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On Analyzing User Location Discovery Methods in Smart Homes: A Taxonomy and Survey

Lee, GM (2016) On Analyzing User Location Discovery Methods in Smart Homes: A Taxonomy and Survey. Journal of Network and Computer Applications, 76. pp. 75-86. ISSN 1084-8045

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Abstract

User Location Discovery (ULD) is a key issue in smart home ecosystems, as it plays a critical role in many applications. If a smart home management system cannot detect the actual location of the users, the desired applications may not be able to work successfully. This article proposes a new taxonomy with a broad coverage of ULD methods in terms of user satisfaction and technical features. In addition, we provide a state-of-the-art survey of ULD methods and apply our taxonomy to map these methods. Mapping contributes to gap analysis for existing ULDs and also validates the applicability and accuracy of the taxonomy. Using this systematic approach, the features and characteristics of the current ULD methods are identified (i.e., equipment and algorithms). Next, the weaknesses and advantages of these methods are analyzed utilizing ten important evaluation metrics. Although we mainly focus on smart homes, the results of this article can be generalized to other spaces such as smart offices and eHealth environments.

Item Type: Article
Uncontrolled Keywords: 0899 Other Information And Computing Sciences
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Computer Science
Publisher: Elsevier
Date Deposited: 29 Sep 2016 08:42
Last Modified: 09 Sep 2017 18:47
DOI or Identification number: 10.1016/j.jnca.2016.09.012
URI: http://researchonline.ljmu.ac.uk/id/eprint/4213

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