Water Demand Prediction Model for Urban Cities
Water is an essential and crucial element of each of the living beings. The urban water systems cater to the water necessities of the communities. Hence urban water management is a very critical task. Water demand modeling and prediction is one of the techniques that elevates resource allocation, supply cost reduction, fatalities supply network reduction, and so on. We are proposing a water demand prediction platform with the existing dependent features and a deep neural network model to incorporate the time series, weather, and demand to predict the short-term water demand effectively. Since the IoT sensors are the major data sources for this prediction model we are proposing a multivariate data imputation model, multi-variate Gaussian- based GAIN (Generative adversarial imputation Net).
Name of students and staff from Amrita : Nibi K V, Research Associate Amrita Center for Wireless Network & Application
International Collaborators : Dragan Savic FREng, Professor University of Exeter & Univ. of Belgrade; KWR Water Research
