Understanding Human Behaviors and Injury Factors in Underground Mines using Data Analytics

Document Type

Conference Proceeding

Publication Date



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.

Publication Title

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)