Evidence map›Paper›PMID 41760663›Full record

ArticleScientific reports2026

AI-powered BlindSpot VisionGuide system on raspberry Pi for enhancing independence of visually impaired users.

M Sudha, S Swaminathan, M Suba, A Suyamburajan

Abstract read
In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

M SudhaDepartment of ECE/Srinivasa Ramanujan Centre, SASTRA Deemed to Be University, Kumbakonam, India. sudha@src.sastra.edu.
S SwaminathanDepartment of ECE/Srinivasa Ramanujan Centre, SASTRA Deemed to Be University, Kumbakonam, India.
M SubaDepartment of ECE/Srinivasa Ramanujan Centre, SASTRA Deemed to Be University, Kumbakonam, India.
A SuyamburajanDepartment of ECE/Srinivasa Ramanujan Centre, SASTRA Deemed to Be University, Kumbakonam, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This work describes BlindSpot-VisionGuide, an integrated, AI-based assistive system that aims to empower visually impaired people towards independence through real-time audio interaction. The system incorporates three fundamental capabilities-face recognition, image captioning, and reading online newspapers-into a voice-based platform deployable in Raspberry Pi hardware. The face recognition capability recognizes known people using deep facial embeddings and returns instant voice feedback. The image captioning module uses a transformer-based BLIP model to produce natural language descriptions of scenes captured. The online newspaper module fetches structured news content through APIs and converts it into speech through a text-to-speech engine. The voice interface is centralized for all the modules, enabling users to interact with their surroundings without their hands. The system has been tested for recognition accuracy, response time, and memory consumption on a Raspberry Pi 5. Experiments indicate that the platform operates reliably in all modules, striking a balance between computation and user-friendliness. Optimized for offline use and low-power devices, BlindSpot illustrates the practical applicability of embedded AI towards the creation of inclusive, scalable assistive technology. The authors conclude by noting potential extensions, such as object detection, multi-language support, and caregiver incorporation, making BlindSpot a fundamental model for vision-based accessibility systems of the next generation.

Indexed as

Artificial IntelligencePersons with Visual DisabilitiesSelf-Help DevicesHumansIntelligent SystemsUser-Computer InterfaceAssistive technologyBLIPDeep learningFace recognitionImage captioningRaspberry PiText-to-speechVisually impaired

Identifiers

PMID41760663
PMCPMC13049014

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.