VisionEase: Reconceptualizing Reading for Partial Vision Seniors

This study focuses on the analysis of recent development in the field of accessible mobile e-Book applications for learners with a particular emphasis on usability demands and technological options. The analysis came up with some of these specific needs, among them being; text-to-speech customization, contrast, text enlargement, and ease of navigation, which this study fills by using machine learning model of gradient boosting to predict fonts and zoom factor for visually impaired to have easy simplified e-book. These usability attributes are important in the provision of access to the visually impaired people when using the digital contents. Although many studies have not addressed these challenges using machine learning, this paper demonstrates enhancing user experience such as incorporating ML models such as (Random forest, SVR, Decision trees and Gradient boosting) for predicting the font size and style. Of them Gradient boosting was chosen the best model due to its propriety to incorporate the numeric variables such as age, screen size, and categorical variables such as e-book content type and brightness. Furthermore, it has high precision and stability, which retains good performance on a small amount of data, satisfying the study’s condition. These model which includes Scikit-learn makes it possible to develop smart areas that adapt the shape and the content depending on the user’s demand to offer a more personalized reading experience. Thus, the outcomes shows that Gradient Boosting model sets the font size ( 27) and font style (Times New Roman) with the input attributes. Beside increasing the convenience in obtaining e-books, such development also provides positive effects for the visually impaired that is to enhance their ability and enable them to be more active members of society. Incorporating these models into the e-book platforms will help add onto the creation of a society where technology fits the needs of all consumers especially touching on the issues affecting the visually impaired.