Electronic Nose Technology and Application: A Review

Illahi, Ana Antoniette C.; Dadios, Elmer P.; Vicerra, Ryan Rhay P.

doi:10.1109/hnicem54116.2021.9731890

Cited by 8 publications

(5 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The main challenge in these advancements lays in the manufacturing of the appropriate electronic parts (acquisition and transmission module), the signal processing and the software to process the gathered data. The detection, classification, and prediction can be improved by using artificial intelligence in an EN [ 82 ].…”

Section: Fast/screening Methods For On-site/mobile Analysis Of Vocsmentioning

confidence: 99%

On-Site Detection of Volatile Organic Compounds (VOCs)

Epping

Koch

2023

Molecules

View full text Add to dashboard Cite

Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.

show abstract

Section: Fast/screening Methods For On-site/mobile Analysis Of Vocsmentioning

confidence: 99%

On-Site Detection of Volatile Organic Compounds (VOCs)

Epping

Koch

2023

Molecules

View full text Add to dashboard Cite

show abstract

“…Various types of gas sensors are typically used in e-nose systems, differing in working principle, sensitivity, selectivity, response time, energy consumption, reversibility, and fabrication cost [36,37] In this section, we provide a short description of the most common sensor technologies used in e-nose systems grouped by working principle:…”

Section: Sensor Technologies Used In E-nose Systemsmentioning

confidence: 99%

“…• Optical sensors: These belong to a family of sensors where the changes in optical properties (color, transmission, etc.) of a sensing element are used to detect volatile compounds or their patterns [37,44].…”

mentioning

confidence: 99%

Physical Confounding Factors Affecting Gas Sensors Response: A Review on Effects and Compensation Strategies for Electronic Nose Applications

Robbiani,

Lotesoriere,

Dellacà

et al. 2023

Chemosensors

View full text Add to dashboard Cite

Electronic noses (e-noses) are devices based on combining different gas sensors’ responses to a given sample for identifying specific odor fingerprints. In recent years, this technology has been considered a promising novel tool in several fields of application, but several issues still hamper its widespread use. This review paper describes how some physical confounding factors, such as temperature, humidity, and gas flow, in terms of flow direction and flow rate, can drastically influence gas sensors’ responses and, consequently, e-nose results. Among the software and hardware approaches adopted to address such issues, different hardware compensation strategies proposed in the literature were critically analyzed. Solutions related to e-nose sensors’ modification, design and readout, sampling system and/or chamber geometry design were investigated. A trade-off between the loss of volatile compounds of interest, the decrease of sensors’ sensitivity, and the lack of fast responses need to be pointed out. The existing body of knowledge suggests that the e-nose design needs to be highly tailored to the target application to exploit the technology potentialities fully and highlights the need for further studies comparing the several solutions proposed as a starting point for the application-driven design of e-nose-based systems.

show abstract

“…Current advances in artificial intelligence and internet-of-things facilitate identifying new input layers as data generators to feed machine learning (ML) for information classification. Before this, electronic noses (eNoses) have nourished the fantasy for more than 60 years of emulating a biological sense to perform classification tasks that sensors can barely make with molecular patterns [1][2][3][4][5]. It is therefore very appropriate to wonder whether conventional approaches to selecting sensing hardware are adapted to information processing requirements, with pattern recognition having more standards nowadays.…”

Section: Introductionmentioning

confidence: 99%

Steady vs. Dynamic Contributions of Different Doped Conducting Polymers in the Principal Components of an Electronic Nose’s Response

Haj Ammar,

Boujnah,

Boubaker

et al. 2023

Eng

View full text Add to dashboard Cite

Multivariate data analysis and machine learning classification have become popular tools to extract features without physical models for complex environments recognition. For electronic noses, time sampling over multiple sensing elements must be a fair compromise between a period sufficiently long to output a meaningful information pattern and sufficiently short to minimize training time for practical applications. Particularly when a reactivity’s kinetics differ from the thermodynamics in sensitive materials, finding the best compromise to get the most from the data is not obvious. Here, we investigate the influence of data acquisition to improve or alter data clustering for molecular recognition on a conducting polymer electronic nose. We found out that waiting for sensing elements to reach their steady state is not required for classification, and that reducing data acquisition down to the first dynamical information suffices to recognize molecular gases by principal component analysis with the same materials. Especially for online inference, this study shows that a good sensing array is not an array of good sensors, and that new figures of merit should be defined for sensing hardware using machine learning pattern recognition rather than metrology.

show abstract

Electronic Nose Technology and Application: A Review

Cited by 8 publications

References 10 publications

On-Site Detection of Volatile Organic Compounds (VOCs)

On-Site Detection of Volatile Organic Compounds (VOCs)

Physical Confounding Factors Affecting Gas Sensors Response: A Review on Effects and Compensation Strategies for Electronic Nose Applications

Steady vs. Dynamic Contributions of Different Doped Conducting Polymers in the Principal Components of an Electronic Nose’s Response

Contact Info

Product

Resources

About