Fog Computing en el contexto de Smart Home, asistente de voz y el futuro de IoT

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dc.contributor.authorPinzón Castellanos, Javierspa
dc.contributor.authorCadena Carter, Miguel Antoniospa
dc.contributor.cvlacPinzón Castellanos, Javier [0000045298]spa
dc.contributor.cvlacCadena Carter, Miguel Antonio [0000068845]spa
dc.contributor.googlescholarPinzón Castellanos, Javier [s0csHZMAAAAJ]spa
dc.contributor.linkedinCadena Carter, Miguel Antonio [miguel-antonio-cadena-carter-17553215]
dc.contributor.orcidPinzón Castellanos, Javier [0000-0003-3956-5749]spa
dc.contributor.orcidCadena Carter, Miguel Antonio [0000-0002-0159-4889]spa
dc.contributor.researchgatePinzón Castellanos, Javier [Javier-Pinzon-Castellanos]spa
dc.date.accessioned2020-10-27T00:19:53Z
dc.date.available2020-10-27T00:19:53Z
dc.date.issued2020-06-01
dc.description.abstractFog Computing es la capa de computacien distribuida mss proxima al usuario. Una arquitectura fog exitosa permite reducir el rerardo o latencia y aumenta la eficiencia. En este articulo se expone el desarrollo e implementación de una arquitectura de computation distribuida, aplicada a un entomo de automatización que aprovecha el Fog Computing como intermediario con la capa de computación en la nube. El estudio utilice una plata de desarrollo Raspberry Pi V3 conecrada a elementos finales de control como servomotor y reles, indicadores y sensores térmicos. Todo controlado por un framework de automatization que recibe las erdenes de Sid, las cuales son ejecutadas por medio de instrucciones previamente determinadas. La conexión a la nube se beneficia al reducirse el envió de datos ya que ahora solo se recibe la información relevante pare su análisis.spa
dc.description.abstractenglishFog Computing is the distributed computing layer closest to the user. A successful fog architecture reduces delay or latency and increases efficiency. This article exposes the development and implementation of a distributed computing architecture, applied to an automation environment that takes advantage of Fog Computing as an intermediary with the cloud computing layer. The study uses a Raspberry Pi V3 development platform connected to final control elements such as servomotor and relays, indicators and thermal sensors. All controlled by an automation framework that receives Sid's orders, which are executed by means of previously determined instructions. The connection to the cloud benefits by reducing the sending of data since now only the relevant information is received for its analysis.eng
dc.format.mimetypeapplication/pdfspa
dc.identifier.doi10.29375/25392115.3894
dc.identifier.instnameinstname:Universidad Autónoma de Bucaramanga UNABspa
dc.identifier.issn2539-2115
dc.identifier.issn1657-2831
dc.identifier.repourlrepourl:https://repository.unab.edu.co
dc.identifier.urihttp://hdl.handle.net/20.500.12749/8818
dc.language.isoengspa
dc.publisherUniversidad Autónoma de Bucaramanga UNAB
dc.relationhttps://revistas.unab.edu.co/index.php/rcc/article/view/3894/3248
dc.relation/*ref*/Artono, B., & Susanto, F. (2017). LED control system with cayenne framework for the Internet of Things (IoT). JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering), 2(1), 95–100.
dc.relation/*ref*/Bakhshi, Z., Rodriguez-Navas, G., & Hansson, H. (2019). Dependable Fog Computing: A Systematic Literature Review. 2019 45th Euromicro Conference on Software Engineering and Advanced Applications (SEAA), 395–403. https://doi.org/10.1109/SEAA.2019.00066
dc.relation/*ref*/Homekit. (2016). Retrieved January 2, 2017, from https://www.domoticz.com/wiki/Homekit_Siri
dc.relation/*ref*/Iorga, M., Feldman, L., Barton, R., Martin, M. J., Goren, N. S., & Mahmoudi, C. (2018). Fog Computing Conceptual Model. Retrieved from https://www.nist.gov/publications/fog-computing-conceptual-model
dc.relation/*ref*/IoT Eclipse. (2019). IoT Developer Survey. Retrieved from Eclipse Foundation website: https://iot.eclipse.org/resources/iot-developer-survey/iot-developer-survey-2019.pdf
dc.relation/*ref*/Isa, I. S. M., Musa, M. O. I., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2019). Energy Efficient and Resilient Infrastructure for Fog Computing Health Monitoring Applications. 2019 21st International Conference on Transparent Optical Networks (ICTON), 1–5. https://doi.org/10.1109/ICTON.2019.8840438
dc.relation/*ref*/Skala, K., Davidovic, D., Afgan, E., Sovic, I., & Sojat, Z. (2015). Scalable distributed computing hierarchy: Cloud, fog and dew computing. Open Journal of Cloud Computing (OJCC), 2(1), 16–24.
dc.relation/*ref*/Tsigkanos, C., Avasalcai, C., & Dustdar, S. (2019). Architectural Considerations for Privacy on the Edge. IEEE Internet Computing, 23(4), 76–83. https://doi.org/10.1109/MIC.2019.2935800
dc.relation/*ref*/Wang, X., Gu, B., Ren, Y., Ye, W., Yu, S., Xiang, Y., & Gao, L. (2019). A Fog-based Recommender System. IEEE Internet of Things Journal, 1–1. https://doi.org/10.1109/JIOT.2019.2949029
dc.relation/*ref*/Wei, X., & Wu, L. (2019). A New Proposed Sensor Cloud Architecture Based on Fog Computing for Internet of Things. 2019 International Conference on Internet of Things (IThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 615–620. https://doi.org/10.1109/iThings/GreenCom/CPSCom/SmartData.2019.00120
dc.relation/*ref*/Zhang, T., Jin, J., Zheng, X., & Yang, Y. (2019). Rate Adaptive Fog Service Platform for Heterogeneous IoT Applications. IEEE Internet of Things Journal, 1–1. https://doi.org/10.1109/JIOT.2019.2945328
dc.relation.referencesArtono, B., & Susano, E (2017). LED control system with cayenne framework for the Internet of Things (loT). JEECAE (Journal of Electrical, Electronics, Control, and Automotive Engineering), 2(1), 95-100.spa
dc.relation.referencesBakhshi, Z., Rodriguez-Navas, G., & Hansson, H. (2019). Dependable Fog Computing: A Systematic Literature Review. 2019 45th Euromicro Conference on Software Engineering and AdwincetI Applications (SEAA), 395-403. https://doi.org/10.1109/SEAA.2019.00066
dc.relation.referencesHomekit. (2016). Retrieved January 2, 2017, from https://www.domoticz.com/wiki/Homekit_Siri
dc.relation.referenceslorga, M., Feldman, L., Barton, R., Martin, M. J., Goren, N. S., & Mahmoudi, C. (2018). Fog Computing Conceptual Model. Retrieved from https:/hvww.nist.gov/publication.s/fog-computing-conceptual-model
dc.relation.referencesloT Eclipse. (2019). loT Developer Survey. Retrieved from Eclipse Foundation website: https://ioteclipse.org/ resourcestiot-developer-survey/iot-develoFer-survey-2019.pdf
dc.relation.referencesIsa, 1. S. M., Musa, M. 0. I., El-Gorashi, T. E. H., & Elmirghani, J. M. H. (2019). Energy Efficient and Resilient Infrastructure for Fog Computing Health Monitoring Applications. 2019 2131 International Conference on Transparent Optical Nenionts (ICTON), 1-5. https://doi.org/10.1109/ICTON.2019.8840438
dc.relation.referencesSkala, K., Davidovic, D., Afgan, E., Sovic,1., & Soja Z. (2015). Scalable distributed computing hierarchy: Cloud, fog and dew computing. Open Journal of Cloud Computing (0,ICC), 2(1), 16-24.
dc.relation.referencesTsigkanos, C., Avasalcai, C., & Dustdar, S. (2019). Architectural Considerations for Privacy on the Edge. IEEE Internes Computing, 23(4), 76-83. https://doi.org/10.1109/MIC.2019.2935800
dc.relation.referencesWang, X., Gu, B., Ren, Y., Ye, W., Yu, S., Xiang, Y., & Gao, L. (2019). A Fog-based Recommender System. IEEE Internes of Things Journal, 1-1. https://doi.m/10.1109/.110T.2019.2949029
dc.relation.referencesWei, X., & Wu, L. (2019). A New Proposed Sensor Cloud Architecture Basad on Fog Computing for Internet of Things. 2019 International Conference on Internet of Things (IThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cybeh Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 615-620. https://doi.org/10.1109/iThings/GreenCom/CPSCom/ SmartData.2019.00120
dc.relation.referencesZhang, T., Jin, J., Zheng, X., & Yang, Y. (2019). Rate Adaptive Fog Service Platform for Heterogeneous loT Applications. WEE Internes of Things Journa1,1-1.httpsildoi.org110.1109310T.2019.2945328
dc.relation.urihttps://revistas.unab.edu.co/index.php/rcc/article/view/3894
dc.rightsDerechos de autor 2020 Revista Colombiana de Computación
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.rights.creativecommonsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.5/co/
dc.sourceRevista Colombiana de Computación; Vol. 21 Núm. 1 (2020): Revista Colombiana de Computación; 6-12
dc.subjectFog Computing
dc.subjectCloud Computing
dc.subjectInternet de las Cosas
dc.subjectComputación distribuida
dc.subjectCasa inteligente
dc.subject.keywordsFog Computingeng
dc.subject.keywordsCloud Computingeng
dc.subject.keywordsInternet of Thingseng
dc.subject.keywordsDistributed Computingeng
dc.subject.keywordsSmart homeeng
dc.subject.keywordsTechnological innovationseng
dc.subject.keywordsComputer scienceeng
dc.subject.keywordsTechnology developmenteng
dc.subject.keywordsSystems engineeringeng
dc.subject.keywordsInvestigationseng
dc.subject.keywordsInformation and communication technologieseng
dc.subject.lembInnovaciones tecnológicasspa
dc.subject.lembCiencias de la computaciónspa
dc.subject.lembIngeniería de sistemasspa
dc.subject.lembInvestigacionesspa
dc.subject.lembTecnologías de la información y la comunicaciónspa
dc.subject.proposalInternet de las cosasspa
dc.subject.proposalComputación distribuidaspa
dc.subject.proposalCasa inteligentespa
dc.subject.proposalDesarrollo tecnológicospa
dc.titleFog Computing en el contexto de Smart Home, asistente de voz y el futuro de IoTspa
dc.title.translatedFog Computing in the context of Smart Home, voice assistant and the future of IoTeng
dc.type.coarhttp://purl.org/coar/resource_type/c_7a1f
dc.type.driverinfo:eu-repo/semantics/article
dc.type.hasversioninfo:eu-repo/semantics/acceptedVersion
dc.type.localArtículospa
dc.type.redcolhttp://purl.org/redcol/resource_type/CJournalArticle

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