Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/2664
Full metadata record
DC FieldValueLanguage
dc.contributor.authorÖnal, Aras Can-
dc.contributor.authorSezer, Ömer Berat-
dc.contributor.authorÖzbayoğlu, Murat-
dc.contributor.authorDoğdu, Erdoğan-
dc.date.accessioned2019-12-25T14:02:00Z
dc.date.available2019-12-25T14:02:00Z
dc.date.issued2019-01
dc.identifier.citationOnal, A. C., Sezer, O. B., Ozbayoglu, M., and Dogdu, E. (2018, December). MIS-IoT: Modular Intelligent Server Based Internet of Things Framework with Big Data and Machine Learning. In 2018 IEEE International Conference on Big Data (Big Data) (pp. 2270-2279). IEEE.en_US
dc.identifier.isbn9.78154E+12
dc.identifier.urihttps://ieeexplore.ieee.org/document/8622247-
dc.identifier.urihttps://hdl.handle.net/20.500.11851/2664-
dc.description2018 IEEE International Conference on Big Data (2018: Seattle, WA)
dc.description.abstractInternet 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. © 2018 IEEE.en_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartofProceedings - 2018 IEEE International Conference on Big Data, Big Data 2018en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectInternet of thingsen_US
dc.subjectmachine learningen_US
dc.subjectbig data analyticsen_US
dc.subjectanomaly detectionen_US
dc.subjectfault detectionen_US
dc.titleMis-Iot: Modular Intelligent Server Based Internet of Things Framework With Big Data and Machine Learningen_US
dc.typeConference Objecten_US
dc.departmentFaculties, Faculty of Engineering, Department of Computer Engineeringen_US
dc.departmentFakülteler, Mühendislik Fakültesi, Bilgisayar Mühendisliği Bölümütr_TR
dc.identifier.startpage2270
dc.identifier.endpage2279
dc.authorid0000-0001-7998-5735-
dc.identifier.wosWOS:000468499302046en_US
dc.identifier.scopus2-s2.0-85062621180en_US
dc.institutionauthorÖzbayoğlu, Ahmet Murat-
dc.identifier.doi10.1109/BigData.2018.8622247-
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
item.openairetypeConference Object-
item.languageiso639-1en-
item.grantfulltextnone-
item.fulltextNo Fulltext-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
crisitem.author.dept02.1. Department of Artificial Intelligence Engineering-
Appears in Collections:Bilgisayar Mühendisliği Bölümü / Department of Computer Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Show simple item record



CORE Recommender

SCOPUSTM   
Citations

4
checked on Dec 21, 2024

WEB OF SCIENCETM
Citations

4
checked on Dec 21, 2024

Page view(s)

56
checked on Dec 23, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.