# Towards Digitalization of Water Supply Systems for Sustainable Smart City Development--Water 4.0
## 4 Digital Technologies in the Water System: Key Drivers of Water 4.0
### Cyber Physical System
The sensor reading is sent to a remote processing area for real-time water quality analysis via wireless communication technology. The wireless communication technology used ranges from short to long range, and high to low power. Amongst the low-power wireless communications, SigFox is power efficient and has the potential to cover relatively large areas in rural settings (up to 50 km). However, the rate at which these data are transmitted is relatively low. Similar to SigFox in data transmission rate, LoRaWAN is another long-range low-power wireless communication system that can be employed due to its potential to cover up to 20 km in rural areas [17]. Additionally, 3G/LTE and LTE-A offer reasonably fast data rates over long distances of up to 30 km, but when compared to other wireless communication technologies, their power utilization is rather high. The literature [43; 44; 45; 46] contains research papers on wireless communication technology utilized for this purpose. For the Water 4.0 architecture to monitor the water supply system infrastructure, long-distance communications with a relatively good data rate are required. Currently, short-range communications are used in CPS architecture. However, future CPSs should take into account incorporating the long-range wireless communication technologies into the system to improve communication coverage in order to provide dependable monitoring of water distribution networks, which are large-scale. Practical applications of CPSs for the management of water systems have been reported in the literature [47; 48; 49]. The research study in [47] presents a CPS framework for real-time control of the urban water cycle as illustrated in Figure 5. In this study, water hydraulic and quality conditions are monitored in real-time. Hydrodynamic modelling is integrated with real-time measurements to generate quality and hydraulic models for optimal control and diagnosis. [PERSON] and [PERSON] [50] proposed a CPS architecture for in-pipe water quality monitoring. The proposed system illustrated in Figure 6 is similar to the conventional wireless sensor network. The physical layer is the water distribution system to be monitored for water quality application. In this context, data from water flow, pH, and contamination sensors located in the sensing platform are acquired, transmitted, processed, and analyzed at the network layer. The data are managed effectively and stored in a database management system. The application tier includes various services for the system administration and a normal user. [PERSON] et al. [51] developed low-cost real-time monitoring and contaminant detection in a drinking water distribution system. In [52], a mobile sensor system is utilized to map river water quality based on in situ data collected in a few Indian rivers. The \begin{table}
\begin{tabular}{c c c} \hline \hline
**Parameter** & **Acceptable Range for Potable Water** & **Unit** \\ \hline pH & 6.5–8.5 & pH \\ \hline DOC & \textgreater{}3 & Mg/L \\ \hline Electrical Conductivity & 500–1000 & \(\upmu\)S/cm \\ \hline Temperature & 5–30 & \({}^{\circ}\)C \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Some water quality parameters and acceptable ranges. Figure 5: A CPS for the control of urban water cycle [47]. data visualization generated permits the detection of pollutant sources. The proposed system has been used to monitor and regulate quality of large bodies of water. The authors in [41] presented a soft computing framework using a multi-sensor array for water quality monitoring. Several other applications could be found in literature to show the potential of CPSs for the provision of sustainable water systems [53; 54; 55].