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The mining industry operates within highly dynamic and hazardous environments where geological uncertainty, operational complexity, and human factors significantly elevate occupational risks. Effective risk identification and mitigation are therefore essential for ensuring sustainable mining operations and worker safety. This study presents a comprehensive framework for risk mapping and safety analysis in the Indian mining industry using qualitative, semi-quantitative, and quantitative risk assessment approaches. Hazard categories including geological, mechanical, environmental, and human-related risks were systematically evaluated using a risk matrix model based on likelihood and consequence analysis. The study identified roof falls and machinery failures as extreme-risk events demanding immediate intervention. Historical accident data from the Directorate General of Mines Safety (DGMS) between 2016 and 2022 indicate a gradual decline in fatality rates due to strengthened regulatory enforcement and improved technological adoption. The findings further demonstrate that the integration of Internet of Things (IoT)-based monitoring systems, artificial intelligence (AI), and GIS-enabled risk mapping substantially enhances hazard prediction and operational safety. The paper concludes with strategic recommendations emphasizing engineering controls, safety culture development, predictive analytics, and technological modernization for achieving sustainable and safer mining practices in India.
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Sudhakar Kumar Ravi
Kundan Kumar
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Ravi et al. (Sun,) studied this question.
www.synapsesocial.com/papers/6a0bfda5166b51b53d378ea2 — DOI: https://doi.org/10.5281/zenodo.20256590
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