Park-oriented access control automatic control management system

Abstract

This invention provides an automated access control management system for industrial parks, belonging to the field of automated management technology. The method includes: matching the identities of park management personnel to generate a personnel management information set; identifying and recording multiple target vehicles entering and exiting the target park to generate a target vehicle information database; retrieving the authorized personnel information database and traversing the target vehicle information database to perform permission association verification; generating an association verification dataset for real-time access monitoring of the target park; generating a park monitoring record set for data statistical analysis; and performing intelligent access control management of the target park. This invention solves the technical problem of high access control management costs in target parks due to the lack of access control for personnel and vehicles entering and exiting the park in existing technologies. It achieves rational and accurate intelligent identification and permission management of personnel and vehicles within the park, reducing the cost of access control management.

Description

Technical Field

[0001] This invention relates to the field of automatic management technology, specifically to an automatic access control management system for industrial parks. Background Technology

[0002] As an important part of modern urbanization, industrial parks are developing in scale, especially in the area of ​​access control. At the same time, as parks continue to expand and population mobility increases, traditional access control methods lack the ability to control personnel and vehicles entering and leaving the park, leading to high technical costs for access control management in target parks. Summary of the Invention

[0003] This application provides an automatic access control management system for industrial parks, which solves the technical problem of high access control management costs in target industrial parks due to the lack of access control for personnel and vehicles entering and exiting the park in existing technologies. It realizes rational and accurate intelligent identification and access management of personnel and vehicles in the park, thereby reducing the access control management cost of the park.

[0004] In view of the above problems, this application provides an automatic access control management system and method for industrial parks.

[0005] Firstly, this application provides an automatic access control management system for a park, the system comprising: a first matching module, used to generate a personnel management information set by matching the identities of park management personnel; an authorization management module, used to obtain an authorized personnel information database, which is obtained by authorizing the personnel management information set; an identification and recording module, used to identify and record multiple target vehicles entering and exiting the target park, generating a target vehicle information database; and a first verification module, used to retrieve the authorized personnel information database and traverse the target vehicle information database to perform access control. The system comprises: a joint verification module to generate a joint verification dataset; a first monitoring module to perform real-time access monitoring of the target park based on the joint verification dataset and generate a park monitoring record set; a first analysis module to extract personnel and vehicle entry / exit records from the park monitoring record set for statistical analysis, formulate access control rules to manage the target park, and generate a park management dataset containing personnel and vehicle management data; and a control management module to evaluate and optimize based on the park management dataset, construct access control management decisions, and implement intelligent access control management for the target park. The fifth extraction module is used to extract the k-th group of personnel management record data based on the personnel management data; the fitness analysis module is used to perform fitness analysis on the k-th group of personnel management record data to obtain the fitness of the k-th group of personnel management data, wherein the fitness of the k-th group of personnel management data is obtained by weighting the trigger frequency characteristics and trigger timeliness characteristics of the k-th group of personnel management; the fifth judgment module is used to determine whether the fitness of the k-th group of personnel management data is greater than or equal to the fitness of the (k-1)-th group of personnel management data; the data elimination module is used to determine whether the k-th group of personnel management data is greater than or equal to the fitness of the (k-1)-th group of personnel management data; the data elimination module is used to determine whether the k-th group of personnel management data is greater than or equal to the fitness of the (k-1)-th group of personnel management data. If the fitness of the personnel management data of group k is greater than or equal to the fitness of the personnel management data of group k-1, the personnel management record data of group k-1 is added to the elimination data group. If the fitness of the personnel management data of group k is less than the fitness of the personnel management data of group k-1, the personnel management record data of group k is added to the elimination data group. The elimination data group is a data unit used to delete groups with low personnel management data fitness. The sixth judgment module is used to determine whether k satisfies the taboo table update cycle. The taboo table update cycle is used to characterize the number of iterations in which the taboo object is prohibited in the taboo table, and the taboo object is the fitness of the personnel management data of group k.The seventh judgment module is used to update the taboo table by inputting the fitness of the management data of the k-th group of personnel or the fitness of the management data of the (k-1)-th group of personnel into the taboo table if the taboo table update cycle is met, and to determine whether the taboo table update count meets the preset update count. The taboo table is a data structure used to store taboo objects. The sixth extraction module is used to extract the initial value of the taboo table based on the taboo table if the taboo table update count meets the preset update count. The initial value of the taboo table has the fitness of the management data of the taboo personnel. The eighth judgment module is used to determine the fitness of the management data of the k-th group of personnel. The system is configured to: 1) determine whether the fitness of the personnel management data of the (k-1)th group is greater than or equal to the fitness of the personnel management data of the prohibited group; 2) determine whether the fitness of the prohibited group is greater than or equal to the fitness of the personnel management data of the (k-1)th group; 3) determine whether the initial value of the prohibited group table is replaced and set as the updated value of the prohibited group table if the fitness of the (k-1)th group is greater than or equal to the fitness of the personnel management data of the (k-1)th group; 4) determine whether the initial value of the prohibited group table is set as the updated value of the prohibited group table if the fitness of the (k-1)th group is greater than or equal to the fitness of the personnel management data of the (k-1)th group; 5) determine whether the initial value of the prohibited group table is set as the updated value of the prohibited group table if the fitness of the (k-1)th group is greater than or equal to the fitness of the personnel management data of the (k-1)th group; 6) determine whether the initial value of the prohibited group table table is less than the updated value of the prohibited group table table if the initial value of the prohibited group table table table is less than the updated value of the prohibited group table ...

[0006] Secondly, this application provides an automatic access control management method for industrial parks. The method includes: generating a personnel management information set by matching the identities of park management personnel; obtaining an authorized personnel information database, which is obtained through authorization management of the personnel management information set; identifying and recording multiple target vehicles entering and exiting the target park to generate a target vehicle information database; retrieving the authorized personnel information database and traversing the target vehicle information database to perform permission association verification, generating an association verification dataset; performing real-time access monitoring of the target park based on the association verification dataset to generate a park monitoring record set; and extracting personnel entry / exit records and vehicle entry / exit records from the park monitoring record set for data statistical analysis to formulate... Access control rules manage the target area, generating a park management dataset containing personnel and vehicle management data. Based on this dataset, evaluation and optimization are performed to construct access control management decisions for intelligent access control management of the target area. According to the personnel management data, the k-th group of personnel management records is extracted. Fitness analysis is performed on the k-th group of personnel management records to obtain the fitness of the k-th group of personnel management data. The fitness of the k-th group of personnel management data is obtained by assigning weights based on the trigger frequency and trigger timeliness characteristics of the k-th group of personnel management data. It is then determined whether the fitness of the k-th group of personnel management data is greater than or equal to the fitness of the (k-1)-th group of personnel management data. If the fitness of the personnel management data of the k-th group is greater than or equal to the fitness of the personnel management data of the (k-1)-th group, the personnel management record data of the (k-1)-th group is added to the elimination data group. If the fitness of the personnel management data of the k-th group is less than the fitness of the personnel management data of the (k-1)-th group, the personnel management record data of the k-th group is added to the elimination data group. The elimination data group is a data unit used to delete groups with low personnel management data fitness. It is then determined whether k satisfies the taboo list update cycle, where the taboo list update cycle characterizes the number of iterations in which a taboo object is prohibited in the taboo list, and the taboo object is the fitness of the personnel management data of the k-th group. If k satisfies the taboo list update cycle, the fitness of the personnel management data of the k-th group is added to the elimination data group. Alternatively, the fitness of the personnel management data of the (k-1)th group can be input into the taboo table for updating. It is then determined whether the number of taboo table updates meets the preset update count, where the taboo table is a data structure used to store taboo objects. If the number of taboo table updates meets the preset update count, then an initial value of the taboo table is extracted based on the taboo table, where the initial value of the taboo table has the fitness of the personnel management data of the taboo group. It is then determined whether the fitness of the personnel management data of the k-th group or the fitness of the personnel management data of the (k-1)th group is greater than or equal to the fitness of the personnel management data of the taboo group. If it is greater than or equal to, the initial value of the taboo table is replaced based on the personnel management record data of the k-th group or the personnel management record data of the (k-1)th group, and set as the updated value of the taboo table.If the value is less than the specified value, set the initial value of the taboo table to the updated value of the taboo table, and set the updated value of the taboo table as the personnel management optimization data; update the management strategy of the target park based on the personnel management optimization data.

[0007] One or more technical solutions provided in this application have at least the following technical effects or advantages:

[0008] The automatic access control management system and method for industrial parks provided in this application relate to the field of automatic management technology. It solves the technical problem that the lack of access control for personnel and vehicles entering and exiting the park in the existing technology leads to high access control management costs for the target park. It realizes rational and accurate intelligent identification and access control management of personnel and vehicles in the park, thereby reducing the access control management cost of the park. Attached Figure Description

[0009] Figure 1 This application provides a schematic diagram of the automatic access control management method for industrial parks;

[0010] Figure 2 This application provides a schematic diagram of the structure of an automatic access control management system for industrial parks.

[0011] Explanation of reference numerals in the attached diagram: First matching module 1, authorization management module 2, identification and recording module 3, first verification module 4, first monitoring module 5, first analysis module 6, control management module 7. Detailed Implementation

[0012] This application provides an automatic access control management system and method for industrial parks, which solves the technical problem of high access control management costs in target industrial parks due to the lack of access control for personnel and vehicles entering and exiting the park. It realizes rational and accurate intelligent identification and access management of personnel and vehicles in the park, thereby reducing the access control management cost of the park.

[0013] Example 1

[0014] like Figure 1 As shown in the embodiment of this application, an automatic access control management method for a park is provided, the method including:

[0015] Step A100: Generate a personnel management information set by matching the identities of park management personnel;

[0016] Furthermore, step A100 of this application also includes:

[0017] Step A110: Identify and extract multiple entrances and exits within the target park;

[0018] Step A120: Deploy multiple identity recognition devices based on the multiple entrances and exits, and match the identities of park management personnel with the multiple identity recognition devices to obtain multiple matched identities;

[0019] Step A130: Adaptively input the information of the multiple matched identities to generate the personnel management information set.

[0020] In this application, the automatic access control management method for parks provided in this embodiment is applied to an automatic access control management system for parks. To better control access to the target park, all entrances and exits with access control management within the target park are first identified. At least one identity recognition device is deployed at each of the identified entrances and exits. This identity recognition device can be a facial recognition device, an access card chip recognition device, etc. Further, the identities of park management personnel who need to enter and exit the park are matched based on the deployed identity recognition devices. This means that only the park management personnel within the target park are matched for their corresponding identities. The matched identities can include basic identity information such as name, age, and gender, thereby obtaining the park management personnel whose identities have been matched and acquiring multiple matched identities. When a park management personnel enters the park, the identity recognition device automatically performs identity matching and sends the matched identity information to the system. The system can input information based on multiple matched identities, recording the information set of all park management personnel whose matched identities have been entered as a personnel management information set, serving as an important reference for later implementation of intelligent access control for the target park.

[0021] Step A200: Obtain the authorized personnel information database, which is obtained by performing authorization management on the personnel management information set;

[0022] Furthermore, step A200 of this application also includes:

[0023] Step A210: Extract multiple job information of park management personnel based on the personnel management information set;

[0024] Step A220: Divide the permission levels according to the multiple job information to generate multiple permission levels;

[0025] Step A230: Verify access control of the target park through the multiple permission levels and generate multiple verification messages;

[0026] Step A240: Match the multiple verification messages with multiple access control methods;

[0027] Step A250: Integrate the information of the multiple permission levels and the multiple access control methods to generate the authorized personnel information database.

[0028] In this application, the authorization management of the personnel management information set obtained through the above matching process involves first extracting multiple job information of park management personnel from the personnel management information set, ensuring a correspondence between these job information and the park management personnel in the personnel management information set. Further, multiple different permission levels are set based on these job information, such as park administrator, park department manager, and park employee. Higher job levels correspond to higher permission levels. Multiple permission levels are then obtained, and access control verification of the target park is performed using these multiple permission levels. Since different job positions are matched with different permission levels, and higher permission levels grant more access control functions—for example, park administrators can freely enter and exit all entrances and exits within the entire park, while park employees can only enter and exit within their work area—access control verification is required for each permission level to determine whether the current permission level meets the access control permission level for the current entrance or exit, thereby generating multiple verification messages. Furthermore, matching multiple access control methods based on multiple verification information means defining access control methods according to the permission level requirements within the verification information. When the permission level requirement is high, the access control method can be defined as two-factor authentication, i.e., fingerprint recognition access control and / or facial recognition access control. When the permission level requirement is medium, the access control method can be defined as card swiping access control and / or password access control. When the permission level requirement is low, the access control method can be defined as voice recognition access control and / or remote control access control. Finally, integrating multiple permission levels and multiple access control methods means unifying the management of multiple permission levels and multiple access control methods to achieve permission control and management for park management personnel. Through information integration, unified permission management can be achieved, ensuring that only park management personnel with the corresponding permissions can enter specific areas. Based on this, the data is summarized and integrated to form an authorized personnel information database, thereby ensuring the implementation of intelligent access control for the target park.

[0029] Step A300: Identify and record multiple target vehicles entering and exiting the target park, and generate a target vehicle information database;

[0030] Furthermore, step A300 of this application also includes:

[0031] Step A310: Determine multiple identification points based on the multiple entrances / exits and the multiple target vehicle travel segments;

[0032] Step A320: Deploy the vehicle identification device according to the multiple identification points;

[0033] Step A330: Extract multiple target vehicle images of multiple entering and exiting target vehicles based on the vehicle recognition device;

[0034] Step A340: Perform wavelet decomposition on the image signals of the multiple target vehicle images to obtain the wavelet coefficients of the image signals;

[0035] Step A350: Perform threshold quantization based on the wavelet coefficients of the image signal to determine the wavelet selection threshold for the image signal;

[0036] Step A360: Truncate the wavelet coefficients of the image signal according to the wavelet selection threshold of the image signal, set the noise signal smaller than the wavelet selection threshold of the image signal to zero, and obtain the effective signal information greater than the wavelet selection threshold of the image signal;

[0037] Step A370: Filter and reconstruct the effective signal information to obtain a set of multiple target vehicle images;

[0038] Step A380: Obtain the target vehicle information database based on the multiple target vehicle image sets.

[0039] In this application, to achieve more precise control over access control within the target area, it is necessary to determine vehicle identification points based on multiple entrances and exits within the target area and the driving routes of vehicles within the target area. These vehicle identification points are location information used to identify the access rights of vehicles at multiple entrances and exits within the target area. Based on these determined identification points, at least one vehicle identification device is deployed at each identification point. The vehicle identification device can utilize license plate recognition technology to acquire images of target vehicles, which involves processing and analyzing vehicle images captured by cameras to achieve the purpose of identifying the target vehicles. This results in the acquisition of multiple target vehicle images of multiple vehicles entering and exiting the target area. Furthermore, the principle of wavelet threshold denoising is used to denoise the multiple target vehicle images. The image signals of multiple target vehicles are processed by wavelet transform. The wavelet coefficients generated by the signal contain important information. After wavelet decomposition, the wavelet coefficients of the signal are larger, while the wavelet coefficients of noise are smaller. Furthermore, the wavelet coefficients of noise are smaller than those of the signal. By selecting an appropriate threshold, wavelet coefficients greater than the threshold are considered to be generated by the signal and should be retained, while those less than the threshold are considered to be generated by noise and are set to zero to achieve the purpose of noise reduction. Multiple target vehicle image sets are obtained. Finally, the image data is integrated based on the multiple target vehicle image sets. This means recording and storing the identified target vehicle information to output a target vehicle information database, laying a solid foundation for subsequent intelligent access control of the target park based on park management personnel and vehicles.

[0040] Step A400: Retrieve the authorized personnel information database, traverse the target vehicle information database to perform permission association verification, and generate an association verification dataset;

[0041] Furthermore, step A400 of this application also includes:

[0042] Step A410: Obtain the target vehicle information that requires access control verification;

[0043] Step A420: Traverse the target vehicle information database to query the target vehicle information and obtain the target vehicle identification information, wherein the target vehicle identification information and the target vehicle information have a corresponding relationship;

[0044] Step A430: Traverse the target vehicle identification information and compare it with the authorized personnel information database, and obtain the vehicle-associated personnel information based on the comparison results;

[0045] Step A440: Integrate and connect the authorized personnel information database with the target vehicle information database to generate an integrated access control database for the park;

[0046] Step A450: Verify the vehicle-related personnel information based on the park access control integrated database, and generate the associated verification dataset.

[0047] In this application, to effectively manage and control personnel and vehicles within the park, it is necessary to associate access permissions between park management personnel and vehicles. First, information on target vehicles requiring access control verification is collected and used as index data. This information is then accessed and queried sequentially in the constructed target vehicle information database. The target vehicle can be identified using its license plate number, vehicle identification number (VIN), or other unique identifier, thus obtaining its identification information. A one-to-one correspondence exists between the target vehicle identification information and the target vehicle information. Further, to find the associated personnel information field within the target vehicle identification information, this is achieved by sequentially accessing and traversing the target vehicle identification information to obtain the associated personnel information field for the target vehicle corresponding to the target vehicle identification information. This information can include vehicle owner information, driver information, or other relevant personnel information. The content of the associated field can also include… This includes, but is not limited to, information such as ID card number and name. Further comparison with the authorized personnel information database involves querying the database based on the person's identity information to verify whether the person has the necessary permissions for the target vehicle. This can be done by considering factors such as permission level and department to determine if the person has the necessary permissions. This allows for the acquisition of vehicle-related personnel information. Simultaneously, the authorized personnel information database and the target vehicle information database are integrated and linked to ensure mutual access and querying. This integrated database is designated as the park access control integrated database. Finally, to prevent unauthorized use of vehicles, a dual verification process is performed on the vehicle-related personnel information based on the park access control integrated database. This involves verifying both the target vehicle and the personnel information separately. For example, for an authorized vehicle, only authorized personnel can use it; others are prohibited from using it without authorization. When using the vehicle, the user's identity must be verified to ensure legitimacy. Based on this verification, an associated verification dataset is generated, enabling intelligent access control of the target park based on park management personnel and vehicles.

[0048] Step A500: Based on the aforementioned associated verification dataset, perform real-time access monitoring of the target park and generate a park monitoring record set;

[0049] Furthermore, step A500 of this application also includes:

[0050] Step A510: Construct a real-time monitoring network to monitor real-time access data, wherein the real-time access data includes real-time access personnel data and real-time access vehicle data;

[0051] Step A520: Based on the real-time access personnel data, traverse the authorized personnel information database to determine personnel access permissions;

[0052] Step A530: Verify the access permissions of the personnel and determine whether the personnel accessing the site in real time are allowed to enter or leave the target area;

[0053] Step A540: If possible, monitor and record the personnel data to obtain the first monitoring record data; if not possible, intercept the visitors.

[0054] Step A550: Verify whether the vehicle-associated personnel information has authorized data in the authorized personnel information database;

[0055] Step A560: If the permission data is available, perform permission comparison and matching on the real-time accessed vehicle data according to the permission data, and monitor and record the vehicle data to obtain second monitoring record data; if the permission data is not available, then intercept the accessing vehicle according to the real-time accessed vehicle data.

[0056] Step A570: Generate the park monitoring record set based on the first monitoring record data and the second monitoring record data.

[0057] In this application, in order to implement more intelligent access control for multiple entrances and exits of the park, the association verification dataset generated through the above association verification is used as the basic reference data to monitor the target park in real time. First, a real-time monitoring network needs to be constructed to monitor the real-time access data in the target park. The real-time monitoring network refers to a multi-layer perceptron neural network. The real-time monitoring network is further constructed, and each node of each layer of the real-time monitoring network is fully connected to the nodes of the upper and lower layers. The real-time monitoring network includes an input layer, a hidden layer, and an output layer. The input layer is used for data input, the hidden layer is used to better separate data features, and the output layer is used for result output. The real-time monitoring network is trained using a training dataset and a supervised dataset. Each set of training data in the training dataset includes personnel access data and vehicle access data, and the supervised dataset is supervised data that corresponds one-to-one with the training dataset.

[0058] Furthermore, each set of training data in the training dataset is input into the real-time monitoring network. The output of the real-time monitoring network is adjusted by the supervision data corresponding to this set of training data. When the output of the real-time monitoring network is consistent with the supervision data, the training of the current set ends. The real-time monitoring network training is completed when all the training data in the training dataset has been trained.

[0059] To ensure the convergence and accuracy of the real-time monitoring network, the convergence process can be defined as the output data in the real-time monitoring network converging at a point and moving closer to a certain value. Its accuracy can be tested by processing the real-time monitoring network with a test dataset. For example, the test accuracy can be set to 80%. When the test accuracy of the test dataset meets 80%, the real-time monitoring network is completed.

[0060] Real-time access data is monitored through a real-time monitoring network. This data includes real-time access personnel data and real-time access vehicle data. Furthermore, the real-time access personnel data is used as a data index to sequentially traverse the authorized personnel information database. Matching authorized personnel information is added to the real-time access personnel data to determine personnel access permissions. Further, personnel access permissions are verified, specifically the permission level of the real-time access personnel. Since some personnel with lower permission levels can only enter and exit during fixed time periods—for example, during work hours, some personnel are not allowed to move outside designated work areas—or... During non-working hours, certain personnel are not allowed to enter the park. This is to determine whether the personnel accessing the park in real time have the necessary access level. If the personnel accessing the park in real time have the necessary access level, their data will be monitored and recorded as the first monitoring record data and output. If the personnel accessing the park in real time do not have the necessary access level, their access will be blocked. Furthermore, the system verifies whether the vehicle-related personnel information has the necessary permissions in the authorized personnel information database. This means extracting the associated personnel information from the vehicle-related personnel information and comparing it with the authorized personnel information database. The comparison may include identity information, permission levels, etc. Based on the verification results, it is determined whether the vehicle-associated personnel have the necessary permissions. If the information of the vehicle-associated personnel matches the information in the authorized personnel database and they possess the corresponding permission level, they can be identified as authorized personnel. Simultaneously, permission comparison and matching are performed on the real-time accessed vehicle data based on the permission data. Access monitoring records are recorded for the vehicle data and output as the second monitoring record data. If the information of the vehicle-associated personnel does not match the information in the authorized personnel database and they do not possess the corresponding permission level, the accessing vehicle is intercepted and controlled based on the real-time accessed vehicle data. Finally, data is collected and recorded based on the first and second monitoring record data. The first and second monitoring record data are collected in real time, including data cleaning, preprocessing, feature extraction, data association, and other steps to process and analyze the collected monitoring data, thereby generating a park monitoring record set. This set serves as reference data for later intelligent access control of the target park based on park management personnel and vehicles.

[0061] Step A600: Extract personnel entry and exit records and vehicle entry and exit records from the park monitoring record set, perform data statistical analysis, formulate access control rules to manage the target park, and generate a park management dataset, which includes personnel management data and vehicle management data;

[0062] In this application, statistical analysis of the park monitoring record set involves first extracting personnel and vehicle entry / exit records from the set. Then, statistical analysis is performed on these records, specifically by analyzing daily, weekly, or monthly personnel entry / exit frequency, peak hours, and common routes to extract relevant features. This involves acquiring these personnel and vehicle entry / exit features separately. Further, different access control levels for personnel and vehicles are set, restrictions are placed on specific time periods, and specific routes are defined. Intelligent access control rules adapted to the target park are established based on these features. These rules correspond to personnel and vehicle access control, respectively. Finally, these rules are integrated into the system and configured accordingly for the target park. The system manages personnel and vehicles within the park, ensuring intelligent control and management of their entry and exit according to rules. This involves real-time monitoring of personnel and vehicle access, ensuring timely data acquisition and matching with personnel and / or vehicle access control rules. If rule violations occur, the system can promptly issue alarms or take appropriate measures, thereby acquiring personnel and vehicle control data. Furthermore, regular evaluation and optimization of this data involves adjusting access control rules and optimizing system configuration based on feedback and statistical analysis. It also requires periodic evaluation and optimization of the intelligent access control management effect based on actual operation, generating management decisions to improve efficiency and accuracy. Ultimately, based on these management decisions, intelligent access control management is implemented across the target park, improving the accuracy of future intelligent access control based on park management personnel and vehicles.

[0063] Step A700: Based on the aforementioned park management dataset, conduct evaluation and optimization, and construct access control management decisions to implement intelligent access control management for the target park.

[0064] Furthermore, step A700 of this application also includes:

[0065] Step A710: Based on the personnel management data, extract the personnel management record data for the kth group;

[0066] Step A720: Perform fitness analysis on the personnel management record data of the kth group to obtain the fitness of the personnel management data of the kth group. The fitness of the personnel management data of the kth group is obtained by weighting the personnel management trigger frequency characteristics and the personnel management trigger timeliness characteristics of the kth group.

[0067] Step A730: Determine whether the fitness of the management data for the k-th group of personnel is greater than or equal to the fitness of the management data for the (k-1)-th group of personnel;

[0068] Step A740: If the fitness of the personnel management data of the kth group is greater than or equal to the fitness of the personnel management data of the (k-1)th group, add the personnel management record data of the (k-1)th group to the elimination data group; if the fitness of the personnel management data of the kth group is less than the fitness of the personnel management data of the (k-1)th group, add the personnel management record data of the kth group to the elimination data group. The elimination data group is a data unit used to delete groups with low personnel management data fitness.

[0069] Step A750: Determine whether k satisfies the taboo list update cycle, wherein the taboo list update cycle is used to characterize the number of iterations in which the taboo object is prohibited in the taboo list, and the taboo object is the fitness of the kth group of personnel management data;

[0070] Step A760: If k satisfies the taboo table update cycle, input the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel into the taboo table for update, and determine whether the taboo table update count meets the preset update count. The taboo table is a data structure used to store taboo objects.

[0071] Step A770: If the number of times the taboo list is updated meets the preset number of updates, then extract the initial value of the taboo list according to the taboo list, wherein the initial value of the taboo list has the data fitness of the taboo personnel management data;

[0072] Step A780: Determine whether the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel is greater than or equal to the fitness of the management data of the prohibited personnel;

[0073] Step A790: If it is greater than or equal to, replace the initial value of the taboo table with the personnel management record data of the kth group or the personnel management record data of the (k-1)th group, and set it as the updated value of the taboo table;

[0074] Step A7100: If it is less than, set the initial value of the taboo table to the updated value of the taboo table, and set it as the personnel management optimization data according to the updated value of the taboo table;

[0075] Step A7101: Update the management strategy of the target park based on personnel control optimization data.

[0076] In this application, the aforementioned park management dataset is used as the basic reference data. Personnel management data and vehicle management data are extracted from the park management dataset. Furthermore, the personnel management data is clustered according to the reasons for management. Based on the clustering analysis results, the personnel management data is grouped into clusters. Random selection is made from multiple clusters of personnel management data to obtain the k-th group of personnel management records. The trigger frequency characteristics and trigger timeliness characteristics of the k-th group of personnel management are collected. Then, corresponding weights are assigned to the trigger frequency characteristics and trigger timeliness characteristics of the k-th group of personnel management. Based on the weights assigned to the trigger frequency characteristics and trigger timeliness characteristics of the k-th group of personnel management, the fitness of the k-th group of personnel management data is calculated.

[0077] Further, it is determined whether the fitness of the personnel management data of the k-th group is greater than or equal to that of the (k-1)-th group. If the fitness of the personnel management data of the k-th group is greater than or equal to that of the (k-1)-th group, the personnel management record data of the (k-1)-th group is added to the elimination data group. If the fitness of the personnel management data of the k-th group is less than that of the (k-1)-th group, the personnel management record data of the k-th group is added to the elimination data group. That is, the fitness of personnel management data of each pair of adjacent groups is compared, and the group with lower fitness is added to the elimination data group.

[0078] Therefore, the system determines whether k satisfies the tabu table update cycle. The tabu table is used to prevent loops in the search; fitness values ​​are considered tabu objects, and the tabu table is continuously updated. This means the fitness of the latest personnel management data is included, while the fitness of the oldest personnel management data is removed. If k satisfies the tabu table update cycle, the fitness of the k-th group of personnel management data or the (k-1)-th group of personnel management data is input into the tabu table for updating. Then, the system checks whether the number of updates to the tabu table meets the preset update count. If the number of updates meets the preset update count, the initial value of the tabu table is extracted. The initial value of the tabu table refers to the tabu data before the tabu table was updated; generally, there is only one set, which is the optimal personnel management data after the previous cycle update. The tabu table is used to prevent loops in the search; fitness values ​​are considered tabu objects, and the tabu table is continuously updated. As a taboo object, and the taboo table is a continuously updated table, and the initial value of the taboo table has the taboo personnel management data fitness, it is further judged whether the management data fitness of the k-th group of personnel or the management data fitness of the (k-1)-th group of personnel is greater than or equal to the taboo personnel management data fitness. If the management data fitness of the k-th group of personnel or the management data fitness of the (k-1)-th group of personnel is greater than or equal to the taboo personnel management data fitness, it is considered that the management data fitness of the k-th group of personnel or the management data fitness of the (k-1)-th group of personnel is better than the taboo personnel management data fitness in the current taboo table. Therefore, the initial value of the taboo table is replaced by the management record data of the k-th group of personnel or the management record data of the (k-1)-th group of personnel, and the management record data of the k-th group of personnel or the management record data of the (k-1)-th group of personnel is set as the updated value of the taboo table.

[0079] If the fitness of the management data for the k-th group of personnel or the (k-1)-th group of personnel is less than the fitness of the management data for prohibited personnel, then the management data fitness of the prohibited personnel in the current taboo table is considered to be better than the management data fitness of the k-th group of personnel or the (k-1)-th group of personnel. Therefore, the initial value of the current taboo table is set as the updated value of the taboo table, and the updated value of the replaced taboo table is set as the management data for output.

[0080] If the fitness of the personnel management data in group k or group k-1 is less than the fitness of the personnel management data in the taboo table initial value, then the taboo table initial value is set as the taboo table update value, and the personnel management data is output using the taboo table update value.

[0081] The periodic evaluation and optimization process for vehicle control data is similar to that for personnel control data. Based on the vehicle control data and personnel control data that have undergone periodic evaluation and optimization, access control rules are adjusted, system configuration is optimized, management decisions for the target park are improved, and personnel and vehicle control in the target park are implemented according to the optimized management decisions, thereby improving the park's management level and work efficiency, and ensuring the park's safety and stability.

[0082] In summary, the automatic access control management method for parks provided in this application embodiment has at least the following technical effects: it realizes rational and accurate intelligent identification and access control management of personnel and vehicles in the park, and reduces the access control management cost of the park.

[0083] Example 2

[0084] Based on the same inventive concept as the automatic access control management method for parks described in the foregoing embodiments, such as Figure 2 As shown, this application provides an automatic access control management system for industrial parks. The system and method embodiments in this application are based on the same inventive concept. The system includes:

[0085] The first matching module 1 is used to generate a personnel management information set by matching the identities of park management personnel;

[0086] Authorization management module 2 is used to obtain an authorized personnel information database, which is obtained by performing authorization management on the personnel management information set;

[0087] The identification and recording module 3 is used to identify and record multiple target vehicles entering and exiting the target park, and generate a target vehicle information database.

[0088] First verification module 4, which is used to retrieve the authorized personnel information database, traverse the target vehicle information database to perform permission association verification, and generate an association verification dataset;

[0089] The first monitoring module 5 is used to perform real-time access monitoring of the target park based on the associated verification dataset and generate a park monitoring record set.

[0090] The first analysis module 6 is used to extract personnel entry and exit records and vehicle entry and exit records from the park monitoring record set for data statistical analysis, formulate access control rules to manage the target park, and generate a park management dataset, which includes personnel management data and vehicle management data.

[0091] The control and management module 7 is used to evaluate and optimize based on the park management and control dataset, and to construct access control management decisions to carry out intelligent access control management of the target park.

[0092] Furthermore, the control management module 7 includes:

[0093] The fifth extraction module is used to extract the k-th group of personnel management record data based on the personnel management data.

[0094] The fitness analysis module is used to perform fitness analysis on the personnel management record data of the kth group to obtain the fitness of the personnel management data of the kth group. The fitness of the personnel management data of the kth group is obtained by assigning weights based on the triggering frequency characteristics and triggering timeliness characteristics of the personnel management of the kth group.

[0095] The fifth judgment module is used to determine whether the fitness of the management data of the kth group of personnel is greater than or equal to the fitness of the management data of the (k-1)th group of personnel.

[0096] The data elimination module is used to add the personnel management record data of the (k-1)th group to the elimination data group if the fitness of the personnel management data of the kth group is greater than or equal to the fitness of the personnel management data of the (k-1)th group, and to add the personnel management record data of the kth group to the elimination data group if the fitness of the personnel management data of the kth group is less than the fitness of the personnel management data of the (k-1)th group. The elimination data group is a data unit used to delete groups with low fitness of personnel management data.

[0097] The sixth judgment module is used to determine whether k satisfies the taboo table update cycle, wherein the taboo table update cycle is used to characterize the number of iterations in which the taboo object is prohibited in the taboo table, and the taboo object is the fitness of the k-th group of personnel management data;

[0098] The seventh judgment module is used to update the taboo table if k satisfies the taboo table update cycle, by inputting the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel into the taboo table for updating, and to determine whether the taboo table update count meets the preset update count. The taboo table is a data structure used to store taboo objects.

[0099] The sixth extraction module is used to extract the initial value of the taboo table according to the taboo table if the number of times the taboo table is updated meets the preset number of updates. The initial value of the taboo table has the adaptability of the taboo personnel management data.

[0100] The eighth judgment module is used to determine whether the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel is greater than or equal to the fitness of the management data of the prohibited personnel.

[0101] The ninth judgment module is used to replace the initial value of the taboo table and set it as the updated value of the taboo table if the value is greater than or equal to the data of the k-th group of personnel management records or the data of the (k-1)-th group of personnel management records.

[0102] The tenth judgment module is used to set the initial value of the taboo table to the updated value of the taboo table if the value is less than the specified value, and to set the updated value of the taboo table as the personnel management optimization data.

[0103] The update module is used to update the management strategy of the target park based on personnel management optimization data.

[0104] Furthermore, the first matching module 1 includes:

[0105] The first extraction module is used to identify and extract multiple entrances and exits within the target park.

[0106] The second matching module is used to deploy multiple identity recognition devices based on the multiple entrances and exits, and to match the identities of park management personnel according to the multiple identity recognition devices to obtain multiple matched identities.

[0107] The information entry module is used to adaptively enter information from the multiple matching identities to generate the personnel management information set.

[0108] Furthermore, the authorization management module 2 includes:

[0109] The second extraction module is used to extract multiple job information of park management personnel based on the personnel management information set;

[0110] A segmentation module is used to segment permission levels based on the multiple job information and generate multiple permission levels.

[0111] The second verification module is used to verify the access control of the target park through the multiple permission levels and generate multiple verification messages.

[0112] The third matching module is used to match the multiple verification information with multiple access control methods;

[0113] The information integration module is used to integrate the multiple permission levels and the multiple access control methods to generate the authorized personnel information database.

[0114] Furthermore, the identification and recording module 3 includes:

[0115] The location identification module is used to determine multiple identification points based on the multiple entrances and exits and the multiple target vehicle travel segments;

[0116] The device deployment module is used to deploy the vehicle recognition device according to the multiple recognition points;

[0117] The third extraction module is used to extract multiple target vehicle images of multiple entering and exiting target vehicles based on the vehicle recognition device.

[0118] The decomposition module is used to perform wavelet decomposition on the image signals of the plurality of target vehicle images to obtain wavelet coefficients of the image signals.

[0119] A threshold determination module is used to perform threshold quantization based on the wavelet coefficients of the image signal to determine the wavelet selection threshold of the image signal.

[0120] The truncation module is used to truncate the wavelet coefficients of the image signal according to the wavelet selection threshold of the image signal, set the noise signal smaller than the wavelet selection threshold of the image signal to zero, and obtain the effective signal information larger than the wavelet selection threshold of the image signal.

[0121] A filtering and reconstruction module is used to filter and reconstruct the effective signal information to obtain a set of multiple target vehicle images;

[0122] An information database generation module is used to obtain the target vehicle information database based on the plurality of target vehicle image sets.

[0123] Furthermore, the first verification module 4 includes:

[0124] The third verification module is used to obtain the target vehicle information that needs to be verified by access control.

[0125] The first traversal module is used to traverse the target vehicle information database to query the target vehicle information and obtain the target vehicle identification information, wherein the target vehicle identification information and the target vehicle information have a corresponding relationship.

[0126] The second traversal module is used to traverse the target vehicle identification information and compare it with the authorized personnel information database, and obtain the vehicle-related personnel information based on the comparison results.

[0127] An integrated connection module is used to integrate and connect the authorized personnel information database with the target vehicle information database to generate an integrated access control database for the park.

[0128] The fourth verification module is used to verify the vehicle-related personnel information based on the park access control integrated database and generate the associated verification dataset.

[0129] Furthermore, the first monitoring module 5 includes:

[0130] The second monitoring module is used to construct a real-time monitoring network to monitor real-time access data, wherein the real-time access data includes real-time access personnel data and real-time access vehicle data.

[0131] The third traversal module is used to traverse the authorized personnel information database based on the real-time access personnel data to determine personnel access permissions;

[0132] The first judgment module is used to verify the access rights of the personnel and determine whether the personnel accessing the site in real time can enter or leave the target park.

[0133] The second judgment module is used to monitor and record the personnel data if possible, and obtain the first monitoring record data; if not possible, the access personnel are intercepted.

[0134] The third judgment module is used to verify whether the vehicle-associated personnel information has authorized data in the authorized personnel information database.

[0135] The fourth judgment module is used to, if the permission data is available, compare and match the permissions of the real-time accessed vehicle data, monitor and record the vehicle data, and obtain second monitoring record data; if the permission data is not available, the accessing vehicle is intercepted based on the real-time accessed vehicle data.

[0136] The record integration module is used to generate the park monitoring record set based on the first monitoring record data and the second monitoring record data.

[0137] Through the foregoing detailed description of the automatic access control management method for parks, those skilled in the art can clearly understand the automatic access control management system for parks in this embodiment. As for the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and relevant parts can be referred to the method section description.

[0138] The above description of the disclosed embodiments enables those skilled in the art to make or use this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An automatic access control management system for industrial parks, characterized in that: The system includes: The first matching module is used to generate a personnel management information set by matching the identities of park management personnel. The authorization management module is used to obtain an authorized personnel information database, which is obtained by performing authorization management on the personnel management information set. The identification and recording module is used to identify and record multiple target vehicles entering and exiting the target park, and generate a target vehicle information database. The first verification module is used to retrieve the authorized personnel information database, traverse the target vehicle information database to perform permission association verification, and generate an association verification dataset. The first monitoring module is used to perform real-time access monitoring of the target park based on the associated verification dataset and generate a park monitoring record set. The first analysis module is used to extract personnel entry and exit records and vehicle entry and exit records from the park monitoring record set, perform data statistical analysis, formulate access control rules to manage the target park, and generate a park management dataset, which includes personnel management data and vehicle management data. The control and management module is used to evaluate and optimize based on the park management dataset, and to construct access control management decisions to carry out intelligent access control management of the target park. The fifth extraction module is used to extract the k-th group of personnel management record data based on the personnel management data. The fitness analysis module is used to perform fitness analysis on the personnel management record data of the kth group to obtain the fitness of the personnel management data of the kth group. The fitness of the personnel management data of the kth group is obtained by assigning weights based on the triggering frequency characteristics and triggering timeliness characteristics of the personnel management of the kth group. The fifth judgment module is used to determine whether the fitness of the management data of the kth group of personnel is greater than or equal to the fitness of the management data of the (k-1)th group of personnel. The data elimination module is used to add the personnel management record data of the (k-1)th group to the elimination data group if the fitness of the personnel management data of the kth group is greater than or equal to the fitness of the personnel management data of the (k-1)th group, and to add the personnel management record data of the kth group to the elimination data group if the fitness of the personnel management data of the kth group is less than the fitness of the personnel management data of the (k-1)th group. The elimination data group is a data unit used to delete groups with low fitness of personnel management data. The sixth judgment module is used to determine whether k satisfies the taboo table update cycle, wherein the taboo table update cycle is used to characterize the number of iterations in which the taboo object is prohibited in the taboo table, and the taboo object is the fitness of the k-th group of personnel management data; The seventh judgment module is used to update the taboo table if k satisfies the taboo table update cycle, by inputting the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel into the taboo table for updating, and to determine whether the taboo table update count meets the preset update count. The taboo table is a data structure used to store taboo objects. The sixth extraction module is used to extract the initial value of the taboo table according to the taboo table if the number of times the taboo table is updated meets the preset number of updates. The initial value of the taboo table has the adaptability of the taboo personnel management data. The eighth judgment module is used to determine whether the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel is greater than or equal to the fitness of the management data of the prohibited personnel. The ninth judgment module is used to replace the initial value of the taboo table and set it as the taboo table update value if it is greater than or equal to the data of the k-th group of personnel management records or the data of the (k-1)-th group of personnel management records. The tenth judgment module is used to set the initial value of the taboo table to the updated value of the taboo table if the value is less than the specified value, and to set the updated value of the taboo table as the personnel management optimization data. The update module is used to update the management strategy of the target park based on personnel management optimization data.

2. The system as described in claim 1, characterized in that, The system includes: The first extraction module is used to identify and extract multiple entrances and exits within the target park. The second matching module is used to deploy multiple identity recognition devices based on the multiple entrances and exits, and to match the identities of park management personnel according to the multiple identity recognition devices to obtain multiple matched identities. The information entry module is used to adaptively enter information from the multiple matching identities to generate the personnel management information set.

3. The system as described in claim 1, characterized in that, The system includes: The second extraction module is used to extract multiple job information of park management personnel based on the personnel management information set; A segmentation module is used to segment permission levels based on the multiple job information and generate multiple permission levels. The second verification module is used to verify the access control of the target park through the multiple permission levels and generate multiple verification messages. The third matching module is used to match the multiple verification information with multiple access control methods; The information integration module is used to integrate the multiple permission levels and the multiple access control methods to generate the authorized personnel information database.

4. The system as described in claim 2, characterized in that, The system includes: The location identification module is used to determine multiple identification points based on the multiple entrances and exits and the multiple target vehicle travel segments; The device deployment module is used to deploy the vehicle recognition device according to the multiple recognition points; The third extraction module is used to extract multiple target vehicle images of multiple entering and exiting target vehicles based on the vehicle recognition device. The decomposition module is used to perform wavelet decomposition on the image signals of the plurality of target vehicle images to obtain wavelet coefficients of the image signals. A threshold determination module is used to perform threshold quantization based on the wavelet coefficients of the image signal to determine the wavelet selection threshold of the image signal. The truncation module is used to truncate the wavelet coefficients of the image signal according to the wavelet selection threshold of the image signal, set the noise signal smaller than the wavelet selection threshold of the image signal to zero, and obtain the effective signal information larger than the wavelet selection threshold of the image signal. A filtering and reconstruction module is used to filter and reconstruct the effective signal information to obtain a set of multiple target vehicle images; An information database generation module is used to obtain the target vehicle information database based on the plurality of target vehicle image sets.

5. The system as described in claim 1, characterized in that, The system includes: The third verification module is used to obtain the target vehicle information that needs to be verified by access control. The first traversal module is used to traverse the target vehicle information database to query the target vehicle information and obtain the target vehicle identification information, wherein the target vehicle identification information and the target vehicle information have a corresponding relationship. The second traversal module is used to traverse the target vehicle identification information and compare it with the authorized personnel information database, and obtain the vehicle-related personnel information based on the comparison results. An integrated connection module is used to integrate and connect the authorized personnel information database with the target vehicle information database to generate an integrated access control database for the park. The fourth verification module is used to verify the vehicle-related personnel information based on the park access control integrated database and generate the associated verification dataset.

6. The system as described in claim 5, characterized in that, The system includes: The second monitoring module is used to construct a real-time monitoring network to monitor real-time access data, wherein the real-time access data includes real-time access personnel data and real-time access vehicle data. The third traversal module is used to traverse the authorized personnel information database based on the real-time access personnel data to determine personnel access permissions; The first judgment module is used to verify the access rights of the personnel and determine whether the personnel accessing the site in real time can enter or leave the target park. The second judgment module is used to monitor and record the personnel data if possible, and obtain the first monitoring record data; if not possible, the access personnel are intercepted. The third judgment module is used to verify whether the vehicle-associated personnel information has authorized data in the authorized personnel information database. The fourth judgment module is used to, if the permission data exists, compare and match the permissions of the real-time accessed vehicle data according to the permission data, monitor and record the vehicle data, and obtain second monitoring record data; if the permission data does not exist, the accessing vehicle is intercepted according to the real-time accessed vehicle data. The record integration module is used to generate the park monitoring record set based on the first monitoring record data and the second monitoring record data.

7. A method for automatic access control management in industrial parks, characterized in that: The method includes: By matching the identities of park management personnel, a personnel management information set is generated; The authorized personnel information database is obtained by performing authorization management on the personnel management information set; Identify and record multiple target vehicles entering and exiting the target park to generate a target vehicle information database; The authorized personnel information database is retrieved and the target vehicle information database is traversed to perform permission association verification, generating an association verification dataset. Based on the aforementioned associated verification dataset, real-time access monitoring of the target park is performed to generate a park monitoring record set. Extract personnel entry and exit records and vehicle entry and exit records from the park monitoring record set, perform data statistical analysis, formulate access control rules to manage the target park, and generate a park management dataset, which includes personnel management data and vehicle management data; Based on the aforementioned park management dataset, evaluation and optimization are performed to construct access control management decisions for intelligent access control management of the target park. Based on the personnel management data, extract the personnel management record data for the kth group; A fitness analysis is performed on the personnel management record data of the kth group to obtain the fitness of the personnel management data of the kth group. The fitness of the personnel management data of the kth group is obtained by weighting the personnel management triggering frequency characteristics and the personnel management triggering timeliness characteristics of the kth group. Determine whether the fitness of the management data of the k-th group of personnel is greater than or equal to the fitness of the management data of the (k-1)-th group of personnel; If the fitness of the personnel management data of the kth group is greater than or equal to the fitness of the personnel management data of the (k-1)th group, the personnel management record data of the (k-1)th group is added to the elimination data group. If the fitness of the personnel management data of the kth group is less than the fitness of the personnel management data of the (k-1)th group, the personnel management record data of the kth group is added to the elimination data group. The elimination data group is a data unit used to delete groups with low personnel management data fitness. Determine whether k satisfies the taboo list update cycle, where the taboo list update cycle is used to characterize the number of iterations in which the taboo object is prohibited in the taboo list, and the taboo object is the fitness of the k-th group of personnel management data; If k satisfies the taboo table update cycle, the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel is input into the taboo table for update. It is then determined whether the taboo table update count meets the preset update count. The taboo table is a data structure used to store taboo objects. If the number of times the taboo list is updated meets the preset number of updates, then the initial value of the taboo list is extracted based on the taboo list, wherein the initial value of the taboo list has the adaptability of the taboo personnel management data; Determine whether the fitness of the management data of the kth group of personnel or the fitness of the management data of the (k-1)th group of personnel is greater than or equal to the fitness of the management data of the prohibited personnel. If it is greater than or equal to, the initial value of the taboo table is replaced according to the personnel management record data of the kth group or the personnel management record data of the (k-1)th group, and set as the taboo table update value; If it is less than, set the initial value of the taboo table to the updated value of the taboo table, and set the personnel management optimization data according to the updated value of the taboo table; The management strategy for the target park is updated based on personnel control optimization data.

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