RadonFAN data

[Description of methods used for collection/generation of data] Through radon sensors, Raspberry Pi as control hub, ThingSpeak as could platform.

Detalles Bibliográficos
Autores: Abad Azcutia, Lidia, Ramonet Marques, Fernando, González Hernández, Margarita, Anaya Velayos, José Javier, Aparicio Secanellas, Sofía
Tipo de recurso: conjunto de datos
Fecha de publicación:2025
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/410979
Acceso en línea:http://hdl.handle.net/10261/410979
https://doi.org/10.20350/digitalCSIC/17830
Access Level:acceso abierto
Palabra clave:Indoor radon
Time series
Indoor air quality
IoT data
Long-term monitoring
Low-cost sensors
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spelling RadonFAN dataRadonFAN - Intelligent Real-Time Radon Mitigation through IoT, Rule-Based Logic, and AI ForecastingAbad Azcutia, LidiaRamonet Marques, FernandoGonzález Hernández, MargaritaAnaya Velayos, José JavierAparicio Secanellas, SofíaIndoor radonTime seriesIndoor air qualityIoT dataLong-term monitoringLow-cost sensors[Description of methods used for collection/generation of data] Through radon sensors, Raspberry Pi as control hub, ThingSpeak as could platform.[Methods for processing the data] Timestamp alignment, missing-value imputation (kNN), smoothing, and normalization as described in the associated publication.The dataset contains long-term indoor radon (Rn-222) measurements collected by the RadonFAN system in two underground galleries at ITEFI-CSIC (Madrid, Spain). Data were recorded every 10 minutes from October 2019 to December 2024 using low-cost radon sensors integrated into an IoT infrastructure. The dataset includes over 74,000 samples for Gallery 1 and 57,000 samples for Gallery 2, exhibiting different temporal dynamics: Gallery 1 shows relatively stable behavior, while Gallery 2 presents higher variability and faster radon increases. The dataset is designed for time-series classification, focusing on the anticipation of radon threshold exceedances for preventive ventilation control.Grant RPID2024-159276OB-C41 funded by MICIU/AEI/10.13039/501100011033 and by ERDF/EU.File List: RG1 for Gallery 1 and RG2 for Gallery 2.Peer reviewedDIGITAL.CSICMinisterio de Ciencia, Innovación y Universidades (España)Agencia Estatal de Investigación (España)European CommissionGonzález Hernández, Margarita [0000-0002-0304-1612]Anaya Velayos, José Javier [0000-0003-2415-471X]Aparicio Secanellas, Sofía [0000-0003-4069-015X]Abad Azcutia, Lidia [lidia.abad@csic.es]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202520252025info:eu-repo/semantics/datasethttp://purl.org/coar/resource_type/c_ddb1pthttp://hdl.handle.net/10261/410979https://doi.org/10.20350/digitalCSIC/17830reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)Inglés#PLACEHOLDER_PARENT_METADATA_VALUE#info:eu-repo/grantAgreement/AEI//PID2024-159276OB-C41Abad, L.; Ramonet, F.; González, M.; Anaya, J.J.; Aparicio,S. RadonFAN: Intelligent Real-Time Radon Mitigation through IoT, Rule-Based Logic, and AI Forecasting. https://doi.org/10.3390/ai7020067. http://hdl.handle.net/10261/421498Abad Azcutia, Lidia; Ramonet Marques, Fernando; González Hernández, Margarita; Anaya Velayos, José Javier; Aparicio Secanellas, Sofía; 2025; RadonFAN code [Software]; DIGITAL.CSIC; https://doi.org/10.20350/digitalCSIC/17831https://github.com/lidiaabad/RadonFAN-Intelligent-Real-Time-Radon-Mitigation-through-IoT-Rule-Based-Logic-and-AI-ForecastingSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/4109792026-05-22T06:33:51Z
dc.title.none.fl_str_mv RadonFAN data
RadonFAN - Intelligent Real-Time Radon Mitigation through IoT, Rule-Based Logic, and AI Forecasting
title RadonFAN data
spellingShingle RadonFAN data
Abad Azcutia, Lidia
Indoor radon
Time series
Indoor air quality
IoT data
Long-term monitoring
Low-cost sensors
title_short RadonFAN data
title_full RadonFAN data
title_fullStr RadonFAN data
title_full_unstemmed RadonFAN data
title_sort RadonFAN data
dc.creator.none.fl_str_mv Abad Azcutia, Lidia
Ramonet Marques, Fernando
González Hernández, Margarita
Anaya Velayos, José Javier
Aparicio Secanellas, Sofía
author Abad Azcutia, Lidia
author_facet Abad Azcutia, Lidia
Ramonet Marques, Fernando
González Hernández, Margarita
Anaya Velayos, José Javier
Aparicio Secanellas, Sofía
author_role author
author2 Ramonet Marques, Fernando
González Hernández, Margarita
Anaya Velayos, José Javier
Aparicio Secanellas, Sofía
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Ministerio de Ciencia, Innovación y Universidades (España)
Agencia Estatal de Investigación (España)
European Commission
González Hernández, Margarita [0000-0002-0304-1612]
Anaya Velayos, José Javier [0000-0003-2415-471X]
Aparicio Secanellas, Sofía [0000-0003-4069-015X]
Abad Azcutia, Lidia [lidia.abad@csic.es]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Indoor radon
Time series
Indoor air quality
IoT data
Long-term monitoring
Low-cost sensors
topic Indoor radon
Time series
Indoor air quality
IoT data
Long-term monitoring
Low-cost sensors
description [Description of methods used for collection/generation of data] Through radon sensors, Raspberry Pi as control hub, ThingSpeak as could platform.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025
2025
dc.type.none.fl_str_mv info:eu-repo/semantics/dataset
http://purl.org/coar/resource_type/c_ddb1
format dataset
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/410979
https://doi.org/10.20350/digitalCSIC/17830
url http://hdl.handle.net/10261/410979
https://doi.org/10.20350/digitalCSIC/17830
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv #PLACEHOLDER_PARENT_METADATA_VALUE#
info:eu-repo/grantAgreement/AEI//PID2024-159276OB-C41
Abad, L.; Ramonet, F.; González, M.; Anaya, J.J.; Aparicio,S. RadonFAN: Intelligent Real-Time Radon Mitigation through IoT, Rule-Based Logic, and AI Forecasting. https://doi.org/10.3390/ai7020067. http://hdl.handle.net/10261/421498
Abad Azcutia, Lidia; Ramonet Marques, Fernando; González Hernández, Margarita; Anaya Velayos, José Javier; Aparicio Secanellas, Sofía; 2025; RadonFAN code [Software]; DIGITAL.CSIC; https://doi.org/10.20350/digitalCSIC/17831
https://github.com/lidiaabad/RadonFAN-Intelligent-Real-Time-Radon-Mitigation-through-IoT-Rule-Based-Logic-and-AI-Forecasting
Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv pt
dc.publisher.none.fl_str_mv DIGITAL.CSIC
publisher.none.fl_str_mv DIGITAL.CSIC
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,198674

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