A potential risk personnel early warning system based on XXL timing scheduling

Abstract

The present invention proposes a potential risk personnel early warning system based on XXL scheduled scheduling, which includes: a custom early warning module, a rule verification module, a scheduling module and a matching module, wherein the custom early warning module is used to configure an early warning template containing data source rules, scoring rules and proportions; the rule verification module is used to determine whether the template configured in the custom early warning module complies with the configuration rules. If it does not comply, the custom early warning module is re-entered to modify the early warning template; if it complies, the early warning template is submitted and an early warning task is initiated; the scheduling module receives the early warning task, schedules the execution of the early warning task through the XXL Job scheduler, presents the execution result on the front-end page, and directly optimizes the early warning template on the front-end page to obtain the optimized early warning model; the matching module is used to match the input data one by one with the early warning model, calculate the early warning score and obtain the early warning result.

Description

Technical Field

[0001] The present application relates to the field of intelligent security and smart city technology, and in particular to an early warning system for potential risk personnel based on XXL timing scheduling. Background Art

[0002] With the rapid development of the social economy and the increase in urban population mobility, social public security faces new challenges. Improving personnel risk warning capabilities will help government agencies effectively respond to complex and changing public security situations and strengthen the effectiveness of social governance applications. Relevant departments in various cities across China gather a large amount of data from various industries, such as population data, conflicts and disputes, key personnel data, and incident reporting hotline data from various sources. The integration of this type of data helps to screen potential risk personnel and is confidential data. Using this data as the basis for legal, reasonable and compliant data to create an intelligent potential risk personnel warning system for staff in a certain field to analyze and judge is currently an urgent need for relevant departments in various cities.

[0003] Currently, there's no configurable system on the market that provides real-time intelligent early warnings for specific types of potential risk individuals. The most primitive approach relies on manually entering a specific individual's identification information, such as their ID card or contact number. This approach then searches an existing database for recent incidents involving that individual, either from the department or through a hotline. This approach then manually determines whether the incidents align with specific potential risk events and, in turn, whether the individual is a potential risk. While this approach has some analytical value, it suffers from data limitations and relies on manual analysis. Knowing the individual's information in advance, it then requires significant time and effort to search for relevant information for manual analysis, resulting in unsatisfactory results. A more mature approach involves assigning dedicated analysts to review daily incident data collected by departments and reported through hotlines. These analysts directly identify individuals involved in the incidents through direct analysis of the incident content. Furthermore, these analysts then conduct a comprehensive search for other relevant information, such as criminal records, social security information, and credit status, to determine whether the individual is a potential risk. This method is from event to person. Compared with the previous approach, it improves the accuracy of the analysts. It can start from the event, and the operability and purposefulness will be stronger, and the quality of the final assessment will be better. However, this method does not reduce the workload of the analysts, and the analysts still need to analyze each event one by one. Due to the large number of events reported by departments and hotlines, and most of the events are similar to traffic accidents, property notices, telephone consultations and other event information that are not related to potential risks. Such events increase the analysis time of analysts and reduce the efficiency of analysis. It is impossible to focus more time and energy on risky events and people, resulting in the final manual assessment of potential risk personnel. The results are not ideal, and the approach is rigid and cannot provide flexible and configurable templates for analysts to choose from.

[0004] As the information level of various business departments continues to improve, the business systems built are becoming more and more intelligent, the amount of business data generated is getting larger and larger, and the data of various departments have not yet been effectively integrated. In the face of huge amounts of data, relying on manual methods to search, compare, and judge potential risk personnel has become increasingly inadequate. This method has the following main shortcomings: limited by the conditions for querying personnel identity information, it is necessary to know the personnel identity information in advance before starting the query and judgment work; the judges need to check and analyze events one by one, and when the amount of data is huge, the workload generated is huge; the basis for grading risk personnel is not standardized enough, and the risk level is defined by subjective will, which affects the judgment results; real-time warning or on-demand warning has not been achieved; user-customizable configuration requirements have not been met; the warning process has a low degree of intelligence. Summary of the Invention

[0005] In order to solve the problems that analysts need to check and analyze events one by one, the existing technology does not realize real-time warning or on-demand warning, and does not realize user-customizable configuration requirements, the purpose of the present invention is to provide a potential risk personnel warning system based on XXL timed scheduling to solve the above technical problems.

[0006] The present invention proposes a potential risk personnel early warning system based on XXL timed scheduling, which includes: a custom early warning module, a rule verification module, a scheduling module and a matching module.

[0007] The custom warning module is used to configure warning templates that include data source rules, scoring rules, and proportions.

[0008] The rule verification module is used to determine whether the template configured in the custom warning module complies with the configuration rules. If not, re-enter the custom warning module to modify the warning template. If it complies, submit the warning template and initiate the warning task.

[0009] The scheduling module receives the warning task, schedules the execution of the warning task through the xxl-Job scheduler, presents the execution result on the front-end page, and optimizes the warning template directly on the front-end page to obtain the optimized warning model;

[0010] The matching module is used to match the input data to the warning model one by one, calculate the warning score and obtain the warning result.

[0011] In a specific embodiment, the matching module is used to match the input data to the warning model one by one, calculate the warning score to obtain the warning result, and specifically includes:

[0012] Filter out event data based on the data source rule query configured in the warning template, and traverse the event data to extract personnel identity information and store it in the temporary table of warning personnel identity information;

[0013] Poll and traverse the temporary table of early warning personnel identity information, query the relevant data of personnel involved in the incident and the basic early warning information data of personnel corresponding to the personnel identity information in the system and save them;

[0014] Calculate the original score of each dimension according to the rules configured in the warning template, and then calculate the proportion score according to the proportion rule to finally obtain the warning score;

[0015] According to the configured warning red, yellow and blue rules and score thresholds, determine whether the personnel identity information needs to be marked with the corresponding warning identity label, record the number of warnings, and save the personnel warning result information to the warning result table. The personnel warning result information includes the basic information of the personnel, the basic data of each dimension score, and the final result data.

[0016] In a specific embodiment, it also includes analyzing and judging the potential risk personnel who are warned of potential risks based on the warning results. If the potential risk personnel are determined to be potential risk personnel, the warning result information of the potential risk personnel will be transmitted to the receiving end of the collaborative department, and the feedback data of the collaborative department's handling results will be received and displayed.

[0017] In a specific embodiment, the custom early warning module is used to configure data source rules, scoring rules, and warning templates of proportions, specifically including: custom configuration of filtering the source of events according to different conditions, the time range of event occurrence, and event classification as data source rules, and configuring the basic scores and weight proportions of five dimensions, including personnel identity tags, personnel-involved event tags, total number of involvements, number of involvements in the month, and time span of involvement, as the final scoring basis for potential risk personnel.

[0018] In a specific embodiment, a data storage module is further included, which is used to store the warning template in the custom warning module, record the retention time of the warning template and set the status of the warning template to no warning.

[0019] In a specific embodiment, the scheduling module receives the warning task and schedules the execution of the warning task through the xxl-Job scheduler, including: when the xxl-Job scheduler starts scheduling the execution of the warning task, the status lock of the warning template is updated to warning, and the warning time is updated to generate the warning batch number associated with the warning template, and then the warning task starts to be executed.

[0020] In a specific embodiment, after the warning task is completed, the status of the warning template is locked as completed, and in the subsequent data entry stage, the identity information of the personnel in the event is extracted and the warning model is matched one by one directly according to the identity information of the personnel to automatically initiate a warning.

[0021] In a specific embodiment, a rule verification module is also included to determine whether the template configured by the custom warning module complies with the configuration rules. If not, a prompt message will pop up for the user to re-enter the custom warning module to modify the warning template. After the warning template rule verification is passed, the event data matching the corresponding rule is returned according to the configured data source rule to verify the accuracy of the rule. After the accuracy of the rule meets the standard, the warning template is submitted and the warning task is initiated.

[0022] In a specific embodiment, the optimized warning template is used as a default template. When a new warning task is created next time, the warning parameters of the default template are filled in to initiate a new warning task.

[0023] In a specific embodiment, it also includes judging whether the warning result meets expectations. If so, a real-time warning is issued based on the warning template. The identity information of the personnel in the data is automatically extracted and matched with the warning model one by one at the first time of data entry. The warning score is calculated to obtain the warning result, and the warning result is entered into the data result set of the corresponding template.

[0024] Compared with the prior art, the present invention has the following advantages:

[0025] The screening of potential risk personnel is a very important task for relevant departments. This work is an important part of providing clues to the mediation department to mediate disputes, resolve public safety hazards, and protect the social production and life safety of grassroots people. Doing this work well can greatly ensure social harmony and stability, promote local economic growth, and improve people's sense of security and happiness. Even though government departments have a lot of production and life data, they still have not found a more suitable screening method and screening process in the field of potential risk personnel screening, and are still in the exploratory stage. In order to overcome the shortcomings of existing screening methods and processes, the present invention provides a stable and configurable potential risk personnel screening system design, provides a visual configuration template, and can customize different types of potential risk personnel warning templates, improve the intelligence of risk warning, achieve accurate warning results, and enhance the convenience of personnel analysis and judgment. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Other features, objects and advantages of the present application will become more apparent from the detailed description of non-limiting embodiments made with reference to the following drawings:

[0027] Figure 1 It is a front-end interactive flow chart for screening potential risk personnel according to this application;

[0028] Figure 2 This is a flowchart for warning potential risk personnel according to this application;

[0029] Figure 3 It is a structural diagram of a computer system suitable for implementing the electronic device of the embodiment of the present application. DETAILED DESCRIPTION

[0030] The present application will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described herein are merely for the purpose of explaining the relevant invention and are not intended to limit the invention. It should also be noted that, for ease of description, only portions relevant to the relevant invention are shown in the accompanying drawings.

[0031] It should be noted that, in the absence of conflict, the embodiments and features of the embodiments in this application can be combined with each other. The present application will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0032] This application proposes a potential risk personnel early warning system based on XXL timed scheduling, which includes: a custom early warning module, a rule verification module, a scheduling module and a matching module.

[0033] The custom warning module is used to configure data source rules, scoring rules, and warning templates for proportions.

[0034] The rule verification module is used to determine whether the template configured in the custom warning module complies with the configuration rules. If not, re-enter the custom warning module to modify the warning template. If it complies, submit the warning template and initiate the warning task.

[0035] The scheduling module receives the warning task, schedules the execution of the warning task through the xxl-Job scheduler, presents the execution result on the front-end page, and optimizes the warning template directly on the front-end page to obtain the optimized warning model;

[0036] The matching module is used to match the input data to the warning model one by one, calculate the warning score and obtain the warning result.

[0037] Figure 1 The front-end interactive flow chart for checking potential risk personnel in this application is shown in the figure. Please refer to Figure 1 .

[0038] In a specific embodiment, this application provides a front-end interface for user-configured warning templates. The warning template can be customized to filter the source of events, the time range of events, and event classifications based on different conditions as data sources. Basic scores and weightings for five dimensions, including personnel identity tags, personnel-involved event tags, total number of incidents, number of incidents in the month, and time span of incidents, can be configured as the final scoring basis for potential risk personnel.

[0039] After the user configures the warning template, he can edit and save the warning template, which makes it easier for the user to tune the score and optimize the model later.

[0040] When a user submits an early warning template, the system will automatically verify whether the template's score configuration rules comply with the early warning settings. If not, a friendly prompt message will be provided to allow the user to modify the configuration of the early warning template according to the rules.

[0041] After the template rule verification is passed, the system will return the event data that matches the corresponding rules according to the configured template data source rules, which is convenient for timely verification of the accuracy of the rules. If the user finds that the returned data is not what he wants, he can directly return to modify the configuration template again until it meets his own setting requirements.

[0042] After confirming that the basic data source is correct, the user can submit and initiate an alert task. The submitted alert template is saved and subsequently scheduled through xxlJob to complete the final alert task.

[0043] After the warning task is completed, users can preview the warning results on the front-end page. If they find that the warning results are not satisfactory, they can directly modify the warning score settings of the warning template on the page, and the warning result score can be recalculated without having to execute the warning task again. This reciprocating operation continuously optimizes the warning template.

[0044] The optimized warning template can be used as the default template. The next time you create a new warning task, the warning parameters of the default template will be filled in. You can also specify a template to copy from the existing templates to add a new template. After modification, you can save and initiate a new warning task, thereby improving the efficiency of screening potential risk personnel.

[0045] If the warning result meets expectations, a real-time warning indicator of the template will be set on the front end. The system will automatically extract the identity information of the personnel in the data as soon as the data is entered, match it one by one with the configured warning model, calculate the warning score, and record the warning result of the personnel into the data result set of the corresponding template to achieve the effect of real-time warning.

[0046] Potential risk investigators can directly view warning results from different types of warning models, using this as a starting point for investigation and assessment of individuals identified as potentially at risk. If identified as a potential risk individual, the warning information is transmitted to the collaborative department's receiving end, and feedback from the collaborative department's handling results is received and displayed. This means that the collaborative department directly handles the potential risk individual, and the relevant department's responsible person conducts follow-up processing. Feedback from the department's handling results is also displayed on the collaborative tracking page, ensuring continuous follow-up and supervision to complete the final closed-loop screening of potential risk individuals.

[0047] It should be understood that the implementation of this application solution is based on the premise that all types of data have been collected and managed.

[0048] Figure 2 The flowchart of this application for warning potential risk personnel is shown in Figure 2 .

[0049] After the configured warning template is uploaded to the backend, the system performs the warning task for the warning template. The specific steps are as follows:

[0050] The system receives the warning template configuration data uploaded by the user and stores the warning template configuration data in the database;

[0051] Record the template saving time and set the template status lock to no warning;

[0052] When the xxl-job scheduler starts to schedule the execution of the warning task, it sets the template status lock to warning, updates the warning time, generates a warning batch number and associates it with the warning template, and starts executing the warning task;

[0053] The event data is filtered out through the data source matching rule query configured in the template, and the data is scrolled and polled in a cursor manner. The identity information of the personnel in the event is extracted, and the data is deduplicated using the map or set method. The data is then entered into the temporary table of the warning personnel identity information with the warning batch number.

[0054] In the next stage, the temporary table of the warning personnel's identity information is polled and traversed to query all the personnel's data, labels, and identity labels in the system, calculate the time span of the incident, the first and last occurrence times, the number of incidents in the month, and other basic warning information data of the personnel and save them;

[0055] Calculate the original score of each dimension according to the warning template configuration rules, and calculate the proportion score according to the proportion rule, and finally add them up to get the final warning score;

[0056] According to the configured red, yellow and blue warning rules and scores, it is necessary to add the corresponding warning identity label to the warning personnel information, record the number of system warnings, and save the final personnel warning result information to the warning result table. The warning result information includes the basic information of the personnel, the basic data of each dimension score and the final result data;

[0057] When the warning task is completed, the status of the corresponding template is set to completed;

[0058] In the subsequent data entry stage, the identity information of the people in the incident will be extracted and an early warning will be automatically initiated by matching the templates one by one based on the identity information.

[0059] Compared with the conventional process of screening potential risk personnel, this application is more flexible, intelligent, and real-time. Good UI interaction displays various types of information related to potential risk personnel, allowing screening personnel to better assist in screening. The five scoring models and real-time early warning mechanism designed make early warning and judgment more scientific, and can effectively solve the pain points and difficulties in the customer screening process, effectively judge and analyze, and track the long-term system, improve regional safety, and help enhance the sense of security and happiness of the public.

[0060] Furthermore, this application enables users to have a smooth operational interaction process, with customized on-demand configurations. It can also set customized warning templates for specific potential risk individuals, making the warning results more accurate. It can also greatly simplify the screening process for potential risk individuals and reduce the difficulty of screening, allowing users to focus their time and energy on those with high risk factors. It can also reduce the workload of screening personnel to a certain extent, greatly improving their work efficiency. At the same time, based on the latest data, it can support real-time warnings for new potential risk individuals, ensuring the timeliness of risk personnel screening.

[0061] The model-based, configurable system for identifying potential risk individuals proposed in this application has promising applications in domestic government agencies, including public security departments, political and legal committees, and judicial bureaus. It can assist relevant personnel in quickly identifying potential risk individuals within their area, tracking and controlling them, and, when necessary, taking appropriate measures to prevent them from engaging in behaviors that pose a threat to public security. This significantly enhances regional security within each jurisdiction and serves as a powerful tool for identifying potential risk individuals within society.

[0062] The present application also provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, it implements any of the above methods.

[0063] Reference below Figure 3 , which shows a structural diagram of a computer system 300 suitable for implementing a terminal device or server of an embodiment of the present application. Figure 3 The terminal device or server shown is merely an example and should not limit the functions and scope of use of the embodiments of the present application.

[0064] like Figure 3 As shown, the computer system 300 includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to a program stored in a read-only memory (ROM) 302 or a program loaded from a storage unit 308 into a random access memory (RAM) 303. Various programs and data required for the operation of the system 300 are also stored in the RAM 303. The CPU 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An input / output (I / O) interface 305 is also connected to the bus 304.

[0065] The following components are connected to the I / O interface 305: an input section 306 including a keyboard, a mouse, and the like; an output section 307 including a liquid crystal display (LCD), a speaker, and the like; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN card or a modem. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. Removable media 311, such as a magnetic disk, an optical disk, a magneto-optical disk, or a semiconductor memory, is installed in the drive 310 as needed, so that computer programs read therefrom can be installed into the storage section 308 as needed.

[0066] In particular, according to an embodiment of the present disclosure, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present disclosure includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a program code for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from the network through the communication part 309, and / or installed from the removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, the above-mentioned functions defined in the method of the present application are executed. It should be noted that the computer-readable medium described in the present application can be a computer-readable signal medium or a computer-readable medium or any combination of the above two. The computer-readable medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable media may include, but are not limited to, an electrical connection having one or more conductors, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof. In this application, a computer-readable medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such a propagated data signal may take a variety of forms, including, but not limited to, electromagnetic signals, optical signals, or any suitable combination thereof. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device. Program code embodied on a computer-readable medium may be transmitted using any suitable medium, including, but not limited to, wireless, wire, optical cable, RF, or any suitable combination thereof.

[0067] Computer program code for performing the operations of the present application can be written in one or more programming languages, or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or can be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0068] The flow charts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present application. In this regard, each box in the flow chart or block diagram can represent a module, program segment or a part of code, and the module, program segment or a part of code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order than that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flow chart, and the combination of the boxes in the block diagram and / or flow chart can be implemented by a dedicated hardware-based system that performs the specified function or operation, or can be implemented by a combination of dedicated hardware and computer instructions.

[0069] The modules involved in the embodiments of the present application may be implemented in software or in hardware. The units described may also be provided in a processor. For example, they may be described as follows: a processor includes a receiving module, an acquisition module, a determination module, a calculation module, and a generation module. The names of these units do not, in some cases, constitute limitations on the units themselves. For example, the receiving unit may also be described as a "module that obtains preset, target user configuration information in response to determining that the verification request information includes a user name, a request time, a user signature code, and a client application code."

[0070] As another aspect, the present application also provides a computer-readable medium, which may be included in the server described in the above embodiment; or may exist independently and not be assembled into the server. The computer-readable medium carries one or more programs, and when the one or more programs are executed by the server, the server: receives a verification request message sent by a client of a target user; in response to determining that the verification request message includes a user name, a request time, a user signature code, and a client application code, obtains preset configuration information of the target user, wherein the configuration information includes a preset user password corresponding to the user name; determines whether the verification request message is valid based on the request time, and in response to determining that it is valid, determines whether a preset storage area includes a user signature code; in response to determining that it is not included, stores the user signature code in a preset storage area, and calculates a server application code based on the user password, the request time, and the user signature code; in response to determining that the server application code matches the client application code, generates verification success information for indicating that the verification request is a legitimate request.

[0071] In addition, the computer-readable medium may be included in the terminal device described in the above embodiment, or may exist independently without being incorporated into the terminal device. The computer-readable medium carries one or more programs. When the one or more programs are executed by the terminal device, the terminal device: obtains user information input by the target user, wherein the user information includes a user name and a user password; generates a user signature code representing the target user based on the user information; determines a request time; calculates a client application code based on the user password, the request time, and the user signature code; generates verification request information including the user name, the request time, the user signature code, and the client application code; and sends the verification request information to the server.

[0072] The above description is merely a preferred embodiment of the present application and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this application is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the above-mentioned inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this application.

Claims

1. A potential risk personnel early warning system based on XXL timed scheduling, characterized in that: It includes: a custom warning module, a rule verification module, a scheduling module and a matching module, wherein the custom warning module is used to configure a warning template including data source rules, scoring rules and proportions; The rule verification module is used to determine whether the template configured by the custom warning module complies with the configuration rules. If not, the custom warning module is re-entered to modify the warning template. If it complies, the warning template is submitted and a warning task is initiated. The scheduling module receives the warning task, schedules the execution of the warning task through the xxl-Job scheduler, presents the execution result on the front-end page, and directly optimizes the warning template on the front-end page to obtain the optimized warning model; The matching module is used to match the input data to the early warning model one by one, calculate the early warning score to obtain the early warning result, and specifically includes: Filter out event data based on the data source rule query configured in the warning template, and traverse the event data to extract personnel identity information and store it in the warning personnel identity information temporary table; Poll and traverse the temporary table of the warning personnel identity information, query the system for the personnel-related data and personnel basic warning information data corresponding to the personnel identity information, and save them; Calculate the original score of each dimension according to the rules configured in the warning template, and calculate the proportion score according to the proportion rule to finally obtain the warning score; According to the configured warning red, yellow and blue rules and score thresholds, determine whether the personnel identity information needs to be marked with the corresponding warning identity label, record the number of warnings, and save the personnel warning result information to the warning result table, where the personnel warning result information includes the basic information of the personnel and the basic data of each dimension score and the final result data.

2. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: It also includes analyzing and judging the potential risk personnel who are warned of potential risks based on the warning results. If the potential risk personnel are determined to be potential risk personnel, the warning result information of the potential risk personnel will be transmitted to the receiving end of the collaborative department, and the feedback data of the collaborative department's handling results will be received and displayed.

3. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: The custom early warning module is used to configure data source rules, scoring rules and warning templates of proportions, specifically including: custom configuration of filtering the source of events according to different conditions, the time range of event occurrence, and event classification as the data source rules, and configuring the basic scores and weight proportions of five dimensions including personnel identity tags, personnel-involved event tags, total number of incidents, number of incidents in the current month, and time span of incidents as the final scoring basis for potential risk personnel.

4. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: It also includes a data storage module, which is used to store the warning template in the custom warning module, record the retention time of the warning template and set the status of the warning template to no warning.

5. The XXL time-scheduled potential risk personnel early warning system according to claim 4 is characterized in that: The scheduling module receives the warning task and schedules the execution of the warning task through the xxl-Job scheduler, including: when the xxl-Job scheduler starts to schedule the execution of the warning task, the status lock of the warning template is updated to warning, and the warning time is updated to generate a warning batch number associated with the warning template, and then the warning task starts to be executed.

6. The XXL time-scheduled potential risk personnel early warning system according to claim 5 is characterized in that: It also includes that after the warning task is completed, the status of the warning template is locked as completed, and in the subsequent data entry stage, the identity information of the personnel in the event is extracted and the warning model is matched one by one directly according to the identity information of the personnel to automatically initiate a warning.

7. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: It also includes the rule verification module for determining whether the template configured by the custom warning module complies with the configuration rules. If not, a prompt message will pop up for the user to re-enter the custom warning module to modify the warning template. After the warning template rule verification is passed, the event data matching the corresponding rule will be returned according to the configured data source rule to verify the accuracy of the rule. After the accuracy of the rule meets the standard, the warning template will be submitted and the warning task will be initiated.

8. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: The method further includes using the optimized warning template as a default template, filling in the warning parameters of the default template when creating a new warning task next time, and initiating a new warning task.

9. The XXL time-scheduled potential risk personnel early warning system according to claim 1 is characterized in that: It also includes judging whether the warning result meets expectations. If so, a real-time warning is issued based on the warning template. The identity information of the personnel in the data is automatically extracted and matched one by one with the warning model at the first time of data entry. The warning score is calculated to obtain the warning result, and the warning result is entered into the data result set of the corresponding template.

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