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Nalbantov, G. I., Smirnov, E. N., Nalbantov, D. I., Weiss, G., Nienhaus, K., Warcholik, M., & Mavroudis, F. (2010). Image Mining for Intelligent Autonomous Coal Mining. Industrial Conference on Data Mining-Poster and Industry Proceedings, Berlin, Germany, July 2010, 17-23.

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• TITLE: Safety Measurements and Risk Assessment of Coal Mining Industry Using Artificial Intelligence and Machine Learning

  AUTHORS: Sundas Matloob, Yang Li, Khurram Zaman Khan

  KEYWORDS: Artificial Intelligence, Smart Mining, Risks Assessment, Coal Mining, Economic Benefits

  JOURNAL NAME: Open Journal of Business and Management, Vol.9 No.3, May 21, 2021

  ABSTRACT: Safety is a legal requirement of mining industry. Effective safety measurements and risk management can serve the mine administration to lessen the dangers recognized in the mine. Autonomous technologies, such as Artificial Intelligence (AI) and Machine Learning (ML) models have been integrated with the mining industry to ensure a safe working environment since a decade ago in the form of fully unmanned workfaces and mining robots. These autonomous technologies provide effective risk assessment as well as many economic profits such as cost reduction, continuous production, reducing labors exposure in dangerous environments, and enhanced protection. The main objective of this paper is to highlight the unidentified hazards during mining and find the solutions to those hazards by using AI and Machine Learning. In addition, this paper will also contribute a worthy resource for explaining the AI advancements in risk assessment in the mining industry. Another advantage of this paper is to fill the gaps in modern techniques and AI advancements in the safety measurements of coal mining industry.