Use of Edge Computing for Predictive Maintenance of Industrial Electric Motors

dc.contributorFigueroa-Garcia J.C.
dc.contributorDuarte-Gonzalez M.
dc.contributorJaramillo-Isaza S.
dc.contributorOrjuela-Canon A.D.
dc.contributorDiaz-Gutierrez Y.
dc.creatorDe Leon V.
dc.creatorAlcazar Y.
dc.creatorVilla Ramírez, José Luis
dc.date.accessioned2020-03-26T16:33:07Z
dc.date.available2020-03-26T16:33:07Z
dc.date.created2020-03-26T16:33:07Z
dc.date.issued2019
dc.identifierCommunications in Computer and Information Science; Vol. 1052, pp. 523-533
dc.identifier9783030310189
dc.identifier18650929
dc.identifierhttps://hdl.handle.net/20.500.12585/9170
dc.identifier10.1007/978-3-030-31019-6_44
dc.identifierUniversidad Tecnológica de Bolívar
dc.identifierRepositorio UTB
dc.identifier57212008502
dc.identifier57212005233
dc.identifier55498635300
dc.description.abstractIndustrial Internet of Things has become a reality in many kind of industries. In this paper, We explore the case of high quantity of raw data generated by a machine. In the aforementioned case is not viable store and process the data in a traditional Internet of Things architecture. For this case, We use an architecture based on edge computing and Industrial Internet of Things concepts and apply them to a case of machine monitoring for predictive maintenance. The proof of concept shows the potential benefits in real industrial applications. © 2019, Springer Nature Switzerland AG.
dc.languageeng
dc.publisherSpringer
dc.relation16 October 2019 through 18 October 2019
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.rightsAtribución-NoComercial 4.0 Internacional
dc.sourcehttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85075644036&doi=10.1007%2f978-3-030-31019-6_44&partnerID=40&md5=a3ce01c10e2bb04764c4bb875b31115f
dc.source6th Workshop on Engineering Applications, WEA 2019
dc.titleUse of Edge Computing for Predictive Maintenance of Industrial Electric Motors


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