AN INTELLIGENT IOT- AND AI-DRIVEN SMART WATER DISTRIBUTION MONITORING SYSTEM FOR SUSTAINABLE URBAN WATER RESOURCE MANAGEMENT
AUTHORS:
Mentor
Dr B Rajanna
Affiliation
Department Of ECE, SVS Group of Institutions, Hanmakonda, Telangana
DOI: 
SHARE THIS ARTICLE
CC BY 4.0 License:
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
DOWNLOAD ARTICLE
REVIEW REPORT
CITE THIS ARTICLE
Abstract
Water scarcity and inefficient water distribution have become major challenges in rapidly growing urban environments. Traditional water management systems suffer from leakage, unequal distribution, delayed fault detection, and lack of real-time monitoring. This paper proposes a Smart Water Distribution Monitoring System that integrates Internet of Things (IoT) devices, cloud computing, artificial intelligence (AI), and wireless sensor networks to enhance water distribution efficiency. The proposed system continuously monitors water quality, flow rate, pressure levels, reservoir status, and consumer usage patterns through smart sensors installed at strategic locations. The collected data is transmitted to a cloud platform where machine learning algorithms analyze consumption trends, predict demand, and identify abnormal conditions such as leakage, contamination, and unauthorized usage. Automated control valves regulate water distribution based on demand forecasting and resource availability. The system improves water conservation, reduces operational costs, minimizes water losses, and ensures equitable distribution. Experimental analysis demonstrates significant improvements in monitoring accuracy, leak detection efficiency, and water utilization compared to conventional systems. The proposed framework contributes toward the development of sustainable smart cities and intelligent water resource management.
Keywords
Internet of Things (IoT) Smart Water Management Cloud Computing Artificial Intelligence Water Distribution Network Leak Detection Smart Cities Wireless Sensor Networks.
Article Information
PUBLICATION DETAILS
Review Type:
Double-Blind Peer Review
License:
CC BY-NC 4.0
Volume/Issue:
Volume 02, Issue 7
Review Rounds:
2
Article Type:
Research Article
Publication Date:
Jul 14 2026
Article Metrics
Article Views
47
PDF Downloads
0
HOW TO CITE
Copy
Rakesh, B. & Surendar, K. (2026). An Intelligent IOT- and AI-Driven Smart Water Distribution Monitoring System for Sustainable Urban Water Resource Management. International Journal of Science, Strategic Management and Technology, 02(7), 1-9. https://doi.org/10.55041/ijsmt.v2i7.068
Rakesh, Bandari, and Kalala Surendar. "An Intelligent IOT- and AI-Driven Smart Water Distribution Monitoring System for Sustainable Urban Water Resource Management." International Journal of Science, Strategic Management and Technology, vol. 02, no. 7, 2026, pp. 1-9. doi:https://doi.org/10.55041/ijsmt.v2i7.068.
Rakesh, Bandari, and Kalala Surendar. "An Intelligent IOT- and AI-Driven Smart Water Distribution Monitoring System for Sustainable Urban Water Resource Management." International Journal of Science, Strategic Management and Technology 02, no. 7 (2026): 1-9. https://doi.org/https://doi.org/10.55041/ijsmt.v2i7.068.
References
[1] A. McIntosh and H. Gebrechorkos, “Partnering for Solutions: ICTs in Smart Water Management,” International Telecommunication Union, Geneva, Switzerland, 2014.
[2] T. Robles et al., “An IoT-Based Reference Architecture for Smart Water Management Processes,” IEEE Internet of Things Journal, vol. 3, no. 4, pp. 500–510, 2016.
[3] J. Shah, “An Internet of Things Based Model for Smart Water Distribution with Quality Monitoring,” International Journal of Innovative Research in Science, Engineering and Technology, vol. 6, no. 5, pp. 8542–8548, 2017.
[4] N. A. Cloete, R. Malekian, and L. Nair, “Design of Smart Sensors for Real-Time Water Quality Monitoring,” IEEE Access, vol. 13, no. 9, pp. 125–135, 2014.
[5] M. Kalimuthu, A. S. Ponraj, and C. J. J., “Water Management and Metering System for Smart Cities,” International Journal of Scientific and Technology Research, vol. 9, no. 4, pp. 234–240, 2020.
[6] K. Shruthi, K. Chandrakala, P. Jyothi, and B. Haritha, “Automated Town Water Management System Using PIC Microcontroller,” Journal of Resource Management and Technology, vol. 5, no. 2, pp. 85–92, 2019.
[7] H. Mohapatra et al., “An Efficient Energy Saving Scheme Through Sorting Technique for Wireless Sensor Networks,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 8, pp. 4701–4708, 2020.
[8] S. Perumal, R. Sundaram, and V. Kumar, “Artificial Intelligence Based Water Demand Forecasting for Smart Cities,” IEEE Access, vol. 10, pp. 45211–45223, 2022.
[9] Y. Zhou and M. Zhang, “Smart Water Distribution Systems Using Machine Learning and IoT Technologies,” Sensors, vol. 23, no. 4, pp. 1887–1901, 2023.
[10] World Bank, “Smart Water Management Technologies for Sustainable Urban Development,” Technical Report, Washington, DC, USA, 2023.
[2] T. Robles et al., “An IoT-Based Reference Architecture for Smart Water Management Processes,” IEEE Internet of Things Journal, vol. 3, no. 4, pp. 500–510, 2016.
[3] J. Shah, “An Internet of Things Based Model for Smart Water Distribution with Quality Monitoring,” International Journal of Innovative Research in Science, Engineering and Technology, vol. 6, no. 5, pp. 8542–8548, 2017.
[4] N. A. Cloete, R. Malekian, and L. Nair, “Design of Smart Sensors for Real-Time Water Quality Monitoring,” IEEE Access, vol. 13, no. 9, pp. 125–135, 2014.
[5] M. Kalimuthu, A. S. Ponraj, and C. J. J., “Water Management and Metering System for Smart Cities,” International Journal of Scientific and Technology Research, vol. 9, no. 4, pp. 234–240, 2020.
[6] K. Shruthi, K. Chandrakala, P. Jyothi, and B. Haritha, “Automated Town Water Management System Using PIC Microcontroller,” Journal of Resource Management and Technology, vol. 5, no. 2, pp. 85–92, 2019.
[7] H. Mohapatra et al., “An Efficient Energy Saving Scheme Through Sorting Technique for Wireless Sensor Networks,” International Journal of Emerging Trends in Engineering Research, vol. 8, no. 8, pp. 4701–4708, 2020.
[8] S. Perumal, R. Sundaram, and V. Kumar, “Artificial Intelligence Based Water Demand Forecasting for Smart Cities,” IEEE Access, vol. 10, pp. 45211–45223, 2022.
[9] Y. Zhou and M. Zhang, “Smart Water Distribution Systems Using Machine Learning and IoT Technologies,” Sensors, vol. 23, no. 4, pp. 1887–1901, 2023.
[10] World Bank, “Smart Water Management Technologies for Sustainable Urban Development,” Technical Report, Washington, DC, USA, 2023.
Ethics and Compliance
✓ All ethical standards met
This article has undergone plagiarism screening and double-blind peer review. Editorial policies have been followed. Authors retain copyright under CC BY-NC 4.0 license. The research complies with ethical standards and institutional guidelines.
Indexed In
Similar Articles
A Study on Cash Flow Performance and Profitability Analysis
(2026)
DOI: 10.55041/ijsmt.v2i5.475
Modelling, Control and Battery State Evaluation of A Grid-Interactive Bidirectional Fast DC Charger for Electric Vehicles
(2026)
DOI: 10.55041/ijsmt.v2i6.015
The 16 Samskaras: A Comprehensive Analysis of Lifecycle Milestones in the Sanatana Tradition
(2026)
DOI: 10.55041/ijsmt.v2i4.252
Previous Article
