Electronic nose – an instrument for odour nuisances monitoring

Szulczyński, Bartosz; Gębicki, Jacek

doi:10.1051/e3sconf/201910000079

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…Table 2 presents the selected cases. The majority of studies described so far pertained to the application of e-noses for product quality control (e.g., food or pharmaceutical) [134,135], detection of various ailments [136], or the assessment of odor nuisance [137]. They are also useful for the continuous measurements of the degree of pollution of environmental samples (water and air) as well as for evaluating the effectiveness of sewage and waste gas treatment [98].…”

Section: Gas Sensor Arraymentioning

confidence: 99%

Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies

et al. 2020

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In this review, the problem of microbiological infestation of buildings was discussed. The techniques of detection were described as well, with special attention drawn to the rapid-early detection methods based on gas sensor arrays. The physical and chemical conditions of the building environment conducive to the development of microorganisms and the technical conditions influencing the problem of microbiological infestation were investigated. Additionally, the harmful effects on human health caused by the microbiological contamination were discussed, with a short review of particular groups of microorganisms causing sick building syndrome. Among the detection techniques, the traditional microbiological techniques as well as the molecular and chemical methods were presented. Different designs of the gas sensor arrays together with the various techniques of analyzing the received multidimensional signal were described, analyzed, and compared in detail.

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Section: Gas Sensor Arraymentioning

confidence: 99%

Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies

et al. 2020

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“…The working of the electronic nose is based on a calibration model. To develop such models, signals from electronic nose sensors and odour intensities expressed in verbal scale are used (Szulczyński & Gębicki 2019). The electronic nose can be used for "in-situ" tests.…”

Section: Introductionmentioning

confidence: 99%

Archives of Environmental Protection

Wiśniewska,

Kulig,

Lelicińska-Serafin

2020

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Biogas plants processing municipal waste are very important investments from the point of view of waste management and also the sustainable development of urban infrastructures. They may also have a potentially negative impact on the environment in the form of odour emission. Olfactometry is the main method for odour impact assessment. Field olfactometry allows for performing a wide range of tests, the results of which are practically instantaneous. The purpose of this work is to provide a tool for assessing the odour impacts of municipal management facilities, including biogas plants processing municipal waste and evaluating the correctness of processes carried out in these plants, namely the method of fi eld olfactometry. In order to compare obtained olfactometric results with the concentration of chemical compounds, chromatographic tests were also carried out using the Photovac Voyager portable chromatograph (hydrogen sulphide -H 2 S and dimethyl sulphide -(CH 3 ) 2 S. The results of the odour concentration tests are in line with the results of odorant concentration tests and indicate that c od is strongly related to the concentration of hydrogen sulphide. Thanks to this method, it is possible to fi nd a relationship between odour nuisance, technological processes used in the plant and the type of treated waste.

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“…They turn the chemical information into an analytically useful signal. Then, the signal is sent to the recognition system, which in the case of the human body, is the brain, and in the case of the e-nose, is the appropriate mathematical algorithm [26]. The most commonly used data processing methods are: Principal component analysis (PCA), principal component regression (PCR), partial least square regression (PLSR), fuzzy logic (FL), and artificial neural networks (ANN) [27,28,29,30,31,32,33,34,35].…”

Section: Introductionmentioning

confidence: 99%

Determination of Odor Intensity of Binary Gas Mixtures Using Perceptual Models and an Electronic Nose Combined with Fuzzy Logic

Szulczyński

Gębicki

2019

Sensors

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Measurement and monitoring of air quality in terms of odor nuisance is an important problem. From a practical point of view, it would be most valuable to directly link the odor intensity with the results of analytical air monitoring. Such a solution is offered by electronic noses, which thanks to the possibility of holistic analysis of the gas sample, allow estimation of the odor intensity of the gas mixture. The biggest problem is the occurrence of odor interactions between the mixture components. For this reason, methods that can take into account the interaction between components of the mixture are used to analyze data from the e-nose. In the presented study, the fuzzy logic algorithm was proposed for determination of odor intensity of binary mixtures of eight odorants: n-Hexane, cyclohexane, toluene, o-xylene, trimethylamine, triethylamine, α-pinene, and β-pinene. The proposed algorithm was compared with four theoretical perceptual models: Euclidean additivity, vectorial additivity, U model, and UPL model.

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Electronic nose – an instrument for odour nuisances monitoring

Cited by 5 publications

References 22 publications

Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies

Methods for Early Detection of Microbiological Infestation of Buildings Based on Gas Sensor Technologies

Archives of Environmental Protection

Determination of Odor Intensity of Binary Gas Mixtures Using Perceptual Models and an Electronic Nose Combined with Fuzzy Logic

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