<abstract xmlns="http://www.w3.org/1999/xhtml"><p>This article provides information about a currently developed measurement and analysis system ‘Smart Monitoring’, which is used on scientific project in terms of healthy indoor air coefficients, as well as the processing of the collected data for machine learning algorithms. The target is to reduce CO2 emissions caused by wrong ventilation habits in building sector after renovation process in older buildings.</p></abstract>

This article provides information about a currently developed measurement and analysis system ‘Smart Monitoring’, which is used on scientific project in terms of healthy indoor air coefficients, as well as the processing of the collected data for machine learning algorithms. The target is to reduce CO2 emissions caused by wrong ventilation habits in building sector after renovation process in older buildings.

Data mining methods of healthy indoor climate coefficients for comfortable well-being

Environmental Protection and Natural Resources

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

This article provides information about a currently developed measurement and analysis system ‘Smart Monitoring’, which is used on scientific project in terms...

Data mining methods of healthy indoor climate coefficients for comfortable well-being

Online veröffentlicht: 01. Sept. 2018

Seitenbereich: 7 - 12

DOI: https://doi.org/10.2478/oszn-2018-0013

Schlüsselwörter
Big data, Web-based application, indoor air quality, machine learning, artificial intelligence, neural network, ventilation behaviour

© 2018 Grit Behrens, Klaus Schlender, Florian Fehring, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Data mining methods of healthy indoor climate coefficients for comfortable well-being

Online veröffentlicht: 01. Sept. 2018

Seitenbereich: 7 - 12

DOI: https://doi.org/10.2478/oszn-2018-0013

SchlüsselwörterBig data, Web-based application, indoor air quality, machine learning, artificial intelligence, neural network, ventilation behaviour

© 2018 Grit Behrens, Klaus Schlender, Florian Fehring, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
Big data, Web-based application, indoor air quality, machine learning, artificial intelligence, neural network, ventilation behaviour