Repository logo
 
Publication

Artificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Review

2022-11-05Journal article Open access
Simple item page
dc.contributor.authorFreitas, Mauricio
dc.contributor.authorVinícius Aquino PiaiPT
dc.contributor.authorRicardo Heffel FariasPT
dc.contributor.authorFernandes, Anita
dc.contributor.authorDe Moraes Rossetto, Anubis Graciela
dc.contributor.authorLEITHARDT, VALDERI
dc.date.accessioned2023-02-01T18:04:54ZPT
dc.date.available2023-02-01T18:04:54ZPT
dc.date.issued2022-11-05PT
dc.date.updated2022-11-10T10:27:02Z
dc.description.abstractAccording to the World Health Organization, about 15% of the world’s population has some form of disability. Assistive Technology, in this context, contributes directly to the overcoming of difficulties encountered by people with disabilities in their daily lives, allowing them to receive education and become part of the labor market and society in a worthy manner. Assistive Technology has made great advances in its integration with Artificial Intelligence of Things (AIoT) devices. AIoT processes and analyzes the large amount of data generated by Internet of Things (IoT) devices and applies Artificial Intelligence models, specifically, machine learning, to discover patterns for generating insights and assisting in decision making. Based on a systematic literature review, this article aims to identify the machine-learning models used across different research on Artificial Intelligence of Things applied to Assistive Technology. The survey of the topics approached in this article also highlights the context of such research, their application, the IoT devices used, and gaps and opportunities for further development. The survey results show that 50% of the analyzed research address visual impairment, and, for this reason, most of the topics cover issues related to computational vision. Portable devices, wearables, and smartphones constitute the majority of IoT devices. Deep neural networks represent 81% of the machine-learning models applied in the reviewed research.pt_PT
dc.description.sponsorshipGRANT_NUMBER: 32020
dc.description.versionN/Apt_PT
dc.identifier.doi10.3390/s22218531pt_PT
dc.identifier.slugcv-prod-3074975
dc.identifier.urihttp://hdl.handle.net/10400.26/43550PT
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.subjectAIoT; gpt_PT
dc.subjectartificial intelligence;pt_PT
dc.subjectassistive technology;pt_PT
dc.subjectdeep learning;pt_PT
dc.subjectmachine learninpt_PT
dc.titleArtificial Intelligence of Things Applied to Assistive Technology: A Systematic Literature Reviewpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.titleSensorspt_PT
person.familyNameFreitas
person.familyNameFernandes
person.familyNamede Moraes Rossetto
person.familyNameREIS QUIETINHO LEITHARDT
person.givenNameMauricio
person.givenNameAnita
person.givenNameAnubis Graciela
person.givenNameVALDERI
person.identifierJsOq45sAAAAJ&hl=pt-PT
person.identifier.ciencia-id0614-5834-E7F3
person.identifier.orcid0000-0002-4509-6611
person.identifier.orcid0000-0002-2986-5353
person.identifier.orcid0000-0001-8657-2816
person.identifier.orcid0000-0003-0446-9271
person.identifier.scopus-author-id42861207900
person.identifier.scopus-author-id35303109600
rcaap.cv.cienciaid0614-5834-E7F3 | Valderi Reis Quietinho Leithardt
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
relation.isAuthorOfPublication3eb62f5c-c980-42b1-9168-22f8e3a616ad
relation.isAuthorOfPublication4e0e3a69-c788-455a-81a0-679da835632e
relation.isAuthorOfPublication0a135edf-3899-4260-b32b-47f9a1199750
relation.isAuthorOfPublicationab15f7c6-e882-406e-813d-2629e9cec5c8
relation.isAuthorOfPublication.latestForDiscoveryab15f7c6-e882-406e-813d-2629e9cec5c8

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
sensors-22-08531-v2.pdf
Size:
976.5 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.89 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

VALORIZA - Artigos em Revistas Científicas