The RESSAIG project (Renewable Energy Site Selection using Artificial Intelligence and Geographic Information System) aims to enhance the identification and development of sites for clean renewable energy sources, such as photovoltaic (PV) arrays and both onshore and offshore wind farms. Utilizing a blend of Artificial Intelligence (AI), deep learning, remote sensing data, Geographic Information Systems (GIS), and government datasets, the project seeks to optimize site selection for renewable energy and water desalination necessary for hydrogen production. Amidst the global shift towards sustainable energy solutions to combat climate change, there is an urgent need for more efficient and precise methods for identifying optimal sites for renewable energy installations. Traditional methods often overlook critical environmental, economic, and social factors that RESSAIG's integrative approach will consider, thus ensuring more sustainable and economically viable energy production. The urgency for sustainable and low-carbon energy solutions is accentuated by increasing environmental concerns and international commitments to reduce carbon footprints. RESSAIG's advanced mapping technologies come at a crucial time to meet the growing demand for renewable energy infrastructure and support the transition towards green hydrogen as a key energy carrier for the future. Our team brings together leading experts in AI, GIS, remote sensing, and renewable energy, uniquely positioning us to tackle this complex challenge. Our interdisciplinary approach combines cutting-edge technology with extensive field knowledge, enabling us to provide innovative solutions that are both scientifically rigorous and practically applicable. RESSAIG enhances renewable energy site selection, reducing costs and driving investment through detailed cartographies and economic analyses, fostering informed decisions and promoting sustainability, economic growth, and job creation.