Forecasting domestic water consumption from smart meter readings using statistical methods and artificial neural networks

Abstract

This paper presents an artificial neural network-based model of domestic water consumption. The model is based on real-world data collected from smart meters, and represents a step toward being able to model real-time smart meter data. A range of input schemas are examined, including real meter readings and summary statistics derived from readings, and it is found that the models can predict some consumption but struggle to accurately match in cases of peak usage.