A real-time household water consumption monitoring and processing system aimed at leakage identification at user level is presented here. The system, developed within the GST4Water project, allows consumption data sent by a generic smart meter installed in a user’s house to be received and transferred to a cloud platform. Here, the consumption data are stored and processed through an empirical algorithm able to automatically identify leakage at the individual user level by looking for non-consumption in certain periods of the day. With reference to a real-life case study, the results obtained show that the algorithm enables leakages on users’ properties to be identified with an accuracy of more than 90%. Therefore, the implementation of this algorithm within a highly innovative smart metering system can represent an efficient tool for reducing water losses at user level.

While smart metering applications have initially focused on energy and gas utility markets, water consumption has recently become the subject of increasing attention. Unfortunately, despite the large number of solutions available on the market, the lack of an open and widely accepted communication standard means that vendors typically propose proprietary data collection solutions whose adoption causes non-trivial problems to water utility companies in term of costs, vendor lock-in, and lack of control on the data collection infrastructure. There is the need for open and interoperable smart water metering solutions, capable of collecting data from the wide range of water meters on the market. This paper reports our experience in the development and field testing of a highly interoperable smart water metering solution, which we designed in collaboration with several water utility companies and which we deployed in Gorino Ferrarese, Italy, in collaboration with CADF (Consorzio Acque Delta Ferrarese), the water utility serving the city. At the core of our solution is SWaMM (Smart Water Metering Middleware), an interoperable wireless IoT middleware based on the Edge computing paradigm, which proved extremely effective in interfacing with several types of smart water meters operating with different protocols.

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This paper presents some of the results achieved within the framework of the GST4Water project concerning the development of a real time monitoring and processing system for water consumption at individual user level. The system is based on the most innovative technologies proposed by the ICT sector and allows for receiving consumption data sent by a generic smart-meter installed in an user's house and transfer them to a cloud platform. Here, the consumption data are stored and processed in order to characterize leakage at district meter area (DMA) and at individual user level. Finally, the processed data, on the one hand, are returned to the Water Utility and can be used for billing, on the other hand, they provide frequent feedback to the user thus gaining full awareness of his consumption behaviour.