## 6 Smart Water Methods (SWMs)
[114] developed a smart water network using an experimental water distribution system called EWDS-TUG, including artificial customers, sensors, and control magnetic valves. By applying the smart grid concept, water utilities can minimize water loss through consistent and reliable monitoring of water distribution networks [115]. Real-time monitoring of water distribution networks offers several advantages, including improved network visibility, water and energy savings, early detection of network inefficiencies, reduced need for on-site inspection, and better quality of services for customers. A popular way to determine the level of leakage in smart water networks is by analyzing the minimum night flow (MNF) between midnight and 4 a.m. This analysis is typically performed between 2 a.m. and 4 a.m., when customer demand and network pressures are high, making leakage more apparent in a District Metered Area (DMA) [28]. To create a District Metered Area (DMA), the water distribution network is divided into discrete zones by closing valves [116]. The volume of water entering and leaving the zone is metered to determine the amount of leakage. A leak alarm is triggered when the minimum night flow (MNF) in the DMA exceeds a threshold set by water utility companies. The MNF depends on several factors, including the age and length of pipes, the number of connections, and the pressure in the network. Figure 8: Concept of smart water networks [112]. A wireless sensor network (WSN) is an application of the smart grid in water networks. It consists of interconnected wireless nodes that can sense, compute, and communicate wirelessly, but also have power supply requirements. In a pipeline-monitoring WSN, sensor nodes work together to collect and transmit data to a base station [117]. However, certain factors need to be considered when implementing a smart pipe, such as the radio propagation channel, power and memory limitations, and efficient routing protocols [118]. PipeNet is a wireless sensor network system that is designed to detect, locate, and quantify leaks and bursts in water transmission pipelines [119]. The development of PipeNet is segmented into three stages. The first stage concerns the validation of a small-scale prototype deployment to assess the sensors' durability. In the second stage, advanced data acquisition and analysis techniques are tested and validated in a laboratory setting, including time-synchronized data collection and acoustic leak detection. The third and final stage involves merging the first two stages to create a comprehensive real-time monitoring solution. Another prominent example of WSN application is the Wireless Water Sentinel project, WaterWise@SG, operating in Singapore, known for its comprehensive management of hydraulic, acoustic, and water quality parameters. This platform enables applications such as predicting water demand and hydraulic state, detecting events, such as pipe bursts, and identifying longer-term trends through data mining [120]. Sensor nodes are used to cover an area of 60 km\({}^{2}\), packaged in clear plastic acrylic tubes with PVC caps at each end, supporting the attachment of pressure, hydrophone, and flow meter sensors. The system detects and locates pipe bursts by analyzing pressure, flow, and acoustic signals, providing a comprehensive solution for smart water management. The ICT Solutions for Efficient Water Resources Management (ICeWater) project also aims to enhance freshwater supply stability by leveraging smart grid technology [121]. The system includes three layers: sensor installation, data collection and processing, and user interaction. The project is being tested in Milan (Italy) and Timisoara (Romania), where statistical and machine learning methods are used to predict water loss. The Milan demo site classified data to identify typical urban water demand and provide hourly short-term forecasts [122].