Evidence map›Paper›PMID 42535809›Full record

ArticleIndian journal of ophthalmology2026

Internet of things in assistive technology for people with visual impairment: A scoping review.

Pooja Chauhan, Suraj S Senjam, Salaj Rana, Ravinder Singh, Sandeep Singh

Abstract readScoping Review
In one paragraph

Article in Indian journal of ophthalmology, 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

5 authors.

Pooja ChauhanNational Center for Assistive Health Technology (NCAHT), New Delhi, India.
Suraj S SenjamNational Center for Assistive Health Technology (NCAHT), New Delhi, India.
Salaj RanaNational Center for Assistive Health Technology (NCAHT), New Delhi, India.
Ravinder SinghDivision of Non-Communicable Diseases, Indian Council of Medical Research Headquarters, New Delhi, India.
Sandeep SinghNational Center for Assistive Health Technology (NCAHT), New Delhi, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Assistive technology (AT) can significantly enhance functional abilities among persons with disabilities. Recently, a rapid advance in computer and Internet of Things (IoT)-based AT has been observed with the integration of Artificial Intelligence. The present scoping review explores a range of IoT-based AT for vision impairments, focusing on their functioning, reliability, and identifying the existing gaps and opportunities for future enhancement. We used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The search was conducted for the articles published between 2020 and March 2025. After the initial screening of both titles and abstracts of 705 articles, 18 full-text articles were selected for the review. It was found that the majority of the papers (38%) are related to smart canes/sticks. The findings indicate that several studies use Raspberry Pi and Arduino platform to make products cost-effective and flexible options for real-time processing. The accuracy of these devices ranges from 87.8% in navigation to 93% in voice control and 100% in object identification. Further, challenges such as usability testing, hardware limitations, dataset constraints, and environmental adaptability remain a matter of concern which need to be addressed in future innovation. Incorporating IoT technologies into vision-assistive devices has substantially improved accessibility. Future research should focus on enhancing real-time performance, AI-driven decision-making, and user-centric designs.

Indexed as

Artificial IntelligenceInternet of ThingsPersons with Visual DisabilitiesSelf-Help DevicesVision DisordersHumansAssistive technologyblindnessInternet of Thingslow visionmachine learning

Identifiers

PMID42535809
PMCPMC13485097

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.