City intelligent water affair whole cycle management platform based on digital twinning

Abstract

This invention relates to a digital twin-based smart water management platform for the entire lifecycle of urban water affairs, belonging to the interdisciplinary field of municipal engineering, environmental engineering, smart water management technology, and computer technology. It addresses the problems of low levels of intelligence and insufficient functionality in existing urban water management platforms. The invention comprises an IoT sensing layer, a server infrastructure layer, an algorithm integration layer, a platform service layer, and an application function layer. It monitors, senses, stores, and processes information data from multiple water sources within the city, integrates analytical algorithms, builds a visualized 3D model of urban water projects, and integrates IoT sensing data and emergency resource data. This allows for the visualization of dynamic operational information of urban water projects, real-time analysis of urban water malfunctions, and immediate decision-making on emergency response plans for urban water malfunctions. This invention primarily focuses on the intelligent management and display of urban water affairs.

Description

Technical Field

[0001] This invention belongs to the interdisciplinary field of municipal engineering, environmental engineering, smart water management technology and computer technology. Background Technology

[0002] Digital twins fully utilize data such as physical models, sensor updates, and operational history to integrate multi-disciplinary, multi-physical, multi-scale, and multi-probability simulation processes, completing mapping in virtual space to reflect the entire lifecycle of the corresponding physical equipment.

[0003] Urban water affairs encompass all aspects of urban water resource development, utilization, and protection, including water sources, water supply, water conservation, drainage, and sewage treatment. It is an extremely important part of urban construction, management, operation, and maintenance. The daily monitoring, early warning, and maintenance of pipelines are directly related to the normal lives of urban residents. Therefore, establishing a smart urban water affairs full-cycle management platform is essential.

[0004] Traditional smart water management platforms have the following problems:

[0005] 1. Difficulty in data integration: Urban water systems involve multiple data sources, including sensor data, geographic information data, water quality data, etc. These data are usually scattered in different systems and departments, lacking a unified data integration platform.

[0006] 2. Complex model building: The models of urban water systems are usually very complex, involving multiple aspects such as water resources, water supply networks, and sewage treatment. The model building and maintenance costs are high, and a large amount of real-time data is required.

[0007] 3. Insufficient full-cycle management: Current urban water affairs platforms can usually only monitor and manage some aspects, and cannot integrate functions such as monitoring, early warning, emergency decision-making and maintenance. As a result, the current level of intelligent management of urban water affairs is low and the management platform has insufficient functions.

[0008] Therefore, it is necessary to propose a digital twin-based smart water management platform for the entire lifecycle of urban water affairs, which can digitally map and intelligently simulate all elements of urban water affairs and the entire process of governance and management activities, so as to achieve synchronous simulation operation with urban water affairs projects and support precise decision-making and subsequent operation and maintenance of water conservancy business. Summary of the Invention

[0009] The purpose of this invention is to address the problems of low intelligence levels and insufficient functionality of existing urban water management platforms. This invention provides a digital twin-based full-cycle management platform for smart urban water affairs.

[0010] A digital twin-based smart water management platform for the entire lifecycle of urban water affairs includes:

[0011] The Internet of Things (IoT) sensing layer is used to monitor and sense information data of multi-source water conservancy projects in the city through IoT sensing devices.

[0012] The server infrastructure layer is used to store multi-source water conservancy project information data, as well as to classify, preprocess, and perform data anomaly analysis on the multi-source water conservancy project information data, and store the data after classification, preprocessing, and data anomaly analysis.

[0013] The algorithm integration layer is used to configure corresponding algorithms for classification, preprocessing, and data anomaly analysis of the server infrastructure layer.

[0014] The platform service layer is used to perform visual 3D modeling based on engineering data from the monitored and perceived multi-source water conservancy project information data within the city, thereby obtaining a 3D model of the water conservancy project; it is also used to perform digital mapping between non-engineering data from the multi-source water conservancy project information data and the constructed 3D model of the water conservancy project; and it is also used to realize the management of urban emergency resource data information.

[0015] The application function layer is used for dynamic visualization of urban water affairs, real-time analysis of urban water affairs fault information, and guidance for decision-making on emergency plans for urban water affairs faults.

[0016] Preferably, the information data of multi-source water projects in the city includes data on various water source projects, water supply projects, water conservation projects, drainage projects, sewage treatment projects, water resource recycling projects, and pipeline projects within the city.

[0017] Preferably, the server infrastructure layer includes cloud storage servers and cloud computing servers;

[0018] Cloud storage servers are used to store multi-source water conservancy project information data, as well as data that has been classified, preprocessed, and analyzed for data anomalies;

[0019] The cloud computing server supports big data classification algorithms, big data computing algorithms, and intelligent analysis algorithms for classifying, preprocessing, and analyzing data anomalies in multi-source water conservancy project information data.

[0020] Preferably, the algorithm integration layer includes a big data storage algorithm module, a big data computing algorithm module, and an intelligent analysis algorithm module;

[0021] The big data classification algorithm module embeds a big data classification algorithm, which is used to classify multi-source water conservancy project information data stored in the server infrastructure layer by keywords when data classification and storage work is required; when data extraction work is required, the required data is extracted from the cloud storage server in the server infrastructure layer by searching by the classification keywords corresponding to the data to be extracted.

[0022] The big data computing algorithm module is used to configure the corresponding big data computing algorithm according to the basic functions of the full-cycle management platform, and to preprocess the multi-source water conservancy project information data through the corresponding big data computing algorithm;

[0023] The intelligent analysis algorithm module is equipped with an intelligent analysis algorithm for performing data anomaly analysis on preprocessed multi-source water conservancy project information data.

[0024] Preferably, the platform service layer includes a 3D model system, a 3D pipeline system, an IoT sensing data system, and an emergency resource management system;

[0025] The 3D modeling system is used to construct 3D models of water facilities such as plants and pumping stations based on building data from water source engineering data, water supply engineering data, and drainage engineering data in multi-source water engineering information data.

[0026] A 3D pipeline system is used to construct a 3D model of urban water pipeline facilities based on pipeline engineering data from multi-source water engineering information data.

[0027] The IoT sensing data system is used to mark the location of each monitoring point in the 3D model of plant water facilities, the 3D model of pump station water facilities, and the 3D model of urban water pipeline facilities by using non-engineering data from water source engineering data, water supply engineering data, drainage engineering data, and pipeline engineering data in multi-source water engineering information data.

[0028] The emergency resource management system is used to count the location of urban emergency resources and the quantity of urban emergency resources at each location.

[0029] Preferably, the application function layer includes a multi-data integration and visualization module, an operational status awareness module, a comprehensive analysis and judgment module, and an emergency response and coordination module;

[0030] The multi-source data integration and visualization module is used to dynamically display and visualize the constructed 3D model of water conservancy projects, non-engineering data from multi-source water conservancy project information data, and the locations of various monitoring points in the 3D model of water conservancy projects. It is also used to zoom in, zoom out, move, rotate, and control the 3D model layers of water conservancy projects. Furthermore, it is used to visualize the locations of various monitoring points in the 3D model of water conservancy projects and the locations and quantities of urban emergency resources on a 2D map.

[0031] The operational situation awareness module is used to build an Internet of Things (IoT) system. Through data acquisition and monitoring devices set up at the water engineering site, the system interconnects with the full-cycle management platform via the IoT to realize the perception of the operational status of equipment in the three-dimensional model of the water engineering project and the perception of the changing patterns of water operation.

[0032] The comprehensive analysis and judgment module is used to set the trigger threshold for water conservancy project fault alarms, and compare the abnormal data obtained by data anomaly analysis at the server facility layer with the water conservancy project fault alarm trigger thresholds to make risk judgments and determine the risk level of alarm information.

[0033] The emergency response module is used to enable resource linkage between the multi-data integration and visualization module, the operational situation awareness module, and the comprehensive analysis and judgment module. It also integrates with the communication command platform to achieve cross-departmental and cross-business collaborative command and dispatch, and assist in emergency response and emergency resource allocation.

[0034] Preferably, the big data computing algorithms include water quality monitoring algorithms and pipeline monitoring algorithms.

[0035] This invention proposes a digital twin-based smart water management platform for the entire lifecycle of urban water affairs. The platform includes an IoT sensing layer, a server infrastructure layer, an algorithm integration layer, a platform service layer, and an application function layer. It monitors, senses, stores, and processes information data on water engineering projects such as water sources, water supply, water conservation, drainage, sewage treatment, water resource recycling, and pipelines within the city. It integrates analysis and processing algorithms to build a visualized 3D model of urban water engineering projects. It also integrates IoT sensing data and emergency resource data to visualize the dynamic operation information of urban water engineering projects, analyze urban water failure information in real time, and make immediate decisions on emergency plans for urban water failures.

[0036] The core advantages of this invention are mainly reflected in the following three points:

[0037] (1) Using digital twin technology, a smart water affairs full-cycle management platform is established. The Internet of Things perception layer, server facility layer and algorithm integration layer serve as the foundation of the smart management platform. The platform fully realizes the visualization, digital management and fault monitoring and emergency decision-making of all aspects of urban water affairs from single-line construction to full-network operation and maintenance, so as to achieve the purpose of full-process monitoring of urban water affairs, fault prediction and early warning, and real-time decision-making and maintenance.

[0038] (2) A digital twin-based smart water management platform for the entire lifecycle of urban water affairs is provided. It can integrate multiple data sources, including water sources, water supply, water conservation, drainage, sewage treatment, water resource recycling and utilization and pipelines in the city. It can digitally map and intelligently simulate all elements of urban water affairs and the entire process of governance and management activities, realize synchronous simulation operation with urban water affairs projects, and support precise decision-making and subsequent operation and maintenance of water conservancy business.

[0039] (3) This invention integrates monitoring, early warning, emergency decision-making and maintenance functions in urban water affairs management, solves the problem of imperfect full-cycle management of urban water affairs projects, and is conducive to promoting the intelligent development of urban water affairs management. Attached Figure Description

[0040] Figure 1 This is a schematic diagram illustrating the principle of the digital twin-based smart water management platform for the entire lifecycle of urban water affairs as described in this invention.

[0041] Figure 2 This is a diagram illustrating the monitoring of the river surface after water quality testing equipment has been deployed into the river. Detailed Implementation

[0042] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0043] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0044] This invention addresses the current problems of low intelligence levels and insufficient functionality in urban water management platforms by proposing a digital twin-based full-cycle smart water management platform. This platform comprises an IoT sensing layer 1, a server infrastructure layer 2, an algorithm integration layer 3, a platform service layer 4, and an application function layer 5. It monitors, senses, stores, and processes information data from multiple water-related projects within the city, integrates analytical algorithms, constructs a visualized 3D model of urban water projects, integrates IoT sensing data and emergency resource data, visualizes the dynamic operation information of urban water projects, analyzes urban water-related fault information in real time, and enables immediate decision-making on emergency response plans for urban water-related faults. The specific implementation plan is as follows:

[0045] See Figure 1 This embodiment describes a digital twin-based smart city water management platform that includes:

[0046] IoT sensing layer 1 is used to monitor and sense information data of multi-source water conservancy projects in the city through IoT sensing devices;

[0047] Server facility layer 2 is used to store multi-source water conservancy project information data, and also to classify, preprocess and analyze data anomalies of multi-source water conservancy project information data, and store the data after classification, preprocessing and data anomaly analysis;

[0048] Algorithm integration layer 3 is used to configure corresponding algorithms for classification, preprocessing and data anomaly analysis of server facility layer 2.

[0049] Platform service layer 4 is used to perform visual 3D modeling based on engineering data from the monitored and perceived multi-source water conservancy project information data in the city, thereby obtaining a 3D model of the water conservancy project; it is also used to perform digital mapping between non-engineering data from the multi-source water conservancy project information data and the constructed 3D model of the water conservancy project; and it is also used to realize the management of urban emergency resource data information.

[0050] Application function layer 5 is used for dynamic visualization of urban water affairs, real-time analysis of urban water affairs fault information, and guidance for decision-making on emergency plans for urban water affairs faults.

[0051] Furthermore, IoT sensing devices monitor and perceive information data from multiple water-related projects within the city, including data from various water source projects, water supply projects, water-saving projects, drainage projects, sewage treatment projects, water resource recycling projects, and pipeline projects. In practical applications, the monitored and perceived data is uniformly stored in server infrastructure layer 2 via wireless transmission, and computing processing space is provided for the data.

[0052] Figure 2 The system provides images of the river surface for monitoring. In practical applications, water quality testing equipment is deployed in the river to monitor river temperature, turbidity, conductivity, pH, and dissolved oxygen.

[0053] Furthermore, server infrastructure layer 2 includes cloud storage servers and cloud computing servers;

[0054] The cloud storage server is used to store multi-source water conservancy project information data, as well as data after classification, preprocessing and anomaly analysis; specifically, the stored data is collected and updated to cover diverse data of urban drainage systems such as public facilities, hydrology and meteorology, and geographic information.

[0055] Cloud computing servers support big data classification algorithms, big data computing algorithms, and intelligent analysis algorithms for classifying, preprocessing, and analyzing data anomalies from multiple sources of water conservancy project information. In practical applications, they are primarily used to decompose data processing programs, breaking down massive data processing tasks into numerous smaller programs, which are then processed and analyzed by the server to obtain the results.

[0056] Furthermore, the algorithm integration layer 3 includes a big data storage algorithm module, a big data computing algorithm module, and an intelligent analysis algorithm module;

[0057] The big data classification algorithm module embeds a big data classification algorithm, which is used to classify multi-source water conservancy project information data stored in server facility layer 2 by keywords when data classification and storage work is required; when data extraction work is required, it is used to retrieve the required data from the cloud storage server of server facility layer 2 by searching by the classification keywords corresponding to the data to be extracted.

[0058] The big data computing algorithm module is used to configure corresponding big data computing algorithms based on the basic functions of the full-cycle management platform, and to preprocess multi-source water conservancy project information data through the corresponding big data computing algorithms. In specific applications, the basic functions of the full-cycle management platform include pollutant concentration monitoring and pipeline system operation status data monitoring. The big data computing algorithms include water quality monitoring algorithms and pipeline monitoring algorithms. The water quality monitoring algorithm monitors water quality indicators in real time, detects pollutant concentrations in the water, and the water conservancy project information data applied by the water quality monitoring algorithm includes river temperature, turbidity, conductivity, pH, and dissolved oxygen. The pipeline monitoring algorithm monitors the operation status of the pipeline system in real time.

[0059] The intelligent analysis algorithm module is equipped with an intelligent analysis algorithm for performing data anomaly analysis on preprocessed multi-source water conservancy project information data.

[0060] Furthermore, the platform service layer 4 includes a 3D model system, a 3D pipeline system, an IoT sensing data system, and an emergency resource management system. Based on the sensing data, the platform service layer 4 performs 3D visualization modeling, digitally mapping and intelligently simulating all elements of urban water affairs and the entire process of governance and management activities. Specifically:

[0061] The 3D modeling system is used to construct 3D models of water facilities such as plants and pumping stations based on building data from water source engineering data, water supply engineering data, and drainage engineering data in multi-source water engineering information data.

[0062] A 3D pipeline system is used to construct a 3D model of urban water pipeline facilities based on pipeline engineering data from multi-source water engineering information data.

[0063] The IoT sensing data system is used to mark the location of each monitoring point in the 3D model of plant water facilities, the 3D model of pump station water facilities, and the 3D model of urban water pipeline facilities by using non-engineering data from water source engineering data, water supply engineering data, drainage engineering data, and pipeline engineering data in multi-source water engineering information data.

[0064] The emergency resource management system is used to count the location of urban emergency resources and the quantity of urban emergency resources at each location.

[0065] Furthermore, the application function layer 5 includes a multi-source data integration and visualization module, an operational status awareness module, a comprehensive analysis and judgment module, and an emergency response and coordination module;

[0066] The multi-source data integration and visualization module is used to dynamically display and visualize the constructed 3D model of water conservancy projects, non-engineering data from multi-source water conservancy project information data, and the locations of various monitoring points in the 3D model of water conservancy projects. It is also used to zoom in, zoom out, move, rotate, and control the 3D model layers of water conservancy projects. Furthermore, it is used to visualize the locations of various monitoring points in the 3D model of water conservancy projects and the locations and quantities of urban emergency resources on a 2D map.

[0067] The operational situation awareness module is used to build an Internet of Things (IoT) system. Through data acquisition and monitoring devices set up at the water engineering site, the system interconnects with the full-cycle management platform via the IoT to realize the perception of the operational status of equipment in the three-dimensional model of the water engineering project and the perception of the changing patterns of water operation, providing a foundation for tracing the spatial and temporal evolution of water affairs.

[0068] The comprehensive analysis and judgment module is used to set the trigger threshold for water conservancy project fault alarms, and compares the abnormal data obtained from data anomaly analysis using server facility layer 2 with the water conservancy project fault alarm trigger threshold to identify risks and determine the risk level of alarm information; its comprehensive analysis and judgment module provides early visual warnings and provides scientific decision support for business areas such as water supply scheduling optimization and pipeline planning;

[0069] The emergency response module is used to enable resource linkage between the multi-data integration and visualization module, the operational situation awareness module, and the comprehensive analysis and judgment module. It also integrates with the communication command platform to achieve cross-departmental and cross-business collaborative command and dispatch, and assist in emergency response and emergency resource allocation.

[0070] Specific application examples of this invention are as follows:

[0071] (1) Fault point monitoring: The sensor detects the fault point in the urban water project and transmits it to the full life cycle management platform through wireless transmission. After the platform analyzes and judges the cause of the fault, the future development direction of the fault, various emergency solutions and emergency items that can be urgently called, it displays the data through the multi-data integration visualization module to ensure that the fault point is eliminated as early and accurately as possible.

[0072] (2) Fault point prediction: Sensor detection information is transmitted wirelessly into the full life cycle management platform. The platform analyzes and judges the fault information and suggested maintenance plan that may occur in the future. The data is visualized through the multi-data integration visualization module to ensure that the fault point is accurately eliminated before it occurs.

[0073] (3) Daily maintenance visualization observation: Sensor detection information is transmitted wirelessly into the full-cycle management platform. The platform stores and analyzes the monitoring data and displays it through a multi-data integration visualization module to ensure the daily maintenance visualization observation of urban water affairs.

[0074] While the invention has been described herein with reference to specific embodiments, it should be understood that these embodiments are merely examples of the principles and applications of the invention. Therefore, it should be understood that many modifications can be made to the exemplary embodiments, and other arrangements can be designed without departing from the spirit and scope of the invention as defined by the appended claims. It should be understood that different dependent claims and features described herein can be combined in ways different from those described in the original claims. It is also understood that features described in conjunction with individual embodiments can be used in other described embodiments.

Claims

1. A digital twin-based smart city water management platform covering the entire lifecycle, characterized in that: include: The Internet of Things (IoT) sensing layer is used to monitor and sense information data of multi-source water conservancy projects in the city through IoT sensing devices. The server infrastructure layer is used to store multi-source water conservancy project information data, as well as to classify, preprocess, and perform data anomaly analysis on the multi-source water conservancy project information data, and store the data after classification, preprocessing, and data anomaly analysis. The algorithm integration layer is used to configure corresponding algorithms for classification, preprocessing, and data anomaly analysis of the server infrastructure layer. The algorithm integration layer includes a big data storage algorithm module, a big data computing algorithm module, and an intelligent analysis algorithm module; The big data classification algorithm module embeds a big data classification algorithm, which is used to classify multi-source water conservancy project information data stored in the server infrastructure layer by keywords when data classification and storage work is required; when data extraction work is required, the required data is extracted from the cloud storage server in the server infrastructure layer by searching by the classification keywords corresponding to the data to be extracted. The big data computing algorithm module is used to configure the corresponding big data computing algorithm according to the basic functions of the full-cycle management platform, and to preprocess the multi-source water conservancy project information data through the corresponding big data computing algorithm; The intelligent analysis algorithm module is equipped with an intelligent analysis algorithm for performing data anomaly analysis on the pre-processed multi-source water conservancy project information data. The platform service layer is used to perform visual 3D modeling based on engineering data from the monitored and perceived multi-source water conservancy project information data within the city, thereby obtaining a 3D model of the water conservancy project; it is also used to perform digital mapping between non-engineering data from the multi-source water conservancy project information data and the constructed 3D model of the water conservancy project; and it is also used to realize the management of urban emergency resource data information. The application function layer is used for dynamic visualization of urban water affairs, real-time analysis of urban water affairs fault information, and guidance for decision-making on emergency plans for urban water affairs faults. The application functional layer includes a multi-data integration and visualization module, an operational status awareness module, a comprehensive analysis and judgment module, and an emergency response and coordination module. The multi-source data integration and visualization module is used to dynamically display and visualize the constructed 3D model of water conservancy projects, non-engineering data from multi-source water conservancy project information data, and the locations of various monitoring points in the 3D model of water conservancy projects. It is also used to zoom in, zoom out, move, rotate, and control the 3D model layers of water conservancy projects. Furthermore, it is used to visualize the locations of various monitoring points in the 3D model of water conservancy projects and the locations and quantities of urban emergency resources on a 2D map. The operational situation awareness module is used to build an Internet of Things (IoT) system. Through data acquisition and monitoring devices set up at the water engineering site, the system interconnects with the full-cycle management platform via the IoT to realize the perception of the operational status of equipment in the three-dimensional model of the water engineering project and the perception of the changing patterns of water operation. The comprehensive analysis and judgment module is used to set the trigger threshold for water conservancy project fault alarms, and compare the abnormal data obtained by data anomaly analysis at the server facility layer with the water conservancy project fault alarm trigger thresholds to make risk judgments and determine the risk level of alarm information. The emergency response module is used to enable resource linkage between the multi-data integration and visualization module, the operational situation awareness module, and the comprehensive analysis and judgment module. It also integrates with the communication command platform to achieve cross-departmental and cross-business collaborative command and dispatch, and assist in emergency response and emergency resource allocation.

2. The urban smart water affairs full-cycle management platform based on digital twins as described in claim 1, characterized in that, The information data of multi-source water projects in the city includes data on various water source projects, water supply projects, water conservation projects, drainage projects, sewage treatment projects, water resource recycling projects, and pipeline projects.

3. The urban smart water affairs full-cycle management platform based on digital twins as described in claim 1, characterized in that, The server infrastructure layer includes cloud storage servers and cloud computing servers; Cloud storage servers are used to store multi-source water conservancy project information data, as well as data that has been classified, preprocessed, and analyzed for data anomalies; The cloud computing server supports big data classification algorithms, big data computing algorithms, and intelligent analysis algorithms for classifying, preprocessing, and analyzing data anomalies in multi-source water conservancy project information data.

4. The urban smart water affairs full-cycle management platform based on digital twins as described in claim 1, characterized in that, The platform service layer includes a 3D model system, a 3D pipeline system, an IoT sensing data system, and an emergency resource management system; The 3D modeling system is used to construct 3D models of water facilities such as plants and pumping stations based on building data from water source engineering data, water supply engineering data, and drainage engineering data in multi-source water engineering information data. A 3D pipeline system is used to construct a 3D model of urban water pipeline facilities based on pipeline engineering data from multi-source water engineering information data. The IoT sensing data system is used to mark the location of each monitoring point in the 3D model of plant water facilities, the 3D model of pump station water facilities, and the 3D model of urban water pipeline facilities by using non-engineering data from water source engineering data, water supply engineering data, drainage engineering data, and pipeline engineering data in multi-source water engineering information data. The emergency resource management system is used to count the location of urban emergency resources and the quantity of urban emergency resources at each location.

5. The urban smart water affairs full-cycle management platform based on digital twins as described in claim 1, characterized in that, Big data computing algorithms include water quality monitoring algorithms and pipeline monitoring algorithms.

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