Artificial Intelligence, Machine Learning, and Autonomous Technologies in Mining Industry
By Zeshan Hyder, Keng Leng Siau, Fiona Fui-Hoon Nah. 2019
95 citations recorded by the source corpus.
The implementation of artificial intelligence (AI), machine learning, and autonomous technologies in the mining industry started about a decade ago with autonomous trucks. Artificial intelligence, machine learning, and autonomous technologies provide many economic benefits for the mining industry through cost reduction, efficiency, and improving productivity, reducing exposure of workers to hazardous conditions, continuous production, and improved safety. However, the implementation of these technologies has faced economic, financial, technological, workforce, and social challenges. This article discusses the current status of AI, machine learning, and autonomous technologies implementation in the mining industry and highlights potential areas of future application. The article presents the results of interviews with some of the stakeholders in the industry and what their perceptions are about the threats, challenges, benefits, and potential impacts of these advanced technologies. The article also presents their views on the future of these technologies and what are some of the steps needed for successful implementation of these technologies in this sector.
Subfields: Control and Systems Engineering, Mechanical Engineering, Radiological and Ultrasound Technology, ML Systems & Hardware
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Citations in the corpus
- Measuring the Carbon Intensity of AI in Cloud Instances (2022, background): “AI models continue to be used for oil exploration [32], deforestation [30], and mining [18], among other environmentally-detrimental practices.”
- An integrated artificial intelligence framework for knowledge creation and B2B marketing rational decision making for improving firm performance (2021, methodology): “Autonomous mining haulage trucks, loaders and excavators are gaining popularity as they can operate for 24 × 7 continuously (Hyder et al., 2019).”