Smart park safety operation and maintenance system and method

Abstract

The invention discloses a security operation and maintenance system and method for a smart park, and relates to the technical field of smart parks, and the method comprises the steps: carrying out the preprocessing of visitor information and access data through a cloud server through the cooperative work of an online reservation platform and sensor equipment, and generating a basic data feature vector Xtrack; visitor management is changed from manual operation to intelligent and automatic management. Visitors submit information through the online reservation platform and construct the data feature vectors in combination with the data collected by the sensor equipment, and then feature extraction and normalization processing are performed on the cloud, so that human errors are avoided, and the efficiency and accuracy of data processing are improved. By generating an authority factor Fauth, an authorization area set Rauth and a visitor dynamic authorization code Qauth, the access authority of the visitor can be dynamically adjusted according to real-time data, so that only the visitor meeting the condition can enter a specified area.

Description

Technical Field

[0001] The present invention relates to the technical field of smart parks, and specifically to a security operation and maintenance system and method for smart parks. Background Technique

[0002] The security operation and maintenance of smart parks involves modern park management and security technologies. With the continuous development of technologies such as information technology, Internet of Things (IoT), big data, and cloud computing, smart parks have become an important part of urban management. Smart parks not only focus on the management of infrastructure, resource optimization, and environmental monitoring within the park, but also increasingly attach importance to the visitor management and security operation and maintenance in the park to ensure the safety of personnel, the normal operation of equipment, and the effective utilization of resources within the park. In this field, the dynamic management and permission control of visitors have become key issues. Especially in parks with high security requirements, how to intelligently control the entry, access, and behavior of visitors has become a difficult problem to be solved urgently in park management.

[0003] At the present stage, the existing park security management methods mainly rely on traditional manual review and equipment control, such as visitor registration, identity verification, and access control. However, this method has multiple limitations. Firstly, it is inefficient and relies on manual work. Since a large amount of visitor information and data need to be manually reviewed, it is easy to have human omissions or errors. Secondly, static permission allocation cannot meet the requirements of complex and dynamic park environment. Especially when factors such as the security level, real-time load, and environmental conditions of different areas within the park change, the traditional method cannot adjust permissions in a timely manner and perform dynamic control. In addition, due to the limited data collection and processing capabilities of various sensors and devices within the park, data islands often occur, and effective integration and analysis cannot be carried out, thus affecting the accurate management and behavior analysis of visitors. Finally, the technologies in behavior monitoring and compliance inspection are still relatively backward. The existing methods mostly rely on simple camera monitoring and lack intelligent analysis and instant judgment based on data. Summary of the Invention

[0004] In view of the deficiencies of the prior art, the present invention provides a security operation and maintenance system and method for smart parks, which solves the problems mentioned in the background technique.

[0005] To achieve the above objectives, the present invention is realized through the following technical solutions: including the following steps:

[0006] S1. Submit visitor information through an online reservation platform, combine with sensor devices in the smart park to collect access data, construct a cloud server, transmit the obtained visitor information and access data to the cloud server, and perform preprocessing in the cloud server to generate basic data feature vectors;

[0007] S2. The cloud server audits the basic data feature vectors of the visitor according to the smart park rules, outputs the audit result A, allocates permissions after passing the audit, generates a permission factor Fauth, generates an authorized area set Rauth based on the permission factor Fauth, and generates a visitor dynamic authorization code Qauth based on the obtained authorized area set Rauth;

[0008] S3. Authenticate the identity through the visitor dynamic authorization code Qauth, output the access verification result Vauth, and control the visitor's access area based on the access verification result Vauth;

[0009] S4. Real-time collect the behavior data of the visitor through intelligent cameras and access control devices, generate a behavior feature set Xtarck, and perform compliance verification based on the behavior feature set Xtarck and the authorized area, and output a compliance identifier Ctrack;

[0010] S5. Combine the visitor's permission factor Fauth, access verification result Vauth and compliance identifier Ctrack for summary calculation, generate an access metric Efinal, set an access threshold Eth, then compare the access threshold Eth with the execution result to evaluate and analyze the current visitor's access situation, and generate corresponding security measures based on the evaluation result.

[0011] Preferably, the S1 includes S11 and S12;

[0012] S11. The online reservation platform includes a reservation mini-program, a smart park official website, and an APP application;

[0013] The visitor information includes name Xm, ID number Sfz, phone number Dh, access start timestamp t start 、access end timestamp t end and access area set Rreq;

[0014] The sensor devices include a number monitoring sensor, a visitor device, a temperature sensor, a humidity sensor, and an air quality sensor;

[0015] The access data includes the number of people Qm in the mth smart park area, the power Pdev of the visitor device, the temperature Henv, the humidity Tenv, and the air quality index AQI;

[0016] S12. Connect the online reservation platform to the cloud server through a communication network, and transmit the visitor information to the cloud server;

[0017] At the same time, connect the sensor devices to the cloud server through the local area network in the smart park, and transmit the access data to the cloud server;

[0018] Receive visitor information and access data in real time in the cloud server, and preprocess the visitor information and access data to obtain the basic data feature vector;

[0019] The preprocessing includes encoding conversion, feature extraction and normalization processing;

[0020] The basic data feature vector includes the unique identity identifier U, the access time range (t start , t end ), the access area set Rreq, the area congestion degree Yjd, the environmental impact factor Hj, and the visitor device power Pdev;

[0021] The specific preprocessing method of the encoding conversion and feature extraction is as follows:

[0022] The name Xm is mapped to a numerical value through the character length;

[0023] The ID number Sfz is normalized to a floating-point value in [0, 1] after compliance verification;

[0024] The phone number Dh is mapped to the hash space after compliance verification;

[0025] The unique identity identifier U is generated by using the hash algorithm for the name Xm, the ID number Sfz, and the phone number Dh. The specific generation formula is: U = Hash(Xm + Sfz + Dh), where Hash represents the hash algorithm;

[0026] The access start timestamp t start and the access end timestamp t end are recorded through the UNIX timestamp to generate the access time range (t start , t end );

[0027] The access area set Rreq is generated by numbering all areas in the smart park using one-hot encoding and allowing visitors to select the areas to visit on the online reservation platform. The access area set Rreq includes [r 1 , r 2 , r 3 ,..., r m ; where r represents the smart park area number, and rm represents the mth smart park area number;

[0028] All parameters in the access data are normalized to eliminate the influence of dimensions;

[0029] When summarizing and calculating the temperature Henv, humidity Tenv, and air quality index AQI in the access data to obtain the environmental impact factor Hj, the specific algorithm formula is: Hj = Henv·a1 + Tenv·a2 + AQI·a3, where a1, a2, and a3 respectively represent the weight values of the temperature Henv, humidity Tenv, and air quality index AQI, and a1 + a2 + a3 = 1. Their specific values are set by the user;

[0030] At the same time, based on the number of people Qm in the m-th smart park area, calculate and output the area congestion degree Yjd. The specific algorithm is:

[0031] where maxM represents the upper limit value of the area capacity.

[0032] Preferably, S2 includes S21, S22, and S23;

[0033] S21. According to the rules set for the smart park, review the basic data feature vector of the visitor through the review formula, mark the review result as A, and obtain the review result A;

[0034] The review result A is reviewed through the following review formula;

[0035] A = f(Rreq ∩ Rallow, (t start ,t end ));

[0036] where Rallow represents the set of areas allowed to be accessed in the smart park, f represents the smart park area and time verification function. When the output result of the review result A is 1, the review is passed; when the data result of the review result A is 0, the review fails.

[0037] Preferably, S22. Assign permissions to the visitors who pass the review. The permission assignment is to construct a permission factor calculation formula, extract the area congestion degree Yjd, environmental impact factor Hj, and visitor device power Pdev in the basic data feature vector, input them into the permission factor calculation formula, and calculate and output the permission factor Fauth;

[0038] The permission factor Fauth is output through the following permission factor calculation formula;

[0039]

[0040] In the formula, α represents the environmental impact factor adjustment coefficient, β represents the area congestion degree adjustment coefficient, γ represents the visitor device power adjustment factor, max represents the upper limit value, and Pmax represents the upper limit device power consumption of the visitor device;

[0041] S23. Based on the permission factor Fauth, allocate the permission area set and obtain the authorized area set Rauth. The authorized area set Rauth is generated by the following formula;

[0042] Rauth = {r|r ∈ Rreq, Fauth ≥ Fth};

[0043] In the formula, Fth represents the permission threshold, and r ∈ Rreq means that only the access area set is allocated during permission allocation.

[0044] Preferably, the said S3 includes S31 and S32;

[0045] S31. After allocating the visitor's permission, generate the visitor's dynamic authorization code Qauth according to the visitor's unique identity identifier U, the access time range (t start , t end ), and the authorized area set Rauth;

[0046] The visitor's dynamic authorization code Qauth is generated by the following formula;

[0047] Qauth = HMAC SHA256 (U||(t start , t end ), K);

[0048] In the formula, HMAC SHA256 represents the hash message authentication encryption algorithm, and K represents the key.

[0049] Preferably, S32. When the visitor enters the smart park again, input the visitor's dynamic authorization code Qauth through the smart park access device. Based on the input visitor's dynamic authorization code Qauth, verify and output the access verification result Vauth, and control the visitor's access area based on the verification result;

[0050] The access verification result Vauth is verified by the following formula;

[0051]

[0052] In the formula, Rcurrent represents the area where the visitor is currently attempting to enter, Tnow represents the current access time, and just means that both conditions are satisfied;

[0053] When the output result of the access verification result Vauth is 1, the visitor verification passes;

[0054] When the output result of the access verification result Vauth is 0, the visitor verification fails and access is refused.

[0055] Preferably, the said S4 includes S41 and S42;

[0056] S41. After the visitor verification is passed, the intelligent cameras and access control devices installed inside the smart park are used to capture the behavior feature vector Xtrack of the visitor in the smart park area in real time. The behavior feature vector Xtrack includes l1, l2, l3,..., lk, where l represents a location point, which is set by the access control number and the camera number, and k represents the total number of location points passed by the visitor.

[0057] S42. Based on the obtained behavior feature vector Xtrack, a compliance flag Ctrack is determined and output, and based on the compliance flag Ctrack, the behavior compliance of the visitor is determined according to the result.

[0058] The compliance flag Ctrack is judged by the following formula;

[0059]

[0060] When the output result of the compliance flag Ctrack is 1, it means that the visitor's behavior is compliant;

[0061] When the output result of the compliance flag Ctrack is 0, it means that the visitor's behavior is non-compliant. At this time, a warning is sent to the management client through the cloud server.

[0062] Preferably, S5 includes S51 and S52;

[0063] S51. Based on the obtained permission factor Fauth, access verification result Vauth and compliance flag Ctrack of the visitor, a summary calculation is performed to generate an access metric Efinal, and the access situation of the current visitor is comprehensively analyzed.

[0064] The access metric Efinal is calculated and output by the following algorithm formula;

[0065] Efinal = Fauth · Vauth · Ctrack.

[0066] Preferably, S52. Based on the access rules of the smart park, the user sets an access threshold Eth, and compares and evaluates the access threshold Eth with the access metric Efinal of the visitor, analyzes the access situation of the current visitor, and generates corresponding security measures based on the evaluation result. The specific evaluation content is as follows;

[0067] When the access metric Efinal ≥ the access threshold Eth, it means that the visitor's access is normal and the visitor is allowed to continue the access;

[0068] When the access metric Efinal < access threshold Eth, it indicates that the visitor's access is abnormal. At this time, the cloud server sends the time limit for leaving to the visitor's client and eliminates the visitor's dynamic authorization code Qauth.

[0069] A smart park security operation and maintenance system includes a visitor reservation module, an audit and permission allocation module, a verification module, a compliance analysis module, and a comprehensive analysis module;

[0070] The visitor reservation module submits visitor information through an online reservation platform, combines with sensor devices in the smart park to collect access data, constructs a cloud server, transmits the obtained visitor information and access data to the cloud server, and performs preprocessing in the cloud server to generate a basic data feature vector;

[0071] The audit and permission allocation module audits the basic data feature vector of the visitor according to the smart park rules, outputs the audit result A, performs permission allocation after passing the audit, generates a permission factor Fauth, and generates an authorized area set Rauth based on the permission factor Fauth, and generates a visitor dynamic authorization code Qauth based on the obtained authorized area set Rauth;

[0072] The verification module authenticates the identity through the visitor dynamic authorization code Qauth, outputs the access verification result Vauth, and controls the visitor's access area based on the access verification result Vauth;

[0073] The compliance analysis module collects the behavior data of the visitor in real time through intelligent cameras and access control devices, generates a behavior feature set Xtarck, and performs compliance verification based on the behavior feature set Xtarck and the authorized area, and outputs a compliance identifier Ctrack;

[0074] The comprehensive analysis module performs summary calculations by combining the visitor's permission factor Fauth, access verification result Vauth, and compliance identifier Ctrack, generates an access metric Efinal, sets an access threshold Eth, then compares the access threshold Eth with the execution result to evaluate and analyze the current visitor's access situation, and generates corresponding security measures based on the evaluation result.

[0075] The present invention provides a smart park security operation and maintenance system and method. It has the following beneficial effects:

[0076] (1) This method enables the collaborative work between an online reservation platform and sensor devices, and uses a cloud server to preprocess visitor information and access data, generating a basic data feature vector Xtrack, which transforms visitor management from manual operation to intelligent and automated management. Visitors submit information through the online reservation platform and construct a data feature vector by combining the data collected by sensor devices. Subsequently, feature extraction and normalization processing are performed in the cloud, avoiding human errors and improving the efficiency and accuracy of data processing. By generating a permission factor Fauth, an authorized area set Rauth, and a visitor dynamic authorization code Qauth, the access rights of visitors can be dynamically adjusted according to real-time data, ensuring that only eligible visitors can enter the designated area. During this process, automated permission allocation and real-time data processing greatly improve the efficiency and accuracy of park management, avoiding potential oversights during manual review.

[0077] (2) This method introduces intelligent cameras and access control devices to collect the behavior data of visitors in real time and generate a behavior feature set Xtrack. By combining the compliance verification of authorized areas, it can accurately determine whether a visitor violates the park's safety regulations. Compliance checking is performed based on the intersection of the behavior feature set Xtrack and the authorized area Rauth, and a compliance flag Ctrack is output. When Ctrack = 1, the visitor's behavior complies with the park's regulations; otherwise, it is non-compliant, and a warning signal will be immediately sent to the management personnel and necessary security measures will be taken. In this way, the park can take safety precautions immediately when a visitor fails to complete a scheduled task or exhibits abnormal behavior, avoiding potential security risks. At the same time, the permission factor Fauth, as a key parameter for security control, determines whether a visitor can enter a specific high-security area. Through the permission factor calculation formula, by combining data such as the area congestion degree Yjd, the environmental impact factor Hj, and the visitor device power Pdev, the access rights of visitors can be intelligently allocated to prevent unauthorized visitors from entering sensitive areas. The overall intelligent behavior monitoring and compliance verification mechanism enables the park to promptly detect potential threats and strengthen responses, thus significantly improving the security of the park.

[0078] (3) This method can optimize the allocation of park resources and reduce operating costs by combining the visitor dynamic authorization code Qauth and the comprehensive evaluation access index Efinal. The visitor dynamic authorization code Qauth is based on the visitor's unique identity identifier UUU, the access time range (t start , t end) and the authorized area set Rauth are generated to ensure that each visitor can only access their authorized areas when entering the park. In this process, both the permission factor Fauth and the access verification result Vauth participate in the comprehensive evaluation of the visitor's access behavior to generate the access metric Efinal. After comparing this metric with the access threshold Eth, it helps the park administrator to judge the compliance of the visitor's access in real time. When the access metric Efinal ≥ the access threshold Eth, it means that the visitor's behavior is normal and they can continue to access; otherwise, when the access metric Efinal < the access threshold Eth, an anomaly will be triggered and security measures such as leaving within a time limit will be taken. This mechanism enables the park to dynamically supervise the visitor's behavior in multiple dimensions, detect abnormal behaviors in a timely manner, and prevent the abuse or waste of park resources. Through this method, the park can efficiently manage the visitor flow, regulate the population density in the area, avoid overcrowding, optimize the resource allocation of each area, reduce the additional costs caused by security incidents or management mistakes, and improve the economic efficiency and sustainable development of the park operation. Description of the Drawings

[0079] Figure 1 Schematic diagram of the steps of a smart park security operation and maintenance method of the present invention;

[0080] Figure 2 Schematic diagram of the process of a smart park security operation and maintenance system of the present invention. Detailed Embodiments

[0081] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0082] Embodiment 1

[0083] Please refer to Figure 1 , the present invention provides a smart park security operation and maintenance method. To achieve the above objectives, the present invention is implemented through the following technical solutions: including the following steps:

[0084] S1. Submit visitor information through an online reservation platform, collect access data in combination with sensor devices in the smart park, construct a cloud server, transmit the obtained visitor information and access data to the cloud server, and perform preprocessing in the cloud server to generate basic data feature vectors;

[0085] S2. The cloud server reviews the basic data feature vectors of the visitor according to the smart park rules, outputs the review result A, assigns permissions after passing the review, generates the permission factor Fauth, generates the authorized area set Rauth based on the permission factor Fauth, and generates the visitor dynamic authorization code Qauth based on the obtained authorized area set Rauth;

[0086] S3. Authenticate the identity through the visitor dynamic authorization code Qauth, output the access verification result Vauth, and control the visitor's access area based on the access verification result Vauth;

[0087] S4. Real-time collect the behavior data of the visitor through the intelligent camera and access control device, generate the behavior feature set Xtarck, and perform compliance verification according to the behavior feature set Xtarck and the permission area, and output the compliance identifier Ctrack;

[0088] S5. Combine the visitor's permission factor Fauth, access verification result Vauth and compliance identifier Ctrack for summary calculation, generate the access metric Efinal, set the access threshold Eth, then compare the access threshold Eth with the execution result to evaluate and analyze the current visitor's access situation, and generate corresponding security measures based on the evaluation result.

[0089] In this embodiment, the method submits personal information through an online reservation platform, combines environmental data collected by sensor devices in the park, generates a basic data feature vector, and transmits it to the cloud server for processing. On this basis, the cloud server reviews the visitor information according to the park security rules, generates a review result A, calculates an authorization factor Fauth after passing the review, further generates an authorized area set Rauth and a dynamic authorization code Qauth for the visitor. The visitor uses the dynamic authorization code for identity verification, outputs an access verification result Vauth, and controls the visitor's access area according to the verification result to ensure that their behavior complies with the authorized scope. Further, real-time visitor behavior data is collected through intelligent cameras and access control devices, generates a behavior feature set Xtrack, and performs compliance verification with the authorized area, outputs a compliance identifier Ctrack to ensure that the visitor's behavior is compliant. Once all data processing is completed, the access metric Efinal is calculated by integrating the visitor's authorization factor, access verification result, and compliance identifier, and compared with the access threshold Eth. Based on the evaluation result, corresponding security measures are dynamically generated, such as normal access or access anomaly alerts, permission adjustments, etc. The implementation of this method through intelligent visitor management and behavior monitoring not only ensures that the visitor's access rights are strictly compliant, prevents unauthorized personnel from entering sensitive areas, and improves the security of the park; at the same time, combined with real-time monitoring and compliance verification of behavior data, it ensures that the visitor's behavior complies with the park security rules, effectively reducing potential security risks. Through dynamic evaluation and adaptive security measures, the method further improves the park's response ability and management efficiency to abnormal access.

[0090] Embodiment 2

[0091] Specifically: S1 includes S11 and S12;

[0092] S11. The online reservation platform includes a reservation mini-program, a smart park official website, and an APP application;

[0093] Visitor information includes name Xm, ID number Sfz, phone number Dh, access start timestamp t start and access end timestamp t end and access area set Rreq;

[0094] Sensor devices include a number monitoring sensor, a visitor device, a temperature sensor, a humidity sensor, and an air quality sensor;

[0095] Access data includes the number of people Qm in the mth smart park area, the power Pdev of the visitor device, temperature Henv, humidity Tenv, and air quality index AQI;

[0096] S12. Connect the online reservation platform to the cloud server through a communication network and transmit the visitor information to the cloud server;

[0097] Meanwhile, connect the sensor device to the cloud server through the local area network in the smart park, and transmit the access data to the cloud server;

[0098] Receive the visitor information and access data in real time in the cloud server, and preprocess the visitor information and access data to obtain the basic data feature vector;

[0099] The preprocessing includes encoding conversion, feature extraction and normalization processing;

[0100] The basic data feature vector includes the unique identity U, the access time range (t start , t end ), the access area set Rreq, the area congestion degree Yjd, the environmental impact factor Hj, and the visitor device power Pdev;

[0101] The specific preprocessing methods of encoding conversion and feature extraction are as follows:

[0102] The name Xm is mapped to a numerical value through the character length;

[0103] The ID number Sfz is normalized to a floating-point value in [0, 1] after compliance verification;

[0104] The phone number Dh is mapped to the hash space after compliance verification;

[0105] Generate the unique identity U through the name Xm, the ID number Sfz, and the phone number Dh by using the hash algorithm. The specific generation formula is: U = Hash(Xm + Sfz + Dh), where Hash represents the hash algorithm;

[0106] The access start timestamp t start and the access end timestamp t end are recorded through the UNIX timestamp to generate the access time range (t start , t end );

[0107] The access area set Rreq is generated by numbering all areas in the smart park using one-hot encoding. The visitor selects the access area in the online reservation platform, and the access area set Rreq is generated. The access area set Rreq includes [r 1 , r 2 , r 3 ,..., r m ; where r represents the smart park area number, and rm represents the m-th smart park area number;

[0108] Normalize all parameters in the access data to eliminate the influence of dimensions;

[0109] The temperature Heenv, humidity Tenv and air quality index AQI in the access data are summarized and calculated to obtain the environmental impact factor Hj. The specific algorithm formula is: Hj = Heenv a1 + Tenv a2 + AQI a3, where a1, a2 and a3 represent the weight values ​​of temperature Heenv, humidity Tenv and air quality index AQI respectively, and a1 + a2 + a3 = 1, and the specific value is set by the user;

[0110] At the same time, the regional congestion degree Yjd is calculated and output based on the number of people Qm in the mth smart park area. The specific algorithm is:

[0111] Among them, maxM represents the upper limit of the area capacity.

[0112] In this embodiment, the method submits personal information through an online reservation platform. At the same time, sensor equipment in the park collects various types of environmental data in real time. These visitor information and sensor data are transmitted to the cloud server for centralized processing and analysis. In the cloud server, the visitor information and environmental data are preprocessed, including encoding conversion, feature extraction and normalization, and finally form a basic data feature vector. During the data preprocessing process, the visitor information and access data are preprocessed and converted into computer-processed data, which can evaluate the security status of the park in real time and dynamically adjust the visitor's access rights and area control. In particular, through visitor behavior monitoring based on real-time data, unauthorized access can be effectively prevented to ensure that visitors' activities in the park comply with predetermined security rules.

[0113] Example 3

[0114] Specifically: S2 includes S21, S22 and S23;

[0115] S21. According to the rules set by the smart park, the basic data feature vector of the visitor is audited by using an audit formula, and the audit result is marked as A, thereby obtaining the audit result A;

[0116] Audit result A is audited by the following audit formula;

[0117] A=f(Rreq∩Rallow,(t start , t end ));

[0118] Among them, Rallow represents the set of areas that the smart park allows access to, f represents the smart park area and time verification function, when the audit result A output result is 1, the audit is passed, when the audit result A data result is 0, the audit is not passed;

[0119] When \(R_{area} \cap R_{allow} \neq \varnothing\) and within the development time range of the smart park, \(f = 1\) (i.e., \(A = 1\)); otherwise, \(f = 0\) (i.e., \(A = 0\)).

[0120] S22. Assign permissions to the visitors who have passed the review. The permission assignment is carried out by constructing a permission factor calculation formula, extracting the regional congestion degree \(Y_{jd}\), environmental impact factor \(H_j\), and visitor device power \(P_{dev}\) from the basic data feature vector, inputting them into the permission factor calculation formula, and calculating to output the permission factor \(F_{auth}\).

[0121] The permission factor \(F_{auth}\) is output through the following permission factor calculation formula;

[0122]

[0123] In the formula, \(\alpha\) represents the environmental impact factor adjustment coefficient, \(\beta\) represents the regional congestion degree adjustment coefficient, \(\gamma\) represents the visitor device power adjustment factor, \(max\) represents the upper limit value, and \(P_{max}\) represents the upper limit of the visitor device power consumption;

[0124] S23. Based on the permission factor \(F_{auth}\), allocate the permission area set to obtain the authorized area set \(R_{auth}\). The authorized area set \(R_{auth}\) is generated through the following formula;

[0125] \(R_{auth}=\{r|r\in R_{req}, F_{auth}\geq F_{th}\}\);

[0126] In the formula, \(F_{th}\) represents the permission threshold, which is set according to the security level of different areas by the user. \(r\in R_{req}\) means that only the access area set is allocated during the permission assignment;

[0127] Only when the permission factor \(F_{auth}\) is greater than or equal to the set permission threshold \(F_{th}\) will the visitor be authorized to enter the area;

[0128] If the permission factor \(F_{auth}\) is lower than the permission threshold \(F_{th}\), the permission for this area will not be assigned to this visitor.

[0129] In this embodiment, during the audit phase, the method uses the set audit formula to conduct a strict audit of the basic data feature vector of the visitor by the cloud server to confirm whether the visitor meets the access conditions. Specifically, the audit result A is used to determine whether the visitor's request meets the security rules of the smart park by calculating the intersection of the visitor's access area and the park's allowed access area Rallow, combined with the verification of the access time. When the visitor's request meets the conditions, the audit is passed and A=1 is output, otherwise, the audit result A=0 is output, and the audit fails. In the authority allocation stage, for the visitors who have passed the audit, data such as the regional congestion Yjd, the environmental impact factor Hj, and the visitor's device power Pdev are extracted, and the authority factor Fauth is generated through the constructed authority factor calculation formula. The authority factor is dynamically adjusted according to factors such as environmental impact, regional congestion, and visitor device power, and the allocation of permissions is optimized according to the set adjustment coefficient. Subsequently, the specific area set Rauth that the visitor can access is further determined by the set authority threshold Fth, ensuring that only visitors who meet the authority factor conditions can enter the designated area. If the authority factor is lower than the set threshold, the access rights of the area will not be assigned to the visitor. This implementation method not only ensures the accurate allocation of visitor access rights, but also enhances the security and intelligent management capabilities of the park through comprehensive consideration of multi-dimensional data. Through dynamic monitoring of factors such as regional congestion and environmental impact, it can respond and adjust access rights in a timely manner to avoid safety hazards caused by congestion or unsuitable environment. At the same time, the intelligent permission control and review mechanism effectively reduces the possibility of human intervention and improves the efficiency and security of management.

[0130] Example 4

[0131] Specifically: S3 includes S31 and S32;

[0132] S31, after assigning visitor rights, according to the visitor's unique identity U, access time range (t start ,t end ) and the authorized area set Rauth to generate a visitor dynamic authorization code Qauth;

[0133] The visitor dynamic authorization code Qauth is generated by the following formula;

[0134] Qauth=HMAC SHA256 (U||(t start , t end )||Rauth, K);

[0135] In the formula, HMAC SHA256 It represents the hash message authentication encryption algorithm, K represents the key, which can only be known by the system server and the authorization management system.

[0136] S32. When a visitor enters the smart park again, the visitor inputs the dynamic authorization code Qauth through the smart park access device. Based on the input dynamic authorization code Qauth of the visitor, the access verification result Vauth is output after verification, and the access area of the visitor is controlled based on the verification result;

[0137] The access verification result Vauth is verified through the following formula;

[0138]

[0139] In the formula, Rcurrent represents the area where the visitor is currently attempting to enter, Tnow represents the current access time, and just means satisfying simultaneously;

[0140] When the output result of the access verification result Vauth is 1, the visitor verification passes;

[0141] When the output result of the access verification result Vauth is 0, the visitor verification fails and access is refused.

[0142] In this embodiment, the visitor obtains the dynamic authorization code Qauth generated according to their identity identifier U, access time range (t start , t end ) and the authorized area set Rauth during the permission allocation phase. This authorization code is generated through the HMAC SHA256 hash algorithm, ensuring data encryption and anti-tampering. The key K is only known to the system server and the authorization management system, thus effectively preventing the forgery and abuse of identity information. When the visitor attempts to enter the park, the visitor inputs their dynamic authorization code Qauth through the access device of the smart park, and verifies it according to the input authorization code, the current time Tnow, and the access area Rcurrent. If the verification passes, the access verification result Vauth = 1 is output and the visitor's access will be allowed; otherwise, if the verification fails, access will be refused, the verification result Vauth = 0 will be output, and corresponding security measures will be taken. This implementation method ensures more refined and secure access control in the park through the dynamically generated authorization code and strict verification process. Since the authorization code is dynamic and time-limited, visitors cannot bypass the security control by relying on expired or tampered authorization codes, thus improving the protection level of the park. In addition, this method effectively reduces the risks caused by improper visitor behavior or security vulnerabilities by comprehensively considering the visitor's time, area, and device permissions.

[0143] Embodiment 5

[0144] Specifically: S4 includes S41 and S42;

[0145] S41. After the visitor verification is passed, the intelligent cameras and access control devices installed inside the smart park are used to capture the behavior feature vector Xtrack of the visitor in the smart park area in real time. The behavior feature vector Xtrack includes l1, l2, l3,..., lk, where l represents the position point, which is set through the access control number and the camera number, and k represents the total number of position points passed by the visitor;

[0146] S42. Based on the obtained behavior feature vector Xtrack, a compliance flag Ctrack is determined and output, and based on the compliance flag Ctrack, the behavior compliance of the visitor is determined;

[0147] The compliance flag Ctrack is judged by the following formula;

[0148]

[0149] When the output result of the compliance flag Ctrack is 1, it means that the visitor's behavior is compliant;

[0150] When the output result of the compliance flag Ctrack is 0, it means that the visitor's behavior is non-compliant. At this time, a warning is sent to the management client through the cloud server to drive the visitor out of the current area.

[0151] In this embodiment, after the visitor identity verification, the behavior of the visitor entering the park will be captured in real time by the intelligent cameras and access control devices, generating a series of behavior feature vectors Xtrack. The behavior feature vector includes the position data of the visitor at different position points l1, l2, l3,..., lk, and these position points are identified by the access control number and the camera number. k represents the total number of position points passed by the visitor. These data reflect the dynamic behavior of the visitor in the park and can provide real-time and accurate behavior trajectories. Next, based on these real-time obtained behavior feature vectors Xtrack, the behavior of the visitor is judged to generate a compliance flag Ctrack. If the output result of the flag is 1, it means that the behavior of the visitor complies with the regulations, and the park management will allow it to continue to visit; if the output result is 0, it means that the behavior of the visitor does not comply with the regulations. At this time, a warning will be sent to the management client through the cloud server, and corresponding measures will be taken according to the specific situation, such as driving the visitor out of the current area. This implementation method significantly improves the real-time performance and accuracy of the park's security operation and maintenance. Through the real-time monitoring and behavior trajectory analysis of intelligent devices, it can react in time when the visitor deviates from the specified route or performs non-compliant behaviors. This not only enhances the security prevention ability of the park, but also efficiently manages the personnel flow to ensure that the activities in the park are always within the controllable range.

[0152] Embodiment 6

[0153] Specifically: S5 includes S51 and S52;

[0154] S51 calculates and aggregates based on the obtained permission factor Fauth, access verification result Vauth, and compliance identifier Ctrack of the visitor to generate an access metric Efinal, and comprehensively analyzes the current visitor's access situation;

[0155] The access metric Efinal is calculated and output through the following algorithm formula;

[0156] Efinal = Fauth · Vauth · Ctrack.

[0157] S52. Based on the access rules of the smart park, the user sets an access threshold Eth, compares and evaluates the access threshold Eth with the visitor's access metric Efinal, analyzes the current visitor's access situation, and generates corresponding security measures based on the evaluation results. The specific evaluation content is as follows;

[0158] When the access metric Efinal ≥ the access threshold Eth, it indicates that the visitor's access is normal and the visitor is allowed to continue accessing;

[0159] When the access metric Efinal < the access threshold Eth, it indicates that the visitor's access is abnormal. At this time, the cloud server sends the time limit to leave to the visitor's client, and eliminates the visitor's dynamic authorization code Qauth.

[0160] In this embodiment, the method comprehensively calculates a comprehensive access metric Efinal based on the visitor's permission factor Fauth, access verification result Vauth, and compliance identifier Ctrack, and comprehensively analyzes the current visitor's behavior and permissions. The access metric Efinal is obtained through the comprehensive operation of multiple key factors, which provides a quantitative evaluation of the visitor's access behavior for the park. Next, it is evaluated according to the preset access threshold Eth. If the comprehensive access metric Efinal ≥ the access threshold Eth, it indicates that the visitor's access behavior is normal and the visitor will be allowed to continue accessing the park; if the comprehensive access metric Efinal < the access threshold Eth, it indicates that the visitor's behavior is abnormal, and the cloud server will notify the visitor to leave within a time limit and cancel the visitor's dynamic authorization code Qauth, effectively preventing the visitor from continuing to access the park. The core of this implementation plan is to use the comprehensive access metric Efinal and the access threshold Eth to accurately analyze the visitor's access situation through precise analysis, timely discover and handle abnormal behaviors, and avoid potential security risks. This mechanism improves the security management level of the park, enabling managers to monitor and adjust security policies in real time to ensure that the operation of the park is always in a safe and controllable state.

[0161] Embodiment 7

[0162] Please refer toFigure 2 , a smart park security operation and maintenance system, including a visitor reservation module, an audit and permission allocation module, a verification module, a compliance analysis module, and a comprehensive analysis module;

[0163] The visitor reservation module submits visitor information through an online reservation platform, combines sensor devices in the smart park to collect access data, constructs a cloud server, transmits the obtained visitor information and access data to the cloud server, and performs preprocessing in the cloud server to generate basic data feature vectors;

[0164] The audit and permission allocation module audits the basic data feature vectors of visitors according to the smart park rules, outputs the audit result A, performs permission allocation after passing the audit, generates a permission factor Fauth, and generates an authorized area set Rauth based on the permission factor Fauth, and generates a visitor dynamic authorization code Qauth based on the obtained authorized area set Rauth;

[0165] The verification module authenticates the identity through the visitor dynamic authorization code Qauth, outputs the access verification result Vauth, and controls the access area of the visitor based on the access verification result Vauth;

[0166] The compliance analysis module collects the behavior data of visitors in real time through intelligent cameras and access control devices, generates a behavior feature set Xtarck, and performs compliance verification based on the behavior feature set Xtarck and the permission area, and outputs a compliance identifier Ctrack;

[0167] The comprehensive analysis module performs summary calculations by combining the visitor's permission factor Fauth, access verification result Vauth, and compliance identifier Ctrack, generates an access metric Efinal, sets an access threshold Eth, then compares the access threshold Eth with the execution result to evaluate and analyze the current visitor's access situation, and generates corresponding security measures based on the evaluation result.

[0168] Although the embodiments of the present invention have been shown and described, for those of ordinary skill in the art, it can be understood that various changes, modifications, substitutions, and variations can be made to these embodiments without departing from the principles and spirit of the present invention.

Claims

1. A smart park security operation and maintenance method, characterized by: The following steps are involved: S1. Submit visitor information through the online reservation platform, collect access data in combination with sensor equipment in the smart park, build a cloud server, transmit the acquired visitor information and access data to the cloud server, perform preprocessing in the cloud server, and generate basic data feature vectors; S2. The cloud server reviews the basic data feature vector of the visitor according to the smart park rules, outputs the review result A, allocates permissions after the review is passed, generates the permission factor Fauth, and generates the authorization area set Rauth based on the permission factor Fauth, and generates the visitor dynamic authorization code Qauth based on the obtained authorization area set Rauth; S3, authenticate the visitor through the visitor's dynamic authorization code Qauth, output the access verification result Vauth, and control the visitor's access area based on the access verification result Vauth; S4, collect visitor behavior data in real time through smart cameras and access control devices, generate a behavior feature set Xtarck, perform compliance verification based on the behavior feature set Xtarck and the permission area, and output a compliance mark Ctrack; S5. Combine the visitor's permission factor Fauth, access verification result Vauth and compliance identifier Ctrack for summary calculation to generate access indicator Efinal, set access threshold Eth, and then compare access threshold Eth with the execution result to evaluate and analyze the current visitor's access situation, and generate corresponding security measures based on the evaluation results.

2. A smart park security operation and maintenance method according to claim 1, characterized in that: Said S1 includes S11 and S12; S11. The online reservation platform includes a reservation applet, a smart park official website and an APP application; The visitor information includes name Xm, ID number Sfz, phone number Dh, visit start timestamp t start , access end timestamp t end and the access region set Rreq; The sensor devices include a number monitoring sensor, a visitor device, a temperature sensor, a humidity sensor, and an air quality sensor; The access data includes the number of people Qm in the mth smart park area, the visitor device power Pdev, the temperature Heenv, the humidity Tenv and the air quality index AQI; S12, connecting the online reservation platform to the cloud server through a communication network, and transmitting the visitor information to the cloud server; At the same time, the sensor equipment is connected to the cloud server through the local area network in the smart park, and the access data is transmitted to the cloud server; Receive visitor information and access data in real time in the cloud server, and pre-process the visitor information and access data to obtain basic data feature vectors; The preprocessing includes encoding conversion, feature extraction and normalization processing; The basic data feature vector includes a unique identity identifier U, an access time range (t start ,t end ), access area set Rreq, area congestion Yjd, environmental impact factor Hj and visitor equipment power Pdev; The specific preprocessing methods of the encoding conversion and feature extraction are as follows: The name Xm is mapped to a numerical value by character length; The ID card number Sfz is normalized to a floating point value of [0,1] after passing the compliance check; The telephone number Dh is mapped to the hash space after passing the compliance check; The name Xm, ID number Sfz and phone number Dh are combined through a hash algorithm to generate a unique identity U. The specific generation formula is: U = Hash (Xm + Sfz + Dh), where Hash represents the hash algorithm; The access start timestamp t start and the access end timestamp t end Generate access time range (t start ,t end ); The visit area set Rreq is generated by numbering all areas in the smart park by using one-hot encoding, and the visitor selects the park area to be visited on the online reservation platform to generate the visit area set Rreq, wherein the visit area set Rreq includes [r1, r2, r3, ..., r m ]; where r represents the smart park area number, and rm represents the mth smart park area number; All parameters in the access data are normalized to eliminate the dimension effect; The temperature Heenv, humidity Tenv and air quality index AQI in the access data are summarized and calculated to obtain the environmental impact factor Hj. The specific algorithm formula is: Hj = Heenv a1 + Tenv a2 + AQI a3, where a1, a2 and a3 represent the weight values ​​of temperature Heenv, humidity Tenv and air quality index AQI respectively, and a1 + a2 + a3 = 1, and the specific value is set by the user; At the same time, the regional congestion degree Yjd is calculated and output based on the number of people Qm in the mth smart park area. The specific algorithm is: Among them, maxM represents the upper limit of the area capacity.

3. A smart park security operation and maintenance method according to claim 2, characterized in that: The S2 includes S21, S22 and S23; S21. According to the rules set by the smart park, the basic data feature vector of the visitor is audited by using an audit formula, and the audit result is marked as A, thereby obtaining the audit result A; The audit result A is audited by the following audit formula; A=f(Rreq∩Rallow,(t start ,t end )); Among them, Rallow represents the set of areas that the smart park allows access to, f represents the smart park area and time verification function, when the audit result A output result is 1, the audit is passed, when the audit result A data result is 0, the audit fails.

4. A smart park security operation and maintenance method according to claim 3, characterized in that: S22, assigning permissions to the approved visitors, wherein the permission allocation is performed by constructing a permission factor calculation formula, extracting the regional congestion Yjd, environmental impact factor Hj and visitor device power Pdev in the basic data feature vector, inputting them into the permission factor calculation formula, and calculating and outputting the permission factor Fauth; The authority factor Fauth is output by the following authority factor calculation formula; Where α represents the environmental impact factor adjustment coefficient, β represents the regional congestion adjustment coefficient, γ represents the guest device power adjustment factor, max represents the upper limit value, and Pmax represents the guest device power consumption; S23. Based on the authority factor Fauth, assign an authority region set to obtain an authorization region set Rauth. The authorization region set Rauth is generated by the following formula; Rauth={r|r∈Rreq, Fauth≥Fth}; Where Fth represents the permission threshold, and r∈Rreq means that only the access area set is allocated when permissions are allocated.

5. A smart park security operation and maintenance method according to claim 4, characterized in that: The S3 includes S31 and S32; S31, after assigning visitor rights, according to the visitor's unique identity U, access time range (t start ,t end ) and the authorized area set Rauth to generate a visitor dynamic authorization code Qauth; The visitor dynamic authorization code Qauth is generated by the following formula; Qauth=HMAC SHA256 (U||(t start ,t end )||Rauth,K); In the formula, HMAC SHA256 represents the hash message authentication encryption algorithm, and K represents the key.

6. A smart park security operation and maintenance method according to claim 1, characterized in that: S32. When the visitor enters the smart park again, the visitor enters the visitor's dynamic authorization code Qauth through the smart park access device, performs verification based on the entered visitor's dynamic authorization code Qauth, outputs the access verification result Vauth, and controls the visitor's access area based on the verification result; The access verification result Vauth is verified by the following formula; In the formula, Rcurrent represents the area that the visitor is currently trying to enter, Tnow represents the current access time, and just represents that both conditions are satisfied at the same time; When the output result of the access verification result Vauth is 1, the visitor verification is passed; When the output result of the access verification result Vauth is 0, the visitor verification fails and access is denied.

7. A smart park security operation and maintenance method according to claim 6, characterized in that: The S4 includes S41 and S42; S41. After the visitor is verified, the smart camera and access control equipment installed inside the smart park are used to capture the visitor's behavior feature vector Xtrack in real time in the smart park area. The behavior feature vector Xtrack includes l1, l2, l3, ..., lk, where l represents a location point, which is set by the access control number and the camera number, and k represents the total number of location points passed by the visitor; S42, determining and outputting a compliance mark Ctrack based on the obtained behavior feature vector Xtrack, and determining the behavior compliance of the visitor based on the output result of the compliance mark Ctrack; The compliance mark Ctrack is determined by the following formula; When the output result of the compliance indicator Ctrack is 1, it means that the visitor's behavior is compliant; When the output result of the compliance indicator Ctrack is 0, it means that the visitor behavior is not compliant. At this time, an early warning is sent to the management client through the cloud server.

8. A smart park security operation and maintenance method according to claim 6, characterized in that: The S5 includes S51 and S52; S51 performs summary calculation based on the obtained visitor's permission factor Fauth, access verification result Vauth and compliance identifier Ctrack, generates access indicator Efinal, and comprehensively analyzes the access status of the current visitor; The access index Efinal is calculated and output by the following algorithm formula: Efinal=Fauth·Vauth·Ctrack.

9. A smart park security operation and maintenance method according to claim 8, characterized in that: S52. Based on the smart park access rules, the user sets the access threshold Eth, compares and evaluates the access threshold Eth with the visitor's access index Efinal, analyzes the current visitor's access situation, and generates corresponding security measures based on the evaluation results. The specific evaluation contents are as follows; When the access index Efinal ≥ the access threshold Eth, it means that the visitor's access is normal and is allowed to continue accessing; When the access indicator Efinal is less than the access threshold Eth, it indicates that the visitor's access is abnormal. At this time, the cloud server sends a deadline to the visitor's client and eliminates the visitor's dynamic authorization code Qauth.

10. A smart park security operation and maintenance system, applied to a smart park security operation and maintenance method according to any one of claims 1 to 9, characterized in that: It includes visitor reservation module, review and authority allocation module, verification module, compliance analysis module and comprehensive analysis module; The visitor reservation module submits visitor information through the online reservation platform, collects access data in combination with sensor devices in the smart park, builds a cloud server, transmits the acquired visitor information and access data to the cloud server, performs preprocessing in the cloud server, and generates a basic data feature vector; The review and authority allocation module reviews the basic data feature vector of the visitor according to the smart park rules, outputs the review result A, allocates authority after the review is passed, generates the authority factor Fauth, and generates the authorized area set Rauth according to the authority factor Fauth, and generates the visitor dynamic authorization code Qauth based on the obtained authorized area set Rauth; The verification module performs identity authentication through the visitor's dynamic authorization code Qauth, outputs an access verification result Vauth, and controls the visitor's access area based on the access verification result Vauth; The compliance analysis module collects visitor behavior data in real time through smart cameras and access control devices, generates a behavior feature set Xtarck, performs compliance verification based on the behavior feature set Xtarck and the permission area, and outputs a compliance mark Ctrack; The comprehensive analysis module generates an access index Efinal by summarizing and calculating the visitor's authority factor Fauth, the access verification result Vauth and the compliance identifier Ctrack, and sets an access threshold Eth. The access threshold Eth is then compared with the execution result to evaluate and analyze the current visitor's access situation, and corresponding security measures are generated based on the evaluation results.

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