TY - JOUR
T1 - Artificial intelligence, machine learning, and autonomous technologies in mining industry
AU - Hyder, Zeshan
AU - Siau, Keng
AU - Nah, Fiona
N1 - This has been reprinted in: Hyder, Z., Siau, K., & Nah, F. (2022). Artificial Intelligence, Machine Learning, and Autonomous Technologies in Mining Industry. In Research Anthology on Cross-Disciplinary Designs and Applications of Automation (pp. 478-492). IGI Global. https://doi.org/10.4018/978-1-6684-3694-3.ch024
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
KW - Artificial Intelligence
KW - Autonomous Technology
KW - Autonomous Trucks
KW - Challenges of AI and Machine Learning
KW - Machine Learning
KW - Mining Industry
UR - http://www.scopus.com/inward/record.url?scp=85068701748&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85068701748&origin=recordpage
U2 - 10.4018/JDM.2019040104
DO - 10.4018/JDM.2019040104
M3 - RGC 21 - Publication in refereed journal
SN - 1063-8016
VL - 30
SP - 67
EP - 79
JO - Journal of Database Management
JF - Journal of Database Management
IS - 2
ER -