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：

来源：

PROCEEDINGS OF THE 2ND EUROPEAN FUTURE TECHNOLOGIES CONFERENCE AND EXHIBITION 2011 (FET 11) | 2011年 / 7卷

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

页码：173 / 174

页数：2