A user-guided personalization methodology to facilitate new smart home occupancy

Ali, Murad, Augusto, Juan Carlos ORCID logoORCID: https://orcid.org/0000-0002-0321-9150, Windridge, David ORCID logoORCID: https://orcid.org/0000-0001-5507-8516 and Ward, Emma V. ORCID logoORCID: https://orcid.org/0000-0002-2076-832X (2022) A user-guided personalization methodology to facilitate new smart home occupancy. Universal Access in the Information Society . ISSN 1615-5289 [Article] (Published online first) (doi:10.1007/s10209-022-00883-x)

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Abstract

Smart homes are becoming increasingly popular in providing people with the services they desire. Activity recognition is a fundamental task to provide personalised home facilities. Many promising approaches are being used for activity recognition; one of them is data-driven. It has some fascinating features and advantages. However, there are drawbacks such as the lack of ability to providing home automation from the day one due to the limited data available.

In this paper, we propose an approach, called READY (useR-guided nEw smart home ADaptation sYstem) for developing a personalised automation system that provides the user with smart home services the moment they move into their new house. The system development process was strongly user-centred, involving users in every step of the system’s design. Later, the User-guided Transfer Learning (UTL) approach was introduced that uses an old smart home data set to enhance the existing smart home service with user contributions. Finally, the proposed approach and designed system were tested and validated in the smart lab that showed promising results.

Item Type: Article
Research Areas: A. > School of Science and Technology > Computer Science > Intelligent Environments group
Item ID: 35020
Notes on copyright: Copyright © The Author(s) 2022
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
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Depositing User: Juan Augusto
Date Deposited: 29 Apr 2022 07:58
Last Modified: 12 Feb 2023 15:45
URI: https://eprints.mdx.ac.uk/id/eprint/35020

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