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Artificial vision in renewable photovoltaic systems: a review and vision of specific applications and technologies

2025-12-18Journal article Open access
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authorProfile.emailbiblioteca@isel.pt
datacite.subject.fosEngenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática
dc.contributor.authorAmaral, Tito G.
dc.contributor.authorCordeiro, Armando
dc.contributor.authorFernao Pires, Vitor
dc.date.accessioned2026-01-08T10:50:30Z
dc.date.available2026-01-08T10:50:30Z
dc.date.issued2025-12-18
dc.descriptionThis work was partially supported by national funds through FCT Fundação para a Ciência e a Tecnologia with reference UIDB/00066/2020 and UIDP/00066/2020, and project H2020 MSCA-ITN SMARTGYsum (under Grant no. 955614).
dc.description.abstractRenewable energy resources have become extremely important in the current context of air pollution and the production of significant amounts of greenhouse gas emissions that contribute to global warming. One of the most important renewable energy sources that has shown the highest growth in recent years is photovoltaic (PV) systems. Due to their significance, this research presents a review of the applications in which artificial computer vision can be used in photovoltaic systems. From the results presented in this review, it will be evident that artificial vision can be applied for several different purposes. The advantages of using this technique will also be highlighted. Additionally, a systematic literature review is presented on the research associated with this topic. Through this review, it will be evident that many advanced algorithms related to image acquisition equipment have been proposed to ensure high reliability and fast results. This review does not merely focus on a specific topic or algorithms associated with image processing applied to photovoltaic systems. Rather, this work presents a broad and comprehensive review detailing all viable applications and associated computer vision technologies that can be deployed within these systems. Besides that, the review will clearly specify which work one is based on public datasets. To allow future reproducibility or research, the links to all public datasets utilized in the works based on them are included.eng
dc.identifier.citationAmaral, T. G., Cordeiro, A., & Pires, V. F. (2025). Artificial vision in renewable photovoltaic systems: a review and vision of specific applications and technologies. Applied Sciences, 15(24), 13285. https://doi.org/10.3390/app152413285
dc.identifier.doi10.3390/app152413285
dc.identifier.eissn2076-3417
dc.identifier.urihttp://hdl.handle.net/10400.21/22456
dc.language.isoeng
dc.peerreviewedyes
dc.publisherMDPI AG
dc.relationCentre of Technology and Systems
dc.relationH2020 MSCA-ITN SMARTGYsum
dc.relation.hasversionhttps://www.mdpi.com/2076-3417/15/24/13285
dc.relation.ispartofApplied Sciences
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectPhotovoltaic systems
dc.subjectArtificial vision
dc.subjectComputer vision
dc.subjectArtificial intelligence
dc.subjectSystematic revision
dc.subjectUIDB/00066/2020
dc.subjectUIDP/00066/2020
dc.subjectH2020 MSCA-ITN SMARTGYsum
dc.titleArtificial vision in renewable photovoltaic systems: a review and vision of specific applications and technologieseng
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleCentre of Technology and Systems
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00066%2F2020/PT
oaire.citation.endPage93
oaire.citation.issue24
oaire.citation.startPage1
oaire.citation.titleApplied Sciences
oaire.citation.volume15
oaire.fundingStream6817 - DCRRNI ID
oaire.versionhttp://purl.org/coar/version/c_be7fb7dd8ff6fe43
person.familyNameCordeiro
person.familyNameFernao Pires
person.givenNameArmando
person.givenNameVitor
person.identifier2692732
person.identifier1017494
person.identifier.ciencia-idEE1F-34B0-4A02
person.identifier.ciencia-idDC1C-D708-69C5
person.identifier.orcid0000-0001-6658-5783
person.identifier.orcid0000-0002-3764-0955
person.identifier.ridL-6836-2015
person.identifier.scopus-author-id7003305269
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
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relation.isAuthorOfPublicationa996ebdc-6eb2-4493-abb1-0b30fb0ac802
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