Proceedings of the 2016 International Conference on Engineering and Advanced Technology

Research on the application of data mining technology in Internet of things

Authors
Rui Wang, Jinguo Wang, Na Wang
Corresponding Author
Rui Wang
Available Online May 2016.
DOI
10.2991/iceat-16.2017.78How to use a DOI?
Keywords
data mining, internet of things
Abstract

For the current Internet of things system architecture analysis, proposed based on the structure of the central node of the structure of the model. The task of center node is that migrate the task of application node to the central node, using intelligent task management program automatically complete the task. One of the basic tasks of the central node is a routine report, the main content is to submit a judgment of normal data. Research on series of internet of thing's data, given an abnormal sequence detection scheme. In this paper, we use the KNN method in data mining to realize the detection of abnormal sequences, and the automatic detection of anomaly detection is realized by the artificial judgment anomaly to the density deviation on the algorithm.

Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2016 International Conference on Engineering and Advanced Technology
Series
Advances in Engineering Research
Publication Date
May 2016
ISBN
978-94-6252-294-7
ISSN
2352-5401
DOI
10.2991/iceat-16.2017.78How to use a DOI?
Copyright
© 2017, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Rui Wang
AU  - Jinguo Wang
AU  - Na Wang
PY  - 2016/05
DA  - 2016/05
TI  - Research on the application of data mining technology in Internet of things
BT  - Proceedings of the 2016 International Conference on Engineering and Advanced Technology
PB  - Atlantis Press
SP  - 384
EP  - 387
SN  - 2352-5401
UR  - https://doi.org/10.2991/iceat-16.2017.78
DO  - 10.2991/iceat-16.2017.78
ID  - Wang2016/05
ER  -