Recognizing activities of daily living from patterns and extraction of web knowledge

Book chapter

Ihianle, I., Naeem, U., Tawil, A. and Azam, Muhammad Awais 2016. Recognizing activities of daily living from patterns and extraction of web knowledge. in: Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16 New York, NY, USA Association for Computing Machinery (ACM). pp. 1255-1262
AuthorsIhianle, I., Naeem, U., Tawil, A. and Azam, Muhammad Awais
Abstract

The ability to infer and anticipate the activities of elderly individuals with cognitive impairment has made it possible to provide timely assistance and support, which in turn allows them to lead an independent life. Traditional non-intrusive activity recognition approaches are dependent on the use of various machine learning techniques to infer activities given the collected object usage data. Current activity recognition approaches are also based on knowledge driven techniques that require extensive modelling of the activities that needs to be inferred. These models can be seen as too restrictive, prescriptive and static as they are based on a finite set of activities. In this paper, we propose a novel “top down” approach to recognising activities based on object usage data, which detects patterns associated with the activity-object relationship and utilizes web knowledge in order to build dynamic activity models based on the objects used to perform the activity. Experimental results using the Kasteren dataset shows it is comparable to existing approaches.

KeywordsActivity Recognition; Pattern Analysis; Topic Model; Web Extraction; Ontology Model
Book titleProceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing Adjunct - UbiComp '16
Page range1255-1262
Year2016
PublisherAssociation for Computing Machinery (ACM)
Publication dates
Print12 Sep 2016
Publication process dates
Deposited11 May 2017
Accepted2016
Place of publicationNew York, NY, USA
EventACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp 2016)
ISBN978-1-4503-4462-3
Digital Object Identifier (DOI)https://doi.org/10.1145/2968219.2968440
Additional information

© 2016 Copyright is held by the Authors.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for thirdparty components of this work must be honored. For all other uses, contact
the Owner/Author. Ubicomp/ISWC'16 Adjunct, September 12-16, 2016, Heidelberg, Germany ACM978-1-4503-4462-3/16/09.
http://dx.doi.org/10.1145/2968219.2968440

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