A Geo-AI Approach for Electric Vehicle Charging Infrastructure Allocation: Case Studies from Marrakech-Safi Region, Morocco, and Andalucia Region, Spain

The rise of electric vehicles (EVs) in Morocco’s Marrakesh-Safi region and Spain’s Andalucia demands a well-developed network of charging stations. This network would make charging EVs convenient, leading to more people choosing sustainable transportation. This study uses a Geo-Spatial Artificial Intelligence (GEO-AI) approach to pinpoint the best places to put these stations. We considered both technical factors and social and economic ones. To identify promising areas, we used clustering algorithms along with the Elbow Method. Then, we used a Random Forest algorithm to choose the exact spots within those areas. Our research shows that the best places for charging stations are cities, including Marrakesh, Benguerir, Safi, Essaouira, and Kelaat Seraghna in Marrakesh-Safi, and Seville, Malaga, and Cádiz in Andalucia. Model evaluation demonstrates the efficacy of the Random Forest model in placement prediction. The outcomes results highlight how RF-based prediction models can improve e-mobility infrastructure not only in the cities studied but also in other African and European urban areas.