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Deep-Learning-Based Cognitive Assistance Embedded Systems for People with Visual Impairment

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Publicado en:Applied Sciences vol. 15, no. 11 (2025), p. 5887
Autor principal: Ngo Huu-Huy
Otros Autores: Le, Hung Linh, Feng-Cheng, Lin
Publicado:
MDPI AG
Materias:
Visual impairment
Embedded systems
Deep learning
Smartphones
Social interaction
Internet access
Age
Computer vision
Gender
Sensors
Classification
Blindness
Algorithms
Facial recognition technology
Surveillance
Emotions
Internet of Things
Acceso en línea:Citation/Abstract
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Resumen:For people with vision impairment, various daily tasks, such as independent navigation, information access, and context awareness, may be challenging. Although several smart devices have been developed to assist blind people, most of these devices focus exclusively on navigation assistance and obstacle avoidance. In this study, we developed a portable system for not only obstacle avoidance but also identifying people and their emotions. The core of the developed system is a powerful and portable edge computing device that implements various deep learning algorithms for images captured from a webcam. The user can easily select a function by using a remote control device, and the system vocally reports the results to the user. The developed system has three primary functions: detecting the names and emotions of known people; detecting the age, gender, and emotion of unknown people; and detecting objects. To validate the performance of the developed system, a prototype was constructed and tested. The results reveal that the developed system has high accuracy and responsiveness and is therefore suitable for practical applications as a navigation and social assistive device for people with visual impairment.
ISSN:2076-3417
DOI:10.3390/app15115887
Fuente:Publicly Available Content Database