On-line classification of pollutants in water using wireless portable electronic noses

被引:39
作者
Luis Herrero, Jose [1 ]
Lozano, Jesus [2 ]
Pedro Santos, Jose [3 ]
Ignacio Suarez, Jose [2 ]
机构
[1] Univ Extremadura, Dept Comp & Telemat Syst Engn, Avda Elvas S-N, Badajoz 06006, Spain
[2] Univ Extremadura, Dept Elect Technol Elect & Automat, Avda Elvas S-N, Badajoz 06006, Spain
[3] Spanish Council Sci Res ITEFI CSIC, Inst Phys Technol & Informat, Serrano 144, Madrid, Spain
关键词
Electronic nose; Neural networks; Web applications; Components; Web services; MEMS GAS-SENSOR; MACHINE OLFACTION; NETWORK;
D O I
10.1016/j.chemosphere.2016.02.106
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
A portable electronic nose with database connection for on-line classification of pollutants in water is presented in this paper. It is a hand-held, lightweight and powered instrument with wireless communications capable of standalone operation. A network of similar devices can be configured for distributed measurements. It uses four resistive microsensors and headspace as sampling method for extracting the volatile compounds from glass vials. The measurement and control program has been developed in LabVIEW using the database connection toolkit to send the sensors data to a server for training and classification with Artificial Neural Networks (ANNs). The use of a server instead of the microprocessor of the e-nose increases the capacity of memory and the computing power of the classifier and allows external users to perform data classification. To address this challenge, this paper also proposes a web based framework (based on RESTFul web services, Asynchronous JavaScript and XML and JavaScript Object Notation) that allows remote users to train ANNs and request classification values regardless user's location and the type of device used. Results show that the proposed prototype can discriminate the samples measured (Blank water, acetone, toluene, ammonia, formaldehyde, hydrogen peroxide, ethanol, benzene, dichloromethane, acetic acid, xylene and dimethylacetamide) with a 94% classification success rate. (C) 2016 Elsevier Ltd. All rights reserved.
引用
收藏
页码:107 / 116
页数:10
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