Premium
Data analytics for internet of things: A review
Author(s) -
Tsai ChunWei,
Tsai PangWei,
Chiang MingChao,
Yang ChuSing
Publication year - 2018
Publication title -
wiley interdisciplinary reviews: data mining and knowledge discovery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.506
H-Index - 47
eISSN - 1942-4795
pISSN - 1942-4787
DOI - 10.1002/widm.1261
Subject(s) - computer science , data science , analytics , key (lock) , the internet , data analysis , big data , internet of things , focus (optics) , world wide web , architecture , service (business) , computer security , data mining , art , physics , economy , optics , economics , visual arts
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