In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection

Celaya-Padilla, Jose M.; Romero-González, Jonathan S.; Galvan-Tejada, Carlos E.; Galvan-Tejada, Jorge I.; Luna-García, Huizilopoztli; Arceo-Olague, Jose G.; Gamboa-Rosales, Nadia K.; Sifuentes-Gallardo, Claudia; Martinez-Torteya, Antonio; De la Rosa, José I.; Gamboa-Rosales, Hamurabi

doi:10.3390/s21227752

Submit to this Journal Review for this Journal Edit a Special Issue

Article Menu

...

Open AccessArticle

In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection

Jose M. Celaya-Padilla

^1,2,†

Jonathan S. Romero-González

^1,†,

Carlos E. Galvan-Tejada

Jorge I. Galvan-Tejada

¹,

Huizilopoztli Luna-García

Jose G. Arceo-Olague

Nadia K. Gamboa-Rosales

^1,2,

Claudia Sifuentes-Gallardo

¹,

Antonio Martinez-Torteya

José I. De la Rosa

and

Hamurabi Gamboa-Rosales

^1,*

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juárez 147, Centro, Zacatecas 98000, Mexico

Cátedras-CONACyT, Consejo Nacional de Ciencia y Tecnología, Ciudad de México 03940, Mexico

Escuela de Ingeniería y Tecnologías, Universidad de Monterrey, San Pedro Garza García 66238, Mexico

Author to whom correspondence should be addressed.

^†

These authors contributed equally to this work.

Academic Editors: Alexey Kashevnik, Andrei Gurtov, Sara Ferreira and Felipe Jiménez

Sensors 2021, 21(22), 7752; https://doi.org/10.3390/s21227752

Received: 27 September 2021 / Revised: 9 November 2021 / Accepted: 16 November 2021 / Published: 21 November 2021

(This article belongs to the Special Issue Smartphone Sensors for Driver Behavior Monitoring Systems)

View Full-Text Download PDF

Browse Figures

Citation Export

Abstract

Worldwide, motor vehicle accidents are one of the leading causes of death, with alcohol-related accidents playing a significant role, particularly in child death. Aiming to aid in the prevention of this type of accidents, a novel non-invasive method capable of detecting the presence of alcohol inside a motor vehicle is presented. The proposed methodology uses a series of low-cost alcohol MQ3 sensors located inside the vehicle, whose signals are stored, standardized, time-adjusted, and transformed into 5 s window samples. Statistical features are extracted from each sample and a feature selection strategy is carried out using a genetic algorithm, and a forward selection and backwards elimination methodology. The four features derived from this process were used to construct an SVM classification model that detects presence of alcohol. The experiments yielded 7200 samples, 80% of which were used to train the model. The rest were used to evaluate the performance of the model, which obtained an area under the ROC curve of 0.98 and a sensitivity of 0.979. These results suggest that the proposed methodology can be used to detect the presence of alcohol and enforce prevention actions. View Full-Text

Keywords: drinking and driving; smart vehicle; smart infotainment; alcohol detection; genetic algorithm

▼ Show Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Share and Cite

MDPI and ACS Style

Celaya-Padilla, J.M.; Romero-González, J.S.; Galvan-Tejada, C.E.; Galvan-Tejada, J.I.; Luna-García, H.; Arceo-Olague, J.G.; Gamboa-Rosales, N.K.; Sifuentes-Gallardo, C.; Martinez-Torteya, A.; De la Rosa, J.I.; Gamboa-Rosales, H. In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection. Sensors 2021, 21, 7752. https://doi.org/10.3390/s21227752

AMA Style

Celaya-Padilla JM, Romero-González JS, Galvan-Tejada CE, Galvan-Tejada JI, Luna-García H, Arceo-Olague JG, Gamboa-Rosales NK, Sifuentes-Gallardo C, Martinez-Torteya A, De la Rosa JI, Gamboa-Rosales H. In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection. Sensors. 2021; 21(22):7752. https://doi.org/10.3390/s21227752

Chicago/Turabian Style

Celaya-Padilla, Jose M., Jonathan S. Romero-González, Carlos E. Galvan-Tejada, Jorge I. Galvan-Tejada, Huizilopoztli Luna-García, Jose G. Arceo-Olague, Nadia K. Gamboa-Rosales, Claudia Sifuentes-Gallardo, Antonio Martinez-Torteya, José I. De la Rosa, and Hamurabi Gamboa-Rosales. 2021. "In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection" Sensors 21, no. 22: 7752. https://doi.org/10.3390/s21227752

Find Other Styles

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Abstract views Pdf views Html views

Article Menu

In-Vehicle Alcohol Detection Using Low-Cost Sensors and Genetic Algorithms to Aid in the Drinking and Driving Detection

Abstract

Share and Cite

Article Metrics

Article Access Statistics

Article Access Map by Country/Region

Further Information

Guidelines

MDPI Initiatives

Follow MDPI