Understanding Human Behaviors and Injury Factors in Underground Mines using Data Analytics
Department of Civil, Environmental, and Geospatial Engineering; Department of Geological and Mining Engineering and Sciences; Department of Mechanical Engineering-Engineering Mechanics
This study aims to understand human behaviors and associated injury causing factors in underground mines using data analytics of historical mining data. Decision tree and association rule were used to provide a statistical analysis of leading factors of hazards in underground mines. Based on the results, we were able to explore hazard feature identification using image feature recognition aiming to provide real-time monitoring for miners to secure healthy and safety operation via wearable computing.
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Understanding Human Behaviors and Injury Factors in Underground Mines using Data Analytics.
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/16092