Intelligent monitoring system for village and town rain sewage pipe network

Abstract

The invention discloses an intelligent monitoring system for a village and town rain and sewage pipe network, which relates to the technical field of village and town rain and sewage management and control and comprises an equipment construction module, a data acquisition and transmission module, a storage management module, an analysis processing module, a display output module, a remote supervision module and an intelligent supervision module. According to the intelligent monitoring system for the village and town rain and sewage pipe network, monitoring point positions can be reasonably increased and monitoring equipment can be installed and deployed according to actual conditions of village and town areas, so that the running state and sewage discharge conditions of the pipe network can be comprehensively reflected, and meanwhile, an efficient data transmission and processing flow is established; the accuracy and reliability in the monitoring data transmission process are improved through a verification mechanism, meanwhile, the monitoring data are analyzed and mined by means of big data, cloud computing and other technical means, decision support is provided for managers, intelligent and automatic monitoring of a rain and sewage pipe network is promoted, and the management efficiency is improved. The problem that manual monitoring is low in working efficiency and prone to errors is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of rainwater and sewage control in towns and villages, and specifically to an intelligent monitoring system for rainwater and sewage pipe networks in towns and villages. Background Art

[0002] As an important part of water resources management and environmental protection, rainwater and sewage control is of great significance for protecting water sources, preventing and controlling water pollution, and promoting sustainable development. In recent years, with the increasing attention paid by the country to environmental protection, rainwater and sewage control in towns and villages has become an important part of environmental governance, and documents such as "Data Transmission Standard for Online Pollutant Monitoring (Monitoring) System" (HJ212-2017) and "Technical Specification for Sewage Monitoring" (HJ 91.1-2019) have been issued to clearly regulate the technical standards for monitoring. At present, a relatively mature technical system has been formed in the field of rainwater and sewage control at home and abroad, including rainwater and sewage diversion technology, biological treatment technology, membrane treatment technology, etc. These technologies not only improve the efficiency of sewage treatment, but also reduce the treatment cost, providing strong technical support for rainwater and sewage control in towns and villages.

[0003] Although the background of rainwater and sewage control is becoming increasingly mature, the current situation of township sewage treatment is still not optimistic. There are still some obvious defects in the monitoring of township rainwater and sewage pipe networks, as follows: First, due to funding and technical limitations, the number of monitoring points for rainwater and sewage pipe networks in some townships is insufficient, which cannot fully reflect the operation status of the pipe network and sewage discharge. In addition, the monitoring equipment for rainwater and sewage pipe networks in some townships is outdated and may not accurately reflect the real-time status of the pipe network, resulting in data distortion or omissions, and cannot meet modern monitoring needs. Secondly, existing monitoring systems generally have problems with slow data transmission speeds and low processing efficiency, which results in the inability to promptly feedback monitoring results to managers, affecting the timeliness and accuracy of decision-making. In addition, rainwater and sewage pipe network monitoring in some township areas still relies on manual inspections and records, lacking intelligent and automated monitoring methods, resulting in low work efficiency and prone to errors.

[0004] Therefore, it is urgent to improve this shortcoming. The present invention studies and improves the existing structure and deficiencies, and provides an intelligent monitoring system for township rainwater and sewage pipe networks. Summary of the invention

[0005] The purpose of the present invention is to provide a smart monitoring system for township rainwater and sewage pipe networks to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: A smart monitoring system for a township rainwater and sewage pipe network, comprising: an equipment construction module, a data acquisition and transmission module, a storage management module, an analysis and processing module, a display output module, a remote supervision module and an intelligent supervision module; The equipment construction module is responsible for installing and deploying various monitoring equipment, and collecting key data such as water quality, flow, pressure, liquid level, etc. in the pipe network in real time through the monitoring equipment to provide data support; The data acquisition and transmission module is responsible for collecting the raw data collected by the monitoring equipment in real time, and transmitting it to the central server or cloud platform for storage and processing by wired or wireless means, and a verification mechanism is adopted during the data transmission process; The storage management module is responsible for storing and managing the received data, including establishing a database, data backup and recovery mechanism, data authority management, and building an efficient data storage architecture; The analysis and processing module uses data analysis algorithms and models to deeply mine and process the stored data, extract valuable information, and generate statistical reports, monitoring and early warning, etc. The display output module is responsible for visual display, presenting the monitoring data to users in an intuitive manner, such as displaying the operation status and monitoring data of the pipeline network in the form of charts, maps, etc., and supports report output, generates monitoring reports and analysis results, and sends them to regulatory authorities for decision-making and management; The remote monitoring module is responsible for providing a user operation interface, allowing management personnel to monitor the operation status of the pipeline network in real time through remote network access, and to remotely control and operate the system; The intelligent supervision module realizes intelligent management of the township rainwater and sewage pipe networks from two aspects: fault warning and maintenance management based on real-time monitoring.

[0007] Furthermore, the monitoring equipment includes flow meters, water quality monitoring instruments, liquid level meters, pressure sensors, gas monitors, rainfall sensors, pipeline CCTV inspection robots, manhole cover displacement monitors, and smart cameras, and all hardware equipment is selected from existing products that are relatively mature in the market and meet relevant technical standards; Flow meter: a device used to measure and record the flow of rainwater and sewage, capable of monitoring the flow changes of rainwater and sewage in the pipeline in real time; Water quality monitoring equipment: equipment that monitors and analyzes the quality of rainwater and sewage in real time. It can detect various water quality indicators in rainwater and sewage, so as to judge the water quality level and treatment effect of rainwater and sewage; Liquid level meter: used to monitor the liquid level in the pipeline in real time. The liquid level meter can be used to determine the flow rate and flow rate in the pipeline to prevent sewage overflow and determine the operating status of the pump station; Pressure sensor: Set pressure monitoring points in the pressure-carrying drainage pipe section to monitor the pressure changes in the pipe in real time; Gas monitor: used to monitor the concentration of harmful gases such as hydrogen sulfide and methane in the pipeline; Rainfall sensor: installed at appropriate locations to monitor rainfall conditions and help analyze changes in the flow of rainwater entering the pipe network; Pipe CCTV inspection robot: a device used for video and inspection inside pipelines. Through remote control, the robot can move inside drainage pipes and transmit images of the inside of the pipes in real time. Manhole cover displacement monitor: used to monitor the position status of the manhole cover in real time; Smart Camera: Equipped with a high-definition camera and intelligent analysis function, it can monitor the operating status of key nodes in the pipeline network in real time and identify abnormal situations through image recognition technology.

[0008] Furthermore, the verification mechanism calculates and compares the transmitted data to detect whether the data is erroneous or lost during the transmission process, specifically including: Parity check: Detects single-bit errors by adding a check bit to the data frame to ensure that the total number of bits is odd or even. CRC check: A series of mathematical operations are performed on the data to generate a check code of fixed length, which is then appended to the end of the data. After receiving the data, the receiving end will perform the same operation on the data and the check code. If the result is incorrect, it means that an error has occurred during the data transmission process. Hash verification: By calculating the hash value of the data, that is, using a specific algorithm to map the data into a fixed-length digital sequence, and then comparing it with the original calculated hash value, it is possible to determine whether the data has been changed during transmission or storage. If the hash value is different, it means that the data may have been tampered with or damaged; Hamming code check: It detects and corrects errors that may occur during data transmission or storage by adding a certain number of check bits to the original data.

[0009] Furthermore, the storage management module includes the following submodules: Database construction and maintenance submodule: responsible for creating, optimizing and maintaining the database, including designing the database structure, defining data tables, establishing indexes, etc.; Backup and recovery submodule: responsible for regularly backing up data to prevent data loss and quickly recovering data when it is damaged or lost, including full backup, incremental backup, differential backup and other backup strategies, as well as automatic or manual data recovery mechanisms; Data permission management submodule: responsible for setting and managing data access permissions to ensure that only authorized users or systems can access, modify or delete data, including user role management, access control list (ACL) settings, permission auditing and other functions; Architecture optimization submodule: optimizes data storage architecture based on distributed storage, load balancing, data compression, and deduplication technology; Monitoring and alarm submodule: responsible for real-time monitoring of data storage status, access status and performance. Once an abnormal situation is found or exceeds the preset threshold, an alarm is triggered to notify the management personnel to handle it; Migration and integration submodule: responsible for implementing the data migration and integration process, used to migrate data from the old system to the new system, or integrate data from different sources together.

[0010] Furthermore, the data analysis algorithm and model used by the analysis and processing module are as follows: Time series analysis: When monitoring the flow data in the township rainwater and sewage pipe network, use the ARIMA or SARIMA model to analyze the change trend of flow over time. By fitting and predicting the historical flow data, the flow situation in the future can be predicted to provide a basis for pipe network scheduling and optimization; Association rule mining: In the rainwater and sewage pipe network, the Apriori algorithm or FP-Growth algorithm is used to analyze the association rules between various environmental parameters and discover potential relationships; Cluster analysis: Use K-Means algorithm or DBSCAN algorithm to group each monitoring point in the pipe network according to its data characteristics; Decision tree and random forest: Use C4.5, CART decision tree, and random forest integrated models to predict faults or abnormal conditions in the pipeline network. Specifically, by learning from historical fault data, a prediction model is built to identify key indicators and thresholds that may cause faults. When real-time monitoring data reaches these thresholds, the system can automatically issue an early warning to remind managers to take timely measures. Neural networks and deep learning: For complex nonlinear relationships and spatiotemporal pattern recognition, neural networks and deep learning models are used to learn the complex relationships between various parameters in the pipeline network and predict future states or trends, including recurrent neural networks, long short-term memory networks, and convolutional neural networks.

[0011] Furthermore, the data analysis algorithms and models are interdependent and cooperate with each other within the analysis and processing framework and are not applied in isolation. The analysis and processing framework also includes steps such as data preprocessing and feature extraction. These steps also cooperate with the data analysis algorithms and models, and through mutual verification, supplementation and collaboration, deep mining and processing of pipeline network data can be achieved.

[0012] Furthermore, the visual display specifically includes the following methods: Dynamic data charts: Use bar charts, line charts or pie charts to dynamically display real-time or historical monitoring data; Real-time monitoring instrument: simulate the display mode of physical instruments and update data in real time, such as tachometer, pressure gauge, etc. Geographic Information System Map: Display the pipe network layout, monitoring point locations and real-time monitoring data on the map; Video stream integration: Integrate the video stream captured by the on-site camera into the system; Alarm and event list: Displays alarm and event information in a list format, including alarm type, time, location, etc.; Interactive heat map: Use the depth of color to indicate the size or intensity of data, allowing for intuitive comparison of data.

[0013] Furthermore, the user operation interface specifically includes: Login verification area: used to verify the user identity before accessing the user operation interface. Only authorized personnel can access it. Real-time monitoring display area: used to display the operation status and key parameters of the pipeline network in real time, including dashboards, charts, maps and dynamic data updates; Control operation area: allows managers to remotely control and operate equipment in the pipe network, and provides a variety of control methods such as buttons, switches, sliders, drop-down menus, etc. Alarm and event management area: used to display the alarm and event information of the pipeline network in real time. When the pipeline network operation is abnormal or fails, the system will automatically trigger an alarm and display relevant information on the user operation interface, including the alarm type, time, location and recommended response measures; Historical data query and analysis area: managers use this area to query and analyze the historical operation data of the pipeline network; Configuration and settings area: allows managers to configure and set up the system according to actual needs, including but not limited to the setting of device parameters, management of user permissions, adjustment of interface layout, etc., to meet the usage requirements of different scenarios and roles; Help and Documentation Area: Provides user manuals, operation guides, FAQs and other document resources to help managers better understand and use the user interface; Notification and message area: used to send system notifications and messages to managers, such as alarm confirmation, operation result feedback, system update prompts, etc.

[0014] Furthermore, the intelligent supervision module includes the following submodules: Data monitoring submodule: responsible for receiving pipeline network data in real time, and using built-in algorithms or models to analyze it in real time to extract basic trend, fluctuation and other information; Fault warning submodule: responsible for monitoring the status of the pipeline network. Once an abnormal situation or potential fault is found, it will immediately send out a warning signal to notify the management personnel for timely processing; based on the preset threshold or pattern recognition algorithm, it monitors the abnormal situation in the pipeline network data in real time, such as water quality exceeding the standard, abnormal flow, etc., and uses historical data and machine learning technology to predict the type and time of possible faults, providing a basis for preventive maintenance. Once an abnormal situation is detected or a fault is predicted, it will immediately send a warning signal to the management personnel through sound and light alarms, SMS notifications, etc.; Maintenance management submodule: responsible for providing advice and guidance on maintenance management, helping managers maintain and manage the pipeline network.

[0015] Furthermore, the use process of the township rainwater and sewage pipe network intelligent monitoring system is as follows: Step 1: Install and deploy various monitoring devices through the equipment construction module, and use the monitoring devices to collect key data in the pipe network in real time. The raw data collected by the monitoring devices are collected in real time through the data collection and transmission module, and transmitted to the central server or cloud platform by wired or wireless means. The received data is stored and managed using the storage management module; Step 2: The analysis and processing module uses data analysis algorithms and models to deeply mine and process the stored data, extract valuable information, and visualize it through the display output module, presenting the monitoring data to users in an intuitive way. At the same time, it supports report output, generates monitoring reports and analysis results, and sends them to the regulatory authorities for decision-making and management; Step 3: The remote monitoring module provides a user operation interface to the supervisory department, allowing the management personnel to monitor the operation status of the pipeline network in real time through remote network access, and remotely control and operate the system; Step 4. The intelligent supervision module receives the pipeline network data in real time through the data monitoring submodule, and uses the built-in algorithm or model to analyze the real-time and extract information. The fault warning submodule monitors the pipeline network status based on the extracted information. Once an abnormal situation or potential fault is found, it immediately issues a warning signal to notify the management personnel for timely processing. At the same time, the maintenance management submodule provides maintenance management suggestions and guidance based on the extracted information to help managers maintain and manage the pipeline network.

[0016] The present invention provides a smart monitoring system for township rainwater and sewage pipe networks, which has the following beneficial effects: The present invention can reasonably increase monitoring points according to the actual situation in township areas, and install and deploy monitoring equipment to ensure that the operation status of the pipe network and the sewage discharge situation are fully reflected. At the same time, an efficient data transmission and processing process is established, and the accuracy and reliability of the monitoring data transmission process are improved through the verification mechanism. At the same time, the monitoring data is analyzed and mined by technical means such as big data and cloud computing to provide decision support for managers. The present invention realizes real-time monitoring and early warning of the pipe network status by installing sensors and intelligent equipment, promotes the intelligent and automated monitoring of rainwater and sewage pipe networks, and solves the problems of low work efficiency and easy errors in manual monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 It is a schematic diagram of the overall operation process of a smart monitoring system for township rainwater and sewage pipe networks of the present invention; Figure 2 This is a schematic diagram of the operation flow of a storage management module of a smart monitoring system for a township rainwater and sewage pipe network according to the present invention; Figure 3 This is a schematic diagram of the operation flow of a remote supervision module of a smart monitoring system for township rainwater and sewage pipe networks according to the present invention. DETAILED DESCRIPTION

[0018] The following embodiments of the present invention are described in further detail in conjunction with the accompanying drawings and examples. The following examples are used to illustrate the present invention, but are not intended to limit the scope of the present invention.

[0019] like Figure 1-Figure 3 As shown, a smart monitoring system for township rainwater and sewage pipe networks includes: Equipment construction module, which is responsible for installing and deploying various monitoring equipment, and collecting key data such as water quality, flow, pressure, liquid level, etc. in the pipe network in real time through monitoring equipment to provide data support; the monitoring equipment includes flow meters, water quality monitoring instruments, liquid level meters, pressure sensors, gas monitors, rainfall sensors, pipeline CCTV detection robots, manhole cover displacement monitors, and smart cameras, and all hardware equipment is relatively mature and meets relevant technical standards. Existing products; Flow meter: a device used to measure and record the flow of rainwater and sewage. It can monitor the flow changes of rainwater and sewage in the pipeline in real time, help managers understand the operation status of the pipeline network, and grasp the flow distribution, flow velocity and other information of rainwater and sewage in the pipeline network; Water quality monitoring equipment: equipment that monitors and analyzes the quality of rainwater and sewage in real time. It can detect various water quality indicators in rainwater and sewage, such as pH value, ammonia nitrogen, total phosphorus, suspended solids, etc., so as to judge the water quality level and treatment effect of rainwater and sewage; Liquid level meter: used to monitor the liquid level in the pipeline in real time. The liquid level meter can be used to determine the flow rate and flow velocity in the pipeline to prevent sewage overflow and determine the operating status of the pump station. For example, the ultrasonic liquid level meter uses the ultrasonic principle to measure the liquid level, which has high accuracy and stability. Pressure sensor: In the pressure-carrying drainage pipe section, a pressure monitoring point is set to monitor the pressure changes in the pipe in real time. The pressure sensor can detect problems such as pipe damage and sewage leakage in time to ensure the safe operation of the pipe network; Gas monitor: used to monitor the concentration of harmful gases such as hydrogen sulfide and methane in the pipeline. Once the concentration exceeds the preset threshold, the monitor will issue an alarm to help staff discover and deal with it in time to avoid accidents such as pipeline explosions; Rainfall sensor: installed at a suitable location to monitor rainfall conditions and help analyze the flow changes of rainwater entering the pipe network, which is of great significance to the operation and scheduling of the pipe network and sewage treatment; Pipe CCTV inspection robot: a device used for video and inspection inside pipelines. Through remote control, the robot can move inside the drainage pipe and transmit images of the inside of the pipe in real time. The staff can observe the conditions inside the pipe at the control center, including pipe rupture, blockage, sediment, etc., so as to carry out repairs and maintenance in a timely manner. Manhole cover displacement monitor: used to monitor the position status of the manhole cover in real time. Once the manhole cover is displaced, the monitor will immediately trigger an alarm to remind the staff to deal with it in time to ensure the safety of residents' travel; Smart camera: equipped with high-definition camera and intelligent analysis function, it can monitor the operation status of key nodes of the pipeline network in real time and identify abnormal conditions such as leakage and blockage through image recognition technology; The data acquisition and transmission module is responsible for collecting the raw data collected by the monitoring equipment in real time, and transmitting it to the central server or cloud platform for storage and processing by wired or wireless means. During the data transmission process, a verification mechanism is adopted; the verification mechanism calculates and compares the transmitted data to detect whether there is any error or loss in the data transmission process, which specifically includes: Parity check: Detects single-bit errors by adding a check bit to the data frame to ensure that the total number of bits is odd or even. CRC check: A series of mathematical operations are performed on the data to generate a check code of fixed length, which is then appended to the end of the data. After receiving the data, the receiving end will perform the same operation on the data and the check code. If the result is incorrect, it means that an error has occurred during the data transmission process. Hash verification: By calculating the hash value of the data, that is, using a specific algorithm to map the data into a fixed-length digital sequence, and then comparing it with the original calculated hash value, it is possible to determine whether the data has been changed during transmission or storage. If the hash value is different, it means that the data may have been tampered with or damaged; Hamming code check: It detects and corrects errors that may occur during data transmission or storage by adding a certain number of check bits to the original data; The storage management module is responsible for storing and managing the received data, including establishing a database, data backup and recovery mechanism, data authority management, and building an efficient data storage architecture; the storage management module has the following submodules: Database construction and maintenance submodule: responsible for creating, optimizing and maintaining the database, including designing the database structure, defining data tables, establishing indexes, etc., to provide a stable and efficient data storage environment; Backup and recovery submodule: responsible for regularly backing up data to prevent data loss and quickly recovering data when it is damaged or lost, including full backup, incremental backup, differential backup and other backup strategies, as well as automatic or manual data recovery mechanisms; Data permission management submodule: responsible for setting and managing data access permissions to ensure that only authorized users or systems can access, modify or delete data, including user role management, access control list (ACL) settings, permission auditing and other functions; Architecture optimization submodule: Based on distributed storage, load balancing, data compression, and deduplication technology, it optimizes the data storage architecture to improve data reading and writing performance and reduce storage costs; Monitoring and alarm submodule: responsible for real-time monitoring of data storage status, access status and performance. Once an abnormal situation is found or exceeds the preset threshold, an alarm is triggered to notify the management personnel to handle it; Migration and integration submodule: responsible for implementing the data migration and integration process, ensuring the integrity and consistency of data. With the development of business or the update of technology, it is used to migrate data from the old system to the new system, or integrate data from different sources together; The analysis and processing module uses data analysis algorithms and models to perform in-depth mining and processing on the stored data, extract valuable information, and generate statistical reports, monitoring and early warning, etc. The data analysis algorithms and models used by the analysis and processing module are as follows: Time series analysis: When monitoring the flow data in the township rainwater and sewage pipe network, use the ARIMA or SARIMA model to analyze the change trend of flow over time. By fitting and predicting the historical flow data, the flow situation in the future can be predicted to provide a basis for pipe network scheduling and optimization; Association rule mining: In the rainwater and sewage pipe network, the Apriori algorithm or FP-Growth algorithm is used to analyze the association rules between various environmental parameters (such as rainfall, pipe pressure, water quality indicators, etc.) to discover potential relationships. For example, the system may find that when the rainfall exceeds a certain threshold, the pressure of a certain section of the pipe will increase significantly, so as to issue an early warning and take corresponding measures; Cluster analysis: Use the K-Means algorithm or DBSCAN algorithm to group the monitoring points in the pipe network according to their data characteristics. For example, the monitoring points can be divided into different categories based on the similarity of indicators such as flow and water quality to identify areas or pipe sections with similar problems, so as to formulate targeted maintenance and renovation plans; Decision tree and random forest: Use C4.5, CART decision tree, and random forest integrated models to predict faults or abnormal conditions in the pipeline network. Specifically, by learning from historical fault data, a prediction model is built to identify key indicators and thresholds that may cause faults. When real-time monitoring data reaches these thresholds, the system can automatically issue an early warning to remind managers to take timely measures. Neural networks and deep learning: For complex nonlinear relationships and spatiotemporal pattern recognition, neural networks and deep learning models are used to learn the complex relationships between various parameters in the pipe network and predict future states or trends, including recurrent neural networks (RNN), long short-term memory networks (LSTM), and convolutional neural networks (CNN); The above-mentioned data analysis algorithms and models are interdependent and coordinated within the analysis and processing framework, and are not applied in isolation. The analysis and processing framework also includes steps such as data preprocessing and feature extraction. These steps also cooperate with the data analysis algorithms and models, and through mutual verification, supplementation and collaborative work, deep mining and processing of pipeline network data can be achieved. The display output module is responsible for visual display, presenting the monitoring data to the user in an intuitive way, such as displaying the operation status and monitoring data of the pipeline network in the form of charts, maps, etc., and supports report output, generates monitoring reports and analysis results, and sends them to the regulatory department for decision-making and management; the visual display specifically includes the following methods: Dynamic data charts: Use bar charts, line charts or pie charts to dynamically display real-time or historical monitoring data. For example, when monitoring sewage flow in real time, a line chart can show the flow rate change trend over time, and a pie chart can be used to show the flow rate ratio at different monitoring points; Real-time monitoring instrument: simulates the display mode of physical instruments and updates data in real time, such as tachometers, pressure gauges, etc. For example, when monitoring the operating status of a sewage pumping station, the tachometer can display the operating speed of the pump in real time; Geographic Information System (GIS) Map: Display the pipe network layout, monitoring point locations and real-time monitoring data on the map. For example, through the GIS map, users can clearly see the distribution and direction of the pipe network. At the same time, the marker points on the map can display the real-time water quality data or alarm status of each monitoring point; Video stream integration: Integrate the video stream captured by the on-site camera into the system. For example, for key monitoring points or areas prone to problems, real-time images can be captured by the camera and displayed in the system. Alarm and event list: Displays alarm and event information in a list format, including alarm type, time, location, etc. For example, when the water quality data at a certain monitoring point exceeds the preset threshold, the system will generate an alarm and display relevant information in the alarm list; Interactive heat map: The size or intensity of data is indicated by the depth of color, so that data can be compared intuitively. For example, when displaying the degree of water pollution, a heat map can be used to indicate the degree of pollution in different areas or monitoring points. The darker the color, the more serious the pollution, so that users can quickly identify the seriously polluted areas. Remote monitoring module, which is responsible for providing a user operation interface, so that managers can monitor the operation status of the pipeline network in real time through remote network access, and remotely control and operate the system; the user operation interface specifically includes: Login verification area: used to verify the user identity before accessing the user operation interface. Only authorized personnel can access it. Real-time monitoring display area: used to display the operation status and key parameters of the pipeline network in real time, including dashboards, charts, maps and dynamic data updates, so that managers can intuitively understand the real-time situation of the pipeline network, including key indicators such as flow, pressure, temperature, and water quality; Control operation area: allows managers to remotely control and operate equipment in the pipe network, and provides a variety of control methods such as buttons, switches, sliders, drop-down menus, etc. Alarm and event management area: used to display the alarm and event information of the pipeline network in real time. When the pipeline network operation is abnormal or fails, the system will automatically trigger an alarm and display relevant information on the user operation interface, including the alarm type, time, location and recommended response measures; Historical data query and analysis area: managers use this area to query and analyze the historical operation data of the pipeline network; Configuration and settings area: allows managers to configure and set up the system according to actual needs, including but not limited to the setting of device parameters, management of user permissions, adjustment of interface layout, etc., to meet the usage requirements of different scenarios and roles; Help and Documentation Area: Provides user manuals, operation guides, FAQs and other document resources to help managers better understand and use the user interface; Notification and message area: used to send system notifications and messages to managers, such as alarm confirmation, operation result feedback, system update prompts, etc. Intelligent supervision module, based on real-time monitoring, realizes intelligent management of township rainwater and sewage pipe networks from two directions: fault warning and maintenance management; the intelligent supervision module includes the following sub-modules: Data monitoring submodule: responsible for receiving pipeline network data in real time, and using built-in algorithms or models to analyze it in real time to extract basic trend, fluctuation and other information; Fault warning submodule: responsible for monitoring the status of the pipeline network. Once an abnormal situation or potential fault is found, it will immediately send out a warning signal to notify the management personnel for timely processing; based on the preset threshold or pattern recognition algorithm, it monitors the abnormal situation in the pipeline network data in real time, such as water quality exceeding the standard, abnormal flow, etc., and uses historical data and machine learning technology to predict the type and time of possible faults, providing a basis for preventive maintenance. Once an abnormal situation is detected or a fault is predicted, it will immediately send a warning signal to the management personnel through sound and light alarms, SMS notifications, etc.; Maintenance management submodule: responsible for providing maintenance management advice and guidance to help managers maintain and manage the pipeline network; for example, based on monitoring data and fault warning information, provide managers with targeted maintenance suggestions, such as replacing worn parts, clearing blocked pipes, etc., or based on the operating status and maintenance history of the pipeline network, assist managers in formulating long-term maintenance plans. At the same time, evaluate and provide feedback on the effectiveness of maintenance activities in order to continuously optimize maintenance strategies and improve maintenance efficiency.

[0020] In summary, combined Figure 1-Figure 3 As shown in the figure, the use process of the township rainwater and sewage pipe network intelligent monitoring system is as follows: Step 1: Install and deploy various monitoring devices through the equipment construction module, and use the monitoring devices to collect key data in the pipe network in real time. The raw data collected by the monitoring devices are collected in real time through the data collection and transmission module, and transmitted to the central server or cloud platform by wired or wireless means. The received data is stored and managed using the storage management module; Step 2: The analysis and processing module uses data analysis algorithms and models to deeply mine and process the stored data, extract valuable information, and visualize it through the display output module, presenting the monitoring data to users in an intuitive way. At the same time, it supports report output, generates monitoring reports and analysis results, and sends them to the regulatory authorities for decision-making and management; Step 3: The remote monitoring module provides a user operation interface to the supervisory department, allowing the management personnel to monitor the operation status of the pipeline network in real time through remote network access, and remotely control and operate the system; Step 4. The intelligent supervision module receives the pipeline network data in real time through the data monitoring submodule, and uses the built-in algorithm or model to analyze the real-time and extract information. The fault warning submodule monitors the pipeline network status based on the extracted information. Once an abnormal situation or potential fault is found, it immediately issues a warning signal to notify the management personnel for timely processing. At the same time, the maintenance management submodule provides maintenance management suggestions and guidance based on the extracted information to help managers maintain and manage the pipeline network.

[0021] The embodiments of the present invention are given for the purpose of illustration and description, and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those of ordinary skill in the art. The embodiments are selected and described in order to better illustrate the principles and practical applications of the present invention and to enable those of ordinary skill in the art to understand the present invention and thereby design various embodiments with various modifications suitable for specific uses.

Claims

1. A smart monitoring system for township rainwater and sewage pipe networks, characterized in that: include: Equipment construction module, data acquisition and transmission module, storage management module, analysis and processing module, display and output module, remote supervision module and intelligent supervision module; The equipment construction module is responsible for installing and deploying various monitoring equipment, and collecting key data in the pipe network in real time through the monitoring equipment to provide data support; The data acquisition and transmission module is responsible for collecting the raw data collected by the monitoring equipment in real time, and transmitting it to the central server or cloud platform for storage and processing by wired or wireless means, and a verification mechanism is adopted during the data transmission process; The storage management module is responsible for storing and managing the received data, including establishing a database, data backup and recovery mechanism, data authority management, and building an efficient data storage architecture; The analysis and processing module uses data analysis algorithms and models to deeply mine and process the stored data, extract valuable information, and generate statistical reports, monitoring and early warning; The display output module is responsible for visual display, presenting the monitoring data to the user in an intuitive manner, and supports report output, generating monitoring reports and analysis results, and sending them to the regulatory authorities for decision-making and management; The remote monitoring module is responsible for providing a user operation interface, allowing management personnel to monitor the operation status of the pipeline network in real time through remote network access, and to remotely control and operate the system; The intelligent supervision module realizes intelligent management of the township rainwater and sewage pipe networks from two aspects: fault warning and maintenance management based on real-time monitoring.

2. According to claim 1, a smart monitoring system for township rainwater and sewage pipe networks is characterized in that: The monitoring equipment includes flow meters, water quality monitoring instruments, liquid level gauges, pressure sensors, gas monitors, rainfall sensors, pipeline CCTV inspection robots, manhole cover displacement monitors, and smart cameras, and all hardware equipment is sourced from existing products that are relatively mature on the market and meet relevant technical standards.

3. According to claim 1, a smart monitoring system for township rainwater and sewage pipe networks is characterized in that: The verification mechanism calculates and compares the transmitted data to detect whether the data is erroneous or lost during the transmission process, specifically including: Parity check: Detects single-bit errors by adding a check bit to the data frame to ensure that the total number of bits is odd or even. CRC check: A series of mathematical operations are performed on the data to generate a check code of fixed length, which is then appended to the end of the data. After receiving the data, the receiving end will perform the same operation on the data and the check code. If the result is incorrect, it means that an error has occurred during the data transmission process. Hash verification: By calculating the hash value of the data, that is, using a specific algorithm to map the data into a fixed-length digital sequence, and then comparing it with the original calculated hash value, it is possible to determine whether the data has been changed during transmission or storage; Hamming code check: It detects and corrects errors that may occur during data transmission or storage by adding a certain number of check bits to the original data.

4. According to claim 1, a smart monitoring system for township rainwater and sewage pipe networks is characterized in that: The storage management module has the following submodules: Database construction and maintenance submodule: responsible for creating, optimizing and maintaining the database; Backup and recovery submodule: responsible for regularly backing up data to prevent data loss and quickly recovering data when it is damaged or lost, including backup strategies and automatic or manual data recovery mechanisms; Data permission management submodule: responsible for setting and managing data access permissions to ensure that only authorized users or systems can access, modify or delete data; Architecture optimization submodule: optimizes data storage architecture based on distributed storage, load balancing, data compression, and deduplication technology; Monitoring and alarm submodule: responsible for real-time monitoring of data storage status, access status and performance. Once an abnormal situation is found or exceeds the preset threshold, an alarm is triggered to notify the management personnel to handle it; Migration and integration submodule: responsible for implementing the data migration and integration process, used to migrate data from the old system to the new system, or integrate data from different sources together.

5. The intelligent monitoring system for township rainwater and sewage pipe networks according to claim 1 is characterized in that: The data analysis algorithms and models used by the analysis and processing module are as follows: Time series analysis: When monitoring the flow data in the township rainwater and sewage pipe network, use the ARIMA or SARIMA model to analyze the change trend of flow over time. By fitting and predicting the historical flow data, the flow situation in the future can be predicted to provide a basis for pipe network scheduling and optimization; Association rule mining: In the rainwater and sewage pipe network, the Apriori algorithm or FP-Growth algorithm is used to analyze the association rules between various environmental parameters and discover potential relationships; Cluster analysis: Use K-Means algorithm or DBSCAN algorithm to group each monitoring point in the pipe network according to its data characteristics; Decision Tree and Random Forest: Use C4.5, CART decision tree, and random forest ensemble models to predict faults or abnormalities in the pipe network; Neural networks and deep learning: For complex nonlinear relationships and spatiotemporal pattern recognition, neural networks and deep learning models are used to learn the complex relationships between various parameters in the pipeline network and predict future states or trends, including recurrent neural networks, long short-term memory networks, and convolutional neural networks.

6. A smart monitoring system for township rainwater and sewage pipe networks according to claim 5, characterized in that: The data analysis algorithms and models are interdependent and cooperate with each other within the analysis and processing framework and are not applied in isolation. The analysis and processing framework also includes steps such as data preprocessing and feature extraction. These steps also cooperate with the data analysis algorithms and models, and through mutual verification, supplementation and collaboration, deep mining and processing of pipeline network data can be achieved.

7. The intelligent monitoring system for township rainwater and sewage pipe networks according to claim 1 is characterized in that: The visual display specifically includes the following methods: Dynamic data charts: Use bar charts, line charts or pie charts to dynamically display real-time or historical monitoring data; Real-time monitoring instrument: simulates the display mode of physical instruments and updates data in real time; Geographic Information System Map: Display the pipe network layout, monitoring point locations and real-time monitoring data on the map; Video stream integration: Integrate the video stream captured by the on-site camera into the system; Alarm and event list: Display alarm and event information in list form; Interactive heat map: Use the depth of color to indicate the size or intensity of data, allowing for intuitive comparison of data.

8. The intelligent monitoring system for township rainwater and sewage pipe networks according to claim 1 is characterized in that: The user operation interface specifically includes: Login verification area: used to verify the user identity before accessing the user operation interface. Only authorized personnel can access it. Real-time monitoring display area: used to display the operation status and key parameters of the pipeline network in real time; Control operation area: allows managers to remotely control and operate equipment in the pipe network, and provides buttons, switches, sliders, and drop-down menu control methods; Alarm and event management area: used to display the alarm and event information of the pipe network in real time; Historical data query and analysis area: managers use this area to query and analyze the historical operation data of the pipeline network; Configuration and settings area: allows managers to configure and set up the system according to actual needs; Help and Documentation Area: Provides user manuals, operation guides, and FAQs to help managers better understand and use the user interface; Notification and message area: used to send system notifications and messages to managers.

9. The intelligent monitoring system for township rainwater and sewage pipe networks according to claim 1 is characterized in that: The intelligent supervision module includes the following submodules: Data monitoring submodule: responsible for receiving pipeline network data in real time, and using built-in algorithms or models to analyze it in real time to extract basic trend and fluctuation information; Fault warning submodule: responsible for monitoring the status of the pipeline network. Once an abnormal situation or potential fault is found, it will immediately issue a warning signal to notify the management personnel for timely processing; Maintenance management submodule: responsible for providing advice and guidance on maintenance management, helping managers maintain and manage the pipeline network.

10. A smart monitoring system for township rainwater and sewage pipe networks according to any one of claims 1 to 9, characterized in that: The usage process of the township rainwater and sewage pipe network intelligent monitoring system is as follows: Step 1: Install and deploy various monitoring devices through the equipment construction module, and use the monitoring devices to collect key data in the pipe network in real time. The raw data collected by the monitoring devices are collected in real time through the data collection and transmission module, and transmitted to the central server or cloud platform by wired or wireless means. The received data is stored and managed using the storage management module; Step 2: The analysis and processing module uses data analysis algorithms and models to deeply mine and process the stored data, extract valuable information, and visualize it through the display output module, presenting the monitoring data to users in an intuitive way. At the same time, it supports report output, generates monitoring reports and analysis results, and sends them to the regulatory authorities for decision-making and management; Step 3: The remote monitoring module provides a user operation interface to the supervisory department, allowing the management personnel to monitor the operation status of the pipeline network in real time through remote network access, and remotely control and operate the system; Step 4. The intelligent supervision module receives the pipeline network data in real time through the data monitoring submodule, and uses the built-in algorithm or model to analyze the real-time and extract information. The fault warning submodule monitors the pipeline network status based on the extracted information. Once an abnormal situation or potential fault is found, it immediately issues a warning signal to notify the management personnel for timely processing. At the same time, the maintenance management submodule provides maintenance management suggestions and guidance based on the extracted information to help managers maintain and manage the pipeline network.

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