Year: 2025
Type: article
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
Author: Hoysala Y Devanga
Institution: Kammavari Sangham Institute of Technology
Language: English
Subfield: Occupational Therapy
Field: Health Professions
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W4413279496