# Optimal Arrangement Strategy of IoT Sensors in Urban Drainage Networks: A Review
## 1 Introduction  
The Urban Drainage Network (UDN) is a type of underground municipal infrastructure for transferring and transporting rainwater and sewage. Owing to complex operating conditions, their inspection and maintenance are difficult [1]. Monitoring the operational status of pipeline networks using Internet of Things (IoT) sensors can facilitate the identification of problems such as blockage, pollution, and leakage, owing to factors such as pipeline failure. This is critical to the safe and stable operation of drainage networks. In a UDN, the parameters that are monitored by sensors include water quality and hydraulic parameters. By monitoring the composition of sewage [2, 3, 4], low water quality and illegal discharge points can be identified in pipelines, and corresponding measures can be implemented to reduce the operational burden of sewage treatment plants during pollution events. Moreover, by monitoring hydraulic parameters such as the flow rate and water level, the flow state inside a pipeline can be evaluated [5, 6], and abnormal events, such as blockage, external water infiltration, backflow, and overflow [7, 8, 9], can be analyzed to guide the operation and maintenance of the network.  
Traditional drainage network operation and maintenance rely heavily on regular field surveys [10, 11] or sewage and sediment sampling [3, 12, 13] to obtain network operational data.  
Currently, high-precision sensors such as flow, level, and current meters are widely utilized in important nodes of UDNs. However, owing to several limitations, including their data temporal resolution, the amount of data collected, and the spatial distribution of sampling points, it is difficult to adequately assess the real-time operational status of the drainage network using regular manual sampling or empirical judgment. Consequently, there is a lag in accident monitoring such as illegal discharge and flood overflow. Thus, it is impossible to reflect real-time hydraulic and water quality status in the pipeline network.  
The advancement of IoT technology and the iterative improvement in sensors have led to the development of IoT sensors that facilitate real-time data transmission for safety and health monitoring of structures such as bridges [14] and dams [15], as well as environmental monitoring such as air quality [16]. They are also widely used in the monitoring of hydraulic parameters in water supply projects [17; 18; 19], surface rivers [20], groundwater [21], and rainfall [22]. Recently, IoT sensors have also been widely used in the monitoring of water quality hydraulic parameters in UDNs. The application of IoT in UDN monitoring is shown in Figure 1.  
However, the complexity of sewage composition and variable flow patterns in drainage pipes pose great challenges to the application of IoT monitoring devices and communication technologies. In addition, drainage networks have a complex pipeline network topology, consisting of pipelines at different levels, such as main drains, main sewers, branch pipelines, and connecting pipelines. Therefore, the application of IoT sensors, especially the selection of monitoring locations, is difficult. Numerous studies have been conducted on the optimized layout of sensors. A universal layout strategy has not been established yet. This investigation focused on the monitoring needs and structural characteristics of drainage pipelines, proposed a general framework applicable to the optimal layout of IoT sensors for UDNs and classified the monitored parameters at different nodes, and compared the advantages, disadvantages, and application scopes of different types of sensor layout optimization methods.