A power grid digital service background management system

Abstract

The present invention relates to the field of power grid service management and discloses a digital grid service backend management system for power grids. The system includes a backpack management module, a power-on self-test log module, a peripheral operation log module, a device operation status management module, a user information query module providing functions for managing and querying basic user information, and a one-click service call module. Compared to existing service systems that typically rely on traditional fixed counters or window equipment, which often fail to achieve efficient and real-time service management, particularly when responding to complex and changing door-to-door service needs, the present application, through the comprehensive utilization of grid information technology and digital backpack information technology, achieves efficient and real-time power grid service management even when responding to complex and changing door-to-door service needs, thereby improving service quality.

Description

Technical Field

[0001] The present invention relates to the technical field of power grid service management, and in particular to a power grid digital grid service background management system. Background Art

[0002] Currently, traditional power grid service management systems typically rely on fixed-location counters or window devices to provide services. These systems can meet basic operational requirements when handling daily, standardized service needs. However, when service needs become complex, dynamic, or require special processing, this fixed-location service model can easily become inflexible, especially when dealing with complex and changing on-site service needs, and cannot respond effectively and in real time. Therefore, in order to better adapt to rapidly changing service needs and improve user satisfaction, there is an urgent need for a power grid service management system that does not rely on fixed counters. It can improve the efficiency and effectiveness of service management through a more flexible and intelligent approach to better meet diverse user needs. Summary of the Invention

[0003] In response to the above-mentioned technical deficiencies, the purpose of the present invention is to propose a power grid digital grid service background management system, which aims to solve the technical problem that the existing technology relies on traditional fixed counter or window equipment service systems, especially when dealing with complex and changing door-to-door service needs, and cannot achieve efficient and real-time service management.

[0004] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides a power grid digital grid service background management system,

[0005] Preferably, the system comprises:

[0006] Backpack management module, used to maintain detailed information about the backpack; the backpack's detailed information includes the device number, device MAC address, and manufacturer;

[0007] The backpack authentication module is used to register and authenticate the backpack based on its device MAC address and device number. Specifically, the module records the MAC address and device number of each backpack device in a database before the device is used. When the device is started, the device automatically sends its own MAC address and device number to the backend via TLS / SSL encryption. The backend receives the MAC address and device number sent by the backpack device and matches and verifies them with the pre-stored information in the database. Based on the result of the matching verification, an authentication result signal is returned. If the verification is successful, the device is allowed to access the network. If the verification fails, the device access is denied and a security alarm is triggered.

[0008] The power-on self-test log module is used to record and upload the backpack power-on self-test information based on the backpack's registration and authentication information;

[0009] The peripheral operation log module is used to record and upload the operation status of peripherals connected to the backpack based on the backpack's power-on self-test information;

[0010] The device operation status management module is used to count the backpack's operation status after the power-on self-test and peripheral operation log recording are completed, and use the improved random forest algorithm to predict faults;

[0011] User information query module, used to provide management and query of user information functions when the device is operating normally;

[0012] The grid worker service information query module is used to provide users with the function of viewing the service information of grid workers in the service area;

[0013] The one-click call service module is used to select and connect with the grid worker based on the service information of the grid worker in the service area.

[0014] Preferably, the backpack management module further includes:

[0015] UKEY management unit, used to manage database access permission control keys;

[0016] Device status query unit, used to query the running status of the backpack according to the device number or manufacturer;

[0017] The automated dispatching unit is used to automatically optimize dispatching instructions and respond to service requests based on current service demands and backpack locations.

[0018] Preferably, the backpack authentication module further includes:

[0019] The identity authentication unit is used to authenticate the legitimacy of the grid worker's identity based on the authorization code. After the authentication is passed, the grid worker is allowed to enter the normal operation interface. If the authentication fails, the grid worker is prohibited from using the backpack.

[0020] Preferably, the power-on self-test log module further includes:

[0021] Self-test information recording unit, used to record the time of each power-on, offline time and self-test information of peripherals;

[0022] Preferably, the peripheral operation log module further includes:

[0023] The peripheral call recording unit is used to record the operation result information of each peripheral call;

[0024] The peripheral log query unit is used to query the operation log of the peripheral hardware and record the operation time, status, operation and results of the peripheral.

[0025] Preferably, the device operation status management module further includes:

[0026] Real-time monitoring unit, used to collect statistics on the operating status of the equipment through real-time monitoring data and equipment status identification;

[0027] The status query unit is used to query the operating status of the equipment according to the manufacturer and equipment number.

[0028] Preferably, the user information query module further includes:

[0029] Area Publicity Unit: Divides the service area into grids and pushes the corresponding grid worker information within the service area to the Power Grid Service Mini Program;

[0030] The information query unit is used to query based on user number, manufacturer, and registration time information.

[0031] Preferably, the grid worker service information query module further includes:

[0032] Backpack power query unit, used by users to view the power information of grid workers' grid backpacks in the service area through the grid service applet;

[0033] Location query unit, used by users to check the location of grid workers in the service area through the power grid service applet;

[0034] The service scope query unit is used by users to view the service scope of grid workers in the service area through the power grid service applet.

[0035] Preferably, the one-key call service module further includes:

[0036] The calling unit is used by users to call grid workers through the grid service applet.

[0037] The beneficial effect of the present invention is that compared with the prior art which usually relies on traditional fixed counter or window equipment service systems, especially when dealing with complex and changing door-to-door service needs, the technical problem of being unable to achieve efficient and real-time service management, this application achieves efficient and real-time grid service management when dealing with complex and changing door-to-door service needs through the comprehensive use of grid information technology and digital backpack information technology, thereby improving service quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1This is a schematic diagram of the power grid digital service background management system device of the present invention. DETAILED DESCRIPTION

[0040] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0041] like Figure 1 FIG. 1 is a flow chart of the first embodiment of the background management system for digital grid services of the power grid according to the present invention, and provides the first embodiment of the background management system for digital grid services of the power grid according to the present invention.

[0042] In a first embodiment, the system includes:

[0043] Backpack management module: used to maintain detailed information about the backpack, including the device number, device MAC address, and manufacturer.

[0044] The backpack authentication module is used to register and authenticate the backpack based on its device MAC address and device number. Specifically, the module records the MAC address and device number of each backpack device in a database before the device is used. When the device is started, the device automatically sends its own MAC address and device number to the backend via TLS / SSL encryption. The backend receives the MAC address and device number sent by the backpack device and matches and verifies them with the pre-stored information in the database. Based on the result of the matching verification, an authentication result signal is returned. If the verification is successful, the device is allowed to access the network. If the verification fails, the device access is denied and a security alarm is triggered.

[0045] It should be noted that the authentication module ensures that all used backpacks are verified through the core security protocol, thereby protecting the service network from unauthorized access and potential security threats.

[0046] It is understandable that the functionality of the backpack authentication module is not limited to initial registration authentication, but also includes continuous monitoring and regular re-authentication of the backpack to ensure compliance and security throughout the life cycle of the device.

[0047] It should be understood that the registration authentication method can be based on the device MAC address and device number. The system compares the MAC address and device number of the backpack with the pre-registration information stored in the database to ensure that each device is unique and matches the original registration information, providing physical and logical dual verification to enhance security. The specific implementation steps can be:

[0048] (1) Pre-registration process:

[0049] Before the device is put into use, the MAC address and device ID of each backpack are recorded in a secure database. This information serves as the device's unique identifier and is used in subsequent verification processes. To ensure the security of the database, encrypted storage and access control mechanisms are used to prevent unauthorized access and information leakage.

[0050] (2) Authentication request when the device starts: Whenever the backpack device starts and attempts to connect to the network, the device automatically sends its stored MAC address and device number to the backend service system. This information transmission process needs to be carried out through a secure channel (such as using TLS / SSL encryption) to prevent the data from being intercepted or tampered with during transmission.

[0051] (3) Backend Verification Process: After the backend service system receives the MAC address and device number sent from the backpack, it matches and verifies this information with the information stored in the database. The verification algorithm checks whether the received MAC address and device number are completely consistent with the records in the database.

[0052] (4) Authentication result processing: If the verification is successful, the system will return a successful authentication signal to the backpack, and the backpack can then enter the normal operation state and access the grid service network for regular operations. If the verification fails (i.e., the information does not match or does not exist in the database), the system will reject the backpack's access request and may trigger a security alarm to notify the system administrator for further inspection and processing.

[0053] (5) Logging and Monitoring: All details of the authentication process, including successful and failed authentication attempts, should be recorded in security logs. These logs are very important for subsequent security audits and problem solving. Regular security checks and audits should be carried out to ensure that the effectiveness and security of the authentication system have not been compromised.

[0054] The power-on self-test log module is used to record and upload the backpack power-on self-test information based on the backpack's registration and authentication information;

[0055] It should be noted that the core function of this module is to ensure that a comprehensive self-check is performed every time the backpack is powered on, including hardware status, software integrity and peripheral functions, to ensure that the device is in optimal working condition before being put into use.

[0056] It is understandable that the power-on self-test log module not only provides service providers with real-time data on equipment health, but also predicts potential maintenance needs of equipment through historical log analysis, thereby taking maintenance measures in advance and reducing unexpected downtime.

[0057] The peripheral operation log module is used to record and upload the operation status of peripherals connected to the backpack based on the backpack's power-on self-test information;

[0058] It should be noted that peripherals refer to various auxiliary devices connected to the grid service backpack, including receipt printers, barcode readers, ID card readers, etc. These devices are typically used for field service operations such as identity verification, item tracking, and data printing, thereby improving service efficiency and customer satisfaction.

[0059] The device operation status management module is used to count the backpack's operation status after the power-on self-test and peripheral operation log recording are completed, and use the improved random forest algorithm to predict faults;

[0060] It's important to note that the core function of this module is to provide a centralized view, enabling managers to monitor and control the operating status of all devices, including those with real-time monitoring and those not yet connected to automatic monitoring. This unified access control not only improves operational efficiency but also supports the informatization and digital transformation of business hall cloud services.

[0061] It should be understood that the statistics and display of equipment operating status can be implemented through the use of dynamic dashboards displaying key performance indicators (KPIs) such as total operating time, number of failures, and maintenance cycles, updated in real time to reflect the current status. This allows managers to intuitively understand the operating efficiency and health of equipment, enabling them to make decisions quickly. Statistical analysis tools can also be used to track equipment operating data over time, generating trend charts and forecast reports. This helps identify long-term trends in equipment performance and optimize maintenance plans and resource allocation.

[0062] It's understandable that the device health management module not only serves as a data display platform but, through integrated analytical tools, also predicts future equipment maintenance needs and potential failures, enabling proactive preventative measures to maintain business continuity and equipment performance. In traditional random forest algorithms, each tree has the same weight. However, in device health management, changes in device status during specific time periods or under specific conditions (such as a sudden temperature rise or increased load) may be more indicative than usual. Therefore, a dynamic weight adjustment mechanism can be introduced to automatically adjust the weights of each decision tree based on specific characteristics of the device status or the severity of data changes, giving important decision trees a greater role in the final prediction.

[0063] It should be understood that the specific implementation steps for predicting faults using the improved random forest algorithm include:

[0064] (1) Dynamic weight adjustment mechanism

[0065] Improved formula:

[0066]

[0067] in, is the dynamic weight of the t-th decision tree. Weight The value of is adjusted based on specific characteristics of the device status data (such as load, temperature, historical abnormal conditions, etc.). To represent the prediction function in the equipment operation status management module, is the length of the time period, t is the current time step, is the predicted function value at the tth time step.

[0068] For example, if a device is more likely to fail under certain high-load conditions, you can define a function to dynamically adjust the weights of the decision tree based on the current load. For example, when the load exceeds 80%, a higher weight is assigned to the decision tree that processes historically high-load data.

[0069]

[0070] If the current load is 90% and the historical maximum load is 100%, the decision tree weight related to the load at that moment is =0.9 gives priority to the impact of load on equipment status.

[0071] (2) Adaptive adjustment of feature importance

[0072] Improvements: Traditional random forest models rely on feature importance (calculated through information gain or the Gini coefficient) when constructing decision trees, but these feature importances are static. To manage device status, we designed an adaptive feature importance adjustment mechanism that dynamically adjusts feature importance over time or under different operating conditions, enabling more accurate identification of faults or anomalies.

[0073] Traditional formula:

[0074]

[0075] in, For the t-th decision tree, the feature The importance of is the length of the time period, t is the time step, Indicates that at the tth time step, the feature of immediate importance.

[0076] Improved to adaptively adjust feature importance:

[0077]

[0078] Among them, λ(t) is the feature importance adjustment factor, which is dynamically adjusted according to the time period or equipment operation status.

[0079] For example, if temperature is more important during a specific peak period of equipment operation (such as summer), you can define an adjustment factor to adaptively adjust the importance of the feature based on seasonal or equipment temperature changes.

[0080]

[0081] If the current temperature is higher than the historical average temperature, for example, the current temperature is 40°C and the historical average temperature is 30°C, the importance of the temperature feature can be adjusted to λ(t) = 1.33, making the temperature feature more influential when the decision tree splits.

[0082] It should be understood that the complete process of improved random forest fault prediction can be:

[0083] (1) Data collection and feature extraction

[0084] First, the device's operating status management module regularly collects various data features of the device, such as:

[0085] Temperature, load (CPU usage, memory usage, etc.), device working hours, power status

[0086] Network connection status and historical fault records.

[0087] Assume that the data sample is as shown in Table 1:

[0088] Table 1 Feature data sample table

[0089]

[0090] (2) Model training

[0091] The model is trained using a modified random forest algorithm. Using historical device data, the model learns to predict device failures based on different feature combinations. The model attempts to optimize based on the following improvements:

[0092] Dynamic weight adjustment: When device characteristics such as temperature and load reach abnormally high values, the weight of the corresponding decision tree in the random forest will be dynamically increased, making the model more focused on predictions under high load or high temperature conditions.

[0093] Unbalanced Data Processing: Because normal operating data far outweighs fault data, the model assigns a higher penalty to fault data to balance the classification. Using this historical data as input, the model constructs multiple decision trees, each classifying the data based on a different data slice (such as temperature or load). Each decision tree determines whether a device failure is likely under specific conditions.

[0094] (3) Decision tree classification example

[0095] For example, let's consider a simple decision tree (in reality, many more features are used): First split: If the temperature is > 40°C, continue the split; otherwise, predict "normal." Second split: If the CPU load is > 85%, predict "failed"; otherwise, predict "normal." Based on these rules, if the device temperature is 42°C and the CPU load is 90%, the decision tree will conclude that the device is likely faulty. A random forest will have multiple different decision trees, each making decisions based on a different combination of features.

[0096] (4) Dynamic weight adjustment

[0097] Now introduce dynamic weight adjustment:

[0098] Assuming the current temperature is 45°C and the historical average temperature is 35°C, the weight adjustment coefficient of the temperature feature is: 温度 =1.29, then the weight of the decision tree involving the temperature feature will automatically increase by 1.29 times, and participate in the final prediction with a higher weight. In addition, if the current CPU load of the device is 95% and the historical maximum load is 100%, then the weight of the decision tree related to the CPU load will be adjusted to: w 负载 =0.95. After these adjustments, the decision tree for predicting faults is more sensitive to high temperature and high load conditions, and therefore pays more attention to changes in these features.

[0099] (5) Fault prediction

[0100] Through the improved random forest algorithm, we get the prediction results of each decision tree, for example:

[0101] Decision Tree 1: Prediction: "Failure"

[0102] Decision Tree 2: Prediction: "Normal"

[0103] Decision Tree 3: Prediction: "Failure"

[0104] Decision Tree 4: Prediction: "Normal"

[0105] At this point, the model takes a weighted average of the predictions based on the weight of each tree. If the weighted "failure" predictions account for a large proportion of the predictions, the model will ultimately output a prediction of "failure." For example, if the device temperature reaches 45°C and the CPU load reaches 95% at a certain moment, the decision tree will prioritize these important features and, through dynamic weighting adjustments, increase their weight in the prediction. Ultimately, the random forest model may predict that the device will fail within the next few days, issuing an early alert to prompt the user to inspect or adjust device settings. This improvement allows the model to more flexibly respond to device operating data in varying states, improving the accuracy and timeliness of failure predictions. This approach not only allows the model to focus more on critical conditions but also balances data imbalances, thereby better meeting the practical needs of device status management.

[0106] User information query module, used to provide management and query of user information functions when the device is operating normally;

[0107] It should be noted that the user's basic information may include: Personal identification information: For example, name, address, and contact information. This information is used to ensure that services can be accurately delivered and to communicate effectively with users. Service history: For example, the user's previous service requests, fault reports, and their resolutions. This helps provide more personalized services and quickly respond to known issues.

[0108] It is understandable that the user information query module is not only used for basic data query, it can also be integrated into a broader service management system, such as quickly locating affected users and responding when equipment failure occurs or specific services are needed.

[0109] It should be understood that the management and query of user information may specifically include:

[0110] User information collection: for example, name, address, and contact information. This information is used to ensure that services can be delivered accurately and to communicate effectively with users.

[0111] Service history: For example, users’ previous service requests, incident reports, and their resolutions, which helps provide more personalized service and quick responses to known issues.

[0112] Information storage and management: Store users' basic information and service history in the database. Use a structured approach to store data to ensure that each piece of information is properly filed and tagged.

[0113] Information Query: Provides a query interface that allows administrators to quickly find a user's basic information and history based on their name, address, or other identifying information. Query efficiency can be improved through keyword searches and filtering conditions.

[0114] Integration into service management systems: When a device fails or a specific service is required, the system automatically retrieves affected user information and notifies relevant personnel for processing. Fault reports are linked to user information, enabling rapid response and resolution of user issues.

[0115] In addition, to address the privacy and security issues of user information query design, the system also adopts the following security protection measures:

[0116] AES Encryption: User information is encrypted and stored using the Advanced Encryption Standard (AES). AES is a symmetric encryption algorithm that uses the same key for encryption and decryption. First, a secure, random AES key is generated and kept secure. The user's personal information (such as name, address, and contact information) and service history (such as service requests, incident reports, and resolutions) are then encrypted with the AES key. The encrypted data is stored in the database and can only be decrypted and viewed with the correct key.

[0117] Encrypted Transmission: TLS (Transport Layer Security) is used to encrypt data during network transmission, ensuring data security. The TLS protocol encrypts transmitted data to prevent theft or tampering during transmission. The server and client negotiate encryption when establishing a connection to ensure the security of the transmission channel.

[0118] Permission Management: Role-Based Access Control (RBAC): Set different user roles and permissions to ensure that only authorized personnel can access and query user information. The RBAC system controls access to resources by assigning one or more roles to each user and assigning corresponding permissions to each role. For example, the administrator role can access and manage all user information, while the user role can only view their own information. The system verifies the requester's role and permissions when processing each request, ensuring that only requests that meet the required permissions are processed.

[0119] The grid worker service information query module is used to provide users with the function of viewing the service information of grid workers in the service area;

[0120] It should be noted that this module allows users to directly view the location of available grid workers, service types and estimated arrival times in the surrounding area through the interface, enhancing service transparency and user convenience.

[0121] It is understandable that by updating the location and status of grid workers in real time, users can make more reasonable service request decisions, while this also helps service providers optimize resource allocation and response speed.

[0122] It should be understood that the design of the grid worker service information query module not only facilitates users to understand service availability in real time, but also supports more efficient service scheduling. Specifically, the module may include:

[0123] Real-time location tracking: For example, displaying the real-time location of each grid worker, allowing users to select the nearest service provider.

[0124] Service status updates: For example, displaying the grid worker's current task load and estimated completion time to help users assess waiting time.

[0125] Interactive features: For example, allowing users to send service requests or inquiries directly from within the app, improving communication efficiency and reducing response time

[0126] One-click call service module, used to select and connect with grid workers based on their service information within the service area;

[0127] It should be noted that this module enables users to quickly establish contact with grid workers through a simplified interface design and intuitive user interaction process, greatly improving the response efficiency of emergency service requests.

[0128] It is understandable that through the one-click call function, users can directly initiate service requests without performing complex operations or multi-step confirmation. This design is particularly suitable for urgent or immediate service needs.

[0129] It should be understood that the implementation of the one-touch call service module provides instant messaging and efficient scheduling support, particularly in the following aspects:

[0130] Direct communication connection: For example, one-click calling can immediately start a voice or video call, allowing users and grid workers to communicate directly and quickly clarify service needs and response details.

[0131] Intelligent recommendation system: For example, the system automatically recommends the grid worker that best suits the user's needs based on the grid worker's location, skills, and historical service evaluation.

[0132] Urgent response optimization: For example, for service requests marked as urgent, the system can prioritize them to ensure a quick response.

[0133] In a second embodiment, the backpack management module in the power grid digital service background management system further includes:

[0134] UKEY management unit, used to manage database access permission control keys;

[0135] Device status query unit, used to query the running status of the backpack according to the device number or manufacturer;

[0136] The automated dispatching unit is used to automatically optimize dispatching instructions and respond to service requests based on current service demands and backpack locations.

[0137] It should be noted that a UKEY is a digital key or authentication token that includes a set of encrypted authentication credentials and is used to enhance the security of devices and systems. This type of UKEY is typically used to control access to sensitive data and operations, ensuring that only authorized users can access or modify configurations.

[0138] It is understandable that the function of the UKEY management unit is not limited to verifying the validity of UKEY. It is also responsible for monitoring the usage of UKEY, updating and revoking UKEY, and recording UKEY security events to ensure the overall security of the system.

[0139] It should be understood that the specific implementation of querying based on the device number or device manufacturer can be:

[0140] Database query: By establishing a central database containing detailed information on all devices, the query function can quickly retrieve the current status and historical operating data of the corresponding device from the database by entering the device number or manufacturer's key information.

[0141] Real-time monitoring system: Combined with the real-time data acquisition system, using the equipment number or manufacturer information as the filtering condition, it can display the operating status of the equipment in real time, including but not limited to operating efficiency, fault reports and maintenance reminders.

[0142] API calls: Through programming interfaces (APIs), internal or external systems are allowed to request and retrieve status information of specific devices. This approach improves system interoperability and scalability, making device management more flexible and automated.

[0143] In a third embodiment, the backpack authentication module in the power grid digital service background management system further includes:

[0144] The identity authentication unit is used to authenticate the legitimacy of the grid worker's identity based on the authorization code. After the authentication is passed, the grid worker is allowed to enter the normal operation interface. If the authentication fails, the grid worker is prohibited from using the backpack.

[0145] It should be noted that the grid worker authorization code is a unique code used to identify and verify each grid worker. This authorization code can be a combination of numbers and letters, generated based on the grid worker's name, position number, area code, and other information; a dynamically generated time-sensitive authorization code, similar to the temporary verification code used in two-factor authentication, with a new authorization code generated each time the grid worker logs in; or a token encrypted using public keys, which further enhances security and ensures that the authorization code cannot be stolen or tampered with during transmission.

[0146] As you can see, by using authorization codes for authentication, the system ensures that only authorized grid workers can operate backpack devices. This mechanism not only improves system security but also prevents unauthorized access to sensitive information, ensuring overall system stability and data integrity.

[0147] It should be understood that the process of authenticating the legitimacy of a grid worker's identity based on their authorization code may specifically include the following steps:

[0148] Static authorization code: When a grid worker joins the system, the backend management system generates a unique authorization code and assigns it to the grid worker. This authorization code is bound to the grid worker's personal information and stored in the system's security database.

[0149] Dynamic Authorization Code: Each time a grid worker attempts to log in, the system generates a dynamic authorization code based on the current time, the grid worker's personal information, and a security algorithm. This dynamic authorization code is valid for a limited time and needs to be regenerated after it expires.

[0150] Authorization code input and submission: When using a backpack device, grid workers need to enter their authorization code. This authorization code is encrypted and transmitted to the system's backend server to prevent it from being intercepted during transmission.

[0151] Server Verification: After receiving the authorization code, the system's backend server compares it with the information in its database. For dynamic authorization codes, the server also verifies the consistency of the timestamp and the generation algorithm. If the authorization code matches the grid worker's identity information and is within the validity period, the authentication is successful.

[0152] Authentication passed: The system allows the backpack device to enter the normal operation interface, and the grid worker can perform the corresponding tasks.

[0153] Authentication failed: The system will prohibit the use of the backpack device and record the failed authentication attempt. The system may issue a warning to the administrator to prevent potential security threats.

[0154] In a fourth embodiment, the power-on self-test log module in the power grid digital service background management system further includes:

[0155] The self-test information recording unit is used to record the time of each power-on, offline time and self-test information of peripherals.

[0156] It should be noted that the main purpose of these components is to ensure the reliability and safety of the equipment every time it is started, while providing sufficient data support for equipment performance monitoring and fault prevention.

[0157] It is understandable that the design of the power-on self-test log module not only enhances the self-diagnosis capability of the equipment, but also provides an efficient way to track equipment health and operation history by continuously recording and uploading key operating data, which is crucial for maintenance work and service optimization.

[0158] It should be understood that specific implementations may include:

[0159] Detailed boot logging: The self-diagnosis information recording unit records the boot time, operating system loading status, hardware status check results, and any error or warning messages each time the device is turned on. This information helps quickly identify potential problems during the boot process.

[0160] Timed and triggered upload mechanisms: The self-test information upload unit can be configured to automatically upload logs after each power-up, or trigger uploads when specific events or errors are detected. This ensures data timeliness and integrity while reducing pressure on local storage.

[0161] Cloud storage and analysis: Uploaded self-test data can be stored on a cloud platform for remote query and analysis by system administrators or maintenance teams. This approach supports cross-regional device management and immediate fault response.

[0162] In a fifth embodiment, the grid worker service information query module in the power grid digital grid service background management system further includes:

[0163] The backpack power query unit is used for users to view the power information of the grid worker's grid backpack in the service area through the power grid service applet. The power information is sorted by the recommendation algorithm and pushed;

[0164] The location query unit is used by users to view the location of grid workers in the service area through the power grid service applet. The location information is sorted by the recommendation algorithm and then pushed;

[0165] The service scope query unit is used by users to view the service scope of grid workers in the service area through the power grid service applet. The service scope information is sorted by the recommendation algorithm and then pushed;

[0166] The recommendation algorithm is a multi-factor ranking algorithm that comprehensively considers the power information, location information and service scope information of the grid worker's grid backpack.

[0167] It should be noted that these functions are designed to provide transparent service information, enabling users to make informed choices based on the actual situation of grid workers, thereby optimizing user experience and service efficiency.

[0168] It is understandable that by providing real-time information on the location, power consumption, and service scope of grid workers, the system greatly facilitates users in finding appropriate service resources when needed, while also helping managers to better dispatch personnel and resources.

[0169] It should be understood that the recommendation algorithm is a multi-factor ranking algorithm that takes into account the grid worker's grid backpack power information, location information, and service range information. The algorithm makes recommendations based on the following principles:

[0170] Battery priority: Prioritize the delivery of grid workers’ backpacks with sufficient battery power to ensure that grid workers can continue to provide services without being affected by insufficient battery power.

[0171] Location priority: When the battery levels are similar, the grid worker closest to the user's current location is recommended to reduce response time.

[0172] Prioritize service range: When power consumption and location are similar, grid workers with higher service demand or activity within the service range are recommended to optimize resource utilization.

[0173] Comprehensive weight: By setting weight coefficients for power consumption, location, and service range, the comprehensive score of each grid worker is calculated, and finally the results are ranked according to the comprehensive score and pushed to the user.

[0174] For example, suppose there are three grid workers A, B, and C. They are located in different locations, and their backpack power levels and service ranges are also different. Now, a user needs to call a grid worker for door-to-door service. The data example is as follows:

[0175] Grid worker A: Battery level is 80%, 1 km away from the user, and there are 10 active users within the service area.

[0176] Grid worker B: Battery level is 60%, the user is 0.5 km away, and there are 15 active users within the service area.

[0177] Grid worker C: Battery level is 90%, 1.5 kilometers away from the user, and there are 8 active users within the service area.

[0178] The recommendation algorithm steps are as follows:

[0179] (1) Electricity calculation:

[0180] Grid worker C has the highest power level at 90%, and therefore scores the highest in terms of power level.

[0181] Grid worker A has the second highest electricity consumption, at 80%.

[0182] Grid worker B has the lowest battery level, at 60%.

[0183] (2) Position calculation:

[0184] Grid worker B is closest to the user at 0.5 km, and therefore has the highest score in terms of location.

[0185] Grid worker A is 1 km away from the user and has a middle location score.

[0186] Grid worker C is the farthest away, at 1.5 kilometers, and has the lowest location score.

[0187] Assuming that the maximum effective service distance is 2 kilometers, the calculation formula is: Location score = (1-actual distance / maximum effective service distance) * 100%. It can be obtained that the location score of grid worker A is 50%, the location score of grid worker B is 75%, and the location score of grid worker C is 25%.

[0188] (3) Calculation of service scope:

[0189] Grid worker B has 15 active users within his service area and therefore scores the highest in terms of service coverage.

[0190] Grid worker A has 10 active users within his service area and scores in the middle.

[0191] Grid worker C has 8 active users within his service area and has the lowest score.

[0192] It is understandable that considering that the more active users a grid worker has, the busier he is, and the lower his recommendation priority should be, a reverse weighted approach can be used to calculate the service coverage score. In this way, the more active users a grid worker has, the lower his service coverage score will be.

[0193] The calculation formula can be: Service scope score = (1-active users / 20) * 100%. It can be obtained that the service scope score of grid worker A is 50%, the service scope score of grid worker B is 25%, and the service scope score of grid worker C is 60%.

[0194] (4) Comprehensive weight and score:

[0195] The weight coefficients of power, location, and service range are set to 0.4, 0.3, and 0.3 respectively (the total is 1).

[0196] Calculate the comprehensive score of each grid worker:

[0197] Grid worker A: Comprehensive score = 80% × 0.4 + 50% × 0.3 + 50% × 0.3 = 32% + 15% + 15% = 62%

[0198] Grid worker B: Comprehensive score = 60% × 0.4 + 75% × 0.3 + 25% × 0.3 = 24% + 22.5% + 7.5% = 54%

[0199] Grid worker C: Comprehensive score = 90% × 0.4 + 25% × 0.3 + 60% × 0.3 = 36% + 7.5% + 18% = 61.5%

[0200] (5) Final recommendation:

[0201] Based on the comprehensive score, the recommendation algorithm ranks grid worker A as the first choice, grid worker C as the second choice, and grid worker B as the last.

[0202] This recommendation method takes into account power consumption, location, and service range, and adjusts the service range through inverse weighting to reflect the busyness of grid workers and ensure that users can obtain services more efficiently.

[0203] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A power grid digital service background management system, characterized in that: The system includes: Backpack management module, used to maintain detailed information of the backpack; the detailed information of the backpack includes the device number, device MAC address, and manufacturer; The backpack authentication module is used to register and authenticate the backpack based on its device MAC address and device number. Specifically, the module records the MAC address and device number of each backpack device in a database before the device is used. When the device is started, the device automatically sends its own MAC address and device number to the backend via TLS / SSL encryption. The backend receives the MAC address and device number sent by the backpack device and matches and verifies them with the pre-stored information in the database. Based on the result of the matching verification, an authentication result signal is returned. If the verification is successful, the device is allowed to access the network. If the verification fails, the device access is denied and a security alarm is triggered. The power-on self-test log module is used to record and upload the backpack power-on self-test information based on the backpack's registration and authentication information; The peripheral operation log module is used to record and upload the operation status of peripherals connected to the backpack based on the backpack's power-on self-test information; The device operation status management module is used to collect statistics on the backpack's operation status after the power-on self-test and peripheral operation log recording are completed, and to predict faults using an improved random forest algorithm. The improved random forest algorithm has an adaptive feature importance adjustment mechanism designed for device status management. User information query module, used to provide management and query of user information functions when the device is operating normally; The grid worker service information query module is used to provide users with the function of viewing the service information of grid workers in the service area; specifically, it includes: a backpack power query unit, which is used for users to view the power information of grid workers' grid backpacks in the service area through the grid service applet, and the power information is pushed after being sorted by the recommendation algorithm; a location query unit, which is used for users to view the location information of backpacks carried by grid workers in the service area through the grid service applet, and the location information is pushed after being sorted by the recommendation algorithm; a service range query unit, which is used for users to view the service range information of grid workers in the service area through the grid service applet, and the service range information is pushed after being sorted by the recommendation algorithm; wherein, the recommendation algorithm is a sorting algorithm that is comprehensively calculated based on the power information, location information and service range information of the grid worker's grid backpack, and the processing steps specifically include power calculation, location calculation, service range calculation, comprehensive weight and score calculation and final recommendation; The one-click call service module is used to select and connect with the grid worker based on the service information of the grid worker in the service area.

2. The power grid digital service background management system according to claim 1, characterized in that: The backpack management module further includes: UKEY management unit, used to manage database access permission control keys; The automated dispatching unit is used to automatically optimize dispatching instructions and respond to service requests based on current service demands and backpack locations.

3. The power grid digital service background management system according to claim 1, characterized in that: The backpack authentication module further includes: The identity authentication unit is used to authenticate the legitimacy of the identity based on the authorization code of the grid worker. After the authentication is passed, the grid worker is allowed to enter the normal operation interface of the backpack. If the authentication fails, the grid worker is prohibited from using the backpack.

4. The power grid digital service background management system according to claim 1, characterized in that: The power-on self-test log module further includes: Self-test information recording unit, used to record the time of each power-on, offline time and self-test information of peripherals; The self-test information uploading unit is used to upload the self-test information to the database.

5. The power grid digital service background management system according to claim 1, characterized in that: The peripheral operation log module also includes: The peripheral call recording unit is used to record the operation result information of each peripheral call; The peripheral log query unit is used to query the operation log of the peripheral hardware and record the operation time, status, operation and results of the peripheral.

6. The power grid digital service background management system according to claim 1, characterized in that: The device operation status management module further includes: Real-time monitoring unit, used to collect statistics on the operating status of the equipment through real-time monitoring data and equipment status identification; The status query unit is used to query the operating status of the equipment according to the manufacturer and equipment number.

7. The power grid digital service background management system according to claim 1, characterized in that: The user information query module further includes: Area Publicity Unit: Divides the service area into grids and pushes the corresponding grid worker information within the service area to the Power Grid Service Mini Program; The information query unit is used to query based on user number, manufacturer, and registration time information.

8. The power grid digital service background management system according to claim 1, characterized in that: The one-key call service module further includes: The calling unit is used by users to call grid workers through the grid service applet.

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