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e-Article

A Review on Electronic Nose: Coherent Taxonomy, Classification, Motivations, Challenges, Recommendations and Datasets
Document Type
Periodical
Source
IEEE Access Access, IEEE. 9:88535-88551 2021
Subject
Aerospace
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
Fields, Waves and Electromagnetics
General Topics for Engineers
Geoscience
Nuclear Engineering
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Pattern recognition
Electronic noses
Olfactory
Taxonomy
Food industry
Sensor arrays
Quality assessment
Artificial olfaction
electronic nose
feature classification
food quality
machine learning
pattern recognition
Language
ISSN
2169-3536
Abstract
Context: Quality Control (QC) has been constantly an essential concern in many fields like food industry production, medical drugs, environmental protection, and so on. An odor or flavor, as a global fingerprint, can be implemented as a non-invasive mechanism for quality assurance. This computer-based approach can assure accurate detection and precise identification of the product quality or manufactured goods. Objective: This paper aims to achieve a systematic review about e-nose by introducing the achievements made by researchers in this area, to summarize their findings, to provide motivations and challenges to new researchers in the field of e-nose. Methods: The articles that were being utilized in the e-nose field were systematically achieved using three search engines: The online library of IEEE Explore, Web of Science and Science Direct for time span of 7 years (from 2013 to 2020). Both medical literature reviews and technical reviews were considered in the criteria of the research for wider understanding in the field of e-nose. The articles were categorized according to the objective of the research and projected into four classes. Upon completion of screening process 333 research papers using the exclusion and inclusion conditions, as the final set 54 articles were selected. Results: The taxonomy of this research was classified into four categories. The first one included the suggested methods that introduced the utilization of the e-nose for classification purposes (9/54 papers). The second category comprises the methods related to the development of e-nose (24/54 papers). The third one included the review studies about the e-nose (8/54 papers). The fourth group comprises comparative studies and evaluation (13/54 papers). Discussion: This systematic review contributes for a clearer understanding and a full insight in the e- nose research field by surveying and categorizing pertinent research efforts. Conclusion: This review paper will help to address the up-to-date research opportunities, challenges, problems, motivations and recommendations related to the utilization of e-nose in all fields of sciences and industries.