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    A New Modular Approach for Low-Cost Electronic Noses

    Depari, A. ; Ferrari, P. ; Flammini, A. ; Marioli, D. ; Rosa, S. ; Taroni, A.
    Instrumentation and Measurement Technology Conference, 2006. IMTC 2006. Proceedings of the IEEE

    Digital Object Identifier: 10.1109/IMTC.2006.328627
    Publication Year: 2006 , Page(s): 578 - 583
    Cited by:  Papers (2)

    IEEE Conference Publications

    Electronic noses are used for important applications as food processing, pollution control and security system, as well as for laboratory works, as new sensors characterization. In the first case the main limit still remains the high cost of the equipment due to the need of powerful systems, as personal computer, for the elaboration process. In the second case a high level of flexibility is required, as possibility to add new and well-tailored hardware (e.g. sensor interface circuits). In this paper we propose a solution for the implementation of low-cost electronic noses suitable for both uses. The system has modular low-noise architecture, thus it can be tailored for the particular application, lowering the overall cost. In this work, two innovative chemical sensor typologies (resonant and resistive) have been taken into account and the related high-performance first conditioning circuits have been designed and experimentally tested. The detection process can be performed directly by the instrument using a neural network approach; in this way, no expensive external elaborators are needed, allowing a further reduction in the system cost View full abstract»

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    Discrimination of black tea using electronic nose and electronic tongue: A Bayesian classifier approach

    Banerjee, R. ; Chattopadhyay, P. ; Rani, R. ; Tudu, B. ; Bandyopadhyay, R. ; Bhattacharyya, N.
    Recent Trends in Information Systems (ReTIS), 2011 International Conference on

    Digital Object Identifier: 10.1109/ReTIS.2011.6146832
    Publication Year: 2011 , Page(s): 13 - 17

    IEEE Conference Publications

    Electronic nose and electronic tongue is highly acceptable in the field of food quality research as well as in different food industry which are capable of analyzing food quality like human panel taster in a more accurate way. Just like human sensing system electronic nose can discriminate food samples based on aroma and electronic tongue classifies samples based on their taste. As per human perception process to perceive the taste of food the sense of smell is equally responsible to its taste. Considering this issue, we propose a multi sensor data fusion based on Bayesian theorem which is applied to the data obtained from electronic nose and electronic tongue for classification of black tea. Numerical results show that the error in classification is reduced considerably in multivariate data fusion compared to univariate case. View full abstract»

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    Pattern Recognition of the Universal Electronic Nose

    Zhou Tao ; Wang Lei ; Jionghua Teng
    Intelligent Information Technology Application, 2008. IITA '08. Second International Symposium on

    Volume: 3
    Digital Object Identifier: 10.1109/IITA.2008.416
    Publication Year: 2008 , Page(s): 249 - 253
    Cited by:  Papers (1)

    IEEE Conference Publications

    An electronic nose is the intelligent instrument that identifies the chemical odors mimicking a human. Now the majority of electronic noses could only identify the specific species, however the human olfactory system is able to characterize and classify many different odors. The problem has prevented their use in wider commercial applications. The pattern recognition methods based on the probabilistic neural networks (PNN) are studied in this paper. The electronic nose systems designed could identify all the samples of beer, fruit juice and milk successfully in the experiments. The results of the experiments showed that the researched systems have a better classification and generalization capacity. The pattern recognition methods of the universal electronic nose are proposed in the paper. The effective universal electronic nose has much advantage over others such as simple methods of pattern recognition and classification, easy training approaches and wider application fields. View full abstract»

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    Combination of an electronic nose, an electronic tongue and an electronic eye for the Analysis of Red Wines aged with alternative methods

    Rodriguez-Mendez, M.L. ; Apetrei, C. ; Apetrei, I. ; Villanueva, S. ; de Saja, I.J.A. ; Nevares, I. ; del Alamo, M.
    Industrial Electronics, 2007. ISIE 2007. IEEE International Symposium on

    Digital Object Identifier: 10.1109/ISIE.2007.4375050
    Publication Year: 2007 , Page(s): 2782 - 2787

    IEEE Conference Publications

    A combination of an electronic nose, an electronic tongue and an electronic eye has been used to discriminate between red wines aged in oak barrels and red wines matured in steel tanks in contact with oak wood chips. The quality of wines has also been analyzed by means of conventional chemical methods. Principal component analysis has demonstrated that both methods allow discriminating wines according to the type of ageing. Moreover, partial least squares (PLS) has demonstrated that measurements carried out with the electronic system allow establishing prediction models that are capable to infer the methodology used to age wines. Good correlations have been found between the signals obtained with the electronic system and the chemical parameters. The electrochemical signals have been successfully employed to estimate chemical parameters related to the polyphenolic content or the pH such as the tannins content. View full abstract»

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    Electronic Noses Sniff Success

    Chang, J.B. ; Subramanian, Vivek
    Spectrum, IEEE

    Volume: 45 , Issue: 3
    Digital Object Identifier: 10.1109/MSPEC.2008.4457857
    Publication Year: 2008 , Page(s): 50 - 56

    IEEE Journals & Magazines

    E-nose technology has quietly advanced during the past two decades. Commercial models equipped with sensor arrays came to market in the mid-1990s, and today they're used to distinguish wines, analyze food flavors, and sort lumber. Benchtop systems are also used in the pharmaceutical, food, cosmetics, and packaging industries, while smaller, portable units are used to monitor air quality. But these noses cost in the range of US $5000 to $100 000. A coming convergence between e-nose technology and advances in printed electronics will finally bring the price down; way down. Within a decade we'll see e-noses that cost tens of dollars and appear in smart packaging for high-end items like pharmaceuticals or as part of intelligent or interactive appliances- picture a refrigerator that knows when milk has gone bad. Prices could easily drop to under a dollar by 2020. The secret? Conducting polymers. Developers of both electronic noses and printed electronics are exploiting these materials, which can be sensitive to the chemicals that make up odors and are also capable of producing electrical signals. E-nose developers are concentrating on honing the sensing properties of conducting polymers, while the printed-electronics people are investigating ways of using these materials to fabricate ultralow-cost electronics. Combining the fruits of these two separate efforts will finally bring e-noses into our supermarkets, homes, and daily life. View full abstract»

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    Chemical substance classification by electronic noses

    Pornpanomchai, C. ; Khongchuay, P.
    Computer Science and Information Technology, 2009. ICCSIT 2009. 2nd IEEE International Conference on

    Digital Object Identifier: 10.1109/ICCSIT.2009.5234995
    Publication Year: 2009 , Page(s): 68 - 72
    Cited by:  Papers (1)

    IEEE Conference Publications

    Normally, an electronic nose project uses two researches areas which are hardware for developing sensors to detect substance smell and software using pattern matching theorem for recognizing substance. The operation begins with sensors hit the smell of chemical substance. The result is converted from analog to digital representation. An artificial intelligence is a tool of a thinking system which can create knowledge as if a human does. The objective of this research is to classify chemical substance by using electronic noses. We used eight types of chemical substance in the experiment which are 1) acetone, 2) benzene, 3) propanal, 4) butanol, 5) chloroform, 6) ethanol, 7) methane and 8) tetrahydrofuran. We compared nine structures of neural network to classify the chemical substance data. The precision of correctness is equal to 94.64 for a neural network structure as 54 input-layer nodes, 216 hidden-layer1 nodes, 8 hidden-layer2 nodes and 8 output-layer nodes. View full abstract»

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    Experimental use of electronic nose for analysis of volatile organic compound (VOC)

    Saeed, S.H. ; Abbas, Z. ; Gopal, B.
    Multimedia, Signal Processing and Communication Technologies, 2009. IMPACT '09. International

    Digital Object Identifier: 10.1109/MSPCT.2009.5164187
    Publication Year: 2009 , Page(s): 113 - 115
    Cited by:  Papers (1)

    IEEE Conference Publications

    An electronic nose is an instrument intended to mimic the human sense of smell. Electronic noses (e-nose) employ an array of chemical gas sensors, a sample handling system and a pattern recognition system. Pattern recognition provides a higher degree of selectivity and reversibility to the system leading to an extensive range of applications. These ranges from the food and medical industries to environmental monitoring and process control. Many other types of different gas sensors available. These include conducting polymers (CP), metal oxide semiconductors (MOS), piezoelectric, optical fluorescence, quartz crystal microbalance (QCM) and amperometric gas sensors. The ideal gas sensor would exhibit reliability, robustness, sensitivity, selectivity and reversibility. High selectivity with high reversibility is difficult to attain. After signal processing and feature extraction the output of the sensors provide a unique ldquosmellprintrdquo for that substances which can be used to classify, measure concentration, or verify quality. The present paper illustrates the function of electronic nose, its application and investigates the effective use of e-nose in detecting gases that have some smell developed by the volatile organic compounds (VOC) like ethanol, acetone and benzene at different concentrations. The response and characteristics prove that the Electronic nose is a reliable instrument which can be used for environment control (air quality, pollutants, and gas emission levels), medical science (urine, skin and breath odour etc.), food industry (coffee, milk, soft drink fish, meat etc.), pharmaceutics, chemical industry, Defence and security industries (detecting humanitarian land mines etc.) and semiconductor industrial processes. View full abstract»

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    Electronic noses for monitoring environmental pollution and building regression model

    Morsi, I.
    Industrial Electronics, 2008. IECON 2008. 34th Annual Conference of IEEE

    Digital Object Identifier: 10.1109/IECON.2008.4758215
    Publication Year: 2008 , Page(s): 1730 - 1735
    Cited by:  Papers (3)

    IEEE Conference Publications

    Electronic noses are intelligent designs that are able to classify and quantify different gases/ odors. This concept permits us to easily provide remote connectivity, large data storage and complex signal processing by using commercial sensors. In this paper a case study is presented for examining the use of sensor grid system concerning urban air pollution monitoring for carbon monoxide, carbon dioxide (CO, CO2) gases for three different regions in Alexandria- Egypt along the Corniche and 2 different traffic roads. This is based on the integration of distributed sensors, data integration and developing a simple air pollutant model. The analysis and the characterization of environmental data are acquired by building a prototype of multi-sensors monitoring system (electronic nose), which are TGS 822, TGS 2442, TGS 813, TGS 4160, TGS 2600, temperature sensor, humidity sensor and wind speed measurements. All sensors are connected to the microcontroller (Pic 16F 628A) and PC to visualize and analyze data. Quadratic surface regression method is used to find possible correlations exisistance between some pollutants, elaborated by Matlab software and statistical analysis. The influence of meteorological quantities is taken into account to improve the model as well as different factors including weather conditions, topography and local situation. To investigate the performance of quadratic model, the interpolation quadrate function obtained is compared using the reduced data set after eliminating data in a random way with the results obtained using the original data set, then the mean square error (mse) is calculated. Analysis of variance (ANOVA) is used to detect the significant factors in the final quadrate equation and understanding the functional relationship between a set of independent factors. View full abstract»

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    An wireless electronic nose network for odours around livestock farms

    Leilei Pan ; Rui Liu ; Shanghong Peng ; Yi Chai ; Yang, Simon X.
    Mechatronics and Machine Vision in Practice, 2007. M2VIP 2007. 14th International Conference on

    Digital Object Identifier: 10.1109/MMVIP.2007.4430745
    Publication Year: 2007 , Page(s): 211 - 216
    Cited by:  Papers (3)

    IEEE Conference Publications

    An electronic nose-based network system is developed for monitoring odours around livestock farms remotely. This network is built from compact electronic noses which are tailored to detect odour compounds and environment conditions such as temperature, wind speed, and humidity. The electronic noses are placed at various locations of interest around the farm, and the collected odour data are dissemination via a wireless network to a computer server, where the sensor fusion algorithms process and analyze the data. The developed electronic nose network system can provide farmers and researchers with more accurate odour management capabilities for more efficient operation of odour control practice by providing consistent, comprehensive, detailed, real-time data about the environment and odour profile around livestock farms. View full abstract»

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    Using Stationary Electronic Noses Network to Locate Dynamic Odour Source Position

    Jie Cai ; Levy, D.C.
    Integration Technology, 2007. ICIT '07. IEEE International Conference on

    Digital Object Identifier: 10.1109/ICITECHNOLOGY.2007.4290431
    Publication Year: 2007 , Page(s): 793 - 798
    Cited by:  Papers (1)

    IEEE Conference Publications

    Source localization based on electronic nose system is a very interesting research. There are two basic methods to solve this problem. One is performed by robotics with build-in electronic nose (Enose) system. Another is performed by stationary electronic nose systems. First approach is well developed with the improving robotic techniques. However this approach will have difficulty to solve several situations, such as "instantaneous source" and complex landscape to prevent robotics reaching the source. Stationary electronic nose system has the capability to solve these problems. This paper presents a two-step approach based on a novel stationary electronic nose systems network to locate the dynamic odour source position. It is considered in a set of natural wind situations, including x axis advection, and wind with a break case. It is an extended work based on our previous research. View full abstract»

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    Optimal weighting of networked electronic noses for the source localization

    Matthes, J. ; Groll, L. ; Keller, H.B.
    Systems Communications, 2005. Proceedings

    Digital Object Identifier: 10.1109/ICW.2005.64
    Publication Year: 2005 , Page(s): 455 - 460
    Cited by:  Papers (1)

    IEEE Conference Publications

    Based on concentration measurements from spatially distributed electronic noses, the location of a point source is to be determined. It is assumed that the emitted substance is transported by advection caused by a known homogeneous wind field and by diffusion. A new two-step approach for solving the source localization problem is presented. The new approach overcomes the problem of poor convergence of iterative algorithms, which try to minimize the least squares output error An optimal weighting strategy is introduced, which yields to approximate maximum-likelihood estimates for the source position. View full abstract»

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    Optimization of sensor array in electronic nose by combinational feature selection method

    Saha, P. ; Ghorai, S. ; Tudu, B. ; Bandyopadhyay, R. ; Bhattacharyya, N.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461698
    Publication Year: 2012 , Page(s): 341 - 346

    IEEE Conference Publications

    Electronic nose (e-nose) is a machine olfaction system and the sensor array is an essential part of the electronic olfaction process. A pattern recognition unit is necessary in electronic nose system to efficiently decide about the output of the test using the responses of all the sensors in the array. The output of a pattern recognition algorithm depends on the quality of the feature set used for training and testing. Relevant and independent feature set improves the performance of a pattern classification algorithm. In some applications of electronic nose, the responses of few sensors are highly corrupted with noise and are either irrelevant or are redundant to the process. These sensors should be identified and eliminated from the sensor system for better accuracy. This paper addresses the selection of sensors in an e-nose system by different feature selection methods and then integrates them to achieve improved classification performance. We have used three types of feature selection methods namely, t-statistics, Fisher's criterion and minimum redundancy maximum relevance (MRMR) technique to select the most informative features. We have tested the proposed method on data obtained from the major aroma producing chemicals of black tea. Multi-class support vector machine (SVM) has been used as a pattern classifier in an electronic nose with black tea samples. The experimental results show that the performance of the e-nose system increased by 6-10% with the use of the proposed combinational feature selection technique. View full abstract»

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    Denoising by Singular Value Decomposition and Its Application to Electronic Nose Data Processing

    Jha, S.K. ; Yadava, R.D.S.
    Sensors Journal, IEEE

    Volume: 11 , Issue: 1
    Digital Object Identifier: 10.1109/JSEN.2010.2049351
    Publication Year: 2011 , Page(s): 35 - 44
    Cited by:  Papers (5)

    IEEE Journals & Magazines

    This paper analyzes the role of singular value decomposition (SVD) in denoising sensor array data of electronic nose systems. It is argued that the SVD decomposition of raw data matrix distributes additive noise over orthogonal singular directions representing both the sensor and the odor variables. The noise removal is done by truncating the SVD matrices up to a few largest singular value components, and then reconstructing a denoised data matrix by using the remaining singular vectors. In electronic nose systems this method seems to be very effective in reducing noise components arising from both the odor sampling and delivery system and the sensors electronics. The feature extraction by principal component analysis based on the SVD denoised data matrix is seen to reduce separation between samples of the same class and increase separation between samples of different classes. This is beneficial for improving classification efficiency of electronic noses by reducing overlap between classes in feature space. The efficacy of SVD denoising method in electronic nose data analysis is demonstrated by analyzing five data sets available in public domain which are based on surface acoustic wave (SAW) sensors, conducting composite polymer sensors and the tin-oxide sensors arrays. View full abstract»

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    Electronic nose to detect sulphate reducing bacteria which is an agent of corrosion

    Chandaran, U.D. ; Halim, Z.A. ; Sidek, O. ; Darah, I. ; Mohamad-Salleh, J. ; Mohamad, N. ; Rashidah, A.R.
    Computer and Communication Engineering (ICCCE), 2010 International Conference on

    Digital Object Identifier: 10.1109/ICCCE.2010.5556756
    Publication Year: 2010 , Page(s): 1 - 4

    IEEE Conference Publications

    Sulfate reducing bacteria (SRB) is a nonpathogenic and anaerobic bacterium which can produce enzyme to accelerate the reduction of sulfate compounds to hydrogen sulphate that corrodes metal. This paper will study the possibility of using electronic nose which consists of chemical sensing system, data acquisition system and pattern recognition system such as artificial neural network to detect hydrogen sulphide. There are a few methods of detecting SRB such as laboratory analysis and field test kit but the procedures are costly and take longer time, within 1 to 2 days. Study shows that electronic nose can be used to detect SRB by detecting hydrogen sulphide that is produced during reduction process. The electronic nose can detect hydrogen sulphide within 16 hours where the detection period is reduced from 30% to 65%. Study also shows that the electronic nose with micro hotplate sensor base will reduce 86% of power consumption compared to electronic nose with alumina ceramic sensor base. View full abstract»

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    Optimization of Sensor Array in Electronic Nose: A Rough Set-Based Approach

    Bag, A.K. ; Tudu, B. ; Roy, J. ; Bhattacharyya, N. ; Bandyopadhyay, R.
    Sensors Journal, IEEE

    Volume: 11 , Issue: 11
    Digital Object Identifier: 10.1109/JSEN.2011.2151186
    Publication Year: 2011 , Page(s): 3001 - 3008
    Cited by:  Papers (3)

    IEEE Journals & Magazines

    In an electronic nose, the most important component is the sensor array and the classification accuracy of an electronic nose that depends significantly upon the choice of the sensors in the array. While deploying an electronic nose for a specific application, it is observed that some of the sensors in the array may not be required and only a subset of the sensor array contributes to the decision. Thus, the number of sensors used in the electronic nose may be minimized for a particular application without affecting the classification accuracy. In many cases, the sensor array produces an imprecise, incomplete, redundant, and inconsistent dataset and thus the classification accuracy degrades due to these redundant sensors. The rough set theory is a mathematical tool capable of selecting the most relevant and nonredundant feature from such datasets. In this paper, the notion of rough set theory is utilized for pattern classification in an electronic nose with black tea samples and at the same time optimization of the sensor set is carried out. View full abstract»

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    Portable Electronic Nose System for Aroma Classification of Black Tea

    Chowdhury, S.S. ; Tudu, B. ; Bandyopadhyay, R. ; Bhattacharyya, N.
    Industrial and Information Systems, 2008. ICIIS 2008. IEEE Region 10 and the Third international Conference on

    Digital Object Identifier: 10.1109/ICIINFS.2008.4798403
    Publication Year: 2008 , Page(s): 1 - 5
    Cited by:  Papers (1)

    IEEE Conference Publications

    A portable electronic nose system has been developed with an array of five commercially available Metal Oxide Semiconductor (MOS) sensors, where a microcontroller (muc) is used for the pattern recognition. The classification of black tea aroma is carried out in the muc (PIC18F4520) and is based on feed forward multilayer perceptron (FF-MLP) algorithm. With the samples collected from the different gardens of north-east and eastern India, the MLP is trained first using the back-propagation algorithm with the fingerprint from the sensor array and the corresponding tea tasters' mark in a PC to obtain the optimum architecture and weights and biases of the neurons. Once it is trained, the computed weights and biases of the neurons are programmed in the muc and it then becomes a portable instrument, which gives the aroma index directly for new unknown tea samples. It is observed from the results that the performance of the muc-based electronic nose is at par with that of the PC-based electronic nose system when compared with unknown finished black tea samples. View full abstract»

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    Electronic noses and their applications

    Keller, P. E.
    Northcon 95. I EEE Technical Applications Conference and Workshops Northcon95

    Digital Object Identifier: 10.1109/NORTHC.1995.485024
    Publication Year: 1995
    Cited by:  Papers (10)  |  Patents (8)

    IEEE Conference Publications

    Electronic/artificial noses are being developed as systems for the automated detection and classification of odors, vapors, and gases. An electronic nose is generally composed of a chemical sensing system (e.g., sensor array or spectrometer) and a pattern recognition system (e.g., artificial neural network). We are developing electronic noses for the automated identification of volatile chemicals for environmental and medical applications. In this paper, we briefly describe an electronic nose, show some results from a prototype electronic nose, and discuss applications of electronic noses in the environmental, medical, and food industries View full abstract»

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    Multi-class support vector machine for quality estimation of black tea using electronic nose

    Saha, P. ; Ghorai, S. ; Tudu, B. ; Bandyopadhyay, R. ; Bhattacharyya, N.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461744
    Publication Year: 2012 , Page(s): 571 - 576

    IEEE Conference Publications

    Electronic nose (e-nose) is a machine olfaction system that has shown significant possibilities as an improved alternative of human taster as olfactory perceptions vary from person to person. In contrast, electronic noses also detect smells with their sensors, but in addition describe those using electronic signals. An efficient e-nose system should analyze and recognize these electronic signals accurately. For this it requires a robust pattern classifier that can perform well on unseen data. This research work shows the efficient prediction of black tea quality using machine learning algorithm with e-nose. This paper investigates the potential of three different types of multi-class support vector machine (SVM) to build taster-specific computational models. Experimental results show that all the three models offer more than 97% accuracies to predict the considerable variation in tea quality. View full abstract»

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    Evaluation of an electronic nose to assess fruit ripeness

    Brezmes, J. ; Fructuoso, Ma.L.L. ; Llobet, E. ; Vilanova, X. ; Recasens, I. ; Orts, J. ; Saiz, G. ; Correig, X.
    Sensors Journal, IEEE

    Volume: 5 , Issue: 1
    Digital Object Identifier: 10.1109/JSEN.2004.837495
    Publication Year: 2005 , Page(s): 97 - 108
    Cited by:  Papers (18)

    IEEE Journals & Magazines

    The main goal of our study was to see whether an artificial olfactory system can be used as a nondestructive instrument to measure fruit maturity. In order to make an objective comparison, samples measured with our electronic nose prototype were later characterized using fruit quality techniques. The cultivars chosen for the study were peaches, nectarines, apples, and pears. With peaches and nectarines, a PCA analysis on the electronic nose measurements helped to guess optimal harvest dates that were in good agreement with the ones obtained with fruit quality techniques. A good correlation between sensor signals and some fruit quality indicators was also found. With pears, the study addressed the possibility of classifying samples regarding their ripeness state after different cold storage and shelf-life periods. A PCA analysis showed good separation between samples measured after a shelf-life period of seven days and samples with four or less days. Finally, the electronic nose monitored the shelf-life ripening of apples. A good correlation between electronic nose signals and firmness, starch index, and acidity parameters was found. These results prove that electronic noses have the potential of becoming a reliable instrument to assess fruit ripeness. View full abstract»

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    Health-care electronic nose to detect beer odor in breath after drinking

    Thepudom, T. ; Kerdcharoen, T. ; Tuantranont, A. ; Pogfay, T.
    Biomedical Engineering International Conference (BMEiCON), 2012

    Digital Object Identifier: 10.1109/BMEiCon.2012.6465444
    Publication Year: 2012 , Page(s): 1 - 4

    IEEE Conference Publications

    Breath analysis is an interesting technique to detect several volatile organic compounds presented within the human body that can indicate the health status of individuals. For this purpose, electronic nose is a convenient device, which is based on a sensor array similar to the olfactory sense as presented in human nose. At present, electronic nose has been widely applied to classify various kinds of odors including those related to healthcare such as breath monitoring. Beer is one of the most popular alcoholic beverages which effects on health and beer odor can be detected in breathing. Beer contains various volatile organic compounds (VOCs) such as ethanol, ethyl acetate and acetaldehyde. In this work, an optical electronic nose that comprises 2 thin films acting as multiple gas sensors (Zinc-5,10,15,20-tetra-phenyl-21H-porphyrin or ZnTPP and Zinc-2,9,16,23-tetra-tert-butyl-29H, 31H-phthalocyanine or ZnTTBPc) were applied to monitor the reduction of alcohol in human breath after drinking of beer. The measurement of VOCs was investigated based on change in the optical absorption of both thin films upon interactions with the breath sample. Principal component analysis (PCA) was used as classification technique to analyze VOCs in form of fingerprint. It was found that the optical electronic nose is capable of tracking alcohol decay in exhaled breath with the passing time. View full abstract»

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    Study of a Signal Classification Method in Electronic Noses Based on Suprathreshold Stochastic Resonance

    Wu Lili ; Yuan Chao ; Lin Aiying ; Zheng Baozhou ; Guo Miao
    Measuring Technology and Mechatronics Automation (ICMTMA), 2010 International Conference on

    Volume: 3
    Digital Object Identifier: 10.1109/ICMTMA.2010.205
    Publication Year: 2010 , Page(s): 531 - 534

    IEEE Conference Publications

    The research on stochastic resonance (SR) in threshold systems has received much attention recently, for multithreshold networks, SR is also observed in suprathreshold system. Generally suprathreshold SR (SSR) has been shown to exist by the mutual information and input-output cross-correlation. In this project, a novel method of ¿maximum cross-correlation coefficient¿ based on SSR was proposed to identify five gases gathered by the electronic nose. In the experiment, six carbon nanotubes gas sensors were chosen to compose a sensor array of the electronic nose, which were all sensitive to formaldehyde, benzene, toluene, xylene and ammonia. The data gathered from the sensor array were passed through the SSR system, which was quantified by the cross-correlation coefficient. Form the SSR curves, ¿maximum cross-correlation coefficient¿ of different gas classes was found to be completely different, and the ¿maximum cross-correlation coefficient¿ was a constant for each gas. So it can be used to accurately represent the different classes of gases. Compared with the classified results of the BP(back propagation) network, the method of ¿maximum cross-correlation coefficient¿ based on SSR has high accuracy in identifying five kinds of gases. So the method of ¿maximum cross-correlation coefficient¿ can be used as a new signal classification method. View full abstract»

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    Discrimination and characterization of breath from smokers and non-smokers via electronic nose and GC/MS analysis

    Witt, K. ; Reulecke, S. ; Voss, A.
    Engineering in Medicine and Biology Society,EMBC, 2011 Annual International Conference of the IEEE

    Digital Object Identifier: 10.1109/IEMBS.2011.6090618
    Publication Year: 2011 , Page(s): 3664 - 3667

    IEEE Conference Publications

    The objective of this study was to prove the general applicability of an electronic nose for analyzing exhaled breath considering the dependency on smoking. At first, odor compounds from spices (n=6) were detected via the electronic nose and further characterized and classified with gas chromatography/ mass spectrometry to demonstrate the principle ability of the electronic nose. Then, the exhaled breath from smokers and non-smokers were analyzed to prove the influence of smoking on breath analyses with the electronic nose. The exhaled breath was sampled from 11 smokers and 11 non-smokers in a special sampling bag with the mounted sensor chip of the electronic nose. Additionally, solid phase micro-extraction (SPME) technique was established for detection of the specific chemical compounds with gas chromatography and mass spectrometry (GC/MS). For analyses of the sensor signals the principle component analysis (PCA) was applied and the groups were differentiated by linear discriminant function analysis. In accordance to the discrimination between the different spices and between smokers and non-smokers the PCA analysis leads to an optimum accuracy of 100%. The results of this study show that an electronic nose has the ability to detect different changes of odor components and provides separation of smoking side effects in smelling different diseases. View full abstract»

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    Towards an All Polymeric Electronic Nose: Device Fabrication and Characterization, Electronic Control, Data Analysis

    De Girolamo Del Mauro, A. ; Burrasca, G. ; De Vito, S. ; Massera, E. ; Loffredo, F. ; Quercia, L. ; Di Francia, G. ; della Sala, D.
    Solid-State Sensors, Actuators and Microsystems Conference, 2007. TRANSDUCERS 2007. International

    Digital Object Identifier: 10.1109/SENSOR.2007.4300304
    Publication Year: 2007 , Page(s): 1011 - 1014

    IEEE Conference Publications

    In this work, a wireless electronic nose prototype, called TinyNose, hosting an array of four different polymeric-composite sensors developed at ENEA, is presented. Sensors are fabricated using a carbon black conducting phase dispersed in different polymeric matrices. The prototype has shown interesting results for VOC compounds detection and discrimination purposes during a measurement campaign. View full abstract»

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    Electronic nose as the rapid technique for aroma assesment of vegetable oils

    Rashid, F.N.A. ; Maamor, H.N. ; Zakaria, N.Z.I. ; Yusuf, N. ; Adnan, K.A.K. ; Zakaria, A. ; Kamarudin, L.M. ; Shakaff, A.Y.M.
    Wireless Sensor (ICWISE), 2013 IEEE Conference on

    Digital Object Identifier: 10.1109/ICWISE.2013.6728794
    Publication Year: 2013 , Page(s): 130 - 133

    IEEE Conference Publications

    Vegetable oil of various types and sources may produce different aroma. This study explores the application of electronic nose for aroma analysis, mainly for characterization and classification of different types of vegetable oils. The electronic nose system comprises of metal oxide semiconductor (MOS) sensors which is used to extract the fingerprint of volatile compounds that is present in the samples. In this study, a linear discriminant analysis (LDA) was applied for electronic nose data processing and recognition. Analysis of the LDA showed that the percentage performance for the training group was 100%, while for test group was 93.6% and 85.4% validated. Based on the results obtained, the electronic nose was able to classify the aroma of different types of vegetable oil. View full abstract»

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    Notice of Retraction
    Instant coffee classification by electronic noses

    Pornpanomchai, C. ; Jurangboon, K. ; Jantarasee, K.
    Mechanical and Electronics Engineering (ICMEE), 2010 2nd International Conference on

    Volume: 1
    Digital Object Identifier: 10.1109/ICMEE.2010.5558605
    Publication Year: 2010 , Page(s): V1-10 - V1-13
    Cited by:  Papers (2)

    IEEE Conference Publications

    Notice of Retraction

    After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE's Publication Principles.

    We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

    The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

    Normally, an electronic nose project uses two researches areas which are hardware for developing sensors to detect substance smell and software using pattern matching theorem for recognizing substance. For this research, the operation begins with sensors hit the coffee smell. The result is converted from analog to digital representation. An artificial intelligence is a tool of a thinking system which can create knowledge as if a human does. The objective of this research is to classify instant coffee by using electronic noses. We used eight types of coffee in Thailand market for this project which are (1) Moccona-select, (2) Moccona-royal gold, (3) Nescafe redcup, (4) Nescafe gold, (5) Khao Shong brown, (6) Khao Shong red, (7) Oem-Big C and (8) Superclass. We compared four structures of neural network to classify the coffee data. The precision of correctness is equal to 65.63 for a neural network structure as 7 input-layer nodes, 14 hidden-layer1 nodes, 48 hidden-layer2 nodes and 8 output-layer nodes. View full abstract»

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    Incremental PNN classifier for a versatile electronic nose

    Bhattacharyya, N. ; Metla, A. ; Bandyopadhyay, R. ; Tudu, B. ; Jana, A.
    Sensing Technology, 2008. ICST 2008. 3rd International Conference on

    Digital Object Identifier: 10.1109/ICSENST.2008.4757106
    Publication Year: 2008 , Page(s): 242 - 247
    Cited by:  Papers (1)

    IEEE Conference Publications

    Due to robustness of the probabilistic neural network (PNN) architecture, it has been widely used for pattern classification tasks. Commonly used PNN algorithms are not capable of incremental learning. The classifiers having the incremental learning ability can be of great benefit by automatically including the newly presented patterns in the training dataset without affecting class integrity of the previously trained classifier. This signifies that, the incremental classifiers have the ability to accommodate new classes and new knowledge within an already trained model. Under the present study, an electronic nose anchored aroma characterization model based on PNN classification strategy has been developed whereby the sensor array outputs of the electronic nose can be co-related to the sensory panel (tea tasters) quality scores for black tea. The whole study has been done in few tea gardens in north-east India. In pursuit of development of optimal strategy for data collection from dispersed locations followed by dynamically augmenting the training data corpus of the already trained PNN model, the incremental leaning mechanism has bee suitably grafted to the PNN model to have efficient co-relation of electronic nose signature with tea tasterspsila scores. The incremental PNN classifier promises to be a versatile pattern classification algorithm for black tea grade discrimination using electronic nose system. View full abstract»

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    Source localization by spatially distributed electronic noses for advection and diffusion

    Matthes, J. ; Groll, L. ; Keller, H.B.
    Signal Processing, IEEE Transactions on

    Volume: 53 , Issue: 5
    Digital Object Identifier: 10.1109/TSP.2005.845423
    Publication Year: 2005 , Page(s): 1711 - 1719
    Cited by:  Papers (19)

    IEEE Journals & Magazines

    Based on continuous concentration measurements from spatially distributed electronic noses, the location of a point source is to be determined. It is assumed that the emitted substance is transported by advection caused by a known homogeneous wind field and by isotropic diffusion. A new two-step approach for solving the source localization problem is presented. In the first step, for each sensor i, the set of points Pi is determined, on which the source can lie, taking only the specific concentration measurement Ci at sensor i into account. In the second step, an estimate for the source position is evaluated by intersecting the sets Pi. The new approach overcomes the problem of poor convergence of iterative algorithms, which try to minimize the least squares output error. Finally, experimental results showing the capability of the new approach are presented. View full abstract»

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    Quality Assessment of Beef Based of Computer Vision and Electronic Nose

    Chen Cunshe ; Li Xiaojuan ; Yuan Huimei
    Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing, 2007. SNPD 2007. Eighth ACIS International Conference on

    Volume: 2
    Digital Object Identifier: 10.1109/SNPD.2007.195
    Publication Year: 2007 , Page(s): 627 - 631
    Cited by:  Papers (2)

    IEEE Conference Publications

    Current techniques for beef quality evaluations rely on sensory methods. These procedures are subjective, prone to error, and difficult to quantify. Automated evaluation of color and odor is desirable to reduce subjectivity and discrepancies and assist with the creation of standards for inspectors worldwide. The objectives of this study were to develop color machine vision techniques for visual evaluation and to test electronic nose sensors for odor raw and beef. A color machine vision system was developed to analyze the color of beef samples. The system was able to analyze the color of samples with non-uniform color surfaces. An electronic nose sensors was used to measure odors of beef and beef stored at different temperatures, with different levels of spoilage. Discriminant function analysis was used as the pattern recognition technique to differentiate samples based on odors. Results showed that the electronic nose could discriminate differences in odor due to storage time and spoilage levels for beef. Results also showed good correlation of sensor reading with sensory scores overall, the electronic nose showed good sensitivity and accuracy. Results from this work could lead to methodologies that will assist in the objective and repeatable quality evaluation of beef. These methods have potential in industrial and regulatory application where rapid response, no sample preparation, and no need for chemicals are required. View full abstract»

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    Improving the classification accuracy in electronic noses using multi-dimensional combining (MDC)

    Hong Chen ; Goubran, R.A. ; Mussivand, T.
    Sensors, 2004. Proceedings of IEEE

    Digital Object Identifier: 10.1109/ICSENS.2004.1426233
    Publication Year: 2004 , Page(s): 587 - 590 vol.2
    Cited by:  Papers (3)  |  Patents (1)

    IEEE Conference Publications

    Traditional pattern recognition (PARC) methods, used in electronic noses (e-noses) are either parametric (such as k-nearest neighbors, KNN, and linear discriminant analysis, LDA) or non-parametric (such as artificial neural network and fuzzy logic). Multi-dimensional combining (MDC) is proposed to combine the classification outputs of individual classifiers into a more robust and accurate one. Two implementations are proposed to find the individual classifiers, one is based on various feature extraction methods and the other is based on various dimension reduction methods, with three means of combining. Six household fragrances were sampled using the Cyranose 320 e-nose device. The acquired data (600 measurements) was split into two sets, training and testing. Experiments were conducted at various concentrations of the sample smell, various sample numbers and various training numbers. Results show the advantage of MDC over the individual classifiers, and over the other traditional PARC methods under all conditions. View full abstract»

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    Discrimination of aliphatic homologues and isomers using trap and GC enhanced SAW based electronic noses

    Barie, N. ; Rapp, M.
    Sensors, 2004. Proceedings of IEEE

    Digital Object Identifier: 10.1109/ICSENS.2004.1426389
    Publication Year: 2004 , Page(s): 1183 - 1186 vol.3

    IEEE Conference Publications

    We present a new electronic nose system for discrimination of chemically related analytes and complex mixtures. The system employs a miniaturized array of eight polymer coated surface acoustic wave (SAW) sensors and a small preconcentration unit ('trap'). A GC column with atmospheric pressure air as the carrier gas is implemented as a separation unit. Design considerations are made with particular emphasis on the necessities arising from the interplay between sensors, coatings, trap, column, gas fluidics, and pattern recognition software. The system was tested against alkane homologues and hexane isomers. It successfully identifies n-hexane from other alkanes, even at very small concentrations (<1 ppm). View full abstract»

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    Advances in food analysis by electronic nose

    Di Natale, C. ; Macagnano, A. ; Mantini, A. ; Davide, F. ; D'Amico, A. ; Paolesse, R. ; Boschi, T. ; Faccio, M. ; Ferri, G.
    Industrial Electronics, 1997. ISIE '97., Proceedings of the IEEE International Symposium on

    Volume: 1
    Digital Object Identifier: 10.1109/ISIE.1997.651747
    Publication Year: 1997 , Page(s): SS122 - SS127 vol.1
    Cited by:  Papers (8)

    IEEE Conference Publications

    Electronic noses have been designed and utilized for a variety of different applications. Undoubtedly, among these, food analysis has gained the major attention. In fact in food analysis there is a double opportunity for electronic nose developers. The first is that the chemical patterns considered are sometimes rather complex, so the introduction of an instrument able to consider at the same time, in an easy experimental procedure, all the chemical patterns, is certainly appealing. The second aspect of food analysis concerns the wide utilization of natural olfaction and taste. Panels of well trained tasters and smellers are daily utilized to certify the goodness of foods and their fitting with the human taste. Therefore food analysis also represents a practical field where performances of natural and artificial olfaction and taste can be compared and where an electronic nose can be utilized as an essential support of the human capabilities. In this paper some key issues concerning the application of electronic noses to food analysis are examined and examples of applications, related to the electronic nose developed at the University of Rome Tor Vergata are illustrated and discussed View full abstract»

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    Dealing With Redundant Features and Inconsistent Training Data in Electronic Nose: A Rough Set Based Approach

    Bag, A.K. ; Tudu, B. ; Bhattacharyya, N. ; Bandyopadhyay, R.
    Sensors Journal, IEEE

    Volume: 14 , Issue: 3
    Digital Object Identifier: 10.1109/JSEN.2013.2286110
    Publication Year: 2014 , Page(s): 758 - 767

    IEEE Journals & Magazines

    In many applications of electronic nose, the instrument is trained with data generated by human experts prior to its deployment in the fields. Quite often, these data are conflicting and inaccurate and thus the performance of an electronic nose is degraded. Moreover, degradation of its performance may also be due to the presence of redundant features or sensors in the array. While deploying an electronic nose for a specific application, it is observed that some of the sensors may not be required and only a subset of the sensor array contributes to the decision, which implies that optimization of the sensor array is also very important. To obtain a consistent and precise data set, both the conflicting data and irrelevant features must be removed. The rough set theory is capable of dealing with such an imprecise, inconsistent data set and in this paper, the rough-set based algorithm has been applied to remove the conflicting training patterns and optimize the sensor array in an electronic nose instrument used for sensing aroma of black tea samples. View full abstract»

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    Geographical classification of Virgin Olive Oils by combining the electronic nose and tongue

    Haddi, Z. ; Boughrini, M. ; Ihlou, S. ; Amari, A. ; Mabrouk, S. ; Barhoumi, H. ; Maaref, A. ; Bari, N.E. ; Llobet, E. ; Jaffrezic-Renault, N. ; Bouchikhi, B.
    Sensors, 2012 IEEE

    Digital Object Identifier: 10.1109/ICSENS.2012.6411502
    Publication Year: 2012 , Page(s): 1 - 4

    IEEE Conference Publications

    Although the great interest of development of performed gas and liquid sensors, lack of cross-sensitivity still remains the major drawback of electronic sensing systems such as electronic nose and tongue. We propose here an approach aimed at overcoming this shortcoming. So a performed data fusion method of electronic nose and tongue was used in order to classify five Virgin Olive Oils (VOOs) picked up from five Moroccan geographical areas. The electronic nose instrument consists of five commercial available MOS TGS gas sensors and the electronic tongue was designed using four voltammetric electrodes. Two techniques, i.e., Principal Component Analysis (PCA) and Support Vector Machines (SVMs) were used to develop classification models using as inputs specific features extracted from the collected sensor signals. Great enhancement in successful discrimination between all VOOs was achieved when compared to the individual systems due to a performed low-level of abstraction data fusion. View full abstract»

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    Design of a Bionic Electronic Nose for Robot

    Xiaojun Zhang ; Minglu Zhang ; Jianguang Sun ; Chunyan He
    Computing, Communication, Control, and Management, 2008. CCCM '08. ISECS International Colloquium on

    Volume: 2
    Digital Object Identifier: 10.1109/CCCM.2008.69
    Publication Year: 2008 , Page(s): 18 - 23
    Cited by:  Papers (2)

    IEEE Conference Publications

    The robot assembled electronic nose has extensive applications, such as detecting toxic gases, searching explosives, detecting leakage, etc. Following the robot modular design concept, the paper designs a bionic electronic nose for robot, which has a human-like nasal cavity structure. It can simultaneously detect five kinds of different toxic gases, namely, CO, SO2, H2S, Cl2 and NH3, by using of electrochemical gas sensor array. The electrochemical gas sensor only responds to the specific gas, and has good selectivity and linear output, so the electronic nose dispenses with the pattern recognition algorithm in measuring multi-type gases simultaneously, which greatly reduces the operation task of olfactory system and improves the detection accuracy and efficiency to meet the robotpsilas real-time requirement, and can be conveniently changed corresponding gas sensors based on the target gases. By virtue of the compact structure, simple mechanical interface and communication interface, not only can the bionic electronic nose be used as a standardized component for all types of robots to help them to accomplish works related to olfaction, but also as a portable electronic nose applied to detect toxic gas in many fields. View full abstract»

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    Recognition of Coffee Using Differential Electronic Nose

    Brudzewski, K. ; Osowski, Stainslaw ; Dwulit, A.
    Instrumentation and Measurement, IEEE Transactions on

    Volume: 61 , Issue: 6
    Digital Object Identifier: 10.1109/TIM.2012.2184011
    Publication Year: 2012 , Page(s): 1803 - 1810
    Cited by:  Papers (1)

    IEEE Journals & Magazines

    This paper studies the application of the differential electronic nose for the recognition of coffee, particularly the forgery of it, made by mixing two different quality coffee brands (the mediocre product and the high-quality coffee type), sold as the high-quality coffee brand. Since the beans are practically unrecognizable by the shape and visual inspection, the only solution to this problem is the application of the chemical analysis. The usually applied approach is the liquid chromatography. However, it is a laborious and expensive method, requiring special equipment and an experienced operator. In this paper, we propose the application of the differential electronic nose, relying its decision on the measurement of the coffee smell by the semiconductor gas sensors organized in the form of a matrix. We will show that differential electronic nose applying the special procedure of signal processing is of sufficient sensitivity for the recognition of the forgery of coffee and performs much better than the classical electronic nose (e-nose). View full abstract»

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    Classification of beverages using electronic nose and machine vision systems

    Mamat, M. ; Samad, S.A.
    Signal & Information Processing Association Annual Summit and Conference (APSIPA ASC), 2012 Asia-Pacific

    Publication Year: 2012 , Page(s): 1 - 6

    IEEE Conference Publications

    In this work, the classification of beverages was conducted using three approaches: by using the electronic nose alone, by using the machine vision alone and by using the combination of electronic nose and machine vision. A total of two hundred and twenty eight beverages from fifteen different brands were used in this classification problem. A supervised Support Vector Machine was used to classify beverages according to their brands. Results show that by using the electronic nose alone and the machine vision alone were able to respectively classify 73.7% and 92.9% of the beverages correctly. When combining the electronic nose and the machine vision, the classification accuracy increased to 96.6%. Based on the results, it can be concluded that the combination of the electronic nose and machine vision is able to extract more information from the sample, hence improving the classification accuracy. View full abstract»

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    Putting olfaction into action: using an electronic nose on a multi-sensing mobile robot

    Loutfi, A. ; Coradeschi, S. ; Karlsson, L. ; Broxvall, M.
    Intelligent Robots and Systems, 2004. (IROS 2004). Proceedings. 2004 IEEE/RSJ International Conference on

    Volume: 1
    Digital Object Identifier: 10.1109/IROS.2004.1389374
    Publication Year: 2004 , Page(s): 337 - 342 vol.1
    Cited by:  Papers (3)

    IEEE Conference Publications

    Olfaction is a challenging new sensing modality for intelligent systems. With the emergence of electronic noses it is now possible to detect and recognise a range of different odours for a variety of applications. An existing application is to use electronic olfaction on mobile robots for the purpose of odour based navigation. In this work, we introduce a new application where electronic olfaction is used in cooperation with other types of sensors on a mobile robot in order to acquire the odour property of objects. The mobility of the robot facilitates the execution of specific perceptual actions, such as moving closer to objects to acquire odour properties. Additional sensing modalities provides the spatial detection of objects and electronic olfaction then acquires the odour property which can be used for discrimination and recognition of the object being considered. We examine the problem of deciding when, how and where the e-nose should be activated by planning for active perception. We investigate the use of symbolic reasoning techniques in this context and consider the problem of integrating the information provided by the e-nose with both prior information and information from other sensors (e.g., vision). Finally, experiments are performed on a mobile robot equipped with an e-nose together with a variety of sensors that can perform decision making tasks in realistic environments. View full abstract»

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    Source localization with a network of electronic noses

    Matthes, J. ; Gröll, L. ; Keller, H.B.
    Sensors, 2004. Proceedings of IEEE

    Digital Object Identifier: 10.1109/ICSENS.2004.1426338
    Publication Year: 2004 , Page(s): 987 - 990 vol.2

    IEEE Conference Publications

    A new two-step approach for locating an emission source is presented. It is based on an analytical diffusion-advection model and on pointwise concentration measurements from a network of stationary spatially distributed electronic noses (EN). In the first step, for each EN the set of points is determined, on which the source can lie, taking only the concentration measurement from the particular EN into account. In the second step, an estimate for the source position is evaluated by intersecting these sets. The new two-step approach overcomes the problem of poor convergence and multiple solutions of iterative algorithms, which minimize the output error of the model. Finally, experimental results are given, that show the capability of the new approach. View full abstract»

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    An Electronic Nose for Detecting Hazardous Chemicals and Explosives

    Kurup, P.U.
    Technologies for Homeland Security, 2008 IEEE Conference on

    Digital Object Identifier: 10.1109/THS.2008.4534439
    Publication Year: 2008 , Page(s): 144 - 149
    Cited by:  Papers (1)

    IEEE Conference Publications

    This study describes a portable system based on mimicking the mammalian olfactory mechanism (electronic nose), that can sense and identify chemical vapors by automated odor recognition. The electronic nose developed in this research consists of an array of tin oxide sensors, with each sensor in the array giving a different electrical response for a particular target vapor introduced into the sensing chamber. The combined output from the sensor array forms a fingerprint, or signature, that is unique for a particular odor. Pattern recognition techniques based on principal component analysis and artificial neural networks were developed for learning different chemical signatures. The electronic nose was successfully trained and tested in the laboratory to recognize various chemicals such as benzene, toluene, ethyl benzene, xylene, and gasoline. This study successfully demonstrates the feasibility of an electronic nose for detecting and identifying chemical and explosive vapors. View full abstract»

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    The design and testing of an Electronic Nose prototype for classification problem

    Mamat, M. ; Samad, S.A.
    Computer Applications and Industrial Electronics (ICCAIE), 2010 International Conference on

    Digital Object Identifier: 10.1109/ICCAIE.2010.5735108
    Publication Year: 2010 , Page(s): 382 - 386

    IEEE Conference Publications

    This paper reports the design of an Electronic Nose prototype based on commercially available metal oxide gas sensors and a temperature sensor. The Electronic Nose system comprises of a sampling chamber, sensing chamber, pumps, data acquisition system and controller unit and a computer for data analysis. To verify its repeatability, reproducibility and discriminative characteristics, several experiments were conducted using three beverages: blackcurrant juice, orange juice and soy milk. Results obtained from the experiments verify that the developed Electronic Nose is reliable to produce correct measurement with high repeatability, reproducibility and discriminative ability. View full abstract»

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    Least Square Support Vector Machines in Combination with Principal Component Analysis for Electronic Nose Data Classification

    Xiaodong Wang ; Jianli Chang ; Ke Wang ; Meiying Ye
    Information Science and Engineering (ISISE), 2009 Second International Symposium on

    Digital Object Identifier: 10.1109/ISISE.2009.138
    Publication Year: 2009 , Page(s): 348 - 352
    Cited by:  Papers (1)

    IEEE Conference Publications

    In this paper, an electronic nose data classification approach based on least square support vector machines (LS-SVM) in combination with principal component analysis (PCA) is investigated. The electronic nose data are first converted into PCA, where the data are projected from a high dimensional space into a low dimensional space, preferably two or three dimensions. Then the resulting features from the PCA are sent into the LS-SVM classifier in order to recognize the gas category. The performance of the proposed approach is validated by cross-validation technique. An experiment has been demonstrated by using coffee data from different types of coffee blends. Experimental results show that the LS-SVM in combination with PCA is an effective technique for the classification of electronic nose data. View full abstract»

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    Personal shirt odor classification using an electronic nose

    Chansri, C. ; Srinonchat, J.
    Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on

    Volume: 2
    Digital Object Identifier: 10.1109/ICCAE.2010.5451662
    Publication Year: 2010 , Page(s): 562 - 565

    IEEE Conference Publications

    This paper presents the classify personal shirt odor by electronic nose. Because body odor of a particular person varies, the researcher has picked up 4 volunteers to do exercise for 2 hours. After that bring their shirts to evaluate volatile organic compounds (VOCs) from the dirt on that shirts. The resistance of gas sensor array in the electronic nose will be changed depend on the amount VOCs when various kinds of gas sensor are combined together, the result will vary according to the property of each particular gas sensor. Then evaluate highest signal changing value of gas sensor and analyze by Principal Component Analysis (PCA). This technique is to identify the influence of the gas sensor array on the volunteer's shirts odor. From the experiment, we found that electronic nose can identify the odor of each shirt well, the data has been separated to 4 groups after analyze by PCA technique. It can extract data relation and percentage accumulation of PCA1 and PCA2 are 82.39. View full abstract»

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    An Electronic Nose Network System for Online Monitoring of Livestock Farm Odors

    Leilei Pan ; Yang, Simon X.
    Mechatronics, IEEE/ASME Transactions on

    Volume: 14 , Issue: 3
    Digital Object Identifier: 10.1109/TMECH.2009.2012850
    Publication Year: 2009 , Page(s): 371 - 376
    Cited by:  Papers (4)

    IEEE Journals & Magazines

    An electronic nose (e-nose)-based network system is developed for monitoring odors in and around livestock farms remotely. This network is built from compact e-noses that are tailored to measure odor compounds and environmental conditions such as temperature, wind speed, and humidity. The e-noses are placed at various applicable locations in and around the farm, and the collected odor data are transmitted via wireless network to a computer server, where the data processing algorithms process and analyze the data. The developed e-nose network system enables more effective odor management capabilities for more efficient operation of odor control practice by providing consistent, comprehensive, real-time data about the environment and odor profile in and around the livestock farms. Experimental and simulation results demonstrate the effectiveness of the developed system. View full abstract»

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    A new hardware approach to realize low-cost electronic noses

    Depari, A. ; Flammini, A. ; Marioli, D. ; Rosa, S. ; Taroni, A. ; Falasconi, M. ; Sberveglieri, G.
    Sensors, 2005 IEEE

    Digital Object Identifier: 10.1109/ICSENS.2005.1597680
    Publication Year: 2005
    Cited by:  Papers (4)

    IEEE Conference Publications

    In this paper, a new approach to realize low-cost electronic noses is presented. Particularly, a novel instrument to manage high-value resistive sensors varying over a wide range, from kiloOhms to gigaOhms, is discussed. It is a modular architecture which takes advantage from an improved resistance-to-period converter (RPC), where sensors are DC powered. Relative standard deviation is below 0.01% and relative displacement to the reference line is less than 1% over six decades if commercial resistors are considered. A prototype has been realized to manage up to eight sensors, qualify and quantify substances and communicate results to Internet View full abstract»

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    Electronic Noses as Flexible Tools to Assess Food Quality and Safety: Should We Trust Them?

    Concina, I. ; Falasconi, M. ; Sberveglieri, V.
    Sensors Journal, IEEE

    Volume: 12 , Issue: 11
    Digital Object Identifier: 10.1109/JSEN.2012.2195306
    Publication Year: 2012 , Page(s): 3232 - 3237
    Cited by:  Papers (1)

    IEEE Journals & Magazines

    This paper presents three different applications of an electronic nose (EN) based on a metal oxide sensor array, in order to illustrate the broad spectrum of potential uses of the technique in food quality control. The following scenarios are considered: 1) the screening of a typical error that may occur during the processing of tomato pulp, which leads to sensory damage of the product; 2) the detection of microbial contamination by Alicyclobacillus spp. (ACB) affecting soft drinks; and 3) the proof of evidence of extra virgin olive oil fraudulently adulterated with hazelnut oil. In each case, the EN is able to identify the spoiled product by means of the alterations in the pattern of volatile compounds, reconstructed by principal component analysis of the sensor responses. View full abstract»

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    Design and implementation a real-time electronic nose system

    Kai Song ; Qi Wang ; Hongquan Zhang ; Yingguo Cheng
    Instrumentation and Measurement Technology Conference, 2009. I2MTC '09. IEEE

    Digital Object Identifier: 10.1109/IMTC.2009.5168519
    Publication Year: 2009 , Page(s): 589 - 592
    Cited by:  Papers (2)

    IEEE Conference Publications

    A real-time electronic nose system is designed to analyze methane (CH4), hydrogen (H2) and their mixtures, the main combustible gases in the environment. The system is based on a single chip for acquiring measurement data from a gas sensor array. Four Fe2O3 gas sensors with little humidity effect are employed in the gas sensor array. A principal component regression (PCR) method is applied to process the electronic nose data. Software is developed in the LabVIEW environment for detecting the above combustible gases. Experimental results show that PCR has a good performance for predicting gas concentrations in a binary gas mixture. It proves that the designed electronic nose system can detect the combustible gases in real-time and quantify their concentrations accurately. View full abstract»

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    Regression model on electronic nose data from aromatic rice samples

    Jana, A. ; Bhattacharyya, N. ; Mukheriee, S. ; Ghosh, D. ; Roy, J.K. ; Bandvopadhyay, R. ; Tudu, B.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461712
    Publication Year: 2012 , Page(s): 418 - 421

    IEEE Conference Publications

    As of today, aroma of rice is measured by an expert sensory panel and they assign scores like `+', `++', `+++' and `NA' for mild, medium, strong and non aromatic varieties of rice respectively. This method of human panel testing is very subjective with numerous problems like inaccuracy, non-repeatability and it is laborious and time consuming also. On the other hand, the analytical instruments, which are used for this purpose are prohibitively expensive and are available in the laboratories only. It is in this pursuit, an electronic nose with an array of gas sensors has been developed for aroma measurement of rice. This user friendly and low cost electronic nose may be extremely useful for rice scientists, researchers and exporters to determine the aroma of aromatic rice. In this paper, we describe the experimental setup and the regression model for classification of rice samples. With unknown rice samples, aroma based classification accuracy by multi-sensor electronic nose using the regression model, has been found to be more than 80%. View full abstract»

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    Black tea quality evaluation using electronic nose: An Artificial Bee Colony approach

    Dutta, A. ; Tudu, B. ; Bandyopadhyay, R. ; Bhattacharyya, N.
    Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE

    Digital Object Identifier: 10.1109/RAICS.2011.6069290
    Publication Year: 2011 , Page(s): 143 - 146

    IEEE Conference Publications

    The process of evaluating the quality of black tea by human sensory panel known as “Tea Tasters” is very subjective and its accuracy is questionable. As a result various instrumental setups have been investigated in the past for quality determination of black tea. The electronic nose is one such instrument, consisting of sensor arrays, odor detection and data acquisition system. Many clustering algorithms are available that can be used to differentiate between tea with various scores as given by the “Tea Tasters”, the data for which is obtained by an electronic nose. Recently, a heuristic algorithm called the Artificial Bee Colony (ABC) has been devised by Karaboga mainly for solving optimization problems but which has also been applied for data clustering. In this paper, the algorithm devised by Karaboga has been used on the data obtained by an electronic nose to distinguish among the various scores of black tea. Also the results obtained by ABC have been compared with the well known Fuzzy C-Means (FCM) algorithm. The paper is concluded by some observations made by the authors. View full abstract»

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    Independent Component Analysis and Neural Network Applied on Electronic Nose System

    Xiaochuan He ; Shoushui Wei ; Ruiqing Wang
    Bioinformatics and Biomedical Engineering, 2008. ICBBE 2008. The 2nd International Conference on

    Digital Object Identifier: 10.1109/ICBBE.2008.119
    Publication Year: 2008 , Page(s): 490 - 493

    IEEE Conference Publications

    Electronic noses are being developed as systems for the automated detection and classification of odors, vapors, and gases. Based on the study of the theory and constitutes of the electronic nose system, a set of independent component analysis (ICA) algorithms with BP neural network, for detection of gas mixture is designed and constructed, and the data processing which is measured by an electronic nose system consisting of five gas sensors is carried out. The results show that ICA algorithm can make a good classification for the data and reduce the data correlation. As the input of the BP network, it can predigest the structure and improve the convergence speed of the network. View full abstract»

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    Development and application of electronic nose for agricultural robot

    Siyang, S. ; Lorwongtragool, P. ; Noosidum, A. ; Wongchoosuk, C. ; Kerdcharoen, T.
    Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on

    Digital Object Identifier: 10.1109/ECTICon.2013.6559500
    Publication Year: 2013 , Page(s): 1 - 4

    IEEE Conference Publications

    A portable electronic nose (E-nose) based on metal oxide gas sensor was used for detection of a total volatile compound in soil headspace and greater wax moth (Galleria mellonella L.). Sensor elements were selected in order to possibly respond to a wide range of the volatiles including both of oxidizing and reducing gases. The aim of this work was to relate the soil volatile fingerprints at their depth levels and less number of greater wax moth that can be detected by electronic nose. Soil was sampled from the field of the vinery located near Khao Yai world heritage, Thailand at a depth level of 10 cm, 30 cm and 50 cm. Male and female greater wax moths were treated from egg to senile adult in plastic box and measured with electronic nose by varying number of moth. The results could identify the difference of the volatile fingerprints by employing principal component analysis (PCA) as the signal pattern recognition technique. The volatile profiles from eight TGS elements relating chemical emissions will be discussed in more details. View full abstract»

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    A Novel Cost-Effective Portable Electronic Nose for Indoor-/In-Car Air Quality Monitoring

    Tian, F.C. ; Kadri, C. ; Zhang, L. ; Feng, J.W. ; Juan, L.H. ; Na, P.L.
    Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on

    Digital Object Identifier: 10.1109/CDCIEM.2012.9
    Publication Year: 2012 , Page(s): 4 - 8

    IEEE Conference Publications

    With today's competitive and complex environment which results from rapid industrial development, air quality monitoring is becoming a necessity. Devising devices that provide reliable, cost-effective, and fast monitoring of indoor/in-car harmful chemical compounds is of paramount importance for governments as well as individuals. Sensors array systems or commonly called electronic nose (E-nose) systems have been used in various fields of consumer applications. Owing to their versatility and ease of use, these systems can be an adequate alternative for indoor/in-car air quality monitoring. In this study a novel self-made and cost-effective electronic nose aiming at quantifying five indoor/in-car harmful gases (formaldehyde, benzene, CO, NO2, toluene), has been devised and implemented at the college of electronic and communication engineering of Chongqing University, China. A hybrid genetic algorithm support machine vector regression (GA-LSSVMR) model is used for pattern recognition and concentrations estimation. With absolute relative errors of prediction (MAREP) less than 10%, these models outperform those based on hybrid genetic algorithm back-propagation neural network regression (GA-BPNNR). Furthermore, the best regression models were embedded into the system for real-time concentration estimation, our system's predictions mostly agree with those of specific gas detectors. The product will therefore be a good alternative for indoor/in-car air quality monitoring. View full abstract»

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    Malicious odor item identification using an electronic nose based on support vector machine classification

    ul Hasan, N. ; Ejaz, N. ; Ejaz, W. ; Hyung Seok Kim
    Consumer Electronics (GCCE), 2012 IEEE 1st Global Conference on

    Digital Object Identifier: 10.1109/GCCE.2012.6379638
    Publication Year: 2012 , Page(s): 399 - 400

    IEEE Conference Publications

    The aim of this study is to develop an electronic nose for identifying the spoiled meat stocked inside a refrigerator. Electronic nose analyses the samples of beef and fish and applies a classifier named support vector machine (SVM) to identify the meat creating malodor. To evaluate, the experiment is performed for a week. The results indicate that SVM classifier exhibits good generalization performance and enable accuracy rate of almost 94.5 % for both beef and fish. This means that SVM is an effective pattern classification technique for spoiled meat identification using electronic nose. View full abstract»

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    Substance classification and measure for low-cost electronic noses

    Depari, A. ; Flammini, A. ; Marioli, D. ; Rosa, S. ; Taroni, A. ; Falasconi, M. ; Sberveglieri, G.
    Sensors, 2005 IEEE

    Digital Object Identifier: 10.1109/ICSENS.2005.1597944
    Publication Year: 2005
    Cited by:  Papers (2)

    IEEE Conference Publications

    In this paper, a new approach to classify and quantify substances is presented to be suitable for low-cost electronic noses. An appropriate architecture based on multi-layer perceptron neural networks is proposed to shorten training set and improve accuracy if a substance is clearly detected. Elaboration is suitable to be implemented in an eight-bit microcontroller due to its simplicity. Experimental results, reported in presence of mixture of ethanol and methanol, shows a classification error within 10% and a quantification error in the order of 10% of full scale View full abstract»

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    Mimicking biology: applications of cognitive systems to electronic noses

    Keller, P.E.
    Intelligent Control/Intelligent Systems and Semiotics, 1999. Proceedings of the 1999 IEEE International Symposium on

    Digital Object Identifier: 10.1109/ISIC.1999.796696
    Publication Year: 1999 , Page(s): 447 - 451

    IEEE Conference Publications

    The electronic nose draws its inspiration from biology. Both the electronic nose and the biological olfactory system consist of an array of chemical sensing elements and a pattern recognition system. This paper reviews the basic concepts of electronic noses and their relationship to biological olfaction. Different approaches to chemical data analysis including statistical methods, standard artificial neural network approaches, and those based on advanced biological models of the olfaction are described. Finally, a prototype system is reviewed View full abstract»

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    Comparison of multivariate normalization techniques as applied to electronic nose based pattern classification for black tea

    Tudu, B. ; Kow, B. ; Bhattacharyya, N. ; Bandyopadhyay, R.
    Sensing Technology, 2008. ICST 2008. 3rd International Conference on

    Digital Object Identifier: 10.1109/ICSENST.2008.4757108
    Publication Year: 2008 , Page(s): 254 - 258

    IEEE Conference Publications

    An appropriate normalization technique selection is one of the key issues for increasing the accuracy of correct classification for pattern recognition in an electronic nose system. This paper presents a comparative study of different normalization techniques for enhancing pattern classification of black tea using electronic nose. For this study black tea samples were collected from different tea gardens in India. At first principal component analysis (PCA) was used to investigate presence of clusters in the sensors responses in multidimensional space. Then different normalization techniques were used on the black tea data. Finally classification performances were done using BP-MLP. BP-MLP algorithm for black tea classifications using normalized data marginally enhances the pattern recognition accuracy of electronic nose system. View full abstract»

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    Chemical Sensors and Electronic Noses Based on 1-D Metal Oxide Nanostructures

    Po-Chiang Chen ; Guozhen Shen ; Chongwu Zhou
    Nanotechnology, IEEE Transactions on

    Volume: 7 , Issue: 6
    Digital Object Identifier: 10.1109/TNANO.2008.2006273
    Publication Year: 2008 , Page(s): 668 - 682
    Cited by:  Papers (45)

    IEEE Journals & Magazines

    The detection of chemicals such as industrial gases and chemical warfare agents is important to human health and safety. Thus, the development of chemical sensors with high sensitivity, high selectivity, and rapid detection is essential and could impact human beings in significant ways. 1-D metal oxide nanostructures with unique geometric and physical properties have been demonstrated to be important candidates as building blocks for chemical sensing applications. Chemical sensors composed of a wide range of pristine 1-D metal oxide nanostructures, such as In2O3, SnO2, ZnO, TiO2, and CuO, have been fabricated, and exhibited very good sensitivity in the detection of important industrial gases, chemical warfare agents, and human breath. In this review, we provide an overview of this chemical sensing field. Various key elements of the topics will be reviewed, including 1-D metal oxide nanostructure synthesis, electronic properties of nanowire-based FETs, and their chemical sensing behaviors. In addition, this paper provides a review of the recent development of electronic nose systems based on metal oxide nanowires, which indicate great potential for the improvement of sensing selectivity. View full abstract»

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    Towards a fully integrated electronic nose SoC

    Shih-Wen Chiu ; Jen-Huo Wang ; Guan-Ting Lin ; Chia-Lin Chang ; Hsin Chen ; Kea-Tiong Tang
    Circuits and Systems (MWSCAS), 2012 IEEE 55th International Midwest Symposium on

    Digital Object Identifier: 10.1109/MWSCAS.2012.6291983
    Publication Year: 2012 , Page(s): 166 - 169

    IEEE Conference Publications

    Electronic noses (e-nose) have been studied for several years and extensively applied; however, they are limited by their volume and high manufacturing cost. Portable devices have become popular in recent years; therefore, it is crucial to integrate e-noses in portable devices (e.g., mobile phones). This study used TSMC 90nm 1P9M CMOS MSG technology to develop a front-end system-on-chip (SoC) for an electronic nose. The SoC contained interdigitated electrodes, multi-channel sensor interface circuits, an analog to digital converter, and a digital continuous restricted Boltzmann machine (CRBM). Various conducting-polymer materials were titrated on the interdigitated electrodes to form an on-chip sensor array. This SoC was controlled through an external microcontroller to perform odor identification and analysis. The simulation results of the SoC and gas classification show that this chip is suitable for portable applications and further integration. View full abstract»

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    New methods for the early detection of fungal contamination on green coffee beans by an Electronic Nose

    Sberveglieri, V. ; Fava, P. ; Pulvirenti, A. ; Concina, I. ; Falasconi, M.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461711
    Publication Year: 2012 , Page(s): 414 - 417

    IEEE Conference Publications

    Electronic Noses (ENs) are attracting a relevant interest as valuable monitoring tool in several fields, between which the food industry, with special emphasis on microbial contamination detection on food products. Herein we present the ability of an Electronic Nose to early identify the fungi contamination in green coffee. The detection of mold in green coffee was achieved thanks to the cooperative use of different chemical and microbiological (fenotipic) techniques aimed to detect the secondary metabolites. Obtained results strongly recommend the use of the ENs as screening tools in industrial quality control laboratories, emphasizing at the same time some limits still affecting the sensor technology. View full abstract»

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    A flexible electronic nose for odor discrimination using different methods of classification

    Chilo, J. ; Horvath, G. ; Lindblad, T. ; Olsson, R. ; Redeby, J. ; Roeraade, J.
    Real Time Conference, 2009. RT '09. 16th IEEE-NPSS

    Digital Object Identifier: 10.1109/RTC.2009.5321955
    Publication Year: 2009 , Page(s): 317 - 320

    IEEE Conference Publications

    Ovarian cancer is one of the leading causes of death from cancer in women. The lifetime risk is around 1.5%, which makes it the second most common gynecologic malignancy (the first one being breast cancer). To have a definitive diagnose, a surgical procedure is generally required and suspicious areas (samples) will be removed and sent for microscopic and other analysis. This paper describes the result of a pilot study in which an electronic nose is used to ldquosmellrdquo the aforementioned samples, analyze the multi-sensor signals and have a close to real-time answer on the detection of cancer. Besides being fast, the detection method is inexpensive and simple. Experimental analysis using real ovarian carcinoma samples shows that the use of proper algorithms for analysis of the multi-sensor data from the electronic nose yielded surprisingly good results with more than 77% classification rate. The electronic nose used in this pilot study was originally developed to be used as a ldquobomb dogrdquo and can distinguish between e.g. TNT, Dynamex, Prillit. However, it was constructed to be a flexible multi-sensor device and the individual (16) sensors can easily be replaced/exchanged. This is suggestive for further investigations to obtain even better results with new, specific sensors. In another pilot experiment, headspace of an ovarian carcinoma sample and a control sample were analyzed using gas chromatography-mass spectrometry. Significant differences in chemical composition and compound levels were recorded, which would explain the different response obtained with the electronic nose. View full abstract»

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    Use of an electronic nose to estimate paper insulation degradation

    Lessard, M.-C. ; Noirhomme, B. ; Larocque, G. ; Vienneau, M.
    Electrical Insulation (ISEI), Conference Record of the 2012 IEEE International Symposium on

    Digital Object Identifier: 10.1109/ELINSL.2012.6251488
    Publication Year: 2012 , Page(s): 350 - 355

    IEEE Conference Publications

    The ultimate life of a transformer primarily depends on the insulation of its active part, i.e., mainly the oil and paper complex. At present, the tools used to directly determine the state of solid insulation require transformers to be detanked in order to take paper samples for laboratory analysis. Indirect methods (oil analysis) require a complex separation system and need accurate calibration of a detector. The electronic nose technology is now widely used in different industrial areas to detect the degradation of several convenience goods like wine, coffee and cheese. Based on metal oxide semiconductor sensors from different technologies, these instruments are designed to detect odours just like a human nose. They can be set to recognize different types of degradation processes, thus serving as an efficient diagnostic tool. This original method applied to the characterization of insulation paper aging should be easier to perform than ASTM D 4243, which required the oil to be removed from the paper, dissolving it, and then measuring the degree of polymerization (DPv) by viscosimetry. This paper presents the development of a method that uses an electronic nose to determine the degree of polymerization of paper samples processed through a head space system with an automatic sampler device without having to remove the oil. Aged laboratory samples were analyzed with the electronic nose and with the standard ASTM D 4243 test method to build a calibration curve. This curve was then used to determine the DPv value of different field paper samples and compared to ASTM D 4243 results. Until now, the method developed by IREQ is reproducible and less time-consuming than the standard method currently used by Hydro-Québec, but is unfortunately less precise (20% vs. 5%). More work is needed to optimize the calibration model to potentially improve the method's precision. View full abstract»

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    A comparison between an electronic nose and human olfaction in a selected case study

    Di Natale, C. ; Macagnano, A. ; Paolesse, R. ; Tarizzo, E. ; D'Amico, A. ; Davide, F. ; Boschi, T. ; Faccio, M. ; Ferri, G. ; Sinesio, F. ; Bucarelli, F.M. ; Moneta, E. ; Quaglia, G.B.
    Solid State Sensors and Actuators, 1997. TRANSDUCERS '97 Chicago., 1997 International Conference on

    Volume: 2
    Digital Object Identifier: 10.1109/SENSOR.1997.635483
    Publication Year: 1997 , Page(s): 1335 - 1338 vol.2

    IEEE Conference Publications

    An electronic nose is now becoming available as a commercial product. Nevertheless its performances are not fully understood and interpreted. Also the differences between electronic noses and the human olfaction have not yet been sufficiently studied. This is an important issue in many industrial sectors, such as food analysis. In this paper a comparison between the performances of an electronic nose and a panel of human tasters is presented in a selected case (tomato paste). An extensive set of tools for data analysis was available. A number of chemometrics based methods (principal component analysis and cluster analysis) and neural networks (feedforward backpropagation trained networks, self organizing maps, adaptive resonance theory based networks) have been utilized to analyze electronic nose data in order to extract the relevant information. The electronic nose and the human panel show strong similarities but the former displays a more concise classification capability for the data View full abstract»

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    Simulated Detection of VCHs in Soil by Using a Self-made Electronic Nose

    Xiaogang Wen ; Rui Liu ; Qiang Cai ; Fanyang Bu ; Mei Wan
    Computer Distributed Control and Intelligent Environmental Monitoring (CDCIEM), 2012 International Conference on

    Digital Object Identifier: 10.1109/CDCIEM.2012.152
    Publication Year: 2012 , Page(s): 617 - 620

    IEEE Conference Publications

    An electronic nose principally composed of a photo ionization detector (PID) was developed for rapid detection of volatile chlorinated hydrocarbons (VCHs) in contaminated soil. Interference gases such as benzene homologues were removed with a halogenated hydrocarbon RAE-SEP tube and the removal effect was estimated with gas chromatography (GC). Different concentrations of perchloroethylene (PCE) and trichloroethylene (TCE) gases were used to evaluate the precision and reproducibility of electronic nose by comparing with GC. On these bases, ventilation purification experiments of contamination soil were simulated with three typical paddy soils in Yangtze River delta region. Results showed that RAE-SEP tube was effective to remove interference gases, with 80~97% of benzene homologues being removed and at the same time more than 90% of VCHs passed through. With PCE or TCE gas, a linear dependence was derived between the data got by electronic nose and GC, the slope is near 1.0 and the correlation coefficient R2>;0.99. Electronic nose showed data consistency with GC (R2>;0.99, n=47)when used for soil ventilation process monitoring. Therefore, electronic nose is applicable for rapid determination of soil pollution by VCHs, improving the efficiency of pollution diagnosis and remediation. View full abstract»

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    Simultaneous estimation of odor classes and concentrations using an electronic nose

    Daqi, G. ; Miao Qin ; Nie Guiping
    Neural Networks, 2004. Proceedings. 2004 IEEE International Joint Conference on

    Volume: 2
    Digital Object Identifier: 10.1109/IJCNN.2004.1380145
    Publication Year: 2004 , Page(s): 1353 - 1358 vol.2

    IEEE Conference Publications

    This paper sets up an electronic nose, and presents a kind of combinative and modular single-hidden-layer perceptrons. Every module is made up of multiple single-input single-output multilayer perceptrons (MLPs). One MLP is regarded as an expert, and one module consists of several such experts. In electronic noses, one module is behalf of a kind of odor, and determines its similar degrees, namely its strengths. The most similar module gives the class and strength of the odor. By means of enlarging the input components to the range of [0, 6.0] and transforming the standard sigmoid activation function to be f(x)=3(1+exp(-x/3))-1, the learning speeds of MLPs are sped up. The experiment for simultaneously estimating the classes and concentrations of 4 kinds of fragrant materials, namely ethanol, ethyl acetate, ethyl caproate and ethyl lactate in different concentrations, shows that the proposed method is quite effective. View full abstract»

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    An embedded Electronic Nose for identification of aroma index for different tea aroma chemicals

    Das, A. ; Ghosh, T.K. ; Ghosh, A. ; Ray, H.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461745
    Publication Year: 2012 , Page(s): 577 - 582

    IEEE Conference Publications

    Quantification of tea quality based on its aroma characteristics using a portable/handheld device with a set of tea aroma volatile specific sensors and generic gas sensors is one of the valuable requirements in tea industry. Conventionally the tea quality parameters are quantified in a scale of 1 to 10 based on human senses by some professional human experts called “tea tasters”. Electronic Nose has been successfully implemented for quality evaluation of finished tea as well as end-point detection of tea fermentation process. This paper includes the description of Handheld Electronic Nose (HEN) and its response in various tea aroma chemicals to validate the sensor array and the system. The overall system is based on a 16-bit microcontroller platform with touch screen as graphical user interface. View full abstract»

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    Beer classification by electronic nose

    Pornpanomchai, C. ; Suthamsmai, N.
    Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on

    Volume: 1
    Digital Object Identifier: 10.1109/ICWAPR.2008.4635799
    Publication Year: 2008 , Page(s): 333 - 338

    IEEE Conference Publications

    An electronic nose is a smart instrument that is designed to detect and discriminate among complex odors by using arrays of sensors. The arrays of sensors are treated with a variety of odor-sensitive biological or chemical materials. An electronic nose is a project that uses two researches areas which are hardware for developing sensors and software using theorem from neuron network technology. The operation begins when sensors hit the smell of beer. The result is converted from analog to digital and represented in a graph form. An artificial intelligence is a tool of a thinking system which can create knowledge as if a human does. This project concerns training and testing beer by using 10 types of beer which are Asahi, Chang, Cheer, Samiguel, Singha, Kloster, Heineken, Leo, Tiger and Tai. We separate the experiment into two parts. The first part is immediate checking, which is performed immediately after the beer can is opened. The second part is to check the beer after the can is opened for 24 hours. This project consists of two data classifications which are Rule base and Neural Network. Rule base is used to classify unknown data. Neural network is used to check types of beer. Our structure in a neural network consists of 25 input nodes, 28 hidden nodes, and 10 output nodes. The percentage of correctness is equal to 87.5%. View full abstract»

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    Detection of microorganisms in water and different food matrix by Electronic Nose

    Nunez Carmona, E. ; Sberveglieri, V. ; Pulvirenti, A.
    Sensing Technology (ICST), 2013 Seventh International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2013.6727743
    Publication Year: 2013 , Page(s): 699 - 703

    IEEE Conference Publications

    In the food matrix are involved very elemental products like water to other more complex like, for example, processed and non processed, vegetables and dairy products. All these matrix pass very restrictive controls and a intensive monitoring during the processing time to evaluate their safety and quality. The early detection of the contamination is critical to preserve the consumer's health and to avoid economic losses for the industry. On the other hand, microorganisms are part of a wide range and significant managing process, like fermentations used since ancient times and applied to many different matrix. One of this group of microorganism are Lactic Acid Bacteria (LAB) that play a different role, fermentative or contaminant, depending on the matrix where are founded. Electronic Noses (ENs) has shown to be a very effective and fast tool for monitoring microbiological spoilage and food quality control. The ability of this instrument can also be used for the selection of the most appropriate species or strains for a determinate purpose. The aim of this study was essay the ability of a novel EN for the detection of bacterial presence in water and other foodstuff in cooperation with classical microbiological and chemical techniques like Gas Chromatography Mass Spectrometry with SPME (GC-MS-SPME). The achieved results notably advocate the use of EN in industry laboratories like a very important tool in quality control. View full abstract»

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    Classification of aromatic and non-aromatic rice using electronic nose and artificial neural network

    Jana, A. ; Bhattacharyya, N. ; Bandyopadhyay, R. ; Adhikari, B. ; Tudu, B. ; Kundu, C. ; Roy, J.K. ; Mukherjee, S.
    Recent Advances in Intelligent Computational Systems (RAICS), 2011 IEEE

    Digital Object Identifier: 10.1109/RAICS.2011.6069320
    Publication Year: 2011 , Page(s): 291 - 294
    Cited by:  Papers (1)

    IEEE Conference Publications

    Classification of rice is carried out by human experts in the industry and apart from other attributes like grain size, elongation ratio, aroma plays a significant role in the classification process. On the basis of aroma, the rice samples are manually categorized as strongly aromatic, moderately aromatic, slightly aromatic and non aromatic. Instrumental evaluation of aroma of rice is much needed in the industry and in this paper, we describe an electronic nose instrument, that has been developed for aroma characterization of rice. Artificial neural network is used for the pattern classification on data obtained from the sensor array of the electronic nose. With unknown rice samples, aroma based classification accuracy has been observed to be more than 80%. View full abstract»

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    Detection of volatile compounds in urine using an electronic nose instrument

    Sabeel, T.M.A. ; CheHarun, F.K. ; Eluwa, S.E. ; Sabeel, S.M.A.
    Computing, Electrical and Electronics Engineering (ICCEEE), 2013 International Conference on

    Digital Object Identifier: 10.1109/ICCEEE.2013.6633956
    Publication Year: 2013 , Page(s): 1 - 4

    IEEE Conference Publications

    Current clinical diagnostics are based on biochemical, physics and microbiological methods. The electronic nose system used to detect chemical components or VOCs in urine sample is meant to classify different urine components so as to be able to diagnose diseases and other elements accurately. This study used urine sample from 13 patients from Universiti Teknologi Malaysia (UTM) health centre for the urine analysis. Findings from the study revealed that six patients tested abnormal with mucus while only one patient tested abnormal with bacteria and two healthy. The test conducted from using Cyranose 320 shows that volatile compounds were present in their urine. Principal component analysis (PCA) was used to extract first and second principal components from 32 sensors used for the urine analysis. The study suggests the possibility of using e-nose as an early detection system for illness such as diabetes and bacterial infections. View full abstract»

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    Towards the Development of a Portable Smell-Seeing Electronic Nose and its Applications in Amine Recognition

    Tang Zhonglin ; Yang Jianhua ; Xu Ying ; Yu JunYun
    Image and Signal Processing, 2009. CISP '09. 2nd International Congress on

    Digital Object Identifier: 10.1109/CISP.2009.5304113
    Publication Year: 2009 , Page(s): 1 - 5

    IEEE Conference Publications

    A portable smell-seeing electronic nose (e-nose) device based on webcam and white LEDs was designed. The time stability and spatial uniformity errors of the device in color measuring was processed. Six kinds of sensitive materials, including porphyrins and phthalocyanines with typical central ions and functional groups, were selected to fabricate the odor sensitive arrays and their principles of color change upon interaction with odors were analyzed. The odor recognition capability of the e-nose was then tested by six volatile organic amines and the results showed that the designed smell-seeing electronic nose was capable of not only discriminating all the vapors correctly but also clustering those analytes with similar molecular structures and electronic properties. View full abstract»

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    Diagnosis of bacteria for diabetic foot infection using electronic nose technology

    Yusuf, N. ; Omar, M.I. ; Zakaria, A. ; Abdullah, A.A. ; Kamarudin, L.M. ; Shakaff, A.Y.M. ; Masnan, M.J. ; Zakaria, N.Z.I. ; Yeap, E.J. ; Othman, A. ; Yassin, M.S.
    Wireless Sensor (ICWISE), 2013 IEEE Conference on

    Digital Object Identifier: 10.1109/ICWISE.2013.6728791
    Publication Year: 2013 , Page(s): 114 - 118

    IEEE Conference Publications

    Foot infections may lead to serious complications if failed to detect at an early stage; especially for diabetic patients. It is necessary to develop an easy and reliable method to identify and classify the causative bacteria from the wound to assist health care practitioners. Therefore, this study proposed an alternative to the conventional technique by using an electronic nose with 32 matrices of non-specific conducting polymer sensors known as Cyranose320. A novel odour detection method is developed and targeted for microbial bacteria causing infection on diabetic foot using direct injection of static headspace. The bacteria are obtained from the clinical specimens by swabbing technique and isolated in a blood agar medium to verify the performance of the bacterial specialized medium. Various classification algorithm techniques proved that each bacteria produce certain characteristic of odour and can be used as a surrogate bio-marker. Thus, preliminary results from this study show that the electronic nose is able to identify and classify the presence of causative bacteria with high success rate of over 90% in diabetic foot infection. View full abstract»

  • Full text access may be available. Click article title to sign in or learn about subscription options.

    Development of electronic nose for diagnosis of lung cancer at early atage

    Ping Wang ; Xing Chen ; Fengjuan Xu ; Deji Lu ; Wei Cai ; Kejing Ying ; Yongqing Wang ; Yanjie Hu
    Information Technology and Applications in Biomedicine, 2008. ITAB 2008. International Conference on

    Digital Object Identifier: 10.1109/ITAB.2008.4570629
    Publication Year: 2008 , Page(s): 588 - 591
    Cited by:  Papers (4)

    IEEE Conference Publications

    In this paper, we proposed a novel non-invasive electronic nose for detection and diagnosis of lung cancer based on an electronic nose instrument which includes a gas extraction and capillary column to concentrate, desorb and separate volatile organic compounds (VOCs) in patientspsila breath, respectively. Surface Acoustic Wave (SAW) gas sensors was used to detect chemical compounds. The specific VOCs exhaled by lung cancer cells in the microenvironment are proven the source biomarkers of lung cancer. The clinical experimental results show that this kind of novel electronic nose is effective for recognition of lung cancer patents and healthy persons and will be also possible non-invasive method to diagnose of lung cancer at early stage. View full abstract»

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    Classification of instant coffee odors by electronic nose toward quality control of production

    Thepudom, T. ; Sricharoenchai, N. ; Kerdcharoen, T.
    Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON), 2013 10th International Conference on

    Digital Object Identifier: 10.1109/ECTICon.2013.6559482
    Publication Year: 2013 , Page(s): 1 - 4

    IEEE Conference Publications

    Electronic nose (e-nose) is a device that plays an important role for odor assessment due to its low cost and widerange applications. Currently, e-nose is widely used in the food industry such as coffee, wines, beers etc. Coffee is one of the most popular beverages in the human history. There are various types of products, for examples, roast/round, instant/soluble and ready-to-drink coffees etc. At present, coffee shop businesses are growing in Thailand and each of which has promoted its identity of coffee aroma. Nevertheless, the taste and aroma of the coffee are often not well controlled due to the lack of method to identify the odor standard. Hence, this problem should be solved to maintain consumers' satisfaction. In this paper, we have studied about the factors that affect on coffee taste and coffee aroma by using electronic nose. This instrument was designed to be portable and capable of measuring the coffee samples in both liquid and solid forms. Metal oxide semiconductors (MOS) were used as the sensing materials to detect changing of coffee odor at different conditions. The e-nose is composed of a flow system, a sensor array and data acquisition/analysis. It was found that the e-nose is capable to distinguish different brands of instant coffee products and is able to classify coffee odors at different mixtures. The results reveal that the concentrations and temperatures can affect the smell of quality of coffee. Based on this study, we are very optimistic that this e-nose will be very useful for coffee industry in Thailand. View full abstract»

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    Applies of Neural Networks to Identify Gases Based on Electronic Nose

    Hong Men ; Xiaoying Li ; Jianguo Wang ; Jing Gao
    Control and Automation, 2007. ICCA 2007. IEEE International Conference on

    Digital Object Identifier: 10.1109/ICCA.2007.4376852
    Publication Year: 2007 , Page(s): 2699 - 2704
    Cited by:  Papers (1)

    IEEE Conference Publications

    Intensive research and fast developments in electronic nose (EN) technologies provide the users with a wide spectrum of sensors and systems for their applications. Back-propagation neural network (BP), radial basis function neural network (RBF), and self-organization mapping networks (SOM) were applied to identify three gases by electronic nose gas sensors (CO, SO2, and NO2) qualitatively. Three training algorithms, gradient descent (traingd), gradient descent with momentum of variable learning rate (traingdx) and Levenberg-Marquardt (trainlm) algorithm, were applied for training. The results show the first two algorithms are too slow for practical problems. Training speed of trainlm is faster more. The RBF networks provide a simple and robust method. The sampling gases were clearly classified with few errors. The RBF networks train faster than the BP networks do, while exhibiting none of back-propagation's training pathologies such as paralysis of local minima problems. The SOM networks can classify accurately and generalization capability is far superior. While recognized patterns are non-rectangular shape and size, the performance is poor. View full abstract»

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    Exploratory study on aroma profile of cardamom by GC- MS and Electronic nose

    Ghosh, D. ; Mukherjee, S. ; Sarkar, S. ; Murthy, K. ; Leela, N.K. ; Bhattacharyya, N. ; Muneeb, A.M.
    Sensing Technology (ICST), 2012 Sixth International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2012.6461708
    Publication Year: 2012 , Page(s): 399 - 403

    IEEE Conference Publications

    Cardamom is known as “Queen of Spices”. It is one of the most highly priced spices in the world. The commercial part of the cardamom is the fruit (Capsule) of the plant that is used as a spice and a flavoring agent. The major quality measurement parameter of the cardamom is freshness, size, colour, aroma etc. Aroma is one of the main and crucial quality parameter for cardamom. The present practice of aroma quality estimation is done by GC, GC-MS, where different volatile oil and chemicals qualitative and quantitative tests are done. The present practice is laborious, time consuming and skilled manpower demanding process. In our present study an effort has been made to develop an Electronic Nose for rapid aroma determination of cardamom. Centres for Development of Advanced Computing, (C-DAC), Kolkata has indigenously developed the Electronic Nose (E-Nose) to estimate the quality of food and agro produces. Three-clone specific cardamom samples ware tested using this system as an exploratory study to determine the quality of cardamom and found the system is able to differentiate the samples. The principal component analysis shows distinct three clusters with principal component (PC1) 91.6% and PC2 6.8%. This paper demonstrates the quality estimation of cardamom by E-Nose. View full abstract»

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    Towards a Wearable Electronic Nose Chip

    Kea-Tiong Tang ; Goodman, R.M.
    Custom Integrated Circuits Conference, 2006. CICC '06. IEEE

    Digital Object Identifier: 10.1109/CICC.2006.320857
    Publication Year: 2006 , Page(s): 273 - 276
    Cited by:  Papers (3)

    IEEE Conference Publications

    An electronic nose chip which uses three carbon black polymer sensors as its input is fabricated and tested. Results of longitudinal testing, response to analyte mixtures, temperature dependence, and power dissipation are discussed in the paper. Future work towards a fully integrated wearable electronic nose chip is discussed at the end of the paper View full abstract»

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    Towards Versatile Electronic Nose Pattern Classifier for Black Tea Quality Evaluation: An Incremental Fuzzy Approach

    Tudu, B. ; Metla, A. ; Das, B. ; Bhattacharyya, N. ; Jana, A. ; Ghosh, D. ; Bandyopadhyay, R.
    Instrumentation and Measurement, IEEE Transactions on

    Volume: 58 , Issue: 9
    Digital Object Identifier: 10.1109/TIM.2009.2016874
    Publication Year: 2009 , Page(s): 3069 - 3078
    Cited by:  Papers (8)

    IEEE Journals & Magazines

    Commonly used classification algorithms are not capable of incremental learning. When a new pattern is presented to such a computational model, it can either classify the unknown pattern based on its legacy training or declare the pattern as an outlier if such a provision is built into the associated algorithm. In the case of the pattern being an outlier to the existing training model, it is desirable that the same could be seamlessly included in the training model with appropriate class labels so that a universal computational model may be evolved incrementally. To this end, classifiers having the incremental-learning ability can be of great benefit by automatically including the newly presented patterns in the training data set without affecting class integrity of the previously trained system. In the present treatise, an incremental-learning fuzzy model for classification of black tea using electronic nose measurement is proposed. For application in black tea grade discrimination, an attempt has been made to correlate the multisensor aroma pattern of electronic nose with sensory panel (tea tasters) evaluation. However, this problem is associated with 2-D complexities. On one hand, the aroma of tea depends on the agroclimatic condition of a particular location, the specific season of flush, and the clonal variation for the tea plant. On the other hand, the sensory evaluation is completely human dependent that often suffers from subjectivity and nonrepeatability. In our pursuit of developing a universal computational model capable of objectively assigning tea-taster-like scores to tea samples under test, it has been felt that an incremental approach could be extremely beneficial for electronic-nose-based tea quality estimation. To this end, the proposed incremental-learning fuzzy model promises to be a versatile pattern classification algorithm for black tea grade discrimination using electronic nose. The algorithm has been tested in some tea gardens of northeast I- - ndia, and encouraging results have been obtained. View full abstract»

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    Identification of typical wine aromas by means of an electronic nose

    Lozano, J. ; Santos, J.P. ; Aleixandre, M. ; Sayago, I. ; Gutierrez, J. ; Horrillo, M.C.
    Sensors Journal, IEEE

    Volume: 6 , Issue: 1
    Digital Object Identifier: 10.1109/JSEN.2005.854598
    Publication Year: 2006 , Page(s): 173 - 178
    Cited by:  Papers (25)

    IEEE Journals & Magazines

    In the field of electronic noses (e-noses), it is not very usual to find many applications to wine detection. Most of them are related to the discrimination of wines in order to prevent their illegal adulteration and detection of off-odors, but their objective is not the identification of wine aromas. In this paper, an application of an e-nose for the identification of typical aromatic compounds present in white and red wines is shown. The descriptors of these compounds are fruity, floral, herbaceous, vegetative, spicy, smoky, and microbiological, and they are responsible for the usual aromas in wines; concentrations differ from 2-8× the threshold concentration humans can smell. Some of the measured aromas are pear, apple, peach, coconut, rose, geranium, cut green grass, mint, vanilla, clove, almond, toast, wood, and butter. Principal component analysis and linear discriminant analysis show that datasets of these groups of compounds are clearly separated, and a comparison among several types of artificial neural networks has been also performed. The results confirm that the system has good performance in the classification of typical red and white wine aromas. View full abstract»

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    Signals recognition of electronic nose based on support vector machines

    Xiao-Dong Wang ; Hao-Ran Zhang ; Zhang Chang-jiang
    Machine Learning and Cybernetics, 2005. Proceedings of 2005 International Conference on

    Volume: 6
    Digital Object Identifier: 10.1109/ICMLC.2005.1527528
    Publication Year: 2005 , Page(s): 3394 - 3398 Vol. 6
    Cited by:  Papers (1)

    IEEE Conference Publications

    A new intelligent method for signals recognition of electronic nose, based on support vector machine (SVM) classification, is presented. The SVM operates on the principle of structure risk minimization; hence a better generalization ability is guaranteed. This paper discusses the basic principle of the SVM at first, and then uses it as a classifier to recognize the gas category. The method can classify complicated patterns and achieve higher recognition rate at reasonably small size of training sample set and can overcome disadvantages of the artificial neural networks. The experiments of the recognition of three different gases, ethanol, gasoline and acetone, have been presented and discussed. The results indicate that the SVM classifier exhibits good generalization performance and enables the average recognition rate to reach 88.33% for the testing samples. This means the method proposed is effective for signals recognition of electronic nose. View full abstract»

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    Health status monitoring by discrimination of exhaled breath with an electronic nose

    Seesaard, T. ; Kerdcharoen, T. ; Kladsomboon, S. ; Lorwongtragool, P. ; Kitiyakara, T.
    Biomedical Engineering International Conference (BMEiCON), 2012

    Digital Object Identifier: 10.1109/BMEiCon.2012.6465431
    Publication Year: 2012 , Page(s): 1 - 5

    IEEE Conference Publications

    In an aging society, people unprecedentedly spend more attention to routine assessment of their health status. Besides self-check and doctor's examination, there are also biomedical devices capable of monitoring and indicating the status of human health. In this paper, we proposed an electronic nose system that has been developed to have the ability to detect odor from human breath in order to indicate the health status of its owner. Metal-porphyrins (MPs)/SWNT-COOH and polymer/SWNT-COOH nanocomposites sensors were used as the array of chemical gas sensors inside the electronic nose system. These sensing materials are sensitive to odor molecules presented in the exhaled breath. The constructed device consumes low power and can be operated at room temperature. A preliminary experiment was conducted on the sample group consisting of cancer patients and healthy volunteers to distinguish their health status indicating diseases. It was found that the e-nose can detect exhaled breath odors and discriminate the pattern of breath odor of each person. This will be useful in discriminating one's breath odor and identifying his health status. This device could help reduce the risks of getting infected from any disease beforehand. View full abstract»

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    Electronic tongue and electronic nose data fusion in classification with neural networks and fuzzy logic based models

    Sundic, T. ; Marco, S. ; Samitier, J. ; Wide, P.
    Instrumentation and Measurement Technology Conference, 2000. IMTC 2000. Proceedings of the 17th IEEE

    Volume: 3
    Digital Object Identifier: 10.1109/IMTC.2000.848719
    Publication Year: 2000 , Page(s): 1474 - 1479 vol.3
    Cited by:  Papers (3)

    IEEE Conference Publications

    One of the most interesting application areas of electronic noses is the food industry. In some cases when the results are not satisfactory, fusing the data of an electronic nose and an electronic tongue can result in highly increased performance. In this paper we combine the information of both instruments, and test their performance in potato chips and potato creams classification problem. Results for five classification techniques are compared, all based either on fuzzy logic systems or artificial neural networks. The results obtained using just nose or tongue information are compared to those when both instruments were fused. We show that the overall performance of a classifier was substantially increased for all algorithms View full abstract»

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    The novel EOS835 electronic nose sniffs out the Italian espresso coffee quality

    Falasconi, M. ; Pardo, M. ; Sberveglieri, G. ; Ricco, I. ; Nardini, F. ; Delia Torre, M. ; Bresciani, A.
    Sensors, 2003. Proceedings of IEEE

    Volume: 1
    Digital Object Identifier: 10.1109/ICSENS.2003.1278889
    Publication Year: 2003 , Page(s): 26 - 29 Vol.1
    Cited by:  Papers (3)

    IEEE Conference Publications

    We present the novel electronic olfactory system EOS835 manufactured by Sacmi Imola s.c.a.r.l. based on the University of Brescia electronic nose prototype Pico2. The EOS835 is a reliable system equipped with very sensitive and stable thin-film metal oxide gas sensors. A new feature extraction algorithm (phase space integral) has been applied to improve the system classification performance. The electronic nose has been used to evaluate the quality of the Italian espresso coffee produced by Jolly Caffe S.p.A. in order to determine the best time for packaging. View full abstract»

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    Electronic noses: prospects for applications in Australian industry

    Levy, D.C. ; Barnett, D.A. ; Bell, G.A.
    Knowledge-Based Intelligent Electronic Systems, 1998. Proceedings KES '98. 1998 Second International Conference on

    Volume: 3
    Digital Object Identifier: 10.1109/KES.1998.725962
    Publication Year: 1998 , Page(s): 126 - 133 vol.3

    IEEE Conference Publications

    The term `electronic nose' is a generic name for an analytical instrument that profiles the headspace volatiles over or around a sample. The technology is based on an array of chemical sensors whose outputs are integrated by advanced signal processing to rapidly identify complex odour mixtures. The paper gives a brief overview of the current state of the art of electronic noses and then goes on to discuss work which may lead to the development and improvement of nose instruments and their application in industries such as food manufacturing View full abstract»

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    Detection of stress through sweat analysis with an electronic nose

    Garcia-Cortes, A. ; Marti, J. ; Sayago, I. ; Santos, J.P. ; Gutierrez, J. ; Horrillo, M.C.
    Electron Devices, 2009. CDE 2009. Spanish Conference on

    Digital Object Identifier: 10.1109/SCED.2009.4800501
    Publication Year: 2009 , Page(s): 338 - 341

    IEEE Conference Publications

    Cortisol and adrenaline are two hormones associated with stress. Therefore, their detection is important for applications in medicine and security. We propose to detect the presence of these chemical compounds in the body's sweat by electronic noses with resistive sensors as a non-invasive method. Low concentrations of cortisol (5 muM - 50 muM) and adrenaline (0.3 mM - 5.5 mM) have been measured. Furthermore, our electronic nose have been able to distinguish between sweat from physical stress and quiet situation by two pattern recognition techniques as principal component analysis (PCA) and probabilistic neuronal network (PNN), being the prediction rate of the network 85%. View full abstract»

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    An Improved Integrated Electronic Nose for Online Measurement of VOCs in Indoor Air

    Fang Xiangsheng ; Qi Guowei ; Guo Miao ; Pan Min ; Chen Yuquan
    Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005. 27th Annual International Conference of the

    Digital Object Identifier: 10.1109/IEMBS.2005.1617079
    Publication Year: 2005 , Page(s): 2894 - 2897
    Cited by:  Patents (1)

    IEEE Conference Publications

    An improved integrated electronic nose mimic human olfactory system was developed and applied to online measurement of volatile organic compounds (VOCs) in indoor air. An enrichment unit based on active adsorbent sampling and thermal desorption was employed to lower detection limits to matching environmental concentrations. Two kinds of optimized arrays of sensors were designed, and an FFT and RBF artificial neural network were employed for dynamic signal extraction and pattern recognition, respectively. Results showed good performance of our electronic nose in qualitative and semi-quantitative measurement View full abstract»

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    Data acquisition system development of an electronic nose for sulphate-reducing bacteria detection

    Tan, E.T. ; Halim, Z.A.
    Intelligent and Advanced Systems (ICIAS), 2012 4th International Conference on

    Volume: 2
    Digital Object Identifier: 10.1109/ICIAS.2012.6306079
    Publication Year: 2012 , Page(s): 567 - 571

    IEEE Conference Publications

    In the past few decades, electronic nose technologies have been increasingly implemented for environmental monitoring. This research aims to develop a portable instrument to measure and monitor the presence of sulphate-reducing bacteria (SRB) using the artificial olfactory system. The unchecked growth of SRB in anaerobic environments causes severe microbiological corrosion problems. Conventional methods or detection kits currently available in the market for SRB detection are very time-consuming to use and are thus inefficient for field use. The electronic nose system comprises an array of metal-oxide semiconductor sensors, a data processing unit, and an artificial neural network (ANN) pattern recognition unit. This paper presents the hardware and software design of a data acquisition system for the development of an electronic nose using field programmable gate array (FPGA) as the data processing unit. The data acquisition system is successfully designed and tested. Data collected from assessment experiments show that the oxidation-reduction reaction attributed to the presence of SRB leaves an obvious pattern on the outputs of the sensor within three hours. The characteristics observed and data collected from experiments are used to configure the recognition system for the implementation of automated identification in the future. View full abstract»

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    An electronic nose system for assessing horse mackerel freshness

    Guney, S. ; Atasoy, A.
    Innovations in Intelligent Systems and Applications (INISTA), 2012 International Symposium on

    Digital Object Identifier: 10.1109/INISTA.2012.6246940
    Publication Year: 2012 , Page(s): 1 - 5
    Cited by:  Papers (1)

    IEEE Conference Publications

    An electronic nose is developed and applied to freshness test of the horse mackerels. 8 metal oxide gas sensors are used in the electronic nose. The data obtained from the electronic nose are processed with baseline manipulation, normalization, feature extraction, feature subset selection and classification stages respectively. Only one feature is extracted from each sensor. So every odor has 8 features. The classification of freshness is implemented with k-nearest neighbor, artificial neural network and decision tree methods and the success rates of three methods are compared with each other. It is observed that decision tree method is the best of these tree methods for freshness classification of the horse mackerels. View full abstract»

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    Aroma characterization of orthodox black tea with electronic nose

    Bhattacharyya, N. ; Tudu, B. ; Bandyopadhyay, R. ; Bhuyan, M. ; Mudi, R.
    TENCON 2004. 2004 IEEE Region 10 Conference

    Volume: B
    Digital Object Identifier: 10.1109/TENCON.2004.1414623
    Publication Year: 2004 , Page(s): 427 - 430 Vol. 2
    Cited by:  Papers (2)

    IEEE Conference Publications

    Black tea quality is a very complex phenomenon. There are almost two hundred varieties of bio-chemical compounds, both volatile and nonvolatile present in tea and each of these compounds contribute to tea quality (B. Banerjee, 1996), The major quality attributes of tea are flavour, aroma, colour and strength. Acceptance by consumers and price realized depend on these attributes (S.Y. Dheodhar et al.,). Out of these, aroma is the most important of the attributes and in common parlance, aroma means smell of the tea. Characterization of aroma of tea has been a challenge for tea scientists for long. Efforts have been made towards this through chemical analysis and instrumental studies through gas chromatography (GC) and high profile liquid chromatography (HPLC) techniques. Research and studies have been reported with success for quality characterization of food and beverages using electronic nose (T.C. Pearce et al., 2003). This paper reports a study and results on applicability of electronic nose for aroma characterization of orthodox black tea. Six varieties of orthodox tea samples were tested using Alpha MOS 2000 Electronic Nose and data obtained from the experimental setup have been successfully classified using principal component analysis (PCA) and back-propagation multilayer perceptron model. View full abstract»

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    Insect herbivory information detection by Principal Component Analysis on Electronic Nose System

    Sheng Ye ; Jie Hu
    Neural Networks and Brain, 2005. ICNN&B '05. International Conference on

    Volume: 1
    Digital Object Identifier: 10.1109/ICNNB.2005.1614642
    Publication Year: 2005 , Page(s): 401 - 404

    IEEE Conference Publications

    In response to insect herbivory, plants synthesize and emit blends of volatile compounds from their damaged and undamaged tissues. A system comprised of computer and electronic nose could fast detect the blends of volatile of paddy rice. The method for fast detecting pest information of rice includes detecting the volatile odor, classifying volatile odor by insects, and using principal component analysis (PCA). The best opportunity for detecting pest information using electronic nose is found out, which is in a range from 15 to 36 hour after insect herbivory. The results of this experiment demonstrate electronic nose is efficient to obtain pest information of rice View full abstract»

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    ICA Algorithm Based on Intelligent Electronic Nose in the Mixed Gas of Feature Extraction

    Xiufeng Meng
    Wireless Communications Networking and Mobile Computing (WiCOM), 2010 6th International Conference on

    Digital Object Identifier: 10.1109/WICOM.2010.5600613
    Publication Year: 2010 , Page(s): 1 - 4

    IEEE Conference Publications

    Electronic nose sensors in the gas mixture concentration of environmental pollution monitoring and detection of industrial waste gas has an important role, but because of the recognition capacity of existing algorithms and anti-jamming ability is poor, affecting recognition accuracy.Independent Component Analysis is a highly efficient method of blind signal separation. It an independent source signal from the mixed-signal separation. This paper through the electronic nose sensors to detect gas mixture signal, through the ICA decomposition algorithm of mixed gases on the outside interference to eliminate the noise, so that gas composition identified to achieve good results. Thanks to MATLAB simulation on the identification of the original gas composition come out with high precision. View full abstract»

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    Monolithic electronic nose system fabricated by post CMOS micromachining

    Cho, S.M. ; Sang Choon Ko ; Seung-Chul Ha ; Yong Shin Kim ; Young Jun Kim ; Yoonseok Yang ; Hyeon-Bong Pyo ; Chang Auck Choi
    Sensors, 2005 IEEE

    Digital Object Identifier: 10.1109/ICSENS.2005.1597725
    Publication Year: 2005

    IEEE Conference Publications

    A monolithic electronic nose system, which has 12 independent channels, was fabricated by post CMOS micromachining process. Read-out integrated circuits were fabricated with the standard CMOS processes with design rule of 0.8 mum. And, the MEMS parts of the electronic nose were fabricated by hybrid etching, composed of bulk micromachining with TMAH (tetramethy lammonium hydroxide) and deep dry etching, on the backside of the wafer after the CMOS processes. Resistance matching circuit, instrumentation amplifier, multiplexer, and transducer circuits with bridge structure were included in the read-out circuitry. And, heat control circuits were also implanted in the monolithic circuit to maintain the temperature of the MEMS sensing parts as constant. Carbon black-polymer composites and Au nano-particles were used as sensor materials. The MEMS parts of the electronic nose were designed to have well-shaped structures. These structures are considered to be suitable for drop coating procedure View full abstract»

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    Breath Analysis of Lung Cancer Patients Using an Electronic Nose Detection System

    Tran, V.H. ; Hiang Ping Chan ; Thurston, M. ; Jackson, P. ; Lewis, C. ; Yates, D. ; Bell, G. ; Thomas, P.S.
    Sensors Journal, IEEE

    Volume: 10 , Issue: 9
    Digital Object Identifier: 10.1109/JSEN.2009.2038356
    Publication Year: 2010 , Page(s): 1514 - 1518
    Cited by:  Papers (6)

    IEEE Journals & Magazines

    Background. The measurement of gaseous compounds in exhaled breath, such as volatile organic compounds (VOCs), may provide a noninvasive technique for assessing lung pathology, some of which are associated with lung cancer (LC). VOC analysis is laborious while electronic noses are emerging as rapid detectors of an array of gaseous markers recognizing a characteristic “smellprint.” Objectives. To conduct a pilot breath analysis using an electronic nose to test the hypothesis that there would be significant differences in the smellprint patterns between newly diagnosed LC patients and control subjects. Methods. Eighty-nine subjects were recruited, consisting of nonsmokers (33), ex-smokers (11), smokers (18), patients with respiratory disorders (11), and LC patients (16). Subjects exhaled into gas-impermeable bags for offline eNose measurements with a six-channel electronic detection module ENS Mk 3 (E-Nose Pty, Sydney). The time-response curve from each channel was evaluated for four parameters: rate to peak height, peak height, rate to recovery, and area under the curve. Results. The results showed significant differences between lung cancer and control groups when measuring peak height in channel 1 (p = 0.025); rate to recovery in channel 3 (p = 0.045); and rate to peak height in channel 3 (p = 0.001). Conclusion. The results show promise in that there were significant differences in the smellprint of subjects with lung cancer compared with control subjects. Further standardization of the technique will assist in improving the sensitivity and specificity of the method, with potential to use the analysis in a number of diseases where characteristic signatures occur in the breath. View full abstract»

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    Artificial electronic tongue in comparison to the electronic nose. State of the art and trends

    Hauptmann, P. ; Borngraeber, R. ; Schroeder, J. ; Auge, J.
    Frequency Control Symposium and Exhibition, 2000. Proceedings of the 2000 IEEE/EIA International

    Digital Object Identifier: 10.1109/FREQ.2000.887324
    Publication Year: 2000 , Page(s): 22 - 29
    Cited by:  Papers (3)  |  Patents (1)

    IEEE Conference Publications

    Many researchers aim for the development of sensors or sensor systems which are similar or comparable to the human sensory system. Of all the human sensory systems, olfaction is the least understood in terms of the primary receptor mechanism and biological transduction. It is difficult to describe a set of reference odours that describe the olfactory input. A high degree of signal processing takes place in the olfactory system so that compounds of similar chemical structure can give completely different olfactory responses. That is the reason why the understanding of the olfactory system is relatively poor. The situation is comparable in the case of gustation. Nevertheless, there are many practical applications that require a quantitative or qualitative objective recording of odours or taste. In the following the development in the field of electronic tongue is described. It is a relatively new field. The state-of-the-art in understanding of electronic noses and tongues is discussed. They are illustrated describing their working principles, the types of sensors, circuit architectures and features. The applied sensor types are considered more in detail. Future perspectives of electronic tongue systems and their applications are illustrated. Problems which had to be solved yet are discussed View full abstract»

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    Application of PCA Method on Pest Information Detection of Electronic Nose

    Jie Hu
    Information Acquisition, 2006 IEEE International Conference on

    Digital Object Identifier: 10.1109/ICIA.2006.305973
    Publication Year: 2006 , Page(s): 1465 - 1468
    Cited by:  Papers (1)

    IEEE Conference Publications

    In this paper, we apply electronic nose to detect crop pest information for the first time, based on the obtained sensor array data. Feature parameters from each sensor curve such as maximum, max differential value, mean value and stable value etc. are extracted and then used as the input of pattern recognition, then principal component analysis (PCA) is adopted to analyze the test sample. Experiments investigate the PCA method on electronic nose is able to detect whether rice is attacked by insect pests, to know the inroad extent of damaged rice and the amount of pests on each stem of paddy rice. View full abstract»

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    Electronic nose for the early detection of different types of indigenous mold contamination in green coffee

    Sberveglieri, V. ; Comini, E. ; Zappa, D. ; Pulvirenti, A. ; Nunez Carmona, E.
    Sensing Technology (ICST), 2013 Seventh International Conference on

    Digital Object Identifier: 10.1109/ICSensT.2013.6727696
    Publication Year: 2013 , Page(s): 461 - 465

    IEEE Conference Publications

    In the last few years Electronic Noses (ENs) have been revealed to be a very effective and fast tool for monitoring the microbiological spoilage and food quality control. European regulations report the maximum concentration of mycotoxins permitted in green coffee beans. The aim of this study was to test the ability of a novel EN, equipped with an array of MOX gas sensors based on thin films as well as nanowires, to early detect mold contaminations from Aspergillus spp., in cooperation with classical microbiological and chemical techniques like Gas Chromatography coupled with Mass Spectroscopy with SPME technique. In general the selection of the green coffee is controlled by visual inspection of shape, color and size. However, this process in often not enough to prevent the entrance in the food chains of contaminated products. We have demonstrated that the novel EN is able to early detect the qualitative and quantitative differences between contaminate and uncontaminated samples. Achieved results vividly recommend the use of our EN as a quality control tool in coffee producer industry. View full abstract»