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

Book chapter

Naeem, U., Tawil, A., Semelis, Ivans, Azam, Muhammad Awais and Ghazanfar, Mustansar Ali 2017. Inference Engine Based on a Hierarchical Structure for Detecting Everyday Activities within the Home. in: Bi, Yaxin, Kapoor, Supriya and Bhatia, Rahul (ed.) Proceedings of SAI Intelligent Systems Conference (IntelliSys) 2016 Springer, Cham. pp. 969-986
AuthorsNaeem, U., Tawil, A., Semelis, Ivans, Azam, Muhammad Awais and Ghazanfar, Mustansar Ali
EditorsBi, Yaxin, Kapoor, Supriya and Bhatia, Rahul
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 hierarchal structure, which allows
modelling, representation and recognition of 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.

KeywordsActivity Recognition; Alzheimer’s disease; Assisted Living; Elderly Monitoring; Activities of Daily Life; Activity Modelling; Inference Engine
Book titleProceedings of SAI Intelligent Systems Conference (IntelliSys) 2016
Page range969-986
Year2017
PublisherSpringer, Cham
Publication dates
Print20 Aug 2017
Publication process dates
Deposited11 May 2017
Accepted2016
Series Lecture Notes in Networks and Systems
EventSAI Intelligent Systems Conference (IntelliSys) 2016
ISBN978-3-319-56993-2
978-3-319-56994-9
Digital Object Identifier (DOI)https://doi.org/10.1007/978-3-319-56994-9_66
Web address (URL)https://doi.org/10.1007/978-3-319-56994-9_66
Accepted author manuscript
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