Method and system for realizing vertical multi-level water resource management

Abstract

The invention provides a method and a system for realizing vertical multi-level water resource management, and belongs to the technical field of water affairs. The water resource management method is applied to a vertical multi-level water resource management system. The water resource management system comprises a water resource data terminal, a regional gateway and a cloud platform. The water resource management method comprises the steps that water resource data terminals of different levels in multiple vertical levels report water consumption data; the regional level gateway aggregates the water consumption data reported by each terminal, performs data preprocessing on the water consumption data and forwards the water consumption data to the cloud platform; the cloud platform performs correlation analysis on the water consumption data to obtain an early warning and decision report; and the cloud platform issues the early warning and decision report to a corresponding water resource data terminal, so that the terminal adjusts the next batch of water consumption data in combination with the early warning and decision report. The problems that the popularization and operation effects of an existing vertical multi-level water resource scheme are restricted, and multi-level vertical integrated water resource comprehensive management is difficult to really achieve can be solved.

Description

Technical Field

[0001] This application belongs to the field of water technology, specifically relating to a method and system for realizing vertical multi-level water resource management. Background Technology

[0002] With the deep integration of digital technologies such as cloud computing, big data, the Internet of Things (IoT), and digital twins in the water sector, smart water management platforms have evolved from simple monitoring and dispatching systems to integrated solutions covering data collection, transmission, storage, processing, and application. To adapt to this change, some manufacturers have launched data aggregation and intelligent analysis products based on IoT sensing and cloud platforms. However, the smart water management market is highly fragmented, with both specialized research institutes focusing on information services and manufacturers primarily producing sensors and hardware, resulting in fierce market competition and varying levels of integration.

[0003] The main shortcomings of existing technologies lie in the data silos caused by the fragmentation of multi-departmental and multi-level systems, the lack of interface standards, and the difficulty in achieving unified management and control at vertical levels (e.g., city-county-town-end point). Existing multi-level inter-collaboration mechanisms and standardized data models have not yet been implemented, and the high deployment and maintenance costs deter small and medium-sized water utilities. The main reason is that water conservancy systems at various levels are often independently constructed by different manufacturers or departments, lacking a unified top-level design after introducing new technologies, and lacking mature interface and data standards within the industry. To address these issues, related technologies provide a cloud-based water resources management system that integrates GIS, monitoring data interfaces, and business model modules. This technology enables cyclical allocation at three levels: time, space, and user. In addition, there are methods for managing urban multi-source safe water supply that emphasize digital management of the pipeline network and optimal scheduling.

[0004] Although the above solutions have made breakthroughs in physical sensing, cloud analysis and decision support, they still have shortcomings in multi-level linkage, real-time collaboration, closed-loop process and standardization scalability: due to the lack of unified industry standards and the different levels of infrastructure construction in various regions, the promotion and operation of the above measures are still constrained, and it is difficult to truly achieve vertical integrated water resource management from city to county to town to end point. Summary of the Invention

[0005] This application aims to provide a method, equipment, and medium for realizing vertical multi-level water resource management. It addresses the limitations of existing technologies, such as the lack of unified industry standards, varying levels of infrastructure development across regions, and limited funding, which hinder the promotion and effective operation of vertical multi-level water resource solutions and make it difficult to truly achieve integrated water resource management across the city, county, town, and end-point levels.

[0006] According to a first aspect of this application, embodiments of this application provide a method for implementing vertically multi-level water resource management, used in a vertically multi-level water resource management system. The water resource management system includes water resource data terminals respectively set in each level of the vertical multi-level system, a regional gateway electrically connected to the water resource data terminals, and a cloud platform electrically connected to the regional gateway. The water resource management method includes:

[0007] Water resource data terminals at different levels in a vertical multi-level system report water usage data, which includes water usage plan data, water usage statistics data, and payment data.

[0008] The regional gateway aggregates water usage data reported by various water resource data terminals, and forwards the water usage data to the cloud platform after data preprocessing.

[0009] The cloud platform performs correlation analysis on water usage planning data, water usage statistics, and payment data to generate early warning and decision-making reports;

[0010] The cloud platform will distribute early warnings and decision reports to the corresponding water resource data terminals in the vertical multi-level system, so that the water resource data terminals can adjust the water use data for the next batch based on the early warnings and decision reports.

[0011] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, the steps of water resource data terminals at different levels reporting water use data include:

[0012] The water resources data terminal at the highest level of the vertical multi-level system issues water use plan application templates to each of the lower-level water resources data terminals.

[0013] Each lower-level water resources data terminal fills in the water use plan application template, obtains water use plan data, and reports the water use plan data to the cloud platform;

[0014] A water resource data terminal at a specific level in a vertical multi-level system aggregates water metering data collected by various end-user water devices and submits the aggregated water metering data to the water resource data terminal at the higher level to obtain water usage statistics.

[0015] The user terminals of end users in the vertical multi-level system upload real-time report data and payment requests to the cloud platform to obtain payment data.

[0016] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, the step of the regional gateway aggregating water usage data reported by various water resource data terminals and forwarding the water usage data to the cloud platform after data preprocessing includes:

[0017] The regional gateway uses an MQTT / REST dual-protocol gateway and a local caching mechanism to perform format verification, local caching, and message aggregation processing on the water usage data reported by each water resource data terminal.

[0018] The regional gateway uses the HTTPS / OAuth protocol to forward the processed water usage data to the cloud platform in batches.

[0019] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, the step of the cloud platform performing correlation analysis on water use planning data, water use statistics data, and payment data to obtain early warning and decision reports includes:

[0020] The cloud platform uses the Spring Cloud microservice framework to acquire and track water usage plan data, water usage statistics, and payment data.

[0021] The cloud platform uses Spark SQL and a unified data model to perform ETL operations on water usage planning data, water usage statistics data, and payment data to generate early warning and decision reports.

[0022] The cloud platform uses GIS visualization methods to display early warning and decision-making reports.

[0023] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, the step of the cloud platform performing correlation analysis on water use planning data, water use statistics data, and payment data to obtain early warning and decision reports includes:

[0024] The cloud platform inputs water usage plan data, water usage statistics, and payment data into the built-in distributed deep learning model;

[0025] The cloud platform uses a distributed deep learning model to perform correlation learning on water usage plan data, water usage statistics data, and payment data, and predicts the early warning feature information corresponding to each water usage data.

[0026] The cloud platform uses dynamic knowledge graphs to match early warning feature information to obtain decision-making solutions;

[0027] The cloud platform combines early warning feature information and decision-making schemes to generate early warning and decision-making reports.

[0028] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, the step of the cloud platform distributing early warning and decision reports to the corresponding water resource data terminals in the vertical multi-level system includes:

[0029] The cloud platform uses unified key management and TLS encryption services to encrypt early warning and decision reports;

[0030] The cloud platform will distribute encrypted early warnings and decision reports to the water resources data terminal;

[0031] The cloud platform uses the multi-level log tracing mechanism provided by the Spring Cloud microservice framework to track the transmission process of alerts and decision reports.

[0032] Preferably, in the above-mentioned method for implementing vertical multi-level water resource management, after the step of the cloud platform distributing early warning and decision reports to the corresponding water resource data terminals in the vertical multi-level system, the method further includes:

[0033] The cloud platform triggers a full ETL operation on water usage data at fixed times through a pipeline mechanism, and processes the water usage data by scheduling Spark SQL tasks through the data middle platform, generating reports and pushing them out.

[0034] The cloud platform controls the regional gateway and performs aggregation operations on water usage data at fixed intervals.

[0035] The end-user firmware in a vertically multi-level system performs meter reading operations at fixed intervals to obtain and upload report data.

[0036] According to a second aspect of this application, this application also provides a vertically multi-level water resource management system, the water resource management system comprising:

[0037] Water resource data terminals are respectively set up at each level of the vertical multi-level system; regional gateways are electrically connected to the water resource data terminals; and cloud platforms are electrically connected to the regional gateways.

[0038] Water resource data terminals at different levels in a vertical multi-level system are used to report water use data, which includes water use planning data, water use statistics data, and payment data.

[0039] The regional gateway is used to aggregate water usage data reported by various water resource data terminals and forward the water usage data to the cloud platform after data preprocessing.

[0040] The cloud platform is used to perform correlation analysis on water usage planning data, water usage statistics data, and payment data to obtain early warning and decision-making reports;

[0041] The cloud platform is also used to distribute early warnings and decision reports to the corresponding water resource data terminals in the vertical multi-level system, so that the water resource data terminals can adjust the water use data for the next batch based on the early warnings and decision reports.

[0042] Preferably, in the above-mentioned water resources management system, the water resources data terminal corresponding to the highest level of the vertical multi-level system is used to issue water use plan application templates to each of the lower-level water resources data terminals respectively.

[0043] Each lower-level water resources data terminal is used to fill in the water use plan application template, obtain water use plan data, and report the water use plan data to the cloud platform;

[0044] A water resources data terminal at a specific level in a vertical multi-level system is used to aggregate water metering data collected by various end-use water devices under its jurisdiction, and submit the aggregated water metering data to the water resources data terminal at the higher level to obtain water usage statistics.

[0045] The user terminals of end users in the vertical multi-level system are used to upload real-time report data and payment requests to the cloud platform to obtain payment data.

[0046] Preferably, in the aforementioned water resource management system, the regional gateway is used to aggregate water usage data reported by various water resource data terminals, and to preprocess the water usage data before forwarding it to the cloud platform, specifically including:

[0047] The regional gateway is specifically used to perform format verification, local caching, and message aggregation processing on the water usage data reported by each water resource data terminal using an MQTT / REST dual-protocol gateway and a local caching mechanism.

[0048] The regional gateway is specifically used to forward processed water usage data to the cloud platform in batches using the HTTPS / OAuth protocol.

[0049] Preferably, in the aforementioned water resource management system, the cloud platform is specifically used to obtain and track water usage plan data, water usage statistics data, and payment data using the Spring Cloud microservice framework;

[0050] The cloud platform is specifically used to perform ETL operations on water usage planning data, water usage statistics data, and payment data using Spark SQL and a unified data model, generating early warning and decision reports.

[0051] The cloud platform is specifically used to display early warning and decision-making reports using GIS visualization methods.

[0052] Preferably, in the aforementioned water resource management system, the cloud platform is specifically used to input water use planning data, water use statistics data, and payment data into a built-in distributed deep learning model; use the distributed deep learning model to perform correlation learning on the water use planning data, water use statistics data, and payment data to predict the early warning feature information corresponding to each water use data; use a dynamic knowledge graph to match the early warning feature information to obtain a decision-making scheme; and combine the early warning feature information and the decision-making scheme to generate early warning and decision-making reports.

[0053] Preferably, in the aforementioned water resources management system, the cloud platform is specifically used to encrypt early warning and decision reports using unified key management and TLS encryption services; to distribute the encrypted early warning and decision reports to the water resources data terminal; and to use the multi-level log tracing mechanism provided by the Spring Cloud microservice framework to track the transmission process of early warning and decision reports.

[0054] Preferably, in the aforementioned water resource management system, the cloud platform is also used to trigger a full ETL operation on water usage data at fixed times through a pipeline mechanism, process the water usage data through Spark SQL tasks scheduled by the data platform, generate reports and push them; the cloud platform is also used to control regional gateways to perform aggregation operations on water usage data at fixed times; the end-user firmware in the vertical multi-level system is also used to perform meter reading operations at fixed times, obtain report data and upload it.

[0055] The technical solution of this application has at least the following technical effects:

[0056] This application's water resource management method is used in a vertically multi-level water resource management system, such as a city-county-town-end-terminal vertical multi-level structure. The water resource management system includes water resource data terminals set up at each level of the vertical multi-level structure; for example, each level from city to county to town to end-terminal has a water resource data terminal. The end-terminal water resource data terminals can be smart water meters, multi-functional sensors, and user terminals, while other levels' water resource data terminals can be servers and displays, etc. Specifically, in this water resource management method, water resource data terminals at different levels of the vertical multi-level structure report water usage data. For example, lower-level water resource data terminals report water usage plans, and specific-level water resource data terminals aggregate water metering data from subordinate end-terminal water-using devices to obtain water usage statistics; end-terminal user terminals upload payment data, etc. This allows the water usage data reported by each water resource data terminal to be aggregated through a regional gateway, and the water usage data is preprocessed before being forwarded to the cloud platform. The cloud platform can perform correlation analysis on the above water usage data, provide early warnings and make decisions, and finally distribute the early warning and decision reports to the corresponding water resource terminals in the vertical multi-level system. This enables each water resource terminal to adjust the water usage data for the next batch, thus realizing a closed-loop connection from material signal acquisition to decision support, and is compatible with practicality, high reliability and scalability.

[0057] In summary, the technical solution of this application constructs a multi-level, vertically integrated water resource management platform capable of operating at the city-county-town-end-terminal levels. This platform employs a three-layer architecture of edge sensing, regional aggregation, and cloud application, combined with containerized deployment and microservice orchestration. This ensures both the real-time performance of end-user devices and the platform's high availability and ease of maintenance. Through this three-layer architecture of edge sensing, regional aggregation, and cloud application of water resource data terminals, seamless flow and closed-loop management of physical signals and business data are achieved. Furthermore, by combining a unified data platform, a multi-table data model, and microservice-based business logic, the platform meets the high timeliness requirements of real-time meter reading and monthly statistics, while also supporting annual plan applications, intelligent analysis, and precise decision-making. This method enables closed-loop feedback scheduling and dynamic parameter adjustment, addressing the limitations imposed by the lack of unified industry standards and varying levels of infrastructure development across regions in existing technologies, which hinder the widespread adoption and effective operation of these measures and prevent the true realization of vertically integrated water resource management at the city-county-town-end-terminal levels. Attached Figure Description

[0058] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0059] Figure 1 A flowchart illustrating the first method for implementing vertical multi-level water resource management provided in this application embodiment;

[0060] Figure 2 A flowchart illustrating a second method for implementing vertical multi-level water resource management, provided in an embodiment of this application;

[0061] Figure 3 This is a schematic diagram of a vertically multi-level water resource management system provided in an embodiment of this application. Detailed Implementation

[0062] To more clearly illustrate the overall concept of this application, a detailed explanation is provided below with reference to the accompanying drawings.

[0063] Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application may also be implemented in other ways different from those described herein. Therefore, the scope of protection of this application is not limited to the specific embodiments disclosed below. It should be noted that, unless otherwise specified, the embodiments of this application and the features thereof can be combined with each other.

[0064] In this application, unless otherwise expressly specified and limited, the terms "above" and "below" the second feature can refer to direct contact between the first and second features, or indirect contact between the first and second features through an intermediate medium. In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described can be combined in any suitable manner in one or more embodiments or examples.

[0065] The existing technology has the following drawbacks:

[0066] The main shortcomings of existing technologies lie in the data silos caused by the fragmentation of multi-departmental and multi-level systems, the lack of interface standards, and the difficulty in achieving unified management and control at vertical levels (e.g., city-county-town-end point). The primary reason is that water conservancy systems at various levels are often independently constructed by different manufacturers or departments, lacking a unified top-level design after the introduction of new technologies, and lacking mature interface and data standards within the industry. To address these issues, related technologies have provided cloud-based water resource management systems. While such systems have made breakthroughs in physical sensing, cloud analysis, and decision support, they still have shortcomings in multi-level linkage, real-time collaboration, closed-loop processes, and standardized scalability: due to the lack of unified industry standards and varying levels of infrastructure development across regions, the promotion and operational effectiveness of these measures remain constrained, making it difficult to truly achieve vertically integrated water resource management across the city-county-town-end point.

[0067] To address the aforementioned technical issues such as data silos, the following embodiments of this application provide a vertically multi-level water resource management solution. This solution introduces a unified data platform and microservice architecture, and attempts to achieve intelligent early warning and optimized scheduling based on digital twins and AI models. To address the issue of manual delays, it introduces automatic meter reading and online reporting functions to improve statistical timeliness. To address the challenges of multi-level collaboration, it strengthens top-level design and establishes unified API standards. The water resource management solution provided in the following embodiments of this application achieves seamless flow and closed-loop management of physical signals and business data through a three-layer architecture of edge perception, regional aggregation, and cloud applications for water resource data terminals. Simultaneously, by combining a unified data platform, a multi-meter data model, and microservice-based business logic, it not only meets the high timeliness requirements of real-time meter reading and monthly statistics but also supports annual plan applications, intelligent analysis, and precise decision-making.

[0068] To achieve the above objectives, see [link to relevant documentation]. Figure 1 , Figure 1 This is a flowchart illustrating a method for implementing vertical multi-level water resource management, provided as an embodiment of this application. Figure 1 As shown, this method for implementing vertically multi-level water resource management is used in a vertically multi-level water resource management system, such as a city-county-town-end-terminal vertical multi-level structure. The water resource management system includes water resource data terminals respectively set at each level of the vertical multi-level structure, a regional gateway electrically connected to the water resource data terminals, and a cloud platform electrically connected to the regional gateway; the water resource management method includes:

[0069] S110: Water resource data terminals at different levels in the vertical multi-level system report water use data respectively. The water use data includes water use planning data, water use statistics data, and payment data.

[0070] Specifically, in a preferred embodiment, step S110, the step of water resource data terminals at different levels in a vertical multi-level system reporting water use data, specifically includes the following:

[0071] S111: The water resources data terminal corresponding to the highest level in the vertical multi-level system, which issues water use plan application templates to each lower-level water resources data terminal.

[0072] S112: Each lower-level water resources data terminal fills in the water use plan application template, obtains the water use plan data, and reports the water use plan data to the cloud platform.

[0073] S113: A water resource data terminal at a specific level in a vertical multi-level system, which aggregates water metering data collected by subordinate end-user water devices, submits the aggregated water metering data to the superior water resource data terminal, and obtains water usage statistics.

[0074] S114: The user terminal of the end user in the vertical multi-level system uploads real-time report data and payment requests to the cloud platform to obtain payment data.

[0075] Combination Figure 3 The vertical multi-level structure shown, from city to county to town to end point, is illustrated using the corresponding water resource management method as an example:

[0076] First, during the initialization phase, the municipal water resources bureau server distributes annual water use plan application templates to county-level, town-level, and end-user terminals, completing the definition of the objects and data structures for each level of plan application.

[0077] Secondly, management entities at the county and township levels fill in their annual plans on their respective interfaces and upload the information, along with water usage plan data (objects: water consumption, water usage type, user information, etc.), to the unified data platform of the cloud platform. The system will automatically verify the format and return the upload results.

[0078] Then, the monthly water usage statistics are collected periodically (e.g., at the beginning of each month) by the township-level server through end-point water metering devices such as smart water meters and wireless transmission modules, supplemented by manual data entry, and detailed agricultural water usage data (specific to the land conditions, planting structure, start and end times of water use, and average water consumption per mu of water users). The water metering data (objects) are then summarized and submitted to the county and city-level databases, resulting in the generation of monthly water usage statistics reports.

[0079] Finally, there is the end-user metering and water bill payment stage. End-users submit real-time reports and payment requests through mobile devices or self-service terminals (e.g., smart terminals and QR code payment modules). The system calculates the fees based on a preset rate model and completes the deduction, resulting in an updated user account balance and payment record.

[0080] The relationships between the above steps are as follows: initialization → plan application → data collection → payment deduction → statistical analysis. If processed through a cloud platform, feedback and adjustment are also included. The output of the previous step becomes the input of the next step. Among them, the key step "monthly water consumption statistics" is broken down into four sub-steps: data collection, format verification, data aggregation, and report generation, thereby ensuring the accuracy and completeness of the collected smart water meter data. A unified data structure adopts a multi-table association method, with annual plan tables, monthly statistics tables, and payment record tables linked through user ID and timestamp fields. Each step performs read and write operations on these data structures. Fields in the data structure, such as "water consumption," "timestamp," and "hierarchical identifier," correspond to the actual processing objects (annual plan application, monthly meter reading, and payment transactions), ensuring a one-to-one mapping between data and business objects. Hardware aspects include city-county-town level servers, cloud storage devices, end-point smart water meters and wireless communication modules, and user mobile terminals, all working together to support the implementation of each step of the system.

[0081] Figure 1 The water resource management method provided in the illustrated embodiment, after water resource data terminals at different levels in a vertical multi-level system report water usage data respectively, further includes:

[0082] S120: The regional gateway aggregates water usage data reported by various water resource data terminals, performs data preprocessing on the water usage data, and then forwards it to the cloud platform.

[0083] Specifically, in a preferred embodiment, step S120, which involves the regional gateway aggregating water usage data reported by various water resource data terminals and preprocessing the water usage data before forwarding it to the cloud platform, includes:

[0084] S121: The regional gateway uses an MQTT / REST dual-protocol gateway and a local caching mechanism to perform format verification, local caching, and message aggregation processing on the water usage data reported by each water resource data terminal;

[0085] S122: The regional gateway uses the HTTPS / OAuth protocol to forward the processed water usage data to the cloud platform in batches.

[0086] In summary, the technical solution provided in this application deploys smart water meters and multi-functional sensors at the terminal to collect physical quantities such as flow rate, pressure, and temperature in real time, and uploads them to a regional-level MQTT / REST dual-protocol gateway via an LPWAN wireless network. The server within the regional-level gateway performs format verification, local caching, and preliminary statistics on the data, and then forwards it to the cloud platform via HTTPS / OAuth protocol. Through the above method, the regional-level gateway provided in this application embodiment can achieve data format verification, duplicate data filtering, and minute-level caching of water usage data. The regional-level gateway, through its built-in MQTT / REST dual-protocol gateway and local caching mechanism, can perform format verification, duplicate filtering, and batch forwarding of reported data, while also providing retransmission and alarm functions in case of network anomalies.

[0087] Figure 1 The water resource management method provided in the illustrated embodiment, after the regional gateway performs data preprocessing on water usage data and forwards it to the cloud platform, further includes:

[0088] S130: The cloud platform performs correlation analysis on water usage planning data, water usage statistics data, and payment data to obtain early warning and decision reports.

[0089] The technical solution of this application employs a multi-table association method for its unified data structure. Water usage data, such as the annual plan table, monthly statistics table, and payment record table, are associated through user ID and timestamp fields. The aforementioned steps perform read and write operations on these data structures. Fields in the data structures, such as "water consumption," "timestamp," and "hierarchical identifier," correspond to the actual processing objects (annual plan application, monthly meter reading, and payment transactions), thereby ensuring a one-to-one mapping between data and business objects.

[0090] For example, in the water resource management method corresponding to the above-mentioned vertical multi-level structure of city-county-town-end, the city-level server performs correlation analysis and visualization of annual plans, monthly statistics, water fee payment and other data based on a unified data model and multi-dimensional data structure (tables, time series, geographic information, etc.) to generate reports, and the results are intelligent early warning and decision-making suggestions.

[0091] Specifically, as a preferred embodiment, in the above-described method for implementing vertical multi-level water resource management, step S130: the cloud platform performs correlation analysis on water use planning data, water use statistics data, and payment data to obtain early warning and decision reports, including:

[0092] S131: The cloud platform uses the Spring Cloud microservice framework to obtain and track water usage plan data, water usage statistics data, and payment data.

[0093] S132: The cloud platform uses Spark SQL and a unified data model to perform ETL operations on water usage planning data, water usage statistics data, and payment data to generate early warning and decision reports.

[0094] S133: The cloud platform uses GIS visualization methods to display early warning and decision-making reports.

[0095] The technical solution provided in this application utilizes a cloud platform based on Spring Cloud microservices and a Hadoop / Spark big data platform. This platform enables multi-meter ETL operations to be performed on water usage data, including annual plans, monthly statistics, and payment records, generating reports and driving visualization dashboards and intelligent early warning systems. The entire system achieves a closed-loop connection from physical signal acquisition to decision support, balancing real-time performance, high availability, and scalability. By aggregating annual plans, meter reading data, monthly statistics, and water bill payment information into a unified data platform, and using Spark SQL and machine learning models for multi-dimensional correlation analysis, the system provides managers with visualized reports and intelligent early warning systems, significantly improving the scientific rigor and timeliness of decision-making.

[0096] In addition, as a preferred embodiment, in this method for implementing vertical multi-level water resource management, step S130, where the cloud platform performs correlation analysis on water use planning data, water use statistics data, and payment data to obtain early warning and decision reports, includes:

[0097] S134: The cloud platform inputs water usage plan data, water usage statistics data, and payment data into the built-in distributed deep learning model.

[0098] S135: The cloud platform uses a distributed deep learning model to perform correlation learning on water usage plan data, water usage statistics data, and payment data, and predicts the early warning feature information corresponding to each water usage data.

[0099] S136: The cloud platform uses dynamic knowledge graphs to match early warning feature information to obtain decision-making solutions.

[0100] S137: The cloud platform combines early warning feature information and decision-making schemes to generate early warning and decision-making reports.

[0101] The cloud platform in this application uses a distributed deep learning model based on TensorFlow on Spark to perform correlation learning on water usage plan data, water usage statistics data, and payment data. It predicts the early warning feature information corresponding to each water usage data, thereby providing early warnings for water usage at each level. Furthermore, it uses a dynamic knowledge graph, i.e., a case library, to perform feature similarity matching between cases and solutions, thereby obtaining a solution.

[0102] Figure 1 The water resource management method for vertical multi-level management provided in the illustrated embodiment, after the step of performing correlation analysis on water use planning data, water use statistics data, and payment data on the cloud platform to obtain early warning and decision reports, further includes:

[0103] S140: The cloud platform will distribute early warnings and decision reports to the corresponding water resource data terminals in the vertical multi-level system, so that the water resource data terminals can adjust the water use data for the next batch based on the early warnings and decision reports.

[0104] Specifically, in a preferred embodiment, step S140 involves the cloud platform distributing early warning and decision reports to the corresponding water resource data terminals at the vertical multi-level hierarchy, specifically including:

[0105] S141: The cloud platform uses unified key management and TLS encryption services to encrypt early warning and decision reports.

[0106] S142: The cloud platform will send encrypted early warning and decision reports to the water resources data terminal.

[0107] S143: The cloud platform uses the multi-level log tracing mechanism provided by the Spring Cloud microservice framework to track the transmission process of alerts and decision reports.

[0108] The technical solution provided in this application employs a distributed ECS cluster and object storage system on the cloud platform, combined with load balancing and container orchestration to ensure high availability and elastic scaling. All devices communicate via unified key management and TLS encrypted communication, balancing security and performance. In summary, the technical solution of this application adopts a three-layer architecture of edge awareness—regional aggregation—cloud application, combined with containerized deployment and microservice orchestration, ensuring both the real-time performance of end devices and the high availability and ease of maintenance of the platform. Multi-level log tracing and Trace ID auditing mechanisms achieve end-to-end operational visualization, providing a solid guarantee for system operation and maintenance and regulatory compliance. Simultaneously, modular design and standardized interfaces provide a convenient path for subsequent functional expansion and third-party access, enhancing the system's sustainable development capabilities throughout its lifecycle.

[0109] In addition, as a preferred embodiment, in the above-described method for implementing vertical multi-level water resource management, after the step of the cloud platform distributing the early warning and decision reports to the corresponding water resource data terminals in the vertical multi-level system, the method further includes:

[0110] S150: The cloud platform triggers a full ETL job on water usage data at fixed times through a pipeline mechanism. The data middle platform schedules Spark SQL tasks to process the water usage data, generate reports, and push them out.

[0111] S160: The cloud platform controls the regional gateway and performs aggregation operations on water usage data at fixed intervals.

[0112] S170: The end firmware for end users in a vertical multi-level system, which performs meter reading operations at fixed intervals, obtains report data, and uploads it.

[0113] As a specific implementation, the city-level cloud platform can trigger a full ETL job daily at 03:00 via a CI / CD pipeline (Jenkins + GitLab CI), with Spark-SQL scheduled by the data platform.

[0114] The task processes the previous day's data, generates a report at 06:00 and pushes it to the dashboard; the regional gateway service is continuously run by the system integrator in the county-level data center, and performs local monthly sampling verification at 03:00 and 15:00; the terminal firmware is burned by the manufacturer at the factory, and automatically performs meter reading and upload at 00:00 and 12:00 after the device is powered on. If there is a network error, it will retry every 5 minutes until it succeeds.

[0115] The technical solution in this application, based on Spring-Cloud microservices and a Hadoop / Spark big data platform in the cloud, performs ETL jobs on multiple tables, including annual water usage plans, monthly statistics, and payment records, to generate reports and drive visualization dashboards and intelligent early warning systems. It achieves a closed-loop process from physical signal acquisition to decision support, balancing real-time performance, high availability, and scalability.

[0116] In summary, the vertical multi-level water resource management method provided in this application is used in vertical multi-level water resource management systems, such as those applicable to a city-county-town-end-terminal vertical multi-level structure. This water resource management system includes water resource data terminals set up at each level of the vertical multi-level structure; for example, each level from city to county to town to end-terminal has a water resource data terminal. The end-terminal water resource data terminals can be smart water meters, multi-functional sensors, and user terminals, while other levels' water resource data terminals can be servers and displays, etc. Specifically, in this water resource management method, water resource data terminals at different levels of the vertical multi-level structure report water usage data. For example, lower-level water resource data terminals report water usage plans, and specific-level water resource data terminals aggregate water metering data from subordinate end-terminal water-using devices to obtain water usage statistics; end-terminal user terminals upload payment data, etc. This allows the water usage data reported by each water resource data terminal to be aggregated through a regional gateway, and the water usage data is preprocessed before being forwarded to the cloud platform. The cloud platform can perform correlation analysis on the above water usage data, provide early warnings and make decisions, and finally distribute the early warning and decision reports to the corresponding water resource terminals in the vertical multi-level system. This enables each water resource terminal to adjust the water usage data for the next batch, thus realizing a closed-loop connection from material signal acquisition to decision support, and is compatible with practicality, high reliability and scalability.

[0117] The technical solution described in this application constructs a multi-level, vertically integrated water resource management platform capable of operating at the city-county-town-end-terminal levels. This platform employs a three-layer architecture of edge sensing, regional aggregation, and cloud applications, combined with containerized deployment and microservice orchestration. This ensures both the real-time performance of end-user devices and the platform's high availability and ease of maintenance. Through this three-layer architecture of edge sensing, regional aggregation, and cloud applications for water resource data terminals, seamless flow and closed-loop management of physical signals and business data are achieved. Furthermore, by combining a unified data platform, a multi-table data model, and microservice-based business logic, the platform meets the high-timeliness requirements of real-time meter reading and monthly statistics, while also supporting annual plan applications, intelligent analysis, and precise decision-making. This method enables closed-loop feedback scheduling and dynamic parameter adjustment, addressing the limitations imposed by existing technologies due to a lack of unified industry standards and varying levels of infrastructure development across regions, which hinder the widespread adoption and effective operation of these measures and prevent the true realization of vertically integrated water resource management at the city-county-town-end-terminal levels.

[0118] Additionally, see Figure 2 , Figure 2 This is a flowchart illustrating a second vertical multi-level water resource management method provided in an embodiment of this application. (Combined with...) Figure 3 As shown in the system, this water resource management method includes the following steps:

[0119] S201: System initialization.

[0120] S202: Issuance of Annual Plan Templates. During the system initialization phase, the municipal water resources bureau server issues annual water use plan application templates to county-level, town-level, and end-user water terminals, completing the definition of the objects and data structures for plan applications at each level.

[0121] S203: Regional-level data entry and upload. Management entities at all levels fill in their annual plans (actions) on their respective interfaces and upload the information (objects: water consumption, water type, user information, etc.) to the unified data platform. The system automatically verifies the format and returns the upload results.

[0122] S204: Determine whether the approval has been granted.

[0123] S205: Water meter reading.

[0124] S206: Regional final-level monthly summary.

[0125] S207: User payment deduction.

[0126] S208: Statistical analysis.

[0127] S209: Loop closed.

[0128] In summary, the technical solution of this application, by constructing a vertically integrated multi-level water resource management system, enables integrated water resource management at the city, county, town, and end-point levels. This achieves closed-loop management throughout the entire process, from annual planning, real-time meter reading, and monthly statistics to payment analysis and decision support, significantly improving water resource allocation efficiency and management accuracy. Furthermore, by leveraging cloud platforms, big data, and the Internet of Things, it achieves efficient data aggregation and transparent sharing, providing reliable support for emergency dispatch and refined irrigation.

[0129] Furthermore, the beneficial effects of the product embodiments provided in the following embodiments of this application are the same as the beneficial effects of the vertical multi-level water resource management method provided in the above embodiments, and other technical features in the product embodiments are the same as the features disclosed in the methods of the above embodiments, and will not be repeated here.

[0130] See Figure 3 , Figure 3 A schematic diagram of a vertically multi-level water resource management system provided in this application embodiment is shown below. Figure 3 As shown, the water resource management system includes:

[0131] A water resource data terminal 1 is installed at each level of the vertical multi-level system; a regional gateway 2 is electrically connected to the water resource data terminal 1; and a cloud platform 3 is electrically connected to the regional gateway 2.

[0132] Water resource data terminals 1 at different levels in a vertical multi-level system are used to report water use data, which includes water use planning data, water use statistics data, and payment data.

[0133] Regional gateway 2 is used to aggregate water usage data reported by various water resource data terminals 1, and forward the water usage data to cloud platform 3 after data preprocessing.

[0134] Cloud Platform 3 is used to perform correlation analysis on water usage planning data, water usage statistics data, and payment data to obtain early warning and decision reports;

[0135] The cloud platform 3 is also used to distribute early warning and decision reports to the corresponding water resource data terminals 1 in the vertical multi-level system, so that the water resource data terminals can adjust the water use data for the next batch based on the early warning and decision reports.

[0136] Specifically, as a preferred embodiment, in the above-mentioned water resource management system, the water resource data terminal 1 corresponding to the highest level of the vertical multi-level system is used to issue water use plan application templates to each of the lower-level water resource data terminals respectively.

[0137] Each lower-level water resources data terminal 1 is used to fill in the water use plan application template, obtain water use plan data, and report the water use plan data to the cloud platform 3;

[0138] A water resource data terminal 1 at a specific level in a vertical multi-level system is used to aggregate water metering data collected by various terminal water-using devices below, and submit the aggregated water metering data to the water resource data terminal 1 at the higher level to obtain water usage statistics.

[0139] The user terminals of end users in the vertical multi-level system are used to upload real-time report data and payment requests to the cloud platform 3 to obtain payment data.

[0140] Specifically, as a preferred embodiment, in the above-mentioned water resource management system, cloud platform 3 is specifically used to obtain and track water use plan data, water use statistics data, and payment data using the Spring Cloud microservice framework;

[0141] Cloud Platform 3 is specifically used to perform ETL operations on water usage planning data, water usage statistics data, and payment data using Spark SQL and a unified data model, generating early warning and decision reports.

[0142] Cloud Platform 3 is specifically used to display early warning and decision-making reports using GIS visualization methods.

[0143] The vertical multi-level water resource management system provided in the above embodiments of this application adopts a three-layer IoT architecture: edge sensing, regional gateway preprocessing, and cloud microservice applications.

[0144] At the end of the system, smart water meters and multi-functional sensors are deployed to collect physical quantities such as flow rate, pressure, and temperature in real time. These data are then uploaded to a regional MQTT / REST gateway via an LPWAN wireless network. The regional server performs format verification, local caching, and preliminary statistics on the data before forwarding it to the cloud platform via HTTPS / OAuth. On the cloud, based on Spring Cloud microservices and a Hadoop / Spark big data platform, ETL jobs are run on multiple tables, including annual plans, monthly statistics, and payment records, to generate reports and drive visualization dashboards and intelligent early warning systems. The entire system achieves a closed-loop connection from physical signal acquisition to decision support, ensuring real-time performance, high availability, and scalability.

[0145] The device layer is responsible for the acquisition and preprocessing of physical signals, the edge layer (regional gateway) performs MQTT message aggregation and RESTful forwarding, and the cloud layer is responsible for business logic, data storage and visualization.

[0146] At the device level, the smart water meter has a built-in mechanical turbine flow sensor or ultrasonic flow meter, and is equipped with secondary pressure and temperature sensors. Its pulses or signals are sampled by the MCU and stored in the on-chip 256 KB Flash, and pushed in real time through the NB-IoT / LoRaWAN network.

[0147] The edge gateway service is deployed using a Docker + Kubernetes cluster at the regional layer. It is responsible for data format verification, duplicate data filtering, and minute-level caching. If the verification fails, an error code is returned and the terminal is triggered to retransmit.

[0148] At the cloud platform layer, based on Spring Cloud microservice orchestration, the data middleware uses Hadoop HDFS to store raw files, SparkSQL to execute ETL jobs, generate various statistical tables, and display real-time and historical trends through ECharts / Grafana dashboards.

[0149] At the physical layer, end-point hardware components include flow, pressure, and temperature sensor modules, all connected to a low-power MCU and LPWAN communication module. Local status and fault information are fed back via buzzers and LED indicators. Regional gateway hardware can be a standard x86 server or an ARM edge box, equipped with a 500GB SSD for local caching and logging. The cloud utilizes a distributed ECS cluster and object storage system, combined with load balancing and container orchestration to ensure high availability and elastic scaling. All devices communicate via unified key management and TLS encrypted communication, balancing security and performance.

[0150] In summary, the technical solution of this application, by constructing a vertically integrated multi-level water resource management system, enables integrated water resource management at the city, county, town, and end-point levels. This achieves closed-loop management throughout the entire process, from annual planning, real-time meter reading, and monthly statistics to payment analysis and decision support, significantly improving water resource allocation efficiency and management accuracy. Furthermore, by leveraging cloud platforms, big data, and the Internet of Things, it achieves efficient data aggregation and transparent sharing, providing reliable support for emergency dispatch and refined irrigation.

[0151] Furthermore, the application of multi-table association and intelligent analysis models not only optimizes operating costs but also contributes to water conservation, emission reduction, and ecological protection, further enhancing the system's scalability and maintainability.

[0152] By using smart water meters and wireless transmission modules to collect data in real time, the traditional manual reporting is replaced, which greatly shortens the statistical cycle and eliminates the manual review process, thereby significantly improving the efficiency of water usage data processing.

[0153] The architecture based on digital twins and cloud-based automated operation and maintenance not only reduces equipment maintenance costs, but also reduces the high repair costs caused by unexpected downtime through predictive fault warnings.

[0154] The regional and cloud-based tiered caching and batch synchronization mechanism effectively reduces network load and ensures high availability and elastic scalability of the system, further saving on IT infrastructure investment and operation and maintenance costs.

[0155] The system integrates annual plans, meter reading data, monthly statistics, and water bill payment information into a unified data platform. It uses Spark SQL and machine learning models to perform multidimensional correlation analysis, providing managers with visual reports and intelligent early warnings, which greatly improves the scientific nature and timeliness of decision-making.

[0156] Furthermore, the water resource management system described in this application, through the use of GIS and geographic heat maps, allows managers to intuitively understand water usage dynamics and potential risks at all levels, enabling precise resource allocation and emergency response. Simultaneously, the system's open APIs and standardized data interfaces provide technical support for third-party system integration and cross-departmental collaboration, promoting government-enterprise cooperation and public participation.

[0157] In irrigation scenarios, this application supports precise water use guidance based on soil type and crop water requirement coefficient through refined end-point irrigation records and deep integration of land, crop, time period, and water volume. This significantly reduces agricultural irrigation water waste and continuously improves water use efficiency. The system's built-in water quality monitoring and alarm functions provide real-time protection for irrigation safety and ecological conservation, contributing to water pollution prevention and ecological restoration. Global research indicates that integrated water resource management can effectively alleviate water shortages and regional water crises while balancing economic benefits and ecological balance.

[0158] In summary, the technical solution presented in this application adopts a three-tier architecture of edge awareness, regional aggregation, and cloud application. Combined with containerized deployment and microservice orchestration, it ensures both the real-time performance of end-devices and the high availability and maintainability of the platform. Multi-level log tracing and Trace ID auditing mechanisms provide end-to-end operational visibility, offering a solid guarantee for system operation, maintenance, and regulatory compliance. Furthermore, the modular design and standardized interfaces provide a convenient path for subsequent functional expansion and third-party integration, enhancing the system's sustainable development capabilities throughout its lifecycle.

[0159] Specifically, according to the embodiments disclosed in this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In this embodiment, the computer program can be downloaded and installed from a network via a communication device, or installed from a storage device, or installed from a ROM. When the computer program is executed by a processing device, it performs the functions defined in the methods of the embodiments disclosed in this application.

[0160] It should be understood that the various parts disclosed in this application can be implemented using hardware, software, firmware, or a combination thereof. In the description of the above embodiments, specific features, structures, materials, or characteristics can be combined in any suitable manner in one or more embodiments or examples.

[0161] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0162] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. In this regard, each block in a flowchart or block diagram can represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks can actually be executed substantially in parallel, and they can sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0163] The modules described in the embodiments of this application can be implemented in software or hardware. The names of the modules do not necessarily limit the functionality of the unit itself. The various embodiments in this specification are described in a progressive manner; similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments.

[0164] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for realizing vertical multi-level water resource management, characterized in that, A vertically multi-tiered water resource management system, comprising water resource data terminals respectively installed at each tier of the vertical multi-tiered system, a regional gateway electrically connected to the water resource data terminals, and a cloud platform electrically connected to the regional gateway; the water resource management method includes: Water resource data terminals at different levels in the vertical multi-level system report water usage data, which includes water usage plan data, water usage statistics data, and payment data. The regional gateway aggregates water usage data reported by various water resource data terminals, performs data preprocessing on the water usage data, and then forwards it to the cloud platform. The cloud platform performs correlation analysis on the water usage plan data, water usage statistics data, and payment data to obtain early warning and decision reports; The cloud platform sends the early warning and decision report to the corresponding water resource data terminals in the vertical multi-level system, so that the water resource data terminals can adjust the water use data for the next batch based on the early warning and decision report.

2. The method as described in claim 1, characterized in that, The steps for water resource data terminals at different levels in the vertical multi-level system to report water usage data include: The water resources data terminal corresponding to the highest level of the vertical multi-level system issues water use plan application templates to each of the lower-level water resources data terminals respectively. Each lower-level water resources data terminal fills in the water use plan application template, obtains water use plan data, and reports the water use plan data to the cloud platform; The water resource data terminal at a specific level in the vertical multi-level system aggregates the water metering data collected by each subordinate end-use water device, and submits the aggregated water metering data to the upper-level water resource data terminal to obtain the water usage statistics data. The user terminals of the end users in the vertical multi-level system upload real-time report data and payment requests to the cloud platform to obtain the payment data.

3. The method as described in claim 1, characterized in that, The steps of the regional gateway aggregating water usage data reported by various water resource data terminals, preprocessing the water usage data, and forwarding it to the cloud platform include: The regional gateway uses an MQTT / REST dual-protocol gateway and a local caching mechanism to perform format verification, local caching, and message aggregation processing on the water usage data reported by each water resource data terminal. The regional gateway uses the HTTPS / OAuth protocol to forward the processed water usage data to the cloud platform in batches.

4. The method as described in claim 1, characterized in that, The cloud platform performs correlation analysis on the water usage plan data, water usage statistics data, and payment data to obtain early warning and decision reports, including the following steps: The cloud platform uses the Spring Cloud microservice framework to obtain and track the water usage plan data, water usage statistics data, and payment data. The cloud platform uses Spark SQL and a unified data model to perform ETL operations on the water usage plan data, water usage statistics data, and payment data to generate the early warning and decision reports. The cloud platform uses the GIS visualization method to display the early warning and decision reports.

5. The method as described in claim 4, characterized in that, The cloud platform performs correlation analysis on the water usage plan data, water usage statistics data, and payment data to obtain early warning and decision reports, including the following steps: The cloud platform inputs the water usage plan data, water usage statistics data, and payment data into the built-in distributed deep learning model; The cloud platform uses the distributed deep learning model to perform correlation learning on the water usage plan data, water usage statistics data and payment data, and predicts the early warning feature information corresponding to each water usage data. The cloud platform uses a dynamic knowledge graph to match the early warning feature information to obtain a decision-making scheme. The cloud platform combines the early warning feature information and the decision-making scheme to generate the early warning and decision report.

6. The method as described in claim 1, characterized in that, The step of the cloud platform distributing the early warning and decision report to the corresponding water resource data terminals in the vertical multi-level system includes: The cloud platform uses unified key management and TLS encryption services to encrypt the early warning and decision reports; The cloud platform will send the encrypted early warning and decision reports to the water resources data terminal; The cloud platform uses a multi-level log tracing mechanism provided by the Spring Cloud microservice framework to track the transmission process of the early warning and decision reports.

7. The method as described in claim 1, characterized in that, After the cloud platform distributes the early warning and decision report to the corresponding water resource data terminals in the vertical multi-level system, the method further includes: The cloud platform triggers a full ETL operation on the water usage data at fixed times through a pipeline mechanism, and processes the water usage data through Spark SQL tasks scheduled by the data middle platform to generate reports and push them out. The cloud platform controls the regional gateway to perform aggregation operations on the water usage data at fixed intervals. The end-user firmware in the vertical multi-level system performs meter reading operations at fixed intervals to obtain and upload report data.

8. A vertically integrated, multi-level water resource management system, characterized in that, The water resources management system includes: A water resource data terminal is respectively installed at each level of the vertical multi-level system; a regional gateway electrically connected to the water resource data terminal; and a cloud platform electrically connected to the regional gateway; wherein... Water resource data terminals at different levels in a vertical multi-level system are used to report water use data, which includes water use planning data, water use statistics data, and payment data. The regional gateway is used to aggregate water usage data reported by various water resource data terminals, and to forward the water usage data to the cloud platform after data preprocessing. The cloud platform is used to perform correlation analysis on the water usage plan data, water usage statistics data and payment data to obtain early warning and decision reports. The cloud platform is also used to distribute the early warning and decision reports to the corresponding water resource data terminals in the vertical multi-level system, so that the water resource data terminals can adjust the water usage data for the next batch based on the early warning and decision reports.

9. The water resource management system as described in claim 8, characterized in that, The water resources data terminal corresponding to the highest level of the vertical multi-level system is used to send water use plan application templates to each of the lower-level water resources data terminals respectively. Each of the lower-level water resources data terminals is used to fill in the water use plan application template, obtain water use plan data, and report the water use plan data to the cloud platform. The water resource data terminal at a specific level in the vertical multi-level system is used to aggregate water metering data collected by each subordinate end-use water device, and submit the aggregated water metering data to the superior water resource data terminal to obtain the water usage statistics. The user terminals of the end users in the vertical multi-level system are used to upload real-time report data and payment requests to the cloud platform to obtain the payment data.

10. The water resource management system as described in claim 8, characterized in that, The cloud platform is specifically used to obtain and track the water usage plan data, water usage statistics data, and payment data using the Spring Cloud microservice framework. The cloud platform is specifically used to perform ETL operations on the water usage plan data, water usage statistics data, and payment data using Spark SQL and a unified data model, and to generate the early warning and decision reports. The cloud platform is specifically used to display the early warning and decision reports using the GIS visualization method.

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