Data processing method based on point management cloud platform

Abstract

The invention discloses a data processing method based on an integral management cloud platform, and belongs to the technical field of law enforcement data analysis, and the method specifically comprises the steps: setting a monitoring period, dividing the monitoring period into n evaluation periods, and collecting the law enforcement data of any law enforcement officer, inputting the law enforcement data into a preset management platform and carrying out comprehensive scoring to obtain each project score P; drawing a change curve of project scores along with time, calculating a mean value P'of the project scores, obtaining a coordinate point with a score P 'in the change curve, and marking the coordinate point as a reference point; the segmentation values of all the sub-curves are calculated, if the segmentation values are larger than 0, the sub-curves are calibrated as positive curves, and if the segmentation values are smaller than 0, the sub-curves are calibrated as negative curves; and calculating an evaluation score K, and when the evaluation score is greater than or equal to a preset score threshold, determining that the law enforcement effect of the project is good, thereby facilitating the law enforcement level of law enforcement officers.

Description

Technical Field

[0001] The present invention relates to the technical field of law enforcement data analysis, and in particular to a data processing method based on a points management cloud platform. Background Art

[0002] As the types of subjects covered by comprehensive urban management law enforcement increase, and the inspection items become more and more extensive, under the condition of limited law enforcement force, it is necessary to inspect these subjects one by one, and to inspect them item by item according to different types of subjects and their corresponding law enforcement power lists. There are many industry standards and norms in my country, and there may be certain deviations in the inspection process of grassroots law enforcement personnel. In addition, in the process of supervision and law enforcement, due to the large amount of supervision information collected, the grassroots law enforcement personnel have a large workload and low efficiency in processing supervision information, and need to manually process a large amount of data and information, which is not only time-consuming and labor-intensive, but also prone to errors.

[0003] In the field of law enforcement, it is crucial to evaluate and monitor the effectiveness of law enforcement personnel. Traditional methods of evaluating law enforcement effectiveness often rely on manual observation and subjective judgment, which is not only time-consuming and labor-intensive, but also easily affected by personal bias, making it difficult to ensure the accuracy and fairness of the evaluation results. With the development of information technology, it has become a trend to use big data analysis and intelligent algorithms to automatically process and evaluate law enforcement data.

[0004] Existing technologies usually set an evaluation cycle, during which the law enforcement data of law enforcement officers are collected, including law enforcement case information, law enforcement process information, and law enforcement appeal information, etc., and the law enforcement effectiveness of law enforcement officers is evaluated through a comprehensive scoring system. However, these scoring results are often static and holistic, lacking in-depth analysis of the changing trends of law enforcement data, and it is difficult to reveal potential problems in the law enforcement process of law enforcement officers. Summary of the invention

[0005] The purpose of the present invention is to provide a data processing method based on a points management cloud platform to solve the following technical problems:

[0006] Existing technologies usually set an evaluation cycle, during which the law enforcement data of law enforcement officers are collected, including law enforcement case information, law enforcement process information, and law enforcement appeal information, etc., and the law enforcement effectiveness of law enforcement officers is evaluated through a comprehensive scoring system. However, these scoring results are often static and holistic, lacking in-depth analysis of the changing trends of law enforcement data, and it is difficult to reveal potential problems in the law enforcement process of law enforcement officers.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A data processing method based on a points management cloud platform comprises the following steps:

[0009] S1, set a monitoring period and divide the monitoring period into n evaluation periods, collect the law enforcement data of any law enforcement personnel during the evaluation period, input the law enforcement data into a preset management platform and perform a comprehensive score to obtain a score P for each item; the law enforcement data includes law enforcement case information, law enforcement process information and law enforcement complaint information;

[0010] S2, select any project and obtain the project score of the project, draw a curve P(t) of the change of the project score over time with time as the horizontal axis and the project score as the vertical axis, calculate the mean value P' of the project score, obtain all coordinate points with the project score P' in the change curve P(t) and mark them as reference points D1, D2, ..., Dn; D = (ti, P'), where ti is the time corresponding to the i-th reference point;

[0011] S3, dividing the change curve P(t) into several sub-curves with any adjacent reference point as a dividing point, selecting any sub-curve and calculating the dividing value C=P'-max(f(t)), t∈[ti,ti+1], of the sub-curve, wherein ti and ti+1 respectively represent the starting time point and the ending time point of the sub-curve segment, if the dividing value C is greater than 0, the sub-curve is calibrated as a positive curve, and if the dividing value C is less than 0, the sub-curve is calibrated as a negative curve;

[0012] S4, calculate the evaluation score K according to the calculation formula, Wherein, Tz is the time length corresponding to any positive curve, Tf is the time length corresponding to any negative curve; M is the number of all positive curves, m is the number of all negative curves; Czp is the evaluation score corresponding to any positive curve, and Cfu is the evaluation score corresponding to any negative curve, and When the evaluation score is greater than or equal to the preset scoring threshold, it is judged that the law enforcement effect of the project is good.

[0013] As a further solution of the present invention: in S1, the projects include conflict risk resolution, basic prevention, preventable case occurrence, preventable case return, door-to-door work, new business security risk management, entertainment service venue management, key industry supervision, etc.

[0014] As a further solution of the present invention: in S1, the management platform includes a reading module, an acquisition module, and a comprehensive assessment score calculation module. The reading module is used to parse the law enforcement data and set the control and inspection items and law enforcement inspection frequency requirement thresholds corresponding to the law enforcement data for the law enforcement personnel; the acquisition module is used to obtain the law enforcement inspection records and results of the subject based on the control and inspection items and law enforcement inspection frequency requirement thresholds of the law enforcement personnel; the comprehensive assessment score calculation module is used to calculate the comprehensive assessment score of the law enforcement inspection records and results based on pre-established assessment items and scoring rules.

[0015] As a further solution of the present invention: it also includes setting up different law enforcement inspection catalog lists according to the different law enforcement fields of different law enforcement personnel, so that law enforcement personnel can easily check the law enforcement inspection catalog lists during law enforcement inspection activities.

[0016] As a further solution of the present invention: it also includes an audit maintenance module, which is used to make a score appeal after comprehensively scoring the law enforcement data.

[0017] As a further solution of the present invention: in S2, if the mean value of the project scores is greater than or equal to a preset score threshold, the subsequent steps will not be executed and it will be determined that the law enforcement effect of the project is good.

[0018] As a further solution of the present invention: in S2, drawing the curve P(t) of the change of the project score over time also includes taking the first score of the project in the monitoring period as the project score when time t is equal to 0.

[0019] As a further solution of the present invention: if there is a position change of any law enforcement officer during the monitoring period, the subsequent steps will not be executed.

[0020] Beneficial effects of the present invention:

[0021] In the present invention, the law enforcement data of law enforcement personnel are first collected, and the corresponding law enforcement projects are scored according to the law enforcement data, which is the basis for subsequent processing; it is worth noting that the behavioral data includes but is not limited to the resolution of conflict risks, basic prevention, the occurrence of preventable cases, the return of preventable cases, door-to-door work, new business security risk management, entertainment service venue management, key industry supervision, etc., so as to comprehensively reflect the performance of law enforcement personnel in enforcing a certain project; draw a project score change curve to calculate the mean of the project score and determine the reference point; it can be understood that this mean reflects the average law enforcement level of law enforcement personnel during the entire monitoring period, provides a benchmark point for further analysis, and can reflect the trend of the students' law enforcement effectiveness; then calculate the segmentation value, and determine the curve and the negative curve; the preferred score Cz is calculated according to the positive curve, and the difference score Cf is calculated according to the negative curve. It should be noted that the larger the preferred score, the better the law enforcement effect of the law enforcement personnel, and the larger the difference score, the worse the law enforcement effect of the law enforcement personnel; finally, the evaluation score is comprehensively calculated, and the law enforcement level of the corresponding law enforcement project is determined according to the evaluation score; it is worth noting that the longer the duration corresponding to the positive curve, the more time the law enforcement effect of the law enforcement personnel is greater than the average law enforcement level during the law enforcement process, which can reflect that the law enforcement effect of the law enforcement project is better; the longer the duration corresponding to the negative curve, the more time the law enforcement effect of the law enforcement personnel is less than the average law enforcement level during the law enforcement process, which reflects that the law enforcement effect of the law enforcement project is poor. The present invention can evaluate the law enforcement efficiency of different law enforcement projects, remind attention to law enforcement projects with poor law enforcement effects, and improve the law enforcement level. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The present invention will be further described below in conjunction with the accompanying drawings.

[0023] Figure 1 It is a flow chart of a data processing method based on a points management cloud platform of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1 As shown, the present invention is a data processing method based on a points management cloud platform, comprising the following steps:

[0026] S1, set a monitoring period and divide the monitoring period into n evaluation periods, collect the law enforcement data of any law enforcement personnel during the evaluation period, input the law enforcement data into a preset management platform and perform a comprehensive score to obtain a score P for each item; the law enforcement data includes law enforcement case information, law enforcement process information and law enforcement complaint information;

[0027] S2, select any project and obtain the project score of the project, draw a curve P(t) of the change of the project score over time with time as the horizontal axis and the project score as the vertical axis, calculate the mean value P' of the project score, obtain all coordinate points with the project score P' in the change curve P(t) and mark them as reference points D1, D2, ..., Dn; D = (ti, P'), where ti is the time corresponding to the i-th reference point;

[0028] S3, dividing the change curve P(t) into several sub-curves with any adjacent reference point as a dividing point, selecting any sub-curve and calculating the dividing value C=P'-max(f(t)), t∈[ti,ti+1], of the sub-curve, wherein ti and ti+1 respectively represent the starting time point and the ending time point of the sub-curve segment, if the dividing value C is greater than 0, the sub-curve is calibrated as a positive curve, and if the dividing value C is less than 0, the sub-curve is calibrated as a negative curve;

[0029] S4, calculate the evaluation score K according to the calculation formula, Wherein, Tz is the time length corresponding to any positive curve, Tf is the time length corresponding to any negative curve; M is the number of all positive curves, m is the number of all negative curves; Czp is the evaluation score corresponding to any positive curve, and Cfu is the evaluation score corresponding to any negative curve, and When the evaluation score is greater than or equal to the preset scoring threshold, it is judged that the law enforcement effect of the project is good.

[0030] In the present invention, the law enforcement data of law enforcement personnel are first collected, and the corresponding law enforcement projects are scored according to the law enforcement data, which is the basis for subsequent processing; it is worth noting that the behavioral data includes but is not limited to the resolution of conflict risks, basic prevention, the occurrence of preventable cases, the return of preventable cases, door-to-door work, new business security risk management, entertainment service venue management, key industry supervision, etc., so as to comprehensively reflect the performance of law enforcement personnel in enforcing a certain project; draw a project score change curve to calculate the mean of the project score and determine the reference point; it can be understood that this mean reflects the average law enforcement level of law enforcement personnel during the entire monitoring period, provides a benchmark point for further analysis, and can reflect the trend of the students' law enforcement effectiveness; then calculate the segmentation value, and determine the curve and the negative curve; the preferred score Cz is calculated according to the positive curve, and the difference score Cf is calculated according to the negative curve. It should be noted that the larger the preferred score, the better the law enforcement effect of the law enforcement personnel, and the larger the difference score, the worse the law enforcement effect of the law enforcement personnel; finally, the evaluation score is comprehensively calculated, and the law enforcement level of the corresponding law enforcement project is determined according to the evaluation score; it is worth noting that the longer the duration corresponding to the positive curve, the more time the law enforcement effect of the law enforcement personnel is greater than the average law enforcement level during the law enforcement process, which can reflect that the law enforcement effect of the law enforcement project is better; the longer the duration corresponding to the negative curve, the more time the law enforcement effect of the law enforcement personnel is less than the average law enforcement level during the law enforcement process, which reflects that the law enforcement effect of the law enforcement project is poor. The present invention can evaluate the law enforcement efficiency of different law enforcement projects, remind attention to law enforcement projects with poor law enforcement effects, and improve the law enforcement level.

[0031] In a preferred embodiment of the present invention, in S1, the projects include conflict risk resolution, basic prevention, preventable case occurrence, preventable case return, door-to-door work, new business security risk management, entertainment service venue management, key industry supervision, etc.

[0032] In another preferred embodiment of the present invention, in S1, the management platform includes a reading module, an acquisition module, and a comprehensive assessment score calculation module. The reading module is used to parse the law enforcement data and set the control and inspection items and law enforcement inspection frequency requirement thresholds corresponding to the law enforcement data for the law enforcement personnel; the acquisition module is used to obtain the law enforcement inspection records and results of the subject based on the control and inspection items and law enforcement inspection frequency requirement thresholds of the law enforcement personnel; the comprehensive assessment score calculation module is used to calculate the comprehensive assessment score for the law enforcement inspection records and results based on pre-established assessment items and scoring rules.

[0033] Through automated data processing, law enforcement data can be quickly classified and analyzed, ensuring the rapid circulation and efficient use of information. According to the control inspection items and frequency requirement thresholds, law enforcement inspection records and results can be obtained in real time, which helps to timely understand the implementation of law enforcement activities and make corresponding adjustments. According to the pre-established assessment items and scoring rules, the comprehensive assessment scores of law enforcement inspection records and results are automatically calculated, realizing the automation of the evaluation process. Automated calculation reduces the interference of human factors, ensures the objectivity and consistency of the evaluation, and improves the efficiency of the evaluation work. The modular design of the management platform makes the reading, acquisition and evaluation of law enforcement data a complete process. Each module has a specific function, ensuring the scientificity and systematicness of the entire law enforcement management system.

[0034] In another preferred embodiment of the present invention, different law enforcement inspection catalog lists are set up according to the different law enforcement fields of different law enforcement personnel, so that law enforcement personnel can easily check the law enforcement inspection catalog lists during law enforcement inspection activities.

[0035] In another preferred embodiment of the present invention, it also includes an audit and maintenance module for making score appeals after comprehensively scoring the law enforcement data.

[0036] In another preferred embodiment of the present invention, in S2, if the mean value of the project scores is greater than or equal to a preset score threshold, the subsequent steps will not be executed and it will be determined that the law enforcement effect of the project is good.

[0037] It is understandable that this indicates that the law enforcement officer has an overall high project score for the project, which can reflect that the law enforcement effect of the law enforcement officer is good and there is no need to perform subsequent steps, thereby saving computing resources and improving processing efficiency.

[0038] In another preferred embodiment of the present invention, in said S2, drawing the curve P(t) of the change of the project score over time further includes taking the first score of the project in the monitoring period as the project score when time t is equal to 0.

[0039] In another preferred embodiment of the present invention, if there is a position change of any law enforcement officer during the monitoring period, the subsequent steps will not be executed.

[0040] It is understandable that changes in law enforcement officers’ positions may affect their job content and responsibilities, making the assessment results based on the original position no longer applicable. By not performing subsequent assessment steps, inaccurate or inconsistent assessment results caused by position changes can be avoided.

[0041] The above is a detailed description of an embodiment of the present invention, but the content is only a preferred embodiment of the present invention and cannot be considered to limit the scope of implementation of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A data processing method based on a points management cloud platform, characterized in that: The following steps are involved: S1, set a monitoring period and divide the monitoring period into n evaluation periods, collect the law enforcement data of any law enforcement personnel during the evaluation period, input the law enforcement data into a preset management platform and perform a comprehensive score to obtain a score P for each item; the law enforcement data includes law enforcement case information, law enforcement process information and law enforcement complaint information; S2, select any project and obtain the project score of the project, draw a curve P(t) of the change of the project score over time with time as the horizontal axis and the project score as the vertical axis, calculate the mean value P' of the project score, obtain all coordinate points with the project score P' in the change curve P(t) and mark them as reference points D1, D2, ..., Dn; D = (ti, P'), where ti is the time corresponding to the i-th reference point; S3, dividing the change curve P(t) into several sub-curves with any adjacent reference point as a dividing point, selecting any sub-curve and calculating the dividing value C=P'-max(f(t)), t∈[ti,ti+1], of the sub-curve, wherein ti and ti+1 respectively represent the starting time point and the ending time point of the sub-curve segment, if the dividing value C is greater than 0, the sub-curve is calibrated as a positive curve, and if the dividing value C is less than 0, the sub-curve is calibrated as a negative curve; S4, calculate the evaluation score K according to the calculation formula, Wherein, Tz is the time length corresponding to any positive curve, Tf is the time length corresponding to any negative curve; M is the number of all positive curves, m is the number of all negative curves; Czp is the evaluation score corresponding to any positive curve, and Cfu is the evaluation score corresponding to any negative curve, and When the evaluation score is greater than or equal to the preset scoring threshold, it is judged that the law enforcement effect of the project is good.

2. A data processing method based on a points management cloud platform according to claim 1, characterized in that: In S1, the projects include conflict risk resolution, basic prevention, preventable case occurrence, preventable case handling, door-to-door work, new business security risk management, entertainment service venue management, and key industry supervision.

3. A data processing method based on a points management cloud platform according to claim 1, characterized in that: In S1, the management platform includes a reading module, an acquisition module, and a comprehensive assessment score calculation module. The reading module is used to parse the law enforcement data and set the control and inspection items and law enforcement inspection frequency requirement thresholds corresponding to the law enforcement data for law enforcement personnel; the acquisition module is used to obtain the law enforcement inspection records and results of the subject based on the control and inspection items and law enforcement inspection frequency requirement thresholds of the law enforcement personnel; the comprehensive assessment score calculation module is used to calculate the comprehensive assessment score of the law enforcement inspection records and results based on pre-established assessment items and scoring rules.

4. A data processing method based on a points management cloud platform according to claim 3, characterized in that: It also includes setting up different law enforcement inspection catalog lists according to the different law enforcement areas of different law enforcement personnel, so that law enforcement personnel can easily check the law enforcement inspection catalog lists during law enforcement inspection activities.

5. The data processing method based on the points management cloud platform according to claim 3 is characterized in that: It also includes an audit and maintenance module for making score appeals after comprehensively scoring the law enforcement data.

6. The data processing method based on the points management cloud platform according to claim 1 is characterized in that: In S2, if the mean value of the project scores is greater than or equal to the preset score threshold, the subsequent steps will not be executed and it will be determined that the law enforcement effect of the project is good.

7. The data processing method based on the points management cloud platform according to claim 1 is characterized in that: In S2, drawing the curve P(t) of the change of the project score over time also includes taking the first score of the project in the monitoring period as the project score when time t is equal to 0.

8. The data processing method based on the points management cloud platform according to claim 1 is characterized in that: It also includes that if any law enforcement officer changes his position during the monitoring period, the subsequent steps will not be executed.

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