Catalogue of Services

Evaluation of Precision Herbicide Application Systems

Universitat de Lleida (UdL)

Location

At user's premises

Spain

Arable farming

Horticulture

This service tests the performance, efficacy and efficiency of herbicide application systems that use AI and robotics to optimise spray treatments, including spot spraying booms and variable-rate applicators. It evaluates the system’s ability to apply herbicides accurately, reducing usage while maintaining effective weed control. Through controlled field experiments and real-farm testing, we assess herbicide savings, weed control effectiveness, crop yield impact and environmental benefits compared to conventional broadcast spraying methods. The service also validates the system's adaptability to different environmental conditions, such as varying soil types, weather, and crop growth stages, and it is applicable to herbaceous and arable crops, offering valuable insights for improving targeted weed control and reducing unnecessary herbicide use.

Evaluation of sprayer boom for spot spraying site-specific applications

Universidad de Córdoba

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service evaluates the efficiency of sprayer booms equipped with sensors that use artificial vision to detect weeds and enable site-specific phytosanitary applications. Through field tests and drone-assisted monitoring, the service examines how accurately the sprayer boom applies treatments, identifying false positives (detecting weeds where none exist) and false negatives (failing to detect actual weeds). The service is essential for improving precision agriculture practices in arable and horticultural crops, as well as in tree crops and viticulture.

Evaluation of the framework and internal functioning of virtual assistants

Universidad de Córdoba

Location

Remote

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

Technical evaluation of frameworks developed for the creation of virtual assistants, focusing on elements such as the underlying architecture, natural language processing methods, and interactions with databases. Tests will include measuring response times, the ability to handle simultaneous queries, and overall system efficiency. Potential security vulnerabilities will also be identified, with recommendations proposed to strengthen data protection.

Experimentation implementing robotics in agricultural processes

Hispatec

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This pilot service focuses on the integration of robotic systems into agricultural processes, enabling the automation of key tasks such as planting, harvesting, and crop monitoring. By combining robotics with advanced software, this service improves operational efficiency, reduces labor costs, and enhances the precision of agricultural tasks. The integration ensures that robotic systems work seamlessly within existing workflows and provide consistent, high-quality performance.

Experimentation with Artificial Intelligence for Agricultural Optimisation

Hispatec

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service applies artificial intelligence (AI) algorithms to process and analyse large datasets collected from agricultural operations. By leveraging machine learning and data analytics, the service generates predictive insights about crop needs, such as water, fertilizer, and pest control, allowing for more accurate and efficient resource use. The AI-driven approach helps farmers and agribusinesses optimise their production processes, reduce waste, and improve yields by making data-driven decisions.

Generation of datasets using network-connected sensors

Gradiant Technologies

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 Technologies

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. 

Lab testing and validation of non-destructive spectral devices focused on agri-food products

Universidad de Córdoba

Location

Spain

Food processing

Horticulture

Tree Crops

Viticulture

This service supports companies that are developing non-destructive spectral (NDS) instrumentation for agri-food applications, providing validation studies focused on spectral repeatability, signal-to-noise ratio, and quality assessment. Using a well-equipped sensor lab, the service includes comparisons with commercially available instruments and access to a referenced agri-food sample bank. By conducting repeatability and performance assessments, clients gain insights into device robustness and potential design improvements.

Optimised Irrigation Scheduling for Smart Agriculture

Hispatec

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This experimental service offers agrotech companies customised irrigation schedules based on real-time and historical data analysis. By taking into account soil moisture levels, weather conditions, and crop requirements, the service generates irrigation plans that improve efficiency and crop yields. The service delivers detailed reports with actionable insights, ensuring that water is used efficiently without compromising crop health.

Performance Data Collection for Agricultural Technologies

Hispatec

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This experimental service involves monitoring and collecting performance data from newly implemented technologies in agricultural production environments. Data is collected in real-time or at regular intervals, capturing key metrics such as water or energy usage, production yield, and overall efficiency. This data helps in evaluating the system’s performance and provides valuable insights for further optimisation and decision-making.

Performance Evaluation and Efficiency Measurement Experimenting with Different Agricultural Technologies

Hispatec

Location

Spain

Arable farming

Greenhouse

Horticulture

Tree Crops

Viticulture

This service evaluates the performance of newly implemented agricultural technologies by analysing key performance metrics such as resource usage, production yield, and cost savings. The evaluation compares the technology's projected benefits against real-world performance data, identifying areas where the system is performing well and areas where improvements can be made. The goal is to provide a clear picture of the technology's effectiveness and its impact on the overall production process.

Performance testing of deep learning solutions

Universidad de Córdoba

Location

Remote

Spain

Arable farming

Food processing

Greenhouse

Horticulture

Livestock farming

Tree Crops

Viticulture

This service evaluates the performance of deep learning algorithms to determine their efficiency and feasibility for migration to embedded devices. By leveraging high-performance computing (HPC) and GPU resources, this testing helps developers understand how well their algorithms perform in terms of speed, accuracy, and resource consumption. The service is particularly beneficial for applications in food processing, such as beekeeping and pollen counting, where real-time data processing is essential.