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shARe-IT: Ad hoc Remote Troubleshooting through Augmented Reality

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10 years ago, Castellani et al. (Journal of Computer Supported Cooperative Work, vol. 18, no. 2–3, 2009, pp. 199–227, 2009) showed that using just an audio channel for remote troubleshooting can lead to a range of problems and already envisioned a future in which augmented reality (AR) could solve many of these issues. In the meantime, AR technologies have found their way into our everyday lives and using such technologies to support remote collaboration has been widely studied within the fields of Human-Computer Interaction and Computer-Supported Cooperative Work. In this paper, we contribute to this body of research by reporting on an extensive empirical study within a Fab Lab of troubleshooting and expertise sharing and the potential relevance of articulation work to their realization. Based on the findings of this study, we derived design challenges that led to an AR-based concept, implemented as a HoloLens application, called shARe-it. This application is designed to support remote troubleshooting and expertise sharing through different communication channels and AR-based interaction modalities. Early testing of the application revealed that novel interaction modalities such as AR-based markers and drawings play only a minor role in remote collaboration due to various limiting factors. Instead, the transmission of a shared view and especially arriving at a shared understanding of the situation as a prerequisite for articulation work continue to be the decisive factors in remote troubleshooting.

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Ludwig, Thomas; Stickel, Oliver; Tolmie, Peter; Sellmer, Malte (2021): shARe-IT: Ad hoc Remote Troubleshooting through Augmented Reality. Computer Supported Cooperative Work (CSCW): Vol. 30, No. 1. DOI: 10.1007/s10606-021-09393-5. Springer. PISSN: 1573-7551. pp. 119-167

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Augmented reality, CSCW, Expertise sharing, Fab lab, Remote troubleshooting

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Number of citations to item: 9

  • Shuguang Liu, Jiacheng Xie, Xuewen Wang, Hao Meng (2023): Mixed Reality collaboration environment improves the efficiency of human-centered industrial system: A case study in the mining industry, In: Computers & Industrial Engineering, doi:10.1016/j.cie.2023.109257
  • Kailiang Shou, Qingshu Yuan, Keming Chen, Zhengwei Yao, Zhigeng Pan (2023): A Perspective Taking Supported AR Learning Platform with a User Study on Learning Three-View Drawing, In: International Journal of Human–Computer Interaction 23(40), doi:10.1080/10447318.2023.2276521
  • Zhenning Zhang, Zhigeng Pan, Weiqing Li, Zhiyong Su (2022): Imitative Collaboration: A mirror-neuron inspired mixed reality collaboration method with remote hands and local replicas, In: Journal of Visual Communication and Image Representation, doi:10.1016/j.jvcir.2022.103600
  • Bernardo Marques, Samuel Silva, António Teixeira, Paulo Dias, Beatriz Sousa Santos (2022): A vision for contextualized evaluation of remote collaboration supported by AR, In: Computers & Graphics, doi:10.1016/j.cag.2021.10.009
  • Sven Hoffmann, Thomas Ludwig, Florian Jasche, Volker Wulf, David Randall (2022): RetrofittAR: Supporting Hardware-Centered Expertise Sharing in Manufacturing Settings through Augmented Reality, In: Computer Supported Cooperative Work (CSCW) 1(32), doi:10.1007/s10606-022-09430-x
  • Bernardo Marques, Carlos Ferreira, Samuel Silva, Paulo Dias, Beatriz Sousa Santos (2023): Is social presence (alone) a general predictor for good remote collaboration? comparing video and augmented reality guidance in maintenance procedures, In: Virtual Reality 3(27), doi:10.1007/s10055-023-00770-7
  • Ziming Li, Yiming Luo, Jialin Wang, Yushan Pan, Lingyun Yu, Hai-Ning Liang (2024): Feasibility and performance enhancement of collaborative control of unmanned ground vehicles via virtual reality, In: Personal and Ubiquitous Computing 3-4(28), doi:10.1007/s00779-024-01799-4
  • Melanie Duckert, Louise Barkhuus, Pernille Bjørn (2023): Collocated Distance: A Fundamental Challenge for the Design of Hybrid Work Technologies, In: Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, doi:10.1145/3544548.3580899
  • Jacob T. Biehl, Rosta Farzan, Yingfan Zhou (2022): Can Anybody Help Me?: Using Community Help Desk Call Records to Examine the Impact of Digital Divides During a Global Pandemic, In: CHI Conference on Human Factors in Computing Systems, doi:10.1145/3491102.3517693
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