We would like to join a consortium on data collection and AI for the agricultural value chain, starting from production to the table (more specifically, greenhouse, vegetable, and fruit production), as we have broad interests and knowledge. Our current research focus is on sensing, AI, and autonomous technological solutions, besides decision-making supporting growers in making better-informed decisions that enhance the attractiveness of the sector, profitability, and sustainability.

Our institution has several core academic strengths: Research in sensor integration, machine vision, and the development of autonomous systems for crop monitoring and operations on FAIR data principles and AI applications. Works on climate change adaptation and farm performance assessment. Expertise contributes to creating practical tools for informed decision-making in the field. Provides critical support for the advanced modeling, including multivariate statistics, fuzzy logic, and robust regression models—essential for interpreting complex agricultural datasets.