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AuthorDin I.U.
AuthorGuizani M.
AuthorRodrigues J.J.P.C.
AuthorHassan S.
AuthorKorotaev V.V.
Available date2020-04-05T10:53:20Z
Publication Date2019
Publication NameFuture Generation Computer Systems
ResourceScopus
ISSN0167739X
URIhttp://dx.doi.org/10.1016/j.future.2019.04.017
URIhttp://hdl.handle.net/10576/13814
AbstractMachine learning is one of the emerging technologies that has grabbed the attention of academicians and industrialists, and is expected to evolve in the near future. Machine learning techniques are anticipated to provide pervasive connections for wireless nodes. In fact, machine learning paves the way for the Internet of Things (IoT)—a network that supports communications among various devices without human interactions. Machine learning techniques are being utilized in several fields such as healthcare, smart grids, vehicular communications, and so on. In this paper, we study different IoT-based machine learning mechanisms that are used in the mentioned fields among others. In addition, the lessons learned are reported and the assessments are explored viewing the basic aim machine learning techniques are expected to play in IoT networks.
SponsorThis work is supported by National Funding from the FCT— Fundação para a Ciência e a Tecnologia, Portugal, through the UID/EEA/50008/2019 Project; by RNP, Brazil, with resources from MCTIC, Grant No. 01250.075413/2018-04, under the Centro de Referência em Radiocomunicações — CRR project of the Instituto Nacional de Telecomunicações (Inatel), Brazil; by the Government of the Russian Federation, Grant 08-08; and by Brazilian National Council for Research and Development (CNPq) via Grant No. 309335/2017-5.
Languageen
PublisherElsevier B.V.
SubjectInternet of Things
Machine learning
Medical
Smart grid
VANET
TitleMachine learning in the Internet of Things: Designed techniques for smart cities
TypeArticle
Pagination826-843
Volume Number100


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