Mobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People

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Autore principale: Camila Bolaños-Fernández
Natura: Artículo científico
Lingua:en
Pubblicazione: Universidad Distrital Francisco José de Caldas 2024
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author Camila Bolaños-Fernández
author_facet Camila Bolaños-Fernández
contents Mobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People Camila Bolaños-Fernández Eval Bladimir Bacca-Cortes Ingeniería Mobile application visually impaired people convolutional neural network Colombian currency recognition Context: According to the census conducted by the National Department of Statistics (DANE) in 2018, 7.1\% of the Colombian population has a visual disability. These people face conditions with limited autonomy, such as the handling of money. In this context, there is a need to create tools to enable the inclusion of visually impaired people in the financial sector, allowing them to make payments and withdrawals in a safe and reliable manner.Method: This work describes the development of a mobile application called CopReader. This application enables the recognition of coins and banknotes of Colombian currency without an Internet connection, by means of convolutional neural network models. CopReader was developed to be used by visually impaired people. It takes a video or photographs, analyzes the input data, estimates the currency value, and uses audio feedback to communicate the result. Results: To validate the functionality of CopReader, integration tests were performed. In addition, precision and recall tests were conducted, considering the YoloV5 and MobileNet architectures, obtaining 95 and 93\% for the former model and 99\% for the latter. Then, field tests were performed with visually impaired people, obtaining accuracy values of 96%. 90% of the users were satisfied with the application’s functionality.Conclusions: CopReader is a useful tool for recognizing Colombian currency, helping visually impaired people gain to autonomy in handling money. 2024 artículo científico 0121-750X https://www.redalyc.org/articulo.oa?id=498880092006 https://www.redalyc.org/journal/4988/498880092006/ https://www.redalyc.org/journal/4988/498880092006/html/ https://www.redalyc.org/journal/4988/498880092006/498880092006.epub https://www.redalyc.org/journal/4988/498880092006/movil 10.14483/23448393.21408 en http://www.redalyc.org/revista.oa?id=4988 Ingeniería application/pdf Universidad Distrital Francisco José de Caldas Ingeniería (Colombia) Num.2 Vol.29
format Artículo científico
id redalyc_498880092006
institution Redalyc
language en
publishDate 2024
publisher Universidad Distrital Francisco José de Caldas
spellingShingle Mobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People
Camila Bolaños-Fernández
Ingeniería
Mobile application
visually impaired people
convolutional neural network
Colombian currency recognition
Mobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People Camila Bolaños-Fernández Eval Bladimir Bacca-Cortes Ingeniería Mobile application visually impaired people convolutional neural network Colombian currency recognition Context: According to the census conducted by the National Department of Statistics (DANE) in 2018, 7.1\% of the Colombian population has a visual disability. These people face conditions with limited autonomy, such as the handling of money. In this context, there is a need to create tools to enable the inclusion of visually impaired people in the financial sector, allowing them to make payments and withdrawals in a safe and reliable manner.Method: This work describes the development of a mobile application called CopReader. This application enables the recognition of coins and banknotes of Colombian currency without an Internet connection, by means of convolutional neural network models. CopReader was developed to be used by visually impaired people. It takes a video or photographs, analyzes the input data, estimates the currency value, and uses audio feedback to communicate the result. Results: To validate the functionality of CopReader, integration tests were performed. In addition, precision and recall tests were conducted, considering the YoloV5 and MobileNet architectures, obtaining 95 and 93\% for the former model and 99\% for the latter. Then, field tests were performed with visually impaired people, obtaining accuracy values of 96%. 90% of the users were satisfied with the application’s functionality.Conclusions: CopReader is a useful tool for recognizing Colombian currency, helping visually impaired people gain to autonomy in handling money. 2024 artículo científico 0121-750X https://www.redalyc.org/articulo.oa?id=498880092006 https://www.redalyc.org/journal/4988/498880092006/ https://www.redalyc.org/journal/4988/498880092006/html/ https://www.redalyc.org/journal/4988/498880092006/498880092006.epub https://www.redalyc.org/journal/4988/498880092006/movil 10.14483/23448393.21408 en http://www.redalyc.org/revista.oa?id=4988 Ingeniería application/pdf Universidad Distrital Francisco José de Caldas Ingeniería (Colombia) Num.2 Vol.29
title Mobile Application for Recognizing Colombian Currency with Audio Feedback for Visually Impaired People
topic Ingeniería
Mobile application
visually impaired people
convolutional neural network
Colombian currency recognition
url https://www.redalyc.org/articulo.oa?id=498880092006
https://www.redalyc.org/journal/4988/498880092006/
https://www.redalyc.org/journal/4988/498880092006/html/
https://www.redalyc.org/journal/4988/498880092006/498880092006.epub
https://www.redalyc.org/journal/4988/498880092006/movil