Underground Personnel Trajectory Mining Method Based on Key Areas

A trajectory mining framework for underground personnel based on key areas is proposed. The framework consists of key location discovery algorithm and moving object trajectory mining algorithm. Firstly, the key location discovery algorithm is used to transform the positioning data under the mine into a key position sequence with specific semantics. Then the moving object trajectory mining algorithm is used to cluster the key position sequences into key regions, so as to find the daily trajectory of the moving objects in the underground, and then use the trajectory. Structural similarity screens out anomalous trajectories. Experiments using miners’ positioning datasets show that the trajectory mining framework based on key areas solves the problem of multi-density area identification, which can accurately identify the daily trajectory and abnormal trajectory of miners.