Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31246
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dc.contributor.authorCecere, L-
dc.contributor.authorColace, F-
dc.contributor.authorLorusso, A-
dc.contributor.authorMessina, B-
dc.contributor.authorTucker, A-
dc.contributor.authorSantaniello, D-
dc.coverage.spatialSalerno, Italy-
dc.date.accessioned2025-05-15T11:55:24Z-
dc.date.available2025-05-15T11:55:24Z-
dc.date.issued2024-11-08-
dc.identifierORCiD: Allan Tucker https://orcid.org/0000-0001-5105-3506-
dc.identifier.citationCecere, L. et al. (2024) 'IoT and Digital Twin: A new perspective for Cultural Heritage predictive maintenance', Procedia Structural Integrity, 64, pp. 2181 - 2188. doi: 10.1016/j.prostr.2024.09.334.en_US
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/31246-
dc.description.abstractIn the construction sector, the maintenance and monitoring of buildings are of fundamental importance, both in civil and cultural heritage buildings, ensuring their preservation, safety, and proper functioning over time. The preservation of the built heritage is one of the main objectives that a nation must pursue, and thanks to the ever-increasing spread of new technologies, it is possible to apply innovative approaches capable of monitoring in real-time the progressive damage of structures or intercepting sudden situations capable of causing extensive damage. Traditional monitoring methodologies, employed so far, are based on direct inspections and manual data collection, and are often expensive and only sometimes effective. In this scenario, a significant contribution has been made by the Internet of Things (IoT) paradigm, which has made it possible to collect real-time data from sensors placed on the structures to be monitored, thus enabling the implementation of predictive maintenance methodologies. A further contribution to the development of these methodologies has come from the emergence of the concept of the Digital Twin (DT), a digital model of an intended or actual real-world product, system or physical process that serves as an effectively indistinguishable digital counterpart of it for practical purposes such as simulation, integration, testing, monitoring and maintenance. In order to make the DT even more effective, it is possible to link it to the real structure through BIM, i.e. a process applied to existing buildings or monuments that aims not only at the mere restitution of the three-dimensional model but above all at the creation of so-called ‘intelligent models’. The latter is rich in geometric information, including the state of conservation of materials, in which all components are parametric objects with well-defined semantics and can contain all the historical information derived from an adequate documentary analysis. Starting from the above, this paper aims to present a methodology for monitoring an existing building, exploiting innovative technologies based on DT and IoT concepts. The case study analyzed is the Scientific Library of the University of Salerno, and the first results of the experiment are more than satisfactory.en_US
dc.format.extent2181 - 2188-
dc.format.mediumElectronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherElsevieren_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International-
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/-
dc.source7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures, SMAR 2024-
dc.source7th International Conference on Smart Monitoring, Assessment and Rehabilitation of Civil Structures, SMAR 2024-
dc.subjectInternet of Thingsen_US
dc.subjectHBIMen_US
dc.subjectpredictive maintenanceen_US
dc.titleIoT and Digital Twin: A new perspective for Cultural Heritage predictive maintenanceen_US
dc.typeConference Paperen_US
dc.identifier.doihttps://doi.org/10.1016/j.prostr.2024.09.334-
dc.relation.isPartOfProcedia Structural Integrity-
pubs.finish-date2024-09-06-
pubs.finish-date2024-09-06-
pubs.publication-statusPublished-
pubs.start-date2024-09-04-
pubs.start-date2024-09-04-
pubs.volume64-
dc.identifier.eissn2452-3216-
dc.rights.licensehttps://creativecommons.org/licenses/by-nc-nd/4.0/legalcode.en-
dc.rights.holderThe Authors-
Appears in Collections:Dept of Computer Science Research Papers

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