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Combating Illegal Small-scale Mining (galamsey) in Ghana With Artificial Intelligence: a Comprehensive Approach

Year: 2025

Type: article

Abstract: 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.

Source: DOAJ (DOAJ: Directory of Open Access Journals)

Authors: Dennis Redeemer Korda, Nicholas Naawe, Eric Ayintareba Akolgo, Obeng Owusu-Boateng

Institutions: Bolgatanga Technical University, Regentropfen University College, Evangelical Presbyterian College of Education, Bimbilla

Language: English

Topic: Mining and Resource Management

Subfield: Building and Construction

Field: Engineering

Domain: Physical Sciences

SDG: Industry, innovation and infrastructure

Open Access status: green

OpenAlex ID: W7046107227

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