Article

A model for using machine learning in smart environments

Author:

Sakari StenuddAuthors Info & Claims

GPC'11: Proceedings of the 6th international conference on Grid and Pervasive Computing

Pages 24 - 33

https://doi.org/10.1007/978-3-642-27916-4_4

Published: 11 May 2011 Publication History

Abstract

This work presents a model for using machine learning in the adaptive control of smart environments. The model is based on an investigation of the existing works regarding smart environments and an analysis of the machine learning uses within them. Four different categories of machine learning in smart environments were identified: prediction, recognition, detection and optimisation. These categories can be deployed to different phases of a self-adaptive application utilising the adaptation loop structure. The use of machine learning in one phase of the adaptation loop was demonstrated by carrying out an experiment utilising neural networks in the prediction of latencies.

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Cited By

Carolis BFerilli SRedavid D(2015)Incremental Learning of Daily Routines as Workflows in a Smart Home EnvironmentACM Transactions on Interactive Intelligent Systems10.1145/26750634:4(1-23)Online publication date: 28-Jan-2015
https://dl.acm.org/doi/10.1145/2675063
Rodríguez NCuéllar MLilius JCalvo-Flores M(2014)A survey on ontologies for human behavior recognitionACM Computing Surveys10.1145/252381946:4(1-33)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1145/2523819

Index Terms

A model for using machine learning in smart environments
1. Computing methodologies
  1. Machine learning

Index terms have been assigned to the content through auto-classification.

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Information & Contributors

Information

Published In

cover image Guide Proceedings

GPC'11: Proceedings of the 6th international conference on Grid and Pervasive Computing

May 2011

179 pages

ISBN:9783642279157

Editors:
Mika Rautiainen
Department of Computer Science and Engineering, University of Oulu, Oulu, Finland
,
Timo Korhonen
Department of Computer Science and Engineering, Aalto University, Helsinki, Finland
,
Edward Mutafungwa
Department of Computer Science and Engineering, Aalto University, Helsinki, Finland
,
Eila Ovaska
Department of Computer Science and Engineering, VTT Technical Research Centre of Finland, Oulu, Finland
,
Artem Katasonov
Department of Computer Science and Engineering, VTT Technical Research Centre of Finland, Oulu, Finland

Sponsors

The Academy of Finland
Infotech Oulu: Infotech Oulu

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 11 May 2011

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Cited By

Carolis BFerilli SRedavid D(2015)Incremental Learning of Daily Routines as Workflows in a Smart Home EnvironmentACM Transactions on Interactive Intelligent Systems10.1145/26750634:4(1-23)Online publication date: 28-Jan-2015
https://dl.acm.org/doi/10.1145/2675063
Rodríguez NCuéllar MLilius JCalvo-Flores M(2014)A survey on ontologies for human behavior recognitionACM Computing Surveys10.1145/252381946:4(1-33)Online publication date: 1-Mar-2014
https://dl.acm.org/doi/10.1145/2523819

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