Abstract
The massive machines connected to the industrial cyber-physical systems bring challenges to the machine management in the industrial human machine interaction (HMI). The engineer has to identify the target machine from a long list which is a non-trivial problem. Observing the fact that the industrial HMI is generally executed in a face-to-machine manner, the face-to-machine proximity estimation (FaceME) algorithm has been proposed to solve this problem. Nevertheless, due to the randomness of wireless signal, the estimation accuracy of FaceME is not sufficient in the scenarios with densely deployed machines. In this paper, we exploit the RSSI difference among multiple neighbors in the industrial HMI. Based on the analysis, we propose a face-to-machine proximity estimation algorithm called FaceME+ which takes advantages of the RSSI difference among multiple neighbors to improve the estimation accuracy. Its performance is studied on the mobile industrial HMI testbed, and the results prove the efficiency of FaceME+.
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