AI-Driven Vision Assistance for Visually Impaired

ThisprojectintroducesanAI-basedreal-timeobjectdetectionandvoiceassistancesystemdesigned to support visually impaired individuals in navigating their surroundings independently and safely. The solution combines a mobile application with a portable camera module, enabling continuous environmental awareness without relying solely on the smartphone’s builtin camera. By utilizing advanceddeeplearningalgorithmssuchasYOLO orSSD,thesystemdetectsandidentifiesobjects in real time.Once an object is recognized, the application uses a Text-to-Speech (TTS) engine to provide immediate voice feedback, informing the user of the object’s identity. The integration of a portable camera enhances flexibility and usability, allowing for hands-free operation and more accurate object capture. The system is optimized for performance on mobile devices, ensuring low latency, high accuracy, and energy efficiency. This project aims to deliver a cost-effective, accessible,andpracticalassistivetechnologysolutionthatimprovesautonomy,mobility,andquality of life for visually impaired users

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Publication Details

Journal
International Journal for Research in Applied Science and Engineering Technology
Published
2025-08-18
DOI
https://doi.org/10.22214/ijraset.2025.73684
Primary Topic
Tactile and Sensory Interactions
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-Driven Vision Assistance for Visually Impaired

Hoysala Y Devanga
International Journal for Research in Applied Science and Engineering Technology
Tactile and Sensory Interactions
article

AI-Driven Vision Assistance for Visually Impaired

Hoysala Y Devanga
article en

Abstract

ThisprojectintroducesanAI-basedreal-timeobjectdetectionandvoiceassistancesystemdesigned to support visually impaired individuals in navigating their surroundings independently and safely. The solution combines a mobile application with a portable camera module, enabling continuous environmental awareness without relying solely on the smartphone’s builtin camera. By utilizing advanceddeeplearningalgorithmssuchasYOLO orSSD,thesystemdetectsandidentifiesobjects in real time.Once an object is recognized, the application uses a Text-to-Speech (TTS) engine to provide immediate voice feedback, informing the user of the object’s identity. The integration of a portable camera enhances flexibility and usability, allowing for hands-free operation and more accurate object capture. The system is optimized for performance on mobile devices, ensuring low latency, high accuracy, and energy efficiency. This project aims to deliver a cost-effective, accessible,andpracticalassistivetechnologysolutionthatimprovesautonomy,mobility,andquality of life for visually impaired users

International Journal for Research in Applied Science and Engineering TechnologyVol. 13(8)
Institute of Engineering Science (RU)
Openalex Percentile: Top 79%
Tactile and Sensory Interactions
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