IoT Technology Applications in Drainage Pipe Networks

I. Introduction

1.1 Background and Challenges of Drainage Pipe Network Management

Urban drainage pipe networks serve as critical "underground lifelines" that ensure urban water security. As urbanization accelerates, these systems face increasingly severe challenges:

1. Aging Infrastructure and Frequent Failures: Traditional pipeline materials are prone to corrosion, leading to sedimentation, cracks, leaks and other issues that reduce drainage efficiency. According to statistics, the average leakage rate of urban drainage pipe networks in China exceeds 20%, causing annual economic losses of billions of yuan (1).
2. Flooding and Pollution Risks: Inadequate drainage during heavy rains can easily lead to urban waterlogging, while sewage overflow affects the ecological environment. During summer 2025, many cities in China experienced short-term heavy rainfall, with some cities experiencing "sea-viewing" phenomena, traffic paralysis and property losses (1).
3. Low Detection Efficiency: Traditional drainage pipe network inspections rely heavily on manual patrols, which often lag in responding to issues such as stormwater waterlogging, pipeline blockages, and sewage overflows. Manual inspections are time-consuming and labor-intensive, making it difficult to detect hidden problems in a timely manner, with scattered data management (1).
4. Difficulty in Coordination and Management: Urban drainage pipe networks involve multiple departments and units, making coordination and management difficult. Poor information sharing further complicates efforts to address waterlogging, often making it difficult to form a concerted effort (1).

1.2 Application Value and Advantages of IoT Technology

IoT technology provides a completely new solution for drainage pipe network management through the organic combination of sensors, communication networks and intelligent analysis platforms:

1. Real-time Perception and Intelligent Early Warning: By deploying various sensors at key nodes of drainage pipe networks, real-time monitoring of water levels, flow rates, water quality and other parameters is achieved, allowing for early detection of potential risks and warnings. Through real-time monitoring-intelligent analysis-dynamic dispatching closed-loop management, smart systems can improve emergency response efficiency by more than 70%, truly realizing the transformation from "passive emergency response" to "active prevention and control" (1).
2. Accurate Diagnosis and Positioning: With the help of IoT sensor networks and data analysis technology, it is possible to accurately locate pipeline leaks, blockages and other problems, significantly improving fault diagnosis efficiency. For example, by capturing pipeline vibration signals and comparing acoustic characteristics, pinhole-level leaks can be identified, forming a three-dimensional monitoring network covering both main and branch pipes (1).
3. Data-driven Decision Making: The massive data collected by IoT technology provides a scientific basis for the planning, design, renovation and operation of drainage pipe networks, supporting data-based intelligent decision-making. Through big data cleaning and fusion technology, surveying and mapping data, IoT real-time data, business approval data are integrated into a spatio-temporal database to support in-depth analysis such as pollution source tracing and waterlogging simulation (1).
4. Remote Control and Intelligent Dispatching: Combined with IoT technology and automatic control equipment, remote control and intelligent dispatching of drainage pump stations, valves and other equipment can be realized, optimizing resource allocation and improving drainage efficiency. For example, smart pipe network systems can comprehensively analyze historical rainfall data, real-time meteorological information, pipe network operation data, etc., predict the impact of rainfall on the pipe network, and automatically adjust the operating parameters of pump stations and the opening degree of valves to achieve intelligent dispatching of drainage systems (1).
5. Reduced Operation and Maintenance Costs: By accurately locating fault points and predicting maintenance needs, unnecessary inspections and maintenance work can be reduced, lowering operation and maintenance costs. For example, in a demonstration area in Chongqing, the three-dimensional model of the pipe network is updated synchronously with the physical system, allowing staff to "see through" the deformation of underground 5-meter pipes in a virtual scene, reducing maintenance costs by 40% (1).

II. System Architecture and Key Technologies of IoT Drainage Pipe Networks

2.1 Overall System Architecture

IoT drainage pipe network systems adopt a hierarchical architecture design, typically including four layers: perception layer, transmission layer, platform layer and application layer:

1. Perception Layer: Composed of various sensors installed at key nodes of drainage pipe networks, including level gauges, flow meters, water quality sensors, gas detectors, manhole cover status monitors and other equipment, covering key nodes such as drainage connection wells, waterlogging-prone points, and pump station inlets and outlets (1).
2. Transmission Layer: Utilizes wired or wireless communication technologies (such as WiFi, LoRa, 3G/4G/5G, etc.) to transmit data collected by the perception layer to the management cloud platform, ensuring the real-time, accuracy and security of data (1).
3. Platform Layer: Also known as the data center or cloud platform, it is responsible for receiving, storing, processing and analyzing data from the transmission layer, conducting real-time monitoring, early warning and evaluation of drainage pipe network operation status, and providing decision support for managers (1).
4. Application Layer: Various application interfaces for users, such as PC management software, mobile APP, etc. Users can intuitively view the operation status of pipe networks through the management cloud platform, receive early warning information, carry out remote control or issue instructions (1).

The system operation involves five links: "perception-transmission-analysis-decision-feedback". Through the perception layer equipment to collect various parameters in the pipe network, using the transmission layer technology to upload data to the platform layer in real time, process and analyze the data, execute alarms, management, etc., managers make decisions based on early warning information, and issue instructions through the application layer, and make corresponding adjustments or maintenance according to the instructions, forming a closed-loop management.

2.2 Key Technologies and Applications

2.2.1 Multi-type Sensor Network Technology

The perception layer of IoT drainage pipe network systems mainly relies on multiple types of sensors to achieve comprehensive monitoring of pipe network status:

1. Water Level Monitoring: Adopting radar level gauges, pressure-type water level sensors and other equipment with accuracy up to ±1cm, which can monitor water level changes in rivers, reservoirs, and low-lying urban roads in real time. For example, the new generation of water level warning monitoring equipment developed by Tianjin has a measurement accuracy of 0.1 cm and a data collection frequency of up to 5 minutes/time (1).
2. Flow Monitoring: Doppler current meters and electromagnetic flow meters work together to dynamically evaluate the load capacity of drainage systems. In the Suyu District project, 160 sets of monitoring equipment, 134 level gauges, 42 video surveillance systems and 8 online waterlogging monitoring stations were installed to achieve 24-hour continuous visual monitoring (1).
3. Water Quality Monitoring: Online detection of COD, ammonia nitrogen and other indicators to trace sewage discharge and rain-sewage mixing problems. Water quality sensors can monitor water quality parameters in the pipe network in real time, such as pH value, dissolved oxygen, ammonia nitrogen, etc., and promptly detect sewage discharge or rain-sewage mixing (1).
4. Gas Monitoring: Install gas detectors for harmful gases that may exist in drainage pipe networks, such as methane and hydrogen sulfide, to ensure the safety of underground operations and prevent explosion risks (1).
5. Manhole Cover Status Monitoring: Tilt + displacement sensors to prevent theft and displacement, ensuring public safety (1).
6. Video Surveillance: Corrosion-resistant cameras installed at key nodes to provide visual assistance and support remote diagnosis (1).

2.2.2 Data Transmission and Communication Technology

The data transmission layer of IoT drainage pipe network systems adopts multiple communication technologies to ensure reliable data transmission:

1. Wireless Transmission Technology: 4G/5G, LoRa, NB-IoT and other technologies to achieve low-power, wide-coverage data backhaul. For example, buried water accumulation monitoring instruments transmit data through LoRa wireless spread spectrum signals, with built-in batteries that can last up to 5 years (1).
2. Wired Transmission Technology: Fiber optic networks ensure the stability of data transmission in key areas, suitable for fixed monitoring points such as reservoirs and pump stations (1).
3. Satellite Communication Technology: In remote mountainous areas or communication blind spots, the Beidou satellite short message function can ensure continuous data (1).
4. Edge Computing Technology: Data preprocessing and edge reasoning are implemented at the sensor end to reduce cloud pressure (1). Edge computing nodes achieve millisecond-level response speed, combined with adaptive control algorithms to complete multi-level coordination from macro area scheduling to micro valve adjustment.

2.2.3 Data Analysis and Intelligent Decision-making Technology

The platform layer and application layer of IoT drainage pipe network systems adopt multiple data analysis and intelligent decision-making technologies:

1. Big Data Analysis Technology: Standardized processing of multi-source heterogeneous data to eliminate redundancy and noise. For example, superimposing meteorological radar data, rain gauge measured data and drainage pipe network GIS data for analysis (1).
2. Artificial Intelligence Algorithms: Deep learning-based waterlogging prediction models can dynamically generate water level trend predictions and flood peak flow simulations by combining historical data with real-time monitoring results. For example, AI prediction models analyze ten years of historical data through machine learning, and the system in Suzhou New District can predict sewage overflow risks three hours in advance with 92% accuracy (1).
3. Digital Twin Technology: Building a virtual mirror image of urban water systems that synchronously maps the physical world in real time, assisting decision makers in simulating the effects of different drainage schemes. In a demonstration area in Chongqing, the three-dimensional model of the pipe network is updated synchronously with the physical system, allowing staff to "see through" the deformation of underground 5-meter pipes in a virtual scene (1).
4. Hydraulic Model Technology: Drainage hydraulic models are abstractions of real drainage pipe network systems, combined with related hydrological and hydraulic theoretical formulas. These mathematical models include rain models, surface runoff generation and concentration models, and pipeline transmission models. By setting model boundary conditions, they simulate the flow conditions in drainage pipe networks (1).
5. Intelligent Early Warning Technology: Set threshold values to automatically trigger alarms (such as water level exceeding limits, abnormal water quality), and link pump stations or emergency responses. Waterlogging alarms are triggered according to application needs, such as setting level exceeding warning values. Once the alarm conditions are triggered, linked response actions are initiated, that is, automatic start of pump stations + pushing emergency routes to mobile terminals (1).

III. Typical Application Cases of IoT Technology in Drainage Pipe Networks

3.1 Smart Drainage Pipe Network Information System Cases

3.1.1 Shenyang Smart Drainage Platform

Shenyang's smart drainage platform uses big data cleaning and fusion technology to integrate surveying and mapping data, IoT real-time data, and business approval data into a spatio-temporal database, supporting in-depth analysis such as pollution source tracing and waterlogging simulation. The main features and effects of this platform include:

1. Functional Features:
   • Can simulate waterlogging diffusion paths under different rainfall conditions to assist in formulating flood control plans.
   • Constructed a "single map of pipe networks", integrating more than 200 types of data such as pipeline attributes, operating status, and historical maintenance records.
   • Achieved a transformation from static management to dynamic control, promoting integrated management of drainage systems.
2. Implementation Effects:
   • Emergency response efficiency improved by more than 70%, truly realizing the transformation from "passive emergency response" to "active prevention and control".
   • Enhanced the city's flood control and drainage capacity, providing decision-making basis for urban planning, construction and management (1).

3.1.2 Chongqing Smart Drainage Pipe Network System

Chongqing has achieved remarkable results in smart drainage pipe network construction, with its main applications and features including:

1. Functional Features:
   • The three-dimensional model of the pipe network is updated synchronously with the physical system, allowing staff to "see through" the deformation of underground 5-meter pipes in a virtual scene.
   • Integrated smart drainage into the overall framework of "Digital Chongqing" to ensure interconnection and interoperability with emergency, environmental protection and other departments' systems.
   • Adopted a precise chemical dosing system that dynamically adjusts carbon source dosing according to incoming ammonia nitrogen load, reducing chemical consumption in wastewater treatment plants by 15%-20% (1).
2. Implementation Effects:
   • Maintenance costs reduced by 40%.
   • Smart manhole covers use solar power supply with a battery life of 5 years, reducing maintenance costs and energy consumption (1).

3.2 City-level Smart Drainage Platform Cases

3.2.1 Suyu District Smart Water Management Platform

The "One Network Management Area" system of the Comprehensive Command and Dispatch Center of Suyu District Data Bureau continues to gather information platforms from various units, especially the smart water management platform of the housing and construction department. As the "underground lifeline" of the city, the drainage system has undergone digital and intelligent upgrades through the application of big data, IoT, artificial intelligence and other cutting-edge technologies.

1. Implementation Content:
   • Detailed Exploration of Urban 脉络: A comprehensive inspection of the diameter, 走向，and geographical coordinates of rain and sewage pipes within approximately 670 kilometers of the central urban area and surrounding parks. Through the use of Geographic Information System (GIS) technology, all drainage facilities in the district were recorded into the platform, achieving "one map management" of drainage facilities.
   • Construction of Smart Perception System: Installed 160 sets of monitoring equipment, 134 level gauges, 42 video surveillance systems and 8 online waterlogging monitoring stations in key areas such as schools, sluice gates and pump stations to achieve 24-hour continuous visual monitoring.
   • Creation of Operational Management Center: Connected information such as urban drainage pipe networks, pump stations, sluice gates, rivers, waterlogging-prone points, wastewater treatment plants, and waterworks into the system according to platform data standards, establishing an efficient and scientific information-based dynamic management platform for drainage systems.
2. Implementation Effects:
   • During several rainstorms in 2024, through platform monitoring and timely dispatching and disposal, all road accumulations in the urban area were completely drained within half an hour after the rain, without serious water accumulation problems.
   • Construction of a pipe network topology management system that can automatically identify and recognize 7 types of topology problems such as rain-sewage mixing, large pipes connected to small pipes, and pipes leaking out of the ground, effectively enhancing the city's flood control and drainage capacity.
   • Promoted integrated management of drainage systems, effectively improving the healthy and efficient operation level of drainage systems, meeting the needs of sewage system quality improvement and efficiency enhancement, achieving integrated management of plants, stations, rivers and sources, and greatly enhancing governance effectiveness (1).

3.2.2 Zhongshan City Smart Drainage Platform

The urban smart drainage platform developed by the Zhongshan City Water Affairs Bureau constructs a "single map" of the drainage pipe network through census data, relies on IoT, big data and other technologies to monitor the operation status of the drainage pipe network in real time, assists in precise decision-making and risk early warning, and realizes unified dispatching of wastewater treatment plants, drainage pipe networks and pump gates, thereby improving the operation efficiency and stability of the drainage system.

1. Implementation Content:
   • Drainage Plant-Network Integration Project: Coordinating the operation and maintenance of urban wastewater treatment plants, drainage pipe networks and drainage pump gates.
   • Three-dimensional Visual Interface: Dynamically presents pipe network water levels, water quality, flow and other data to achieve visual management of drainage facilities.
   • Mobile Flood Control Emergency Rescue System: Including emergency equipment configuration, emergency response mechanism and actual combat experience, providing a reference model for urban waterlogging emergency disposal.
2. Implementation Effects:
   • Improved the operation efficiency and stability of the drainage system.
   • The application of amphibious rescue vehicles, large-flow drainage rescue vehicles and other equipment has enhanced emergency rescue capabilities (1).

3.3 Pipe Network Monitoring and Leakage Location Cases

3.3.1 Jinan Water Affairs Smart Leakage Control Noise Distribution System

The North City Water Supply Branch of Jinan Water Affairs Group has carried out noise distribution work in the irrigation area. By capturing pipeline vibration signals through probes and comparing acoustic characteristics, it can identify pinhole-level leaks and form a three-dimensional monitoring network covering main and branch pipes.

1. Technical Features:
   • Adopted the innovative mode of "noise distribution alarm + smart leakage control", building a scientific and technological defense line for precise monitoring and rapid response for urban underground pipe networks.
   • Once the system detects abnormal signal fluctuations, it can immediately issue an alarm, winning valuable time for timely leak detection, location and repair.
2. Implementation Effects:
   • Significantly optimized the leak detection operation process, improved the accuracy of leak detection, and greatly shortened the response time.
   • Effectively reduced water resource waste and reduced the leakage rate of pipe networks (1).

3.3.2 Application of H20 Intelligent Water Saving System in Pipe Network Leakage Location

As an innovative solution in the field of water resource management, the H20 intelligent water saving system constructs a three-dimensional monitoring system through IoT sensor networks and cloud computing platforms. Based on real-time data collection and combined with machine learning prediction models, the system forms a complete solution in four major scenarios: smart city water supply pipe networks, agricultural precision irrigation, industrial circulating water systems and commercial building water use.

1. Technical Features:
   • Pipe network leakage location: Adopts spatio-temporal convolutional neural networks to analyze parameters such as pipeline vibration frequency and flow anomalies.
   • Edge computing nodes achieve millisecond-level response speed, combined with adaptive control algorithms to complete multi-level coordination from macro area scheduling to micro valve adjustment.
   • Innovatively integrates negative pressure wave positioning technology with spectrum analysis method. By capturing low-frequency vibration signals below 0.5Hz, it can locate pipeline micro-leaks larger than 2mm within 30 minutes, with positioning accuracy up to ±1.5 meters.
2. Implementation Effects:
   • Reduced the pipe network leakage rate from the industry average of 15% to 4.8%, increasing the annual water saving benefit by 32 times.
   • Shortened the traditional manual inspection positioning cycle of 72 hours to within 45 minutes, with a leak point identification accuracy rate of 92.7% (1).

3.4 Waterlogging Monitoring and Early Warning Cases

3.4.1 Tianjin Urban Automatic Water Accumulation Monitoring and Early Warning System

Tianjin has constructed an intelligent urban waterlogging early warning system through "data elements × meteorological services" integration.

1. Implementation Content:
   • Hardware Upgrading: Developed narrowband IoT water level monitoring equipment suitable for complex environments such as bridges and culverts, with data collection frequency increased to 5 minutes/time.
   • Algorithm Optimization: Using neural network algorithms to calculate the correlation between precipitation intensity and water accumulation depth, generating water accumulation distribution maps for the next 1 hour.
   • Service Extension: Completed the construction of a mountain flood ditch water level monitoring experimental station in Jizhou District, collecting minute-level data in real time, and issuing risk warnings through a big data visualization platform.
   • Image Recognition: Intelligent cameras combined with AI algorithms can automatically identify road water accumulation depth and vehicle wading risks, and superimpose them onto a three-dimensional urban geographic information model.
   • Satellite Communication: In remote mountainous areas or communication blind spots, Beidou satellite short message function can ensure continuous data.
2. Implementation Effects:
   • Tianjin's urban automatic water accumulation monitoring and early warning system can link drainage equipment to drain 54 cm deep water accumulation within 1 hour.
   • Early warning time has been compressed from hour-level to minute-level, with a false alarm rate of less than 5%.
   • During Typhoon "Doksuri", through the system's rapid drainage, traffic paralysis and property losses were avoided (1).

3.4.2 Chuzhou Smart Drainage Monitoring System

Chuzhou's "four types of current situation data + three types of planning data" model can accurately predict the impact of new pipelines on existing pipe networks.

1. Technical Features:
   • Established a comprehensive data model system that integrates current situation data and planning data of pipe networks.
   • Adopted advanced data analysis and prediction technologies that can accurately assess the impact of new projects on existing pipe network systems.
2. Implementation Effects:
   • Improved the scientific nature of pipe network planning and construction, avoiding planning conflicts and potential Nimby effects.
   • Up to now, the system has provided support for the planning and approval of 29 municipal projects and 105.35 kilometers of municipal pipe networks, significantly improving the efficiency and quality of municipal project planning and approval (1).

3.5 IoT Application Cases in Village and Town Wastewater Treatment

3.5.1 Chongqing Environmental Investment Group IoT Automation System

The IoT automation system developed by Chongqing Environmental Investment Group is based on "edge intelligent computing + big data middle platform support + front-end application integration", tailored for village and town wastewater treatment plants, comprehensively realizing the operation status perception of village and town wastewater treatment plants.

1. Implementation Content:
   • The system integrates IoT automatic control technology to automatically adjust the operation mode of wastewater treatment plants at low cost, and uses AI supervision assistance to carry out abnormality early warning, providing protection for safe and stable operation.
   • The system forms a "one plant, one standard spectrum" through big data analysis, and issues early warnings for situations of high energy consumption and high drug consumption in non-precision operation status, providing data support for rapid response and decision analysis, and promoting cost reduction and efficiency improvement in village and town wastewater treatment.
2. Implementation Effects:
   • The system's automatic control has reduced the average electricity consumption per ton of water in wastewater treatment facilities by 24%, and the average drug consumption per ton of water by 11%.
   • Achieved digital innovation to empower operation quality improvement and cost reduction and efficiency enhancement, jointly building a new chapter of digital villages and beautiful villages (1).

3.5.2 Hudong Village Wastewater Treatment Project

In 2024, Hudong Village in Ningxi Street upgraded and transformed its wastewater treatment project to improve the regional water environment and enhance the quality of the living environment.

1. Implementation Content:
   • Optimized the wastewater pipe network system, introduced advanced wastewater treatment processes, constructed complete supporting facilities and other measures to enhance domestic wastewater treatment capacity and ensure up-to-standard discharge of water quality.
   • Adopted the multi-stage biological contact oxidation process, which combines the characteristics of both activated sludge process and biological filter, and can achieve stable effluent results.
2. Implementation Effects:
   • Improved the regional water environment and enhanced the quality of the living environment.
   • Ensured up-to-standard discharge of water quality and protected local water resources (1).

IV. Operational Processes of IoT Drainage Pipe Network Systems

4.1 System Planning and Design Process

4.1.1 Needs Research and Scheme Design

1. Needs Research:
   • Conduct a detailed investigation of the layout, scale, and operation characteristics of urban drainage pipe networks to determine the location and quantity of monitoring points.
   • Analyze the defects and needs of existing systems, and clarify the functional requirements of IoT drainage pipe network systems.
   • Determine the overall objectives and technical routes of the system, and formulate project implementation plans.
2. Scheme Design:
   • Design the technical scheme for IoT drainage pipe networks based on the results of needs research.
   • Determine system architecture, equipment selection, communication methods and data processing methods.
   • Develop detailed technical schemes, including hardware configuration, software functions, system interfaces, etc.
   • Conduct investment estimation and benefit analysis to form a project feasibility study report.

4.1.2 System Design and Equipment Procurement

1. System Design:
   • Conduct detailed system design, including perception layer design, transmission layer design, platform layer design and application layer design.
   • Design data collection schemes, data transmission schemes, data storage schemes and data analysis schemes.
   • Design system security schemes to ensure the security and reliability of system data.
   • Design system interfaces to ensure interconnection and interoperability with other systems.
2. Equipment Procurement:
   • According to the system design scheme, procure hardware equipment such as sensors, data acquisition equipment, communication equipment, servers, etc.
   • Procure or develop system software, including data processing software, data analysis software, application display software, etc.
   • Conduct equipment acceptance to ensure that the equipment meets design requirements and technical standards.

4.2 System Implementation and Deployment Process

4.2.1 Hardware Equipment Installation and Debugging

1. Sensor Deployment:
   • Install water level sensors, flow sensors, water quality sensors and other equipment at key nodes of drainage pipe networks.
   • Install data acquisition terminals and communication equipment to ensure the normal operation of equipment and data accuracy.
   • Install servers and other hardware equipment to build the system hardware platform.
2. Equipment Debugging:
   • Calibrate sensors to ensure data accuracy and reliability.
   • Test data acquisition equipment and communication equipment to ensure the stability and timeliness of data transmission.
   • Conduct system joint debugging to ensure the coordinated operation of various equipment.

4.2.2 Software System Development and Integration

1. Software System Development:
   • Develop data acquisition and processing software to achieve data acquisition, storage and preliminary processing.
   • Develop data analysis and mining software to achieve in-depth analysis and mining of data.
   • Develop application display software to achieve visual display of data and application functions.
   • Develop system management software to achieve system configuration, monitoring and maintenance functions.
2. System Integration:
   • Integrate hardware equipment and software systems to form a complete IoT drainage pipe network system.
   • Conduct system testing, including functional testing, performance testing, security testing, etc.
   • Optimize the system to improve its stability, reliability and efficiency.

4.3 System Operation and Maintenance Process

4.3.1 System Trial Operation and Optimization

1. System Trial Operation:
   • Conduct system trial operation, collect operation data, and evaluate system performance.
   • Conduct a comprehensive test of the system, including functional testing, performance testing, security testing, etc.
   • Identify and solve problems in system operation, optimize system parameters and configuration.
2. System Optimization:
   • According to the results of the trial operation, optimize the system to improve its stability, reliability and efficiency.
   • Adjust sensor layout and parameter settings to optimize data acquisition effects.
   • Optimize data analysis models and algorithms to improve the accuracy and efficiency of data analysis.
   • Improve application functions and interface design to enhance user experience.

4.3.2 System Formal Operation and Maintenance

1. System Formal Operation:
   • The system is officially put into operation, beginning real-time monitoring and management of drainage pipe networks.
   • Establish system operation management systems to standardize system operation and management processes.
   • Conduct system training to improve the skills and levels of operators.
2. System Maintenance:
   • Regularly maintain and service the system, including cleaning equipment surfaces, checking equipment operating status, calibrating equipment parameters, etc.
   • Regularly calibrate and maintain sensors to ensure data accuracy and reliability.
   • Timely handle system failures and anomalies to ensure the normal operation of the system.
   • Regularly upgrade and optimize the system to improve its performance and functions.
   • Establish and improve equipment maintenance files, record equipment maintenance situations and fault handling processes, providing a basis for equipment management and renewal.

4.4 Data Analysis and Decision-making Process

4.4.1 Data Acquisition and Processing

1. Data Acquisition:
   • Sensors collect water level, flow, water quality and other data of drainage pipe networks in real time.
   • Data acquisition equipment preprocesses and stores the collected data.
   • Data is transmitted to the data center or cloud platform through communication networks.
2. Data Processing:
   • Clean, transform and integrate the collected data to eliminate data noise and inconsistencies.
   • Standardize and normalize the data to improve data comparability and usability.
   • Store and manage data, establish data warehouses or databases.

4.4.2 Data Analysis and Decision-making

1. Data Analysis:
   • Conduct statistical analysis on data to understand the operation status and patterns of drainage pipe networks.
   • Conduct correlation analysis on data to discover correlation relationships and patterns between data.
   • Conduct predictive analysis on data to predict the future operation trends and potential problems of drainage pipe networks.
   • Conduct anomaly detection on data to identify abnormal situations and potential risks in drainage pipe networks.
2. Decision Support:
   • Generate decision suggestions and early warning information based on data analysis results.
   • Display data analysis results and decision suggestions through visual interfaces.
   • Support managers in making decisions and scheduling to optimize the operation management of drainage pipe networks.
   • Generate various reports and provide data support for management decisions.

V. Comparative Analysis of IoT Technology and Other Drainage Pipe Network Technologies

5.1 Comparison between IoT Technology and Traditional Drainage Pipe Network Technology

 

Comparison Item	Traditional Drainage Pipe Network Technology	IoT Drainage Pipe Network Technology
Monitoring Method	Mainly manual inspection, supplemented by a small number of fixed monitoring equipment	Comprehensive deployment of sensor networks to achieve real-time and automatic monitoring
Data Acquisition	Low data acquisition frequency, small amount of data	High data acquisition frequency, large amount of data, multi-dimensional data fusion
Data Analysis	Simple statistical analysis, relying on manual judgment	Big data analysis, artificial intelligence algorithms, intelligent analysis and decision-making
Fault Location	Inaccurate positioning, relying on experience judgment	Precise positioning, based on data analysis and model calculation
Emergency Response	Slow response, relying on manual dispatching	Fast response, automatic early warning and intelligent dispatching
Maintenance Management	Regular maintenance, passive response	Predictive maintenance, proactive prevention
Management Efficiency	Low, high labor cost	High, high degree of automation, low labor cost
Decision Support	Lack of data support, subjective decision-making	Data-driven decision-making, scientific and accurate
Investment Cost	Low initial investment, but high long-term maintenance cost	High initial investment, but low long-term operation cost
Application Effect	Late fault detection, high waterlogging risk, low management efficiency	Timely fault early warning, reduced waterlogging risk, high management efficiency

5.2 Comparison between IoT Technology and SCADA System

 

Comparison Item	SCADA System	IoT Drainage Pipe Network Technology
System Architecture	Centralized architecture, equipment communication relies on dedicated network	Distributed architecture, flexible and diverse equipment communication
Equipment Interconnection	Poor equipment interconnection, limited scalability	Highly interconnected equipment, strong scalability
Data Processing	Limited data processing capacity, mainly used for monitoring	Strong data processing capacity, supporting in-depth analysis and mining
Intelligent Functions	Basic logic control, limited intelligent functions	Powerful intelligent functions, supporting prediction, optimization, etc.
Cost-effectiveness	High hardware cost, limited software functions	Relatively low hardware cost, powerful software functions
Deployment Flexibility	Complex deployment, poor flexibility	Simple deployment, strong flexibility
Applicable Scenarios	Large industrial control systems, suitable for fixed scenarios	Widely applicable to various scenarios, especially complex and changeable environments

5.3 Comparison between IoT Technology and GIS System

 

Comparison Item	GIS System	IoT Drainage Pipe Network Technology
Data Type	Mainly processes static geographic data	Processes dynamic real-time data combined with static data
Functional Focus	Geographic information management and analysis, strong spatial analysis functions	Real-time monitoring and control, data analysis and decision support
Timeliness	Long data update cycle, poor timeliness	Real-time data update, strong timeliness
Interactivity	Mainly used for query and analysis, limited interactivity	Supports real-time interaction and control, strong interactivity
System Integration	Difficult to integrate with other systems	Easy to integrate with other systems, good openness
Application Scenarios	Suitable for planning, design and analysis stages	Suitable for operation, management and decision-making stages
Development Trend	Developing towards Web GIS and 3D GIS	Developing towards intelligence, networking and servitization

5.4 Comparison between IoT Technology and Manual Inspection

 

Comparison Item	Manual Inspection	IoT Drainage Pipe Network Technology
Work Efficiency	Low, limited inspection range	High, can achieve full coverage monitoring
Data Accuracy	Greatly affected by human factors, unstable accuracy	Objective and accurate, not affected by human factors
Safety Risk	High, especially in underground and dangerous areas	Low, reduces personnel entering dangerous areas
Cost-effectiveness	High labor cost, high long-term cost	Higher initial investment, but lower long-term cost
Monitoring Frequency	Low, regular inspection	High, real-time monitoring
Fault Discovery	Lagging, relying on accidental discovery	Timely, real-time early warning
Data Recording	Incomplete, difficult to preserve and analyze for a long time	Complete, can be preserved and analyzed in depth for a long time
Adaptability	Strong adaptability, but affected by personnel quality	Strong adaptability, high standardization

5.5 Summary of Advantages and Characteristics of IoT Technology

Based on the above comparative analysis, IoT technology has the following significant advantages and characteristics in drainage pipe network management:

1. Comprehensive Perception Capability: Through the deployment of 大量 sensors, it achieves all-round and real-time perception and monitoring of drainage pipe networks, obtaining rich and accurate data.
2. Efficient Data Transmission: Adopting various communication technologies to ensure reliable and real-time data transmission, realizing remote monitoring and control.
3. Intelligent Data Analysis: Combining big data analysis and artificial intelligence technology to achieve intelligent analysis and prediction of drainage pipe network operation status, providing scientific decision support.
4. Precise Early Warning Capability: Based on real-time data and intelligent algorithms, it can detect potential risks in advance, issue early warnings in a timely manner, and reduce waterlogging and other risks.
5. Remote Control Function: Supports remote control of drainage pump stations, valves and other equipment, realizes intelligent dispatching and management, and improves emergency response capabilities.
6. Data-driven Decision-making: Through the analysis and mining of massive data, it provides a scientific basis for the planning, design, renovation and operation of drainage pipe networks, realizing data-driven decision-making.
7. Full Life Cycle Management: Supports the full life cycle management of drainage pipe networks from planning and design to construction and operation to maintenance and renewal, forming a complete closed loop.
8. Significant Cost-effectiveness: Although the initial investment is relatively high, the long-term operation cost is low, which can effectively reduce maintenance costs and waterlogging losses.
9. Strong System Expandability: The system architecture is flexible, equipment interconnection is strong, easy to expand and upgrade, and adapts to future development needs.
10. Integration and Sharing Capability: Can integrate with other systems, realize data sharing and business collaboration, and enhance the overall management level of the city.

VI. Domestic Relevant Standards for IoT Drainage Pipe Network Systems

6.1 National Standards

6.1.1 Technical Requirements for Data Transmission of Pollutant Automatic Monitoring and Control Systems (HJ 212-2025)

HJ 212-2025 "Technical Requirements for Data Transmission of Pollutant Automatic Monitoring and Control Systems" is a revision of "Data Transmission Standard for On-line Monitoring (Monitoring) Systems" (HJ 212-2017), which will come into effect on January 1, 2026.

1. Main Content:
   • Specifies the system structure of pollutant automatic monitoring and control systems, the protocol hierarchy between field machines and upper computers, the communication protocol between field machines and upper computers, the communication methods between automatic monitoring field instruments and data acquisition instruments, and the technical requirements for data acquisition, processing and uploading.
   • Adds terms and definitions such as "power consumption monitoring", "video monitoring", and "data marking".
   • Adds requirements related to "communication security" and "communication bandwidth requirements between field machines and upper computers".
   • Adds coding rules for monitoring parameters such as "power consumption" and "key production conditions".
   • Improves "data marking content".
   • Adds requirements for data acquisition, processing and uploading.
   • Appendix A adds examples of data segment encryption and key management processes.
   • Appendix B improves the classification and coding table of field equipment and the coding table of field information; adds the classification and coding table of facility power consumption monitoring, the coding table of facility power consumption monitoring parameters, the classification and coding table of key production conditions by industry, and the coding table of key production condition parameters.
   • Appendix D deletes the calculation methods for real-time and minute emissions of water pollutants, the calculation methods for minute and hour values (weighted average method) of water pollutant concentrations, and the calculation methods for minute, hour and daily average values (arithmetic average method) of flue gas data; modifies the calculation methods for hourly and daily emissions of water pollutants, and the calculation methods for daily average values (weighted average method) of water pollutant concentrations.
   • Adds Appendix E communication protocol between data acquisition instruments and mobile terminals.
   • Adds Appendix F confirmation form for networking information of pollutant emission automatic monitoring equipment.
   • Adds Appendix G effectiveness determination method for pollutant emission automatic monitoring data.
   • Adds Appendix H technical requirements for multimedia file transmission.
2. Standard Significance:
   • The biggest change in HJ 212-2025 compared to the 2017 version is the upgrade from "on-line monitoring" to an "automatic monitoring + intelligent monitoring" integrated system, realizing the deep integration of pollutant monitoring, power consumption monitoring, condition identification, video monitoring and data security.
   • For the first time, power consumption data, key production conditions, access control status, VOCs spectra, noise recordings, video streams, etc. are included in the mandatory transmission scope, constructing a data closed loop covering the whole chain of "pollution discharge-treatment-supervision-evidence collection".
   • Enhanced data security requirements, improving the reliability and security of the system (1).

6.1.2 Technical Requirements for On-line Monitoring System of Urban Drainage Water Quality and Quantity (CJ/T 252-2011)

CJ/T 252-2011 "Technical Requirements for On-line Monitoring System of Urban Drainage Water Quality and Quantity" is a technical standard for on-line monitoring systems of urban drainage water quality and quantity issued by the Ministry of Housing and Urban-Rural Development.

1. Main Content:
   • Specifies the general requirements, technical requirements, test methods, inspection rules, and marking, packaging, transportation and storage of urban drainage water quality and quantity on-line monitoring systems.
   • Clarifies the composition and functional requirements of on-line monitoring systems.
   • Specifies the technical indicators and performance requirements of monitoring equipment.
   • Proposes requirements for system installation, debugging and acceptance.
2. Standard Significance:
   • Provides a technical basis for the design, construction and operation of urban drainage water quality and quantity on-line monitoring systems.
   • Standardizes the performance and technical indicators of monitoring equipment to ensure the accuracy and reliability of monitoring data.
   • Guides system installation and debugging, improving system stability and reliability.
   • In Article 5.3 of Chapter 5 "General Requirements" of this standard, it is clearly stipulated that the service life of related instruments is generally 5 years, which can be adjusted as appropriate under harsh or special working conditions (1).

6.1.3 Technical Requirements for Urban Smart Drainage Pipe Network Systems (T/CAS 784-2023)

T/CAS 784-2023 "Technical Requirements for Urban Smart Drainage Pipe Network Systems" is a Chinese group standard that specifies the basic provisions, system architecture, perception layer, infrastructure layer, platform layer, application layer, user layer, operation management system and security system architecture and technical standards and specifications for urban smart drainage pipe network systems.

1. Main Content:
   • Specifies the basic provisions, system architecture, perception layer, infrastructure layer, platform layer, application layer, user layer, operation management system and security system architecture and technical standards and specifications for urban smart drainage pipe network systems.
   • Applies to the operation, design and implementation of urban smart drainage pipe network systems.
   • Specifies the terms and definitions of smart drainage pipe network systems, including smart drainage pipe network systems, drainage hydraulic models, water affairs big data, drainage pipe network facilities, etc.
   • Clarifies the technical requirements and performance indicators of the system.
2. Standard Significance:
   • Provides a technical basis for the design, construction and operation of urban smart drainage pipe network systems.
   • Standardizes the architecture and technical requirements of the system, promoting the standardization and normalization of smart drainage pipe network systems.
   • Improves the reliability, security and interoperability of the system, promoting system integration and sharing (1).

6.2 Local Standards

6.2.1 Technical Standard for Smart Drainage Pipe Networks in Chongqing (DBJ50/T-XXX-2024)

The "Technical Standard for Smart Drainage Pipe Networks" issued by Chongqing is a local standard for smart drainage pipe networks in Chongqing.

1. Main Content:
   • Specifies the technical requirements for the planning, design, construction, acceptance and operation and maintenance of smart drainage pipe networks.
   • Applies to the planning, design, construction, acceptance and operation and maintenance of smart drainage pipe networks in Chongqing.
   • The standard system includes basic standards, technical standards, data standards, construction and operation standards, information security standards, etc.
   • The construction of smart drainage pipe network support platforms includes the construction of data platforms, model platforms, business platforms, etc.
   • Puts forward power supply requirements for outdoor monitoring equipment, which should preferably use a combination of solar energy and rechargeable batteries, and should be able to work normally under non-sunlight conditions.
   • Provides specific regulations for the selection of rain gauges.
2. Standard Significance:
   • Provides a technical basis for the construction and management of smart drainage pipe networks in Chongqing.
   • Promotes the standardized and normalized construction of smart drainage pipe networks in Chongqing.
   • Improves the management level and operation efficiency of drainage pipe networks in Chongqing (1).

6.2.2 Spatial Data Standard for "One Map" of Drainage Pipe Networks in Chuzhou City (Trial)

Based on national pipeline detection and system construction standards, Chuzhou City has compiled the "Spatial Data Standard for 'One Map' of Drainage Pipe Networks in Chuzhou City (Trial)" in combination with the actual situation of Chuzhou, and developed supporting data quality inspection software.

1. Main Content:
   • Specifies the technical requirements for data collection, processing, storage and transmission of drainage pipe networks.
   • Puts forward requirements for the standardization, integrity, accuracy and logic of drainage pipe network data.
   • Specifies the quality inspection and acceptance methods for drainage pipe network data.
   • Specifies the requirements for data update and maintenance of drainage pipe networks.
2. Standard Significance:
   • Provides a technical basis for the construction and operation of the "One Map" system of drainage pipe networks in Chuzhou City.
   • Ensures the quality and consistency of drainage pipe network data, improving data availability and sharing.
   • Supports the information management and intelligent construction of drainage pipe networks in Chuzhou City (1).

6.3 Standard Compliance Suggestions

To ensure that IoT drainage pipe network systems comply with relevant domestic standards, the following measures are recommended:

1. System Design Stage:
   • Refer to standards such as HJ 212-2025, CJ/T 252-2011, T/CAS 784-2023, etc., to design the architecture, functions and technical parameters of the system.
   • According to local standards, such as Chongqing's "Technical Standard for Smart Drainage Pipe Networks", Chuzhou's "Spatial Data Standard for 'One Map' of Drainage Pipe Networks", etc., carry out targeted design.
   • Ensure that the system's security design complies with national information security related standards, such as "Information Security Technology Network Security Level Protection Basic Requirements" (GB/T22239), etc.
2. Equipment Selection Stage:
   • Select hardware equipment such as sensors, data acquisition equipment, communication equipment, etc., that comply with national standards and industry standards.
   • Ensure that equipment performance indicators meet relevant standard requirements, such as accuracy, stability, reliability, etc.
   • Select certified equipment to ensure that the equipment complies with relevant standards and specifications.
3. System Implementation Stage:
   • Install, debug and accept equipment in accordance with relevant standard requirements.
   • Ensure that system data acquisition, transmission, storage and processing comply with relevant standard requirements.
   • Establish and improve system operation management systems and operating procedures to ensure the normal operation and maintenance of the system.
4. System Operation Stage:
   • Regularly maintain and calibrate the system to ensure that system performance meets relevant standard requirements.
   • Manage and apply data in accordance with relevant standard requirements to ensure data accuracy and reliability.
   • Regularly conduct system security assessments and risk assessments to ensure system security and compliance.
   • Timely update system software and hardware to ensure that the system complies with the latest standards and specifications.
5. Data Management Stage:
   • Collect, process and transmit data in accordance with HJ 212-2025 and other standards to ensure data integrity and accuracy.
   • Establish and improve data management systems to ensure data security and confidentiality.
   • Store and back up data in accordance with relevant standard requirements to ensure data reliability and recoverability.
   • Share and exchange data in accordance with relevant standard requirements to ensure data compliance and interoperability.

VII. Future Development Trends and Recommendations

7.1 Development Trends of IoT Technology in Drainage Pipe Networks

1. Technology Integration Trends:
   • Deep Integration of AI and IoT: AI prediction models analyze historical data through machine learning, which will further improve the accuracy and timeliness of predictions.
   • Deepening Application of Digital Twin Technology: Digital twin technology will achieve real-time synchronous update of three-dimensional pipe network models and physical systems, providing more intuitive and accurate support for pipe network management.
   • Integration of 5G and IoT: The high-speed and low-latency characteristics of 5G technology will further enhance the communication capabilities and response speed of IoT devices.
   • Combination of Edge Computing and IoT: Edge computing technology will enable IoT devices to have stronger local data processing capabilities, reduce cloud pressure, and improve system response speed.
2. System Function Expansion Trends:
   • Multi-functional Integration: IoT drainage pipe network systems will integrate more functions, such as water quality monitoring, gas monitoring, flow monitoring, etc., to achieve multi-functional integrated monitoring.
   • Increased Intelligence: Systems will have stronger autonomous decision-making capabilities to achieve fully automated control of pipe network operations.
   • Predictive Maintenance: Through analysis of equipment operation data, the system will be able to predict equipment failures, carry out maintenance in advance, and reduce failure rates and maintenance costs.
   • Resource Recycling: Systems will not only focus on drainage functions, but also pay attention to water resource recycling and energy recovery to achieve sustainable development.
3. Expansion of Application Scenarios:
   • City-level Integrated Management: IoT drainage pipe network systems will deeply integrate with other urban infrastructure systems, such as linking with intelligent transportation systems to promptly release traffic information and guide vehicles around waterlogged sections.
   • Regional Collaborative Governance: Systems will support cross-regional and cross-departmental collaborative governance, forming a regional integrated drainage management system.
   • Public Participation: Systems will provide real-time water accumulation data and disaster prevention guidelines to the public through mobile APPs, WeChat official accounts and other channels, enhancing public participation.
   • Carbon Footprint Management: Systems will account for energy consumption and carbon emissions from pipe network maintenance, helping achieve the "dual carbon" goals (1).

7.2 Recommendations for IoT Drainage Pipe Network System Construction

1. Overall Planning and Step-by-step Implementation:
   • Develop an overall plan and long-term development strategy for IoT drainage pipe network systems, clarifying construction objectives and paths.
   • Promote system construction in accordance with the principle of "overall planning, step-by-step implementation, key breakthroughs, and gradual improvement" to ensure construction continuity and consistency.
   • Give priority to pilot construction in waterlogging-prone areas, important areas and problem-prone areas, summarize experience, and then promote it comprehensively.
2. Data-driven, Intelligent Decision-making:
   • Give full play to the data acquisition advantages of IoT technology, establish a comprehensive and accurate drainage pipe network database.
   • Strengthen data analysis and mining, improve the utilization value of data, and provide scientific basis for decision-making.
   • Establish and improve data sharing mechanisms, break down information silos, and promote data circulation and utilization.
3. Resource Integration and Collaborative Promotion:
   • Integrate resources from government departments, research institutions, enterprises and other parties to form a joint force to promote the construction of IoT drainage pipe network systems.
   • Establish and improve cross-departmental and cross-regional collaborative work mechanisms to form a unified and coordinated management system.
   • Strengthen cooperation with universities and research institutes to carry out research and innovation on key technologies, and improve the technical level of the system.
4. Emphasis on Standards and Security Assurance:
   • Strictly follow relevant national and local standards and specifications to ensure system compliance and interoperability.
   • Strengthen system security guarantees, establish and improve network security protection systems, and ensure system and data security.
   • Pay attention to data privacy protection, comply with relevant laws and regulations, and protect user privacy and data security.
5. Strengthen Operation and Maintenance, Continuous Optimization:
   • Establish and improve system operation and maintenance mechanisms to ensure the normal operation of the system and data continuity.
   • Strengthen the training and management of operation and maintenance personnel, improve their professional quality and skill level.
   • Continuously optimize and upgrade the system to adapt to changing needs and technological developments.
   • Establish a system evaluation mechanism, regularly evaluate the performance, effectiveness and value of the system, and provide a basis for system improvement.

7.3 Recommendations for Engineering and Technical Personnel

1. Strengthen Learning and Improve Skills:
   • Study new technologies such as IoT, big data, artificial intelligence, etc., and master the principles and applications of smart drainage pipe network systems.
   • Study relevant standards and specifications to understand the technical requirements for system construction and operation.
   • Participate in professional training and academic exchanges to understand the latest development trends and technical trends in the industry.
2. Focus on Practice and Accumulate Experience:
   • Actively participate in the planning, design, implementation and operation and maintenance of IoT drainage pipe network systems, and accumulate practical experience.
   • Summarize project experience and lessons learned to form replicable and promotable solutions and best practices.
   • Participate in industry case studies and analyses, and learn from successful experiences and advanced technologies.
3. Innovative Thinking to Solve Problems:
   • Apply innovative thinking and methods to solve practical problems in the construction and operation of IoT drainage pipe network systems.
   • Explore the application of new technologies and methods in drainage pipe network management, and promote technological innovation and application innovation.
   • Pay attention to cutting-edge technologies and development trends in the industry, and actively explore future development directions and models.
4. Team Collaboration and Common Development:
   • Strengthen cooperation with personnel from different professions and fields to form a team with complementary advantages.
   • Share experience and knowledge to promote the common growth and development of team members.
   • Participate in industry organizations and communities, exchange and cooperate with peers, and jointly promote industry development.
5. Pay Attention to Standards and Ensure Compliance:
   • Pay attention to the formulation and update of relevant national and local standards and specifications, and promptly understand the latest requirements.
   • Strictly follow relevant standards and specifications in work to ensure system compliance and reliability.
   • Participate in the formulation and revision of standards to contribute to industry development.

VIII. Conclusion

This article has elaborated on the application of IoT technology in drainage pipe networks in detail. Through the analysis of the technical architecture, typical cases, operation processes, technical comparisons and relevant standards of IoT drainage pipe network systems, the following conclusions are drawn:

1. IoT technology provides a revolutionary solution for drainage pipe network management. Through comprehensive perception, reliable transmission, intelligent processing and accurate decision-making, IoT technology can effectively solve many challenges faced by traditional drainage pipe network management, significantly improving the operational efficiency and management level of drainage pipe networks.
2. IoT drainage pipe network systems have been widely applied across the country. From city-level smart drainage platforms in Shenyang, Chongqing, Suyu District, etc., to special applications such as Jinan Water Affairs and Tianjin waterlogging monitoring, IoT technology has demonstrated remarkable results in drainage pipe network management, including more than 70% improvement in emergency response efficiency, 40% reduction in maintenance costs, and reduction of leakage rates from 15% to 4.8%.
3. The operation process of IoT drainage pipe network systems includes system planning and design, system implementation and deployment, system operation and maintenance, data analysis and decision-making, etc.. The standardized implementation of these processes is crucial to ensuring the stable operation and effective application of the system.
4. Compared with traditional drainage pipe network technology, SCADA systems, GIS systems, etc., IoT technology has significant advantages such as comprehensive perception, efficient transmission, intelligent analysis, accurate early warning, and remote control, and is the mainstream technical direction for future drainage pipe network management.
5. The construction and application of IoT drainage pipe network systems need to follow relevant national standards and local standards, such as HJ 212-2025, CJ/T 252-2011, T/CAS 784-2023, etc., to ensure system compliance and interoperability.
6. The application of IoT technology in drainage pipe networks will develop towards technology integration, functional expansion, and scenario expansion, and will achieve more intelligent, collaborative, and sustainable drainage pipe network management in the future.

In summary, the application of IoT technology in drainage pipe networks is an important means to improve urban drainage management levels, enhance urban flood control and drainage capabilities, and improve the urban water environment. With the continuous advancement of technology and in-depth application, IoT drainage pipe network systems will play an increasingly important role in smart city construction, providing strong support for the sustainable development of cities.

Engineering and technical personnel should fully understand the application value and development trends of IoT technology in drainage pipe networks, strengthen learning, focus on practice, think innovatively, and jointly promote the development and application of IoT drainage pipe network technology, contributing to urban drainage management.

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