Model Development for Alcohol Concentration in Exhaled Air at Low Temperature Using Electronic Nose

Autor: Lidong Tan, Jiexi Wang, Guiyou Liang, Zongwei Yao, Xiaohui Weng, Fangrong Wang, Zhiyong Chang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Chemosensors, Vol 10, Iss 9, p 375 (2022)
Druh dokumentu: article
ISSN: 2227-9040
DOI: 10.3390/chemosensors10090375
Popis: 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.
Databáze: Directory of Open Access Journals