Abstract
Driving safety issues, such as drunk driving, have drawn a lot of attention since the advent of shared automobiles. We used an electronic nose (EN) detection device as an onboard system for shared automobiles to identify drunk driving. The sensors in the EN, however, can stray in cold winter temperatures. We suggested an independent component analysis (ICA) correction model to handle the data collected from the EN in order to lessen the impact of low temperature on the device. Additionally, it was contrasted with both the mixed temperature correction model and the single temperature model. As samples, alcohol mixed with concentrations of 0.1 mg/L and 0.5 mg/L were tested at (20 ± 2) °C, (−10 ± 2) °C, and (−20 ± 2) °C. The results showed that the ICA correction model outperformed the other models with an accuracy of 1, precision of 1, recall of 1, and specificity of 1. As a result, this model can be utilized to lessen the impact of low temperature on the EN’s ability to detect the presence of alcohol in the driver’s inhaled gas, strongly supporting its use in car-sharing drink driving. Other ENs that need to function in frigid conditions can also use this technique.
Funder
the National Natural Science Foundation of China
Subject
Physical and Theoretical Chemistry,Analytical Chemistry
Cited by
1 articles.
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1. Programmable Olfactory Computing;Proceedings of the 50th Annual International Symposium on Computer Architecture;2023-06-17