Author:
Becks Eileen,Zdankin Peter,Matkovic Viktor,Weis Torben
Abstract
Setup and management of smart home systems is a complex task, and thus challenging for technically inexperienced users. We conducted a qualitative user study to evaluate whether an assistance system could empower users to make better and informed decisions regarding the selection of devices, their interoperability, the resulting set of features and their price. A group of 20 participants used our assistance app on a smartphone to configure a smart home while optimizing for features, interoperability, and the price-performance ratio. The results of our user study show that our assistance app can ease the problem of selecting useful devices and at the same time users become aware of new features resulting from the interoperation of selected devices. Furthermore, the assistance app can counteract the inherent interoperability problem between devices of different vendors or platforms. Finally, users are not only interested in individual device prices. They want to learn the cost of a certain feature set, including the cost of all devices necessary to realize this feature. Interestingly, none of the current smart home systems on the market offer a comparable assistance mechanism. Third-party solutions are not available either, because an assistance app requires meta data about features, interoperability, and usage of devices. This meta data is currently not available via APIs in state-of-the-art smart home systems and marketplaces. Therefore, we present a smart home architecture resulting from our research that can, among other benefits, provide the necessary meta data. Our research indicates that commercial smart home systems should invest more effort in user assistance to gain widespread adoption among technically inexperienced users. This in turn requires substantial changes to the meta data management in smart homes, because otherwise these assistance systems cannot be realized.
Subject
Computer Science (miscellaneous)
Reference25 articles.
1. Gjoreski, H., Kozina, S., Gams, M., and Luštrek, M. (2014, January 24–28). RAReFall—Real-time activity recognition and fall detection system. Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS), Budapest, Hungary.
2. Interoperability among heterogeneous systems in smart home environment;Perumal;Web-Based Inf. Technol. Distrib. Syst.,2010
3. Mennicken, S., Vermeulen, J., and Huang, E.M. (2014, January 13–17). From today’s augmented hou- ses to tomorrow’s smart homes: New directions for home automation research. Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Seattle, WA, USA.
4. Zdankin, P., Picone, M., Mamei, M., and Weis, T. (2022, January 10–13). A Digital-Twin Based Architecture for Software Longevity in Smart Homes. Proceedings of the 2022 IEEE 42nd International Conference on Distributed Computing Systems (ICDCS), Bologna, Italy.
5. Aldrich, F.K. (2003). Inside the Smart Home, Springer.
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