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Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems
Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem wh...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143880/ https://www.ncbi.nlm.nih.gov/pubmed/25153475 http://dx.doi.org/10.3390/ijerph110808597 |
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author | Sinčak, Peter Ondo, Jaroslav Kaposztasova, Daniela Virčikova, Maria Vranayova, Zuzana Sabol, Jakub |
author_facet | Sinčak, Peter Ondo, Jaroslav Kaposztasova, Daniela Virčikova, Maria Vranayova, Zuzana Sabol, Jakub |
author_sort | Sinčak, Peter |
collection | PubMed |
description | Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem which cannot be overlooked for health protection reasons. We analysed several methods to program a virtual hot water tank with AI (artificial intelligence) tools including neuro-fuzzy systems as a precaution against legionelosis. The main goal of this paper is to present research which simulates the temperature profile in the water tank. This research presents a tool for a water management system to simulate conditions which are able to prevent legionelosis outbreaks in a water system. The challenge is to create a virtual water tank simulator including the water environment which can simulate a situation which is common in building water distribution systems. The key feature of the presented system is its adaptation to any hot water tank. While respecting the basic parameters of hot water, a water supplier and building maintainer are required to ensure the predefined quality and water temperature at each sampling site and avoid the growth of Legionella. The presented system is one small contribution how to overcome a situation when legionelosis could find good conditions to spread and jeopardize human lives. |
format | Online Article Text |
id | pubmed-4143880 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-41438802014-08-26 Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems Sinčak, Peter Ondo, Jaroslav Kaposztasova, Daniela Virčikova, Maria Vranayova, Zuzana Sabol, Jakub Int J Environ Res Public Health Article Good quality water supplies and safe sanitation in urban areas are a big challenge for governments throughout the world. Providing adequate water quality is a basic requirement for our lives. The colony forming units of the bacterium Legionella pneumophila in potable water represent a big problem which cannot be overlooked for health protection reasons. We analysed several methods to program a virtual hot water tank with AI (artificial intelligence) tools including neuro-fuzzy systems as a precaution against legionelosis. The main goal of this paper is to present research which simulates the temperature profile in the water tank. This research presents a tool for a water management system to simulate conditions which are able to prevent legionelosis outbreaks in a water system. The challenge is to create a virtual water tank simulator including the water environment which can simulate a situation which is common in building water distribution systems. The key feature of the presented system is its adaptation to any hot water tank. While respecting the basic parameters of hot water, a water supplier and building maintainer are required to ensure the predefined quality and water temperature at each sampling site and avoid the growth of Legionella. The presented system is one small contribution how to overcome a situation when legionelosis could find good conditions to spread and jeopardize human lives. MDPI 2014-08-21 2014-08 /pmc/articles/PMC4143880/ /pubmed/25153475 http://dx.doi.org/10.3390/ijerph110808597 Text en © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Article Sinčak, Peter Ondo, Jaroslav Kaposztasova, Daniela Virčikova, Maria Vranayova, Zuzana Sabol, Jakub Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title | Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title_full | Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title_fullStr | Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title_full_unstemmed | Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title_short | Artificial Intelligence in Public Health Prevention of Legionelosis in Drinking Water Systems |
title_sort | artificial intelligence in public health prevention of legionelosis in drinking water systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4143880/ https://www.ncbi.nlm.nih.gov/pubmed/25153475 http://dx.doi.org/10.3390/ijerph110808597 |
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