Aplicación para detectar microsueños para la prevención de accidentes viales en trayectos largos
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Fecha
2024
Autores
Moreno Martínez, Juan José
Arteta Jiménez, Jaime Junior
Barraza Polo, Carlos Andrés
Ricardo Molina, Andrés Felipe
De La Cruz Cáceres, Jerson Javid
Escorcia Suárez, Juan José
Fontalvo De Las Aguas, Yorcelis Judith
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Ediciones Universidad Simón Bolívar
Facultad de Ingenierías
Facultad de Ingenierías
Resumen
Los microsueños, son breves momentos de sueño involuntario que representan un peligro importante para la seguridad vial, que pueden resultar en una disminución de la atención y la capacidad de reacción, aumentando drásticamente el riesgo de colisiones. El proyecto propone abordar la problemática de los accidentes viales causados por el sueño y la fatiga del conductor en trayectos largos de viajes, centrándose en el desarrollo de una aplicación innovadora para detectar el microsueño y prevenir accidentes. La relevancia de esta investigación radica en la creciente movilidad y los viajes por carretera, lo que exige soluciones efectivas para mitigar los riesgos asociados con el sueño al volante. Se emplearán técnicas de inteligencia artificial y aprendizaje automático para entrenar y afinar los algoritmos de detección de microsueños, tales como las redes neuronales convolucionales. A través del análisis de imágenes del rostro de conductor se podrá detectar si este cierra los ojos por periodos prolongados, aplicando técnicas de inteligencia artificial, y visión computacional. La divulgación de los resultados contribuirá a crear conciencia sobre la importancia de mantenerse alerta durante los viajes por carretera y promoverá el uso de tecnología para la seguridad vial.
Microsleeps are brief moments of involuntary sleep that represent a significant danger to road safety, which can result in a decrease in attention and reaction capacity, drastically increasing the risk of collisions. The project proposes to address the problem of road accidents caused by sleep and driver fatigue on long journeys, focusing on the development of an innovative application to detect microsleep and prevent accidents. The relevance of this research lies in the increasing mobility and road travel, which requires effective solutions to mitigate the risks associated with drowsy driving. Artificial intelligence and machine learning techniques will be used to train and fine-tune microsleep detection algorithms, such as convolutional neural networks. Through the analysis of images of the driver's face, it will be possible to detect if he or she closes his eyes for prolonged periods, applying artificial intelligence and computer vision techniques. Disseminating the results will help raise awareness about the importance of staying alert during road trips and promote the use of technology for road safety.
Microsleeps are brief moments of involuntary sleep that represent a significant danger to road safety, which can result in a decrease in attention and reaction capacity, drastically increasing the risk of collisions. The project proposes to address the problem of road accidents caused by sleep and driver fatigue on long journeys, focusing on the development of an innovative application to detect microsleep and prevent accidents. The relevance of this research lies in the increasing mobility and road travel, which requires effective solutions to mitigate the risks associated with drowsy driving. Artificial intelligence and machine learning techniques will be used to train and fine-tune microsleep detection algorithms, such as convolutional neural networks. Through the analysis of images of the driver's face, it will be possible to detect if he or she closes his eyes for prolonged periods, applying artificial intelligence and computer vision techniques. Disseminating the results will help raise awareness about the importance of staying alert during road trips and promote the use of technology for road safety.
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Palabras clave
Accidentes viales, Microsueño, Visión computacional, Redes neuronales convolucionales