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Combating Illegal Mining (Galamsey) In Ghana Using Artificial Intelligence (AI)

By Abraham Selby
Article Combating Illegal Mining (Galamsey) In Ghana Using Artificial Intelligence (AI)
THU, 06 JUN 2024 LISTEN

Illegal mining, commonly referred to as "galamsey" in Ghana, involves the extraction of minerals or precious metals without government authorization or licensing. This practice has become widespread in Ghana and other African countries, leading to severe environmental degradation, deforestation, and contributing to climate change. The need for innovative solutions to tackle this issue has never been more pressing. One such solution is the application of Artificial Intelligence (AI), which offers promising capabilities for monitoring and regulating mining activities.

Ghana's illegal gold miners (galamseyers) face significant mercury contamination and marginalization, but recognition and learning opportunities can help resolve the current impasse in the small-scale mining sector. (Tschakert, P., & Singha, K., 2007). Illegal mining in the Offin shelterbelt forest reserve, Ghana, has increased income, employment opportunities, and market activities, but has also degraded the reserve and threatened community livelihoods according to research by Boadi, et al. 2016.

The role of AI in mining

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. AI technologies include machine learning, computer vision, natural language processing, and robotics. In the context of mining, AI can be used to enhance exploration, optimize operations, ensure safety, and improve environmental sustainability.

AI as a guardian of the environment

AI can be an asset in the fight to protect our planet and Ghana needs to adapt to the changing world and its technological usage.

Resource Management: AI can analyze data on things like water usage or energy consumption to identify areas for conservation. This can help nations manage their resources more sustainably and reduce their environmental footprint.

Precision Agriculture: AI can be used to monitor crops and identify potential problems like pests or diseases. This allows farmers to take targeted action, reducing reliance on pesticides and ensuring better yields with less environmental impact.

Renewable Energy Integration: AI can help manage smart grids, allowing for better integration of renewable energy sources like solar and wind power. This can help nations transition away from fossil fuels and reduce greenhouse gas emissions.

Disaster Management: AI can be used to analyze weather patterns and predict natural disasters. This allows for early warnings and better preparedness, saving lives and minimizing damage to infrastructure.

AI Applications in Combating Illegal Mining

1. Monitoring and Surveillance
AI can be employed to monitor illegal mining activities through satellite imagery and drones equipped with computer vision technology. These systems can detect unauthorized mining operations, track the movement of excavators, and identify changes in land use patterns that indicate illegal mining activities. For instance, John Dramani Mahama, the flagbearer of the National Democratic Congress (NDC), has pledged to use AI to locate all small-scale mining and galamsey operations, track excavators, and geofence all concessions to help coordinate and monitor activities within the small-scale mining sector. (Citi Newsroom, 2024)

2. Geofencing
Geofencing involves creating virtual boundaries around specific geographic areas. AI can be used to establish geofences around authorized mining concessions, ensuring that mining activities do not encroach on protected areas such as water bodies and forests. This technology can send real-time alerts to authorities when illegal mining activities are detected within these geofenced areas.

3. Predictive Analytics
AI-driven predictive analytics can forecast potential illegal mining hotspots by analyzing historical data, environmental factors, and socio-economic conditions. This allows for proactive measures to be taken to prevent illegal mining before it occurs. Predictive models can also help in planning and optimizing legal mining operations, thereby reducing the incentive for illegal mining.

4. Community Reporting Tools:
AI can enhance community-based reporting systems where residents use mobile apps to report suspected illegal mining activities. Natural language processing (NLP) can analyze these reports to identify patterns and prioritize responses.

Successful Cases of AI in Mining

1. Pan African Resources (PAR)
Pan African Resources (PAR) has successfully implemented AI and other digital technologies to combat illegal mining in South Africa. By leveraging AI for geotechnical monitoring and predictive maintenance, PAR has improved safety standards and operational efficiency. The company has also used AI to enhance supply chain management, ensuring real-time visibility and optimization of logistics operations. (PAR, 2024)

2. Global Mining Industry
Globally, the mining industry has seen significant benefits from AI adoption. AI technologies have been used for exploration, geotechnical monitoring, mine planning, and supply chain management. These applications have led to increased productivity, reduced costs, and improved safety standards. For example, AI-driven predictive maintenance systems have minimized equipment downtime, enhancing overall operational efficiency. (Shabir, A., 2024)

Recommendations

The following recommendations are proposed to the Government of Ghana, security agencies, mining organizations, community leaders, chiefs, private sector organizations and other stakeholders, to help effectively combat illegal mining:

  1. Government and Private Sector Collaboration: Establish partnerships between the government, private sector, and academic institutions to develop and implement AI solutions tailored to the mining sector.
  2. Investment in AI Infrastructure: Invest in technology infrastructure, including satellite imagery, drones, and AI software, to support monitoring and surveillance efforts.
  3. Capacity Building: Provide training and resources to local authorities and mining communities to enhance their understanding and use of AI technologies. Investing in training programs for local authorities and communities on the use of AI tools is crucial. Enhancing the technical skills of law enforcement agencies will improve the effectiveness of AI-based interventions.
  4. Regulatory Framework: Develop a robust regulatory framework that supports the ethical use of AI in mining, the integration of AI in environmental monitoring, addressing concerns such as data privacy, explainability, and accountability.
  5. Public Awareness Campaigns: Conduct public awareness campaigns to educate communities about the environmental and economic impacts of illegal mining and the benefits of AI in promoting sustainable mining practices.
  6. Continuous Monitoring and Evaluation: Implementing a system for continuous monitoring and evaluation of AI interventions will help in assessing their effectiveness and making necessary adjustments. This adaptive approach ensures sustained impact in combating illegal mining.

Conclusion

AI offers promising solutions to the complex problem of illegal mining in Ghana. Through satellite imagery analysis, drone surveillance, predictive analytics, and community reporting tools, AI can significantly enhance the detection and prevention of unauthorized mining activities. Successful case studies demonstrate the practical benefits of AI applications, providing a model for broader implementation. By fostering strong partnerships, building capacity, and engaging communities, Ghana can harness the power of AI to protect its natural resources and ensure sustainable development. I can say that, while technology opens doors to incredible possibilities, it takes skilled people and the right infrastructure to turn those ideas into reality.

Author: Abraham Selby | PG, UCL, School of Public Policy, UK | Digital Analyst | Member - IIPGH, Internet Society (Ghana Chapter), ICANN.

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