Metering device management method, computer device, storage medium and program product

Abstract

The application discloses a metering equipment management method, computer equipment, a storage medium and a program product, relates to the technical field of equipment management, and comprises the following steps: determining target user field information corresponding to user login information in a geographic information model; determining target area field information and target role field information in the geographic information model according to the target user field information, determining target area and user area permissions respectively according to the field information, and managing to-be-managed equipment in the target area according to the user area permissions. The problems that the area management mode of metering equipment is too broad, user permissions are confused, and metering equipment is difficult to be managed across areas can be solved. The method refines the area management mode, binds user roles and areas, grants user area permissions, and facilitates users with permissions to manage metering equipment across areas. The user is accurately authorized based on the role and the area, overreach operation is effectively prevented, and data security is fundamentally guaranteed.

Description

Technical Field

[0001] This invention relates to the field of equipment management technology, specifically to a method for managing metering equipment, computer equipment, storage media, and program products. Background Technology

[0002] Measuring equipment mainly includes specialized instruments in fields such as geometry, temperature, mechanics, and electricity. Measuring equipment is common in factories and workshops, numerous, and widely installed. In traditional metering equipment management, the regional management model is too broad, simply classifying metering equipment by department or type, resulting in chaotic user permissions and complicating cross-regional scheduling and status monitoring of metering equipment.

[0003] Therefore, the relevant technologies suffer from problems such as overly broad regional management models for metering equipment, chaotic user permissions, and difficulty in managing metering equipment across regions. Summary of the Invention

[0004] In view of this, the present invention provides a method for managing metering equipment, a computer device, a storage medium, and a program product to solve the problems of overly broad regional management modes for metering equipment, chaotic user permissions, and difficulty in cross-regional management of metering equipment.

[0005] In a first aspect, this application provides a method for managing metering equipment, the method comprising:

[0006] In the geographic information model, the target user field information corresponding to the user login information is determined, and the region character and role character are obtained from the target user field information. The geographic information model is generated based on the user field information, role field information and region field information.

[0007] Based on the region character, determine the target region field information in the geographic information model, and based on the role character, determine the target role field information in the geographic information model.

[0008] Based on the node characters and hierarchy characters in the target area field information, the target area is determined in the preset area hierarchy of the geographic information model, and the user's area permissions are determined based on the permission characters in the target role field information.

[0009] Manage the devices to be managed in the target area based on the user's area permissions.

[0010] Secondly, this application provides a metering equipment management device, which includes:

[0011] The character acquisition module is used to determine the target user field information corresponding to the user login information in the geographic information model, and to obtain the region character and role character in the target user field information. The geographic information model is generated based on the user field information, role field information and region field information.

[0012] The information determination module is used to determine the target region field information in the geographic information model based on the region character, and to determine the target role field information in the geographic information model based on the role character.

[0013] The permission determination module is used to determine the target area in the preset area hierarchy of the geographic information model based on the node characters and hierarchy characters in the target area field information, and to determine the user's area permissions based on the permission characters in the target role field information.

[0014] The device management module is used to manage devices in a target area based on user area permissions.

[0015] Thirdly, this application provides a computer device, including: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the metering device management method of the first aspect or any corresponding embodiment described above.

[0016] Fourthly, this application provides a computer-readable storage medium storing computer instructions for causing a computer to execute the metering device management method of the first aspect or any corresponding embodiment described above.

[0017] Fifthly, this application provides a computer program product, including computer instructions for causing a computer to execute the metering equipment management method described in the first aspect or any corresponding embodiment.

[0018] This application addresses the problems of overly broad regional management models for metering devices, chaotic user permissions, and difficulties in cross-regional management by using this method. The method involves determining the target user field information corresponding to the user login information within the geographic information model; determining the target region field information and the target role field information based on the target user field information; determining the user's region permissions based on the target role field information; and managing the devices to be managed within the target region based on the user's region permissions. This method implements multi-level regional management, refines the regional management model, and, by binding users to roles and regions, grants users corresponding user region permissions, facilitating cross-regional management of metering devices by authorized users. Precise authorization based on roles and regions effectively prevents unauthorized operations and fundamentally ensures data security. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this application, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0020] Figure 1 This is a flowchart illustrating a metering equipment management method according to an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of a geographic information model according to an embodiment of this application;

[0022] Figure 3 This is a flowchart illustrating the uploading of a measurement report according to an embodiment of this application;

[0023] Figure 4 This is a flowchart illustrating the early warning process based on device status scoring according to an embodiment of this application;

[0024] Figure 5 This is a flowchart of a computing device status scoring method according to an embodiment of this application;

[0025] Figure 6 This is a flowchart illustrating the verification of measurement report data according to an embodiment of this application;

[0026] Figure 7 This is a flowchart of another method for uploading a measurement report according to an embodiment of this application;

[0027] Figure 8 This is a structural block diagram of a metering equipment management device according to an embodiment of this application;

[0028] Figure 9 This is a schematic diagram of the hardware structure of a computer device according to an embodiment of this application. Detailed Implementation

[0029] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0030] Traditional metering equipment management methods suffer from several problems, including: overly broad regional management models that simply categorize equipment by department or type, lacking a refined management system based on geographical hierarchy, which complicates cross-regional equipment scheduling and status monitoring; reliance on manual maintenance of ledgers for metering cycle management, which is prone to omissions or errors, making it difficult to achieve dynamic tracking of the entire equipment lifecycle; manual data entry, lacking standardized verification mechanisms during batch imports, compromising data accuracy; and a lack of systematic support for report management, with paper documents easily lost and difficult to archive, and electronic documents not linked to the actual operating status of the equipment in real time, resulting in inefficient historical data tracing and analysis. These problems limit the intelligent and refined development of equipment management, making it difficult to meet the requirements of precise control over the entire equipment lifecycle in the era of the Industrial Internet of Things.

[0031] Based on the above, this application provides a method for managing metering equipment. It integrates geographic information modeling and access control, supports dynamic regional division and the creation of a three-level geographic information model, enabling refined management of equipment. Combined with a role-based access control model, it implements data isolation to ensure the security of cross-regional data access. Automated task scheduling and intelligent early warning are implemented, dynamically generating task lists based on the metering cycle and automatically pushing them to relevant personnel. A multi-dimensional evaluation model is used to achieve tiered early warning. Data standardization and blockchain notarization are achieved by using an Excel spreadsheet component to batch import metering files and automatically verifying the accuracy of the spreadsheet data; regular expressions are used to validate the data format to ensure data standardization. Decentralized storage is used for critical operations to ensure data immutability. This method achieves refined management and control by constructing a geographic information model, designing an intelligent task scheduling mechanism, employing blockchain notarization technology, and using a multi-dimensional risk assessment model. It solves the four core problems in traditional metering equipment management: extensive regional division, inefficient cycle management, chaotic data entry, and difficulty in operation traceability.

[0032] According to an embodiment of this application, a metering device management embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, for example, a computer, a server, etc., and although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0033] This embodiment provides a method for managing metering equipment. Figure 1 This is a flowchart of a metering equipment management method according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0034] Step S101: Determine the target user field information corresponding to the user login information in the geographic information model, and obtain the region character and role character from the target user field information. The geographic information model is generated based on the user field information, role field information and region field information.

[0035] Specifically, the metering equipment management method is implemented through a regional metering management and uploading system, which includes an intelligent metering management platform. This embodiment divides the region into three levels: region, factory, and workshop. Furthermore, this embodiment employs a Role-Based Access Control (RBAC) model for permission management. Region field information is generated for each region based on its level, such as the region's level, parent region, and region identifier. Multiple roles are generated according to the access control model, and role field information is generated for each role, such as the permission characters included in each role. User field information is generated for each user, such as user identifier, the user's bound role, and the user's bound region. A geographic information model is generated based on the user field information, role field information, and region field information. If the region is divided into three levels (region, factory, workshop), the geographic information model is a three-level model; if it is divided into four levels (first-level region, second-level region, factory, workshop), the geographic information model is a four-level model. The geographic information model enables refined management of equipment, and the RBAC model ensures data isolation and secure cross-regional data access. Implement geographic information modeling and access control isolation.

[0036] The equipment metering regional management and upload system includes an intelligent metering management platform. This platform consists of multiple modules, including a regional management module. This module contains the aforementioned geographic information model, employing a tree structure to flexibly store multiple regional nodes and assigning corresponding regional permissions to different users within the system. Users can only see the regions and devices within their authorized scope, thus achieving data isolation.

[0037] Geographic information models, for example: Figure 2 As shown, the geographic information model is generated based on user field information, role field information, and region field information. Based on the user login information, the corresponding target user field information is retrieved from all user field information included in the geographic information model. From the target user field information, region characters and role characters are obtained. Region characters are used to record the region bound to the user, and role characters are used to record the role bound to the user.

[0038] Step S102: Determine the target region field information in the geographic information model based on the region character, and determine the target role field information in the geographic information model based on the role character.

[0039] Specifically, the region bound to the user is determined based on the region character, and the target region field information corresponding to the region bound to the user is determined in the geographic information model. For example, the region field information records the region identifier character, and the target region field information is determined by matching the region identifier. Similarly, the role bound to the user is determined based on the role character, and the target role field information corresponding to the role bound to the user is determined in the geographic information model. For example, the role field information records the role identifier character, and the target role field information is determined by matching the role identifier.

[0040] Step S103: Determine the target region in the preset region hierarchy of the geographic information model based on the node characters and hierarchy characters in the target region field information, and determine the user's region permissions based on the permission characters in the target role field information.

[0041] Specifically, the node characters in the region field information are used to record the parent or child nodes of the corresponding region. A parent node represents the region's parent region, and a child node represents its child region. The hierarchy characters in the region field information are used to record the region's hierarchy, such as: region, factory, workshop. Preset region hierarchies in the geographic information model include: region, factory, workshop, equipment, etc. Based on the node characters in the target region field information, the parent or child nodes of the target region are determined, and based on the hierarchy characters, the region hierarchy of the target region is determined, thus identifying the target region. The permission characters in the role field information are used to record the permissions possessed by the corresponding role. Based on the permission characters in the target role field information, the permissions used for the bound region, i.e., the user's region permissions, are determined.

[0042] This embodiment employs a region-based role-based access control mechanism, combined with an operation log traceability module, to ensure transparent supervision of the entire operation process. Regarding region-based role-based access control, the system precisely allocates corresponding access permissions based on different business regions and functional roles. Through detailed business scenario segmentation, the system determines the functional boundaries of each region and, in conjunction with the user's role attributes, grants them operational permissions within specific regions.

[0043] Step S104: Manage the devices to be managed in the target area according to the user's area permissions.

[0044] Specifically, users manage devices within a target area based on their user area permissions. For example, user area permissions include viewing and data entry permissions, allowing users to view the status of devices or enter their data into the system; user area permissions include data query, review, and modification permissions, allowing users to query data corresponding to devices, review the data, and modify the data based on the review results; user area permissions include permission assignment permissions, allowing users to assign permissions corresponding to devices to other users, etc.

[0045] The metering equipment management method provided in this embodiment determines the target user field information corresponding to the user login information in the geographic information model; determines the target area field information and target role field information in the geographic information model based on the target user field information; determines the target area based on the target area field information; determines the user's area permissions based on the target role field information; and manages the devices to be managed in the target area according to the user's area permissions. This method provides multi-level management of areas, refines the area management mode, and, by binding users to roles and areas, grants users corresponding user area permissions, facilitating cross-area management of metering equipment by authorized users. Precise authorization of users based on roles and areas effectively prevents unauthorized operations and fundamentally ensures data security. It solves the problems of overly broad area management modes for metering equipment, chaotic user permissions, and difficulty in cross-area management of metering equipment.

[0046] As an optional embodiment, before determining the target user field information corresponding to the user login information in the geographic information model, the method further includes:

[0047] Obtain the regions under the first preset number of regional levels, and determine the region identifier and associated regions of the regions according to the regional levels;

[0048] Generate the corresponding region field information based on the region level, region identifier, and associated regions;

[0049] Generate a second preset number of regional management roles and obtain the management permissions corresponding to the regional management roles;

[0050] Generate role field information based on the region management role and management permissions;

[0051] Obtain user information and determine the corresponding regional management role and region;

[0052] Generate user field information based on user information, region management role, and region;

[0053] A geographic information model is generated based on user field information, role field information, and region field information.

[0054] Specifically, in combination Figure 2 This embodiment will be described below. The first preset quantity represents multiple regions, such as: region, factory, workshop, equipment, etc. Specific region levels can be manually divided based on the actual location of the equipment. Regions under the first preset quantity of region levels are obtained, for example: region 1 and region 2 under the region level, factory 1 and factory 2 under the factory level, workshop 1 and workshop 2 under the workshop level, etc. Based on the region level, the region identifier and associated regions are determined. Associated regions include upper-level regions or lower-level regions. For example: the region identifier for region 1 is region 1, and the lower-level region of region 1 includes factory 2; the region identifier for factory 1 is factory 1, and the lower-level region of factory 1 includes workshop 1, and the upper-level region of factory 1 includes region 2.

[0055] Generate region-level characters based on the region hierarchy, determine the region identifier characters, and generate node characters based on the aforementioned associated regions. Integrate the region identifier characters, region-level characters, and node characters to generate the region field information corresponding to the region.

[0056] Generate a second preset number of area management roles, such as: ordinary employees, managers, etc. Obtain the management permissions corresponding to each area management role. For example, ordinary employees have viewing and data entry permissions, and can view the status of the devices to be managed or enter the data of the devices to be managed into the system; managers have data query, review, and modification permissions, and can query the data corresponding to the devices to be managed, review the data, and modify the data according to the review results.

[0057] The system retrieves user information and determines the corresponding regional management role and region. Different users are assigned different regional management roles and bound regions to define user permissions and achieve data isolation. For example, assigning factory permissions allows a user to see all equipment within that factory, while equipment in other factories remains hidden. Assigning workshop permissions restricts a user to seeing only equipment within that workshop, and equipment in other regions is also disabled. Multiple region selection is supported. User information includes, for example, username and user account ID.

[0058] Generate user identifier characters based on user information, such as User 1, abcdef, etc.; generate role characters based on region management roles, such as Role 1, Role 2, etc.; and generate region characters based on region. Integrate user identifier characters, role characters, and region characters to generate user field information.

[0059] Integrating the aforementioned user field information, role field information, and region field information to generate a geographic information model, such as... Figure 2 As shown.

[0060] In this embodiment, a geographic information model is generated based on user field information, role field information, and region field information. The geographic information model is used to achieve geographic information modeling and permission isolation, enabling refined management of devices. Combined with a role-based access control model, data isolation is implemented to ensure the security of cross-regional data access.

[0061] As an optional embodiment, managing the devices to be managed in the target area according to user area permissions includes:

[0062] Obtain the metering report and upload time of the metering report for the equipment to be managed;

[0063] The metering report is verified according to preset rules. If the metering report passes the verification, the equipment data of the equipment to be managed is obtained from the metering report.

[0064] The task list is determined based on the measurement report and upload time, and push notifications are generated based on the task list.

[0065] Specifically, the system retrieves metering reports uploaded by users for the equipment to be managed. These reports may include equipment details, equipment BOM (Bill of Materials), equipment technical documents, and other information. The system also determines the upload time of the metering reports.

[0066] Preset rules include, for example, precisely validating the type, length, and value range of each field in the metering report. For instance, for date fields, the system checks if their format is correct; for numeric fields, it verifies if they are within a reasonable range. The metering report is validated according to these preset rules. If the validation passes, the data in the metering report is parsed and read to obtain the equipment data for the devices to be managed.

[0067] The system determines a task list based on metering reports and upload times, and generates push notifications accordingly. For example, it dynamically generates a task list based on upload time and metering cycle and automatically pushes it to relevant personnel. A multi-dimensional evaluation model is used to implement tiered early warnings: a yellow warning is triggered if the remaining deadline is less than or equal to 30 days, and a red warning is triggered if the remaining deadline is 0 days, resulting in equipment shutdown. This achieves automated task scheduling and intelligent early warning. Furthermore, since metering devices have different metering cycles, the current metering time and cycle must be entered when initializing or adding metering devices. The system automatically calculates and stores the deadline for the next metering based on the metering cycle, sending an email reminder one month before the next deadline. It also supports changing the color status of devices whose deadlines are approaching orange in the device list, reminding engineers to complete metering work on time. When an engineer uploads a device's metering report, the system automatically updates the next deadline based on the current metering time and the device's metering cycle. The device ledger list in the metering management module clearly shows the metering time and the number of metering report uploads for different devices, and supports quick report filtering and statistics.

[0068] In addition, the aforementioned intelligent metering management platform also includes an equipment management module and a metering management module. The equipment management module employs a multi-table relational structure, recording detailed information about the equipment, such as initial information, equipment code, and equipment location. This information needs to be entered into the system by equipment engineers. If the equipment has a built-in intelligent module, its status can be automatically obtained via the network; otherwise, the status can be updated based on employee-reported anomalies. The metering management module focuses on metering equipment, summarizing information from all metering devices. Some metering devices are independent, while others are associated with production equipment, essentially forming subsets. Metering equipment data is extracted separately for the purpose of independently summarizing metering work reminders, facilitating data retrieval for users. The list displays different data focuses, allowing users to customize additional data, such as periodic metering reports, calibration dates, and the next calibration deadline. It also supports batch addition and import of metering devices into the equipment management module via Excel spreadsheets. Some metering devices support IoT technology and can periodically feed back equipment data to the system via TCP (Transmission Control Protocol). The metering management module is a subset of the equipment module, differing only in its specific content. The page list displays content with a different focus; the former emphasizes recording historical data for the metering equipment and promptly reminding engineers to complete metering tasks. The latter focuses on displaying equipment status, summarizing alarm information, maintaining equipment technical documents, and providing inspection and maintenance information. The "Batch Add" function in the table indicates adding metering equipment in batches, meaning entering metering equipment data into the system in bulk. A separate button for metering equipment is available; clicking it displays a pop-up window where users can upload the current metering report and add notes. The system automatically calculates the deadline for the next report based on the metering time and cycle, providing reminders as the deadline approaches.

[0069] The above process is as follows Figure 3 As shown, the user logs into the app and sends their login information to the system. The system verifies the user's regional permissions based on the login information; loads the device list; the user submits a metering report; the report format is verified; the next metering date is updated; and the system sends a confirmation email to the user. Loading the device list and submitting the device report are primarily intended to achieve data isolation, meaning each user only sees and fully accesses content within their authorized scope. Because the responsible person for each region is different, it is necessary to enable the corresponding region's manager to oversee the metering devices within their region.

[0070] In this embodiment, Excel is used to import measurement reports in batches, while automatically verifying the accuracy of the table data; regular expressions are used to validate the data format to ensure the data is standardized.

[0071] As an optional embodiment, the equipment data of the equipment to be managed is obtained based on the metering report, including:

[0072] Obtain equipment data for the managed equipment from the metering report;

[0073] Obtain the operation information corresponding to the measurement report;

[0074] Using a preset synchronization mechanism, device data and operation information are synchronized to a third preset number of storage nodes.

[0075] Specifically, the metering report retrieves equipment data for the managed equipment, such as equipment details, equipment bill of materials, and equipment technical documents. It also retrieves corresponding operational information from the metering report, such as the operation time, operator, and imported data.

[0076] This embodiment utilizes blockchain evidence storage technology to design a preset synchronization mechanism. Blockchain evidence storage technology provides a solid traceability guarantee for operation records. Each data import operation is recorded on the blockchain, forming an immutable record. Whether it is for data review, auditing, or subsequent problem investigation, accurate information can be obtained by querying the records on the blockchain, ensuring the transparency and traceability of data operations.

[0077] The third preset quantity represents multiple storage nodes, such as the initiator, reviewer, storage provider, and query provider. The preset synchronization mechanism, for example, is based on a "transaction broadcast - consensus verification - block synchronization" process to ensure complete consistency of ledgers across all nodes, and any modifications require network-wide consensus, ultimately achieving "full traceability and non-repudiation" of data import records. Utilizing this preset synchronization mechanism, device data and operational information are synchronized to various storage nodes, enabling multi-party supervision and preventing a single node from monopolizing data recording rights.

[0078] In this embodiment, a decentralized storage method is used to store device data and operational information to ensure the immutability of the data. Whether for data review, auditing, or subsequent problem investigation, accurate information can be obtained by querying records on the blockchain, ensuring the transparency and traceability of data operations.

[0079] As an optional embodiment, a preset synchronization mechanism is used to synchronize device data and operation information to a third preset number of storage nodes, including:

[0080] Store device data and operational information to the target storage node;

[0081] If the block height of the target storage node is greater than the block height of other storage nodes, generate a synchronization request containing device data and operation information.

[0082] The synchronization request is sent to other storage nodes. These other storage nodes are used to filter the data in the synchronization request according to the defined storage rules, and only store the data that meets the storage rules. The storage rules are generated when the storage node is created. Other storage nodes are also used to store the storage rules of their own storage node and the storage rules of the target storage node.

[0083] Specifically, a third preset number of storage nodes are selected, such as the initiator, reviewer, storage provider, and queryer. One of these storage nodes is chosen as the target storage node, for example, the storage provider. The aforementioned device data and operation information are then stored on the target storage node.

[0084] Block height is an incrementing integer representing the number of "blocks" stored on that node. Analogously, like page numbers in a book, the higher the page number, the newer and more complete the content. In blockchain, block height equals the total number of blocks on the chain. In distributed storage, it can also refer to "data version" or "log sequence number."

[0085] If the block height of the target storage node is less than the block height of other storage nodes, it means that the data on the target storage node is lagging behind. It has a newer data version than other nodes and needs to synchronize data with other storage nodes, generating a synchronization request containing device data and operation information.

[0086] Synchronization requests are sent to other storage nodes. Data in these requests is filtered according to defined storage rules, storing only data that conforms to those rules. Through a user interface, the blockchain administrator can configure corresponding storage rules for this blockchain node using the storage rule definition module 11. A storage rule can be a piece of code that expresses complex meanings. The input is the blockchain's transaction content, and the output is True or False, indicating whether the data conforms to the storage rule.

[0087] Storage rules are as follows:

[0088] bool filter(transaction): / / Validates the input data to determine whether it meets the storage rules.

[0089] wrid = transaction.wrid; / / Get the warehouse receipt identifier in the synchronization request.

[0090] type = transaction.type; / / Get warehouse receipt operations in the synchronization request.

[0091] if(type==PLEDGE&&node==ICBC): / / If the most recent operation before this warehouse receipt identifier was a pledge to this storage node.

[0092] return True; / / Output True, indicating that the data conforms to the storage rules.

[0093] else: / / Other cases.

[0094] return False; / / Output False, indicating that the data does not conform to the storage rules.

[0095] As an optional embodiment, after obtaining the equipment data of the equipment to be managed based on the metering report, the method further includes:

[0096] Retrieve a fourth preset number of device status data from the device data;

[0097] Based on the equipment status data, determine the equipment status score of the metering equipment, which includes equipment to be managed;

[0098] Based on the equipment status score and equipment status data, determine the equipment control strategy;

[0099] The first push notification is generated based on the score range corresponding to the device status rating and the device control strategy.

[0100] Specifically, a fourth preset number of device status data points are obtained from the device data. This fourth preset number represents multiple data points, and examples of these data points include: cumulative device operating time, mode operating time, device fault type, fault frequency, and the temperature, humidity, pressure, and vibration of the metering device. Furthermore, this embodiment deploys various environmental sensors around the metering device, including temperature sensors, humidity sensors, pressure sensors, and vibration sensors, to monitor the device's environmental temperature, humidity, pressure, vibration, and other device status data in real time. This device status data is crucial for assessing the device's operating condition and potential risks, as adverse environmental conditions can accelerate device aging and damage.

[0101] The aforementioned equipment status data is input into a multidimensional assessment model, which outputs an equipment status score for the metering equipment. The multidimensional assessment model decomposes the equipment data into three core dimensions (usage intensity, failure risk, and environmental adaptability). Each dimension contains specific quantifiable indicators and is labeled with a weighted percentage (W1 / W2 / W3 can be dynamically configured according to equipment characteristics). A total score is obtained through weighted summation, and the warning level is determined based on the score range. Finally, warning information and recommendations are output. The equipment status score calculation is the process of transforming equipment data into a quantifiable risk value; essentially, it is a multidimensional data weighting / rule mapping.

[0102] Based on equipment status scores and data, the system determines equipment control strategies. For example, if an equipment status score of 59 indicates a high-risk condition, the control strategy would be to replace it with another metering device that has the same status data. Additionally, the system measures the time of failure, type of failure, location of failure, environmental parameters at the time of failure, the handling process and results, and the equipment status before the failure. Failure modes refer to the recurring failure characteristics exhibited by equipment during long-term operation, summarizing "how and why failures occur." Historical failure data forms a "case library," and comparative analysis is a process of "inductive reasoning." By identifying patterns through numerous cases, the system ultimately upgrades from "passively responding to failures" to "actively predicting and controlling failures."

[0103] Based on the score range corresponding to the equipment status score and the equipment control strategy, the first push notification is generated. For example, if the equipment status score is 81, which is in the 80-100 range, the metering equipment is in a low-risk state, triggering a yellow alert and generating the first push notification. Additionally, the equipment status score can be compared with the corresponding threshold to determine the metering equipment failure risk. The threshold is determined by using statistical methods, correlating the risk and failure of historical failure data to find the critical value at which an increase in risk score leads to a failure.

[0104] The equipment metering regional management and uploading system also includes an intelligent early warning subsystem. By integrating an assessment model based on equipment usage time, fault frequency, and environmental parameters, it achieves risk-level early warning and precise management of equipment status. This system integrates with the equipment's control system, tracking equipment start-up and shutdown times and cumulative runtime in real time. For equipment with complex operating modes, the system also records the runtime in each mode in detail, providing accurate data support for subsequent assessments. Utilizing the equipment's built-in fault diagnosis module and sensors installed in key locations, the system can monitor equipment fault conditions in real time. Once a fault is detected, the system automatically records the time, type, and specific location of the fault and performs statistical analysis on the fault frequency. Using a multi-dimensional assessment model, based on parameters such as equipment start-up time and their weights, it automatically determines the early warning level. Furthermore, the system compares fault information with the equipment's historical fault data to gain a more comprehensive understanding of the equipment's fault modes.

[0105] The above process is as follows Figure 4 As shown, the device collects data; calculates risk scores; determines whether the risk score exceeds the threshold. If it does, a red warning is issued; otherwise, a yellow warning is issued.

[0106] In this embodiment, an equipment status score is determined based on equipment status data. When an anomaly is identified in the metering equipment based on the equipment status score, a first push notification is generated promptly according to the score range corresponding to the equipment status score and the equipment control strategy. This ensures the normal operation of the metering equipment and avoids business disruptions due to metering equipment failure.

[0107] As an optional embodiment, determining the equipment status score of the metering equipment based on equipment status data includes:

[0108] Obtain equipment operation data, fault information data, and environmental parameter data from the equipment status data;

[0109] Preprocess the equipment operation data, fault information data, and environmental parameter data to obtain the fifth preset number of initial indicator data and the indicator type of the initial indicator data;

[0110] If the indicator type is type 1, the initial indicator data will be used as the indicator data; if the indicator type is type 2, the difference between the preset parameter and the initial indicator data will be used as the indicator data.

[0111] Based on the preset indicator weights and indicator data, a sixth preset number of indicator scores are generated;

[0112] The equipment status score is obtained based on the indicator scores and score weights.

[0113] Specifically, this embodiment mainly targets smart devices. The system stores relevant data about the device, such as usage time and number of failures. Then, engineers configure corresponding weights and other parameters for the device. The system performs a calculation based on these parameters and historical data to obtain the final result.

[0114] Combination Figure 5 This embodiment will be described in detail. Equipment operation data, fault information data, and environmental parameter data are obtained from the equipment status data. Equipment operation data includes, for example, cumulative duration and mode operation duration; fault information data includes, for example, fault type and fault frequency; and environmental parameter data includes, for example, temperature, humidity, pressure, and vibration.

[0115] Preprocessing involves initial processing of the collected data, including standardization and outlier filtering. Preprocessing of equipment operation data, fault information data, and environmental parameter data yields a fifth preset number of initial indicator data points and their indicator types, such as positive and negative indicators. Examples of the initial indicator data are shown in Table 1. Figure 5As shown, the equipment operation data, fault information data, and environmental parameter data were cleaned and standardized to obtain six indicators: indicator 1, cumulative runtime exceeding rate; indicator 2, high load mode operation ratio; indicator 3, number of faults per unit time; indicator 4, recurrence probability of similar faults; indicator 5, deviation of key environmental parameters; and indicator 6, duration of abnormal environment.

[0116] Table 1. Indicator Data, Preset Indicator Weights, and Scoring Weights

[0117]

[0118] The first type is a positive indicator, and the second type is a negative indicator. If the indicator type is the first type, the initial indicator data is used as the indicator data. For example, the initial indicator data for the first type includes the cumulative runtime percentage and the percentage of operation in high-load mode; these initial indicator data are directly used as the indicator data. For example, if the cumulative runtime percentage is 0.85 and the high-load mode operation percentage is 0.3, the corresponding indicator data is 0.3. If the indicator type is Type II, the difference between the preset parameter and the initial indicator data is used as the indicator data. For example, if the preset parameter is 1, the initial indicator data for Type II includes the number of failures per unit time, the probability of recurrence of similar failures, the deviation of key environmental parameters, and the duration of abnormal environments. The indicator data is 1 minus the above initial indicator data. For example, if the probability of recurrence of similar failures, the number of failures per unit time, the deviation of key environmental parameters, and the duration of abnormal environments are all Type II, the probability of recurrence of similar failures is 0.15, and the corresponding indicator data is 1-0.15=0.85; the number of failures per unit time is 0.2, and the corresponding indicator data is 1-0.2=0.8; the deviation of key environmental parameters is 0.25, and the corresponding indicator data is 0.75; the duration of abnormal environments is 0.1, and the corresponding indicator data is 0.9.

[0119] Based on preset indicator weights and indicator data, a sixth preset number of indicator scores are generated. For example, the indicator score obtained from the equipment usage intensity assessment is equal to (0.85 × W). 11 ) + (0.3 × W 12 The score obtained from the fault risk assessment is 0.8 × W = 0.52. 21 ) + (0.85 × W 22 The environmental adaptability assessment score is 0.75 × W = 0.825. 31 ) + (0.9 × W 32 =0.855. The above process is as follows: Figure 5As shown, the indicator score for dimension 1, equipment usage intensity assessment, is calculated using indicator 1, cumulative runtime exceeding rate, and indicator 2, high load mode operation ratio. The indicator score for dimension 2, fault risk assessment, is calculated using indicator 3, number of faults per unit time, and indicator 4, recurrence probability of similar faults. The indicator score for dimension 3, environmental adaptability assessment, is calculated using indicator 5, deviation of key environmental parameters, and indicator 6, duration of abnormal environment.

[0120] Based on the indicator scores and their weights, the equipment status score is obtained. For example, the equipment status score equals ∑(indicator score × weight) = (0.52 × W1) + (0.825 × W2) + (0.855 × W3) = 0.712. The above process is as follows... Figure 5 As shown, the weighted sum of all indicator scores is calculated as the equipment status score.

[0121] In addition, such as Figure 5 As shown, the method also includes: determining the warning level based on the equipment status score and outputting the result.

[0122] As an optional embodiment, determining the area corresponding to the user information includes:

[0123] Obtain a region map containing the areas to be managed, and identify the areas to be managed within the region map;

[0124] Based on the number of metering devices and the amount of metering data in the area to be managed, a feature vector of the area to be managed is generated.

[0125] Determine the distance between the areas to be managed based on the feature vectors;

[0126] Determine whether there are two managed areas whose distance is greater than or equal to a distance threshold;

[0127] If the distance between two regions to be managed is greater than or equal to the distance threshold, the two regions to be managed will be merged into a new region to be managed.

[0128] If there is no distance between two regions to be managed that is greater than or equal to the distance threshold, determine the region corresponding to the user information within the regions to be managed, wherein the region corresponding to the user information is contained within the regions to be managed.

[0129] Specifically, obtain a region map containing all areas to be managed, identify the boundary lines of each area to be managed in the region map, and determine the areas to be managed based on the boundary lines.

[0130] Based on the number of metering devices and the amount of metering data in the area to be managed, a feature vector of the area to be managed is generated. The feature vector consists of the number of metering devices and the amount of metering data.

[0131] The feature vector is treated as an independent cluster. The distance between the regions to be managed is determined by calculating the distance between each pair of clusters. For example, the centroid distance or Euclidean distance between the clusters corresponding to adjacent regions to be managed is calculated, and the result is used as the distance between the regions to be managed.

[0132] The maximum service radius, or distance threshold, of the monitoring area is set by the expert group based on the management capabilities of the administrators.

[0133] If the distance between two regions to be managed is greater than or equal to the distance threshold, the two regions to be managed will be merged into a new region to be managed.

[0134] If there is no distance between two regions to be managed that is greater than or equal to the distance threshold, determine the region corresponding to the user information in the regions to be managed, and bind the region field information of the region to be managed with the user field information of the user.

[0135] In this embodiment, dynamic optimization and automated merging of areas to be managed are achieved, enhancing the system's adaptability and scalability, and providing a foundation for precise services. Within the areas to be managed, the regions corresponding to user information are determined, and user region management permissions are clearly defined.

[0136] As an optional embodiment, the measurement report is verified according to preset rules, including:

[0137] Obtain a template for the measurement report;

[0138] The file template is compared with the preset template. If the file template is inconsistent with the preset template, a prompt message is generated.

[0139] If the file template matches the preset template, retrieve the field information from the measurement report;

[0140] The field information is validated according to the preset field format.

[0141] Specifically, the system includes a data standardization module that integrates template recognition, field validation, and blockchain notarization technologies to ensure the standardization of batch data import and the traceability of operation records.

[0142] The data standardization module can accurately identify data templates of various formats. For example, the data standardization module judges whether the content of the template conforms to the standard template content. If it does not conform, it gives the corresponding error message. The preset template uses the Excel parsing module to convert the corresponding field data and store the corresponding data in the database through dictionaries and other methods.

[0143] The data standardization module compares the file template with the preset template. If the file template is inconsistent with the preset template, there may be some abnormal data. The system cannot automatically correct this abnormal data and needs to revert the operation, generate prompt information, and guide the user to modify the content and re-import. For example, the imported content contains abnormal system data, incorrect date data, or numerical data.

[0144] The data standardization module's field validation function performs rigorous checks on every field of the imported data. If the file template matches the preset template, it retrieves the field information from the measurement report and validates it according to the preset field format. For example, for date fields, the data standardization module checks if the format is correct; for numeric fields, it verifies if they are within a reasonable range. If any data is found to be non-compliant, the data standardization module clearly identifies the problem, allowing users to make timely corrections.

[0145] In this embodiment, the file template of the measurement report is checked first, and then the field information in the measurement report is checked. When the check fails, the problem is clearly pointed out so that the user can make timely corrections and ensure that the measurement report format is correct.

[0146] As an optional embodiment, the field information is validated according to a preset field format, including:

[0147] Get the regular expression corresponding to the preset field format;

[0148] Based on regular expressions, the data type and data length of the field information are validated to obtain the first validation result;

[0149] Based on regular expressions, determine whether the values ​​of field information are within a preset range to obtain the second verification result;

[0150] If an abnormal field is determined based on the first verification result, or if an abnormal field is determined based on the second verification result, a prompt message is generated based on the abnormal field.

[0151] If no abnormal field is identified based on the first verification result, and no abnormal field is identified based on the second verification result, the measurement report verification is deemed successful.

[0152] Specifically, precise validation of field type, length, value range, encoding format, etc., is achieved through regular expressions. Preset field formats include, for example, the field type, length, value range, and encoding format. The corresponding regular expression is generated based on the requirements for type, length, value range, encoding format, etc.

[0153] Based on regular expressions, the data type and data length of the field information are validated to obtain the first validation result. For example, the date field is checked for correct format and whether the data length meets the length requirement based on regular expressions.

[0154] Based on regular expressions, determine whether the numerical value of the field information is within a preset range to obtain a second verification result. For example, use regular expressions to verify whether the numerical field is within a reasonable range.

[0155] If an abnormal field is identified based on either the first or second validation result, the abnormal field is a field whose data does not conform to the rules. Once an abnormal field is found, a prompt message is generated to clearly indicate the problem, allowing the user to correct it promptly.

[0156] If no abnormal field is identified based on the first verification result, and no abnormal field is identified based on the second verification result, the measurement report verification is deemed successful.

[0157] The above process is as follows Figure 6 As shown, the process involves data import, template matching (if matching fails, a template prompt is displayed), field validation (if field validation fails, an error message is displayed), and blockchain storage is performed if field validation passes.

[0158] As an optional embodiment, a task list is determined based on the metering report and upload time, and push notifications are generated based on the task list, including:

[0159] Generate pending measurement tasks based on the measurement report;

[0160] Obtain the metering cycle for the metering task to be processed;

[0161] Determine the deadline for the metering tasks to be processed based on the upload time and metering period;

[0162] Generate a task list based on the metering tasks to be processed and the task deadlines;

[0163] Based on the difference between the current system time and the task deadline, a second push notification containing a task list is generated.

[0164] Specifically, because metering devices have different metering cycles, the current metering time and metering cycle of the metering device must be filled in when initializing or adding new metering devices. Based on the metering report, pending metering tasks are generated, such as: re-uploading the metering report, repairing the metering device, and testing the metering device.

[0165] Obtain the metering cycle of the metering tasks to be processed, such as: uploading a metering report every 30 days, testing the metering equipment every 3 months, etc.

[0166] Based on the upload time and the metering period, determine the deadline for the metering tasks to be processed. For example, if the upload time is X month Y day and the metering period is 1 month, then the deadline for the task is X+1 month Y day.

[0167] A task list is generated based on the pending metering tasks and their deadlines. A second push notification containing the task list is generated based on the difference between the current system time and the task deadline. For example, if the second push notification is an email, the deadline for the next metering cycle is automatically calculated and stored, and an email reminder is sent one month before the next due date. Simultaneously, the color status of devices whose deadlines are approaching in the device list changes to orange to remind engineers to complete their metering work on time. When an engineer uploads a device's metering report, the system automatically updates the next deadline based on the current metering time and the device's metering cycle.

[0168] In addition, the system includes an automated task scheduling module. A scheduled task engine triggers metering reminder tasks daily at 9:00 AM (configurable and modifiable), automating task allocation in conjunction with an email notification system. This module utilizes the Spring framework's TaskScheduler to trigger metering reminder tasks on a regular schedule. Through join queries, the module retrieves a list of all metered devices with deadlines within one month. It then groups the devices by their responsible personnel and summarizes the list of devices under their responsibility. Next, it iterates through the metering deadlines of the devices in the list, checking for devices with deadlines exactly one month after the current date, exactly 15 days from the current date, or devices whose metering expires on the current day or within the current month. If any such devices are found, the module summarizes the device list by deadline into emails indicating expired, due today, within 15 days, or within one month, and sends email reminders to the responsible personnel. Different metering deadlines are marked with different colors to promptly remind engineers to complete metering work and upload metering reports to the system.

[0169] The equipment ledger list in the metrology management module clearly displays the metrology time and the number of times metrology reports have been uploaded for different devices, and supports quick report filtering and statistics. The ledger list contains information from the metrology management module, mainly displaying: equipment ID, equipment name, equipment model, manufacturer, serial number, metrology cycle, calibration date, next calibration deadline, responsible person, number of reports, user unit, associated equipment, associated region, and other list data.

[0170] The above process is as follows Figure 7As shown, the process involves: establishing a record for the metering equipment; entering the current metering time and cycle; the system automatically calculating the next deadline; the equipment transmitting data via the IoT terminal and periodically running the "Equipment transmitting data via IoT terminal" function; determining if the deadline is approaching; if so, sending an email reminder and marking the record in orange; the engineer uploading the metering report; the system automatically updating the next deadline; and if the deadline is not approaching, re-executing the "Equipment transmitting data via IoT terminal" function.

[0171] In this embodiment, by automatically generating tasks, intelligently calculating deadlines, and dynamically pushing reminders, the automation level, execution efficiency, and time controllability of metering management are significantly improved, effectively preventing task omissions or overdue deadlines and ensuring the compliance and stable operation of the system.

[0172] As an optional embodiment, after obtaining the equipment data of the equipment to be managed based on the metering report, the method further includes:

[0173] Acquire data on the upload process of the measurement report, and generate an operation log based on the upload process data, the measurement report, user login information, and upload time;

[0174] If the managed device is abnormal, determine whether the user area permissions include the permissions corresponding to the operation log;

[0175] If the user area permissions include the permissions corresponding to the operation log, the abnormal information and responsible person information of the device to be managed can be determined based on the operation log.

[0176] Specifically, operation logs are generated based on uploaded data, metering reports, user login information, and upload time. These logs record every operation within the system in detail, including data queries, modifications, and system configuration changes, noting key information such as the time, operator, content, and result. These operation logs are securely stored for easy retrieval and auditing. Operation logs are also managed based on role and region permissions.

[0177] If a managed device exhibits abnormal behavior, first determine if the user has the necessary permissions for the operation logs, such as read, download, or modify permissions. Abnormal behavior on the managed device could include instances of unusual operations or data security incidents.

[0178] When user area permissions include permissions corresponding to operation logs, for example, if the user is an administrator, the administrator can quickly locate the time, location, and responsible person of the problem through the operation logs, determine the abnormal information of the device to be managed and the information of the responsible person, and achieve transparent supervision of the entire process.

[0179] In this embodiment, when abnormal operation or data security incident occurs, managers can use operation logs to quickly locate the time, location and responsible person of the problem, and achieve transparent supervision of the entire process.

[0180] As an optional embodiment, the above step "manage the devices to be managed in the target area according to the user's area permissions" may also include steps A1 to A3.

[0181] Step A1: Verify the total equipment reading error of the devices to be managed within the target area, and mark the target area with measurement error as an abnormal area.

[0182] Specifically, a regional input metering unit is set up in each target area. The regional input metering unit is used to calculate the readings of the input devices in the corresponding target area, obtain the metering data of the devices to be managed in each target area, calculate the total metering data of the devices to be managed in the target area based on the obtained metering data of the devices to be managed in the target area, and mark it as the regional device to be managed data. The allowable metering error of the devices to be managed in the corresponding target area is set. The allowable metering error of the devices to be managed is set according to the characteristics and number of devices to be managed. The difference between the readings of the devices to be managed in the regional input metering unit and the regional device to be managed data is calculated and marked as the regional difference. The target area where the absolute value of the regional difference is greater than the allowable metering error of the devices to be managed is obtained, because the regional difference may be negative.

[0183] Step A2: Obtain the analysis model corresponding to the abnormal area, collect the metering data of each managed device in the abnormal area during the current time period, analyze the collected metering data of the managed devices through the analysis model, obtain the metering devices corresponding to the abnormal device metering data, and mark them as abnormal devices; the time span of the current time period is set by the expert group according to the metering device usage specifications.

[0184] Specifically, the system acquires historical metering data of devices under management for each target area, filters out accurate metering data from this historical data, marks it as regional training data, and obtains a metering device analysis model. This model is a currently available neural network model for analyzing metering anomalies. The model is trained and validated using the regional training data. Successfully validated models are marked as analysis models, and the analysis models are labeled with the corresponding target area. The system then matches the abnormal areas to obtain analysis models with the corresponding target area labels.

[0185] Step A3: Establish a metering equipment analysis library, obtain the metering data of the abnormal equipment for the previous N days, where N is a positive integer, input the obtained metering data into the metering equipment analysis library for analysis, and obtain the inaccuracy judgment result of the abnormal equipment.

[0186] Specifically, a large amount of historical metering data from metering equipment is acquired. Metering data from inaccurate metering equipment is filtered out and marked as inaccurate data. Inaccurate data includes the metering date and the corresponding metering data. The cause of the fault corresponding to the inaccurate data is obtained. Data bars are set up, with N data padding positions, each corresponding to a metering date. A group of inaccurate data is integrated into one data bar, and the data bars are numbered. A fault cause matching table is set up based on the data bar number and the corresponding fault cause. A database is established, and the data bars are input into the database for storage. The database contains clustering units to cluster the data bars, obtaining k inaccurate clusters. A matching unit is set up in the database to match the input data bar vectors. The database is then marked as a metering equipment analysis library.

[0187] The metering equipment analysis library acquires the input metering data, inputs the acquired metering data into data bars, and marks them as analysis data bars. The analysis data bars are vectorized and marked as analysis data bar vectors. The analysis data bar vectors are mapped to a vector space and clustered by a clustering unit to obtain the cluster to which the analysis data bar vector belongs and mark it as an analysis cluster. The matching unit matches the analysis data bar vectors with the data bar vectors in the analysis cluster one by one to obtain the matching degree between the analysis data bar vectors, which refers to the proportion of data with the same position in two vectors. Data bar vectors with a matching degree greater than a first threshold are marked as matched data. The proportion of matched data in the analysis cluster is calculated and marked as the inaccuracy probability. When the inaccuracy probability is greater than a second threshold, the corresponding input metering data is marked as inaccurate data, and the fault cause corresponding to the matched data is obtained. The obtained fault causes are sorted and sent to the relevant management personnel.

[0188] In this embodiment, by setting a regional input metering unit, the problem investigation area can be further narrowed down. Combined with the target area, when a metering discrepancy occurs, the investigation area can be quickly narrowed down, reducing the workload of investigation and improving the efficiency of investigation.

[0189] This embodiment also provides a metering equipment management device for implementing the above embodiments and preferred embodiments; details already described will not be repeated. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0190] This embodiment provides a metering equipment management device, such as... Figure 8 As shown, it includes:

[0191] The character acquisition module 801 is used to determine the target user field information corresponding to the user login information in the geographic information model, and to obtain the region character and role character in the target user field information. The geographic information model is generated based on the user field information, role field information and region field information.

[0192] The information determination module 802 is used to determine the target area field information in the geographic information model based on the area character, and to determine the target role field information in the geographic information model based on the role character;

[0193] The permission determination module 803 is used to determine the target area in the preset area hierarchy of the geographic information model based on the node characters and hierarchy characters in the target area field information, and to determine the user's area permissions based on the permission characters in the target role field information.

[0194] The device management module 804 is used to manage devices in a target area based on user area permissions.

[0195] Further functional descriptions of the above modules are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0196] In this embodiment, the metering equipment management device is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0197] This application also provides a computer device having the above-described features. Figure 8 The metering equipment management device shown.

[0198] Please see Figure 9 , Figure 9 This is a schematic diagram of the structure of a computer device provided in an optional embodiment of this application, such as... Figure 9As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 9 Take a processor 10 as an example.

[0199] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include an integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field-programmable gate array (FPGA), a general-purpose array logic (GPA), or any combination thereof.

[0200] The memory 20 stores instructions executable by at least one processor 10 to cause at least one processor 10 to perform the method shown in the above embodiments.

[0201] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0202] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0203] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0204] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0205] A portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0206] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by this application.

Claims

1. A method for managing metering equipment, characterized in that, The method includes: In the geographic information model, the target user field information corresponding to the user login information is determined, and the region character and role character are obtained from the target user field information. The geographic information model is generated based on the user field information, role field information and region field information. Based on the region character, the target region field information is determined in the geographic information model, and based on the role character, the target role field information is determined in the geographic information model. Based on the node characters and hierarchy characters in the target area field information, the target area is determined in the preset area hierarchy of the geographic information model, and the user's area permissions are determined based on the permission characters in the target role field information. Manage the devices to be managed in the target area according to the user's area permissions; The step of managing the devices to be managed in the target area according to the user's area permissions includes: obtaining the metering report of the device to be managed and the upload time of the metering report; verifying the metering report according to preset rules; if the metering report passes the verification, obtaining the device data of the device to be managed based on the metering report; Obtain a fourth preset number of device status data from the device data; determine the device status score of the metering device based on the device status data, wherein the metering device includes the device to be managed; determine the device control strategy based on the device status score and the device status data; generate a first push message based on the score range corresponding to the device status score and the device control strategy. A task list is determined based on the measurement report and the upload time, and push notifications are generated based on the task list.

2. The method according to claim 1, characterized in that, Before determining the target user field information corresponding to the user login information in the geographic information model, the method further includes: Obtain regions under a first preset number of regional levels, and determine the region identifier and associated regions of the regions based on the regional levels; Based on the region level, the region identifier, and the associated region, generate the region field information corresponding to the region; Generate a second preset number of regional management roles and obtain the management permissions corresponding to the regional management roles; The role field information is generated based on the region management role and the management permissions; Obtain user information and determine the corresponding regional management role and region; The user field information is generated based on the user information, the region management role, and the region. The geographic information model is generated based on the user field information, the role field information, and the region field information.

3. The method according to claim 1, characterized in that, The step of obtaining the equipment data of the equipment to be managed based on the metering report includes: Obtain the equipment data of the managed equipment from the metering report; Obtain the operation information corresponding to the measurement report; Using a preset synchronization mechanism, the device data and the operation information are synchronized to a third preset number of storage nodes.

4. The method according to claim 3, characterized in that, The step of using a preset synchronization mechanism to synchronize the device data and the operation information to a third preset number of storage nodes includes: Store the device data and the operation information to the target storage node; If the block height of the target storage node is greater than the block height of other storage nodes, a synchronization request containing the device data and the operation information is generated. The synchronization request is sent to the other storage nodes, wherein the other storage nodes are used to filter the data in the synchronization request according to the defined storage rules, and only store the data that conforms to the storage rules. The storage rules are generated when the storage node is created. The other storage nodes are also used to store the storage rules of their own storage nodes and the storage rules of the target storage node.

5. The method according to claim 1, characterized in that, The step of determining the equipment status score of the metering equipment based on the equipment status data includes: The device operation data, fault information data, and environmental parameter data are obtained from the device status data. The equipment operation data, the fault information data, and the environmental parameter data are preprocessed to obtain a fifth preset number of initial indicator data and the indicator type of the initial indicator data; If the indicator type is the first type, the initial indicator data is used as the indicator data; if the indicator type is the second type, the difference between the preset parameter and the initial indicator data is used as the indicator data. Based on the preset indicator weights and the indicator data, a sixth preset number of indicator scores are generated; The device status score is obtained based on the index score and the score weight.

6. The method according to claim 2, characterized in that, Determining the region corresponding to the user information includes: Obtain a region map containing the area to be managed, and identify the area to be managed in the region map; Based on the number of metering devices and the amount of metering data in the area to be managed, a feature vector of the area to be managed is generated. The distance between the areas to be managed is determined based on the feature vector; Determine whether there are two managed areas whose distance is greater than or equal to a distance threshold; If the distance between two regions to be managed is greater than or equal to the distance threshold, the two regions to be managed will be merged into a new region to be managed. If there is no distance between two regions to be managed that is greater than or equal to the distance threshold, the region corresponding to the user information is determined within the regions to be managed, wherein the region corresponding to the user information is included in the regions to be managed.

7. The method according to claim 1, characterized in that, The step of verifying the measurement report according to preset rules includes: Obtain the file template of the measurement report; The file template is compared with a preset template. If the file template is inconsistent with the preset template, a prompt message is generated. If the file template matches the preset template, obtain the field information from the measurement report; The field information is validated according to the preset field format.

8. The method according to claim 7, characterized in that, The step of validating the field information according to the preset field format includes: Obtain the regular expression corresponding to the preset field format; Based on the regular expression, the data type and data length of the field information are validated to obtain a first validation result; Based on the regular expression, determine whether the value of the field information is within a preset range, and obtain a second verification result; If an abnormal field is determined based on the first verification result, or if the abnormal field is determined based on the second verification result, a prompt message is generated based on the abnormal field; If no abnormal field is identified based on the first verification result, and the abnormal field is not identified based on the second verification result, the measurement report verification is deemed successful.

9. The method according to claim 1, characterized in that, The step of determining a task list based on the metering report and the upload time, and generating push information based on the task list, includes: Based on the measurement report, generate a measurement task to be processed; Obtain the metering cycle of the metering task to be processed; The deadline for the pending metering task is determined based on the upload time and the metering period. The task list is generated based on the pending metering tasks and the task deadlines; Based on the difference between the current system time and the task deadline, a second push notification containing the task list is generated.

10. The method according to claim 1, characterized in that, After obtaining the equipment data of the device to be managed based on the metering report, the method further includes: Obtain the upload process data of the metering report, and generate an operation log based on the upload process data, the metering report, the user login information, and the upload time; If the managed device is abnormal, determine whether the user area permissions include the permissions corresponding to the operation log; If the user area permissions include the permissions corresponding to the operation log, the abnormal information and responsible person information of the device to be managed are determined based on the operation log.

11. A computer device, characterized in that, include: A memory and a processor are communicatively connected, the memory stores computer instructions, and the processor executes the computer instructions to perform the metering equipment management method according to any one of claims 1 to 10.

12. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions for causing the computer to execute the metering equipment management method according to any one of claims 1 to 10.

13. A computer program product, characterized in that, It includes computer instructions for causing a computer to execute the metering equipment management method according to any one of claims 1 to 10.

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