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FaceME: Face-to-Machine Proximity Estimation Based on RSSI Difference for Mobile Industrial Human__achine Interaction
IEEE Transactions on Industrial Informatics ( IF 11.7 ) Pub Date : 4-24-2018 , DOI: 10.1109/tii.2018.2829847
Zhezhuang Xu , Rongkai Wang , Xi Yue , Ting Liu , Cailian Chen , Shih-Hau Fang

In the mobile industrial human-machine interaction (HMI), to establish the data connection, the engineer has to manually select the target machine from a long list, which may lead to wrong connection and waste of time. We observe that the engineer should face to the machine during the interaction to ensure that the machine works accurately, and this characteristic makes the proximity estimation algorithm suitable to simplify the data connection. However, due to the densely deployed machines, the existing algorithms cannot provide sufficient accuracy with limited latency. In this paper, we implement a testbed to evaluate the performance in the mobile industrial HMI. Based on the experimental results, we propose the definition of received signal strength indicator (RSSI) difference and then use it to design the face-to-machine proximity estimation (FaceME) algorithm. The experimental results prove that FaceME can provide guaranteed estimation accuracy and low-time complexity.

中文翻译:


FaceME:基于RSSI差异的移动工业人机交互的人机接近度估计



在移动工业人机交互(HMI)中,为了建立数据连接,工程师必须手动从长列表中选择目标机器,这可能会导致错误连接并浪费时间。我们观察到,工程师在交互过程中应该面向机器,以确保机器准确工作,这一特性使得邻近估计算法适合简化数据连接。然而,由于机器部署密集,现有算法无法在有限的延迟下提供足够的精度。在本文中,我们实现了一个测试平台来评估移动工业 HMI 的性能。基于实验结果,我们提出了接收信号强度指示符(RSSI)差异的定义,然后用它来设计人机接近度估计(FaceME)算法。实验结果证明FaceME能够提供有保证的估计精度和较低的时间复杂度。
更新日期:2024-08-22
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