Intelligent
Agriculture
Development project of an intelligent system for extracting knowledge from large volumes of data through the application of Artificial Intelligence and Data Science techniques.
The data is obtained through combined remote sensing techniques with drones, satellites and sensors in the field.
The knowledge generated supports farmers' decisions in the field of planning and management of agricultural production.
Increased productivity
of crops
Analysis of the phenological states of crops allows for better planning of farming operations. Early detection of diseases prevents crop deaths. Diagnosis of nutritional status allows detecting deficiencies. Phenotyping allows to better understand the potential of cultures.
Increased quality
of food
Correct management of water stress intensity and of the ideal level of fertilizers allows for better quality food.
Optimisation
of resources
Determining cultural coefficients and applying deficit irrigation strategies allow for better use of water. Assessing the nutritional status of crops allows for better use of nutrients.
Provide an increase in agricultural production and food quality in an environmentally sustainable way, through preventive or corrective actions
At the service of the farmer
We use drones with different sensors to obtain data from various bands of the electromagnetic spectrum, from regions visible to the human eye to the infrared, as well as from the thermal band.
We reconstruct a digital model of the terrain in three dimensions, from the images acquired by the drones, after orthorectification.
We combine all different types of data with innovative fusion techniques that allow to obtain more expressive information.
We apply innovative Data Science techniques that ensure more efficient extraction of knowledge hidden in the data.
And we offer:
including general crop statistics and indicators for each plant, for a more informed, rational and optimised agricultural culture and harvest.
NDVI (Normalized Difference Vegetation Index) per plant
Partners
Co-financed by
