TY - JOUR
T1 - Review on Algorithm Design in Electronic Noses
T2 - Challenges, Status, and Trends
AU - Liu, Taoping
AU - Guo, Lihua
AU - Wang, Mou
AU - Su, Chen
AU - Wang, Di
AU - Dong, Hao
AU - Chen, Jingdong
AU - Wu, Weiwei
N1 - Publisher Copyright:
© 2023 Taoping Liu et al.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85149725251&partnerID=8YFLogxK
U2 - 10.34133/icomputing.0012
DO - 10.34133/icomputing.0012
M3 - 文献综述
AN - SCOPUS:85149725251
SN - 2771-5892
VL - 2
JO - Intelligent Computing
JF - Intelligent Computing
M1 - 0012
ER -