Services by Sector
AgrifoodTEF provides services for different sectors in the agrifood domain:
Sectors
For the Arable sector, AgrifoodTEF will propose services for testing and validation of robotic, selective weeding and geofencing technologies to enhance autonomous driving vehicle performances and therefore decrease farmers' reliance on traditional agricultural inputs. Show services
For the Tree Crop sector, AgrifoodTEF will propose services for testing and validation of AI solutions supporting optimisation of natural resources and inputs (fertilisers, pesticides, water) for Mediterranean crops (Fruit orchards, Olive groves). Show services
For the Horticulture sector, AgrifoodTEF will propose services for testing and validation of AI-based solutions helping to strike the right balance of nutrients while ensuring the crop and yield quality. Show services
For the Livestock sector, AgrifoodTEF will propose services for testing and validation of AI-based livestock management applications and organic feed production improving the sustainability of cows, pigs and poultry farming. Show services
For the Food Processing sector, AgrifoodTEF will propose services for testing and validation of standardised data models and self-sovereign data exchange technologies, providing enhanced traceability in the production and supply chains. Show services
For the Viticulture sector, AgrifoodTEF will propose services for testing and validation of AI solutions supporting optimisation of natural resources and inputs (fertilisers, pesticides, water) for Viticulture crops. Show services
Following is a list of services sorted by sector:
arable farming
- Assessment of environmental impacts when applying digital technologies in agriculture
- Mediation and networking
- Testing of weeding performance
- Testing of spot spraying performance
- Testing of crop detection
- Testing of weed detection
- Providing dataset for training purpose
- Providing benchmark dataset
- Usability & UX testing
- Testing of biomass estimation
- Testing of Follow-me function of a robot
- Testing of person detection function of a robot
- Testing of field navigation
- Testing of sensor performance
- AI Model Training and Benchmarking
- Data analysis
- Data augmentation
- Test suitability of an agricultural implement on an autonomous carrier platform
- Performance evaluation of an AI model
- Hyperspectral measurements and analysis
- Fertilizer spreader calibration based on vision and AI-methods
- Robotic Software Framework
- Agri Dataset generation
- Evaluation of the performance of crop protection equipment
- Artifcial intelligence in irrigation systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Validation and testing UAV-remote sensing products
- UAV: Collection of test data during physical testing
- UAV: Evaluation of results of physical testing
- Satellite based-models for precision agriculture
- Satellite: Evaluation of results of physical testing
- AI model training traceability
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC1 - Qualification of trajectory execution accuracy of crop production robots (out-door mobility).
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision for weed detection
- Automatic machines and Agricultural robots
- Automatic machines and Agricultural robots
- Automatic machines and Agricultural robots
- Automatic machines and Agricultural robots
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- Provision of physical testing and experimentation facilities
- Evaluation of Smart Perception Systems for Precision Farming: agrophotonic sensors
- Evaluation of Smart Perception Systems for Precision Farming: satellite data
- AI robustness evaluation based on testing datasets
- Evaluation of Automatic Machines and Agricultural robots: insects in storage silos
- Evaluation of Automatic Machines and Agricultural robots: insect pests
- AI performance evaluation based on physical testing environments: weed control - software
- Evaluation of Automatic Machines and Agricultural robots: weed control - hardware
- Dataset provision for weed detection
- AI performance evaluation based on physical testing environments: irrigation - software
- Evaluation of Automatic Machines and Agricultural robots: irrigation - hardware
- Evaluation of Automatic Machines and Agricultural robots: plant species detection
- General Purpose Datasets via Multisensored Ground Robot
- General purpose datasets via multisensored aerial robot
- General Purpose Datasets with user specified sensor(s)
- Testing and Evaluation of Mobility Algorithms for Ground Robot
- Testing and Evaluation of Mobility Algorithms for an Aerial Robot
- Design of test environments for physical testing
- Design of testing protocols for physical testing
- Design of evaluation metrics for the results of physical testing
- Desk assessment activities for physical systems
- Preparation of physical test environment
- Support in interconnecting system under test to AgrifoodTEF’s physical infrastructure
- Execution of physical testing
- Collection of test data during physical testing
- Evaluation of results of physical testing
- Data validation and processing services
- LCA analysis
- Training services
- AI hardware performance assessment
- Data valorization and dataspace integration assessment
- Design of computational environments for digital testing
- Design of testing protocols for digital testing
- Design of evaluation metrics for the results of digital testing
- Desk assessment activities for digital systems and/or data
- Preparation of digital test environment
- Support in interconnecting system under test to AgrifoodTEF’s computational infrastructure
- Execution of digital testing
- Collection of test data during digital testing
- Evaluation of results of digital testing
- Testing Integration and performance of advanced weather forecasting
- Testing for safety in alignment with relevant legislation
- Testing of translation solutions for multilingual applications
- IoT and Blockchain enabling technologies to measure and improve workplace safety
- Design and implementation of certified smart irrigation systems
- Design and implementation of certified smart fertilisation systems
- Combating forgery in the agri-food chain
- Improve energy efficiency along agricultural value chains
- IoT weather predictive models and greenhouse gas emissions from agriculture
- UAV-based remote sensing for supporting precision agriculture
- Wireless communication infrastructure serving the agricultural
- Blockchain in agriculture traceability systems
- Cold chain monitoring
- Applications of artificial intelligence and visual recognition for assessing quality of agri-food industry products
- Test and development of innovative and practical agri-food applications of the metaverse.
- Navigation for ground robots in plots of land
- Precision weed mapping
- Co-design of Robotic and AI systems and components for arable farming solutions
- Test, validation and data collection of Robotic and AI systems and components for arable farming solutions
- Business Model and Market development support for Robotic and AI solutions in arable farming
- Provision of specific and long term data sets for arable and livestock farming data from the Farm of the Future experimental farms
- Data analysys support for specific and long term data sets for arable and livestock farming data sets
- Fenotyping support for AI and robotic based plant and livestock data handling and modelling (outdoor + indoor)
- R&D support AI development and robotics crops, livestock and post harvest
- Provision of Farmmaps platform to support Precison farming and KPI accounting data services
- Support in using explainable AI Models (simulation, early warning, DSS) and Digital Twins for crop and livestock management
- ELSA scan and support for AI and Robotic applications -- Ethical, Legal and Social Aspects
- Value Sensitive Design support in AI-and Robotic developments
- Business Innovation support using the 5D model of business innovation (modelling)
- User Acceptance Testing (UAT) of AI and robotic solutions
- Cultivating Data in Farming with Semantic Standards and Interoperability Support
- Provision of Agro Data Cube platform for data handling
- Training for AI- and Robotic Skills and Education, MOOCs
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- Expand training datasets by using synthetic data based on existing datasets
- Usability & UX testing
- Test design: definition of the test environment
- Test design: definition of the test protocol
- Test design: definition of the test evaluation
- Desk assessment activities
- Testbed preparation
- Support for interconnection of the system under test to agrifoodTEF’s technical infrastructure
- Test execution services
- Data collection services
- Performance evaluation services
- Data validation and processing services
- LCA assessment
- AI-Testfield – Demonstration
- AI-Testfield – Development
- UAV-Testfield – Development
- Datasets - Benchmark
- High-Value-Testfield – Usability / UX
- Robotic Integration - Algorithms
- Testing - Cybersecurity
- AI-Testfield – Model Improvement / Adaptation
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Model Improvement / Adaptation
- AI Integration - Algorithms
- AI Integration - Predictive System
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Validation and development of AI-powered agricultural irrigation systems
- Virtual training for crops, livestock, and food processing
- Conformity roadmap for an innovation
- Compliance for robotic machine
- Compliance for AI innovation
- Conformity and Safety tests
- Test of error handling and failiure monitoring
- Experimentation AI Crop production
- Experimentation Robotics Crop production
- Experimentation UAV Crop production
- Policy Lab
- Virtual training or validation of crop and weed detection
- Validation of work result under real conditions crop production robotics
- Validation of work result under real conditions crop production sensors and decision support systems
- Validation of work result under real conditions crop production UAV
- Expand weed identify functionality to new crops and weeds
- Expand training datasets by using synthetic data based on existing datasets
- Provisioning of testbed for crop production
- Evaluation of applied natural language processing
- Evaluation of readiness for testing
arable farminghorticulturegreenhousetree cropsviticulturelivestock farmingfood processing
- AI model training
- AI model evaluation
- AI algorithm test scenario design
- AI model deployment
- Deployed model monitoring
- AI test scenario execution
arable farminghorticulturetree cropsviticulture
arable farminghorticulturetree cropsviticulturelivestock Farming
arable farminghorticulturetree cropsviticulturelivestock Farmingfood processing
arable farminghorticulturetree cropsviticulturelivestock Farmingfood processinggreenhouse
arable farminghorticulturetree cropsviticulturelivestock Farminggreenhouse
- Automatic capture of aerial images and videos over UAV
- Automatic capture of ground images and videos over UGV
food processing
- Hyperspectral measurements and analysis
- AI-driven LCA-analysis during food processing
- Food consumption analysis
- Computer Vision for automated food quality assessment
- Performance testing of deep learning solutions
- Lab gold-standard evaluation
- AI model training traceability
- Computer Vision for automated food quality assessment
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- General Purpose Datasets via Multisensored Ground Robot
- General purpose datasets via multisensored aerial robot
- General Purpose Datasets with user specified sensor(s)
- Testing and Evaluation of Mobility Algorithms for Ground Robot
- Testing of translation solutions for multilingual applications
- Improve energy efficiency along agricultural value chains
- IoT weather predictive models and greenhouse gas emissions from agriculture
- UAV-based remote sensing for supporting precision agriculture
- Wireless communication infrastructure serving the agricultural
- Blockchain in agriculture traceability systems
- Cold chain monitoring
- Applications of artificial intelligence and visual recognition for assessing quality of agri-food industry products
- Test and development of innovative and practical agri-food applications of the metaverse.
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- Expand training datasets by using synthetic data based on existing datasets
- AI-Testfield – Demonstration
- AI-Testfield – Development
- UAV-Testfield – Development
- Datasets - Benchmark
- High-Value-Testfield – Usability / UX
- Robotic Integration - Algorithms
- Testing - Cybersecurity
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Algorithms
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Virtual training for crops, livestock, and food processing
- Conformity roadmap for an innovation
- Compliance for robotic machine
- Compliance for AI innovation
- Conformity and Safety tests
- Policy Lab
- Expand training datasets by using synthetic data based on existing datasets
- Evaluation of readiness for testing
greenhouse
- AI model training traceability
- Validation of Yield Estimation based on Computer Vision
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC1 - Qualification of trajectory execution accuracy of crop production robots (out-door mobility).
- AI hardware performance assessment
- Testing and experimentation of environment mapping for precision agriculture applications
- Testing Integration and performance of advanced weather forecasting
- Testing for safety in alignment with relevant legislation
- Testing of translation solutions for multilingual applications
- AI-Testfield – Demonstration
- AI-Testfield – Development
- UAV-Testfield – Development
- Datasets - Benchmark
- High-Value-Testfield – Usability / UX
- Robotic Integration - Algorithms
- Testing - Cybersecurity
- AI-Testfield – Model Improvement / Adaptation
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Model Improvement / Adaptation
- AI Integration - Algorithms
- AI Integration - Predictive System
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Validation and development of AI-powered agricultural irrigation systems
- Virtual training for crops, livestock, and food processing
horticulture
- Testing of weeding performance
- Testing of spot spraying performance
- Testing of crop detection
- Testing of weed detection
- Providing dataset for training purpose
- Providing benchmark dataset
- Usability & UX testing
- Testing of Follow-me function of a robot
- Testing of person detection function of a robot
- Testing of field navigation
- Testing of sensor performance
- AI Model Training and Benchmarking
- Data analysis
- Data augmentation
- Test suitability of an agricultural implement on an autonomous carrier platform
- Performance evaluation of an AI model
- Hyperspectral measurements and analysis
- Fertilizer spreader calibration based on vision and AI-methods
- Robotic Software Framework
- Agri Dataset generation
- Evaluation of the performance of crop protection equipment
- AI model training traceability
- Validation of Yield Estimation based on Computer Vision
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC1 - Qualification of trajectory execution accuracy of crop production robots (out-door mobility).
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- General Purpose Datasets via Multisensored Ground Robot
- General purpose datasets via multisensored aerial robot
- General Purpose Datasets with user specified sensor(s)
- Testing and Evaluation of Mobility Algorithms for Ground Robot
- Testing and Evaluation of Mobility Algorithms for an Aerial Robot
- Design of test environments for physical testing
- Design of testing protocols for physical testing
- Design of evaluation metrics for the results of physical testing
- Desk assessment activities for physical systems
- Preparation of physical test environment
- Support in interconnecting system under test to AgrifoodTEF’s physical infrastructure
- Execution of physical testing
- Collection of test data during physical testing
- Evaluation of results of physical testing
- Data validation and processing services
- LCA analysis
- Training services
- Edge intelligence and IoT architectures testing and benchmarking
- AI hardware performance assessment
- AI algorithms performance assessment
- Data valorization and dataspace integration assessment
- Design of computational environments for digital testing
- Design of testing protocols for digital testing
- Design of evaluation metrics for the results of digital testing
- Desk assessment activities for digital systems and/or data
- Preparation of digital test environment
- Support in interconnecting system under test to AgrifoodTEF’s computational infrastructure
- Execution of digital testing
- Collection of test data during digital testing
- Evaluation of results of digital testing
- Testing and experimentation of environment mapping for precision agriculture applications
- Testing Integration and performance of advanced weather forecasting
- Testing for safety in alignment with relevant legislation
- Testing of translation solutions for multilingual applications
- IoT and Blockchain enabling technologies to measure and improve workplace safety
- Design and implementation of certified smart irrigation systems
- Design and implementation of certified smart fertilisation systems
- Combating forgery in the agri-food chain
- Improve energy efficiency along agricultural value chains
- IoT weather predictive models and greenhouse gas emissions from agriculture
- UAV-based remote sensing for supporting precision agriculture
- Wireless communication infrastructure serving the agricultural
- Blockchain in agriculture traceability systems
- Cold chain monitoring
- Applications of artificial intelligence and visual recognition for assessing quality of agri-food industry products
- Test and development of innovative and practical agri-food applications of the metaverse.
- Navigation for ground robots in plots of land
- Precision weed mapping
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- Expand training datasets by using synthetic data based on existing datasets
- Usability & UX testing
- Test design: definition of the test environment
- Test design: definition of the test protocol
- Test design: definition of the test evaluation
- Desk assessment activities
- Testbed preparation
- Support for interconnection of the system under test to agrifoodTEF’s technical infrastructure
- Test execution services
- Data collection services
- Performance evaluation services
- Data validation and processing services
- LCA assessment
- AI-Testfield – Demonstration
- AI-Testfield – Development
- UAV-Testfield – Development
- Datasets - Benchmark
- High-Value-Testfield – Usability / UX
- Robotic Integration - Algorithms
- Testing - Cybersecurity
- AI-Testfield – Model Improvement / Adaptation
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Model Improvement / Adaptation
- AI Integration - Algorithms
- AI Integration - Predictive System
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Validation and development of AI-powered agricultural irrigation systems
- Virtual training for crops, livestock, and food processing
- Conformity roadmap for an innovation
- Compliance for robotic machine
- Compliance for AI innovation
- Conformity and Safety tests
- Test of error handling and failiure monitoring
- Policy Lab
- Expand training datasets by using synthetic data based on existing datasets
- Evaluation of applied natural language processing
- Evaluation of readiness for testing
livestock farming
- Testing of reticulo-ruminal motility measuring systems
- Testing of activity measurement of an animal health monitoring system
- Testing of the heat detection function of an animal health monitoring system
- Assessment of environmental impacts when applying digital technologies in agriculture
- Mediation and networking
- Datasets
- AI Model Training and Benchmarking
- Data analysis
- Data augmentation
- AI model training traceability
- Test and validate intelligent solutions based on sensors to optimize livestock farming
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC2 - Qualification of trajectory execution accuracy of livestock robots (in-door & out-door mobility).
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- Provision of datasets for AI training
- Livestock expertise
- Data labeling
- Data analysis
- Datasets and infrastructure for automatic monitoring of daily individual liveweigth in small ruminants
- Eggs detection
- Goat detection
- Behavior via accelerometers
- Provision of datasets for AI training: photo and video
- Provision of datasets for AI training: feed intake datasets
- Provision of datasets for AI training: health datasets
- Provision of a virtual computing infrastructure
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Edge intelligence and IoT architectures testing and benchmarking
- AI hardware performance assessment
- Testing Integration and performance of advanced weather forecasting
- Testing of translation solutions for multilingual applications
- Co-design of Robotic and AI systems and components for livestock farming solutions
- Test, validation and data collection of Robotic and AI systems and components for livestock farming solutions on Farm of the Future
- Business Model and Market development support for Robotic and AI solutions in livestock farming
- Provision of specific and long term data sets for arable and livestock farming data from the Farm of the Future experimental farms
- Data analysys support for specific and long term data sets for arable and livestock farming data sets
- Fenotyping support for AI and robotic based plant and livestock data handling and modelling (outdoor + indoor)
- R&D support AI development and robotics crops, livestock and post harvest
- Provision of Farmmaps platform to support Precison farming and KPI accounting data services
- Support in using explainable AI Models (simulation, early warning, DSS) and Digital Twins for crop and livestock management
- ELSA scan and support for AI and Robotic applications -- Ethical, Legal and Social Aspects
- Value Sensitive Design support in AI-and Robotic developments
- Business Innovation support using the 5D model of business innovation (modelling)
- User Acceptance Testing (UAT) of AI and robotic solutions
- Cultivating Data in Farming with Semantic Standards and Interoperability Support
- Provision of Agro Data Cube platform for data handling
- Training for AI- and Robotic Skills and Education, MOOCs
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- AI-Testfield – Demonstration
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Algorithms
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Virtual training for crops, livestock, and food processing
- Conformity roadmap for an innovation
- Compliance for robotic machine
- Compliance for AI innovation
- Conformity and Safety tests
- Test of error handling and failiure monitoring
- Experimentation AI Livestock production
- Experimentation Robotics Livestock production
- Experimentation UAV Livestock production
- Policy Lab
- Validation of work result under real conditions livestock robotics
- Validation of work result under real conditions livestock sensors and decision support systems
- Validation of work result under real conditions livestock UAV
- Expand training datasets by using synthetic data based on existing datasets
- Evaluation of applied natural language processing
- Evaluation of readiness for testing
tree crops
- Testing of weeding performance
- Testing of crop detection
- Testing of weed detection
- Providing dataset for training purpose
- Providing benchmark dataset
- Usability & UX testing
- Testing of Follow-me function of a robot
- Testing of person detection function of a robot
- Testing of field navigation
- Testing of sensor performance
- AI Model Training and Benchmarking
- Data analysis
- Data augmentation
- Test suitability of an agricultural implement on an autonomous carrier platform
- Performance evaluation of an AI model
- Robotic Software Framework
- Evaluation of the performance of crop protection equipment
- Provision of physical testing and experimentation facilities to enable the evaluation of AI systems
- Validation and testing UAV-remote sensing products
- UAV: Collection of test data during physical testing
- UAV: Evaluation of results of physical testing
- AI model training traceability
- Validation of Yield Estimation based on Computer Vision
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC1 - Qualification of trajectory execution accuracy of crop production robots (out-door mobility).
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- General Purpose Datasets via Multisensored Ground Robot
- General purpose datasets via multisensored aerial robot
- General Purpose Datasets with user specified sensor(s)
- Testing and Evaluation of Mobility Algorithms for Ground Robot
- Testing and Evaluation of Mobility Algorithms for an Aerial Robot
- Co-designing tools, e.g., image analysis tool for quantitative field phenotyping (phenology, crop production)
- Testing of sensor technology (irrigation scheduling)
- Testing of proximal sensing technology (spectral indices)
- Testing of remote sensing technology (spectral indices)
- Edge intelligence and IoT architectures testing and benchmarking
- AI hardware performance assessment
- AI algorithms performance assessment
- Data valorization and dataspace integration assessment
- Testing and experimentation of environment mapping for precision agriculture applications
- Testing Integration and performance of advanced weather forecasting
- Testing for safety in alignment with relevant legislation
- Testing of translation solutions for multilingual applications
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- AI-Testfield – Demonstration
- UAV-Testfield – Development
- Datasets - Benchmark
- High-Value-Testfield – Usability / UX
- Robotic Integration - Algorithms
- Testing - Cybersecurity
- AI-Testfield – Model Improvement / Adaptation
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Model Improvement / Adaptation
- AI Integration - Algorithms
- AI Integration - Predictive System
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Validation and development of AI-powered agricultural irrigation systems
- Virtual training for crops, livestock, and food processing
- Conformity roadmap for an innovation
- Compliance for robotic machine
- Compliance for AI innovation
- Conformity and Safety tests
- Test of error handling and failiure monitoring
- Policy Lab
- Expand training datasets by using synthetic data based on existing datasets
- Evaluation of applied natural language processing
- Evaluation of readiness for testing
viticulture
- Testing of weeding performance
- Testing of crop detection
- Testing of weed detection
- Providing dataset for training purpose
- Providing benchmark dataset
- Usability & UX testing
- Testing of Follow-me function of a robot
- Testing of person detection function of a robot
- Testing of field navigation
- Testing of sensor performance
- AI Model Training and Benchmarking
- Data analysis
- Data augmentation
- Test suitability of an agricultural implement on an autonomous carrier platform
- AI model training traceability
- Validation of Yield Estimation based on Computer Vision
- Qualification of safety systems providing obstacle detection and robot safety functions (ISO 18497 reference obstacle)
- ARPA 2 - Qualification of perception systems in harsh environmental conditions (rain, fog, night)
- ARPA 3 - Qualification of safety functions ensuring robots keep within their working area (physical or virtual barriers)
- ARPA 4 - Qualification of safety systems for human detection and collision avoidance (diverse working environments)
- ARPA PC1 - Qualification of trajectory execution accuracy of crop production robots (out-door mobility).
- AI performance evaluation based on physical testing environments
- Evaluation of the efficiency of the hardware associated with the AI functionality
- Dataset provision - general
- Dataset quality assessment
- AI performance evaluation based on testing datasets
- Automatic machines and Agricultural robots
- Automatic machines and Agricultural robots
- Automatic machines and Agricultural robots
- AI performance evaluation based on mixed testing environments
- AI robustness evaluation based on testing datasets
- AI resilience evaluation
- AI explainability evaluation
- AI processes certification
- Provision of datasets for AI training in real vinegrowing conditions
- Viticulture expertise for data collection on AI issues
- Data labelling for AI detection purposes in the vineyard
- Data analysis for AI performance evaluation in a real vineyard
- Provision of dedicated and private experimentation facilities on a real vineyard
- Provision of support and expertise for Robotic developments and testing in viticulture
- General Purpose Datasets via Multisensored Ground Robot
- General purpose datasets via multisensored aerial robot
- General Purpose Datasets with user specified sensor(s)
- Testing and Evaluation of Mobility Algorithms for Ground Robot
- Testing and Evaluation of Mobility Algorithms for an Aerial Robot
- Design of test environments for physical testing
- Design of testing protocols for physical testing
- Design of evaluation metrics for the results of physical testing
- Desk assessment activities for physical systems
- Preparation of physical test environment
- Support in interconnecting system under test to AgrifoodTEF’s physical infrastructure
- Execution of physical testing
- Collection of test data during physical testing
- Evaluation of results of physical testing
- Data validation and processing services
- LCA analysis
- Training services
- Edge intelligence and IoT architectures testing and benchmarking
- AI hardware performance assessment
- AI algorithms performance assessment
- Data valorization and dataspace integration assessment
- Design of computational environments for digital testing
- Design of testing protocols for digital testing
- Design of evaluation metrics for the results of digital testing
- Desk assessment activities for digital systems and/or data
- Preparation of digital test environment
- Support in interconnecting system under test to AgrifoodTEF’s computational infrastructure
- Execution of digital testing
- Collection of test data during digital testing
- Evaluation of results of digital testing
- Testing and experimentation of environment mapping for precision agriculture applications
- Testing Integration and performance of advanced weather forecasting
- Testing for safety in alignment with relevant legislation
- Testing of translation solutions for multilingual applications
- AI Integration - Data Storage
- AI Integration - V-Server / PaaS/ AI platform
- AI Integration - Computation Power
- AI-Testfield – Co-design Robots
- Datasets - Real-World Training
- Usability & UX testing
- Test design: definition of the test environment
- Test design: definition of the test protocol
- Test design: definition of the test evaluation
- Desk assessment activities
- Testbed preparation
- Support for interconnection of the system under test to agrifoodTEF’s technical infrastructure
- Test execution services
- Data collection services
- Performance evaluation services
- Data validation and processing services
- LCA assessment
- High-Value-Testfield – Usability / UX
- AI-Testfield – Model Improvement / Adaptation
- Datasets - Real-World Training
- Physical Edge-HW Benchmark
- AI Integration - Model Improvement / Adaptation
- AI Integration - Algorithms
- AI Integration - Predictive System
- Conformity assessment and safety tests
- Testing of error handling, failure monitoring and cybersecurity assessment
- Policy Lab
- Validation and development of AI-powered agricultural irrigation systems
- Virtual training for crops, livestock, and food processing
- Conformity and Safety tests
- Test of error handling and failiure monitoring
- Policy Lab