Learning under uncertainty in smart home environments

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Technologies and services for the home environment can provide levels of independence for elderly people to support ‘ageing in place’. Learning inhabitants' patterns of carrying out daily activities is a crucial component of these technological solutions with sensor technologies being at the core of such smart environments. Nevertheless, identifying high-level activities from low-level sensor events can be a challenge, as information may be unreliable resulting in incomplete data. Our work addresses the issues of learning in the presence of incomplete data along with the identification and the prediction of inhabitants and their activities under such uncertainty. We show via the evaluation results that our approach also offers the ability to assess the impact of various sensors in the activity recognition process. The benefit of this work is that future predictions can be utilised in a proposed intervention mechanism in a real smart home environment.
Original languageEnglish
Title of host publicationUnknown Host Publication
Pages2083-2086
Number of pages4
DOIs
Publication statusPublished - Aug 2008
Event30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - Vancouver
Duration: 1 Aug 2008 → …

Conference

Conference30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Period1/08/08 → …

Fingerprint Dive into the research topics of 'Learning under uncertainty in smart home environments'. Together they form a unique fingerprint.

  • Cite this