Design and Evaluation of Three Interaction Models for Manipulating Internet of Things (IoT) Devices in Virtual Reality

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Abstract

More and more things are getting connected to the internet, including lights, speakers, and refrigerators. These connected things are an example of what a smart home system that is part of the Internet of Things (IoT) can incorporate. IoT enables advanced services by interconnecting physical and virtual things. But, building interactive prototypes for smart home systems can be difficult and costly, since it involves a number of different devices and systems with varying technological readiness level. Virtual reality (VR) is a technology that can create computer-generated environments and has been used as a design tool in many different domains, such as architecture, city planning, and industrial design. However, the focus has traditionally been on visualizing design proposals rather than letting the intended users directly interact with them. Recently, we have seen an intensified development of VR headsets such as HTC Vive and Oculus Rift. These headsets come with relatively well-developed hand controllers, which can be used to interact with the virtual environment. This opens up opportunities to develop and evaluate interactive virtual smart home systems. This paper presents three interaction models developed and evaluated using the new generation of VR technology. The interaction models were then compared in a user study with 18 participants. Some statistically significant differences and subjective preferences could be observed in the quantitative and qualitative data respectively. The main contribution of this paper is to elucidate knowledge about using VR as a prototyping tool to explore IoT interaction. Moreover, this study implies that you can collect and analyze data for statistical analysis using VR.

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Alce, G., Ternblad, E. M., & Wallergård, M. (2019). Design and Evaluation of Three Interaction Models for Manipulating Internet of Things (IoT) Devices in Virtual Reality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11749 LNCS, pp. 267–286). Springer Verlag. https://doi.org/10.1007/978-3-030-29390-1_15

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