Publicação
A digital twin architecture for real-time supervision of an olive oil production mill
| dc.contributor.author | Scheifer, Hendrick | |
| dc.contributor.author | Jorge, Luísa | |
| dc.contributor.author | Pires, Flávia | |
| dc.contributor.author | Vaz, Clara B. | |
| dc.date.accessioned | 2026-03-26T15:54:43Z | |
| dc.date.available | 2026-03-26T15:54:43Z | |
| dc.date.issued | 2025 | |
| dc.description.abstract | The food processing industry is a highly complex sector that is increasingly embracing Industry 4.0 technologies, such as Cyber-Physical Systems, Artificial Intelligence, the Internet of Things, and Digital Twins (DTs), to enhance efficiency, quality, and sustainability. While DTs have demonstrated promising results in industries like dairy, beverages, and chocolate, their implementation in olive oil production remains limited. Key challenges include the need to create models adaptable to different device categories and the lack of standardized methods for capturing and transferring data between physical assets and their virtual counternarts. This work proposes a scalable architecture, based on ISO 23247, for developing DTs that support decision-making, 3D visualization, and simulation. The architecture was experimen-tally validated through a case study of an olive oil production mill where a DT was implemented. The resulting application integrated essential features such as data- and event-driven production monitoring for rapid anomaly detection, as well as digital model management to ensure the DT evolved in step with changes in the physical system's infrastructure. | eng |
| dc.description.sponsorship | This work was supported by Plano de Recuperação e Resiliência, within the project “SustainOlive”, PRR-C05-i03-I-000187. The authors are also grateful to the Foundation for Science and Technology (FCT, Portugal) for financial support through national funds: UID/05757 - Research Centre in Digitalization and Intelligent Robotics (CeDRI); and SusTEC, LA/P/0007/2020 (DOI: 10.54499/LA/P/0007/2020). | |
| dc.identifier.citation | Scheifer, Hendrick; Jorge, Luísa; Pires, Flávia; Vaz, Clara B. (2025). A digital twin architecture for real-time supervision of an olive oil production mill. In 12th International Conference on Internet of Things: Systems, Management and Security (IOTSMS). Lyon, France. ISSN 2832-3033. DOI: 10.1109/IOTSMS68530.2025.11408590 | |
| dc.identifier.doi | 10.1109/IOTSMS68530.2025.11408590 | |
| dc.identifier.issn | 2832-3033 | |
| dc.identifier.uri | http://hdl.handle.net/10198/36327 | |
| dc.language.iso | eng | |
| dc.peerreviewed | yes | |
| dc.publisher | IEEE | |
| dc.relation | Associate Laboratory for Sustainability and Tecnology in Mountain Regions | |
| dc.relation.hasversion | https://ieeexplore.ieee.org/abstract/document/11408590 | |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | Digital Twin | |
| dc.subject | Monitoring | |
| dc.subject | Olivel Oil Mill | |
| dc.subject | Industrial IoT | |
| dc.subject | Industry 4.0 | |
| dc.title | A digital twin architecture for real-time supervision of an olive oil production mill | por |
| dc.type | conference proceedings | |
| dspace.entity.type | Publication | |
| oaire.awardNumber | LA/P/0007/2020 | |
| oaire.awardTitle | Associate Laboratory for Sustainability and Tecnology in Mountain Regions | |
| oaire.awardURI | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/LA%2FP%2F0007%2F2020/PT | |
| oaire.citation.conferenceDate | 2025 | |
| oaire.citation.conferencePlace | Lyon, France | |
| oaire.citation.title | 12th International Conference on Internet of Things: Systems, Management and Security (IOTSMS) | |
| oaire.fundingStream | 6817 - DCRRNI ID | |
| oaire.version | http://purl.org/coar/version/c_ab4af688f83e57aa | |
| person.familyName | Jorge | |
| person.familyName | Vaz | |
| person.givenName | Luísa | |
| person.givenName | Clara B. | |
| person.identifier | R-001-FQC | |
| person.identifier.ciencia-id | AB16-0263-87CB | |
| person.identifier.ciencia-id | 9611-3386-E516 | |
| person.identifier.orcid | 0000-0002-0623-7282 | |
| person.identifier.orcid | 0000-0001-9862-6068 | |
| person.identifier.rid | F-5156-2014 | |
| person.identifier.rid | F-1519-2016 | |
| person.identifier.scopus-author-id | 22134881600 | |
| person.identifier.scopus-author-id | 56352045500 | |
| project.funder.identifier | http://doi.org/10.13039/501100001871 | |
| project.funder.name | Fundação para a Ciência e a Tecnologia | |
| relation.isAuthorOfPublication | 103e1f8c-bbdc-4ea3-a014-7b3b69ae5a00 | |
| relation.isAuthorOfPublication | 34bc350c-28d9-4b06-9874-b2b0dba58d1d | |
| relation.isAuthorOfPublication.latestForDiscovery | 103e1f8c-bbdc-4ea3-a014-7b3b69ae5a00 | |
| relation.isProjectOfPublication | 6255046e-bc79-4b82-8884-8b52074b4384 | |
| relation.isProjectOfPublication.latestForDiscovery | 6255046e-bc79-4b82-8884-8b52074b4384 |
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