Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing

Bruno Eraldo; Grimaldo Quispe; Heyul Chavez-Arias; Carlos Raymundo-Ibanez; Francisco Dominguez

doi:10.1109/CONCAPANXXXIX47272.2019.8976928

Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing

Bruno Eraldo
, Grimaldo Quispe
, Heyul Chavez-Arias
, Carlos Raymundo-Ibanez
, Francisco Dominguez

Universidad Continental
Universidad Nacional Autónoma Altoandina de Tarma
Universidad Rey Juan Carlos

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

2 Scopus citations

Abstract

It is known that 33% of traffic accidents worldwide are caused by drunk driving or drowsiness [1] [2], so a drowsiness level detection system that integrates image processing was developed with the use of Raspberry Pi3 with the OpenCV library; and sensors such as MQ-3 that measures the percentage of alcohol and the S9 sensor that measures the heart rate. In addition, it has an alert system and as an interface for the visualization of the data measured by the sensors a touch screen. With the image processing technique, facial expressions are analyzed, while physiological behaviors such as heart rate and alcohol percentage are measured with the sensors. In image test training you get an accuracy of x in a response time of x seconds. On the other hand, the evaluation of the operation of the sensors in 90% effective. So the method developed is effective and feasible.

Original language	English
Title of host publication	2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728108834
DOIs	https://doi.org/10.1109/CONCAPANXXXIX47272.2019.8976928
State	Published - Nov 2019
Event	39th IEEE Central America and Panama Convention, CONCAPAN 2019 - Guatemala City, Guatemala Duration: 20 Nov 2019 → 22 Nov 2019

Publication series

Name	2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019
Volume	2019-November

Conference

Conference	39th IEEE Central America and Panama Convention, CONCAPAN 2019
Country/Territory	Guatemala
City	Guatemala City
Period	20/11/19 → 22/11/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 7 Affordable and Clean Energy

Keywords

Image processing
Raspberry Pi 3
drowsiness
interface
sensor

Access to Document

10.1109/CONCAPANXXXIX47272.2019.8976928

Cite this

Eraldo, B., Quispe, G., Chavez-Arias, H., Raymundo-Ibanez, C., & Dominguez, F. (2019). Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing. In 2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019 Article 8976928 (2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019; Vol. 2019-November). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CONCAPANXXXIX47272.2019.8976928

Eraldo, Bruno ; Quispe, Grimaldo ; Chavez-Arias, Heyul et al. / Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing. 2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019).

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title = "Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing",

abstract = "It is known that 33\% of traffic accidents worldwide are caused by drunk driving or drowsiness [1] [2], so a drowsiness level detection system that integrates image processing was developed with the use of Raspberry Pi3 with the OpenCV library; and sensors such as MQ-3 that measures the percentage of alcohol and the S9 sensor that measures the heart rate. In addition, it has an alert system and as an interface for the visualization of the data measured by the sensors a touch screen. With the image processing technique, facial expressions are analyzed, while physiological behaviors such as heart rate and alcohol percentage are measured with the sensors. In image test training you get an accuracy of x in a response time of x seconds. On the other hand, the evaluation of the operation of the sensors in 90\% effective. So the method developed is effective and feasible.",

keywords = "Image processing, Raspberry Pi 3, drowsiness, interface, sensor",

author = "Bruno Eraldo and Grimaldo Quispe and Heyul Chavez-Arias and Carlos Raymundo-Ibanez and Francisco Dominguez",

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year = "2019",

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doi = "10.1109/CONCAPANXXXIX47272.2019.8976928",

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Eraldo, B, Quispe, G, Chavez-Arias, H , Raymundo-Ibanez, C & Dominguez, F 2019, Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing. in 2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019., 8976928, 2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019, vol. 2019-November, Institute of Electrical and Electronics Engineers Inc., 39th IEEE Central America and Panama Convention, CONCAPAN 2019, Guatemala City, Guatemala, 20/11/19. https://doi.org/10.1109/CONCAPANXXXIX47272.2019.8976928

Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing. / Eraldo, Bruno; Quispe, Grimaldo; Chavez-Arias, Heyul et al.
2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8976928 (2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019; Vol. 2019-November).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Dominguez, Francisco

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AB - It is known that 33% of traffic accidents worldwide are caused by drunk driving or drowsiness [1] [2], so a drowsiness level detection system that integrates image processing was developed with the use of Raspberry Pi3 with the OpenCV library; and sensors such as MQ-3 that measures the percentage of alcohol and the S9 sensor that measures the heart rate. In addition, it has an alert system and as an interface for the visualization of the data measured by the sensors a touch screen. With the image processing technique, facial expressions are analyzed, while physiological behaviors such as heart rate and alcohol percentage are measured with the sensors. In image test training you get an accuracy of x in a response time of x seconds. On the other hand, the evaluation of the operation of the sensors in 90% effective. So the method developed is effective and feasible.

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KW - sensor

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ER -

Eraldo B, Quispe G, Chavez-Arias H , Raymundo-Ibanez C, Dominguez F. Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing. In 2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8976928. (2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019). doi: 10.1109/CONCAPANXXXIX47272.2019.8976928

Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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