Ве молиме користете го овој идентификатор да го цитирате или поврзете овој запис: http://hdl.handle.net/20.500.12188/19632
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dc.contributor.authorZdraveski, Vladimiren_US
dc.contributor.authorTrajanov, Dimitaren_US
dc.contributor.authorStojanov, Risteen_US
dc.contributor.authorKocarev, Ljupcoen_US
dc.date.accessioned2022-06-27T11:11:44Z-
dc.date.available2022-06-27T11:11:44Z-
dc.date.issued2018-02-
dc.identifier.urihttp://hdl.handle.net/20.500.12188/19632-
dc.description.abstractNowadays we are witnessing the establishment of the data-driven science as a new scientific paradigm, that is opening a waste amount of new opportunities for scientific and technological advances. The data is becoming the main asset in today’s science and technology. Unfortunately, a significant amount of available and stored data is not used today. This data is known as a dark data. Starting from this point, the primary goal of this paper is to raise the awareness of the opportunities that are explored with the dark data utilization in companies and organizations, by giving an overview of the underlining technologies, proposing a methodology and showing example projects that utilize the dark data in the IoT domain.en_US
dc.subjectDark data, Internet of Things (IoT), Machine Learning, Data Scienceen_US
dc.titleDark data in internet of things (IOT): challenges and opportunitiesen_US
dc.typeProceeding articleen_US
dc.relation.conferenceProceedings of the 7th Small Systems Simulation Symposium 2018, Nish, Serbiaen_US
item.fulltextWith Fulltext-
item.grantfulltextopen-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
crisitem.author.deptFaculty of Computer Science and Engineering-
Appears in Collections:Faculty of Computer Science and Engineering: Conference papers
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