Data monitoring and statistical interaction method and system of all-network public network base station based on satellite communication

Abstract

The invention discloses a data monitoring and statistical interaction method and system of an all-network public network base station based on satellite communication. Comprising a data acquisition layer, a data processing layer, a data storage layer and a user interaction layer. The data acquisition layer acquires original data from multiple data sources and preprocesses the original data, the data processing layer processes the data by using an algorithm and supports self-defined logic, the data storage layer designs real-time and historical data tables and has backup and recovery functions, and the user interaction layer provides visualization and interaction functions. Screening query is realized by setting a multi-dimensional screening box and a fuzzy search box, core network link monitoring is realized by acquiring a link state through a timed task, and data statistical fusion is realized by establishing timed task statistical site information and performing combined query. And the system realizes corresponding functions corresponding to the functional modules. According to the invention, efficient data management and analysis are realized, the efficiency of data query, network monitoring and statistical analysis is improved, diversified service requirements are met, and data security is guaranteed.

Description

Technical Field

[0001] The present invention belongs to the technical field of satellite communication, and particularly relates to a data monitoring and statistical interaction method and system for a network-wide public network base station based on satellite communication. Background Art

[0002] In the scope of multi-site data management, with the continuous growth of the number of sites and the continuous expansion of data dimensions, traditional monitoring and statistical technologies are facing severe challenges. Existing solutions have significant deficiencies in the intuitiveness, interactivity of data display, and flexibility of data processing. For example, due to the lack of in-depth integration of multiple dimensions in the filtering and query functions, the data retrieval efficiency is extremely low; the network status monitoring is neither timely nor accurate, and the visualization effect is poor, making it difficult for administrators to quickly lock the fault point; when performing data statistics, there are obstacles in the integration of real-time data and historical data, which affects the comprehensive analysis of the overall operation status of the site and decision-making.

[0003] Specifically, the existing related technologies have at least the following deficiencies: Limited filtering and query functions: Due to the lack of in-depth integration of multiple dimensions in the existing technology, the filtering and query functions are single and not flexible enough. When users try to retrieve specific data, they often need to go through multiple steps or combine different query conditions, which not only reduces the data retrieval efficiency but also increases the operation complexity of users. In addition, the filtering and query functions of the existing technology often lack the ability of fuzzy query, making it difficult for users to find the required information when the data does not exactly match.

[0004] Inaccurate network status monitoring and poor visualization effect: In the existing multi-site data management system, the monitoring of network status is often not timely and accurate. The system cannot reflect the true state of the network link in real time, resulting in administrators' difficulty in discovering and solving network faults in a timely manner. At the same time, the visualization effect of the existing technology is also poor, and it cannot intuitively display the changes and trends of the network status, making it difficult for administrators to locate the fault point.

[0005] Lack of smooth integration of real-time and historical data in data statistics: In the field of multi-site data management, the integration of real-time and historical data in data statistics is an important issue. However, the existing technology often fails to effectively solve this problem. The update of real-time data is not timely enough, and the integration of historical data is also chaotic, lacking a reasonable storage and call mechanism. This results in administrators' difficulty in obtaining comprehensive and accurate data support when analyzing the overall operation status of the site, thus affecting the formulation and implementation of decisions.

[0006] In summary, the deficiencies of existing monitoring and statistical technologies in data screening and querying, network status monitoring, data statistical integration, etc. seriously restrict the efficient operation of satellite communication systems and the accuracy of management decisions. Therefore, there is an urgent need for an innovative technical solution to solve these problems and improve the level and efficiency of multi-site data management. Summary of the Invention

[0007] In view of this, in order to overcome the deficiencies of the existing technology, the present invention provides a data monitoring and statistical interaction method and system for a full-network public network base station based on satellite communication, aiming to build a screening and query system with multi-dimensional combination and fuzzy query function, optimize the list display function to improve the convenience of data retrieval and viewing; realize real-time and accurate monitoring, visual presentation and dynamic reporting of abnormal information of the core network link status, and display data separately according to different operator enterprise roles; establish a reasonable data storage and call mechanism, process historical data through scheduled tasks and effectively integrate and display it with real-time data, so as to provide comprehensive and accurate data support for administrators to analyze the overall operation status of the site and improve the efficiency of communication system management and the scientificity of decision-making.

[0008] To achieve the above object, the technical solution adopted by the present invention is as follows: In the first aspect of the present invention, a data monitoring and statistical interaction method for a full-network public network base station based on satellite communication is provided, including the following steps: S1 System architecture construction step: Build a system architecture including a data acquisition layer, a data processing layer, a data storage layer, and a user interaction layer. The data acquisition layer collects raw data from satellite stations, base stations, and user service-related data sources, and uses API interface calls, log file parsing, and database synchronization to verify and preprocess the collected data; the data processing layer uses cleaning, integration, and analysis algorithms to identify and correct data errors and outliers, classify, aggregate, and transform the data according to business requirements, and also supports custom processing logic; the data storage layer designs a real-time data wide table and a historical data summary table to store data, and has data backup and recovery functions; the user interaction layer adopts an intuitive and easy-to-use interface design, provides data visualization tools and interaction functions, and supports data export; S2 Screening and query implementation step: Set filtering boxes and fuzzy search boxes covering dimensions such as time, city, site type, and affiliated unit in the user interaction layer; after the user selects the filtering conditions, the data processing layer constructs a query statement accordingly, queries data from the database, and displays the query results in a list. At the same time, paging and sorting functions are provided, and the user is also supported to export the list data to Excel format; S3 Core Network Link Monitoring Steps: Set up a scheduled task to call the core network firewall interface to obtain link status data; store the obtained data in the link monitoring table, update the status field in the table according to the link status, and record the interruption time and recovery time of the link; in the page display, draw a visualization graph based on the link status data, with normal lines displayed in green and faulty lines displayed in red. At the same time, design an abnormal information reporting function to store the fault information in a relevant table and display it in real time on the page; for different operator enterprise roles, restrict according to role permissions during data query and display; S4 Data Statistics and Fusion Steps: Establish a scheduled task to count the site information that has been online today, and insert the statistical information into the historical data summary table; design a real-time data wide table to store the real-time data at the current moment; in the statistical query module, the data processing layer performs a joint query on the real-time data wide table and the historical data summary table according to the user's filtering conditions, and associates with the device table to obtain the detailed information of base station devices and satellite devices, and displays the query results in a list. At the same time, provide data visualization tools and interactive functions.

[0009] Furthermore, in the S2 screening and query implementation steps: S21 Time Screening Specific Method: Time screening is implemented through radio buttons for real-time and interval selection. The interval selection can be accurate to query the data of the current day. After the user selects the screening condition, the system updates the data display result in real time; S22 Details of the Fuzzy Search Function: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, including site name, site person in charge, and device number, improving the accuracy and flexibility of data retrieval; S23 Optimization Details of the List Display: The list display supports users to customize the sorting fields and sort according to the data update time and site importance fields; the paging function supports users to manually enter the page number to jump, and at the same time provides quick operation buttons; S24 Linkage Mechanism of the Screening Boxes: There is a linkage relationship between the screening boxes. When the user selects the city screening condition, the site type screening box will be dynamically updated according to the actual site types in the selected city, reducing invalid screening options and improving the screening efficiency; S25 Preprocessing of Exported Data: When exporting the list data to Excel format, the system will preprocess the exported data, such as uniformly adjusting the data format, converting the satellite traffic and user traffic data according to the conversion rules specified by the front end to ensure the standardization and usability of the exported data; S26 Screening Query Data Source and Processing: The data for screening and querying comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO. Among them, BASE_NOW_INFO stores the data of satellite stations or base stations that have been online on the current day, and BASE_ALL_INFO stores the data of satellite stations or base stations that have been online except on the current day. When constructing the query statement, the data processing layer will determine whether to query from a single table or perform a union query on two tables based on the time screening condition. If real-time or daily interval data is selected, the query will mainly be from BASE_NOW_INFO. If cross-day interval data is selected, a union all operation will be performed on the two tables and then the query will be executed, and duplicate data will be removed from the query result. S27 Multi-dimensional Screening Logic: When the user selects multiple screening dimensions simultaneously, the query statement constructed by the data processing layer will combine the screening conditions of each dimension through logical operators. S28 Data Structure Basics: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE. Among them, ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain information related to the combined station. The historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically processed historical data. When performing screening and querying, the data processing layer constructs a query statement based on the meanings and association relationships of the fields in each table and extracts the data that meets the conditions from these tables. S29 Screening Query Result Processing: Before the query result is displayed in a list, the data processing layer will sort the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by site name, the data processing layer will call the sorting function of the database to sort the query result set in ascending order according to the BASE_NAME field. If the user selects to sort in descending order by satellite traffic, the sorting will be performed in descending order according to the STATION_FLOW field to ensure that the display order meets the user's requirements.

[0010] Furthermore, in the core network link monitoring step of step S3: S31 Abnormal Information Announcement Extension: In addition to displaying the interruption time and connection time, the abnormal information announcement also includes the fault type and detailed information about the affected site range, which helps the administrator quickly locate and solve problems. S32 Permission Control Refinement: The permissions of different operation enterprise roles are managed through the permission tables associated with the roles. The permission tables clearly define the range of link data that each role can view, and the system automatically matches the corresponding permissions according to the user role for data display. S33 Visual Graphical Interaction Function: The visual graph supports user click operations. When the user clicks on a certain link, the system pops up a detailed information window to display the real-time traffic and detailed bandwidth utilization data of that link. S34 Link Status Data Update Frequency: The scheduled task is set to call the core network firewall interface every two minutes to obtain the link status data, ensuring the real-time nature of the data for timely detection of network failures.

[0011] S35 Fault Information Storage and Query: Fault information is stored in the link_info_notice table. In addition to recording the fault information, this table is also associated with the primary key ID of the link monitoring table link_info, facilitating the administrator to quickly trace back to the corresponding link status data when querying fault information. At the same time, the system provides a function to query fault information based on conditions such as fault time and fault type, facilitating the administrator to analyze and summarize historical faults. S36 Link Status Judgment and Display Logic: After obtaining the link status data, the system compares and judges the link status with the preset normal status threshold. If the real-time traffic and delay indicators of the link exceed the normal range, it is determined to be in a fault state. In the visual graph displayed on the page, the faulty line is not only shown in red but also flashes to alert the administrator. At the same time, in the abnormal information broadcast area, in addition to text information, an audible alarm is also used to notify the administrator, and the audible alarm can be set with different volumes and frequencies according to the severity of the fault. S37 Data Isolation for Different Role Permissions: For different operation enterprise roles, the system performs data isolation at the database query stage. When the mobile administrator logs in, the system adds restrictive conditions to the SQL statement for querying link data to only obtain link data related to mobile, ensuring that data of other enterprises will not be misqueried or leaked, and safeguarding the security and privacy of the data. S38 Structure of the Link Monitoring Table and Data Storage: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID uniquely identifies each link monitoring record as the primary key, link_type is used to distinguish links of different operators, end_time records the link interruption time, recovery_time records the recovery time, and type represents the link status, where 0 is for fault and 1 is for normal. The link status data obtained by the scheduled task is stored according to these fields, providing data support for subsequent status judgment, historical query, and visual display. S39 Abnormal Information Broadcast Form Structure and Data Processing: The link_info_notice table relied on for abnormal information broadcast stores detailed information at the time of fault through association with the link_info table. When the link status is abnormal, the system inserts fault-related information, including fault time, fault type, and affected scope, into the link_info_notice table. Meanwhile, in the abnormal information broadcast area of the page, the data in this table is read for real-time display to ensure that administrators can obtain fault information in a timely manner.

[0012] Furthermore, in step S4 of data statistics and fusion: S41 Details of Statistical Information Calculation: When counting the information of sites that went online on the same day, key indicators such as satellite traffic and service duration are accurately calculated. Among them, satellite traffic is accumulated based on traffic data in different time periods, and service duration is calculated according to the actual start and end times of site services. S42 Optimization of Union Query: During union query, the data processing layer intelligently selects query strategies according to user filtering conditions. If the filtering conditions involve a large time range, it preferentially queries from the historical data summary table; if it involves real-time data, it focuses on querying the real-time data wide table to improve query efficiency.

[0013] S43 Expansion of Visualization Display: The data visualization tool supports multiple graph display methods, including line charts and radar charts in addition to bar charts and pie charts. Users can select appropriate graphs to display data according to their needs, and the graphs can be interactively operated, including zooming in, zooming out, and viewing data details. S44 Execution Logic of Scheduled Tasks: The scheduled task is executed at 1:00 am every night to count the information of sites that went online on the same day from the original data table BASE_STATION_DATA. During the counting process, it first determines whether a site went online on the same day based on the site's online time, and then extracts and calculates the data of eligible sites, and inserts the calculated statistical information into the historical data summary table BASE_ALL_INFO. S45 Optimization of Associated Device Information Query: When querying the detailed information of base station devices and satellite devices by associating and querying the device table EQUIPMENT_INFO, a caching mechanism is adopted. For frequently queried device information, it is cached in memory. When the same device information is queried again, it is directly obtained from the cache, reducing the number of database queries and improving system performance. S46 Optimization of Statistical Index Calculation: When counting satellite traffic, for different types of sites, including one or more of ground satellite single sites, ground satellite full sites, and drone satellite full sites, they are calculated and statistically analyzed separately. S47 Union Query Data Integration: When performing a union query on the real-time data wide table and the historical data summary table, the data processing layer integrates the data in the two tables. For duplicate fields in the same site, the latest data is used for display; for unique fields in different tables, they are simultaneously displayed in the query result to provide users with more comprehensive data information. For example, the real-time data wide table may contain the number of real-time online users, and the historical data summary table contains the cumulative number of online users, and both fields will be simultaneously displayed in the query result. S48 Structure and Data Insertion of Historical Data Summary Table: The historical data summary table BASE_ALL_INFO obtains the information of the sites launched on the current day from the original data table BASE_STATION_DATA through a scheduled task at 1:00 am every night for statistics. When performing statistics, the data of the current day is filtered based on the launch time of the site, and the satellite traffic and service duration metrics are calculated, and the calculation results are inserted into the BASE_ALL_INFO table. This table is associated with other tables through equipment_rel_id to ensure data consistency and traceability. S49 Associated Query between Real-Time Data Wide Table and Equipment Table: The real-time data wide table BASE_NOW_INFO is associated with the equipment table EQUIPMENT_INFO through the site_id field. In the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed equipment information from EQUIPMENT_INFO through the associated field, including the equipment name and equipment model, to enrich the query result and provide users with more detailed data display.

[0014] The second aspect of the present invention provides a data monitoring and statistical interaction system for a network-wide public network base station based on satellite communication, including: Data Acquisition Layer: Used to collect raw data from satellite stations, base stations, and user service-related data sources, and perform verification and preprocessing on the collected data using API interface calls, log file parsing, and database synchronization technologies. Data Processing Layer: Connected to the data acquisition layer, cleans, integrates, and analyzes the collected data, uses algorithms to identify and correct data errors and outliers, classifies, aggregates, and transforms the data according to business requirements, and supports custom processing logic. Data Storage Layer: Connected to the data processing layer, designed with a real-time data wide table and a historical data summary table for storing data, and having data backup and recovery functions. User Interaction Layer: Connected to the data storage layer, provides an intuitive and easy-to-use interface, has data visualization tools and interaction functions, supports data export, receives user operation instructions, and transmits them to other layers. Screening and Query Module: Set in the user interaction layer, it includes multi-dimensional screening boxes and fuzzy search boxes, receives user screening conditions, triggers the data processing layer to query data from the database, displays the query results in a list, and provides paging and sorting functions; Core Network Link Monitoring Module: It includes a timing task unit, a data storage unit, and a display unit. The timing task unit periodically calls the core network firewall interface to obtain link status data; the data storage unit stores the data in the link monitoring table and records the link interruption time and recovery time; the display unit draws a visualization graph based on the link status data, displays the normal or faulty status, designs an abnormal information broadcast function, and restricts the data display permissions for different operator enterprise roles; Data Statistics and Fusion Module: It includes a timing task sub-module, a data storage sub-module, and a query and display sub-module; the timing task sub-module establishes a timing task to count the site information that went online on the same day and inserts it into the historical data summary table; the data storage sub-module designs a real-time data wide table to store real-time data; the query and display sub-module jointly queries the real-time data wide table and the historical data summary table according to the user's screening conditions, and associates with the device table to obtain the detailed information of base station devices and satellite devices, displays the results in a list, and provides visualization tools and interaction functions.

[0015] Furthermore, it also includes a time screening component: The time screening component in the screening and query module realizes real-time and interval selection through radio buttons. The interval selection can be accurate to the data of the query day. After the user selects the screening conditions, the system updates the data display results in real time; Fuzzy Search Function Module: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, covering fields such as site name, site person in charge, and device number, improving the accuracy and flexibility of data retrieval; List Display Optimization Module: The list display module supports users to customize the sorting fields and can sort according to fields such as data update time and site importance; the paging function supports users to manually enter the page number to jump, and at the same time provides quick operation buttons; Screening Box Linkage Module: There is a linkage mechanism between the screening boxes. When the user selects the city screening condition, the site type screening box will be dynamically updated according to the actual site types in the selected city; Export Data Preprocessing Module: When exporting the list data to Excel format, the system has an export data preprocessing module to uniformly adjust the data format, and convert the satellite traffic and user traffic data according to the conversion rules specified by the front end; Screening Query Data Source and Processing Module: The data of the screening query module comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO; The data processing layer is equipped with a data source judgment and processing module. When constructing a query statement, it judges whether to query from a single table or jointly query two tables according to the time screening condition; If real-time or same-day interval data is selected, it mainly queries from BASE_NOW_INFO; If cross-day interval data is selected, a union all operation is performed on the two tables and then the query is executed, and duplicate data is removed from the query result; Multi-dimensional Screening Logic Module: When the user selects multiple screening dimensions at the same time, the multi-dimensional screening logic module in the data processing layer combines the screening conditions of each dimension through logical operators to construct a query statement.

[0016] Data Structure Association Module: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE, where ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain information related to the combined station; The historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically processed historical data. The screening query module in the data processing layer constructs a query statement based on the meanings and association relationships of the fields in each table, and extracts the data that meets the conditions from these tables; Screening Query Result Processing Module: Before the query result is displayed in a list, the screening query result processing module in the data processing layer sorts the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by station name, the sorting function of the database is called to sort the query result set in ascending order according to the BASE_NAME field; If the user selects to sort in descending order by satellite traffic, it is sorted in descending order according to the STATION_FLOW field to ensure that the display order meets the user's requirements.

[0017] Furthermore, it also includes an Abnormal Information Announcement Extension Module: The abnormal information announcement extension module of the core network link monitoring module not only displays the interruption time and connection time, but also shows the fault type and detailed information about the affected station range, helping the administrator quickly locate and solve problems; Permission Control Refinement Module: The permissions of different operation enterprise roles are managed through the permission tables associated with the roles. The system is equipped with a permission control refinement module that automatically matches the corresponding permissions according to the user role for data display; Visual Graphical Interaction Function Module: The visual graph supports user click operations. When the user clicks on a certain link, the visual graphical interaction function module pops up a detailed information window to display the real-time traffic and detailed bandwidth utilization data of the link; Link Status Data Update Frequency Module: The timing task unit is equipped with a link status data update frequency module, which is set to call the core network firewall interface every two minutes to obtain link status data to ensure the real-time nature of the data for timely detection of network failures; Fault Information Storage and Query Module: Fault information is stored in the link_info_notice table. In addition to recording fault information, this table is also associated with the primary key ID of the link monitoring table (link_info); The system is equipped with a fault information storage and query module, which facilitates the administrator to quickly trace back to the corresponding link status data when querying fault information; At the same time, it provides the function of querying fault information according to conditions such as fault time and fault type, which is convenient for the administrator to analyze and summarize historical faults; Link Status Judgment and Display Logic Module: After obtaining the link status data, the link status judgment and display logic module of the system compares and judges the link status with the preset normal state threshold. If the real-time traffic and delay indicators of the link exceed the normal range, it is determined to be in a fault state. In the visual graph displayed on the page, the faulty line is not only displayed in red but also flashes to alert the administrator. At the same time, in the abnormal information broadcast area, in addition to text information, the administrator will also be notified by a sound alarm, and the sound alarm can be set with different volumes and frequencies according to the severity of the fault; Data Isolation Module for Different Role Permissions: For different operation enterprise roles, the system is equipped with a data isolation module for different role permissions during the database query stage for data isolation; Link Monitoring Table Structure and Data Storage Module: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID uniquely identifies each link monitoring record as the primary key, link_type is used to distinguish links of different operators, end_time records the link interruption time, recovery_time records the recovery time, and type represents the link status. The link status data obtained by the timing task is stored according to these fields, providing data support for subsequent status judgment, historical query, and visual display; Abnormal Information Broadcast Form Structure and Data Processing Module: The link_info_notice table relied on for abnormal information broadcast stores detailed information at the time of a fault through its association with the link_info table. The system is equipped with an abnormal information broadcast form structure and data processing module. When the link status is abnormal, fault-related information is inserted into the link_info_notice table. Meanwhile, in the abnormal information broadcast area on the page, the data in this table is read for real-time display to ensure that administrators can obtain fault information in a timely manner; Real-time Monitoring Support and Assurance Module: In the construction of a real-time monitoring system for all website points, the core network link monitoring data, as a key part, reflects the network quality in real time. Once a link fails, the system promptly notifies relevant personnel through abnormal information broadcast. Combining with permission management, personnel of different roles can obtain corresponding data, providing a real-time network status basis for ensuring smooth network communication during natural disasters and major events, so as to adjust communication strategies in a timely manner.

[0018] Furthermore, it also includes a Statistical Information Calculation Details Module: When the timed task sub-module of the data statistics and fusion module counts the information of sites that went online on the same day, there is a statistical information calculation details module that precisely calculates key indicators such as satellite traffic and service duration. Among them, satellite traffic is accumulated based on traffic data in different time periods, and service duration is calculated according to the actual start and end times of site services; Joint Query Optimization Module: The query display sub-module is equipped with a joint query optimization module. During joint query, the data processing layer intelligently selects a query strategy according to the user's filtering conditions. If the filtering conditions involve a large time range, it preferentially queries from the historical data summary table; if it involves real-time data, it focuses on querying the real-time data wide table to improve query efficiency; Visualization Display Expansion Module: The data visualization tool supports multiple graphical display methods. In addition to bar charts and pie charts, it also includes line charts and radar charts. The system is equipped with a visualization display expansion module. Users can select appropriate graphs to display data according to their needs, and the graphs can be interactively operated; Timed Task Execution Logic Module: The timed task sub-module is equipped with a timed task execution logic module, which is executed at 1:00 am every night. It counts the information of sites that went online on the same day from the original data table BASE_STATION_DATA. During the counting process, it first determines whether a site went online on the same day based on its online time, and then extracts and calculates the data of eligible sites, and inserts the calculated statistical information into the historical data summary table BASE_ALL_INFO.

[0019] Associated Device Information Query Optimization Module: When querying and displaying detailed information of base station devices and satellite devices from the associated device table EQUIPMENT_INFO, the query display sub-module adopts a caching mechanism. There is an associated device information query optimization module that caches frequently queried device information in memory. When the same device information is queried again, it is directly retrieved from the cache, reducing the number of database queries and improving system performance; Statistical Index Calculation Optimization Module: When calculating satellite traffic, different types of sites, including ground satellite single-site, ground satellite full-site, and drone satellite full-site, are calculated and statistically analyzed separately; Joint Query Data Integration Module: When performing a joint query on the real-time data wide table and the historical data summary table, the query display sub-module has a joint query data integration module that integrates the data in the two tables; for duplicate fields in the same site, the latest data is used for display; for unique fields in different tables, they are simultaneously displayed in the query results to provide users with more comprehensive data information; for example, the real-time data wide table may contain the number of real-time online users, and the historical data summary table contains the cumulative number of online users, and both fields will be simultaneously displayed in the query results; Historical Data Summary Table Structure and Data Insertion Module: The historical data summary table BASE_ALL_INFO obtains the information of the sites launched on the same day from the original data table BASE_STATION_DATA through a scheduled task at 1:00 am every night for statistics. The system has a historical data summary table structure and data insertion module. During statistics, the data of the same day is filtered according to the site launch time, and the satellite traffic and service duration indicators are calculated, and the calculation results are inserted into the BASE_ALL_INFO table; this table is associated with other tables through equipment_rel_id to ensure data consistency and traceability; Associated Query Module between Real-Time Data Wide Table and Device Table: The real-time data wide table BASE_NOW_INFO is associated with the device table EQUIPMENT_INFO through the site_id field; the query display sub-module has an associated query module between the real-time data wide table and the device table. In the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed device information from EQUIPMENT_INFO through the associated field to enrich the query results and provide users with more detailed data display.

[0020] Multi-dimensional Cross-analysis Application Module: During natural disasters or major events, the system utilizes the data statistics and fusion function and is equipped with a multi-dimensional cross-analysis application module to conduct multi-dimensional cross-analysis on satellite and base station data. Comprehensive analysis is carried out by combining the time dimension including before, during, and after the disaster, the regional dimension including the core affected area, the surrounding impact area, and the site type dimension including ground satellite single-site and ground satellite full-site, generating refined statistical reports to provide comprehensive data support for command and dispatch.

[0021] The present invention adopts the above technical solutions and has the following specific beneficial effects: Implementation of the multi-dimensional screening and query function: The present invention designs a powerful screening box at the user interaction layer, allowing users to perform screening and query according to multiple dimensions such as time, city, site type, and affiliated unit. At the same time, a fuzzy query function is also provided to further improve the efficiency and accuracy of data retrieval. The implementation of this multi-dimensional screening and query function provides users with a more flexible and convenient data query method.

[0022] Real-time and visualization of core network link monitoring: The present invention calls the core network firewall interface through a scheduled task to obtain link status data, and realizes real-time update and visualization display of the link status. This design not only improves the response speed of the system, but also enhances the reliability and stability of the system. At the same time, according to the needs of different operator enterprise roles, the present invention also designs a permission restriction function to ensure the security and privacy of data.

[0023] Innovative application of data statistics and fusion technology: The present invention establishes a scheduled task to count the site information that has been online on the same day and inserts the statistical results into the historical data summary table. At the same time, a real-time data wide table is also designed to store the real-time data at the current moment. By jointly querying and processing the data in the real-time data wide table and the historical data summary table, the present invention realizes the comprehensive statistics and fusion display of site data. This innovative application of data statistics and fusion technology provides users with more accurate and comprehensive data analysis results.

[0024] Efficient Data Storage and Call Mechanism The present invention realizes the effective management of real-time data and historical data by establishing a reasonable data storage structure, such as a real-time data wide table and a historical data summary table. This design not only improves the data storage efficiency, but also makes the data call more convenient. Compared with the possible problems of chaotic data storage and low call efficiency in the prior art, the present invention significantly improves the speed and accuracy of data processing.

[0025] Scheduled Task Processing and Data Fusion Display The present invention automatically counts and processes historical data every night by setting up scheduled tasks, and effectively integrates it with real-time data. This automated processing method not only reduces the burden of manual operations, but also ensures the timeliness and accuracy of data. At the same time, the integrated data is presented in an intuitive manner on the user interface, enabling users to easily obtain the required information. Compared with the problems of untimely data updates and single display methods that may exist in the prior art, the present invention provides more comprehensive and accurate data support.

[0026] Flexible data analysis and processing capabilities The present invention designs flexible data analysis and processing logic in the data processing layer, which can perform customized data processing according to user needs. This design enables the present invention to handle various complex data analysis scenarios and provide more personalized data services for users. Compared with the problems of insufficient data processing capabilities and single analysis methods that may exist in the prior art, the present invention demonstrates stronger flexibility and adaptability in data processing and analysis. Brief Description of the Drawings

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0028] Figure 1 is a flowchart of the data monitoring and statistical interaction method for the all-net-comprehensive public network base station of the present invention; Figure 2 is a schematic diagram of the data monitoring and statistical interaction system module for the all-net-comprehensive public network base station of the present invention. Detailed Embodiments

[0029] Here, the exemplary embodiments will be described in detail, and the examples are shown in the drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present invention. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present invention as detailed in the appended claims.

[0030] Please refer to Figure 1 , this embodiment provides a data monitoring and statistical interaction method for an all-net-comprehensive public network base station based on satellite communication, including the following steps: Steps for building the S1 system architecture: Build a system architecture that includes a data collection layer, a data processing layer, a data storage layer, and a user interaction layer. The data collection layer collects raw data from satellite stations, base stations, and user service-related data sources, and uses API interface calls, log file parsing, and database synchronization to verify and preprocess the collected data; the data processing layer uses cleaning, integration, and analysis algorithms to identify and correct data errors and outliers, classifies, aggregates, and transforms the data according to business requirements, and also supports custom processing logic; the data storage layer designs a wide table for real-time data and a summary table for historical data to store data, and has data backup and recovery functions; the user interaction layer adopts an intuitive and easy-to-use interface design, provides data visualization tools and interaction functions, and supports data export; Steps for implementing S2 filtering and querying: Set up filtering boxes and fuzzy search boxes covering dimensions such as time, city, site type, and affiliated unit in the user interaction layer; after the user selects the filtering conditions, the data processing layer constructs a query statement accordingly, queries data from the database, and displays the query results in a list. At the same time, paging and sorting functions are provided, and users are also supported to export the list data to Excel format; Steps for monitoring the core network link: Set up a scheduled task to call the core network firewall interface to obtain link status data; store the obtained data in the link monitoring table, update the status field in the table according to the link status, and record the link interruption time and recovery time; in the page display, draw a visualization graph based on the link status data, with normal lines displayed in green and faulty lines displayed in red. At the same time, design an abnormal information reporting function, store the fault information in a relevant table and display it in real time on the page; for different operator enterprise roles, restrictions are imposed according to role permissions during data query and display; Steps for data statistics and fusion: Establish a scheduled task to count the site information that has been online on the same day, and insert the statistical information into the historical data summary table; design a wide table for real-time data to store real-time data at the current moment; in the statistical query module, the data processing layer performs a joint query process on the wide table for real-time data and the historical data summary table according to the user's filtering conditions, and associates with the query device table to obtain detailed information about base station devices and satellite devices, and displays the query results in a list. At the same time, data visualization tools and interaction functions are provided.

[0031] In this embodiment, the data acquisition layer: establishes an API connection through the communication interfaces with the satellite station and the base station, and can obtain in real time data such as the signal strength, transmission rate, and satellite orbit parameters of the satellite station, as well as information such as the number of user connections, traffic data, and device operating status of the base station. At the same time, it parses the log files generated by the satellite station and the base station, and extracts key event records, fault alarm information, etc. Using database synchronization technology, it ensures data consistency with data sources related to user services (such as user management databases, business data repositories), and obtains data such as user location information and business usage.

[0032] Perform format verification on the collected data to check whether the data conforms to the predetermined format specifications, such as whether the time format is correct and whether the data types match. Through preset rules and algorithms, perform preliminary cleaning on the data to remove obviously incorrect data, such as data values outside the reasonable range and duplicate records. For missing data, use methods such as interpolation and mean filling to supplement it to ensure data integrity.

[0033] Data processing layer: Apply data cleaning algorithms to identify and correct errors and outliers in the data. For example, use clustering analysis algorithms to find outliers in the data, and determine whether they are abnormal data and correct them. Use data integration technology to merge and correlate data from different data sources to form a unified data view. Adopt data analysis algorithms, such as statistical analysis and association rule mining, to deeply analyze the data and extract valuable information.

[0034] According to different business requirements, classify, aggregate, and transform the data. For example, classify the data according to site types (ground satellite single-site, ground satellite full-site, drone satellite full-site), and count relevant indicators for different types of sites; use aggregation functions to perform aggregation operations on the data, such as calculating the total traffic of all sites within a certain time period; through data conversion algorithms, convert the data into a format convenient for analysis, such as converting binary data to decimal data.

[0035] To meet the personalized needs of specific users, provide a custom processing logic interface. Users can perform custom calculations, filtering, sorting, etc. on the data by writing scripts or code to achieve flexible processing of the data.

[0036] Data storage layer: Design a real-time data wide table (such as BASE_NOW_INFO) to store the latest data at the current moment, including real-time status data of satellite stations and base stations, real-time service data of users, etc. The real-time data wide table adopts a columnar storage structure to improve the query efficiency and real-time update performance of data. At the same time, design a historical data summary table (such as BASE_ALL_INFO) to store the statistically summarized historical data, such as daily site traffic statistics data, monthly summary of user service usage, etc. The historical data summary table adopts a row-based storage structure, which is convenient for batch processing and analysis of data.

[0037] Regularly perform a full backup of the data and store the backup data in a storage device in a remote location to prevent local data loss. At the same time, adopt incremental backup technology to back up the newly added and modified data every day, reducing the amount of backup data and backup time. When data is lost or damaged, it can be quickly restored from the backup data to ensure the security and reliability of the data.

[0038] User interaction layer: Adopt an intuitive and easy-to-use interface design and apply responsive design technology to ensure a good user experience on different devices (such as computers, tablets, mobile phones). The interface layout is simple and clear, and the commonly used function modules (such as filtering and querying, data visualization, data export) are placed in prominent positions for easy user operation.

[0039] Provide rich data visualization tools, such as bar charts, line charts, pie charts, maps, etc., to display the data to users in an intuitive graphical way. Users can choose the appropriate visualization method according to their own needs. For example, through map visualization, display the distribution and operation status of sites in different regions, and through line charts, display the change trend of the traffic of a certain site over time.

[0040] Support multiple interaction functions, such as filtering, querying, sorting, zooming, etc. Users can select conditions such as specific time ranges, site types, affiliated units, etc. through the filtering box to query data that meets the conditions; they can sort the query results in ascending or descending order according to fields such as data update time and site importance; they can perform zoom operations on the visualization graph to view more detailed data information.

[0041] Support exporting data in formats such as Excel, CSV, PDF, etc., which is convenient for users to perform further analysis and processing in other software. When exporting data, provide data format conversion and data preprocessing functions to ensure that the exported data meets the needs of users.

[0042] As a preferred implementation manner, in the screening and querying implementation steps of step S2 in this embodiment: Specific method of S21 time filtering: Time filtering is implemented through radio buttons for real-time and interval selection. Interval selection can accurately query data for the current day. After the user selects the filtering conditions, the system updates the data display results in real time. In the filtering box area of the user interaction layer, set radio buttons for time filtering, marked as "Real-time" and "Interval" respectively. When the user selects "Real-time", the system immediately obtains the latest data from the real-time data wide table (BASE_NOW_INFO) and updates the display results in the data display area in real time. When the user selects "Interval", a time selector pops up. The user can accurately select data for the current day or select a cross-day time interval. The time selector uses a calendar control to facilitate the user to select dates, and at the same time provides a time input box where the user can select time down to hours and minutes. After the user selects the filtering conditions, the system sends a query request to the server through AJAX technology. The server constructs a query statement according to the time conditions selected by the user, queries data from the corresponding data tables, and returns the query results to the front end. After receiving the data, the front end updates the content of the data display area in real time to ensure that the user can see the data that meets the conditions in a timely manner.

[0043] Details of the S22 fuzzy search function: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, including site name, site person in charge, and equipment number, improving the accuracy and flexibility of data retrieval; The fuzzy search box uses a full-text search algorithm and supports comprehensive fuzzy matching of multiple fields (site name, site person in charge, equipment number). When the user enters keywords in the search box, the system decomposes the keywords into multiple words or character fragments and then performs matching in the relevant fields. For example, when the user enters "Chengdu Satellite Station", the system will search for records containing "Chengdu" and "Satellite Station" in the site name field, and at the same time perform fuzzy matching in the site person in charge and equipment number fields to improve the accuracy and flexibility of data retrieval. The search results are displayed in a list form in the data display area. The list shows the records with the highest matching degree with the keywords and is sorted from high to low according to the matching degree. At the same time, in each record, the matching keywords are highlighted to facilitate the user to quickly locate the key information.

[0044] Optimization Details of S23 List Display: The list display supports users to customize the sorting fields and sort according to the data update time and site importance fields; the paging function supports users to manually enter the page number to jump, and at the same time provides quick operation buttons; the list display area supports users to customize the sorting fields, and users can perform sorting operations by clicking on the column headers. When the user clicks on the "Data Update Time" column header, the system will sort the query results in ascending or descending order according to this field; when the user clicks on the "Site Importance" column header, the system will sort the query results according to the pre-set site importance scoring criteria. The paging function supports users to manually enter the page number to jump, and at the same time provides quick "First Page", "Last Page", "Previous Page", and "Next Page" operation buttons. The system performs paging processing on the query results according to the number of records displayed per page set by the user. For example, if the user sets 10 records to be displayed per page, the system will divide the query results into pages of 10 records each and display the current page number and total number of pages at the bottom of the page, facilitating users to view a large amount of data.

[0045] S24 Filter Box Linkage Mechanism: There is a linkage relationship between the filter boxes. When the user selects the city filter condition, the site type filter box will be dynamically updated according to the actual site types in the selected city, reducing invalid filter options and improving the filtering efficiency; there is a linkage relationship between the filter boxes. When the user selects the city filter condition, the system sends the information of the selected city to the server through an AJAX request. The server queries the relevant data from the database according to the actual site types of this city and returns the query results to the front end. The front end dynamically updates the options of the site type filter box according to the returned data, removing the site type options that are not relevant to the selected city, reducing invalid filter options, and improving the filtering efficiency. When the user selects other filter conditions (such as the affiliated unit), the system will also dynamically update the other filter boxes according to the selected conditions. For example, when the user selects a certain affiliated unit, the system will dynamically update the options of the city filter box and the site type filter box according to the site distribution of this affiliated unit to ensure the consistency and effectiveness of the filter conditions.

[0046] S25 Export Data Preprocessing: When exporting the list data to Excel format, the system will preprocess the exported data, such as uniformly adjusting the data format, converting the satellite traffic and user traffic data to the units according to the conversion rules specified by the front end, ensuring the standardization and usability of the exported data; S26 Screening and Querying Data Sources and Processing: The data for screening and querying comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO. Among them, BASE_NOW_INFO stores the data of satellite stations or base stations that have been online on the current day, and BASE_ALL_INFO stores the data of satellite stations or base stations that have been online except on the current day. When constructing the query statement, the data processing layer will determine whether to query from a single table or jointly query the two tables according to the time screening conditions. If real-time or daily interval data is selected, the query will mainly be from BASE_NOW_INFO. If cross-day interval data is selected, a union all operation will be performed on the two tables and then the query will be carried out, and duplicate data will be removed from the query results. The data for screening and querying comes from the real-time data wide table (BASE_NOW_INFO) and the historical data summary table (BASE_ALL_INFO). BASE_NOW_INFO stores the real-time data of satellite stations or base stations that have been online on the current day, including real-time traffic, real-time user connection numbers, etc. BASE_ALL_INFO stores the historical data of satellite stations or base stations that have been online except on the current day, as well as the historical data that has been statistically summarized, such as the average daily traffic, the total monthly user connection numbers, etc.

[0047] When constructing the query statement, the data processing layer will determine whether to query from a single table or jointly query the two tables according to the time screening conditions. If the user selects real-time or daily interval data, the query will mainly be from BASE_NOW_INFO to obtain the latest real-time data. If the user selects cross-day interval data, a union all operation will be performed on the two tables and then the query will be carried out, and duplicate data will be removed from the query results. During the query process, the system will further screen and filter the query results according to other screening conditions selected by the user (such as city, site type, affiliated unit) to ensure the accuracy and integrity of the query results.

[0048] S27 Multi-dimensional Screening Logic: When the user selects multiple screening dimensions at the same time, the query statement constructed by the data processing layer will combine the screening conditions of each dimension through logical operators (such as AND, OR). For example, if the user selects the city as "Chengdu" and the site type as "ground satellite single site", the query statement will use the AND operator to combine these two conditions to retrieve the relevant data that belongs to both Chengdu and is a ground satellite single site. If the user selects the city as "Chengdu" or "Chongqing", the query statement will use the OR operator to combine these two conditions to retrieve all the relevant data that belongs to Chengdu or Chongqing.

[0049] Support complex combinations of conditions. Users can build complex query logics by selecting filtering conditions multiple times. For example, users can select the city as "Chengdu" or "Chongqing", the site type as "ground satellite single site" and the affiliated unit as "China Mobile". The data processing layer will construct corresponding query statements based on these conditions and accurately query the data that meets the conditions from the database.

[0050] S28 Data Structure Foundation: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE. Among them, ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain relevant information about the combined station; the historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically processed historical data; when performing screening queries, the data processing layer constructs query statements based on the meanings and association relationships of the fields in each table and extracts the data that meets the conditions from these tables. In this embodiment, the real-time data wide table (BASE_NOW_INFO) contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, INFO_TYPE, etc. Among them, ID is the primary key, generated using UUID (Universally Unique Identifier) to ensure the uniqueness of each record; EQUIPMENT_REL_ID is used to associate with the equipment relationship table, and through this field, relevant information about the combined station can be obtained, such as the connection relationships and equipment parameters of each device in the combined station; the BASE_NAME field stores the site name for easy user identification and query; the INFO_TYPE field is used to identify the type of data, such as traffic data, user connection count data, etc.

[0051] The historical data summary table (BASE_ALL_INFO) is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically processed historical data. In addition to the associated fields, it also includes time fields (such as statistical date, statistical month), site-related fields (such as site name, site type), statistical index fields (such as total satellite traffic, total user service duration), etc. Through the design of these fields, it is convenient to query, statistically analyze, and analyze historical data.

[0052] During the screening query, the data processing layer constructs a query statement based on the meanings of the fields in each table and the associated relationships. For example, when a user queries the traffic data of a certain site within a certain time period, the data processing layer will extract the qualified data from the real-time data wide table and the historical data summary table according to the site name selected by the user (matched through the BASE_NAME field) and the time condition (matched through the time field), and obtain the relevant equipment information and combined station information through the associated fields (EQUIPMENT_REL_ID and equipment_rel_id).

[0053] S29 Processing of screening query results: Before the query results are displayed in a list, the data processing layer will sort the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by site name, the data processing layer will call the sorting function of the database (such as the ORDER BY statement in MySQL) to sort the query result set in ascending order according to the BASE_NAME field; if the user selects to sort in descending order by satellite traffic, it will be sorted in descending order according to the STATION_FLOW field. During the sorting process, the system will consider the data type and sorting direction to ensure the accuracy and reasonableness of the sorting result.

[0054] Further optimization processing is performed on the sorted query results, such as formatting the display of the data, adding data descriptions and annotations, etc. In the data display area, important data fields are displayed in a prominent manner for the convenience of users to view and analyze. At the same time, data download and printing functions are provided, and users can download the query results to the local in formats such as Excel and PDF, or directly perform printing operations.

[0055] As a preferred implementation manner, in this embodiment, in step S3 of the core network link monitoring step: S31 Expansion of abnormal information broadcast: In addition to displaying the interruption time and connection time, the abnormal information broadcast area will also display detailed information such as the fault type (such as network congestion, link interruption, signal interference, etc.) and the affected site range (displaying the names and location information of the affected sites through map visualization or list). When a network congestion fault occurs, information such as the location of the congested link and the degree of congestion (such as the proportion of traffic exceeding the threshold) will be displayed; when a link interruption fault occurs, information such as the start and end points of the interrupted link and the estimated recovery time will be displayed.

[0056] By displaying this detailed information, it helps the administrator quickly locate the fault point, analyze the cause of the fault, and take corresponding solutions. For example, when the administrator sees the affected site range and the fault type, they can quickly determine whether it is a base station equipment fault in a certain area or a core network link problem, and then arrange technicians for targeted repair and handling.

[0057] S32 Permission Control Refinement: The permissions of different operation enterprise roles are managed through the permission tables associated with the roles. The permission tables clearly define the scope of link data that each role can view, including links of different operators (such as Mobile, Unicom, Telecom), links in different regions (such as North China, South China), links of different types (such as backbone links, access links), etc. For example, the Mobile administrator role is granted the permission to view all Mobile-related link data in the permission table, but only the permission to view some publicly available link data of other operators.

[0058] The system automatically matches the corresponding permissions according to the user role for data display. When a user logs in to the system, the system reads the user's role information and then queries the permission data corresponding to that role from the permission table. During the data display process, the system filters out the link data that the user has no permission to view according to the permission restrictions, ensuring the security and privacy of the data.

[0059] S33 Visualization Graphic Interaction Function: The visualization graphic supports user click operations. When the user clicks on a certain link, the system pops up a detailed information window to display the real-time traffic, bandwidth utilization rate and other detailed data of that link; the visualization graphic is drawn using HTML5-based Canvas or SVG technology to ensure normal display on different browsers and devices. In the graphic, normal lines are displayed as green lines, and the thickness and color depth of the lines can be dynamically adjusted according to the importance level and traffic volume of the link; faulty lines are displayed as red lines and flash to remind the administrator to pay attention.

[0060] It supports user click operations. When the user clicks on a certain link, the system captures the click event through the JavaScript event listening mechanism and sends the link identification information to the server through an AJAX request. The server queries the real-time traffic, bandwidth utilization rate, latency and other detailed data of that link from the database according to the link identification information and returns the query results to the front end. After receiving the data, the front end pops up a detailed information window to display the detailed data of that link. The detailed information window is displayed in the form of a modal box without blocking other page content, facilitating user viewing and operation. S34 Link Status Data Update Frequency: The scheduled task is set to call the core network firewall interface every two minutes to obtain the link status data. Through the task scheduling tools of the operating system (such as Cron in Linux or Task Scheduler in Windows), the execution time and frequency of the scheduled task are set. The scheduled task runs in the background without affecting other functions of the system and user operations.

[0061] When the scheduled task is executed, a connection is established with the core network firewall through the API interface to obtain link status data. The obtained data is stored in the link monitoring table (link_info), and the status field in the table is updated according to the link status. If the link status changes, such as from normal to faulty or from faulty to normal, the system will promptly update the records in the database and trigger the update of the abnormal information broadcast and the visualization graph to ensure that the administrator can promptly understand the changes in the link status.

[0062] 35 Fault information storage and query: Fault information is stored in the link_info_notice table. In addition to recording fault information (such as fault time, fault type, fault description), this table is also associated with the primary key ID of the link monitoring table (link_info). By associating the primary key ID, it is convenient for the administrator to quickly trace back to the corresponding link status data when querying fault information and understand the detailed situation of the link when the fault occurred.

[0063] The system provides a function to query fault information according to conditions such as fault time and fault type. On the query interface, the user can select the time range of the fault occurrence through the date picker and select the fault type from the drop-down menu, such as network congestion, link interruption, etc. After receiving the user's query request, the system retrieves data in the link_info_notice table and displays the qualified fault information to the user in the form of a list. Each fault record in the list details the fault time, fault type, fault description, and associated link identifier and other information, facilitating the administrator to analyze and summarize historical faults, find the laws and trends of fault occurrence, and provide a basis for network optimization and fault prevention.

[0064] S36 Link status judgment and display logic: After obtaining the link status data, the system compares and judges the link status with the preset normal status threshold; if the real-time traffic and delay indicators of the link exceed the normal range, it is determined to be in a faulty state; in the visualization graph displayed on the page, the faulty line is not only displayed in red but also flashes to remind the administrator to pay attention; at the same time, in the abnormal information broadcast area, in addition to the text information, a sound alarm will also be used to notify the administrator, and the sound alarm can be set with different volumes and frequencies according to the severity of the fault; S37 Data isolation for different role permissions: For different operation enterprise roles, the system performs data isolation at the database query stage; including when the mobile administrator logs in, the system adds restrictive conditions to the SQL statement for querying link data to only obtain link data related to mobile, ensuring that the data of other enterprises will not be misqueried or leaked, and guaranteeing the security and privacy of the data; S38 Link Monitoring Table Structure and Data Storage: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID is used as the primary key, which is generated as an auto-incrementing integer or UUID to uniquely identify each link monitoring record; link_type is used to distinguish links of different operators, for example, 1 represents Mobile, 2 represents China Unicom, 3 represents China Telecom, etc.; end_time records the link interruption time and is stored in timestamp or standard date and time format; recovery_time records the recovery time, also stored in timestamp or standard date and time format; type represents the link status, 0 for fault and 1 for normal.

[0065] The link status data obtained by the scheduled task is stored according to these fields. After obtaining the link status data, first determine whether the link status has changed. If the link status changes from normal to faulty, update the type field to 0 and record the end_time; if the link status recovers from faulty to normal, update the type field to 1 and record the recovery_time. In this way, accurate data support is provided for subsequent status judgment, historical query, and visualization display.

[0066] S39 Abnormal Information Broadcasting Table Structure and Data Processing: The link_info_notice table on which the abnormal information broadcasting depends stores the detailed information when a fault occurs through association with the link_info table. In addition to recording information such as the fault time, fault type, and affected scope, the link_info_notice table also contains a foreign key field that associates with the primary key ID of the link_info table to establish the relationship between the two tables.

[0067] When the link status is abnormal, the system inserts the fault-related information into the link_info_notice table. For example, when it is detected that a certain link has an interruption fault, information such as the fault time, fault type (link interruption), and the scope of affected sites is inserted into the table. At the same time, in the abnormal information broadcasting area of the page, the data in this table is read for real-time display. The system uses real-time data push technology, such as WebSocket. When a new fault record is inserted into the link_info_notice table, the information is immediately pushed to the front-end page to ensure that the administrator can obtain the fault information in a timely manner.

[0068] As a preferred implementation manner, in step S4 of this embodiment, the data statistics and fusion step: S41 Statistical Information Calculation Details: When calculating the statistical information of the sites that went online on the same day, key metrics such as satellite traffic and service duration are accurately calculated. Among them, the satellite traffic is accumulated based on the traffic data in different time periods, and the service duration is calculated according to the actual start and end times of the site's service. S42 Joint Query Optimization: During joint queries, the data processing layer intelligently selects query strategies according to the user's filtering conditions. If the filtering conditions involve a large time range, such as querying the site data for the past month, it is preferred to query from the historical data summary table (BASE_ALL_INFO) because this table stores the historical data that has been statistically summarized and has a high query efficiency. If it involves real-time data, such as querying the real-time status of the current site, the focus is on querying the real-time data wide table (BASE_NOW_INFO) to obtain the latest real-time data. During the query process, the system dynamically adjusts the query strategy according to factors such as the data volume and the complexity of the query conditions to improve the query efficiency.

[0069] S43 Visualization Display Expansion: The data visualization tool supports multiple graph display methods. In addition to bar charts and pie charts, it also includes line charts and radar charts. Users can select appropriate graphs to display data according to their needs, and the graphs can be interactively operated, including zooming in, zooming out, and viewing data details. S44 Scheduled Task Execution Logic: The scheduled task is executed at 1:00 am every night and is set through the task scheduling tool of the operating system (such as Cron in Linux or Task Scheduler in Windows). Before the task is executed, the system will perform a series of preparatory work, such as checking the database connection and cleaning up temporary data.

[0070] Statistical information of the sites that went online on the same day is retrieved from the original data table (BASE_STATION_DATA). During the statistical process, it is first determined whether a site went online on the same day by comparing the timestamp or date field. Then, the data of the eligible sites is extracted and calculated, such as calculating metrics like satellite traffic and service duration. The calculated statistical information is inserted into the historical data summary table (BASE_ALL_INFO) to ensure the integrity and accuracy of the historical data.

[0071] S45 Associated Device Information Query Optimization: When retrieving the detailed information of base station devices and satellite devices through an associated query of the device table (EQUIPMENT_INFO), a caching mechanism is adopted. Memory caching technologies such as Redis are used to cache the frequently queried device information in memory. When the same device information is queried again, it is first checked whether the information exists in the cache. If it exists, it is directly retrieved from the cache, reducing the number of database queries and improving the system performance. When the device information changes, the data in the cache is updated in a timely manner to ensure the consistency of the cached data.

[0072] S46 Optimization of Statistical Index Calculation: When calculating satellite traffic statistics, for different types of sites, including ground satellite single-site, ground satellite full-site, and drone satellite full-site, separate calculations and statistics are performed. For each type of site, an independent statistical model and calculation method are established, and accurate traffic statistics are carried out considering the characteristics and business requirements of different types of sites. For example, for drone satellite full-sites, due to the differences in their mobility and signal stability, different traffic statistical algorithms and data processing methods are adopted.

[0073] S47 Joint Query Data Integration: When performing a joint query on the real-time data wide table (BASE_NOW_INFO) and the historical data summary table (BASE_ALL_INFO), the data processing layer integrates the data in the two tables. For duplicate fields of the same site, the latest data is used for display. For example, for the traffic data of a site, if there are records in both the real-time data wide table and the historical data summary table, the latest data in the real-time data wide table is used. For fields unique to different tables, they are simultaneously displayed in the query result to provide users with more comprehensive data information. For example, the real-time data wide table may contain the number of real-time online users, and the historical data summary table contains the cumulative number of online users. Both fields will be displayed in the query result to facilitate users' comparison and analysis.

[0074] S48 Structure and Data Insertion of Historical Data Summary Table: The historical data summary table (BASE_ALL_INFO) obtains the information of the sites launched on the same day from the original data table (BASE_STATION_DATA) through a scheduled task at 1:00 am every night for statistics. In addition to being associated with other tables through equipment_rel_id, this table also contains time fields (such as statistical date, statistical month), site-related fields (such as site name, site type), statistical index fields (such as total satellite traffic, total user service duration), etc. Through the design of these fields, the consistency and traceability of the data are ensured.

[0075] During statistics, the data of the same day is filtered based on the site's launch time, and indicators such as satellite traffic and service duration are calculated. The calculation results are inserted into the BASE_ALL_INFO table. Before inserting the data, the integrity and accuracy of the data are checked to avoid duplicate insertion and incorrect data insertion. At the same time, relevant indexes and statistical information are updated for subsequent query and analysis.

[0076] S49 Real-time Data Wide Table and Equipment Table Association Query: The real-time data wide table (BASE_NOW_INFO) is associated with the equipment table (EQUIPMENT_INFO) through the site_id field. In the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed equipment information such as equipment name, equipment model, and equipment status from EQUIPMENT_INFO through the associated field site_id. Through this association query, the query results are enriched, providing users with a more detailed data display. During the query process, optimized SQL query statements are used to improve the query efficiency and ensure that users can quickly obtain the required data.

[0077] Such as Figure 2 shown, the second aspect of the present invention provides a data monitoring and statistical interaction system for a network-wide public network base station based on satellite communication, including: Data acquisition layer: Used to collect raw data from satellite stations, base stations, and user service-related data sources, and use API interface calls, log file parsing, and database synchronization technologies to verify and preprocess the collected data; Data processing layer: Connected to the data acquisition layer, cleans, integrates, and analyzes the collected data, uses algorithms to identify and correct data errors and outliers, classifies, aggregates, and transforms the data according to business requirements, and supports custom processing logic; Data storage layer: Connected to the data processing layer, designed with a real-time data wide table and a historical data summary table for storing data, and having data backup and recovery functions; User interaction layer: Connected to the data storage layer, provides an intuitive and easy-to-use interface, has data visualization tools and interaction functions, supports data export, receives user operation instructions and transfers them to other layers; Filtering and query module: Set in the user interaction layer, includes multi-dimensional filtering boxes and fuzzy search boxes, receives user filtering conditions and triggers the data processing layer to query data from the database, displays the query results in a list, and provides paging and sorting functions; Core network link monitoring module: Includes a timing task unit, a data storage unit, and a display unit. The timing task unit periodically calls the core network firewall interface to obtain link status data; the data storage unit stores the data in the link monitoring table and records the link interruption time and recovery time; the display unit draws a visualization graph according to the link status data to display the normal or faulty status, designs an abnormal information broadcast function, and restricts the data display permissions for different operator enterprise roles; Data Statistics and Fusion Module: It includes a Timed Task Sub-module, a Data Storage Sub-module, and a Query and Display Sub-module; the Timed Task Sub-module establishes a timed task to count the site information that went online on the same day and inserts it into the historical data summary table; the Data Storage Sub-module designs a real-time data wide table to store real-time data; the Query and Display Sub-module jointly queries the real-time data wide table and the historical data summary table according to the user's filtering conditions, and associates with the device table to obtain the detailed information of base station devices and satellite devices, and displays the results in a list and provides visualization tools and interactive functions.

[0078] Furthermore, it also includes a Time Filtering Component: The time filtering component in the filtering query module realizes real-time and interval selection through radio buttons. The interval selection can be accurate to the data of the query day. And after the user selects the filtering conditions, the system updates the data display results in real time; Fuzzy Search Function Module: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, covering fields such as site name, site person in charge, and device number, improving the accuracy and flexibility of data retrieval; List Display Optimization Module: The list display module supports users to customize the sorting fields and can sort according to fields such as data update time and site importance level; the paging function supports users to manually enter the page number to jump, and at the same time provides quick operation buttons; Filter Box Linkage Module: There is a linkage mechanism between each filter box. When the user selects the city filtering condition, the site type filter box will be dynamically updated according to the actual site types in the selected city; Export Data Preprocessing Module: When exporting the list data to Excel format, the system has an export data preprocessing module to uniformly adjust the data format and convert the satellite traffic and user traffic data according to the conversion rules specified by the front end; Filtering Query Data Source and Processing Module: The data of the filtering query module comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO; the data source judgment and processing module is provided in the data processing layer. When constructing the query statement, it judges whether to query from a single table or jointly query two tables according to the time filtering conditions; if real-time or same-day interval data is selected, it mainly queries from BASE_NOW_INFO; if cross-day interval data is selected, it performs a unionall operation on the two tables and then queries, and removes duplicate data from the query results; Multi-dimensional Filtering Logic Module: When the user selects multiple filtering dimensions at the same time, the multi-dimensional filtering logic module in the data processing layer combines the filtering conditions of each dimension through logical operators to construct a query statement.

[0079] Data Structure Association Module: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE. Among them, ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain information related to the combined station; the historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically historical data. The filtering and querying module in the data processing layer constructs a query statement based on the meanings and association relationships of the fields in each table, and extracts the data that meets the conditions from these tables; Filtering and Query Result Processing Module: Before the query results are displayed in a list, the filtering and query result processing module in the data processing layer sorts the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by station name, the sorting function of the database is called to sort the query result set in ascending order according to the BASE_NAME field; if the user selects to sort in descending order by satellite traffic, the sorting is performed in descending order according to the STATION_FLOW field to ensure that the display order meets the user's requirements.

[0080] Furthermore, it also includes an Abnormal Information Broadcasting Extension Module: The abnormal information broadcasting extension module of the core network link monitoring module, in addition to displaying the interruption time and connection time, also shows the fault type and detailed information about the affected station range, helping the administrator quickly locate and solve problems; Permission Control Refinement Module: The permissions of different operation enterprise roles are managed through the permission tables associated with the roles. The system is equipped with a permission control refinement module that automatically matches the corresponding permissions according to the user role for data display; Visualization Graphic Interaction Function Module: The visualization graphic supports user click operations. When the user clicks on a certain link, the visualization graphic interaction function module pops up a detailed information window to display the real-time traffic and bandwidth utilization rate detailed data of the link; Link Status Data Update Frequency Module: The timing task unit is equipped with a link status data update frequency module, which is set to call the core network firewall interface every two minutes to obtain the link status data to ensure the real-time nature of the data and facilitate the timely discovery of network failures; Fault Information Storage and Query Module: The fault information is stored in the link_info_notice table. In addition to recording the fault information, this table is also associated with the primary key ID of the link monitoring table (link_info); the system is equipped with a fault information storage and query module, which enables the administrator to quickly trace back to the corresponding link status data when querying the fault information; at the same time, it provides the function of querying the fault information according to the fault time and fault type conditions, facilitating the administrator to analyze and summarize historical faults; Link Status Judgment and Display Logic Module: After obtaining the link status data, the system's link status judgment and display logic module compares the link status with the preset normal status threshold. If the real-time traffic and delay metrics of the link exceed the normal range, it is determined to be in a fault state. In the visual graph displayed on the page, the faulty line is not only shown in red but also flashes to alert the administrator. At the same time, in the abnormal information broadcast area, in addition to the text information, the administrator is notified by a sound alarm, and the sound alarm can be set with different volumes and frequencies according to the severity of the fault; Data Isolation Module for Different Role Permissions: For different operation enterprise roles, the system has a data isolation module for different role permissions during the database query stage for data isolation; Link Monitoring Table Structure and Data Storage Module: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID uniquely identifies each link monitoring record as the primary key, link_type is used to distinguish links of different operators, end_time records the link interruption time, recovery_time records the recovery time, and type represents the link status. The link status data obtained by the scheduled task is stored according to these fields, providing data support for subsequent status judgment, historical query, and visual display; Abnormal Information Broadcast Table Structure and Data Processing Module: The link_info_notice table relied on for abnormal information broadcast stores the detailed information when a fault occurs through association with the link_info table. The system has an abnormal information broadcast table structure and data processing module. When the link status is abnormal, the fault-related information is inserted into the link_info_notice table, and at the same time, in the abnormal information broadcast area on the page, it is displayed in real time by reading the data in this table to ensure that the administrator can obtain the fault information in a timely manner; Real-time Monitoring Support and Guarantee Module: In the construction of the real-time monitoring system for all website nodes, the core network link monitoring data is a key part, reflecting the network quality in real time; once a link fails, the system quickly notifies relevant personnel through abnormal information broadcast. Combining with permission management, personnel of different roles obtain corresponding data, providing a real-time network status basis for ensuring smooth network communication during natural disasters and major events, so as to adjust communication strategies in a timely manner.

[0081] Furthermore, it also includes a statistical information calculation details module: When the scheduled task sub-module of the data statistics integration module counts the site information that went online on the same day, there is a statistical information calculation details module to accurately calculate key metrics such as satellite traffic and service duration. Among them, the satellite traffic is accumulated based on the traffic data in different time periods, and the service duration is calculated according to the actual service start and end times of the site; Union Query Optimization Module: The query display sub-module is equipped with a union query optimization module. During union queries, the data processing layer intelligently selects query strategies based on user filtering conditions. If the filtering conditions involve a large time range, it preferentially queries from the historical data summary table; if real-time data is involved, it focuses on querying the real-time data wide table to improve query efficiency; Visualization Display Expansion Module: The data visualization tool supports multiple graph display methods. In addition to bar charts and pie charts, it also includes line charts and radar charts. The system is equipped with a visualization display expansion module. Users can select appropriate graphs to display data according to their needs, and the graphs can be interacted with; Scheduled Task Execution Logic Module: The scheduled task sub-module is equipped with a scheduled task execution logic module, which executes at 1:00 am every night. It counts the information of the sites that went online on the same day from the original data table BASE_STATION_DATA. During the counting process, it first determines whether a site went online on the same day based on the site's online time, and then extracts and calculates the data of the sites that meet the conditions, and inserts the calculated statistical information into the historical data summary table BASE_ALL_INFO.

[0082] Associated Device Information Query Optimization Module: When querying the detailed information of base station devices and satellite devices from the associated query device table EQUIPMENT_INFO, the query display sub-module adopts a caching mechanism and is equipped with an associated device information query optimization module. For frequently queried device information, it caches it in memory. When querying the same device information again, it directly obtains it from the cache, reducing the number of database queries and improving system performance; Statistical Index Calculation Optimization Module: When calculating satellite traffic, it calculates and statistically analyzes different types of sites, including ground satellite single sites, ground satellite full sites, and drone satellite full sites respectively; Union Query Data Integration Module: When performing a union query on the real-time data wide table and the historical data summary table, the query display sub-module is equipped with a union query data integration module, which integrates the data in the two tables; for duplicate fields of the same site, it displays the latest data as the standard; for unique fields in different tables, they are displayed in the query results at the same time, providing users with more comprehensive data information; for example, the real-time data wide table may contain the number of real-time online users, and the historical data summary table contains the cumulative number of online users, and both fields will be displayed in the query results at the same time; Historical Data Summary Table Structure and Data Insertion Module: The historical data summary table BASE_ALL_INFO obtains the information of the online sites on the current day from the original data table BASE_STATION_DATA through a scheduled task at 1:00 am every night for statistics. The system is equipped with a historical data summary table structure and data insertion module. During statistics, the data of the current day is filtered based on the online time of the sites, and the satellite traffic and service duration indicators are calculated. The calculation results are inserted into the BASE_ALL_INFO table. This table is associated with other tables through equipment_rel_id to ensure data consistency and traceability. Real-time Data Wide Table and Equipment Table Association Query Module: The real-time data wide table BASE_NOW_INFO is associated with the equipment table EQUIPMENT_INFO through the site_id field. The query display sub-module is equipped with a real-time data wide table and equipment table association query module. In the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed equipment information from EQUIPMENT_INFO through the associated fields to enrich the query results and provide more detailed data display for users.

[0083] Multi-dimensional Cross-analysis Application Module: During natural disasters or major events, the system utilizes the data statistics and fusion function and is equipped with a multi-dimensional cross-analysis application module to conduct multi-dimensional cross-analysis on satellite and base station data. Comprehensive analysis is carried out in combination with the time dimension including before, during, and after the disaster, the regional dimension including the core disaster area, the surrounding affected area, and the site type dimension including ground satellite single-site and ground satellite whole-site to generate refined statistical reports and provide comprehensive data support for command and dispatch.

[0084] This patent is a data monitoring and statistical interaction method and system for all-network public network base stations based on satellite communication, which has many significant beneficial effects, effectively solves many problems existing in the prior art, and brings innovation and breakthroughs to data management and analysis in the communication field: Improve Data Query and Management Efficiency: Set multi-dimensional filtering boxes and fuzzy query functions in the user interaction layer, covering dimensions such as time, city, site type, and affiliated unit, greatly improving the efficiency and accuracy of data retrieval. Users can quickly locate the required data, reduce operation steps, and lower operation complexity. At the same time, the optimized list display has functions such as paging, sorting, and field customization, meeting the data viewing needs of different users in different scenarios, enhancing the flexibility and convenience of data query, and making data management more efficient.

[0085] Enhance the network status monitoring ability: By calling the core network firewall interface through a scheduled task to obtain link status data, realize the real-time update and visualization display of the core network link status. The normal lines and faulty lines are visually presented in different colors, and abnormal information is broadcast in real time to help administrators discover and locate network faults in a timely manner. Set permission restrictions for different operator enterprise roles to ensure data security and privacy, guarantee the professionalism and accuracy of network management, and improve the reliability and stability of network operation.

[0086] Optimize the data statistics and analysis effect: Establish a scheduled task to count the information of the sites launched on the same day, and combine the real-time data wide table and the historical data summary table to achieve the comprehensive statistics and integrated display of site data. This data statistics and integration technology enables users to obtain more accurate and comprehensive data analysis results. Whether analyzing the short-term operation status of the site or studying the long-term development trend, strong data support can be obtained, providing a basis for scientific decision-making and improving the reasonable allocation ability of communication resources.

[0087] Enhance the system automation and intelligence level: Set a scheduled task to automatically process historical data and integrate it with real-time data, reduce manual intervention, lower labor costs, and at the same time ensure the timeliness and accuracy of data. The system can automatically run according to preset rules, improve the efficiency and stability of data processing, reflect the automation and intelligence characteristics of the system, and provide users with more efficient data services.

[0088] Meet diverse data analysis requirements: The data processing layer designs flexible data analysis and processing logics, supporting users to customize data processing methods. In the face of complex data analysis scenarios, the system can be customized according to different user requirements to provide personalized data services, meet the diverse business requirements in the communication field, and enhance the adaptability and competitiveness of the system.

[0089] Ensure data security and stability: The system designs a reasonable data storage structure to effectively manage real-time data and historical data, improve storage efficiency, and ensure the convenience and accuracy of data calls. At the same time, perfect security guarantee strategies, including multiple measures such as data encryption, identity authentication, and virus protection, ensure the security and integrity of data during transmission and storage, providing a solid guarantee for the stable operation of the system.

[0090] Although the embodiments of the present invention have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present invention.

Claims

1. A data monitoring and statistical interaction method for a full-network-communication public network base station based on satellite communication, characterized in that: It includes the following steps: S1 Build a system architecture including a data acquisition layer, a data processing layer, a data storage layer, and a user interaction layer; The data acquisition layer collects raw data from satellite stations, base stations, and user service-related data sources, and uses API interface calls, log file parsing, and database synchronization to verify and preprocess the collected data; S2 Set up filtering boxes and fuzzy search boxes covering dimensions such as time, city, site type, and affiliated unit in the user interaction layer; After the user selects the filtering conditions, the data processing layer constructs a query statement accordingly, queries data from the database, and displays the query results in a list; S3 Set up a scheduled task to call the core network firewall interface to obtain link status data; store the obtained data in a link monitoring table, update the status field in the table according to the link status, and record the link interruption time and recovery time; In the page display, draw a visualization graph based on the link status data; S4 Establish a scheduled task to count the site information that has been online on the same day, and insert the statistical information into the historical data summary table; Design a real-time data wide table to store real-time data at the current moment; In the statistical query module, the data processing layer performs a combined query process on the real-time data wide table and the historical data summary table according to the user's filtering conditions, and associates with the query device table to obtain the detailed information of base station devices and satellite devices, displays the query results in a list, and provides data visualization tools and interaction functions at the same time.

2. The method according to claim 1, wherein; In the filtering and query implementation steps of step S2: S21 Specific method of time filtering: Time filtering is implemented through radio buttons for real-time and interval selection. The interval selection can be accurate to query the data of the current day, and after the user selects the filtering conditions, the system updates the data display results in real time; S22 Details of the fuzzy search function: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, including site name, site person in charge, and device number, improving the accuracy and flexibility of data retrieval; S23 Optimization details of list display: The list display supports users to customize the sorting fields and sort according to the data update time and site importance fields; The paging function supports users to manually enter the page number to jump, and provides quick operation buttons at the same time; S24 Linkage mechanism of filtering boxes: There is a linkage relationship between the filtering boxes. When the user selects the city filtering condition, the site type filtering box will be dynamically updated according to the actual site types in the selected city, reducing invalid filtering options and improving the filtering efficiency; S25 Preprocessing of exported data: When exporting list data to Excel format, the system will preprocess the exported data, such as uniformly adjusting the data format, converting the satellite traffic and user traffic data according to the conversion rules specified by the front end to ensure the standardization and usability of the exported data; S26 Screening and Querying Data Sources and Processing: The data for screening and querying comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO. Among them, BASE_NOW_INFO stores the data of satellite stations or base stations that have been online on the current day, and BASE_ALL_INFO stores the data of satellite stations or base stations that have been online except on the current day. When constructing the query statement, the data processing layer will determine whether to query from a single table or jointly query two tables according to the time screening conditions. If real-time or daily interval data is selected, the query will mainly be from BASE_NOW_INFO. If cross-day interval data is selected, a union all operation will be performed on the two tables and then the query will be executed, and duplicate data will be removed from the query results. S27 Multi-dimensional Screening Logic: When the user selects multiple screening dimensions at the same time, the query statement constructed by the data processing layer will combine the screening conditions of each dimension through logical operators. S28 Data Structure Foundation: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE. Among them, ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain information related to combined stations. The historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically processed historical data. When performing screening and querying, the data processing layer constructs the query statement based on the meanings and association relationships of the fields in each table and extracts the data that meets the conditions from these tables. S29 Processing of Screening Query Results: Before the query results are displayed in a list, the data processing layer will sort the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by site name, the data processing layer will call the sorting function of the database to sort the query result set in ascending order according to the BASE_NAME field. If the user selects to sort in descending order by satellite traffic, the sorting will be performed in descending order according to the STATION_FLOW field to ensure that the display order meets the user's requirements.

3. The method according to claim 1, wherein: In step S3, the core network link monitoring step: S31 Expansion of Abnormal Information Broadcasting: In addition to displaying the interruption time and connection time, the abnormal information broadcasting also includes the fault type and detailed information about the affected site range, which helps the administrator quickly locate and solve problems. S32 Refinement of Permission Control: The permissions of different operation enterprise roles are managed through the permission tables associated with the roles. The permission tables clearly define the range of link data that each role can view, and the system automatically matches the corresponding permissions according to the user role for data display. S33 Visualization Graphic Interaction Function: The visualization graphic supports user click operations. When the user clicks on a certain link, the system pops up a detailed information window to display the real-time traffic and bandwidth utilization rate detailed data of the link. S34 Link State Data Update Frequency: The scheduled task is set to call the core network firewall interface every two minutes to obtain link state data, ensuring the real-time nature of the data for timely detection of network failures. S35 Fault Information Storage and Query: Fault information is stored in the link_info_notice table. In addition to recording fault information, this table is associated with the primary key ID of the link monitoring table link_info, facilitating administrators to quickly trace the corresponding link state data when querying fault information. At the same time, the system provides a function to query fault information based on conditions such as fault time and fault type, facilitating administrators to analyze and summarize historical faults. S36 Link State Judgment and Display Logic: After obtaining the link state data, the system compares and judges the link state with the preset normal state threshold. If the real-time traffic and delay metrics of the link exceed the normal range, it is determined to be in a fault state. In the visual graph displayed on the page, the faulty line is not only shown in red but also flashes to alert the administrator. At the same time, in the abnormal information broadcast area, in addition to text information, an audible alarm is used to notify the administrator, and the volume and frequency of the audible alarm can be set according to the severity of the fault. S37 Data Isolation for Different Role Permissions: For different operation enterprise roles, the system performs data isolation at the database query stage. When a mobile administrator logs in, the system adds restrictive conditions to the SQL statement for querying link data to obtain only link data related to mobile, ensuring that data of other enterprises will not be misqueried or leaked, and safeguarding the security and privacy of the data. S38 Structure of the Link Monitoring Table and Data Storage: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID uniquely identifies each link monitoring record as the primary key. link_type is used to distinguish links of different operators. end_time records the link interruption time, recovery_time records the recovery time, and type indicates the link state, where 0 represents a fault and 1 represents normal. The link state data obtained by the scheduled task is stored according to these fields, providing data support for subsequent state judgment, historical query, and visual display. S39 Structure of the Abnormal Information Broadcast Table and Data Processing: The link_info_notice table on which the abnormal information broadcast depends stores detailed information at the time of fault occurrence through association with the link_info table. When the link state is abnormal, the system inserts fault-related information, including fault time, fault type, and affected scope, into the link_info_notice table. At the same time, in the abnormal information broadcast area on the page, the data in this table is read for real-time display to ensure that administrators can obtain fault information in a timely manner.

4. The method according to claim 1, wherein: In step S4, the data statistics and fusion step: S41 Statistical Information Calculation Details: When calculating the statistical information of the sites that went online on the same day, key indicators such as satellite traffic and service duration are accurately calculated. Among them, the satellite traffic is accumulated according to the traffic data in different time periods, and the service duration is calculated according to the actual start and end times of the site's service; S42 Joint Query Optimization: During joint queries, the data processing layer intelligently selects query strategies according to the user's filtering conditions. If the filtering conditions involve a large time range, it preferentially queries from the historical data summary table; if it involves real-time data, it focuses on querying the real-time data wide table to improve query efficiency. S43 Visualization Display Expansion: The data visualization tool supports multiple graph display methods. In addition to bar charts and pie charts, it also includes line charts and radar charts. Users can select appropriate graphs to display data according to their needs, and the graphs can be interactively operated, including zooming in, zooming out, and viewing data details; S44 Scheduled Task Execution Logic: The scheduled task is executed at 1:00 am every night. It counts the information of the sites that went online on the same day from the original data table BASE_STATION_DATA. During the counting process, it first determines whether a site went online on the same day according to the site's online time, and then extracts and calculates the data of the sites that meet the conditions, and inserts the calculated statistical information into the historical data summary table BASE_ALL_INFO; S45 Associated Device Information Query Optimization: When querying the detailed information of base station devices and satellite devices by associating and querying the device table EQUIPMENT_INFO, a caching mechanism is adopted. For frequently queried device information, it is cached in memory. When the same device information is queried again, it is directly obtained from the cache, reducing the number of database queries and improving the system performance; S46 Statistical Index Calculation Optimization: When calculating satellite traffic, for different types of sites, including one or more of single-site ground satellites, all-site ground satellites, and all-site drone satellites, calculations and statistics are carried out separately; S47 Joint Query Data Integration: When jointly querying the real-time data wide table and the historical data summary table, the data processing layer will integrate the data in the two tables. For duplicate fields of the same site, the latest data is used for display; for unique fields in different tables, they are simultaneously displayed in the query results to provide users with more comprehensive data information; For example, the real-time data wide table may include the number of real-time online users, and the historical data summary table includes the cumulative number of online users. These two fields will be simultaneously displayed in the query results; S48 Structure and Data Insertion of the Historical Data Summary Table: The historical data summary table BASE_ALL_INFO obtains the information of the sites that went online on the same day from the original data table BASE_STATION_DATA through a scheduled task at 1:00 am every night for statistics; during the statistics, the data of the same day is filtered according to the site's online time, and the satellite traffic and service duration indicators are calculated, and the calculation results are inserted into the BASE_ALL_INFO table; this table is associated with other tables through equipment_rel_id to ensure data consistency and traceability; S49 Real-time Data Wide Table and Equipment Table Association Query: The real-time data wide table BASE_NOW_INFO is associated with the equipment table EQUIPMENT_INFO through the site_id field; in the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed equipment information from EQUIPMENT_INFO through the associated field; including the equipment name and model, enriching the query results and providing users with more detailed data display.

5. A data monitoring and statistical interaction system for a full-network-communication public network base station based on satellite communication, characterized in that, Including: Data Acquisition Layer: Used to collect raw data from satellite stations, base stations, and user service-related data sources, and use API interface calls, log file parsing, and database synchronization technologies to verify and preprocess the collected data; Data Processing Layer: Connected to the data acquisition layer, cleans, integrates, and analyzes the collected data, uses algorithms to identify and correct data errors and outliers, classifies, aggregates, and transforms the data according to business requirements, and supports custom processing logic; Data Storage Layer: Connected to the data processing layer, designed with a real-time data wide table and a historical data summary table for storing data, and has data backup and recovery functions; User Interaction Layer: Connected to the data storage layer, provides an intuitive and easy-to-use interface, has data visualization tools and interaction functions, supports data export, receives user operation instructions and passes them to other layers; Filter Query Module: Set in the user interaction layer, contains multi-dimensional filter boxes and fuzzy search boxes, receives user filtering conditions and triggers the data processing layer to query data from the database, displays the query results in a list, and provides paging and sorting functions; Core Network Link Monitoring Module: Includes a timing task unit, a data storage unit, and a display unit. The timing task unit periodically calls the core network firewall interface to obtain link status data; the data storage unit stores the data in the link monitoring table and records the link interruption time and recovery time; The display unit draws a visualization graph based on the link status data, displays the normal or faulty status, designs an abnormal information broadcast function, and restricts the data display permissions for different operator enterprise roles; Data Statistics and Fusion Module: Includes a timing task sub-module, a data storage sub-module, and a query display sub-module; the timing task sub-module establishes a timing task to count the site information that has been online today and inserts it into the historical data summary table; The data storage sub-module designs a real-time data wide table to store real-time data; The query display sub-module jointly queries the real-time data wide table and the historical data summary table according to the user's filtering conditions, and associates and queries the equipment table to obtain the detailed information of base station equipment and satellite equipment, displays the results in a list, and provides visualization tools and interaction functions.

6. The system according to claim 5, characterized in that: Also includes Time Filtering Component: The time filtering component in the filter query module realizes real-time and interval selection through radio buttons. The interval selection can be accurate to query the data of the current day, and after the user selects the filtering conditions, the system updates the data display results in real time; Fuzzy Search Function Module: The fuzzy search box supports comprehensive fuzzy matching of multiple fields, covering fields such as site name, site person in charge, and equipment number, improving the accuracy and flexibility of data retrieval; List Display Optimization Module: The list display module supports users to customize the sorting fields and can sort according to the data update time and site importance fields; The paging function supports users to manually enter the page number to jump, and at the same time provides quick operation buttons; Filter Box Linkage Module: There is a linkage mechanism between each filter box. When the user selects the city filter condition, the site type filter box will be dynamically updated according to the actual site types in the selected city; Export Data Preprocessing Module: When exporting list data to Excel format, the system has an export data preprocessing module to uniformly adjust the data format and convert the unit of satellite traffic and user traffic data according to the conversion rules specified by the front end; Filter Query Data Source and Processing Module: The data of the filter query module comes from the real-time data wide table BASE_NOW_INFO and the historical data summary table BASE_ALL_INFO; there is a data source judgment and processing module in the data processing layer. When constructing the query statement, it judges whether to query from a single table or jointly query two tables according to the time filter condition; if real-time or same-day interval data is selected, it mainly queries from BASE_NOW_INFO; if cross-day interval data is selected, it performs a unionall operation on the two tables and then queries, and removes duplicate data from the query results; Multi-Dimensional Filter Logic Module: When the user selects multiple filter dimensions at the same time, the multi-dimensional filter logic module in the data processing layer combines the filter conditions of each dimension through logical operators to construct a query statement. Data Structure Association Module: The real-time data wide table BASE_NOW_INFO contains fields such as ID, EQUIPMENT_REL_ID, BASE_NAME, and INFO_TYPE, where ID is the primary key, and EQUIPMENT_REL_ID is used to associate with the equipment relationship table to obtain relevant information about the combined station; the historical data summary table BASE_ALL_INFO is associated with the real-time data wide table and the equipment relationship table through the equipment_rel_id field to store the statistically historical data. The filter query module in the data processing layer constructs a query statement based on the meanings and association relationships of the fields in each table and extracts the data that meets the conditions from these tables; Filter Query Result Processing Module: Before the query results are displayed in the list, the filter query result processing module in the data processing layer sorts the data according to the sorting rules set by the user in the user interaction layer. If the user selects to sort in ascending order by site name, the sorting function of the database is called to sort the query result set in ascending order according to the BASE_NAME field; if the user selects to sort in descending order by satellite traffic, it sorts in descending order according to the STATION_FLOW field to ensure that the display order meets the user's requirements.

7. The system according to claim 5, characterized in that: It also includes Abnormal Information Broadcasting Extension Module: The abnormal information broadcasting extension module of the core network link monitoring module, in addition to displaying the interruption time and connection time, also shows the fault type and detailed information about the affected site range, helping the administrator quickly locate and solve problems; Permission Control Refinement Module: The permissions of different operation enterprise roles are managed through the permission table associated with the role. The system is equipped with a permission control refinement module to automatically match the corresponding permissions according to the user role for data display; Visual Graphic Interaction Function Module: The visual graphic supports user click operations. When the user clicks on a certain link, the visual graphic interaction function module pops up a detailed information window to display the real-time traffic and bandwidth utilization detailed data of the link; Link Status Data Update Frequency Module: The timing task unit is equipped with a link status data update frequency module, which is set to call the core network firewall interface every two minutes to obtain the link status data to ensure the real-time nature of the data for timely detection of network faults; Fault Information Storage and Query Module: The fault information is stored in the link_info_notice table. In addition to recording the fault information, this table is also associated with the primary key ID of the link monitoring table (link_info); The system is equipped with a fault information storage and query module to facilitate the administrator to quickly trace back to the corresponding link status data when querying the fault information; At the same time, it provides the function of querying the fault information according to the fault time and fault type conditions, which is convenient for the administrator to analyze and summarize historical faults; Link Status Judgment and Display Logic Module: After obtaining the link status data, the link status judgment and display logic module of the system compares and judges the link status with the preset normal state threshold. If the real-time traffic and delay indicators of the link exceed the normal range, it is determined to be in a fault state. In the visual graphic displayed on the page, the fault line is not only displayed in red but also flashes to remind the administrator to pay attention. At the same time, in the abnormal information broadcasting area, in addition to the text information, it will also notify the administrator in the form of a sound alarm, and the sound alarm can be set with different volumes and frequencies according to the severity of the fault; Data Isolation Module for Different Role Permissions: For different operation enterprise roles, the system has a data isolation module for different role permissions during the database query stage for data isolation; Link Monitoring Table Structure and Data Storage Module: The link monitoring table (link_info) contains fields such as ID, link_type, end_time, recovery_time, and type. Among them, ID uniquely identifies each link monitoring record as the primary key, link_type is used to distinguish links of different operators, end_time records the link interruption time, recovery_time records the recovery time, and type represents the link status. The link status data obtained by the timing task is stored according to these fields, providing data support for subsequent status judgment, historical query, and visual display; Abnormal Information Broadcasting Form Structure and Data Processing Module: The link_info_notice table on which abnormal information broadcasting depends stores detailed information at the time of a fault through its association with the link_info table. The system is equipped with an abnormal information broadcasting form structure and data processing module. When the link status is abnormal, relevant fault information is inserted into the link_info_notice table. At the same time, in the abnormal information broadcasting area of the page, the data in this table is read for real-time display to ensure that administrators can obtain fault information in a timely manner; Real-time Monitoring Support and Guarantee Module: In the construction of a real-time monitoring system for all website points, the core network link monitoring data, as a key part, reflects the network quality in real time. Once a link fails, the system quickly notifies relevant personnel through abnormal information broadcasting. Combining with permission management, personnel of different roles can obtain corresponding data, providing a real-time network status basis for ensuring smooth network communication during natural disasters and major events, so as to adjust communication strategies in a timely manner.

8. The system according to claim 5, characterized in that: It also includes Statistical Information Calculation Details Module: When the timed task sub-module of the data statistics integration module counts the site information that went online on the same day, there is a statistical information calculation details module that accurately calculates key indicators such as satellite traffic and service duration. Among them, the satellite traffic is accumulated based on the traffic data in different time periods, and the service duration is calculated according to the actual start and end times of the site's service; Joint Query Optimization Module: The query display sub-module is equipped with a joint query optimization module. When performing a joint query, the data processing layer intelligently selects a query strategy according to the user's filtering conditions. If the filtering conditions involve a large time range, it preferentially queries from the historical data summary table; if it involves real-time data, it focuses on querying the real-time data wide table to improve the query efficiency; Visualization Display Expansion Module: The data visualization tool supports multiple graph display methods. In addition to bar charts and pie charts, it also includes line charts and radar charts. The system is equipped with a visualization display expansion module. Users can select appropriate graphs to display data according to their needs, and the graphs can be interactively operated; Timed Task Execution Logic Module: The timed task sub-module is equipped with a timed task execution logic module to count the site information that went online on the same day from the original data table BASE_STATION_DATA. During the counting process, first judge whether it belongs to the sites that went online on the same day according to the site's online time, and then extract and calculate the site data that meets the conditions, and insert the calculated statistical information into the historical data summary table BASE_ALL_INFO. Associated Device Information Query Optimization Module: When querying the detailed information of base station devices and satellite devices by associating and querying the device table EQUIPMENT_INFO, the query display sub-module adopts a caching mechanism and is equipped with an associated device information query optimization module. For frequently queried device information, it is cached in the memory. When the same device information is queried again, it is directly obtained from the cache, reducing the number of database queries and improving the system performance; Statistical Index Calculation Optimization Module: When counting satellite traffic, calculations and statistics are performed separately for different types of sites, including ground satellite single-site, ground satellite full-site, and drone satellite full-site. Joint Query Data Integration Module: When performing a joint query on the real-time data wide table and the historical data summary table, the query display sub-module is equipped with a joint query data integration module, which integrates the data in the two tables. For duplicate fields of the same site, the latest data is used for display. For unique fields in different tables, they are simultaneously displayed in the query result to provide users with more comprehensive data information. For example, the real-time data wide table may contain the number of real-time online users, and the historical data summary table contains the cumulative number of online users. Both of these fields will be simultaneously displayed in the query result. Historical Data Summary Table Structure and Data Insertion Module: The historical data summary table BASE_ALL_INFO obtains the information of the sites launched on the current day from the original data table BASE_STATION_DATA through a scheduled task at 1:00 am every night for statistics. The system is equipped with a historical data summary table structure and data insertion module. During statistics, the data of the current day is filtered based on the site launch time, and calculations are performed on satellite traffic and service duration indicators, and the calculation results are inserted into the BASE_ALL_INFO table. This table is associated with other tables through equipment_rel_id to ensure data consistency and traceability. Associated Query Module between Real-Time Data Wide Table and Equipment Table: The real-time data wide table BASE_NOW_INFO is associated with the equipment table EQUIPMENT_INFO through the site_id field. The query display sub-module is equipped with an associated query module between the real-time data wide table and the equipment table. In the statistical query module, the data processing layer obtains the basic data from BASE_NOW_INFO according to the user's filtering conditions, and then obtains the detailed equipment information from EQUIPMENT_INFO through the associated field to enrich the query result and provide users with more detailed data display. Multi-Dimensional Cross-Analysis Application Module: During natural disasters or major events, the system uses the data statistics and fusion function and is equipped with a multi-dimensional cross-analysis application module to perform multi-dimensional cross-analysis on satellite and base station data. Comprehensive analysis is carried out in combination with the time dimension (including before, during, and after the disaster), the regional dimension (including the core disaster area, surrounding affected areas), and the site type dimension (including ground satellite single-site, ground satellite full-site) to generate refined statistical reports and provide comprehensive data support for command and dispatch.

Images