A Modeling Study of Sensor Data

Feng Liu; Jian Yong Wang; Ming Liu

doi:10.4028/www.scientific.net/AMR.765-767.1259

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 765-767A Modeling Study of Sensor Data

A Modeling Study of Sensor Data

Abstract:

Nowadays, Internet of Things (IoT) has been becoming a hot research topic. Being an important part of Internet of Things, the wireless sensor networks collect various types of environmental data and construct the fundamental structure of the IoT applications. In order to find out the characteristics of the environmental data, in this paper, we focus on four types of these sensor data: temperature, humidity, light and voltage, and employ statistical methods to analyze and model these sensor data. The results of our research can be used to solve the missing sensor data estimation problem which is inevitable in the wireless sensor networks.

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Periodical:

Advanced Materials Research (Volumes 765-767)

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1259-1262

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.765-767.1259

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Online since:

September 2013

Authors:

Feng Liu, Jian Yong Wang, Ming Liu

Keywords:

Data Modeling, Sensor Data Analysis, Wireless Sensor Network (WSN)

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References

[1] N. Verma, P. Zappi, and T. Rosing, Latent variables based data estimation for sensing applications., in 2011 Seventh International Conference on Intelligent Sensors, Sensor Networks and Information, 2011, pp.335-340.

DOI: 10.1109/issnip.2011.6146590

Google Scholar

[2] G. Y. Lu, and D. W. Wong, An adaptive inverse-distance weighting spatial interpolation technique, Computers & Geosciences, vol. 34, no. 9, pp.1044-1055, (2008).

DOI: 10.1016/j.cageo.2007.07.010

Google Scholar

[3] P. J. Garcia-Laencina, J. -L. Sancho-Gomez, A. R. Figueiras-Vidal et al., K nearest neighbours with mutual information for simultaneous classification and missing data imputation, Neurocomputing, vol. 72, no. 7-9, pp.1483-1493, (2009).

DOI: 10.1016/j.neucom.2008.11.026

Google Scholar

[4] N. Basher, A. Mahanti, A. Mahanti et al., A comparative analysis of web and Peer-to-Peer traffic, in Proceeding of the 17th International Conference on World Wide Web, 2008, pp.287-296.

DOI: 10.1145/1367497.1367537

Google Scholar

[5] G. He, J. Hou, W. -P. Chen et al., One Size Does Not Fit All: A Detailed Analysis and Modeling of P2P Traffic. " in conference of GLOBECOM , 07, 2007, pp.393-398.

DOI: 10.1109/glocom.2007.80

Google Scholar

[6] B. Shen, Y. Liu, and X. Wang, Research on data mining models for the internet of things., in conference on Image Analysis and Signal Processing, 2010, pp.127-132.

Google Scholar

[7] S. Madden. Intel Berkeley research lab data, on http: /berkeley. intel-research. net/labdata.

Google Scholar