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  • 1.
    Zolfaghari, Samaneh
    et al.
    Department of Computer Engineering, Alzahra University, Tehran, Iran.
    Keyvanpour, Mohammad Reza
    Department of Computer Engineering, Alzahra University, Tehran, Iran.
    Zall, Raziyeh
    Department of Computer Engineering, Alzahra University, Tehran, Iran.
    Analytical Review on Ontological Human Activity Recognition Approaches2017In: International Journal of E-Business Research, ISSN 1548-1131, E-ISSN 1548-114X, Vol. 13, no 2, p. 58-78Article in journal (Refereed)
    Abstract [en]

    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.

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