Using Wavelet Transformation for Prediction CO2in Smart Home Care Within IoT for Monitor Activities of Daily Living
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F19%3A10242727" target="_blank" >RIV/61989100:27240/19:10242727 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-030-28374-2_43" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-030-28374-2_43</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-28374-2_43" target="_blank" >10.1007/978-3-030-28374-2_43</a>
Alternative languages
Result language
angličtina
Original language name
Using Wavelet Transformation for Prediction CO2in Smart Home Care Within IoT for Monitor Activities of Daily Living
Original language description
In Smart Home Care (SHC) rooms from the measured operational and technical quantities for monitoring activities of every day of life for support of independent life for elderly people. The proposed algorithm for data processing (predicting the CO2course using neural networks from the measured temperature indoor Ti(oC), temperature outdoor To(oC) and the relative humidity indoor rHi (%)) was applicated, verified and compared in MATLAB SW tool and IBM SPSS SW tool with IoT platform connectivity. In the proposed method, a stationary wavelet transformation algorithm was used to remove the noise of the resulting predicted waveform of expected process. Two long-term experiments were performed (specifically from February 8 to February 15, 2015, from June 8 to June 15, 2015) and two short-term experiments (from February 8, 2015 and from June 8, 2015). For the best results of the trained ANN BRM within the prediction of CO2, the correlation coefficient R for the proposed method was up to 90%. The verification of the proposed method confirmed the possibility to use the presence of people of the monitored SHC premises for rooms ADL monitoring. (C) 2019, Springer Nature Switzerland AG.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
20200 - Electrical engineering, Electronic engineering, Information engineering
Result continuities
Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Volume 11684
ISBN
978-3-030-28373-5
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
500-509
Publisher name
Springer
Place of publication
Cham
Event location
Hendaye
Event date
Sep 4, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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