Your browser does not support JavaScript!

Machine learning algorithms for smart data analysis in the Internet of things: an overview

Machine learning algorithms for smart data analysis in the Internet of things: an overview

For access to this article, please select a purchase option:

Buy chapter PDF
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Intelligent Wireless Communications — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Machine learning (ML) techniques will benefit immensely from the avalanche of data readily available from various (IoT) applications considered as the major contributor of new data for future intelligent network. Based on this new concept, network systems will further magnify their capacity to exploit variety of experimental data across a plethora of network devices, study the data information, obtain knowledge and make informed decisions based on the dataset at their disposal. Smart IoT data analysis are performed utilizing supervised learning, unsupervised learning and reinforced learning. This study is limited to supervised and unsupervised ML techniques. In other to achieve the set objectives, reviews and discussions of substantial issues related to supervised or unsupervised machine learning techniques were executed, highlighting the advantages and limitations of each algorithm as well presenting the recent research trends and recommendations for future study.

Chapter Contents:

  • 12.1 Introduction
  • 12.2 Taxonomies of supervised and unsupervised ML algorithms
  • 12.2.1 Supervised ML algorithm
  • Classification tasks
  • Regression tasks
  • Combining classification and regression tasks
  • 12.2.2 Unsupervised ML algorithm
  • Clustering
  • Feature extraction
  • 12.2.3 Neural networks approach
  • 12.3 Research trends and open issues
  • 12.3.1 Privacy and security
  • 12.3.2 Real-time implementation and data analysis
  • 12.4 Conclusions and recommendations
  • References

Inspec keywords: Internet of Things; unsupervised learning; intelligent networks; supervised learning; data analysis

Other keywords: informed decisions; network systems; supervised machine learning techniques; network devices; smart IoT data analysis; data information; supervised ML techniques; smart data analysis; unsupervised machine learning techniques; unsupervised ML techniques; Internet of Things

Subjects: Ubiquitous and pervasive computing; Other topics in statistics; Data handling techniques

Preview this chapter:
Zoom in

Machine learning algorithms for smart data analysis in the Internet of things: an overview, Page 1 of 2

| /docserver/preview/fulltext/books/te/pbte094e/PBTE094E_ch12-1.gif /docserver/preview/fulltext/books/te/pbte094e/PBTE094E_ch12-2.gif

Related content

This is a required field
Please enter a valid email address