<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...

Features	Unit	Winter ranges		Summer ranges
STwindow	[state]	0.00	2.00	0.00	2.00
RHin	[%]	14.27	77.10	35.71	67.45
p	[hPa]	960.33	1029.31	1006.13	1015.32
Tair	[ºC]	15.89	28.66	21.48	28.93
Wout	[km/h]	0.00	11.40	0.10	2.35
Tout	[ºC]	−10.50	17.60	14.70	32.70
RHout	[%]	22.20	99.00	30.70	86.20
CO2	[ppm]	350.00	6865.00	400.00	1230.00
Theat	[ºC]	14.13	54.44	22.56	28.94
Twall	[ºC]	8.50	27.31	24.13	32.06
AQF	[state]	0.00	2.00	0.00	2.00

DIN standard ranges for winter
Features	Unit	Range good		Range neutral		Range bad
RHin	[%]	40	68	40	62	<40	>70
Tair	[ºC]	21	23	20	24	<20	>24
CO₂	[ppm]	0	1,000	1,000	2,000	2,000	>2,000
Twall	[ºC]	13	23	23	35	>13	>35
DIN standard ranges for summer
Features	Unit	Range good		Range neutral		Range bad
RHin	[%]	40	62	40	55	<40	>70
Tair	[ºC]	23.50	25.50	22	26	<22	>26
CO₂	[ppm]	0	1,000	1,000	2,000	2,000	>2,000
Twall	[ºC]	13	23	23	35	>13	>35

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

Published Online: Sep 01, 2018

Page range: 7 - 12

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

Keywords
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.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Overview of minima and maxima of collected measurement datasets for winter and summer season.

Ranges of sensor data as good, neutral and bad.

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

Published Online: Sep 01, 2018

Page range: 7 - 12

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

KeywordsBig 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.

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Figure 8

Figure 9

Figure 10

Overview of minima and maxima of collected measurement datasets for winter and summer season.

Ranges of sensor data as good, neutral and bad.

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