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dc.contributor.authorÖztürk, Mehmet 
dc.date.accessioned2020-11-19T13:01:03Z
dc.date.available2020-11-19T13:01:03Z
dc.date.issued2020
dc.identifier.citationOzturh. M. (2020). A deep tech architecture for intelligent IoT systems. En Sara Rodríguez González, Fernando de la Prieta Pintado, José Alberto García Coria, Roberto Casado Vara (eds.) The role of artificial intelligence and distributed computing in IOT Applications, pp. 41-54es_ES
dc.identifier.urihttp://hdl.handle.net/10366/144157
dc.description.abstract[EN]The increase in the number of connected devices on the Internet of Things (IoT), interactions and the amount of data raises a number of issues. Two major problems are limitations in terms of network latency and bandwidth. While cloud-based infrastructures give us access to scalable, on-demand storage and processing services that can scale to the requirements of the Internet of Things (IoT), these centralized resources can create unacceptable delays and performance problems for devices that have latency-sensitive applications, such as health monitoring and emergency response applications. This article has been created for the PhD thesis that aims to create a deep tech architecture for intelligent IoT systems.es_ES
dc.language.isoenges_ES
dc.publisherEdiciones Universidad de Salamanca (España)es_ES
dc.relation.ispartofhttps://gredos.usal.es/handle/10366/147206
dc.relation.ispartofseriesAquilafuente;287
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectEdge Computinges_ES
dc.subjectMachine Learninges_ES
dc.subjectDeep Teches_ES
dc.subjectInternet of Thingses_ES
dc.subjectIoTes_ES
dc.titleA deep tech architecture for intelligent IoT systemses_ES
dc.typeinfo:eu-repo/semantics/bookPartes_ES
dc.relation.publishversionhttps://doi.org/10.14201/0AQ02874154
dc.subject.unesco1203.17 Informáticaes_ES
dc.identifier.doi10.14201/0AQ02874154
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES


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