{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T03:55:56Z","timestamp":1772769356521,"version":"3.50.1"},"reference-count":51,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2025,7,6]],"date-time":"2025-07-06T00:00:00Z","timestamp":1751760000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"FCT\/MCTES through national funds (PIDDAC) under the R&amp;D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE)","award":["UIDB\/04029\/2020"],"award-info":[{"award-number":["UIDB\/04029\/2020"]}]},{"name":"FCT\/MCTES through national funds (PIDDAC) under the R&amp;D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE)","award":["LA\/P\/0112\/2020"],"award-info":[{"award-number":["LA\/P\/0112\/2020"]}]},{"name":"FCT\/MCTES through national funds (PIDDAC) under the R&amp;D Unit Institute for Sustainability and Innovation in Structural Engineering (ISISE)","award":["2020.07164.BD"],"award-info":[{"award-number":["2020.07164.BD"]}]},{"name":"Associate Laboratory Advanced Production and Intelligent Systems ARISE","award":["UIDB\/04029\/2020"],"award-info":[{"award-number":["UIDB\/04029\/2020"]}]},{"name":"Associate Laboratory Advanced Production and Intelligent Systems ARISE","award":["LA\/P\/0112\/2020"],"award-info":[{"award-number":["LA\/P\/0112\/2020"]}]},{"name":"Associate Laboratory Advanced Production and Intelligent Systems ARISE","award":["2020.07164.BD"],"award-info":[{"award-number":["2020.07164.BD"]}]},{"DOI":"10.13039\/501100001871","name":"national funds through FCT\u2014Foundation for Science and Technology","doi-asserted-by":"publisher","award":["UIDB\/04029\/2020"],"award-info":[{"award-number":["UIDB\/04029\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"national funds through FCT\u2014Foundation for Science and Technology","doi-asserted-by":"publisher","award":["LA\/P\/0112\/2020"],"award-info":[{"award-number":["LA\/P\/0112\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001871","name":"national funds through FCT\u2014Foundation for Science and Technology","doi-asserted-by":"publisher","award":["2020.07164.BD"],"award-info":[{"award-number":["2020.07164.BD"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The long-term preservation of heritage structures relies on effective Structural Health Monitoring (SHM) systems, where sensor placement is key to ensuring early damage detection and guiding conservation efforts. Optimal Sensor Placement (OSP) methods offer a systematic framework to identify efficient sensor configurations, yet their application in historical buildings remains limited. Typically, OSP is driven by numerical models; however, in the context of heritage structures, these models are often affected by substantial uncertainties due to irregular geometries, heterogeneous materials, and unknown boundary conditions. In this scenario, data-driven approaches become particularly attractive as they eliminate the need for potentially unreliable models by relying directly on experimentally identified dynamic properties. This study investigates how the choice of input data influences OSP outcomes, using the Church of Santa Ana in Seville, Spain, as a representative case. Three data sources are considered: an uncalibrated numerical model, a calibrated model, and a data-driven set of modal parameters. Several OSP methods are implemented and systematically compared. The results underscore the decisive impact of the input data on the optimisation process. Although calibrated models may improve certain modal parameters, they do not necessarily translate into better sensor configurations. This highlights the potential of data-driven strategies to enhance the robustness and applicability of SHM systems in the complex and uncertain context of heritage buildings.<\/jats:p>","DOI":"10.3390\/s25134212","type":"journal-article","created":{"date-parts":[[2025,7,7]],"date-time":"2025-07-07T04:43:37Z","timestamp":1751863417000},"page":"4212","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Optimising Sensor Placement in Heritage Buildings: A Comparison of Model-Based and Data-Driven Approaches"],"prefix":"10.3390","volume":"25","author":[{"given":"Estefan\u00eda","family":"Chaves","sequence":"first","affiliation":[{"name":"Advanced Production and Intelligent Systems Associated Laboratory, Institute for Sustainability and Innovation in Structural Engineering, Department of Civil Engineering, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8377-8149","authenticated-orcid":false,"given":"Alberto","family":"Barontini","sequence":"additional","affiliation":[{"name":"Department of Engineering and Geology, University \u201cG. d\u2019Annunzio\u201d of Chieti-Pescara, 65127 Pescara, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1796-686X","authenticated-orcid":false,"given":"Nuno","family":"Mendes","sequence":"additional","affiliation":[{"name":"Advanced Production and Intelligent Systems Associated Laboratory, Institute for Sustainability and Innovation in Structural Engineering, Department of Civil Engineering, University of Minho, 4800-058 Guimar\u00e3es, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6478-1833","authenticated-orcid":false,"given":"V\u00edctor","family":"Comp\u00e1n","sequence":"additional","affiliation":[{"name":"Department of Building Structures and Geotechnical Engineering, University of Seville, 41012 Seville, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2025,7,6]]},"reference":[{"key":"ref_1","unstructured":"Ramos, L.F., De Roeck, G., Louren\u00e7o, P.B., and Campos-Costa, A. 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