A neural network for the detection of drowsiness in drivers
Keywords:
machine learning, neural network, sensors, somnolence, vigilAbstract
he following article shows the use of machine learning, a type of artificial intelligence, to detect somnolence and the state of vigil in drivers. Somnolence is generated when an individual has high levels of stress or tiredness, and can lead to a potential accident. When alert, it is called vigil state. Two variables are considered: heartbeat and body temperature. Heartbeat was measured with a sensor through the photopletismograph method (PPG). Body temperature was taken through an infrared sensor without contact. The obtained data was used to create a database and to train a neuron network with supervised learning. Later, the information was classified through this data acquisition system.
Published
Issue
Section
License
Copyright (c) 2022 Revista Digital Universitaria
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Revista Digital Universitaria es editada por la Universidad Nacional Autónoma de México se distribuye bajo una Licencia Creative Commons Atribución-NoComercial 4.0 Internacional. Basada en una obra en http://revista.unam.mx/.