IoT Based Occupancy Detection System with Data Stream Processing and Artificial Neural Networks

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Поље DC-а	Вредност	Језик
dc.rights.license	restrictedAccess	-
dc.contributor.author	Markovic D.	-
dc.contributor.author	Vujičić, Dejan	-
dc.contributor.author	Stamenković Z.	-
dc.contributor.author	Randjić, Siniša	-
dc.date.accessioned	2021-04-20T21:57:27Z	-
dc.date.available	2021-04-20T21:57:27Z	-
dc.date.issued	2020	-
dc.identifier.uri	https://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.rights	info:eu-repo/semantics/restrictedAccess	-
dc.source	Proceedings - 2020 23rd International Symposium on Design and Diagnostics of Electronic Circuits and Systems, DDECS 2020	-
dc.title	IoT Based Occupancy Detection System with Data Stream Processing and Artificial Neural Networks	-
dc.type	conferenceObject	-
dc.identifier.doi	10.1109/DDECS50862.2020.9095715	-
dc.identifier.scopus	2-s2.0-85085862230	-
Налази се у колекцијама:	Faculty of Technical Sciences, Čačak

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