Abstract:
This paper presents a model of an occupancy detection system based on artificial neural networks and data stream processing. With already available datasets, an artificia...Show MoreMetadata
Abstract:
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.
Published in: 2020 23rd International Symposium on Design and Diagnostics of Electronic Circuits & Systems (DDECS)
Date of Conference: 22-24 April 2020
Date Added to IEEE Xplore: 19 May 2020
ISBN Information:
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Faculty of Agronomy in Čačak, University of Kragujevac, Čačak, Serbia
Faculty of Technical Sciences Čačak, University of Kragujevac, Čačak, Serbia
IHP - Leibniz-Institut für Innovative Mikroelektronik, Frankfurt, Oder, Germany
Faculty of Technical Sciences Čačak, University of Kragujevac, Čačak, Serbia
Contents Faculty of Agronomy in Čačak, University of Kragujevac, Čačak, Serbia
Faculty of Technical Sciences Čačak, University of Kragujevac, Čačak, Serbia
IHP - Leibniz-Institut für Innovative Mikroelektronik, Frankfurt, Oder, Germany
Faculty of Technical Sciences Čačak, University of Kragujevac, Čačak, Serbia
