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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; in revised form: 15 January 2009 / Accepted: 9 February 2009 / Published: 11 February 2009
Abstract: 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.
Keywords: Kalman filter; MOS gas sensor; noise reduction; data analysis
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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.
Qu J, Chai Y, Yang SX. A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network. Sensors. 2009; 9(2):895-908.
Qu, Jianfeng; Chai, Yi; Yang, Simon X. 2009. "A Real-Time De-Noising Algorithm for E-Noses in a Wireless Sensor Network." Sensors 9, no. 2: 895-908.