Estudio de técnicas de smart IoT aplicadas a la detección de gestos para el accionamiento de dispositivos
Cargando...
Fecha
2023
Autores
Título de la revista
ISSN de la revista
Título del volumen
Editor
Universidad Nacional Arturo Jauretche
Resumen
Este trabajo presenta el desarrollo y la implementación de un sistema basado en Internet de las Cosas (IoT) y visión por computadora para detectar y responder a gestos, destinado a mejorar la autonomía y calidad de vida de personas con discapacidades. El enfoque inclusivo busca empoderar a estos individuos en su interacción con su entorno. El sistema emplea una cámara para capturar imágenes que posteriormente se someten a procesamiento con el fin de identificar gestos como el alzamiento de cejas o el guiño de un ojo. El proceso de desarrollo involucró técnicas de IoT, procesamiento de imágenes y aprendizaje automático para lograr detección precisa. La arquitectura consta de un servidor, una aplicación de procesamiento de imágenes, varios microcontroladores y distintos tipos de dispositivos de visualización. La identificación de gestos activa los microcontroladores para ejecutar acciones en el entorno físico como respuesta. Los dispositivos de visualización muestran el proceso en tiempo real. Este informe detalla los componentes técnicos, herramientas, la implementación y las pruebas, demostrando la eficacia y el potencial del sistema para mejorar la calidad de vida de las personas con discapacidades.
-
This work presents the development and implementation of an Internet of Things (IoT) and computer vision-based system for detecting and responding to gestures, aimed at enhancing the autonomy and quality of life of people with disabilities. The inclusive approach seeks to empower these individuals in their interaction with their environment. The system utilizes a camera to capture images which are subsequently subjected to processing in order to identify gestures such as eyebrow raises or winks. The development process involved IoT, image processing, and machine learning techniques to achieve accurate detection. The architecture consists of a server, an image processing application, multiple microcontrollers, and various types of display devices. Gesture identification triggers the microcontrollers to execute actions in the physical environment as a response. The display devices showcase the process in real-time. This report details the technical components, tools, implementation, and testing, showcasing the effectiveness and potential of the system in improving the quality of life for people with disabilities.
This work presents the development and implementation of an Internet of Things (IoT) and computer vision-based system for detecting and responding to gestures, aimed at enhancing the autonomy and quality of life of people with disabilities. The inclusive approach seeks to empower these individuals in their interaction with their environment. The system utilizes a camera to capture images which are subsequently subjected to processing in order to identify gestures such as eyebrow raises or winks. The development process involved IoT, image processing, and machine learning techniques to achieve accurate detection. The architecture consists of a server, an image processing application, multiple microcontrollers, and various types of display devices. Gesture identification triggers the microcontrollers to execute actions in the physical environment as a response. The display devices showcase the process in real-time. This report details the technical components, tools, implementation, and testing, showcasing the effectiveness and potential of the system in improving the quality of life for people with disabilities.
Descripción
Palabras clave
IoT