Open AccessActivity Recognition in Opportunistic Sensor Environments
Author(s) -
Daniel Roggen,
Alberto Calatroni,
Kilian Förster,
Gerhard Tröster,
Paul Lukowicz,
David Bannach,
Alois Ferscha,
Marc Kurz,
Gerold Hölzl,
Hesam Sagha,
Hamidreza Bayati,
José del R. Millán,
Ricardo Chavarriaga
Publication year - 2011
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.334
H-Index - 76
ISSN - 1877-0509
DOI - 10.1016/j.procs.2011.09.003
Subject(s) - computer science , software deployment , activity recognition , human–computer interaction , key (lock) , ambient intelligence , wireless sensor network , smart environment , embedded system , artificial intelligence , computer security , internet of things , software engineering , operating system
OPPORTUNITY is project under the EU FET-Open funding11We acknowledge the support of the commission's research programme under under FET-Open grant number 225938. www.opportunity-project.eu. Contact author: Daniel Roggen, droggen@gmail.com 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. OPPORTUNITY mainstreams 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
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