Environment Descriptor for Visually Impaired People Implemented on Raspberry Pi Based on Convolutional and Recurrent Artificial Neural Networks
DOI:
https://doi.org/10.54139/revinguc.v28i1.15Keywords:
Artificial Neural Network, Natural Languaje Processing, Raspberry Pi, Deep Learning, Features ExtractionAbstract
Vision problems and blindness are disorders of the human body that according to figures from the World Health Organization affect 217 million people in low-income countries. The quality of life of at least 75 million of them can be improved with the development of systems that allow guiding them safely in their daily tasks; this is where it is important to look for technological alternatives oriented to solve this problem and it is precisely where the idea of this research work was born. The idea presented here is based on the development of an image description system trained with deep learning algorithms based on convolutional and recurrent neural networks, implemented in a single-board computer. This implementation uses a low-cost camera for taken images of the environment and obtains a description of it that can be converted to an audible voice signal through a hearing aid system so that visually impaired people can improve their standard of living by obtaining real-time information from the environment surrounding.
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