Οn 10 September 2024, a new publication titled “A Generalized Machine Learning Approach for Cost-Effective Monitoring of Irrigation Suitability: A Case Study in El Fahs Aquifer (Tunisia)” was released as part of the AI-OBSERVER project, in collaboration with the University of Cyprus and INAT. It has been published in Groundwater for Sustainable Development (Elsevier, IF: 5). The authors are Dr. Constantinos Panagiotou (ERATOSTHENES Centre of Excellence), Dr. Charalampos Konstantinou (University of Cyprus), and Professor Anis Chekirbane (INAT). Available at: https://doi.org/10.1016/j.gsd.2024.101324