Analytical Review on Ontological Human Activity Recognition Approaches
Samaneh Zolfaghari,
Mohammad Reza Keyvanpour and
Raziyeh Zall
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Samaneh Zolfaghari: Department of Computer Engineering, Alzahra University, Tehran, Iran
Mohammad Reza Keyvanpour: Department of Computer Engineering, Alzahra University, Tehran, Iran
Raziyeh Zall: Department of Computer Engineering, Alzahra University, Tehran, Iran
International Journal of E-Business Research (IJEBR), 2017, vol. 13, issue 2, 58-78
Abstract:
New advancements in pervasive computing technology have turned smart homes into a daily living monitoring tool increasingly used for elderly. Recently, using knowledge driven approaches such as ontology to introduce semantic smart homes has received attention due to their flexibility, reasoning and knowledge representation. Due to the vast number of ontological human activity recognition methods, the proposed ontological human activity recognition framework can be effective in analyzing and evaluating different methods in different applications and dealing with various challenges. Also, due to numerous challenges involved in different aspects of ontology-based human activity recognition in smart homes, this paper offers a classification for challenges in human activity recognition in ontology based systems. Then the proposed ontological human activity recognition framework is evaluated based on the proposed classification and ontology-based techniques which are thought to solve some of the challenges are examined and analyzed.
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jebr00:v:13:y:2017:i:2:p:58-78
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