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Frequent pattern clustering for ADLs recognition in smart environments

Published: 01 July 2015 Publication History

Abstract

Smart habitats are considered by many researchers as a promising potential solution to help supporting the needs of elders. It aims to provide cognitive assistance by taking decisions, such as giving hints, suggestions and reminders to a resident in order to increase their autonomy. Smart homes can be seen as a huge data warehouse on the person's lifestyle. However, one of the major issues which emerge from this context of big data is learning. So it is essential to develop techniques to learn from patients before being able to assist them. In fact, each person makes a number of recurring activities, but not necessarily the same, not in the same way, not at the same time, etc. It is difficult for an expert to establish a knowledge library of activities as is often the case in the literature. A promising solution that is beginning to be explored seriously by many scientists concerning the application of data mining techniques to learn behaviors, habits and routines of people. About it, we present in this paper an affordable activity recognition system, based on frequent sensor clustering, able to recognize the patterns of the daily routine activities.

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Cited By

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  • (2021)The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological FrameworkSustainability10.3390/su13211158713:21(11587)Online publication date: 20-Oct-2021

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cover image ACM Other conferences
PETRA '15: Proceedings of the 8th ACM International Conference on PErvasive Technologies Related to Assistive Environments
July 2015
526 pages
ISBN:9781450334525
DOI:10.1145/2769493
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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

  • NSF: National Science Foundation
  • University of Texas at Austin: University of Texas at Austin
  • Univ. of Piraeus: University of Piraeus
  • NCRS: Demokritos National Center for Scientific Research
  • Ionian: Ionian University, GREECE

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 July 2015

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Author Tags

  1. activity recognition
  2. clustering
  3. frequent item sets

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PETRA '15
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  • NSF
  • University of Texas at Austin
  • Univ. of Piraeus
  • NCRS
  • Ionian

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  • (2021)The Role of Big Data in Aging and Older People’s Health Research: A Systematic Review and Ecological FrameworkSustainability10.3390/su13211158713:21(11587)Online publication date: 20-Oct-2021

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