Validation of irrigation AI models through soil sensors and climatic data

Using data collected from soil sensors, the service tests the recalibration of irrigation models across various systems powered by artificial intelligence.

Interested in this service? Contact us at fmarquez@uco.es

Overview

This service focuses on the validation of intelligent irrigation systems through the recalibration of the model based on data obtained from soil sensors, and evaluation with other data sources. It includes physicochemical parameters of the soil, and variable distribution of water and supplies. Observations are systematic and cover different conditions and crops to verify model accuracy and the effectiveness of site-specific input distribution.

More about the service

Discover more about our service, including how it can benefit you, the delivery process, and the options for customisation tailored to your specific needs!

The validation of the service, developed by the customer, addresses the critical needs for optimised water distribution and improved agricultural efficiency. Before using this service, companies may struggle with inconsistent irrigation models, leading to either over- or under-irrigation, which can negatively impact crop health and yield. By extracting and analysing data from soil sensors, the service ensures that water and inputs are distributed accurately based on real-time conditions, crop types, and soil properties. After implementing the service, companies benefit from improved system accuracy, and enhanced productivity through tailored water and nutrient application across different crops and conditions.

The service is conducted at the Rabanales Experimental Farm facilities in Rabanales. To ensure accurate efficiency analysis, it is tailored to the crop cycle under evaluation. The crop must be one of those grown in the plots where the irrigation system being tested is installed. The customer is required to provide the mathematical irrigation model, and upon completion, will receive a comprehensive final report detailing the results of the service.

The service will be customized according to customer needs (model, irrigation system, crop, season…), and can be extended over the entire crop cycle, including extensive crops such as corn, wheat, or barley, as well as woody crops like olive or almond trees.
Location
Spain
Type of Sector
Arable farming
Horticulture
Tree Crops
Type of service
Collection of test data
Data analysis
Performance evaluation
Test design
Test execution
Test setup
Accepted type of products
Data
Physical system
Software or AI model