DocumentCode :
190130
Title :
Odor assessment of automobile cabin air by machine olfaction
Author :
Li, J. ; Hodges, R.D. ; Schiffman, S.S. ; Nagle, H.T. ; Gutierrez-Osuna, R. ; Luckey, G. ; Crowell, J.
Author_Institution :
Dept. of Electr. & Comput. Eng., North Carolina State Univ., Raleigh, NC, USA
fYear :
2014
fDate :
2-5 Nov. 2014
Firstpage :
1726
Lastpage :
1729
Abstract :
Odor quality in the cabin air of automobiles can be a significant factor in the decision to purchase a vehicle and the overall customer satisfaction with the vehicle over time. Current standard practice uses a human panel to rate the vehicle cabin odors on intensity, irritation, and pleasantness. However, human panels are expensive, time-consuming and complicated to administer. To address this issue, we have developed a machine olfaction approach to assess odors inside automobiles for the purpose of enhancing or replacing the human panel by evaluating the correlation between the system performance and a trained human panel. Our approach employs an ion-mobility spectrometer and a photoionization detector for measuring volatile organic compounds inside automobiles. Our olfactory system achieves good correlations (range from 0.72 to 0.84) with a trained human panel using predictive models generated by linear regression and cross-validation. Our results support the feasibility of replacing human panel assessments by a machine olfaction system.
Keywords :
chemical sensors; electronic noses; ion mobility spectrometers; organic compounds; photodetectors; automobile cabin air; ion-mobility spectrometer; linear regression; machine olfaction; odor assessment; photoionization detector; volatile organic compounds; Automobiles; Chemicals; Correlation; Predictive models; Principal component analysis; Sensors; air quality; ion mobility spectrometry; linear regression; machine olfaction; odor assessment; photoionization; principal components analysis; volatile organic compounds;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
SENSORS, 2014 IEEE
Conference_Location :
Valencia
Type :
conf
DOI :
10.1109/ICSENS.2014.6985356
Filename :
6985356
Link To Document :
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