An extension of regression-based automatic calibration method for sensor networks

Tomoyuki Fujino, Satoshi Honda

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

This work proposes a new automatic calibration method for the sensor network which measures the distribution of physical fields. In case of these sensor networks, the regular calibration of the sensors is necessary for obtaining reliable information. However, it is not an easy task in the case of a large scale sensor network, because the manual calibration is time consuming and costly. To solve this problem, this present study proposes a new method which is based on the two concepts of regression analysis and cross validation. In this paper, the new method is explained and the efficient extension is also proposed, and the performance of the proposed methods is verified by a simulation.

Original languageEnglish
Title of host publication9th International Conference on Networked Sensing Systems, INSS 2012 - Conference Proceedings
PublisherIEEE Computer Society
ISBN (Print)9781467317856
DOIs
Publication statusPublished - 2012
Event9th International Conference on Networked Sensing Systems, INSS 2012 - Antwerp, Belgium
Duration: 2012 Jun 112012 Jun 14

Publication series

Name9th International Conference on Networked Sensing Systems, INSS 2012 - Conference Proceedings

Other

Other9th International Conference on Networked Sensing Systems, INSS 2012
CountryBelgium
CityAntwerp
Period12/6/1112/6/14

Keywords

  • Calibration
  • Particle filters
  • Semisu-pervised learning
  • Wireless sensor networks

ASJC Scopus subject areas

  • Computer Networks and Communications

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    Fujino, T., & Honda, S. (2012). An extension of regression-based automatic calibration method for sensor networks. In 9th International Conference on Networked Sensing Systems, INSS 2012 - Conference Proceedings [6240569] (9th International Conference on Networked Sensing Systems, INSS 2012 - Conference Proceedings). IEEE Computer Society. https://doi.org/10.1109/inss.2012.6240569