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Smart city article details

Title A Proof-Of-Concept Study Towards Developing Digital Twins For Operational Excellence In Large-Scale Water Distribution Networks
ID_Doc 3837
Authors Singh A.; Singh S.; Maheshwari A.
Year 2025
Published Urban Water Journal, 22, 5
DOI http://dx.doi.org/10.1080/1573062X.2025.2480632
Abstract In the current face of water scarcity, water losses due to leakages in large-scale water distribution networks (WDN) and non-revenue water are challenging factors. In this direction, Digital Twins integrate concepts like IoT, ML (machine learning), and DL (deep learning) with a water pave path for smart urban water infrastructure. Herein, we propose a holistic digital twin systems framework and its application in leak detection, validated with field-data on Indian Institute of Technology Jodhpur (IIT-J) campus WDN. A detailed methodology developing monitoring digital twins supported on the python platform and using open-source WDN simulators; EPANET and WNTR for hydraulic simulations and a Graph-convolution Neural Network-based leak detection model is elucidated. Results are analysed and demonstrated for the highest water consumption zone of the campus, with the model giving an accuracy of 90% for leakage detection. Further, a test scenario is described where the proposed framework shows water savings of up to 58% which would have been otherwise lost due to leaks in WDN. © 2025 Informa UK Limited, trading as Taylor & Francis Group.
Author Keywords Leakages; real-time monitoring; smart city; smart water infrastructure; water supply


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