AI4RealAg
AI4RealAg
About the Project
This project, under the code LISBOA-01-0247-FEDER-069670 and POCI-01-0247-FEDER-069670, embodies the core aim of enhancing research, technological development, and innovation. Focused on the regions of Lisboa, Center, and Alentejo, it brings together key beneficiary entities, including SISCOG – Sistemas Cognitivos, S.A., Beyond Vision – Sistemas Móveis Autónomos de Realidade Aumentada, Lda, and the Instituto Nacional de Investigação Agrária e Veterinária, I.P.
Approved on May 24, 2021, this project commenced on September 1, 2020, and is slated for completion on June 30, 2023. With a total eligible cost of 2,661,843.68 Euros, it benefits from significant financial support of 1,562,945.17 Euros from the European Union’s European Regional Development Fund, paving the way for innovative Artificial Intelligence and Data Science solutions to drive the implementation and democratization of digital agriculture through AI4RealAg.
Goals, activities and expected results
Develop AI and Data Science
Develop Artificial Intelligence (AI) and Data Science models that, through the analysis of large volumes of data, enable to uncover hidden knowledge from data, such as patterns, trends and correlations, which support smarter decision-making, as well as preparation of forecasts
Advanced Sensing Solutions
In order to ensure AI4RealAg produces the best quality result, we developed a comprehensive solution that combines remote multispectral, thermal, 4K, 360º, and LiDAR sensing. By exploring larger drone payloads, we aim to enhance data quality, which in turn feeds our AI and Data Science models for advanced agricultural analysis.
The project addresses six topics
phenological states
Characterization of the phenological states of cultures
cultural coefficients
Determination of cultural coefficients
water stress
Estimation of the intensity of water stress;
nutritional status
Diagnosis of nutritional status
detection of diseases
Health diagnosis for early detection of diseases
phenotyping platform
Development of an advanced phenotyping platform
