To search, Click
below search items.
|
|
All
Published Papers Search Service
|
Title
|
Digital Twin based Household Water Consumption Forecasting
using Agent Based Modeling
|
Author
|
Sultan Alamri, Muhammad Saad Qaisar Alvi, Imran Usman, and Adnan Idris
|
Citation |
Vol. 24 No. 4 pp. 147-154
|
Abstract
|
The continuous increase in urban population due to migration of mases from rural areas to big cities has set urban water supply under serious stress. Urban water resources face scarcity of available water quantity, which ultimately effects the water supply. It is high time to address this challenging problem by taking appropriate measures for the improvement of water utility services linked with better understanding of demand side management (DSM), which leads to an effective state of water supply governance. We propose a dynamic framework for preventive DSM that results in optimization of water resource management. This paper uses Agent Based Modeling (ABM) with Digital Twin (DT) to model water consumption behavior of a population and consequently forecast water demand. DT creates a digital clone of the system using physical model, sensors, and data analytics to integrate multi-physical quantities. By doing so, the proposed model replicates the physical settings to perform the remote monitoring and controlling jobs on the digital format, whilst offering support in decision making to the relevant authorities.
|
Keywords
|
Water Resources; Water Supply; Water System Dynamics; Agent
Based Modelling (ABM); Digital Twin (DT); Demand Side
Management(DSM)
|
URL
|
http://paper.ijcsns.org/07_book/202404/20240417.pdf
|
|