COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH - Dennis Redeemer Korda; Nicholas Naawe; Eric Ayintareba Akolgo; Obeng Owusu-Boateng (Academy Journal of Science and Engineering)
Galamsey, also known as illegal small-scale mining, persists in causing significant damage to Ghana's environment, including water bodies, agricultural areas, and public health. The present study introduces a comprehensive approach that utilizes Artificial Intelligence (AI) technology to promptly identify, oversee, and forecast illicit mining operations. By employing satellite imaging, drone monitoring, predictive analytics, and machine learning models, we propose a scalable and effective method to reduce the environmental and economic impact of galamsey. A methodology is presented that describes the development and execution of an artificial intelligence system utilizing actual data from high-risk mining areas in Ghana. The present study provides empirical evidence supporting the efficacy of artificial intelligence (AI) in facilitating real-time surveillance and forecasting forthcoming illicit mining operations. Furthermore, we address possible obstacles, including technical constraints, privacy issues, and the scarcity of proficient staff, and provide suggestions for surmounting these hindrances.