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Article

Wavelet-Based Filtration Procedure for Denoising the Predicted CO2 Waveforms in Smart Home within the Internet of Things

Department of Cybernetics and Biomedical Engineering, VSB-Technical University of Ostrava, FEECS, 708 Ostrava-Poruba, Czech Republic
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Sensors 2020, 20(3), 620; https://doi.org/10.3390/s20030620
Received: 17 December 2019 / Revised: 13 January 2020 / Accepted: 17 January 2020 / Published: 22 January 2020
(This article belongs to the Special Issue Sensor Technology for Smart Homes)
The operating cost minimization of smart homes can be achieved with the optimization of the management of the building’s technical functions by determination of the current occupancy status of the individual monitored spaces of a smart home. To respect the privacy of the smart home residents, indirect methods (without using cameras and microphones) are possible for occupancy recognition of space in smart homes. This article describes a newly proposed indirect method to increase the accuracy of the occupancy recognition of monitored spaces of smart homes. The proposed procedure uses the prediction of the course of CO2 concentration from operationally measured quantities (temperature indoor and relative humidity indoor) using artificial neural networks with a multilayer perceptron algorithm. The mathematical wavelet transformation method is used for additive noise canceling from the predicted course of the CO2 concentration signal with an objective increase accuracy of the prediction. The calculated accuracy of CO2 concentration waveform prediction in the additive noise-canceling application was higher than 98% in selected experiments. View Full-Text
Keywords: intelligent buildings; wavelet transformation; prediction; artificial neural network; multilayer perceptron; cloud computing; Internet of Things; smart home intelligent buildings; wavelet transformation; prediction; artificial neural network; multilayer perceptron; cloud computing; Internet of Things; smart home
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MDPI and ACS Style

Vanus, J.; Fiedorova, K.; Kubicek, J.; Gorjani, O.M.; Augustynek, M. Wavelet-Based Filtration Procedure for Denoising the Predicted CO2 Waveforms in Smart Home within the Internet of Things. Sensors 2020, 20, 620. https://doi.org/10.3390/s20030620

AMA Style

Vanus J, Fiedorova K, Kubicek J, Gorjani OM, Augustynek M. Wavelet-Based Filtration Procedure for Denoising the Predicted CO2 Waveforms in Smart Home within the Internet of Things. Sensors. 2020; 20(3):620. https://doi.org/10.3390/s20030620

Chicago/Turabian Style

Vanus, Jan, Klara Fiedorova, Jan Kubicek, Ojan M. Gorjani, and Martin Augustynek. 2020. "Wavelet-Based Filtration Procedure for Denoising the Predicted CO2 Waveforms in Smart Home within the Internet of Things" Sensors 20, no. 3: 620. https://doi.org/10.3390/s20030620

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