1. University of Kragujevac Digital Archive
  2. University of Kragujevac
  3. Faculty of Technical Sciences, Čačak
Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/12875
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dc.rights.licenserestrictedAccess-
dc.contributor.authorMarkovic D.-
dc.contributor.authorVujičić, Dejan-
dc.contributor.authorStamenković Z.-
dc.contributor.authorRandjić, Siniša-
dc.date.accessioned2021-04-20T21:57:27Z-
dc.date.available2021-04-20T21:57:27Z-
dc.date.issued2020-
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/12875-
dc.description.abstract© 2020 IEEE. This paper presents a model of an occupancy detection system based on artificial neural networks and data stream processing. With already available datasets, an artificial neural network was trained and the accuracy of 98.88% was achieved. Furthermore, data stream processing can be used as a part of the system for collecting and analysing data from IoT devices and their sensors.-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.sourceProceedings - 2020 23rd International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2020-
dc.titleIoT Based Occupancy Detection System with Data Stream Processing and Artificial Neural Networks-
dc.typeconferenceObject-
dc.identifier.doi10.1109/DDECS50862.2020.9095715-
dc.identifier.scopus2-s2.0-85085862230-
Appears in Collections:Faculty of Technical Sciences, Čačak

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