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Volume 13
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10.3390/app13105882
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Article

Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network

by
Jaime Mercado Reyna
1,
Huizilopoztli Luna-Garcia
1,*,
Carlos H. Espino-Salinas
1,
José M. Celaya-Padilla
1,*,
Hamurabi Gamboa-Rosales
1,
Jorge I. Galván-Tejada
1,
Carlos E. Galván-Tejada
1,
Roberto Solís Robles
1,
David Rondon
2 and
Klinge Orlando Villalba-Condori
3
1
Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Jardín Juarez 147, Centro, Zacatecas 98000, Mexico
2
Departamento Estudios Generales, Universidad Continental, Arequipa 04001, Peru
3
Vicerrectorado de Investigación, Universidad Católica de Santa María, Arequipa 04002, Peru
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2023, 13(10), 5882; https://doi.org/10.3390/app13105882
Submission received: 18 April 2023 / Revised: 3 May 2023 / Accepted: 9 May 2023 / Published: 10 May 2023
(This article belongs to the Section Transportation and Future Mobility)
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Abstract

The lack of helmet use in motorcyclists is one of the main risk factors with severe consequences in traffic accidents. Wearing a certified motorcycle helmet can reduce the risk of head injuries by 69% and fatalities by 42%. At present there are systems that detect the use of the helmet in a very precise way, however they are not robust enough to guarantee a safe journey, that is why is proposed an intelligent model for detecting the helmet in real time using training images of a camera mounted on the motorcycle, and convolutional neural networks that allow constant monitoring of the region of interest to identify the use of the helmet. As a result, a model was obtained capable of identifying when the helmet is used or not in an objective and constant manner while the user is making a journey, with a performance of 97.24%. Thus, it was possible to conclude that this new safety perspective provides a first approach to the generation of new preventive systems that help reduce accident rates in these means of transport. As future work, it is proposed to improve the model with different images that may violate the helmet detection.
Keywords: helmet detection; deep learning; InceptionV3; convolutional neural network; motorcyclist safety helmet detection; deep learning; InceptionV3; convolutional neural network; motorcyclist safety

Share and Cite

MDPI and ACS Style

Mercado Reyna, J.; Luna-Garcia, H.; Espino-Salinas, C.H.; Celaya-Padilla, J.M.; Gamboa-Rosales, H.; Galván-Tejada, J.I.; Galván-Tejada, C.E.; Solís Robles, R.; Rondon, D.; Villalba-Condori, K.O. Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network. Appl. Sci. 2023, 13, 5882. https://doi.org/10.3390/app13105882

AMA Style

Mercado Reyna J, Luna-Garcia H, Espino-Salinas CH, Celaya-Padilla JM, Gamboa-Rosales H, Galván-Tejada JI, Galván-Tejada CE, Solís Robles R, Rondon D, Villalba-Condori KO. Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network. Applied Sciences. 2023; 13(10):5882. https://doi.org/10.3390/app13105882

Chicago/Turabian Style

Mercado Reyna, Jaime, Huizilopoztli Luna-Garcia, Carlos H. Espino-Salinas, José M. Celaya-Padilla, Hamurabi Gamboa-Rosales, Jorge I. Galván-Tejada, Carlos E. Galván-Tejada, Roberto Solís Robles, David Rondon, and Klinge Orlando Villalba-Condori. 2023. "Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network" Applied Sciences 13, no. 10: 5882. https://doi.org/10.3390/app13105882

APA Style

Mercado Reyna, J., Luna-Garcia, H., Espino-Salinas, C. H., Celaya-Padilla, J. M., Gamboa-Rosales, H., Galván-Tejada, J. I., Galván-Tejada, C. E., Solís Robles, R., Rondon, D., & Villalba-Condori, K. O. (2023). Detection of Helmet Use in Motorcycle Drivers Using Convolutional Neural Network. Applied Sciences, 13(10), 5882. https://doi.org/10.3390/app13105882

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