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An Intelligent Wireless Electronic Nose Node for Monitoring Gas Mixtures Using Neuro-Fuzzy Networks Implemented on a Microcontroller

机译:用于使用在微控制器上实现的神经模糊网络监控气体混合物的智能无线电子鼻节点

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This paper presents an intelligent wireless electronic nose node (WENN) that has been designed to classify and quantify binary gas mixtures, NH3 and H2S, the main malodors in various environments. The proposed WENN is based on embedded PC technology and neuro-fuzzy network algorithms. The hardware part of the designed system consists of a microcontroller for processing the measured data set obtained from a micro-gas sensor array, and a Zigbee-ready RF transceiver for transmitting the processed data to a base node. The main program embedded on the designed hardware performs real-time classification and concentration estimation of the binary gas mixtures using the fuzzy ART and ARTMAP neural networks. To verify performance of the designed intelligent WENN, the measured data from the experiments for the binary gas mixtures have been executed using the WENN. The results show the reproducibility of the measured data and the verification of real-time classification and concentration estimation for the target gas.
机译:本文介绍了一个智能无线电子鼻子节点(Wenn),该节点(Wenn)旨在分类和量化二元气体混合物,NH 3 和H 2 S,主要的恶臭环境。拟议的Wenn基于嵌入式PC技术和神经模糊网络算法。设计系统的硬件部分由微控制器组成,用于处理从微气传感器阵列获得的测量数据集,以及用于将处理的数据发送到基本节点的ZigBee Ready RF收发器。嵌入设计硬件的主程序使用模糊艺术和艺术神经网络执行二元气体混合物的实时分类和浓度估计。为了验证设计智能Wenn的性能,使用Wenn执行了来自二元气体混合物的实验的测量数据。结果显示了测量数据的再现性和靶气体的实时分类和浓度估计的再现性。

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