Abstract: Nowadays, the Artificial Intelligence (AI) field has made a significant change in the real life. Numerous applications use the AI techniques for the purpose of assisting people in different life aspects. Furthermore, with the increased number of people with visual difficulties around the world, there is a need for such AI assistive applications which provide them an independent life. Limited affordable and appropriate solutions developed so far. In this paper, we present a personal AI-based assistive application called (Vivid) that supports visually impaired people being more independent. Vivid has many features such as identifying objects, objects’ colors, recognizing text, and faces detection. It relies on using the mobile camera to sense the environment, and the machine learning techniques to understand the environment. By translating a meaningful information in audible sound for those users, Vivid does not require to have any visual ability. Moreover, the whole interaction with the user is only based on voice commands. The input from the user is captured as finger gestures on tablet or cell phone touch screen. In addition to Vivid, we also shade the lights on a supplementary application that notify/alarm visually impaired people of any nearby objects using sensors. These personal assistive applications were developed then tested on the real world and showed promising results.

Samah Alhazmi, Mohammed Kutbi, Soha Alhelaly, Ulfat Dawood, Reem Felemban and Entisar Alaslani, “Utilizing Artificial Intelligence Techniques for Assisting Visually Impaired People: A Personal AI-based Assistive Application” International Journal of Advanced Computer Science and Applications(IJACSA), 13(8), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130894

@article{Alhazmi2022,
title = {Utilizing Artificial Intelligence Techniques for Assisting Visually Impaired People: A Personal AI-based Assistive Application},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130894},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130894},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {8},
author = {Samah Alhazmi and Mohammed Kutbi and Soha Alhelaly and Ulfat Dawood and Reem Felemban and Entisar Alaslani}
}