Utilization of Machine Learning to Detect Sudden Water Leakage for Smart Water Meter
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25530%2F19%3A39915416" target="_blank" >RIV/00216275:25530/19:39915416 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Utilization of Machine Learning to Detect Sudden Water Leakage for Smart Water Meter
Original language description
This article deals with the use of machine learning to detect sudden water leakage. A smart water meter, which enables monitoring the water consumption of the observed object, is used as the source of input data. Based on these data and their analysis, a symbolic regression, which must know not only the input parameters but also the structure of the model, was finally used to build the model. After finding a suitable function and standard deviation from the model, it is possible to set the required sensitivity and thereby detect anomalous states of water consumption in monitored time windows. Since the smart water meter also has a ball valve, if a sudden water leakage is detected, the water meter can autonomously close the main supply and thus avoid extensive damage.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
29th International Conference Radioelektronika, RADIOELEKTRONIKA 2019
ISBN
978-1-5386-9323-0
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
340-344
Publisher name
IEEE (Institute of Electrical and Electronics Engineers)
Place of publication
New York
Event location
Pardubice
Event date
Apr 16, 2019
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
000492026100062