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Sensors 2009, 9(2), 895-908;

A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network

College of Automation, Chongqing University, Chongqing, 400030, P.R. China
School of Engineering, University of Guelph, Guelph, ON, N1G 2W1, Canada
Author to whom correspondence should be addressed.
Received: 3 December 2008 / Revised: 15 January 2009 / Accepted: 9 February 2009 / Published: 11 February 2009
(This article belongs to the Special Issue Gas Sensors 2009)
Full-Text   |   PDF [260 KB, uploaded 21 June 2014]


A wireless e-nose network system is developed for the special purpose of monitoring odorant gases and accurately estimating odor strength in and around livestock farms. This system is to simultaneously acquire accurate odor strength values remotely at various locations, where each node is an e-nose that includes four metal-oxide semiconductor (MOS) gas sensors. A modified Kalman filtering technique is proposed for collecting raw data and de-noising based on the output noise characteristics of those gas sensors. The measurement noise variance is obtained in real time by data analysis using the proposed slip windows average method. The optimal system noise variance of the filter is obtained by using the experiments data. The Kalman filter theory on how to acquire MOS gas sensors data is discussed. Simulation results demonstrate that the proposed method can adjust the Kalman filter parameters and significantly reduce the noise from the gas sensors. View Full-Text
Keywords: Kalman filter; MOS gas sensor; noise reduction; data analysis Kalman filter; MOS gas sensor; noise reduction; data analysis
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Qu, J.; Chai, Y.; Yang, S.X. A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network. Sensors 2009, 9, 895-908.

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