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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM63273
Volume:
10 |
5 |
May 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Computer Engineering
Sharadchandra Pawar college of engineering,otur
Computer Engineering
Sharadchandra Pawar college of engineering,otur
Computer Engineering
Sharadchandra Pawar college of engineering,otur
Computer Engineering
Sharadchandra Pawar college of engineering,otur
Visually impaired individuals face major challenges in identifying everyday products such as medicines, groceries, and packaged goods, which limits their independence and daily functioning. Braille labels, a traditional solution, are not universally applied and often lack detailed information. To overcome these barriers, voice-based product identification systems using QR code scanning have emerged as a cost-effective and scalable assistive technology. QR codes, when integrated with mobile applications, can be scanned through a smartphone camera and instantly converted into audio output using text-to-speech engines, allowing blind users to access essential product details without external assistance. This survey paper reviews existing QR code–based visual product identification approaches for the blind, comparing them with barcodes, RFID, and computer vision techniques. The paper also highlights current gaps such as dependency on internet access, lack of multilingual voice support, and challenges with damaged or unreadable codes. Finally, it explores future research directions, including AI-driven recognition, offline accessibility, and blockchain-enabled product authenticity to enhance usability and inclusivity.
KEYWORDS
This survey analyzed recent advances in voice-based and QR code-assisted product identification systems for visually impaired users. Current solutions demonstrate promising usability improvements through audio feedback, AI integration, and tactile QR code designs. However, challenges remain in terms of QR code discoverability, system reliability, offline functionality, standardization, and inclusive design for diverse user populations.
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Publication Date
5/16/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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