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A Model for Using Machine Learning in Smart Environments

  • Sakari Stenudd
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7096)

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.

Keywords

control loop adaptive systems self-adaptive software prediction 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Sakari Stenudd
    • 1
  1. 1.VTT Technical Research Centre of FinlandOuluFinland

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