COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH
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 prompt...
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| Format: | Article |
| Language: | English |
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Nigerian Defence Academy
2025-04-01
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| Series: | Academy Journal of Science and Engineering |
| Subjects: | |
| Online Access: | https://ajse.academyjsekad.edu.ng/index.php/new-ajse/article/view/625 |
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| author | Dennis Redeemer Korda Nicholas Naawe Eric Ayintareba Akolgo Obeng Owusu-Boateng |
| author_facet | Dennis Redeemer Korda Nicholas Naawe Eric Ayintareba Akolgo Obeng Owusu-Boateng |
| author_sort | Dennis Redeemer Korda |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-c8dccf555c10443f84db4e9a976da03c |
| institution | OA Journals |
| issn | 2734-3898 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Nigerian Defence Academy |
| record_format | Article |
| series | Academy Journal of Science and Engineering |
| spelling | doaj-art-c8dccf555c10443f84db4e9a976da03c2025-08-20T01:48:24ZengNigerian Defence AcademyAcademy Journal of Science and Engineering2734-38982025-04-01191102115596COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACHDennis Redeemer Korda0Nicholas Naawe1Eric Ayintareba Akolgo2Obeng Owusu-Boateng3 Department of Computing & Info. Tech., Bolgatanga Technical University, Bolgatanga, GhanaDepartment of Mechanical Engineering, Bolgatanga Technical University, Bolgatanga, GhanaDepartment of Computer Science, Regentropfen University College, Bolgatanga, GhanaDepartment of Mathematics/ICT, E.P College of Education, Bimbila, GhanaGalamsey, 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.https://ajse.academyjsekad.edu.ng/index.php/new-ajse/article/view/625artificial intelligencegalamseyillegal small-scale miningconvolutional neural networksmining and drone surveillance |
| spellingShingle | Dennis Redeemer Korda Nicholas Naawe Eric Ayintareba Akolgo Obeng Owusu-Boateng COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH Academy Journal of Science and Engineering artificial intelligence galamsey illegal small-scale mining convolutional neural networks mining and drone surveillance |
| title | COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH |
| title_full | COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH |
| title_fullStr | COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH |
| title_full_unstemmed | COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH |
| title_short | COMBATING ILLEGAL SMALL-SCALE MINING (GALAMSEY) IN GHANA WITH ARTIFICIAL INTELLIGENCE: A COMPREHENSIVE APPROACH |
| title_sort | combating illegal small scale mining galamsey in ghana with artificial intelligence a comprehensive approach |
| topic | artificial intelligence galamsey illegal small-scale mining convolutional neural networks mining and drone surveillance |
| url | https://ajse.academyjsekad.edu.ng/index.php/new-ajse/article/view/625 |
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