Artificial Intelligence Enhances Mining Safety with Natural Language Processing and Machine Learning

Strategic Insights -

Researchers at the Indian Institute of Technology have successfully applied artificial intelligence, specifically natural language processing (NLP) and machine learning (ML), to analyze coal mining accident reports and automate the process of root cause analysis. This research aims to prevent future accidents by leveraging the potential of NLP and ML algorithms to extract unstructured text from vast repositories of accident records. The proposed solution is the first attempt for Indian mines and combines LDA and RAKE algorithms to cluster accidents based on descriptions and generate root cause analysis through keywords from accident descriptions.

Key Takeaways:

  • The researchers proposed a solution that combines NLP and ML to analyze coal mining accident reports, utilizing LDA and RAKE algorithms to extract unstructured text and identify contributing factors.
  • The study used data from the Directorate General of Mines Safety (DGMS), India records from 2010 to 2015, to demonstrate the effectiveness of their approach.
  • The AI-powered system can extract, classify, and analyze data from incident reports and other relevant documents, enhancing the process of creating Swiss Cheese Models and Logic Sequences of Contributory Factors Diagrams.
  • The application of NLP and ML has the potential to significantly enhance mining safety by automating the identification of high-risk areas and recurring issues.
  • The research highlights the importance of proactive measures in preventing future accidents, enabling mining companies to take timely and effective actions.
  • The study involved a team of researchers from the Indian Institute of Technology, including Siddhartha Agarwal, Y. P. Chugh, Atul Singh, Vikram Sakinala, Ayan Mukherjee, Balbir Prasad, Cihan Dagli, and Yuhao Zou.

Statistics:

  • The study used data from 2010 to 2015, a total of 6 years of records from the DGMS.
  • The proposed system can efficiently analyze vast repositories of accident records, reducing the analysis time from months to seconds.
  • The application of NLP and ML algorithms can significantly enhance the accuracy of root cause analysis, enabling mining companies to take more informed decisions.
  • The study highlights the potential of AI to prevent accidents and ensure a safer working environment for miners, with a focus on automating the process of root cause analysis.

Sources:

  • "Application of natural language processing and machine learning for analyzing mining accident reports and automating the process of root cause analysis." International Journal of Coal Science & Technology, 2025, 12(1):1-33. (International Journal of Coal Science & Technology - http://www.springer.com/40789).
  • Indian Institute of Technology Researchers Describe Advances in Machine Learning (Application of natural language processing and machine learning for analyzing mining accident reports and automating the process of root cause analysis). Journal of Engineering. October 20, 2025; p 1157.