Opportunistic Human Activity and Context Recognition

Daniel Roggen; Gerhard Tröster; Paul Lukowicz; Alois Ferscha; José del R. Millán; Ricardo Chavarriaga

doi:10.1109/MC.2012.393

Opportunistic Human Activity and Context Recognition

Daniel Roggen
, Gerhard Tröster
, Paul Lukowicz
, Alois Ferscha
, José del R. Millán
, Ricardo Chavarriaga

Institute of Pervasive Computing

Research output: Contribution to journal › Article › peer-review

Abstract

Achieving true ambient intelligence calls for a new opportunistic activity recognition paradigm in which, instead of deploying information sources for a specific goal, the recognition methods themselves dynamically adapt to available sensor data. The Web extra at http://youtu.be/dMN3Hoq5QfU is a video recording of opportunistic sensor configurations in a highly rich sensor environment that shows how a large number of activity instances occur during early morning activities in an apartment.

Original language	English
Pages (from-to)	36-45
Number of pages	10
Journal	Computer
Volume	46
Issue number	2
DOIs	https://doi.org/10.1109/MC.2012.393
Publication status	Published - Feb 2013

Fields of science

102 Computer Sciences
102009 Computer simulation
102013 Human-computer interaction
102019 Machine learning
102020 Medical informatics
102021 Pervasive computing
102022 Software development
102025 Distributed systems
202017 Embedded systems
211902 Assistive technologies
211912 Product design

JKU Focus areas

Computation in Informatics and Mathematics
Engineering and Natural Sciences (in general)

Access to Document

10.1109/MC.2012.393

Cite this

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title = "Opportunistic Human Activity and Context Recognition",

abstract = "Achieving true ambient intelligence calls for a new opportunistic activity recognition paradigm in which, instead of deploying information sources for a specific goal, the recognition methods themselves dynamically adapt to available sensor data. The Web extra at http://youtu.be/dMN3Hoq5QfU is a video recording of opportunistic sensor configurations in a highly rich sensor environment that shows how a large number of activity instances occur during early morning activities in an apartment.",

author = "Daniel Roggen and Gerhard Tr{\"o}ster and Paul Lukowicz and Alois Ferscha and \{del R. Mill{\'a}n\}, Jos{\'e} and Ricardo Chavarriaga",

year = "2013",

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doi = "10.1109/MC.2012.393",

language = "English",

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journal = "Computer",

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AU - Roggen, Daniel

AU - Tröster, Gerhard

AU - Lukowicz, Paul

AU - Ferscha, Alois

AU - del R. Millán, José

AU - Chavarriaga, Ricardo

PY - 2013/2

Y1 - 2013/2

N2 - Achieving true ambient intelligence calls for a new opportunistic activity recognition paradigm in which, instead of deploying information sources for a specific goal, the recognition methods themselves dynamically adapt to available sensor data. The Web extra at http://youtu.be/dMN3Hoq5QfU is a video recording of opportunistic sensor configurations in a highly rich sensor environment that shows how a large number of activity instances occur during early morning activities in an apartment.

AB - Achieving true ambient intelligence calls for a new opportunistic activity recognition paradigm in which, instead of deploying information sources for a specific goal, the recognition methods themselves dynamically adapt to available sensor data. The Web extra at http://youtu.be/dMN3Hoq5QfU is a video recording of opportunistic sensor configurations in a highly rich sensor environment that shows how a large number of activity instances occur during early morning activities in an apartment.

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U2 - 10.1109/MC.2012.393

DO - 10.1109/MC.2012.393

M3 - Article

SN - 0018-9162

VL - 46

SP - 36

EP - 45

JO - Computer

JF - Computer

IS - 2

ER -

Opportunistic Human Activity and Context Recognition

Abstract

Fields of science

JKU Focus areas

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Opportunity - Activity and Context Recognition with Opportunistic Sensor Configurations

Cite this

Opportunistic Human Activity and Context Recognition

Abstract

Fields of science

JKU Focus areas

Access to Document

Other files and links

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Opportunity - Activity and Context Recognition with Opportunistic Sensor Configurations

Cite this