The Application of Artificial Intelligence to Reduce Greenhouse Gas Emissions in the Mining Industry

Ali Soofastaei

A chapter in Green Technologies to Improve the Environment on Earth from IntechOpen

Abstract: Mining industry consumes a significant amount of energy and makes greenhouse gas emissions in various operations such as exploration, extraction, transportation and processing. A considerable amount of this energy and gas emissions can be reduced by better managing the operations. The mining method and equipment used mainly determine the type of energy source in any mining operation. In surface mining operations, mobile machines use diesel as a source of energy. These machines are haul trucks excavators, diggers and loaders, according to the production capacity and site layout and they use a considerable amount of fuel in surface mining operation; hence, the mining industry is encouraged to conduct some research projects on the energy efficiency of mobile equipment. Classical analytics methods that commonly used to improve energy efficiency and reduce gas emissions are not sufficient enough. The application of artificial intelligence and deep learning models are growing fast in different industries, and this is a new revolution in the mining industry. In this chapter, the application of artificial intelligence methods to reduce the gas emission in surface mines with some case studies will be explained.

Keywords: artificial intelligence; deep learning; fuel consumption; gas emissions; mining operations; prediction models; optimization methods (search for similar items in EconPapers)
JEL-codes: Q55 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:ito:pchaps:161619

DOI: 10.5772/intechopen.80868

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