Interaction patterns for smart spaces: a confident interaction design solution for pervasive sensitive IoT services
Vega-Barbas, Mario, Pau, Iván, Augusto, Juan Carlos 
ORCID: https://orcid.org/0000-0002-0321-9150 and Seoane, Fernando
(2018)
Interaction patterns for smart spaces: a confident interaction design solution for pervasive sensitive IoT services.
IEEE Access, 6
.
pp. 1126-1136.
ISSN 2169-3536
[Article]
(doi:10.1109/ACCESS.2017.2777999)
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Abstract
Smart spaces represent a powerful tool for deploying the new pervasive sensitive services based on Internet of Things products and developed in current Information Society close to users. Researchers have focused their efforts on new techniques to improve systems and products in this area but neglecting the human factors related to psychological aspects of the user and their psycho-social relationship with the deployment space where they live. This research proposes to take into account these cognitive features in early stages of the design of smart spaces by defining a set of interaction patterns. By using this set of interaction patterns it is possible to influence over the confidence that users can develop during the use of IoT products and services based on them. An evaluative verification has been carried out to assess how this design engineering approach provide a real impact on the generation of confidence in the users of this kind of technology.
| Item Type: | Article |
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| Research Areas: | A. > School of Science and Technology > Computer Science > Intelligent Environments group |
| Item ID: | 23309 |
| Notes on copyright: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
| Useful Links: | |
| Depositing User: | Juan Augusto |
| Date Deposited: | 15 Jan 2018 14:42 |
| Last Modified: | 29 Nov 2022 20:14 |
| URI: | https://eprints.mdx.ac.uk/id/eprint/23309 |
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