Artificial Intelligence Access Control Management System

Abstract

The invention discloses an artificial intelligence access control management system, which belongs to the technical field of unmanned access control supervision; it is used to solve the technical problems of poor experience and safety autonomous supervision effect of unmanned access control operation, as well as poor autonomous optimization management and risk prevention management effect in existing solutions; it supervises and processes and analyzes the single start-up operation data of each operation of the unmanned access control, obtains the single start-up operation state and digital data of the unmanned access control start-up operation, implements different aspects of abnormal impact tracking and evaluation on the single start-up operation abnormal state obtained by the unmanned access control single start-up operation supervision processing, and adaptively implements targeted experience optimization management and risk prevention management for the unmanned access control according to the evaluation result, and adaptively implements different aspects of management measures, thereby improving the experience and safety autonomous supervision effect, autonomous optimization management and risk prevention management effect of the unmanned access control operation.

Description

Technical Field

[0001] The present invention relates to the technical field of unmanned access control monitoring, and in particular to an artificial intelligence access control management system. Background Art

[0002] The existing unmanned store access control management system may encounter a series of challenges and problems in actual application, which may affect the system performance, user experience, and overall security and reliability. When implementing the existing unmanned store access control management solution, it is unable to conduct supervision and analysis on the operation of the unmanned access control from different dimensions, and adaptively implement targeted optimization management and risk prevention management based on the results of supervision and analysis, resulting in poor experience and safety autonomous supervision of the operation of the unmanned access control, as well as poor autonomous optimization management and risk prevention management. Summary of the invention

[0003] The purpose of the present invention is to provide an artificial intelligence access control management system to solve the technical problems in existing solutions, such as poor experience of unmanned access control operation and poor autonomous security supervision, as well as poor autonomous optimization management and risk prevention management.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] An artificial intelligence access control management system, including a cloud platform, and an access control opening operation supervision processing module and an access control opening operation abnormality assessment management module connected to the cloud platform in communication;

[0006] The access control opening and operation supervision and processing module is used to supervise and process the single opening and operation data of each operation of the unmanned access control, and to perform data analysis and combination on the single opening and operation processing data to determine the single opening and operation status of the unmanned access control opening and operation; wherein the single opening and operation status includes a single opening and operation normal status or a single opening and operation abnormal status;

[0007] Conduct a retrospective analysis on the single opening operation abnormality type of the unmanned access control, and obtain the opening response type abnormality, opening operation type abnormality and / or opening safety type abnormality corresponding to the unmanned access control;

[0008] The access control opening operation abnormality assessment management module is used to implement abnormal impact tracking and assessment of different aspects of the single opening operation abnormal status obtained by the unmanned access control single opening operation supervision processing, and adaptively implement targeted experience optimization management and risk prevention management for the unmanned access control opening reaction, opening operation and opening safety according to the assessment results;

[0009] Among them, the analysis of the abnormal state of a single opening operation is used to conduct supervision analysis of the impact of local abnormalities of different types of abnormalities on the unmanned access control system, and the special abnormalities marked by the analysis are immediately managed for experience optimization or risk prevention;

[0010] Based on the analysis of the abnormal status of a single opening operation, an overall abnormal impact supervision analysis of all types of abnormalities is performed on the unmanned access control. Based on the analysis results, the existing operation and maintenance plan of the unmanned access control is maintained, or the operation and maintenance of the unmanned access control is immediately implemented.

[0011] Preferably, when a person is detected entering the target area, a control instruction is generated, and the control generation time point corresponding to the control instruction is obtained, and the door access is automatically opened according to the control instruction, and the opening time point of the door access automatically opened and the pause time point of the door access after being fully opened are monitored and obtained;

[0012] The control generation time point, the start time point and the pause time point are sorted and combined to obtain the single opening operation data of the unmanned access control;

[0013] The single opening operation data of each opening of the unmanned access control is calculated by the formula The corresponding single opening validity DKx is calculated; where TS, TC, and TZ are the control generation time point, opening time point, and pause time point respectively; TB1 and TB2 are the opening reaction standard time and the opening operation standard time respectively; α is the safety impact coefficient; A, B, and C are all positive integers and are all different; is the floor function.

[0014] Preferably, data analysis is performed on the single opening validity to determine the single opening operation status of the unmanned access control;

[0015] If the single-open validity is 3, a single-open normal operation state is generated;

[0016] If the single opening validity is not 3, a single opening operation abnormality state is generated, and the single opening operation abnormality type of the unmanned access control is traced and analyzed.

[0017] Preferably, data analysis is performed on different calculation items in the single-opening validity calculation formula. , and / or , then an opening reaction type exception, an opening operation type exception and / or an opening safety type exception corresponding to the unmanned access control is generated.

[0018] Preferably, the step of obtaining the safety impact coefficient includes:

[0019] Based on the detection of the detection sensor, all sound detection data and all vibration detection data of each opening process of the unmanned access control are obtained, and all sound detection data and all vibration detection data are displayed and connected through the pre-constructed first coordinate system and the second coordinate system respectively to obtain the opening sound detection curve and the opening vibration detection curve;

[0020] Acquire a first abnormal area in the opening sound detection curve that is larger than the opening sound standard straight line and enclosed by the opening sound standard straight line, and acquire a second abnormal area in the opening vibration detection curve that is larger than the opening vibration standard straight line and enclosed by the opening vibration standard straight line;

[0021] If neither the first abnormal area nor the second abnormal area exists, the safety impact coefficient α corresponding to the single opening process of the unmanned access control is set to 0.

[0022] Preferably, if the first abnormal region and / or the second abnormal region exists, the areas corresponding to all the first abnormal regions are obtained and summed to obtain a first abnormal detection value Y1, and the areas corresponding to all the second abnormal regions are obtained and summed to obtain a second abnormal detection value Y2;

[0023] The first anomaly detection value and the second anomaly detection value are calculated by the formula Calculate and obtain the safety impact coefficient α corresponding to each opening process of the unmanned access control; where a and b are different proportional coefficients, and a∈(0,1), b∈(2,3).

[0024] Preferably, when performing the local abnormal impact supervision analysis of different types of abnormalities on the unmanned access control according to the single opening operation abnormal state obtained by analysis, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities obtained by the opening operation supervision of the unmanned access control are counted, and the local abnormal impact values ​​corresponding to different types of abnormalities are obtained by formula calculation;

[0025] If the local anomaly impact value is greater than or equal to 1.27, the anomaly of the corresponding type will be marked as a special anomaly, and experience optimization management or risk prevention management will be immediately performed on the special anomaly.

[0026] Preferably, the calculation formula for the local abnormality impact value corresponding to different types of abnormalities is: ; In the formula, JYk is the local abnormality impact value corresponding to different types of abnormalities; k=1, 2, 3, respectively, the opening reaction type abnormality, the opening operation type abnormality and the opening safety type abnormality; NJk is NJ1, NJ2, NJ3, respectively, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities; NZ is the total number of opening operations of unmanned access control after the verification and evaluation instructions; YBk is YB1, YB2, YB3, respectively, the opening reaction abnormality limit value, the opening operation abnormality limit value and the opening safety abnormality limit value.

[0027] Preferably, when performing overall abnormal impact supervision analysis on all types of abnormalities of the unmanned access control based on the single abnormal operation status obtained through analysis, the local abnormal impact values ​​corresponding to all types of abnormalities are calculated by formula to obtain the operation and maintenance implementation value corresponding to the opening of the unmanned access control;

[0028] If the operation and maintenance implementation value is greater than or equal to 1, operation and maintenance will be implemented immediately for the unmanned access control.

[0029] Preferably, the calculation formula of the operation and maintenance implementation value is: ; In the formula, YS is the operation and maintenance implementation value; c1, c2, c3 are all calculation impact factors greater than 0, and c1+c2+c3=1; D is the operation and maintenance implementation limit value.

[0030] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0031] The present invention obtains the single start-up operation status and digital data of the unmanned access control by supervising, processing and analyzing the single start-up operation data of each time the unmanned access control is operated. This can not only realize the supervision and processing and analysis of the single start-up operation status of each time the unmanned access control is turned on, but also provide reliable local supervision and analysis data support for the subsequent autonomous risk prevention management of the unmanned access control.

[0032] The present invention implements different aspects of abnormal impact tracking and evaluation on the abnormal status of single opening and operation obtained through the supervision processing of unmanned access control, and adaptively implements targeted experience optimization management and risk prevention management for the unmanned access control according to the evaluation results, thereby realizing a comprehensive supervision and analysis of the opening and operation of unmanned access control, and adaptively implementing management measures in different aspects, thereby improving the experience of unmanned access control operation and the effect of autonomous safety supervision, autonomous optimization management and risk prevention management. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] The present invention will be further described below in conjunction with the accompanying drawings.

[0034] Figure 1 This is a module block diagram of the artificial intelligence access control management system of the present invention.

[0035] Figure 2 This is a flowchart of the operation of the artificial intelligence access control management system of the present invention.

[0036] Figure 3 It is a flowchart of data analysis of single-opening validity in the present invention. DETAILED DESCRIPTION

[0037] 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.

[0038] like Figure 1 to Figure 2 As shown, the present invention is an artificial intelligence access control management system, including a cloud platform, and an access control opening operation supervision processing module and an access control opening operation abnormality assessment management module connected to the cloud platform in communication; the communication connection can be a wired connection and / or a wireless connection;

[0039] The access control opening and operation supervision and processing module is used to supervise and process the single opening and operation data of each operation of the unmanned access control, and to analyze and combine the single opening and operation processing data to determine the single opening and operation status of the unmanned access control opening and operation; including:

[0040] When someone is detected entering the target area, a control instruction is generated. The target area is set up in front of and behind the door, and detection sensors, such as infrared sensors, are set up in the area. When a person moves to the target area, the access control is automatically opened, saving the waiting time for the person to reach the door and then open the access control. The specific length and width of the target area can be customized according to the actual size of the unmanned access control, and there is no restriction here. The control generation time point corresponding to the control instruction is obtained, and the access control is controlled to open automatically according to the control instruction. At the same time, the opening time point of the access control is monitored and obtained, as well as the pause time point of the access control after it is fully opened; the units of different time points are accurate to seconds;

[0041] The control generation time point, the start time point and the pause time point are sorted and combined to obtain the single opening operation data of the unmanned access control;

[0042] In the embodiment of the present invention, by monitoring and collecting statistics on various data each time the unmanned access control is turned on and off, reliable multi-dimensional supervision data support can be provided for the subsequent status analysis of different aspects of the unmanned access control turn-on and off operation.

[0043] The single opening operation data of each opening of the unmanned access control is calculated by the formula The corresponding single opening validity DKx is calculated; in the formula, TS, TC, and TZ are the control generation time point, the opening time point, and the pause time point respectively; TB1 and TB2 are the opening reaction standard time and the opening operation standard time respectively, which can be determined according to the operation design requirement data of the unmanned access control, or according to the preliminary test data of the unmanned access control; α is the safety impact coefficient; A, B, and C are all positive integers, and they are all different, and there is no limit on the specific values; is the floor rounding function;

[0044] It should be noted that the single opening validity is used to integrate and calculate various monitoring data when the unmanned access control is opened and operated once, so as to digitally represent the single opening operation status of the unmanned access control;

[0045] The steps for obtaining the safety impact factor include:

[0046] Based on the detection of the detection sensor, all the sound detection data and all the vibration detection data of each opening process of the unmanned access control are obtained. The detection sensor can be a number of sound sensors and vibration sensors installed on the access control, and all the sound detection data and all the vibration detection data are respectively displayed and connected through the pre-constructed first coordinate system and the second coordinate system to obtain the opening sound detection curve and the opening vibration detection curve; it can be understood that the shaking and noise problems of the automatic glass door during the opening process not only affect the user experience, but also may indicate potential safety hazards or mechanical failures; in addition, all the sound detection data need to be pre-processed to eliminate irrelevant detection sounds, such as the walking and talking sounds of people. Pre-processing all the sound detection data is an existing conventional technical means, and the specific steps are not repeated here;

[0047] The horizontal axes of the first coordinate system and the second coordinate system are both time points that change in real time, with units accurate to seconds, and the vertical axes are respectively the sound detection difference and the vibration detection difference that change arbitrarily, and both the sound detection difference and the vibration detection difference can be determined by the previous test data;

[0048] A first abnormal area is obtained which is larger than the opening sound standard straight line in the opening sound detection curve and is surrounded by the opening sound standard straight line, and a second abnormal area is obtained which is larger than the opening vibration standard straight line and is surrounded by the opening vibration standard straight line in the opening vibration detection curve; the opening sound standard straight line and the opening vibration standard straight line are determined according to the operational design requirement data of the unmanned access control;

[0049] If neither the first abnormal area nor the second abnormal area exists, the safety impact coefficient α corresponding to the single opening process of the unmanned access control is set to 0;

[0050] If the first abnormal region and / or the second abnormal region exists, the areas corresponding to all the first abnormal regions are obtained and summed to obtain a first abnormal detection value Y1, and the areas corresponding to all the second abnormal regions are obtained and summed to obtain a second abnormal detection value Y2;

[0051] The first anomaly detection value and the second anomaly detection value are calculated by the formula Calculate and obtain the safety impact coefficient α corresponding to each opening process of the unmanned access control; where a and b are different proportional coefficients, and a∈(0,1), a can be taken as 0.74, and b∈(2,3), b can be taken as 1.51;

[0052] It should be noted that the safety impact coefficient is used to integrate and calculate the sound detection data and vibration detection data generated during the unmanned access control opening operation process to digitally represent the safety impact status corresponding to the unmanned access control opening process;

[0053] like Figure 3 As shown, the single opening validity is analyzed to determine the single opening operation status of the unmanned access control;

[0054] If the single-open validity is 3, a single-open normal operation state is generated;

[0055] If the single opening validity is not 3, a single opening operation abnormality state is generated, and the single opening operation abnormality type of the unmanned access control is traced and analyzed;

[0056] Data analysis is performed on different calculation items in the single-opening validity calculation formula. , and / or , then an opening reaction type exception, an opening operation type exception and / or an opening safety type exception corresponding to the unmanned access control is generated;

[0057] In the embodiment of the present invention, by supervising and processing and analyzing the single start-up operation data of the unmanned access control each time it is operated, the single start-up operation status and digital data of the unmanned access control can be obtained, which can not only realize the supervision and processing and analysis of the single start-up operation status of the unmanned access control each time it is opened and operated, but also provide reliable local supervision and analysis data support for the subsequent autonomous risk prevention management of the unmanned access control.

[0058] The access control opening operation abnormality assessment management module is used to implement different aspects of abnormal impact tracking and assessment on the single opening operation abnormal state obtained by the unmanned access control single opening operation supervision processing, and adaptively implement targeted experience optimization management and risk prevention management for the unmanned access control opening reaction, opening operation and opening safety according to the assessment results; including:

[0059] When analyzing the impact of different types of abnormalities on the local abnormality of unmanned access control according to the single abnormal state of opening operation obtained by analysis, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities obtained by the unmanned access control opening operation supervision are counted, and the formula is used to calculate the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities. Calculate and obtain the local abnormal impact value JYk corresponding to different types of abnormalities; where k=1, 2, 3, respectively, are the opening reaction type abnormality, opening operation type abnormality and opening safety type abnormality; NJk is NJ1, NJ2, NJ3, respectively, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities; NZ is the total number of opening operations of the unmanned access control after the verification and evaluation instructions; YBk is YB1, YB2, YB3, respectively, the opening reaction abnormality limit value, the opening operation abnormality limit value and the opening safety abnormality limit value, which can be determined according to the operation design requirement data of the unmanned access control;

[0060] It should be noted that the local anomaly impact value is used to integrate and calculate the local supervision processing data of the same type of anomalies to digitally represent the local anomaly state corresponding to the type of anomaly;

[0061] If the local anomaly impact value is less than 1.27, the anomaly of the corresponding type is marked as a regular anomaly;

[0062] If the local abnormality impact value is greater than or equal to 1.27, the abnormality of the corresponding type will be marked as a special abnormality, and the special abnormality will be immediately managed for experience optimization or risk prevention;

[0063] Among them, if the special exception is an opening reaction type exception or an opening operation type exception, experience optimization management is carried out; if the special exception is an opening safety type exception, risk prevention management is carried out;

[0064] When analyzing the overall abnormal impact of all types of abnormalities on unmanned access control based on the single abnormal operation status obtained by analysis, the local abnormal impact values ​​corresponding to all types of abnormalities are calculated by the formula Calculate and obtain the operation and maintenance implementation value YS corresponding to the opening of the unmanned access control; where c1, c2, and c3 are all calculation influence factors greater than 0, and c1+c2+c3=1; c1 can be taken as 0.23, c2 can be taken as 0.35, and c3 can be taken as 0.42; D is the operation and maintenance implementation limit value, which can be determined based on the operational design requirement data of the unmanned access control, or based on the preliminary test data of the unmanned access control;

[0065] It should be noted that the operation and maintenance implementation value is used to integrate and calculate all types of abnormal data during the opening and operation of the unmanned access control system, so as to digitally represent the necessary state of operation and maintenance implementation of the existing opening and operation of the unmanned access control system;

[0066] If the operation and maintenance implementation value is less than 1, the existing operation and maintenance plan of unmanned access control is maintained;

[0067] If the operation and maintenance implementation value is greater than or equal to 1, operation and maintenance will be implemented immediately for the unmanned access control.

[0068] In the embodiment of the present invention, by implementing different aspects of abnormal impact tracking and evaluation on the abnormal state of single opening and operation obtained through the supervision processing of the unmanned access control, and adaptively implementing targeted experience optimization management and risk prevention management for the unmanned access control according to the evaluation results, a comprehensive supervision and analysis of the opening and operation of the unmanned access control is achieved, and management measures in different aspects are adaptively implemented, thereby improving the experience of the unmanned access control operation and the effect of autonomous safety supervision, autonomous optimization management and risk prevention management.

[0069] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0070] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0071] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0072] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0073] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0074] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. Artificial intelligence access control management system, characterized by: It includes a cloud platform, and a door access control opening operation supervision processing module and a door access control opening operation abnormality assessment management module connected to the cloud platform in communication; The access control opening and operation supervision and processing module is used to supervise and process the single opening and operation data of each operation of the unmanned access control, and to perform data analysis and combination on the single opening and operation processing data to determine the single opening and operation status of the unmanned access control opening and operation; wherein, when a person is detected to enter the target area, a control instruction is generated, and the control generation time point corresponding to the control instruction is obtained, and the access control is controlled to open automatically according to the control instruction, and at the same time, the opening time point of the automatic opening of the access control and the pause time point of the pause after the access control is fully opened are monitored and obtained; The control generation time point, the start time point and the pause time point are sorted and combined to obtain the single opening operation data of the unmanned access control; The single opening operation data of each opening of the unmanned access control is calculated by the formula The corresponding single opening validity DKx is calculated; where TS, TC, and TZ are the control generation time point, opening time point, and pause time point respectively; TB1 and TB2 are the opening reaction standard time and the opening operation standard time respectively; α is the safety impact coefficient; A, B, and C are all positive integers and are all different; is the floor rounding function; Perform data analysis on the single opening validity to determine the single opening operation status of the unmanned access control; the single opening operation status includes a single opening operation normal state or a single opening operation abnormal state; Conduct a retrospective analysis on the single opening operation abnormality type of the unmanned access control, and obtain the opening response type abnormality, opening operation type abnormality and / or opening safety type abnormality corresponding to the unmanned access control; The access control opening operation abnormality assessment management module is used to implement different aspects of abnormal impact tracking and assessment on the single opening operation abnormality status obtained by the unmanned access control single opening operation supervision processing, and adaptively implement targeted experience optimization management and risk prevention management for the unmanned access control opening reaction abnormality, opening operation abnormality and opening safety abnormality according to the assessment results; Among them, the analysis of the abnormal state of a single opening operation is used to conduct supervision analysis of the impact of local abnormalities of different types of abnormalities on the unmanned access control system, and the special abnormalities marked by the analysis are immediately managed for experience optimization or risk prevention; Based on the analysis of the abnormal status of a single opening operation, an overall abnormal impact supervision analysis of all types of abnormalities is performed on the unmanned access control. Based on the analysis results, the existing operation and maintenance plan of the unmanned access control is maintained, or the operation and maintenance of the unmanned access control is immediately implemented.

2. The artificial intelligence access control management system according to claim 1 is characterized in that: Data analysis is performed on different calculation items in the single-opening validity calculation formula. , then an open security type exception corresponding to unmanned access control is generated.

3. The artificial intelligence access control management system according to claim 1 is characterized in that: The steps for obtaining the safety impact factor include: Based on the detection of the detection sensor, all sound detection data and all vibration detection data of each opening process of the unmanned access control are obtained, and all sound detection data and all vibration detection data are displayed and connected through the pre-constructed first coordinate system and the second coordinate system respectively to obtain the opening sound detection curve and the opening vibration detection curve; Acquire a first abnormal area in the opening sound detection curve that is larger than the opening sound standard straight line and enclosed by the opening sound standard straight line, and acquire a second abnormal area in the opening vibration detection curve that is larger than the opening vibration standard straight line and enclosed by the opening vibration standard straight line; If neither the first abnormal area nor the second abnormal area exists, the safety impact coefficient α corresponding to the single opening process of the unmanned access control is set to 0.

4. The artificial intelligence access control management system according to claim 3 is characterized in that: If the first abnormal region and / or the second abnormal region exists, the areas corresponding to all the first abnormal regions are obtained and summed to obtain a first abnormal detection value Y1, and the areas corresponding to all the second abnormal regions are obtained and summed to obtain a second abnormal detection value Y2; The first anomaly detection value and the second anomaly detection value are calculated by the formula Calculate and obtain the safety impact coefficient α corresponding to each opening process of the unmanned access control; where a and b are different proportional coefficients, and a∈(0,1), b∈(2,3).

5. The artificial intelligence access control management system according to claim 1 is characterized in that: When analyzing the local abnormal impact of different types of abnormalities on the unmanned access control based on the single abnormal state of opening and operation obtained by analysis, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities obtained by the unmanned access control opening and operation supervision are counted, and the local abnormal impact values ​​corresponding to different types of abnormalities are obtained through formula calculation; the calculation formula for the local abnormal impact values ​​corresponding to different types of abnormalities is: ; In the formula, JYk is the local abnormality impact value corresponding to different types of abnormalities; k=1, 2, 3, respectively, the opening reaction type abnormality, the opening operation type abnormality and the opening safety type abnormality; NJk is NJ1, NJ2, NJ3, respectively, the total number of opening reaction type abnormalities, the total number of opening operation type abnormalities and the total number of opening safety type abnormalities; NZ is the total number of opening operations of unmanned access control after the verification and evaluation instructions; YBk is YB1, YB2, YB3, respectively, the opening reaction abnormality limit value, the opening operation abnormality limit value and the opening safety abnormality limit value; If the local anomaly impact value is greater than or equal to 1.27, the anomaly of the corresponding type will be marked as a special anomaly, and experience optimization management or risk prevention management will be immediately performed on the special anomaly.

6. The artificial intelligence access control management system according to claim 5 is characterized in that: When conducting overall abnormal impact supervision analysis on all types of abnormalities for unmanned access control based on the single abnormal operation status obtained through analysis, the local abnormal impact values ​​corresponding to all types of abnormalities are calculated through formulas to obtain the operation and maintenance implementation value corresponding to the opening of unmanned access control; the calculation formula for the operation and maintenance implementation value is: ; In the formula, YS is the operation and maintenance implementation value; c1, c2, c3 are all calculation impact factors greater than 0, and c1+c2+c3=1; D is the operation and maintenance implementation limit value; If the operation and maintenance implementation value is greater than or equal to 1, operation and maintenance will be implemented immediately for the unmanned access control.

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