Show simple item record

dc.contributor.authorHidalgo Betanzos, Juan María
dc.contributor.authorProl Godoy, Irati
dc.contributor.authorTerés Zubiaga, Jon
dc.contributor.authorBriones Llorente, Raúl
dc.contributor.authorMartín Garín, Alexánder
dc.date.accessioned2026-07-01T07:48:13Z
dc.date.available2026-07-01T07:48:13Z
dc.date.issued2025
dc.identifier.citationHidalgo Betanzos, J. M., Prol Godoy, I., Terés Zubiaga, J., Briones Llorente, R., y Martín Garín, A. (2025). Can ChatGPT AI Replace or Contribute to Experts’ Diagnosis for Renovation Measures Identification?. Buildings, 15(3). https://doi.org/10.3390/buildings15030421es
dc.identifier.issn2075-5309
dc.identifier.urihttp://hdl.handle.net/20.500.12251/4291
dc.description.abstractBuilding energy renovations demand expertise from professionals to guide processes, including diagnostics, project planning, interventions, and maintenance. The emergence of open-access AI, like ChatGPT in November 2022, offers new possibilities for improving these processes by assisting or potentially replacing human experts. This study explores the effectiveness of ChatGPT in diagnosing energy renovation measures. Initial assessments involve basic queries to the AI, followed by the inclusion of additional data and secondary questions to gauge its full diagnostic potential. An existing building case from the literature is given to the AI to define the best energy renovation measures. Expert evaluations and comparisons with research-backed solutions assess the AI’s performance using different degrees of questioning details over 60 repetitions. The results indicate that ChatGPT can provide valuable insights and generate comprehensive lists of feasible measures and preliminary cost calculations and payback, but, in general, it lacks depth and quality without specialized input and preparation. A significant quality improvement was found between the tests with 2023 and 2024 AI versions. Open-access AI proves capable of enhancing renovation diagnostics but remains a complement rather than a replacement for building renovation expert judgment. This research underscores the potential of mainstream AI to democratize access to knowledge, albeit with limitations tied to its dependence on quality inputs and contextual expertise. © 2025 by the authors.es
dc.language.isoenges
dc.publisherMultidisciplinary Digital Publishing Institute (MDPI)es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.titleCan ChatGPT AI Replace or Contribute to Experts’ Diagnosis for Renovation Measures Identification?es
dc.typearticle
dc.identifier.doi10.3390/buildings15030421
dc.identifier.urlhttps://www.scopus.com/results/results.uri?sort=plf-f&src=s&sid=b6ad86cf9ff00f720c761c167670d858&sot=a&sdt=a&sl=19&s=AU-ID%28+57192984665%29&origin=searchadvanced&editSaveSearch=&txGid=e7fa303205799331e3c356eeb01cddc9&sessionSearchId=b6ad86cf9ff00f720c761c167670d858&limit=200
dc.issue.number3es
dc.journal.titleBuildingses
dc.rights.accessRightsopenAccesses
dc.subject.keywordInteligencia Artificiales
dc.subject.keywordCálculo de costeses
dc.subject.keywordMaterial sosteniblees
dc.subject.keywordMaterial compuestoes
dc.subject.keywordAcústicaes
dc.subject.unesco1203.04 Inteligencia Artificiales
dc.subject.unesco3305 Tecnología de la Construcciónes
dc.subject.unesco3322 Tecnología Energéticaes
dc.subject.unesco3308 Ingeniería y Tecnología del Medio Ambientees
dc.subject.unesco3312 Tecnología de Materialeses
dc.subject.unesco2211.02 Materiales Compuestoses
dc.subject.unesco2201.02 Acústica Arquitectónicaes
dc.volume.number15


Files in this item

FilesSizeFormatView

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record