AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION

Access to fresh water has become a headache for many nations around the world today due to water scarcity. Since this aspect is increasing, this paper introduces a system to estimate the households’ water needs in a day taking into consideration, the size of the family, zone, temperature, season, w...

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Main Author: Arman Mohammad Nakib
Format: Article
Language:English
Published: Lublin University of Technology 2024-12-01
Series:Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
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Online Access:https://ph.pollub.pl/index.php/iapgos/article/view/6106
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author Arman Mohammad Nakib
author_facet Arman Mohammad Nakib
author_sort Arman Mohammad Nakib
collection DOAJ
description Access to fresh water has become a headache for many nations around the world today due to water scarcity. Since this aspect is increasing, this paper introduces a system to estimate the households’ water needs in a day taking into consideration, the size of the family, zone, temperature, season, working status, location, and religion. By applying machine learning, the system determines the balance of water distribution between the families by these parameters. The predicted values determine the water requirements for each household hence the distribution of water in the households on a particular day. This includes the use of an Arduino microcontroller, water flow meter, and solenoid valves that make the water supply system to be an automatic system. As a result of this, the system helps to control the wastage of water and also ensures that the amount of water required in each home is assessed accurately.
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publishDate 2024-12-01
publisher Lublin University of Technology
record_format Article
series Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
spelling doaj-art-81764a8d45bf4a0c82b5a986dab5f5d62025-08-20T02:39:38ZengLublin University of TechnologyInformatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska2083-01572391-67612024-12-0114410.35784/iapgos.6106AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTIONArman Mohammad Nakib0https://orcid.org/0009-0006-4986-8806Nanjing University of Information Science & Technology, Artificial Intelligence Access to fresh water has become a headache for many nations around the world today due to water scarcity. Since this aspect is increasing, this paper introduces a system to estimate the households’ water needs in a day taking into consideration, the size of the family, zone, temperature, season, working status, location, and religion. By applying machine learning, the system determines the balance of water distribution between the families by these parameters. The predicted values determine the water requirements for each household hence the distribution of water in the households on a particular day. This includes the use of an Arduino microcontroller, water flow meter, and solenoid valves that make the water supply system to be an automatic system. As a result of this, the system helps to control the wastage of water and also ensures that the amount of water required in each home is assessed accurately. https://ph.pollub.pl/index.php/iapgos/article/view/6106factors influencing water consumptionmachine learning modelwater distribution controlwater wastage control
spellingShingle Arman Mohammad Nakib
AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska
factors influencing water consumption
machine learning model
water distribution control
water wastage control
title AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
title_full AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
title_fullStr AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
title_full_unstemmed AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
title_short AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
title_sort automated water management system with ai based de mand prediction
topic factors influencing water consumption
machine learning model
water distribution control
water wastage control
url https://ph.pollub.pl/index.php/iapgos/article/view/6106
work_keys_str_mv AT armanmohammadnakib automatedwatermanagementsystemwithaibaseddemandprediction