IVACE - FEDER CERES

Objective

The

general objective

of the CERES project is to develop a compact system for detecting diseases, pests and damage in crops based on photonic technologies and artificial intelligence that can be embedded in autonomous vehicles, capable of carrying out real-time diagnostics and displaying them through advanced augmented reality representations.

To this end, the research activity, developed in collaboration with companies in the definition of needs and in the experimentation and testing phase, will focus on achieving the following

specific objectives

Develop a compact processing unit with computing capacity for artificial intelligence algorithms optimised for agronomic use
Select the most suitable artificial intelligence techniques for analysing agronomic data captured with photonic technologies according to computational efficiency criteria
Implement a demonstrator for real-time processing of agronomic data captured with photonic technologies
Capture physical and chemical data from key crops in the Valencian Community and possible impacts affecting them through simple procedures using the developed platform
Physical and chemical modelling of diseases, pests and damage in key crops of the VC based on the data captured by the developed platform
Compare the predictive capacity existing in current agricultural practice in decision-making with the new methods and models developed in the project for the reference crops
Research advanced data representation in interfaces suitable for agronomy
Implementation of the demonstrator prototype and validation with companies
Disseminate the project results to all interested groups

Activities

Advanced sensorisation of robotic vehicles and real-time analysis.
Field experimentation in key crops of the VC.
Rapid disease diagnosis and application of artificial intelligence.
Advanced representation and augmented reality in the agricultural context.
Dissemination of results obtained.
Transfer of developed technology to companies.
Project coordination and management.

Results obtained

Compact and lightweight unit integrating photonic sensors and real-time computing capacity.
Artificial intelligence algorithms selected to be applied in the detection of diseases, pests and damage in real time from the spectral images obtained with the developed platform.
A demonstrator pilot in which the operation of the compact photonic agronomic data capture unit has been validated.

Project results report (PDF)