TY - JOUR PY - 2021// TI - Understanding human behaviors and injury factors in underground mines using data analytics JO - Annual International Conference of the IEEE Engineering in Medicine and Biology Society. A1 - Liu, Xinyun A1 - Liu, Zhen A1 - Chatterjee, Snehamoy A1 - Portfleet, Matthew A1 - Sun, Ye SP - 2459 EP - 2462 VL - 2021 IS - N2 - 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.

Language: en

LA - en SN - 2375-7477 UR - http://dx.doi.org/10.1109/EMBC46164.2021.9630428 ID - ref1 ER -