Sukor, Abdul Syafiq Abdull, Zakaria, Ammar, Rahim, Norasmadi Abdul and Setchi, Rossitza ![]() ![]() |
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Abstract
Activity recognition plays a major role in smart home technologies in providing services to users. One of the approaches to identify ac-tivity is through the use of knowledge-driven reasoning. This paper presents a framework of semantic activity recognition, which is used to support smart home systems to identify users’ activities based on the existing context. The framework consists of two main compo-nents: a semantic knowledge base and an activity recognition module. The knowledge base is represented using ontology and it is used to provide a semantic understanding of the environment in order to classify users’ patterns of activities. Experimental results show that the proposed approach can support the classification process and accurately infer users’ activities with the accuracy of 90.9%.
Item Type: | Article |
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Date Type: | Publication |
Status: | Published |
Schools: | Engineering |
Publisher: | Science Publishing Corporation |
ISSN: | 2227-524X |
Date of First Compliant Deposit: | 3 January 2019 |
Date of Acceptance: | 22 December 2018 |
Last Modified: | 06 Jul 2023 18:17 |
URI: | https://orca.cardiff.ac.uk/id/eprint/118074 |
Citation Data
Cited 4 times in Scopus. View in Scopus. Powered By Scopus® Data
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