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| dc.contributor.author | Mateo Romero, Héctor Felipe | |
| dc.contributor.author | Hernández Callejo, Luis | |
| dc.contributor.author | González Rebollo, Miguel Ángel | |
| dc.contributor.author | Martínez Sacristán, Óscar | |
| dc.contributor.author | Redondo Plaza, Alberto Gregorio | |
| dc.contributor.author | Amami, Ghada | |
| dc.contributor.author | Alonso Gómez, Víctor | |
| dc.date.accessioned | 2026-04-08T11:41:00Z | |
| dc.date.available | 2026-04-08T11:41:00Z | |
| dc.date.issued | 2026 | |
| dc.identifier.citation | Nesmachnow, S., Hernández Callejo, L. (eds.). Smart Cities. ICSC-CITIES 2025. Communications in Computer and Information Science, vol 2742. Cham: Springer, 2026, p. 3-14 | es |
| dc.identifier.isbn | 978-3-032-19018-5 | es |
| dc.identifier.uri | https://uvadoc.uva.es/handle/10324/83965 | |
| dc.description | Producción Científica | es |
| dc.description.abstract | This work presents a novel database architecture designed to support laboratory-based experimentation with photovoltaic (PV) cells and modules using different kinds of measurements, such as Electroluminescence (EL) Images or Current-Voltage (I-V) curves. The database is implemented in MySQL following established design principles. A web-based application is presented for efficient data insertion and retrieval. The initial population includes over 800 EL images and I–V curves of PV cells, and more than 1100 records of PV modules from diverse installations. This database provides a foundational tool for advancing automated diagnostics, performance analysis, and the integration of Artificial Intelligence in PV research environments. Future work will focus on enhancing the system’s scalability, interoperability, and support for real-time data ingestion and user management. | es |
| dc.format.extent | 12 p. | es |
| dc.format.mimetype | application/pdf | es |
| dc.language.iso | eng | es |
| dc.publisher | Springer | es |
| dc.rights.accessRights | info:eu-repo/semantics/restrictedAccess | es |
| dc.subject.classification | Database | es |
| dc.subject.classification | Photovoltaic | es |
| dc.subject.classification | Electroluminescence | es |
| dc.subject.classification | Machine Learning | es |
| dc.subject.classification | Computer Science | es |
| dc.title | Enhancing Solar Energy Research: A Database Approach for Photovoltaic Laboratories | es |
| dc.type | info:eu-repo/semantics/conferenceObject | es |
| dc.rights.holder | © 2026 The Author(s), under exclusive license to Springer Nature Switzerland AG | es |
| dc.identifier.doi | 10.1007/978-3-032-19019-2_1 | es |
| dc.relation.publisherversion | https://link.springer.com/chapter/10.1007/978-3-032-19019-2_1 | es |
| dc.title.event | 8th Ibero-American Congress of Smart Cities, ICSC-Cities 2025, Puebla, México, November 10–12, 2025 | es |
| dc.description.project | Spanish Ministry of Science, Innovation, and Universities within the framework of the “Plan Estatal de Investigación Científica, Técnica y de Innovación” (project ID: PID2023-148369OB-C43) | es |
| dc.type.hasVersion | info:eu-repo/semantics/acceptedVersion | es |
| dc.subject.unesco | 1203 Ciencia de Los Ordenadores | es |
| dc.subject.unesco | 3306 Ingeniería y Tecnología Eléctricas | es |




