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一种用户引导的个性化方法,以促进新的智能家居居住体验。

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

作者信息

Ali S M Murad, Augusto Juan Carlos, Windridge David, Ward Emma

机构信息

Department of Computer Science, Middlesex University, The Burroughs, Hendon, London, UK.

Department of Psychology, Middlesex University, The Burroughs, Hendon, London, UK.

出版信息

Univers Access Inf Soc. 2022 Jun 15:1-23. doi: 10.1007/s10209-022-00883-x.

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 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.

摘要

智能家居在为人们提供他们想要的服务方面正变得越来越受欢迎。活动识别是提供个性化家庭设施的一项基本任务。许多有前景的方法正被用于活动识别;其中之一是数据驱动的。它具有一些引人入胜的特性和优势。然而,也存在一些缺点,比如由于可用数据有限,从一开始就缺乏提供家庭自动化的能力。在本文中,我们提出了一种名为READY(用户引导的新型智能家居自适应系统)的方法,用于开发一个个性化的自动化系统,该系统能在用户搬进新家时就为他们提供智能家居服务。系统开发过程以用户为中心,让用户参与系统设计的每一步。后来,引入了用户引导的迁移学习方法,该方法使用一个旧的智能家居数据集,通过用户贡献来增强现有的智能家居服务。最后,在智能实验室对所提出的方法和设计的系统进行了测试和验证,结果显示很有前景。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b44c/9200218/434e14d9b8b6/10209_2022_883_Fig1_HTML.jpg

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