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MIS-IoT: Modular Intelligent Server Based Internet of Things Framework with Big Data and Machine Learning

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dc.contributor.author Önal, Aras Can
dc.contributor.author Sezer, Ömer Berat
dc.contributor.author Özbayoğlu, Murat
dc.contributor.author Doğdu, Erdoğan
dc.date.accessioned 2020-04-13T13:37:08Z
dc.date.available 2020-04-13T13:37:08Z
dc.date.issued 2018
dc.identifier.issn 2639-1589
dc.identifier.uri http://hdl.handle.net/20.500.12416/3096
dc.description.abstract Internet of Things world is getting bigger everyday with new developments in all fronts. The new IoT world requires better handling of big data and better usage with more intelligence integrated in all phases. Here we present MIS-IoT (Modular Intelligent Server Based Internet of Things Framework with Big Data and Machine Learning) framework, which is "modular" and therefore open for new extensions, "intelligent" by providing machine learning and deep learning methods on "big data" coming from IoT objects, "server-based" in a service-oriented way by offering services via standart Web protocols. We present an overview of the design and implementation details of MIS-IoT along with a case study evaluation of the system, showing the intelligence capabilities in anomaly detection over real-time weather data. tr_TR
dc.language.iso eng tr_TR
dc.publisher IEEE tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject Internet of Things tr_TR
dc.subject Machine Learning tr_TR
dc.subject Big Data Analytics tr_TR
dc.title MIS-IoT: Modular Intelligent Server Based Internet of Things Framework with Big Data and Machine Learning tr_TR
dc.type conferenceObject tr_TR
dc.relation.journal 2018 IEEE International Conference On Big Data (Big Data) tr_TR
dc.identifier.startpage 2270 tr_TR
dc.identifier.endpage 2279 tr_TR
dc.contributor.department Çankaya Üniversitesi, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümü tr_TR


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