The SmartH2O platform: advancing residential water management by smart metering and data intensive modeling of consumers’ behaviors

The effectiveness of urban Water Demand Management Strategies (WDMS) at the household level does rely on the level of understanding we have about the determinants pushing users’ attitudes to consume or save water. Low-resolution data on residential water consumption, as traditionally metered, can only be exploited to model consumers’ behavior at an aggregate spatial and temporal scale, whereas the allocation among final uses and the motivations behind users’ behavior remain hidden. The recent advent of smart meters allows gathering high frequency, quasi real-time consumption data that can be used both to provide instantaneous information to water utilities on the network load and status and continuously inform the users on their consumption and savings. Hence, smart metered data allow developing models of consumers’ behavior, which are essential for the design of WDMS: the high-frequency consumption information, matched with users’ psychographic variables, constitutes the knowledge basis for developing such individual and multi users models, through which water utilities can test the impact of different WDMS. This study contributes single-user behavioral models, which are derived from fully automated algorithms, characterizing the single-point measured household water consumption into its end uses breakdown, and users’ consumption profiles, assessing the influence of users’ attributes and exogenous drivers on their consumption/saving attitudes. The work is part of the SmartH2O project, which aims at creating an ICT platform to raise customers’ awareness about their consumption and pursue water savings in the residential sector.