ESPYREAL: A Mobile Based Multi-Currency Identifier for Visually Impaired Individuals Using Convolutional Neural Network

Kurt Russel N. De leon, Jhodel D. Datiles, Kyle Condrei N. Cruz, Cruz Kathlyn M. and Ronald Fernandez
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Kurt Russel N. De leon: College of Computing Studies, Universidad De Manila
Jhodel D. Datiles: College of Computing Studies, Universidad De Manila
Kyle Condrei N. Cruz: College of Computing Studies, Universidad De Manila
Cruz Kathlyn M.: College of Computing Studies, Universidad De Manila
Ronald Fernandez: College of Computing Studies, Universidad De Manila

International Journal of Research and Innovation in Applied Science, 2025, vol. 10, issue 9, 165-176

Abstract: Visually impaired person’s faces many issues in handling money because they cannot differentiate different denominations especially in countries like the Philippines where both local and foreign banknotes are circulating together. This challenge may lead to various issues like the misidentification of paper money or coins, depending on others for financial matters, and being open to possible exploitation of finances. Therefore in this study the proponents implemented an image processing techniques that will assist visually impaired people in detecting and identifying money using convolutional neural network algorithm. The main objective of this application is to help the visually impaired individuals identify two different denominations that is commonly used in the contemporary time of the Philippines such as United States Dollar (USD) and Philippine Peso (PHP), making them feel secured and confident when they are conducting financial transaction alone. The application will be implemented as Android-based money detection app. The researchers utilize the AGILE and Tensoflow platform to build accurate and fast model. They collected diverse amount of Philippine Peso and United States Dollar banknotes and coins images, captured in different angles and lighting condition to achieve reliable model for Multi-Money Recognition Application. Furthermore, The proponents created a likert scale questionnaire that will use for survey and interview with visually impaired stakeholders in Pasay, Manila. Based on ISO/IEC 25010 evaluation, Espyreal achieved excellent ratings across functionality (4.74), usability (4.72), performance efficiency (4.64), reliability (4.60), and portability (4.58), with an overall weighted mean of 4.60. A 98 percent accuracy across all bills is achieve through diverse collection of bills datasets and aggressive training with Tensorflow platform. The results demonstrate that the system is functional, dependable, efficient, and user-friendly. The proponents suggest to upload the Espyreal to the Google Play Store for Easy access and download for the intended users.

Date: 2025
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