International Journal of Emerging Research in Science, Engineering, and Management
Vol. 2, Issue 3, pp. 01-07, March 2026.
This work is licensed under a Creative Commons Attribution 4.0 International License.
Smart Vision System for Assistive Object Recognition and Independent Navigation of the Visually Impaired
G Ravi Kumar
Siripireddy Prathyusha
Shaik Thasleem
Shaik Farukh Ahamed
M G Uma Sankar
Chandragiri Venu Gopal Reddy
Department of CSE, Siddartha Institute of Science and Technology, Puttur, India.
Abstract: Smart Vision is an innovative assistive technology designed to foster independence and safety for visually impaired individuals through real-time situational awareness. By integrating high-performance Computer Vision models, specifically Convolutional Neural Networks (CNN) and YOLO, the system provides instantaneous recognition of objects and obstacles. The framework utilizes a compact, wearable camera or mobile interface to capture continuous visual data, which is then processed and converted into intuitive audio feedback for the user. Engineered as a lightweight and energy-efficient solution, the system addresses the critical need for affordable navigation aids. By reducing dependence on human caregivers, Smart Vision enhances mobility and confidence in diverse environments. This research contributes a robust, scalable architecture that balances computational precision with low-latency performance, offering a transformative tool for navigating the modern world with greater autonomy.
Keywords: Assistive Technology, Object Recognition, YOLO, Visually Impaired, Real-time Navigation.
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