AUTOMATED WATER MANAGEMENT SYSTEM WITH AI-BASED DE-MAND PREDICTION
Arman Mohammad Nakib
armannakib35@gmail.comNanjing University of Information Science & Technology, Artificial Intelligence (China)
https://orcid.org/0009-0006-4986-8806
Abstract
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.
Keywords:
factors influencing water consumption, machine learning model, water distribution control, water wastage controlReferences
[1] Almulhim Abdulaziz I., Abubakar I. A.: A segmentation approach to understanding water consumption behavioral patterns among households in Saudi Arabia for a sustainable future. Resources, Environment and Sustainability 15, 2024, 100144.
Google Scholar
[2] Ali A. et al.: Design of an automatic rooftop water tank filling system and measurement of consumed water for home appliance. International Journal of Automation and Smart Technology 13(1), 2023, 2371–2371.
Google Scholar
[3] Adu Manu et al.: Leakage detection and automatic billing in water distribution systems using smart sensors. Digital Transformation for Sustainability: ICT-supported Environmental Socio-economic Development. Springer International Publishing, Cham 2022, 251–270.
Google Scholar
[4] Ali S. et al.: Controlled fluid flow without controlling pump using Arduino. Archives of Advanced Engineering Science 2024, 1-11.
Google Scholar
[5] Bergel T., Młyńska A.: Analysis of the impact of the air temperature on water consumption for household purposes in rural households. Journal of Ecological Engineering 22(3), 2021, 289–302.
Google Scholar
[6] Babu P., Rajasekaran C.: Economically precise water resource management for domestic usage in India. Circuits and Systems 7(10), 2016, 2821.
Google Scholar
[7] Baranidharan S. et al.: Smart water distribution system using internet of things (IoT). AIP Conference Proceedings 2831(1), 2023.
Google Scholar
[8] Chang H. et al.: Sensitivity of urban water consumption to weather and climate variability at multiple temporal scales: The case of Portland, Oregon. International Journal of Geospatial and Environmental Research 1(1), 2014, 7.
Google Scholar
[9] Crouch M. L. et al.: Defining domestic water consumption based on personal water use activities. AQUA—Water Infrastructure, Ecosystems and Society 70(7), 2021, 1002–1011.
Google Scholar
[10] Chavhan S. et al.: IoT-based Remote Control Water Distribution System. International Journal of Intelligent Systems and Applications in Engineering 12(7s), 2024, 572–583.
Google Scholar
[11] Dimkić D.: Temperature impact on drinking water consumption. Environmental Sciences Proceedings 2(1), 2020, 31.
Google Scholar
[12] Fan L. et al.: Factors affecting domestic water consumption in rural households upon access to improved water supply: Insights from the Wei River Basin, China. PloS one 8(8), 2013, e71977.
Google Scholar
[13] Gore S. et al.: Innovations in smart city water supply systems. International Journal of Intelligent Systems and Applications in Engineering 11(9s), 2023, 277–281.
Google Scholar
[14] Jiménez B., Asano T.: Water reuse: An international survey of current practice, issues and needs. IWA publishing 2008.
Google Scholar
[15] Kalyani C. et al.: Regular and equal water supply system. SAMRIDDHI: A Journal of Physical Sciences, Engineering and Technology 15(1), 2023, 34–37.
Google Scholar
[16] Kumar B. S. et al.: Water management and control systems for smart city using IoT and artificial intelligence. International Conference on Edge Computing and Applications (ICECAA). India, Tamilnadu, 2022, 653–657.
Google Scholar
[17] Lenzen M. et al.: International trade of scarce water. Ecological Economics 94, 2013, 78–85.
Google Scholar
[18] Matos C. et al.: Water and energy consumption in urban and rural households. 39th International Symposium CIB W062 on Water Supply and Drainage for Buildings. Japan, Nagano 2013.
Google Scholar
[19] Mule A. et al.: Smart Water Supply Management System With Anti-Theft Measures. International Research Journal of Modernization in Engineering Technology and Science 5(5), 2023, 3607–3614.
Google Scholar
[20] Mekonnen M. M., Hoekstra A. Y.: A global and high-resolution assessment of the green, blue and grey water footprint of wheat. Hydrology and earth system sciences 14(7), 2010, 1259–1276.
Google Scholar
[21] Nirmala D. et al.: System for water quality monitoring and distribution. E3S Web of Conferences 399, EDP Sciences, 2023.
Google Scholar
[22] Nur’Im J., Setyawan G.: Prototype design of clean water distribution system on residential scale using Arduino Mega microcontroller. AIP Conference Proceedings 2540(1), 2023.
Google Scholar
[23] Nakib A. M. et al.: Machine learning-based water requirement forecast and automated water distribution control system. Computer Science & IT Research Journal 5(6), 2024, 1453–1468.
Google Scholar
[24] Nakib A. M., Barua B.: Aqua Flow Master: Intelligent Liquid Flow Control And Monitoring System. International Research Journal of Modernization in Engineering Technology and Science 6(4), 2024, 8232–8237.
Google Scholar
[25] Ogidan O. K., Olla M., Odey I.: Water distribution control with real-time monitoring. IEEE Nigeria 4th International Conference on Disruptive Technologies for Sustainable Development (NIGERCON). 2022.
Google Scholar
[26] Pratama M., Firmansyah M.: AWAS (Automatic Water System) as a clean water distribution device to mitigate the impact of climate change. Research Report. WaterIsLifeSchools 2022.
Google Scholar
[27] Rondinel-Oviedo D. R., Sarmiento-Pastor J. M.: Water: consumption, usage patterns, and residential infrastructure. A comparative analysis of three regions in the Lima metropolitan area. Water International 45(7-8), 2020, 824–846.
Google Scholar
[28] Rondinel O., Daniel R., Sarmiento-Pastor J. M.: Water: consumption, usage patterns, and residential infrastructure. A comparative analysis of three regions in the Lima metropolitan area. Water International 45(7-8), 2020, 824–846.
Google Scholar
[29] Rodríguez C. et al.: Water balance assessment in schools and households of rural areas of Coquimbo region, north-central Chile: Potential for greywater reuse. Water 12(10), 2020, 2915.
Google Scholar
[30] Reddy D. G. et al.: Aadhaar Enabled Water Distribution System. Water Resources Management 38(7), 2024, 2279–2291.
Google Scholar
[31] Rexline S. J., Renold M., Deeba M.: Potable water distribution monitoring system using internet of things. AIP Conference Proceedings 2842(1), 2023.
Google Scholar
[32] Rahmatulloh A. et al.: IoT-Enabled Water Distribution Monitoring: A Sensor-Based Analytical Model. Ingénierie des Systèmes d'Information 28(6), 2023.
Google Scholar
[33] Smith A., Ali M.: Understanding the impact of cultural and religious water use. Water and Environment Journal 20(4), 2006, 203–209.
Google Scholar
[34] Singha B. et al.: Changing patterns of household water consumption and conservation behaviour in Bangladesh: an exploration in the context of COVID-19 pandemic. International Journal of Innovation and Sustainable Development 18(1-2), 2024, 106–122.
Google Scholar
[35] Spang E. S. et al.: The water consumption of energy production: an international comparison. Environmental Research Letters 9(10), 2014, 105002.
Google Scholar
[36] Timmerman M.: Water consumption in the Middle East and North Africa (MENA) region: a virtual water approach, 2013.
Google Scholar
[37] Tejas T. et al.: IoT based water management system with machine learning. AIP Conference Proceedings 2742(1), 2024.
Google Scholar
[38] Utami R. R. et al.: Mapping domestic water use to quantify water-demand and water-related contaminant exposure in a peri-urban community, Indonesia. International Journal of Environmental Health Research 34(1), 2024, 625–638.
Google Scholar
[39] Vladislav D. S.: A short study on smart water distribution through sensor network. Big data and computing visions 2(3), 2022, 122–127.
Google Scholar
[40] Velayudhan N. K. et al.: IoT-enabled water distribution systems – a comparative technological review. IEEE Access 10, 2022, 101042–101070.
Google Scholar
[41] Xenochristou M., Blokker M.: Investigating the influence of weather on water consumption: a Dutch Case Study (032). WDSA/CCWI Joint Conference Proceedings 1, 2018.
Google Scholar
[42] Yan L.: The ethnic and cultural correlates of water consumption in a pluralistic social context – the Sydney Metropolitan Area. Diss. 2015.
Google Scholar
[43] https://www.epa.gov/watersense/statistics-and-facts
Google Scholar
[44] https://www.statista.com/statistics/278066/global-water-demand-by-region/
Google Scholar
Authors
Arman Mohammad Nakibarmannakib35@gmail.com
Nanjing University of Information Science & Technology, Artificial Intelligence China
https://orcid.org/0009-0006-4986-8806
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