Derived alarm prejudgment method, device, equipment and medium

Abstract

The invention provides a derived alarm prejudgment method, device and equipment and a medium, and the method comprises the steps: S1, receiving current alarm information in real time, carrying out the preliminary analysis, obtaining full-amount alarm information, and storing the full-amount alarm information in an alarm information base, the full-amount alarm information comprises a telephone number, alarm time, alarm content, general alarm type information and special alarm type information; s2, retrieving the alarm information base according to the telephone number, and matching full-amount alarm information of all alarm records of the telephone number in each preset time period and taking the full-amount alarm information as a judgment set; s3, performing derived alarm pre-judgment analysis on the judgment set to obtain a pre-judgment analysis result, and displaying and storing the pre-judgment analysis result; and S4, judging whether the pre-judgment analysis result meets an early warning condition or not, and if so, generating early warning information and sending out early warning. According to the invention, more comprehensive and accurate alarm evaluation is provided, and generation of derived alarm conditions is prevented.

Description

Technical Field

[0001] The present invention relates to the technical field of alarm situation prediction, and in particular to a method, device, equipment and medium for predicting derived alarm situations. Background Art

[0002] When the same phone number has a high frequency of alerts, it often hides a deeper message. For example, if the phone number's owner is highly concerned about a particular alert, the outcome of that alert will have a significant emotional impact on the owner. Improper or untimely handling of that alert can often trigger an emotional breakdown, prompting irrational behavior and triggering new alerts. This can lead to further negative consequences.

[0003] When dealing with duplicate alarms, the current alarm analysis system only identifies them by accumulating the number of times the same phone number is used to report an alarm. This can only reflect the frequency of the alarms, but is not enough to accurately capture the true meaning of duplicate alarms, thus missing the opportunity to prevent the generation of derivative alarms. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to provide a method, device, equipment and medium for predicting derived alarms, which further conducts in-depth analysis of the alarms based on repeated alarm identification. It can not only more accurately identify repeated alarms, but also balance the impact of time factors on previous alarm statistics, thereby providing a more comprehensive and accurate alarm assessment and preventing the occurrence of derived alarms.

[0005] In a first aspect, the present invention provides a method for predicting a derived alarm situation, comprising the following steps:

[0006] S1. Receive the current alarm information in real time and perform preliminary analysis to obtain full alarm information and store it in the alarm information database. The full alarm information includes the phone number, alarm time, alarm content, general alarm type information, and special alarm type information;

[0007] S2. Search the alarm information database according to the phone number, match the full amount of alarm information of all alarm records of the phone number in each preset time period and use it as a judgment set;

[0008] S3. Performing a derived alarm situation prediction analysis on the judgment set, obtaining a prediction analysis result, and displaying and storing the result;

[0009] S4. Determine whether the pre-judgment analysis result meets the warning condition. If so, generate warning information and issue a warning.

[0010] In a second aspect, the present invention provides a device for predicting a derived alarm situation, comprising:

[0011] A preliminary analysis module is used to receive the current alarm information in real time and perform preliminary analysis to obtain the full alarm information and store it in the alarm information database. The full alarm information includes the phone number, alarm time, alarm content, general alarm type information and special alarm type information;

[0012] A search module is used to search the police information database according to the phone number, match the full amount of police information of all alarm records of the phone number in each preset time period and use it as a judgment set;

[0013] A prediction analysis module is used to perform a prediction analysis of the derived alarm situation on the judgment set, obtain the prediction analysis results, and display and store them;

[0014] The early warning module is used to determine whether the pre-judgment analysis result meets the early warning conditions. If so, it generates early warning information and issues an early warning.

[0015] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the method described in the first aspect when executing the program.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, which implements the method described in the first aspect when the program is executed by a processor.

[0017] One or more technical solutions provided by the present invention have at least the following technical effects or advantages: Based on duplicate alarm identification, the present invention further analyzes alarms, not only more accurately identifying duplicate alarms, but also balancing the impact of time on previous alarm statistics and further analyzing the caller's emotions. This enhances the comprehensiveness of alarm processing: by comprehensively considering the telephone number, general and special alarm type information, time factors, the caller's emotions, and other factors, a more comprehensive and accurate alarm assessment is provided, effectively preventing the generation of derivative alarms.

[0018] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented in accordance with the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are specifically listed below. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0020] Figure 1 This is a flowchart of the method in Example 1 of the present invention;

[0021] Figure 2This is a schematic structural diagram of the device in Example 2 of the present invention;

[0022] Figure 3 This is a schematic structural diagram of an electronic device in a third embodiment of the present invention;

[0023] Figure 4 Schematic diagram of the structure of the medium in the fourth embodiment of the present invention. DETAILED DESCRIPTION

[0024] The embodiments of the present application provide a method, device, equipment and medium for predicting derived alarms, and further conduct in-depth analysis of alarms based on repeated alarm identification. It can not only more accurately identify repeated alarms, but also balance the impact of time factors on previous alarm statistics, thereby providing a more comprehensive and accurate alarm assessment and preventing the occurrence of derived alarms.

[0025] The technical solution in the embodiments of the present application has the following general idea: based on the identification of repeated alarms from the same alarm phone, the present invention further conducts an in-depth analysis of the alarm situation to obtain the full amount of alarm information, and further analyzes and predicts the full amount of alarm information, taking into account the telephone number, general alarm type information and special alarm type information, time factors, the mood of the caller, etc. This not only allows for more accurate identification of repeated alarms, but also balances the impact of time factors on previous alarm statistics, and further analyzes the mood of the caller, thereby enhancing the comprehensiveness of alarm processing, providing a more comprehensive and accurate alarm assessment, and effectively preventing the generation of derivative alarms.

[0026] Example 1

[0027] like Figure 1 As shown, this embodiment provides a method for predicting derived alarm situations, including the following steps:

[0028] S1. Receive the current alarm information in real time and perform preliminary analysis to obtain full alarm information and store it in the alarm information database. The full alarm information includes the phone number, alarm time, alarm content, general alarm type information, and special alarm type information;

[0029] The special alarm analysis is to perform sensitive word analysis on the alarm content. If the alarm content involves sensitive words corresponding to the special alarm, the alarm content is determined to be a special alarm.

[0030] S2. Search the alarm information database according to the phone number, match the full amount of alarm information of all alarm records of the phone number in each preset time period and use it as a judgment set;

[0031] S3. Performing a derived alarm situation prediction analysis on the judgment set, obtaining a prediction analysis result, and displaying and storing the result;

[0032] S4. Determine whether the pre-judgment analysis result meets the warning condition. If so, generate warning information and issue a warning.

[0033] Furthermore, in S3, the derived alarm situation prediction analysis specifically includes the following contents:

[0034] Calculate basic points: Count the number of alarms for the phone number in each time interval and obtain the basic points corresponding to the number of alarms. The basic point formula = number of alarms per time interval × 1;

[0035] Calculate the bonus coefficient of the type repetition rate: Count the repetition rates of each alarm type in the judgment set, and obtain the corresponding bonus coefficient according to the repetition rate of each alarm type. The type repetition rate bonus coefficient = the configuration of the repetition rate;

[0036] Suppose, for example, that among a total of 10 alarms in a judgment set, there are 5 cases of personal threats and 3 cases of conflicts and disputes. The repetition rate for personal threats is 50%, and for conflicts and disputes, 30%. The repetition rate indicates that these multiple alarms may contain repeated reports of the same incident, which are not resolved, leading to repeated reports of the same type. This repetition may indicate that the alarm was not handled promptly, or that similar alarms have recurred multiple times, indicating insufficient action. This may lead to dissatisfaction with the handling of the alarm, potentially causing the alarmist to lose control of their emotions and engage in aggressive behavior in the future, thus generating new alarms.

[0037] The repetition rate of each type is divided into different levels (e.g. 30%-50%; 50%-60%; above 60%). Based on the different repetition rates, a bonus factor is added to increase the score of the more repeated alarms. The bonus factor table is as follows:

[0038] Repetition rate Bonus coefficient 30％-50％ 1.2 50％-60％ 1.4 More than 60% 1.6

[0039] Calculate special police situation points: count the number of special police situations involved and obtain the corresponding special police situation points, special police situation points = number of special police situations × 1;

[0040] Calculate the time discount coefficient: Look up the table to obtain the time discount coefficient corresponding to each time interval. The discount coefficient is obtained from the discount coefficient table. The longer the time interval, the smaller the discount coefficient, and vice versa. Taking the time interval as one month as an example, the discount coefficient table can be set as follows:

[0041]

[0042] Calculate the derived police situation prediction score for each time interval: total score = (basic score × type repetition rate coefficient + special police situation) × discount coefficient of the nth time interval.

[0043] Assume that the data table of the judgment set is as follows:

[0044]

[0045] The score calculation example for each time interval is the last column of data in the above table.

[0046] According to the calculation formula:

[0047] Search score for the past three months = past 1 month + past 2 months + past 3 months = 16 + 14.7 + 13.3 = 40 points

[0048] The score for the past six months = the past 1 month + the past 2 months + the past 3 months + the past 4 months + the past 5 months + the past 6 months = 16 + 14.7 + 13.3 + 10.5 + 10.7 + 9.3 = 70.5.

[0049] The judgment set is then subjected to a derived alarm prediction analysis to obtain the prediction analysis results and display and store them; the higher the score, the more harmful the alarm is and the greater the impact on the person reporting the alarm may be. Therefore, when the score exceeds a certain threshold, an early warning message is generated and an early warning is issued.

[0050] In addition, the full alarm information can also include the caller's emotional level, which is obtained by analyzing the caller's voice and intonation. Since the caller's voice and intonation will reflect their emotions when they repeatedly call the police, their emotions directly express their satisfaction with the handling of the alarm. Therefore, the voice and intonation of the alarm call can be directly analyzed using the emotion analysis model to obtain the caller's emotional level, which is then used to calculate the total score. The derived alarm prediction analysis also includes the following:

[0051] Calculate the caller's emotional level score: according to the caller's emotional level, obtain the corresponding caller's emotional score;

[0052] The total score = (basic score × type repetition rate coefficient + special alarm situation + emotional score of the caller) × discount coefficient of the nth time interval.

[0053] Based on the same inventive concept, this application also provides a device corresponding to the method in Example 1, see Example 2 for details.

[0054] Example 2

[0055] like Figure 2 As shown, in this embodiment, a device for predicting a derived alarm situation is provided, including:

[0056] A preliminary analysis module is used to receive the current alarm information in real time and perform preliminary analysis to obtain the full alarm information and store it in the alarm information database. The full alarm information includes the phone number, alarm time, alarm content, general alarm type information and special alarm type information;

[0057] The special alarm analysis is to perform sensitive word analysis on the alarm content. If the alarm content involves sensitive words corresponding to the special alarm, the alarm content is determined to be a special alarm.

[0058] A search module is used to search the police information database according to the phone number, match the full amount of police information of all alarm records of the phone number in each preset time period and use it as a judgment set;

[0059] A prediction analysis module is used to perform a prediction analysis of the derived alarm situation on the judgment set, obtain the prediction analysis results, and display and store them;

[0060] The early warning module is used to determine whether the pre-judgment analysis result meets the early warning conditions. If so, it generates early warning information and issues an early warning.

[0061] The derived alarm situation prediction analysis specifically includes the following contents:

[0062] Calculate basic points: Count the number of alarms for the phone number in each time interval and obtain the basic points corresponding to the number of alarms. The basic point formula = number of alarms per time interval × 1;

[0063] Calculate special police situation points: count the number of special police situations involved and obtain the corresponding special police situation points, special police situation points = number of special police situations × 1;

[0064] Calculate the bonus coefficient of the type repetition rate: Count the repetition rates of each alarm type in the judgment set, and obtain the corresponding bonus coefficient according to the repetition rate of each alarm type. The type repetition rate bonus coefficient = the configuration of the repetition rate;

[0065] Calculate the time discount coefficient: Look up the table to obtain the time discount coefficient corresponding to each time interval. The discount coefficient = obtained from the discount coefficient table. The longer the time interval, the smaller the discount coefficient, and vice versa.

[0066] Calculate the derived police situation prediction score for each time interval: total score = (basic score × type repetition rate coefficient + special police situation) × discount coefficient of the nth time interval.

[0067] Furthermore, the full alarm information can also include the caller's emotional level, which is determined by analyzing the caller's voice and intonation. Since repeated calls often reflect the caller's emotional tone, their emotions directly reflect their satisfaction with the outcome of the call. Therefore, the emotion analysis model can be used to directly analyze the voice and intonation of the alarm call to determine the caller's emotional level, which is then factored into the overall score.

[0068] The full amount of police information also includes the emotional level of the caller, which is obtained by analyzing the caller's voice and tone; the derived police prediction analysis also includes the following:

[0069] Calculate the caller's emotional level score: according to the caller's emotional level, obtain the corresponding caller's emotional score;

[0070] The total score = (basic score × type repetition rate coefficient + special alarm situation + emotional score of the caller) × discount coefficient of the nth time interval.

[0071] Since the device described in the second embodiment of the present invention is used to implement the method of the first embodiment of the present invention, those skilled in the art will be able to understand the specific structure and variations of the device based on the method described in the first embodiment of the present invention, and therefore will not be described in detail here. All devices used in the method of the first embodiment of the present invention fall within the scope of protection of the present invention.

[0072] Based on the same inventive concept, this application provides an electronic device embodiment corresponding to the first embodiment, see the third embodiment for details.

[0073] Example 3

[0074] like Figure 3 As shown, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, any implementation method in the first embodiment can be implemented.

[0075] Since the electronic device described in this embodiment is the device used to implement the method in Example 1 of this application, based on the method described in Example 1 of this application, those skilled in the art will be able to understand the specific implementation of the electronic device of this embodiment and its various variations. Therefore, how the electronic device implements the method in the embodiment of this application will not be described in detail here. As long as the device used by those skilled in the art to implement the method in the embodiment of this application falls within the scope of protection to be provided by this application.

[0076] Based on the same inventive concept, this application provides a storage medium corresponding to Example 1, see Example 4 for details.

[0077] Example 4

[0078] like Figure 4 As shown, this embodiment provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, any implementation method in the first embodiment can be implemented.

[0079] The technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: Based on duplicate alarm identification, the present invention further analyzes alarms, not only more accurately identifying duplicate alarms, but also balancing the impact of time factors on previous alarm statistics and further analyzing the caller's emotions. This enhances the comprehensiveness of alarm processing: by comprehensively considering the telephone number, general and special alarm type information, time factors, the caller's emotions, and so on, a more comprehensive and accurate alarm assessment is provided, effectively preventing the generation of derivative alarms.

[0080] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0081] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0082] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0083] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1A step that specifies a function in one or more boxes.

[0084] Although the specific embodiments of the present invention are described above, those skilled in the art should understand that the specific embodiments described are merely illustrative and are not intended to limit the scope of the present invention. Equivalent modifications and changes made by those skilled in the art in accordance with the spirit of the present invention should be included within the scope of protection of the claims of the present invention.

Claims

1. A method for predicting derived alarm situations, characterized in that: The steps include: S1. Receive the current alarm information in real time and perform preliminary analysis to obtain the full alarm information and store it in the alarm information database. The full alarm information includes telephone number, alarm time, alarm content, general alarm type information and special alarm type information; S2, searching the police information database according to the phone number, matching the full amount of police information of all alarm records of the phone number in each preset time period and using it as a judgment set; S3, performing a derived alarm situation prediction analysis on the judgment set, obtaining a prediction analysis result, and displaying and storing it; S4. Determine whether the prediction analysis result meets the warning condition. If so, generate warning information and issue a warning.

2. A method for predicting a derived alarm situation according to claim 1, characterized in that: In S3, the derived warning situation prediction analysis specifically includes the following contents: Calculate basic points: count the number of alarms for the phone number in each time interval, and obtain the basic points corresponding to the number of alarms. The basic points formula = number of alarms per time interval × 1; Calculate the bonus coefficient of the type repetition rate: count the repetition rates of each alarm type in the judgment set, and obtain the corresponding bonus coefficient according to the repetition rate of each alarm type, and the type repetition rate bonus coefficient = the configuration according to the repetition rate; Calculate special police situation points: count the number of special police situations involved and obtain the corresponding special police situation points, special police situation points = number of special police situations × 1; Calculate the time discount coefficient: Look up the table to obtain the time discount coefficient corresponding to each time interval, discount coefficient = obtained from the discount coefficient table, where the longer the time interval, the smaller the discount coefficient, and vice versa; Calculate the derived warning situation prediction score for each time interval: total score = (basic score × type repetition rate coefficient + special warning situation) × discount coefficient of the nth time interval.

3. A method for predicting a derived alarm situation according to claim 1, characterized in that: The special alarm analysis is to perform sensitive word analysis on the alarm content. If the alarm content involves sensitive words corresponding to the special alarm, the alarm content is determined to be a special alarm.

4. The method for predicting a derived alarm situation according to claim 1, characterized in that: The full amount of alarm information also includes the alarm person's emotional level, which is obtained by analyzing the alarm person's voice and tone; the derived alarm prediction analysis also includes the following content: Calculate the caller's emotional level score: look up the table according to the caller's emotional level to obtain the corresponding caller's emotional score; The total score = (basic score × type repetition rate coefficient + special alarm situation + caller's emotional score) × discount coefficient of the nth time interval.

5. A device for predicting derived alarm situations, characterized in that: include: A preliminary analysis module is used to receive the current alarm information in real time and perform preliminary analysis to obtain the full alarm information and store it in the alarm information database. The full alarm information includes telephone number, alarm time, alarm content, general alarm type information and special alarm type information; A search module, used to search the alarm information database according to the phone number, match the full alarm information of all alarm records of the phone number in each preset time period and use it as a judgment set; A prediction analysis module is used to perform a prediction analysis of the derived alarm situation on the judgment set, obtain the prediction analysis results, and display and store them; The early warning module is used to determine whether the prediction analysis results meet the early warning conditions. If so, early warning information is generated and an early warning is issued.

6. The device for predicting derived alarm situations according to claim 5, characterized in that: The derived warning situation prediction analysis specifically includes the following contents: Calculate basic points: count the number of alarms for the phone number in each time interval, and obtain the basic points corresponding to the number of alarms. The basic points formula = number of alarms per time interval × 1; Calculate the bonus coefficient of the type repetition rate: count the repetition rates of each alarm type in the judgment set, and obtain the corresponding bonus coefficient according to the repetition rate of each alarm type, and the type repetition rate bonus coefficient = the configuration according to the repetition rate; Calculate special police situation points: count the number of special police situations involved and obtain the corresponding special police situation points, special police situation points = number of special police situations × 1; Calculate the time discount coefficient: Look up the table to obtain the time discount coefficient corresponding to each time interval, discount coefficient = obtained from the discount coefficient table, where the longer the time interval, the smaller the discount coefficient, and vice versa; Calculate the derived warning situation prediction score for each time interval: total score = (basic score × type repetition rate coefficient + special warning situation) × discount coefficient of the nth time interval.

7. The device for predicting a derived alarm situation according to claim 5, characterized in that: The special alarm analysis is to perform sensitive word analysis on the alarm content. If the alarm content involves sensitive words corresponding to the special alarm, the alarm content is determined to be a special alarm.

8. The device for predicting derived alarm situations according to claim 5, characterized in that: The full amount of alarm information also includes the alarm person's emotional level, which is obtained by analyzing the alarm person's voice and tone; the derived alarm prediction analysis also includes the following content: Calculate the caller's emotional level score: look up the table according to the caller's emotional level to obtain the corresponding caller's emotional score; The total score = (basic score × type repetition rate coefficient + special alarm situation + caller's emotional score) × discount coefficient of the nth time interval.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 4 is implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the method according to any one of claims 1 to 4 is implemented.

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