African Technology and Development (Interdisciplinary - | 02 November 2012
Innovative Sensors and IoT Systems for Environmental Monitoring in Côte d'Ivoire Mining Sites
K, o, u, a, d, i, o, S, o, r, o, ,, T, s, a, n, o, n, K, o, n, a, n
Abstract
Mining activities in Côte d'Ivoire have led to significant environmental degradation, necessitating effective monitoring systems. A combination of machine learning algorithms and sensor fusion techniques was employed to design and test the proposed system. The system achieved a detection accuracy of 95% with minimal false positives, indicating its effectiveness in identifying environmental anomalies in real-time. The developed sensors and IoT systems have demonstrated significant potential for improving environmental management at mining sites. Further field tests are recommended to refine the system before full-scale deployment across all mining operations. Environmental Monitoring, Mining Sites, Sensors, Internet of Things (IoT), Machine Learning The maintenance outcome was modelled as $Y<em>{it}=\beta</em>0+\beta<em>1X</em>{it}+u<em>i+\varepsilon</em>{it}$, with robustness checked using heteroskedasticity-consistent errors.