Environmental monitoring in mining sites is crucial for ensuring safety and compliance with environmental regulations. A hybrid sensor network was deployed across multiple sites, integrating wireless communication devices to transmit data in real time. Data analysis utilised machine learning algorithms for anomaly detection. Real-time data indicated a significant decrease (35%) in particulate matter concentration within the mining area compared to ambient conditions, suggesting effective air quality control measures. The IoT systems demonstrated high reliability and robustness under various environmental conditions, facilitating timely intervention in case of anomalies. Further research should explore integration with existing regulatory frameworks for seamless monitoring and compliance. The maintenance outcome was modelled as Y₈ₓ=₀+₁X₈ₓ+uᵢ+₈ₓ, with robustness checked using heteroskedasticity-consistent errors.
Muhoro et al. (Thu,) studied this question.
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