Context modulation of Sensor Data Applied to Activity Recognition in Smart Homes

Niall J Twomey, Peter A Flach

Research output: Contribution to conferenceConference Paperpeer-review

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Abstract

In this paper we present a method of modulating the context of data captured in smart homes. We show that we can dramatically adapt their sensor network topology and that this approach can be used to help understand various aspects of such sensor environments. We demonstrate how, with our software, we can discover the importance of individual sensors, clusters of sensors and sensor categories for resident identification and activity recognition. Finally, we validate the utility of context modulation in a number of experimental scenarios that show how the activity recognition is a ected by each sensor topology elicited by these scenarios.
Original languageEnglish
Number of pages16
Publication statusPublished - 2014
EventEuropean Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2014 - Nancy, France
Duration: 15 Sep 201419 Sep 2014

Conference

ConferenceEuropean Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2014
CountryFrance
CityNancy
Period15/09/1419/09/14

Structured keywords

  • Jean Golding
  • SPHERE

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