Title
Design of a control and monitoring system to reduce traffic accidents due to drowsiness through image processing
Date Issued
01 November 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
Publisher(s)
Institute of Electrical and Electronics Engineers Inc.
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.
Volume
2019-November
Language
English
OCDE Knowledge area
Telecomunicaciones
Ingeniería industrial
Subjects
Scopus EID
2-s2.0-85084948438
Resource of which it is part
2019 IEEE 39th Central America and Panama Convention, CONCAPAN 2019
ISBN of the container
9781728108834
Conference
39th IEEE Central America and Panama Convention, CONCAPAN 2019 Guatemala City 20 November 2019 through 22 November 2019
Sources of information:
Directorio de Producción Científica
Scopus