SMART VISION AID: INTEGRATED AI SYSTEM FOR OBSTACLE DETECTION, FACE RECOGNITION, CURRENCY IDENTIFICATION FOR THE VISUALLY IMPAIRED

Assistive technologies for visually impaired individuals have evolved significantly with the advancement of Artificial Intelligence and embedded systems. However, many existing systems focus on a single functionality such as obstacle detection or currency recognition. This paper proposes an AI-based Smart Assistive Vision System implemented using Raspberry Pi 4 and computer vision techniques. The system integrates obstacle detection, face recognition, and currency identification into a unified portable device. A camera module captures real-time visual input, which is processed using OpenCV and deep learning models. The recognized information is converted into audio feedback using a Text-toSpeech (TTS) engine. The system ensures real-time processing, cost-effectiveness, and portability. Experimental results demonstrate high detection accuracy and reliable performance under various environmental conditions. This integrated assistive system enhances independence, safety, and social interaction for visually impaired user.

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-04-13
DOI
https://doi.org/10.5281/zenodo.19550458
Primary Topic
Currency Recognition and Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

SMART VISION AID: INTEGRATED AI SYSTEM FOR OBSTACLE DETECTION, FACE RECOGNITION, CURRENCY IDENTIFICATION FOR THE VISUALLY IMPAIRED

A Merlin, K Sowmiya, R Ranjani, S Vanisri et al.
Zenodo (CERN European Organization for Nuclear Research)
Currency Recognition and Detection
article

SMART VISION AID: INTEGRATED AI SYSTEM FOR OBSTACLE DETECTION, FACE RECOGNITION, CURRENCY IDENTIFICATION FOR THE VISUALLY IMPAIRED

A Merlin, K Sowmiya, R Ranjani, S Vanisri, K Gowsalya
article en

Abstract

Assistive technologies for visually impaired individuals have evolved significantly with the advancement of Artificial Intelligence and embedded systems. However, many existing systems focus on a single functionality such as obstacle detection or currency recognition. This paper proposes an AI-based Smart Assistive Vision System implemented using Raspberry Pi 4 and computer vision techniques. The system integrates obstacle detection, face recognition, and currency identification into a unified portable device. A camera module captures real-time visual input, which is processed using OpenCV and deep learning models. The recognized information is converted into audio feedback using a Text-toSpeech (TTS) engine. The system ensures real-time processing, cost-effectiveness, and portability. Experimental results demonstrate high detection accuracy and reliable performance under various environmental conditions. This integrated assistive system enhances independence, safety, and social interaction for visually impaired user.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 7%
Currency Recognition and Detection
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