Artificial intelligence software to detect microsleeps in drivers

This project was developed to address a significant social and economic issue: the detection of microsleeps in minibus drivers. Interprovincial trips, especially at night or during long journeys, increase the risk of fatigue and drowsiness, which affects the driver's attention. The consequences...

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Detalles Bibliográficos
Autor: Morales Gonzales, Ruso Alexander
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2025
País:Perú
Institución:Universidad de San Martín de Porres
Repositorio:Revistas - Universidad de San Martín de Porres
Idioma:español
OAI Identifier:oai:revistas.usmp.edu.pe:article/2933
Acceso en línea:https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/2933
Access Level:acceso abierto
Palabra clave:Artificial intelligence
Microsleep detection with AI
Facial recognition
Inteligencia artificial
Detección de microsueño con IA
Reconocimiento facial
Descripción
Sumario:This project was developed to address a significant social and economic issue: the detection of microsleeps in minibus drivers. Interprovincial trips, especially at night or during long journeys, increase the risk of fatigue and drowsiness, which affects the driver's attention. The consequences not only jeopardize the physical integrity of those involved but also lead to substantial material and economic losses. According to the World Health Organization, drowsiness-related accidents are one of the leading causes of mortality on roads worldwide (WHO, 2021). This project developed artificial intelligence (AI) software to monitor and analyze drivers' facial patterns in real time, identifying early signs of fatigue such as prolonged blinking, yawning, and head nodding. Ultimately, a mobile solution was achieved, capable of alerting the driver with auditory signals upon detecting a potential microsleep, allowing for early and effective interventions to prevent accidents. This technological advancement represents a significant contribution to road safety and can be extended to other public and private transportation contexts.