Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning
The paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-...
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MDPI AG
2020-03-01
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Series: | Sensors |
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Online Access: | https://www.mdpi.com/1424-8220/20/7/1941 |
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author | Bartosz Szeląg Jakub Drewnowski Grzegorz Łagód Dariusz Majerek Ewa Dacewicz Francesco Fatone |
author_facet | Bartosz Szeląg Jakub Drewnowski Grzegorz Łagód Dariusz Majerek Ewa Dacewicz Francesco Fatone |
author_sort | Bartosz Szeląg |
collection | DOAJ |
description | The paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including: artificial neural networks, support vector machines, random forests, boosted trees, and logistic regression. The analysis conducted sought the combinations of independent variables for which the devised soft sensor is characterized with high accuracy and at a relatively low cost of determination. With the measurement results pertaining to the quantity and quality of wastewater as well as the temperature in the activated sludge chambers, a good fit can be achieved with the boosted trees method. In order to simplify the selection of an optimal method for the identification of activated sludge bulking depending on the model requirements and the data collected within the WWTP, an original system of weight estimation was proposed, enabling a reduction in the number of independent variables in a model—quantity and quality of wastewater, operational parameters, and the cost of conducting measurements. |
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format | Article |
id | doaj.art-e0bde57b77494c528f0c1b7538685220 |
institution | Directory Open Access Journal |
issn | 1424-8220 |
language | English |
last_indexed | 2024-03-09T06:18:13Z |
publishDate | 2020-03-01 |
publisher | MDPI AG |
record_format | Article |
series | Sensors |
spelling | doaj.art-e0bde57b77494c528f0c1b75386852202023-12-03T11:51:39ZengMDPI AGSensors1424-82202020-03-01207194110.3390/s20071941Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems FunctioningBartosz Szeląg0Jakub Drewnowski1Grzegorz Łagód2Dariusz Majerek3Ewa Dacewicz4Francesco Fatone5Faculty of Environmental, Geomatic and Energy Engineering, Kielce University of Technology, Tysiąclecia Państwa Polskiego 7, 25-314 Kielce, PolandFaculty of Civil and Environmental Engineering, Gdansk University of Technology, Narutowicza 11/12, 80-233 Gdansk, PolandFaculty of Environmental Engineering, Lublin University of Technology, Nadbystrzycka 40B, 20-618 Lublin, PolandFaculty of Fundamentals of Technology, Lublin University of Technology, Nadbystrzycka 38, 20-618 Lublin, PolandFaculty of Environmental Engineering and Land Surveying, University of Agriculture in Krakow, Mickiewicza 24/28, 30-059 Kraków, PolandDepartment of Science and Engineering of Materials, Environment and Urban Planning-SIMAU, Polytechnic University of Marche Ancona, 60121 Ancona, ItalyThe paper presented the methodology for the construction of a soft sensor used for activated sludge bulking identification. Devising such solutions fits within the current trends and development of a smart system and infrastructure within smart cities. In order to optimize the selection of the data-mining method depending on the data collected within a wastewater treatment plant (WWTP), a number of methods were considered, including: artificial neural networks, support vector machines, random forests, boosted trees, and logistic regression. The analysis conducted sought the combinations of independent variables for which the devised soft sensor is characterized with high accuracy and at a relatively low cost of determination. With the measurement results pertaining to the quantity and quality of wastewater as well as the temperature in the activated sludge chambers, a good fit can be achieved with the boosted trees method. In order to simplify the selection of an optimal method for the identification of activated sludge bulking depending on the model requirements and the data collected within the WWTP, an original system of weight estimation was proposed, enabling a reduction in the number of independent variables in a model—quantity and quality of wastewater, operational parameters, and the cost of conducting measurements.https://www.mdpi.com/1424-8220/20/7/1941soft sensorsmart systems and infrastructuredata miningclassification modelwastewater treatment plantactivated sludge bulking |
spellingShingle | Bartosz Szeląg Jakub Drewnowski Grzegorz Łagód Dariusz Majerek Ewa Dacewicz Francesco Fatone Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning Sensors soft sensor smart systems and infrastructure data mining classification model wastewater treatment plant activated sludge bulking |
title | Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning |
title_full | Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning |
title_fullStr | Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning |
title_full_unstemmed | Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning |
title_short | Soft Sensor Application in Identification of the Activated Sludge Bulking Considering the Technological and Economical Aspects of Smart Systems Functioning |
title_sort | soft sensor application in identification of the activated sludge bulking considering the technological and economical aspects of smart systems functioning |
topic | soft sensor smart systems and infrastructure data mining classification model wastewater treatment plant activated sludge bulking |
url | https://www.mdpi.com/1424-8220/20/7/1941 |
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