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Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities Within the Home

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Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 (IntelliSys 2016)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 15))

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Abstract

One of the key objectives of an ambient assisted living environment is to enable elderly people to lead a healthy and independent life. These assisted environments have the capability to capture and infer activities performed by individuals, which can be useful for providing assistance and tracking functional decline among the elderly community. This paper presents an activity recognition engine based on a hierarchical structure, which allows modelling, representation and recognition of Activities of Daily Life (ADLs), their associated tasks, objects, relationships and dependencies. The structure of this contextual information plays a vital role in conducting accurate ADL recognition. The recognition performance of the inference engine has been validated with a series of experiments based on object usage data collected within the home environment.

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Authors and Affiliations

  1. School of Architecture, Computing and Engineering, University of East London, London, UK

    Usman Naeem, Abdel-Rahman Tawil & Ivans Semelis

  2. Department of Computer Engineering, University of Engineering and Technology, Taxila, Taxila, Pakistan

    Muhammad Awais Azam

  3. Department of Software Engineering, University of Engineering and Technology, Taxila, Taxila, Pakistan

    Mustansar Ali Ghazanfar

Authors
  1. Usman Naeem
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  2. Abdel-Rahman Tawil
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  3. Ivans Semelis
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  4. Muhammad Awais Azam
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  5. Mustansar Ali Ghazanfar
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Corresponding author

Correspondence to Usman Naeem .

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Editors and Affiliations

  1. Faculty of Computing and Engineering, School of Computing and Mathematics, University of Ulster at Jordanstown, Newtownabbey, United Kingdom

    Yaxin Bi

  2. The Science and Information (SAI) Organization, Bradford, West Yorkshire, United Kingdom

    Supriya Kapoor

  3. The Science and Information (SAI) Organization, Bradford, West Yorkshire, United Kingdom

    Rahul Bhatia

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Naeem, U., Tawil, AR., Semelis, I., Azam, M.A., Ghazanfar, M.A. (2018). Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities Within the Home. In: Bi, Y., Kapoor, S., Bhatia, R. (eds) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016. IntelliSys 2016. Lecture Notes in Networks and Systems, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-319-56994-9_66

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  • DOI: https://doi.org/10.1007/978-3-319-56994-9_66

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-56993-2

  • Online ISBN: 978-3-319-56994-9

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