Activity Recognition in Opportunistic Sensor Environments

Daniel Roggen, Alberto Calatroni, Kilian Förster, Gerhard Tröster, Paul Lukowicz, David Bannach, Alois Ferscha, Marc Kurz, Gerold Hölzl, Hesam Sagha, Jose Millan, Ricardo Chavarriaga

Research output: Chapter in Book/Report/Conference proceedingsConference contributionpeer-review

8 Citations (Scopus)

Abstract

OPPORTUNITY is project under the EU FET-Open funding1 in which we develop mobile systems to recognize human activity in dynamically varying sensor setups [1,2]. The system autonomously discovers available sensors around the user and self-configures to recognize desired activities. It reconfigures itself as the environment changes, and encompasses principles supporting autonomous operation in open-ended environments.OPPORTUNITYmainstreams ambient intelligence and improves user acceptance by relaxing constraints on body-worn sensor characteristics, and eases the deployment in real-world environments.We summarize key achievements of the project so far. The project outcomes are robust activity recognition systems. This may enable smarter activity-aware energy-management in buildings, and advanced activity-aware health assistants.

Original languageEnglish
Title of host publicationThe European Future Technologies Conference and Exhibition (FET11)
Pages173-174
Number of pages2
Volume7
DOIs
Publication statusPublished - 2011
EventThe European Future Technologies Conference and Exhibition 2011 - Budapest, Hungary
Duration: 4 May 20116 May 2011

Publication series

NameProcedia Computer Science
PublisherElsevier BV

Conference

ConferenceThe European Future Technologies Conference and Exhibition 2011
CountryHungary
CityBudapest
Period04.05.201106.05.2011

Keywords

  • Activity recognition
  • Adaptive systems
  • Context framework
  • Machine learning
  • Pervasive computing

Fingerprint Dive into the research topics of 'Activity Recognition in Opportunistic Sensor Environments'. Together they form a unique fingerprint.

Cite this