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WIREs Data Mining Knowl Discov
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Data analytics for internet of things: A review

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The internet of things (IoT), which provides a way to connect every “thing” via the internet to further develop a convenient environment, has been around for more than a decade. The trend of the development of IoT nowadays is to focus not only on its devices and systems but also on data analysis. The main reason is that data from sensors or systems typically contain valuable information that is very useful for improving the system performance or providing a better service to the user if we come up with a good “data analysis” solution. This paper begins with a brief review of data mining technologies for IoT. Then, a reference data analytics architecture is given to show how data analysis technologies can be applied to an IoT system. Finally, applications, open issues, and possible research directions are addressed.

This article is categorized under:

  • Application Areas > Internet and Web‐Based Applications
  • Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining
  • Technologies > Computational Intelligence
  • Technologies > Machine Learning
Steps for interpreting the survey in this paper
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The KDD processes of IoT data analytics system
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The comparison between data analytics for IoT architectures. (a) Other existing architectures and (b) the proposed architecture
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The relationship between IoT with KDD (Tsai et al., )
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The architecture of IoT (Bandyopadhyay & Sen, )
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Technologies > Computational Intelligence
Technologies > Machine Learning
Fundamental Concepts of Data and Knowledge > Key Design Issues in Data Mining

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