Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10242080" target="_blank" >RIV/61989100:27240/19:10242080 - isvavai.cz</a>

Result on the web

<a href="https://www.mdpi.com/1424-8220/19/6/1407" target="_blank" >https://www.mdpi.com/1424-8220/19/6/1407</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3390/s19061407" target="_blank" >10.3390/s19061407</a>

Result language

angličtina

Original language name

Using the IBM SPSS SW Tool with Wavelet Transformation for CO2 Prediction within IoT in Smart Home Care

Original language description

Standard solutions for handling a large amount of measured data obtained from intelligent buildings are currently available as software tools in IoT platforms. These solutions optimize the operational and technical functions managing the quality of the indoor environment and factor in the real needs of residents. The paper examines the possibilities of increasing the accuracy of CO1 predictions in Smart Home Care (SHC) using the IBM SPSS software tools in the IoT to determine the occupancy times of a monitored SHC room. The processed data were compared at daily, weekly and monthly intervals for the spring and autumn periods. The Radial Basis Function (RBF) method was applied to predict CO1 levels from the measured indoor and outdoor temperatures and relative humidity. The most accurately predicted results were obtained from data processed at a daily interval. To increase the accuracy of CO1 predictions, a wavelet transform was applied to remove additive noise from the predicted signal. The prediction accuracy achieved in the selected experiments was greater than 95%.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20205 - Automation and control systems

Project

<a href="/en/project/EF16_019%2F0000867" target="_blank" >EF16_019/0000867: Research Centre of Advanced Mechatronic Systems</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2019

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Sensors (Basel, Switzerland)

ISSN

1424-8220

e-ISSN

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Volume of the periodical

19

Issue of the periodical within the volume

6

Country of publishing house

CH - SWITZERLAND

Number of pages

28

Pages from-to

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UT code for WoS article

000465520200096

EID of the result in the Scopus database

2-s2.0-85063664851