriers in field crops. We offer for example the following measurements : -Provide measurements on effectiveness of solutions on control of weeds, pests and diseases (e.g. effectiveness of a weed robot) -Provide timeseries of vegetation indices (drone) -Provide yield measurements (quantity and quality) -Provide plant measurements (emergence, flowering, senescence) -Provide weed countings (including species determination) -Provide sensor data (soil moisture, insect monitoring, etc.) Furthermore we have common agricultural machines and implements available. We can cover different field crops, but we also are specialized in new crop farming systems that are based on agro-ecological principles. Think of strip and mosaic farming. Get in touch to discuss the possibilities for your experiment or test question.

Collection of test data

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

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

Test, validation, and data collection of robotic and AI systems and components for livestock solutions

Wageningen Research - WR

Location

Netherlands

Livestock farming

In the setting of the Farms of the Future (De Marke), we can (physically) test and validate robotic and AI solutions that are dedicated to dairy solutions. In this context we are also able to collect appropriate data sets of these tests and validation experiments. Test and validation data will be compared to ground truth data sets.

Collection of test data

Desk assessment

Performance evaluation

Test design

Test execution

Test setup

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 AI Solutions for Precision Agriculture

Danish Technological Institute

This service focuses on testing and experimenting with AI solutions specifically designed for agricultural applications. It aids companies in robotics and drones by facilitating the implementation and deployment of advanced technologies in farming and food processing environments. The service includes the evaluation of new sensors and algorithms that enhance localisation and positioning, crucial for precise agricultural operations. We offer testing and validation of AI-driven solutions for precision agriculture, support for implementing robotics and AI in agricultural practices, optimisation of sensor and algorithm performance for enhanced crop monitoring and yield prediction, and deployment of drones for aerial surveillance and data collection on large farms.

AI model training

Collection of test data

Data analysis

Performance evaluation

Test design

Test execution

Test setup

Testing and Data Analysis for Agritech Solutions

This experimental service focuses on the provisioning and analysis of customer data for agrotech companies, enabling them to better understand client behavior, optimize service offerings, and improve customer satisfaction. The service involves data collection, cleansing, and advanced analytics, providing insights into customer preferences, usage patterns, and future needs. The goal is to help agrotech companies make data-driven decisions to enhance their products, services, and operational strategies.

Interested in this service? Contact us at innovation@hispatec.com

Testing and evaluating sensor devices

National Institute for Research in Digital Science and Technology  - INRIA

The SOPHIA infrastructure will offer the possibility to test and evaluate the performance of a sensor device in a locally controlled environment. While our indoor facility provides a fully controlled environment (light, volume), all facilities in SOPHIA can be customised to test and evaluate the sensor device. The service consists of three main steps. First, the sensor device will be integrated into the facility. After that, the facility will be customised according to the final application of the sensor device. Then, the performance of the sensor device will be evaluated using quantitative and qualitative metrics. Comparison could be proposed as a complementary option to position the performance of the sensor device in relation to the current state of the technology available in SOPHIA.

Collection of test data

Data analysis

Desk assessment

People training

Performance evaluation

Provision of datasets

Test design

Test execution

Test setup

Testing and evaluating the robot’s functionalities

National Institute for Research in Digital Science and Technology  - INRIA

The SOPHIA infrastructure will offer the possibility to test and evaluate the performance of the robot’s functionalities in a locally controlled environment. While our indoor facility will offer a fully controlled environment (light, volume), all facilities at SOPHIA can be customised to test and evaluate the robot’s functionalities. The service consists of three main steps. The robot will be integrated into the facility. After that, the facility will be customised according to the functionality of the robot. Then, the performance of the robot’s functionalities will be tested and evaluated with quantitative and qualitative metrics.

AI model training

Collection of test data

Data analysis

Desk assessment

People training

Performance evaluation

Test design

Test execution

Test setup

Testing and evaluation of mobility algorithms with ground robots

National Institute for Research in Digital Science and Technology  - INRIA

The SOPHIA infrastructure provides the ability to test and evaluate mobility algorithms embedded on a ground robot. Mobility algorithms concern the classical robotics functionalities of mapping, localisation, SLAM, and navigation. The ground robot is equipped with an array of sensors, including a camera, LiDAR, IMU, and RTK-GPS for ground truth evaluation. The service proceeds in three stages. Firstly, we evaluate the algorithm using representative datasets. After that, the algorithm is integrated into a ROS2 architecture and evaluated with the local agrifoodTEF test infrastructure (various areas are possible). The performance of different attributes of the algorithm is assessed using quantitative and qualitative metrics. Benchmarking could be proposed as a complementary option to position the performance of the proposed algorithm in relation to the current state of the art. The final step involves field testing under real conditions at a specific end-user or customer site using the mobile living lab, which consists of a mobile laboratory deployed in the field and connected to the real robot for monitoring and evaluation purposes.

Collection of test data

Data analysis

Desk assessment

Performance evaluation

Test design

Test execution

Test setup