Activity Recognition in Opportunistic Sensor Environments

被引:8
|
作者
Roggen, Daniel
Calatroni, Alberto
Foerster, Kilian
Troester, Gerhard
Lukowicz, Paul
Bannach, David
Ferscha, Alois
Kurz, Marc
Hoelzl, Gerold
Sagha, Hesam
Bayati, Hamidreza
Millan, Jose del R.
Chavarriaga, Ricardo
机构
关键词
Activity recognition; pervasive computing; adaptive systems; machine learning; context framework;
D O I
10.1016/j.procs.2011.09.003
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
OPPORTUNITY is project under the EU FET-Open funding(1) 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. (C) Selection and peer-review under responsibility of FET11 conference organizers and published by Elsevier B. V.
引用
收藏
页码:173 / 174
页数:2
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