The design of user-customized water demand management strategies (WDMS) does require detailed information on the users’ water consumption habits and demand patterns. While low-resolution consumption data, as traditionally collected for billing purposes, do not allow for detailed investigations on consumers’ behavior, the recent advent of smart water sensors allows metering residential water consumption with sub-daily frequency. High-frequency water data are advancing our ability in characterizing and modeling consumers’ behavior, thus supporting the design of user-oriented residential water demand management strategies. Furthermore, they allow to close the information and communication loop between water utilities and their customers, as they provide instantaneous information on the state of the network and allow to continuously inform the users on their consumption and savings.

SmartH2O is a EU funded project which develops an ICT platform for raising users’ awareness about water consumption and pursuing water savings in the residential sector thanks to the integrated use of smart meters, advanced behavioral modeling, social computation, and personalized demand management strategies such as customized feedbacks and price schemes.

In this work, we present the main components of the SmartH2O integrated platform, with a particular focus on (i) high-resolution water consumption data collection through smart meters, (ii) users’ consumption modeling at the house level and end-use characterization through automatic disaggregation algorithms, and (iii) water consumption data visualization.