Abstract: A digital twin based method for monitoring behavior of a passenger on an escalator includes: first, constructing a digital twin virtual scene of the escalator carrying the passenger; constructing a virtual person model in a physics engine, generating various types of risky behavior in reality, and outputting different types of behavior of a virtual person; second, through a human posture recognition method for monitoring behavior of a passenger, extracting a feature map as an input by means of a visual geometry group 19 (VGG19) pre-training network, to enter part affinity fields (PAFs) and a part confidence map (PCM), so as to complete recognition of human postures; classifying the human postures with a support vector machine; and performing emergency stop control on the escalator under risky behavior of the passenger according to a result of posture classification.