Implementación de un sistema piloto para la detección de cansancio en conductores mediante Machine Learning.
Fatigue in drivers has become a significant issue in terms of road safety. To address the car accidents caused by microsleep episodes, facial and body detection methods are employed using machine learning-based tools, allowing constant monitoring of facial expressions and body movements to generate...
- Autores:
-
Guarnizo Rengifo, Cristian David
Cortes Silvestre, Danilo
- Tipo de recurso:
- Trabajo de grado de pregrado
- Fecha de publicación:
- 2023
- Institución:
- Universidad Antonio Nariño
- Repositorio:
- Repositorio UAN
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.uan.edu.co:123456789/9592
- Acceso en línea:
- http://repositorio.uan.edu.co/handle/123456789/9592
- Palabra clave:
- machine learning
jetson tx2
sistema piloto
machine learning
jetson tx2
pilot system
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)
| Summary: | Fatigue in drivers has become a significant issue in terms of road safety. To address the car accidents caused by microsleep episodes, facial and body detection methods are employed using machine learning-based tools, allowing constant monitoring of facial expressions and body movements to generate alerts. However, when focusing on the average driver's environment, the availability of resources and new technology applications is limited. |
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