The Operation of Urban Water Treatment Plants: A Review of Smart Dashboard Frameworks

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F46747885%3A24620%2F23%3A00012544" target="_blank" >RIV/46747885:24620/23:00012544 - isvavai.cz</a>

Výsledek na webu

<a href="https://journals.tultech.eu/index.php/eil/article/view/106" target="_blank" >https://journals.tultech.eu/index.php/eil/article/view/106</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.15157/eil.2023.1.1.28-45" target="_blank" >10.15157/eil.2023.1.1.28-45</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Operation of Urban Water Treatment Plants: A Review of Smart Dashboard Frameworks

Popis výsledku v původním jazyce

By locating useful characteristics and determining the perfect circumstances to meet ideal water quality criteria, this study seeks to improve the operation of a water treatment facility. The research comprises gathering data from personnel and exposure to system events, as well as from explicit and tacit knowledge sources. The problem at hand is a multi-objective, multi-criteria problem with many variables in spatial and temporal dimensions, requiring the use of powerful tools for analysis. All engineering problems have an objective function consisting of smaller sub-functions, typically in the form of cost or error minimization. To solve such problems, optimization methods based on natural patterns have been introduced, including genetic algorithms, evolutionary algorithms, and particle mass optimization. By optimizing the operation process of the water treatment plant, the quality of the water provided can be improved to meet standards set by organizations such as Iran 1053, WHO, and EPA. The study‘s findings could be used to implement changes to the plant‘s management and operation processes to achieve more ideal water quality conditions. Ultimately, the optimization of water treatment plant processes could have significant positive impacts on public health and well-being, as well as the environment.

Název v anglickém jazyce

The Operation of Urban Water Treatment Plants: A Review of Smart Dashboard Frameworks

Popis výsledku anglicky

By locating useful characteristics and determining the perfect circumstances to meet ideal water quality criteria, this study seeks to improve the operation of a water treatment facility. The research comprises gathering data from personnel and exposure to system events, as well as from explicit and tacit knowledge sources. The problem at hand is a multi-objective, multi-criteria problem with many variables in spatial and temporal dimensions, requiring the use of powerful tools for analysis. All engineering problems have an objective function consisting of smaller sub-functions, typically in the form of cost or error minimization. To solve such problems, optimization methods based on natural patterns have been introduced, including genetic algorithms, evolutionary algorithms, and particle mass optimization. By optimizing the operation process of the water treatment plant, the quality of the water provided can be improved to meet standards set by organizations such as Iran 1053, WHO, and EPA. The study‘s findings could be used to implement changes to the plant‘s management and operation processes to achieve more ideal water quality conditions. Ultimately, the optimization of water treatment plant processes could have significant positive impacts on public health and well-being, as well as the environment.

Druh

J_ost - Ostatní články v recenzovaných periodicích

CEP obor

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OECD FORD obor

20101 - Civil engineering

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2023

Kód důvěrnosti údajů

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

Název periodika

Environmental Industry Letters :

ISSN

2806-2965

e-ISSN

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Svazek periodika

1

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

EE - Estonská republika

Počet stran výsledku

18

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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