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dc.contributor.authorFraga-Lamas, Paula
dc.contributor.authorLópez Iturri, Peio
dc.contributor.authorCelaya-Echarri, Mikel
dc.contributor.authorBlanco, Óscar
dc.contributor.authorAzpilicueta, Leyre
dc.contributor.authorVarela-Barbeito, José
dc.contributor.authorFalcone, Francisco
dc.contributor.authorFernández-Caramés, Tiago M.
dc.date.accessioned2020-03-31T14:54:22Z
dc.date.available2020-03-31T14:54:22Z
dc.date.issued2020-03-04
dc.identifier.citationP. Fraga-Lamas et al., "Design and Empirical Validation of a Bluetooth 5 Fog Computing Based Industrial CPS Architecture for Intelligent Industry 4.0 Shipyard Workshops," in IEEE Access, vol. 8, pp. 45496-45511, 2020.es_ES
dc.identifier.issn2169-3536
dc.identifier.urihttp://hdl.handle.net/2183/25281
dc.description.abstract[Abstract] Navantia, one of largest European shipbuilders, is creating a fog computing based Industrial Cyber-Physical System (ICPS) for monitoring in real-time its pipe workshops in order to track pipes and keep their traceability. The deployment of the ICPS is a unique industrial challenge in terms of communications, since in a pipe workshop there is a significant number of metallic objects with heterogeneous typologies. There are multiple technologies that can be used to track pipes, but this article focuses on Bluetooth 5, which is a relatively new technology that represents a cost-effective solution to cope with harsh environments, since it has been significantly enhanced in terms of low power consumption, range, speed and broadcasting capacity. Thus, it is proposed a Bluetooth 5 fog computing based ICPS architecture that is designed to support physically-distributed and low-latency Industry 4.0 applications that off-load network traffic and computational resources from the cloud. In order to validate the proposed ICPS design, one of the Navantia’s pipe workshops was modeled through an in-house developed 3D-ray launching radio planning simulator that allows for estimating the coverage provided by the deployed Bluetooth 5 fog computing nodes and Bluetooth 5 tags. The experiments described in this article show that the radio propagation results obtained by the simulation tool are really close to the ones obtained through empirical measurements. As a consequence, the simulation tool is able to reduce ICPS design and deployment time and provide guidelines to future developers when deploying Bluetooth 5 fog computing nodes and tags in complex industrial scenarios.es_ES
dc.description.sponsorshipAuto-ID for Intelligent Products research line of the Navantia-UDC Joint Research Unit (Grant Number: IN853B-2018/02) 10.13039/100014440-Ministerio de Ciencia, Innovaci??n y Universidades (Grant Number: RTI2018-095499-B-C31)es_ES
dc.language.isoenges_ES
dc.publisherInstitute of Electrical and Electronics Engineerses_ES
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095499-B-C31/ES/IMPLEMENTACION DE ENTORNOS CONTEXTUALES INTERACTIVOS, CONECTADOS Y SEGUROS PARA EL TRANSPORTE FERROVIARIO DE PASAJEROS APOYADOS EN LA IOT Y TECNICAS DE SOFT COMPUTING
dc.relationinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/RTI2018-095499-B-C31/ES/IMPLEMENTACION DE ENTORNOS CONTEXTUALES INTERACTIVOS, CONECTADOS Y SEGUROS PARA EL TRANSPORTE FERROVIARIO DE PASAJEROS APOYADOS EN LA IOT Y TECNICAS DE SOFT COMPUTING
dc.relation.urihttps://doi.org/10.1109/ACCESS.2020.2978291es_ES
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)
dc.rightsAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectIndustry 4.0es_ES
dc.subjectIIoTes_ES
dc.subjectCyber-physical systemes_ES
dc.subjectICPSes_ES
dc.subjectFog computinges_ES
dc.subjectEdge computinges_ES
dc.subjectShipyard 4.0es_ES
dc.subjectBluetooth 5es_ES
dc.subjectLP-WANes_ES
dc.subject3D ray launchinges_ES
dc.titleDesign and Empirical Validation of a Bluetooth 5 Fog Computing Based Industrial CPS Architecture for Intelligent Industry 4.0 Shipyard Workshopses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.rights.accessinfo:eu-repo/semantics/openAccesses_ES
UDC.journalTitleIEEE Accesses_ES
UDC.volume8es_ES
UDC.startPage45496es_ES
UDC.endPage45511es_ES
dc.identifier.doi10.1109/ACCESS.2020.2978291


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