Wireless electronic nose network for real-time gas monitoring system

Abstract

We present a study on the development and testing of a wireless electronic nose network (WENn) for monitoring real-time gas mixture, NH <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sub> and H <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> S, main malodors in various environments. The proposed WENn is based on an embedded PC, an electronic olfactory system and wireless sensor network (WSN) technology and neuro-fuzzy network algorithms. The WENn used in this work takes advantage of recent advances in low power wireless communication platforms and uses micro-gas sensors with SnO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> -CuO and SnO2-Pt sensing films for detecting the presence of target gases. Each node in the network real-timely performs classification and concentration estimation of the binary gas mixtures using the fuzzy ART and ARTMAP neural networks and calculation of the measured humidity and temperature in a located point and then transmits the computed results from the measured data set to a sink node via a Zigbee ready RF transceiver. In addition, a monitoring manager virtual instrument (MMVI) is developed using LabVIEW to monitor efficiently the analyzed gas information from the sensor node. To test the reproducibility and reliability of the WENn, on-line experiments are conducted with the gas monitoring system.