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      Enhancing Mobility for the Visually Impaired with AI and IoT-Enabled Mobile Applications

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            Revision notes

            The only change for this updated version is changing the affiliation of the second author, Asmaa Ali, to Western University, London, Ontario, Canada.

            Abstract

            Developing a mobile application that assists visually impaired persons (VIPs) in navigating public transportation systems is significantly important for the quality of life of the growing number of VIPs in the world. The application should utilize real-time information about bus and train schedules, as well as the layout of transit stations, to provide step-by-step directions to users for reaching their desired destination. The app should be accessible to individuals with a range of visual impairments, featuring high-contrast colors, large fonts, and text-to-speech functionality. It should also provide alerts when the user is approaching their stop and can communicate with transit operators to request assistance if needed. This paper presents a comprehensive survey of the existing applications and systems available for VIP in transportation and other areas, finding out the limitations of these applications to propose new and efficient solutions, especially solutions involving Artificial Intelligence (AI), Machine Learning (ML), and Internet of Things (IoT) – evolved cutting edge technologies.

            Content

            Author and article information

            Journal
            ScienceOpen Preprints
            ScienceOpen
            9 April 2024
            Affiliations
            [1 ] Alfaisal University, Riyadh, Saudi Arabia ( https://ror.org/00cdrtq48)
            [2 ] Western University, London, Ontario, Canada ( https://ror.org/02grkyz14)
            [3 ] Seneca Polytechnic, Toronto, Canada ( https://ror.org/04qgh9k98)
            [4 ] Prince Sultan University, Riyadh, Saudi Arabia ( https://ror.org/053mqrf26)
            Author notes
            Author information
            https://orcid.org/0000-0002-9532-2074
            Article
            10.14293/PR2199.000775.v2
            247897d0-c6f9-444b-aebf-b1a31fbf63e5

            This work has been published open access under Creative Commons Attribution License CC BY 4.0 , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Conditions, terms of use and publishing policy can be found at www.scienceopen.com .

            History
            : 21 March 2024
            Funding
            Funded by: funder-id http://dx.doi.org/10.13039/501100019345, King Salman Center for Disability Research;
            Award ID: Research Group no KSRG-2023-546
            Categories

            Data sharing not applicable to this article as no datasets were generated or analysed during the current study.
            Software engineering,Communication networks,Applied computer science,Artificial intelligence
            Visually Impaired Persons,Smart Transportation,Artificial Intelligence,Machine Learning,Internet of Things,Accessibility

            References

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