IoT-Integrated Augmented Reality for Spatially Aware Human–Machine Interaction for IEEE Transactions on Human-Machine Systems

IF 4.4 3区 计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Akhil Ajikumar;Mohsen Moghaddam
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引用次数: 0

Abstract

A human–machine interface (HMI) is an essential component of any modern industrial machine, acting as the portal for human workers to setup, monitor, control, and troubleshoot machines. Yet, existing HMIs often pose challenges in usability and learnability due to overwhelming data, nonstandard interfaces, and physical design limitations. We argue that these challenges stem from a lack of spatiotemporal alignment of data and controls with the machine, leading to information overload and loss as the operator repeatedly translates signals between the HMI and machine. We propose a novel augmented reality (AR) interface integrated with Internet of Things (IoT), which affords spatially aware, natural mapping of real-time data and controls with the machine while providing visibility and immediate feedback. We build the IoT-integrated AR system through a Kepware-ThingWorx-Vuforia pipeline implemented in a model cyber-physical factory for cellphone assembly. We conducted a between-subjects user study with 20 participants split into two groups, who operated three assembly line stations using our system deployed on HoloLens 2 and the machine's built-in Siemens HMIs in opposite orders. The findings show the significant effects of our AR interfaces on improving efficiency, lowering task completion times, reducing errors, and enhancing usability and mental load. We conclude the paper by discussing the limitations and several directions for future research on IoT-integrate AR interfaces to transform how humans interact with industrial machines.
空间感知人机交互的物联网集成增强现实,IEEE人机系统汇刊
人机界面(HMI)是任何现代工业机器的重要组成部分,充当人类工作人员设置、监视、控制和排除机器故障的门户。然而,由于大量的数据、非标准接口和物理设计限制,现有的hmi经常在可用性和可学习性方面提出挑战。我们认为,这些挑战源于数据和控制与机器缺乏时空一致性,导致信息过载和丢失,因为操作员反复在HMI和机器之间转换信号。我们提出了一种与物联网(IoT)集成的新型增强现实(AR)接口,它提供了实时数据和机器控制的空间感知,自然映射,同时提供可见性和即时反馈。我们通过Kepware-ThingWorx-Vuforia管道构建了物联网集成的AR系统,该管道在一个用于手机组装的模型网络物理工厂中实现。我们进行了一项受试者之间的用户研究,将20名参与者分成两组,他们使用部署在HoloLens 2上的我们的系统和机器内置的西门子hmi以相反的顺序操作三个装配线站。研究结果表明,我们的AR界面在提高效率、缩短任务完成时间、减少错误、增强可用性和心理负荷方面具有显著效果。最后,我们讨论了物联网集成AR接口的局限性和未来研究的几个方向,以改变人类与工业机器的交互方式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Human-Machine Systems
IEEE Transactions on Human-Machine Systems COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, CYBERNETICS
CiteScore
7.10
自引率
11.10%
发文量
136
期刊介绍: The scope of the IEEE Transactions on Human-Machine Systems includes the fields of human machine systems. It covers human systems and human organizational interactions including cognitive ergonomics, system test and evaluation, and human information processing concerns in systems and organizations.
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