Review on Algorithm Design in Electronic Noses: Challenges, Status, and Trends

Taoping Liu, Lihua Guo, Mou Wang, Chen Su, Di Wang, Hao Dong, Jingdong Chen, Weiwei Wu

科研成果: 期刊稿件文献综述同行评审

53 引用 (Scopus)

摘要

Electronic noses, or e-noses, refer to systems powered by chemical gas sensors, signal processing, and machine learning algorithms for realizing artificial olfaction. They play a crucial role in various applications for decoding chemical environmental information. Despite decades of advances in gas-sensing technology and artificial intelligence, the reliability and stability of e-nose systems remain challenging, which is also one of the major obstacles that prevent e-noses from large-scale deployment. This paper presents a wide-ranging and structured review of the methods and algorithms developed in the e-nose literature over the past few decades. The review adopts a problem-oriented taxonomy aimed at clarifying the motivations and challenges of different methods and algorithms and their pros and cons. Moreover, several promising research directions in this field have been presented.

源语言英语
文章编号0012
期刊Intelligent Computing
2
DOI
出版状态已出版 - 2023

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