Author
Listed:
- Muhammad Arsalan Kamran*, Alishba Orakzai,Umama Noor,Yasir Saleem Afridi, Madiha Sher
(Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan.)
Abstract
This research introduces “Visually”, a revolutionary mobile application that aims to address the complications that visually impaired people come across in their daily lives. By deploying advanced deep learning models for real-time object detection, facial recognition, and currency identification with voice outputs for each feature, the “Visually” application strives to enhance the autonomy, independence, and mobility of visually impaired people. The system undergoes thorough training on a diverse dataset, incorporating augmentation techniques to enhance the robustness of the models. The project's multifaceted objectives include a user-friendly interface, real-time object detection, multi-modal recognition, Text-to-Speech audio output, and an overarching aim of enriching the lives of visually impaired individuals. Driven by the global prevalence of visual impairment and the demand for cost-effective solutions, “Visually” is aligned with international efforts for accessibility and inclusivity. For cross-platform compatibility, the machine learning models have been integrated whilst being deployed with TensorFlow Lite. With Offline availability, the application ensures accessibility even in rural areas with limited network connectivity. To make a substantial societal impact "Visually" aims to contribute to a more inclusive and equitable society, by transforming the way visually impaired individuals navigate around the environment. Positioned at the intersection of technology, accessibility, and empowerment, the “Visually” project is poised to bring about positive change for a community that frequently encounters unique challenges in their daily lives.
Suggested Citation
Muhammad Arsalan Kamran*, Alishba Orakzai,Umama Noor,Yasir Saleem Afridi, Madiha Sher, 2024.
"Visually: Assisting the Visually Impaired People Through AI-Assisted Mobility,"
International Journal of Innovations in Science & Technology, 50sea, vol. 6(5), pages 9-17, May.
Handle:
RePEc:abq:ijist1:v:6:y:2024:i:5:p:9-17
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