A method and system for unified identity management and authentication

Abstract

The present application belongs to the technical field of intelligent construction site, and specifically relates to a unified identity management and authentication method and system, which realizes distributed recognition of worker identity and real-time permission management through edge computing devices, reduces dependence on central servers, and improves system response speed and reliability. The method can dynamically adjust permission levels and resource access permissions according to different construction stages and job requirements, ensuring the accuracy and efficiency of permission management. At the same time, through monitoring, analysis and feedback of operation behavior, the identity verification process and permission management strategy are continuously optimized, forming a complete closed-loop management mechanism, thereby significantly improving the efficiency and safety of intelligent construction site management. This innovation effectively solves the problems of real-time and flexibility in the prior art, and provides a safer and more efficient construction site management solution.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of smart construction sites, and specifically relates to a unified identity management and authentication method and system. BACKGROUND

[0002] In modern smart construction site management, traditional identity management and authentication methods usually rely on centralized control by a central server. This method has some significant limitations:

[0003] Bottleneck of centralized management: Since all identity verification and permission management tasks are handled by the central server, when the construction site is large or the number of workers is large, it is easy to cause the system load to be too high, the response speed to be slow, and even the risk of single point failure.

[0004] Lack of real-time and flexibility: The traditional method is difficult to achieve efficient adjustment of dynamic access control between different types of workers in different construction stages, especially in the case of widespread distribution of edge devices, it is difficult to update the permission level and access control in real time.

[0005] Security and efficiency problems: In a large-scale construction site environment, frequent identity verification and permission adjustment can increase network latency, affecting work efficiency. In addition, once the security of a single central server is compromised, the security of the entire system will be severely threatened.

[0006] In summary, the existing centralized identity management and authentication method is difficult to achieve distributed recognition of worker identities and real-time permission management on a smart construction site without relying on a central server, especially in dynamic access control between different types of workers in different construction stages. This not only affects the efficiency of construction site management, but also may cause security risks. SUMMARY

[0007] The purpose of the present application is to provide a unified identity management and authentication method and system, which effectively solves the problem of lack of real-time and flexibility in the prior art by introducing edge computing devices and dynamic permission management mechanisms, and improves the efficiency and security of smart construction site management.

[0008] To achieve the above purpose, the present application proposes a unified identity management and authentication method, which includes:

[0009] Assign a unique identity identifier to each worker and record it in the edge computing device. When the worker enters the construction site, use the identity identifier to perform first-time identification and login verification at the nearest edge computing node;

[0010] Based on the result of the first identification, the system dynamically updates the permission level of the worker, synchronizes the information within the edge network, and adjusts the access permission of the corresponding type of work to the resource in different construction stages according to the change of the permission level;

[0011] Through the adjustment of the access permission, the operation behavior of the worker is monitored and recorded in real time, and the work efficiency and safety compliance of each type of work are analyzed regularly by means of the record of the operation behavior, and the feedback is fed back to the edge node;

[0012] According to the feedback result, the next stage of identity verification process and permission management strategy are optimized to form a closed loop management, and the data of the closed loop management is summarized at the end of each construction stage to generate a comprehensive report.

[0013] Preferably, the unique identity identifier is assigned to each worker and recorded in the edge computing device, including:

[0014] Collecting the basic information of each worker, including name, position and employment time, generating a preliminary file;

[0015] Based on the preliminary file, a string A is formed by combining the initials of the name, the position code and the employment date, A=initials of the name+position code+employment date;

[0016] The string A is processed to calculate the sum of the ASCII values of its characters B, B=SUM(ASCII(A[i])), where i is the position of the character in the string;

[0017] Using the B value combined with the current timestamp C, a unique identity identifier ID is generated by the formula ID=MOD(B+C,10^8), and stored in the nearest edge computing node.

[0018] Preferably, when the worker enters the construction site, the identity identifier is used for the first identification and login verification in the nearest edge computing node, including:

[0019] When the worker approaches the entrance of the construction site, the identity recognition device worn by the worker automatically sends an information package containing the identity identifier ID to the nearest edge computing node;

[0020] The edge computing node extracts the identity identifier ID after receiving the information package, and generates a verification code D through the formula D=MOD(ID,10^4);

[0021] Based on the verification code D, the edge computing node queries the locally stored identity identifier database to find a matching item, and after confirming the validity of the verification code D, the edge computing node compares the complete identity identifier ID with the record in the database;

[0022] If the matching is successful, the worker is allowed to enter, and the worker's latest login time and location information E, E = current time + construction site location code, the edge computing node sends a notification containing the identity identifier ID and the latest login time and location information E to the central management system.

[0023] Preferably, based on the result of the first identification, the system dynamically updates the worker's permission level, and synchronizes information within the edge network, including:

[0024] After the comparison is successful, the edge computing node reads the current permission level F associated with the identity identifier ID;

[0025] Based on the latest login time and location information E, the edge computing node evaluates the current construction site environment and construction progress, and generates a dynamic adjustment factor G through the formula G = MOD(E, 10^3), which is used to reflect the change in permission requirements under the current environment;

[0026] Using the dynamic adjustment factor G, combined with the current permission level F, a new permission level F' is calculated, F' = F + G - INT((F + G) / 10)*10;

[0027] The edge computing node stores the updated permission level F' in the local database, and broadcasts an information package containing the identity identifier ID and the new permission level F' through the edge network, and the edge computing nodes receiving the broadcast information verify the validity of the identity identifier ID, and update the locally stored permission level to F'.

[0028] Preferably, according to the change of the permission level, the access permission of the corresponding type of work to the resources in different construction stages is adjusted, including:

[0029] When the edge computing node receives the updated permission level F', it reads the type of work information H and the current construction stage I associated with the identity identifier ID, based on the permission level F' and the type of work information H, a resource access adjustment factor K is generated through the formula K = MOD(F' + H, 10), which is used to determine the change of accessible resources under the current permission level;

[0030] Using the resource access adjustment factor K, combined with the current construction stage I, a new access permission set J' is calculated, J' = J + K - INT((J + K) / 10)*10;

[0031] The edge computing node stores the updated access permission set J' in the local database, and sends a notification containing the identity identifier ID, the type of work information H and the new access permission set J' to the resource management system to update the resource access control list;

[0032] The resource management system receives the notification, verifies the validity of the identity identifier ID, adjusts the access rights of the worker to the specific resource according to the new access right set J', records the change, and all related edge computing nodes receive and apply the new access right set J' synchronously.

[0033] Preferably, the worker's operation behavior is monitored and recorded in real time through the adjustment of the access rights, including:

[0034] In the edge computing node, an operation behavior log file L is created for each worker with a new access right set J';

[0035] When the worker accesses a certain resource, the edge computing node checks the access right set J' corresponding to the identity identifier ID, and if the access request meets the requirements of the access right set J', the access is allowed, and the access time and resource identifier M are recorded in the operation behavior log file L, that is, L = L + access time + M;

[0036] Based on the content of the operation behavior log file L, an operation behavior tracking code N is generated using the formula N = MOD(SUM(ASCII(L[i])), 100), where i is the position of the character in the log file;

[0037] At fixed time intervals, the edge computing node summarizes the data in the operation behavior log file L and sends the summary information O to the central management system. The summary information O includes the identity identifier ID, the latest operation time, the cumulative access times P, and the operation behavior tracking code N, where P = COUNT(L);

[0038] After receiving the summary information O, the central management system verifies the validity of the identity identifier ID and stores it in the central database. At the same time, the system evaluates whether the worker's operation behavior conforms to the safety specifications according to the cumulative access times P and the operation behavior tracking code N;

[0039] If abnormal operation behavior is found, the central management system immediately sends a warning notice to the related edge computing node.

[0040] Preferably, the operation behavior is recorded to periodically analyze the work efficiency and safety compliance of each type of work and feedback to the edge node, including:

[0041] The central management system extracts the operation behavior log L, the cumulative access times P, and the operation behavior tracking code N of each worker within the working time period from the summary information O, and generates a preliminary work efficiency indicator R for each type of work, where R = P / time period length.

[0042] Using the records in the operation behavior log L, the safety compliance score S of each job type is calculated, S = 100 - (SUM (abnormal operation times) * 10), wherein the abnormal operation times are obtained by comparing the operation behavior log L with the predefined safety specification;

[0043] Based on the work efficiency indicator R and the safety compliance score S, the central management system generates a comprehensive evaluation report T for each job type, which contains the identity identifier ID, the work efficiency indicator R, the safety compliance score S and the improvement suggestion, and the formula is: T = ID + R + S + improvement suggestion;

[0044] Every fixed period, the central management system sends the comprehensive evaluation report T to the relevant edge computing node, and after the edge node receives the comprehensive evaluation report T, it updates the locally stored work efficiency and safety compliance records of the relevant job type;

[0045] The edge computing node adjusts the permission level F' and the access permission set J' of the corresponding job type according to the improvement suggestion in the comprehensive evaluation report T, including: if the safety compliance score S is lower than the threshold, the access permission of high-risk resources in the access permission set J' is reduced; if the work efficiency indicator R is higher than the set standard, the access permission set J' is relaxed;

[0046] The edge computing node broadcasts the adjusted permission level F' and access permission set J' to the entire edge network again.

[0047] Preferably, the identity verification process and the permission management strategy of the next stage are optimized according to the feedback results, forming a closed-loop management, including:

[0048] The edge computing node receives the comprehensive evaluation report T from the central management system, and extracts the work efficiency indicator R and the safety compliance score S of each job type from it, and generates an optimization weight U for each job type, wherein U = R + S / 100, which is used for subsequent adjustment of the identity verification process and the permission management strategy;

[0049] Using the optimization weight U, the edge computing node reevaluates the effectiveness of the current identity verification process, generates a new verification factor V through the formula V = MOD (U, 10), V determines whether to add an additional identity verification step or simplify the existing process, based on the verification factor V, the identity verification process of the next stage is adjusted; if V is greater than 5, an additional identity confirmation step is added in the identity verification process; if V is less than or equal to 5, the existing process is simplified, and unnecessary verification steps are reduced;

[0050] According to the improvement suggestions in the comprehensive evaluation report T, combined with the optimization weight U, the edge computing node updates the permission management policy, including: for the job whose security compliance score S is lower than the threshold, reducing the access permission of high-risk resources in the access permission set J'; for the job whose work efficiency index R is higher than the set standard, relaxing the access permission set J;

[0051] The edge computing node synchronizes the updated identity verification process and permission management policy to the entire edge network, ensuring that all related nodes consistently apply the new rules, while recording the time W and the change content X of this change, i.e. W = current time, X = change details;

[0052] Every fixed period, the edge computing node summarizes all change records W and X and sends a summary report Y to the central management system, which contains all changes in identity verification processes and permission management policies.

[0053] Preferably, at the end of each construction phase, the data of the closed-loop management is summarized to generate a comprehensive report, including:

[0054] At the end of the current construction phase, the edge computing node collects all change records W and X related to the current construction phase and generates a phase summary index Z for each job, where Z = SUM(W) + COUNT(X), which is used to quantify the number and frequency of management changes in the phase;

[0055] Using the phase summary index Z, combined with the work efficiency index R and the security compliance score S of each job, a comprehensive performance score AA is calculated, the formula is: AA = (R*0.6 + S*0.4) / Z, to measure the comprehensive performance of each job in the entire construction phase;

[0056] Based on the comprehensive performance score AA, the edge computing node generates a performance analysis BB for each job, BB = job name + comprehensive performance score AA + performance details + improvement suggestions;

[0057] The edge computing node summarizes all performance analyses BB of the jobs into a comprehensive report CC, which includes the timeline of key events, main optimization measures and their effect evaluation in the entire construction phase, and generates a report abstract code DD through the formula DD = MOD(SUM(BB), 1000), which is used for quick retrieval and verification of report content;

[0058] The comprehensive report CC is sent to the central management system together with the report abstract code DD, and after receiving it, the central management system stores it in the central database and conducts global comparative analysis to identify the best practice cases and potential improvement areas;

[0059] The central management system sends a next-step action guide EE to the relevant edge computing node according to the content of the comprehensive report CC, and the guide contains specific optimization suggestions and expected targets for the next construction stage;

[0060] The edge computing node receives the action guide EE and adjusts the identity verification process and permission management strategy of the next construction stage according to the content of the guide, forming a new closed-loop management cycle.

[0061] In another aspect, the present application proposes a unified identity management and authentication system, comprising:

[0062] An identity identifier allocation identification module is used to allocate a unique identity identifier to each worker and record it in the edge computing device. When the worker enters the construction site, the identity identifier is used for first identification and login verification at the nearest edge computing node.

[0063] A permission level dynamic updating and synchronization module is used to dynamically update the permission level of the worker based on the result of the first identification, and synchronize the information within the edge network. According to the change of the permission level, the access permission of the corresponding type of work to the resources in different construction stages is adjusted.

[0064] An operation behavior monitoring and analysis module is used to monitor and record the operation behavior of the worker in real time through the adjustment of the access permission, and regularly analyze the work efficiency and safety compliance of each type of work with the help of the record of the operation behavior, and feedback to the edge node.

[0065] An optimization and summary module is used to optimize the identity verification process and permission management strategy of the next stage according to the feedback results, form a closed-loop management, and summarize the data of the closed-loop management at the end of each construction stage to generate a comprehensive report.

[0066] The technical effects and advantages of the present application: the unified identity management and authentication method and system proposed by the present application have the following advantages compared with the prior art:

[0067] The present application realizes distributed identification of worker identity and real-time permission management through edge computing devices, reduces the dependence on central servers, and improves the response speed and reliability of the system. The method can dynamically adjust the permission level and resource access permission according to the needs of different construction stages and types of work, ensuring the accuracy and efficiency of permission management. At the same time, through the monitoring, analysis and feedback of operation behavior, the identity verification process and permission management strategy are continuously optimized to form a complete closed-loop management mechanism, thereby significantly improving the efficiency and safety of intelligent construction site management. This innovation effectively solves the problem of insufficient real-time and flexibility in the prior art, and provides a safer and more efficient construction site management solution. BRIEF DESCRIPTION OF DRAWINGS

[0068] Figure 1 Flowchart of the unified identity management and authentication method of the present application;

[0069] Figure 2 Block diagram of the unified identity management and authentication system of the present application. DETAILED DESCRIPTION

[0070] The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The specific embodiments described herein are only used to explain the present application, and are not used to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0071] The present application provides a unified identity management and authentication method as shown in Figure 1 The present application provides a unified identity management and authentication method as shown in

[0072] The unified identity management and authentication method in the present embodiment comprises:

[0073] Step one: assign a unique identity identifier to each worker and record it in the edge computing device; specifically including:

[0074] Collect the basic information of each worker, including name, position and employment time, and generate a preliminary file; these information is the basic data source for generating a unique identity identifier, which ensures that each worker has clear identity information in the system.

[0075] Based on the preliminary file, a string A is formed by combining the initials of the name in pinyin, the position code and the employment date, A=initials of the name in pinyin+position code+employment date; the initials of the name in pinyin, the position code and the employment date are combined into a string A, so that the identity identifier of each worker has high uniqueness and readability. For example, Zhang San (Zhang San) is an electrician (position code 01), and the employment date is January 1, 2023 (20230101), then the string A is "ZS0120230101".

[0076] The string A is processed to calculate the sum B of the ASCII values of its characters, B=SUM(ASCII(A[i])), where i is the position of the character in the string; this value B can be used as the basis for generating a unique identity identifier, increasing the uniqueness of the identity identifier. For example, for the string A "ZS0120230101":

[0077] The ASCII value of Z is 90;

[0078] The ASCII value of S is 83;

[0079] The ASCII value of 0 is 48;

[0080] The ASCII value of 1 is 49;

[0081] The ASCII value of 2 is 50;

[0082] The ASCII value of 3 is 51;

[0083] B = 90 + 83 + 48 + 49 + 50 + 51 + 48 + 49 + 48 + 49 + 50 + 51 + 48 + 49 + 48 + 49 = 768.

[0084] Using the B value in combination with the current timestamp C, a unique identity identifier ID is generated using the formula ID = MOD(B + C, 10^8) and stored in the nearest edge computing node. ID = MOD(B + C, 10^8) is a unique identity identifier ID generated by taking the sum of character ASCII values B and the current timestamp C modulo 10^8. This method ensures that even if two workers have the same name pinyin initials, position codes, and hire dates, the final generated identity identifier will still be different due to the difference in the timestamp.

[0085] For example: Assuming the current timestamp C is 1673952360 (in seconds), then:

[0086] B = 768 (calculated from the previous step);

[0087] C = 1673952360;

[0088] ID = MOD(768 + 1673952360, 10^8) = MOD(1673953128, 100000000) = 3953128;

[0089] The final generated unique identity identifier ID is 3953128.

[0090] By combining the sum of character ASCII values B and the current timestamp C, a highly unique identity identifier ID is generated. This method not only ensures that each worker's identity identifier is unique, but also enables efficient storage and retrieval of these identifiers in edge computing nodes, improving the reliability and efficiency of the system. In addition, since a timestamp is used, even if multiple workers register at the same time, the uniqueness of their identity identifiers is guaranteed.

[0091] Step two: When the worker enters the site, use the identity identifier to perform the first identification and login verification at the nearest edge computing node; Specifically includes:

[0092] When the worker approaches the site entrance, the identity identification device (such as a smart card or mobile device) worn by the worker automatically sends an information package containing the identity identifier ID to the nearest edge computing node;

[0093] The edge computing node extracts the identity identifier ID after receiving the information package, and generates a verification code D through the formula D = MOD(ID, 10^4); D = MOD(ID, 10^4) is to generate a four-digit verification code D by taking the modulus of the identity identifier ID 10^4. This method can quickly generate a short verification code for preliminary verification of the validity of the identity identifier.

[0094] For example: Assuming the identity identifier ID is 3953128, then: D = MOD(3953128, 10000) = 3128; The final generated verification code D is 3128. By generating the verification code D, the validity of the identity identifier can be quickly verified in the preliminary stage, reducing unnecessary database query operations and improving the response speed of the system.

[0095] Based on the verification code D, the edge computing node queries the locally stored identity identifier database to find a matching item, and after confirming the validity of the verification code D, the edge computing node compares the complete identity identifier ID with the record in the database; This method ensures that only legitimate workers can enter the site, and improves the accuracy of identity verification through double verification (verification code and complete identity identifier).

[0096] If the match is successful, the worker is allowed to enter, and the latest login time and location information E of the worker is updated, E = current time + site location code. The edge computing node sends a notification containing the identity identifier ID and the latest login time and location information E to the central management system. The central management system can further analyze and decide based on these information, such as generating a comprehensive report, optimizing the permission management strategy, etc. At the same time, this also ensures the data consistency and reliability of all edge computing nodes.

[0097] Step three: Based on the results of the first identification, the system dynamically updates the worker's permission level, and synchronizes the information within the edge network; Specifically includes:

[0098] After the comparison is successful, the edge computing node reads the current permission level F associated with the identity identifier ID; This step ensures that subsequent permission adjustments are based on accurate basic data, avoiding errors or inconsistencies.

[0099] Based on the latest login time and location information E, the edge computing node evaluates the current construction site environment and construction progress, and generates a dynamic adjustment factor G through the formula G=MOD(E,10^3) to reflect the changes in permission requirements under the current environment; G=MOD(E,10^3) is a three-digit dynamic adjustment factor G generated by taking the modulus 10^3 of the latest login time and location information E. This method can simplify the complex login time and location information into a smaller value for quick adjustment of the permission level.

[0100] For example: Assuming the latest login time and location information E is "202503171010001" (i.e. March 17, 2025, 10:10, and the construction site location code is 001), then:

[0101] G=MOD(202503171010001,1000)=1, and the final generated dynamic adjustment factor G is 1.

[0102] By generating the dynamic adjustment factor G, the system can flexibly adjust the worker's permission level according to the latest construction site environment and construction progress. This dynamic adjustment mechanism makes the permission management more adaptable to actual work requirements, improving the flexibility and response speed of the system.

[0103] Using the dynamic adjustment factor G, in combination with the current permission level F, calculate the new permission level F', F'=F+G-INT((F+G) / 10)*10, which is by adding the current permission level F and the dynamic adjustment factor G, and subtracting the integer part of its division by 10 multiplied by 10, so as to ensure that the new permission level F' remains within a reasonable range (e.g. 0 to 9). This method ensures that the adjustment of the permission level does not exceed the preset range, while maintaining a certain flexibility.

[0104] For example: Assuming the current permission level F is 5 and the dynamic adjustment factor G is 1, then:

[0105] F'=5+1-INT((5+1) / 10)*10=6-INT(6 / 10)*10=6-0*10=6, and the final generated new permission level F' is 6.

[0106] By calculating the new permission level F', the system can make appropriate adjustments based on the existing permissions, ensuring that the permission level always meets the needs of the current construction site environment and construction progress. This adjustment mechanism not only improves the flexibility of permission management, but also enhances the security and efficiency of the system.

[0107] The edge computing node stores the updated permission level F' in the local database and broadcasts a packet containing the identity identifier ID and the new permission level F' through the edge network. The edge computing nodes receiving the broadcast information verify the validity of the identity identifier ID and update the locally stored permission level to F'.

[0108] Step four: adjust the access permission of resources for corresponding types of work in different construction stages according to the change of the permission level; specifically including:

[0109] When the edge computing node receives the updated permission level F', it reads the type of work information H and the current construction stage I associated with the identity identifier ID. Based on the permission level F' and the type of work information H, a resource access adjustment factor K is generated through the formula K = MOD(F' + H, 10) to determine the change of accessible resources under the current permission level.

[0110] K = MOD(F' + H, 10) is a resource access adjustment factor K generated by taking the modulus 10 of the sum of the permission level F' and the type of work information H. This method can simplify the complex permission level and type of work information into a smaller value for quick adjustment of resource access permission.

[0111] For example: assuming the updated permission level F' is 6 and the type of work information H is 3 (e.g. electrician), then:

[0112] K = MOD(6 + 3, 10) = MOD(9, 10) = 9;

[0113] The final generated resource access adjustment factor K is 9.

[0114] By generating the resource access adjustment factor K, the system can flexibly adjust the resource access permission according to the current permission level and the type of work information. This dynamic adjustment mechanism makes the resource access control more adaptive to actual work requirements, improving the flexibility and response speed of the system.

[0115] Using the resource access adjustment factor K, combined with the current construction stage I, calculate the new access permission set J', J' = J + K - INT((J + K) / 10) * 10; is by adding the current access permission set J and the resource access adjustment factor K, and subtracting the integer part of its divided by 10 multiplied by 10, so as to ensure that the new access permission set J' remains within a reasonable range (e.g. 0 to 9). This method ensures that the adjustment of access permission set will not exceed the preset range, while maintaining a certain flexibility.

[0116] For example: assuming the current access permission set J is 4 and the resource access adjustment factor K is 9, then:

[0117] J' = 4 + 9 - INT((4 + 9) / 10) * 10 = 13 - INT(13 / 10) * 10 = 13 - 1 * 10 = 13 - 10 = 3;

[0118] The final generated new access permission set J' is 3.

[0119] By calculating the new access permission set J', the system can make appropriate adjustments based on the existing access permissions, ensuring that resource access permissions always meet the current permission level, job information, and construction phase requirements.

[0120] The edge computing node stores the updated access permission set J' in the local database and sends a notification containing the identity identifier ID, job information H, and new access permission set J' to the resource management system to update the resource access control list.

[0121] After receiving the notification, the resource management system verifies the validity of the identity identifier ID and adjusts the worker's access permissions to the specific resource according to the new access permission set J', while recording this change. All related edge computing nodes synchronously receive and apply the new access permission set J', ensuring consistent resource access permissions on all nodes. This further enhances the security and reliability of the system, preventing unauthorized access and operations.

[0122] Step five: Real-time monitoring and recording of worker operation behavior through the adjustment of access permissions; specifically including:

[0123] In the edge computing node, an operation behavior log file L is created for each worker with a new access permission set J'. When a worker accesses a resource, the edge computing node checks the access permission set J' corresponding to the identity identifier ID. If the access request complies with the access permission set J', the access is allowed, and the access time and resource identifier M are recorded in the operation behavior log file L, i.e., L = L + access time + M. This mechanism ensures the security and compliance of resource access while providing detailed access records. For example:

[0124] Worker Zhang San (ID = 3953128) accesses resource R1 at 10:20 on March 17, 2025, with resource identifier M as "R1".

[0125] The operation behavior log file L is updated to: "202503171020R1".

[0126] Based on the content of the operation behavior log file L, an operation behavior tracking code N is generated using the formula N = MOD(SUM(ASCII(L[i])), 100), where i is the position of the character in the log file; this formula generates a two-digit operation behavior tracking code N by taking the modulus of 100 of the sum of the ASCII values of each character in the operation behavior log file L. This method can simplify complex operation behavior logs into a smaller numerical value for quick retrieval and verification of operation records within a specific time period.

[0127] For example: assuming the operation behavior log file L is "202503171020R1", then:

[0128] The ASCII values are: 50, 48, 50, 53, 48, 51, 49, 55, 49, 48, 50, 48, 82, 49;

[0129] SUM(ASCII(L[i])) = 50 + 48 + 50 + 53 + 48 + 51 + 49 + 55 + 49 + 48 + 50 + 48 + 82 + 49 = 683

[0130] N = MOD(683, 100) = 83;

[0131] The final operation behavior tracking code N is 83.

[0132] By generating the operation behavior tracking code N, the system can quickly retrieve and verify operation records within a specific time period based on the operation behavior log. This mechanism improves the response speed and query efficiency of the system, facilitating subsequent auditing and analysis.

[0133] Every fixed time interval, the edge computing node aggregates the data in the operation behavior log file L and sends the aggregated information O to the central management system, which includes the identity identifier ID, the latest operation time, the cumulative access count P (P = COUNT(L)), and the operation behavior tracking code N. For example: the identity identifier ID is 3953128, the latest operation time is March 17, 2025, 10:20, the cumulative access count P is 14 times, and the operation behavior tracking code N is 83. The aggregated information O is: "3953128, 202503171020, 14, 83".

[0134] After the central management system receives the summary information O, it verifies the validity of the identity identifier ID and stores it in the central database. At the same time, the system evaluates whether the worker's operation behavior conforms to the safety specifications based on the cumulative access number P and the operation behavior tracking code N. If abnormal operation behavior is found, the central management system immediately sends a warning notice to the relevant edge computing node. This mechanism can timely discover and handle potential safety hazards, enhancing the security of the system.

[0135] Step six: With the record of operation behavior, regularly analyze the work efficiency and safety compliance of each type of work and feedback to the edge node; specifically including:

[0136] The central management system extracts the operation behavior log L, cumulative access number P, and operation behavior tracking code N of each worker within the work time period from the summary information O, and generates a preliminary work efficiency indicator R for each type of work, where R = P / time period length. The work efficiency indicator R is calculated by dividing the cumulative access number P by the time period length (e.g., hours). This method can quantify the work efficiency of each type of work within a specific time period.

[0137] For example: Assuming that a type of work has a cumulative access number P of 40 times within an 8-hour work time period, then R = 40 / 8 = 5, and the final generated work efficiency indicator R is 5.

[0138] Using the records in the operation behavior log L, calculate the safety compliance score S for each type of work, S = 100 - (SUM (abnormal operation times) * 10), where abnormal operation times are obtained by comparing the operation behavior log L with the predefined safety specifications; is calculated by multiplying the sum of abnormal operation times by 10 and subtracting the value from 100 to calculate the safety compliance score S. This method can quantify the safety compliance level of each type of work.

[0139] For example: Assuming that a type of work has 3 abnormal operations within a period of time, then:

[0140] SUM (abnormal operation times) = 3;

[0141] S = 100 - (3 * 10) = 100 - 30 = 70;

[0142] The final generated safety compliance score S is 70.

[0143] By calculating the safety compliance score S, the system can quantify the safety compliance level of each type of work, facilitating the discovery of potential safety hazards and the implementation of appropriate improvement measures.

[0144] Based on the work efficiency indicator R and the safety compliance score S, the central management system generates a comprehensive evaluation report T for each job type, which includes the identity identifier ID, the work efficiency indicator R, the safety compliance score S, and improvement suggestions, and the formula is: T = ID + R + S + improvement suggestions;

[0145] Every fixed period, the central management system sends the comprehensive evaluation report T to the relevant edge computing node. After receiving the comprehensive evaluation report T, the edge node updates the local stored work efficiency and safety compliance records of the relevant job type;

[0146] The edge computing node adjusts the permission level F' and the access permission set J' of the corresponding job type according to the improvement suggestions in the comprehensive evaluation report T, including: if the safety compliance score S is lower than the threshold, reducing the high-risk resource access permission in the access permission set J'; if the work efficiency indicator R is higher than the set standard, relaxing the access permission set J'; the edge computing node broadcasts the adjusted permission level F' and access permission set J' to the entire edge network again. This distributed synchronization mechanism improves the reliability and consistency of the system, avoiding security risks caused by out-of-sync permission information.

[0147] Step seven: optimize the next stage of identity verification process and permission management strategy according to the feedback results, forming a closed-loop management; specifically including:

[0148] The edge computing node receives the comprehensive evaluation report T from the central management system and extracts the work efficiency indicator R and the safety compliance score S of each job type, and generates an optimization weight U for each job type, where U = R + S / 100, which is used for subsequent adjustment of the identity verification process and permission management strategy; this method can comprehensively consider work efficiency and safety compliance to generate a weight value for subsequent adjustment.

[0149] For example: assuming that the work efficiency indicator R of a certain job type is 3.75 and the safety compliance score S is 80, then: U = 3.75 + 80 / 100 = 3.75 + 0.8 = 4.55, and the final generated optimization weight U is 4.55.

[0150] Using the optimization weight U, the edge computing node re-evaluates the effectiveness of the current identity verification process, generates a new verification factor V through the formula V = MOD(U, 10), and V determines whether to add additional identity verification steps or simplify the existing process based on the verification factor V. V = MOD(U, 10) is a verification factor V generated by taking the modulus 10 of the optimization weight U. This method can simplify the complex optimization weight into a smaller value for quickly determining whether to adjust the identity verification process.

[0151] For example, if the optimization weight U is 4.55, then V = MOD(4.55, 10) = 4.55;

[0152] The final verification factor V is 4.55 (rounded to 4). If V is greater than 5, an additional identity confirmation step is added in the identity verification process; if V is less than or equal to 5, the existing process is simplified and unnecessary verification steps are reduced.

[0153] According to the improvement suggestions in the comprehensive evaluation report T and in combination with the optimization weight U, the edge computing node updates the permission management policy, including: for the job type with a security compliance score S lower than the threshold, reducing the high-risk resource access permission in the access permission set J'; for the job type with a work efficiency indicator R higher than the set standard, relaxing the access permission set J.

[0154] The edge computing node synchronizes the updated identity verification process and permission management policy to the entire edge network, ensuring that all related nodes consistently apply the new rules, and records the time W and the change content X of this change, i.e. W = current time, X = change details.

[0155] Every fixed period, the edge computing node aggregates all change records W and X and sends a summary report Y to the central management system, which contains all changes in the identity verification process and permission management policy.

[0156] Step eight: At the end of each construction phase, aggregate the data of the closed-loop management to generate a comprehensive report; specifically including:

[0157] At the end of the current construction phase, the edge computing node collects all change records W and X related to the current construction phase and generates a phase summary indicator Z for each job type, where Z = SUM(W) + COUNT(X), which quantifies the number and frequency of management changes in the phase; it is generated by summing the timestamps W of all change records and adding the number of change contents X. This method can quantify the number and frequency of management changes in the phase.

[0158] For example: suppose a job type has two change records in the current construction phase, with change times of March 17, 2025, 10:30 and March 18, 2025, 11:00, and change contents of "reducing unnecessary identity verification steps" and "adding SMS verification step", respectively. Then:

[0159] SUM(W) = 202503171030 + 202503181100 = 405006352130;

[0160] COUNT(X) = 2;

[0161] Z = 405006352130 + 2 = 405006352132;

[0162] The final generated phase summary indicator Z is 405006352132.

[0163] By generating the phase summary indicator Z, the system can quantify the number and frequency of management changes occurring within each construction phase, facilitating subsequent performance evaluation and optimization.

[0164] Using the phase summary indicator Z, combined with the work efficiency indicator R and safety compliance score S for each type of work, a comprehensive performance score AA is calculated, with the formula: AA = (R * 0.6 + S * 0.4) / Z. This measures the comprehensive performance of each type of work in the entire construction phase. It is generated by multiplying the work efficiency indicator R by 0.6, the safety compliance score S by 0.4, and then adding them together, and dividing by the phase summary indicator Z to generate a comprehensive performance score AA. This method can consider both work efficiency and safety compliance, while also considering the frequency of management changes.

[0165] For example: Suppose the work efficiency indicator R for a certain type of work is 3.75, the safety compliance score S is 80, and the phase summary indicator Z is 405006352132, then:

[0166] AA = (3.75 * 0.6 + 80 * 0.4) / 405006352132;

[0167] AA = (2.25 + 32) / 405006352132;

[0168] AA = 34.25 / 405006352132 ≈ 8.46e-10;

[0169] The final generated comprehensive performance score AA is approximately 8.46e-10 (usually, this value will be adjusted to a reasonable range according to actual conditions).

[0170] By calculating the comprehensive performance score AA, the system can comprehensively evaluate the comprehensive performance of each type of work in the entire construction phase, facilitating the discovery of potential problems and the implementation of corresponding improvement measures.

[0171] Based on the comprehensive performance score AA, the edge computing node generates a performance analysis BB for each trade, BB = trade name + comprehensive performance score AA + performance details + improvement suggestions; the edge computing node aggregates the performance analysis BB of all trades into a comprehensive report CC, which includes a timeline of key events in the entire construction phase, main optimization measures and their effect evaluation, generates a report summary code DD through the formula DD = MOD(SUM(BB), 1000), which is used for quick retrieval and verification of report content; the report summary code DD is generated by taking the sum of all performance analysis BB contents and taking modulo 1000. This method can simplify the report content and facilitate quick retrieval and verification of report information in a specific time period.

[0172] For example: assuming the sum of all trade performance analysis BB is a certain value (for example, 123456), then:

[0173] DD = MOD(123456, 1000) = 456; the final generated report summary code DD is 456.

[0174] By generating the report summary code DD, the system can quickly retrieve and verify the report content in a specific time period, improving the query efficiency and reliability of the system.

[0175] The comprehensive report CC is sent to the central management system together with the report summary code DD, and the central management system receives it and stores it in the central database, and performs global comparative analysis to identify the best practice cases and potential improvement areas;

[0176] The central management system sends the next step action guide EE to the relevant edge computing node according to the content of the comprehensive report CC, which contains specific optimization suggestions and expected targets for the next construction phase; the edge computing node receives the action guide EE and adjusts the identity verification process and permission management strategy of the next construction phase according to its content, forming a new closed-loop management cycle, and improving the overall level of intelligent construction site management.

[0177] On the other hand, the present application proposes a unified identity management and authentication system, as shown in Figure 2 includes:

[0178] An identity identifier allocation identification module is used to allocate a unique identity identifier to each worker and record it in the edge computing device, and when the worker enters the construction site, the identity identifier is used to perform first identification and login verification at the nearest edge computing node;

[0179] The permission level dynamic updating and synchronization module is configured to dynamically update the permission level of the worker based on the first identification result, synchronize information within the edge network, and adjust the access permission of the corresponding type of work to the resource in different construction stages according to the change of the permission level.

[0180] The operation behavior monitoring and analysis module is configured to monitor and record the operation behavior of the worker in real time through the adjustment of the access permission, analyze the work efficiency and safety compliance of each type of work by means of the record of the operation behavior, and feed back to the edge node.

[0181] The optimization and summary module is configured to optimize the identity verification process and permission management strategy of the next stage according to the feedback result, form a closed-loop management, aggregate the data of the closed-loop management at the end of each construction stage, and generate a comprehensive report.

[0182] In addition, each module described above is also used to implement other steps of the unified identity management and authentication method when executed, which will not be described one by one.

[0183] In summary, the present application realizes distributed identification of worker identity and real-time permission management through edge computing devices, reduces the dependence on the central server, and improves the response speed and reliability of the system. The method can dynamically adjust the permission level and resource access permission according to different construction stages and type of work requirements, ensuring the accuracy and efficiency of permission management.

[0184] At the same time, through the monitoring, analysis and feedback of the operation behavior, the identity verification process and permission management strategy are continuously optimized to form a complete closed-loop management mechanism, thereby significantly improving the efficiency and safety of intelligent construction site management. This innovation effectively solves the problems of real-time and flexibility in the prior art, and provides a safer and more efficient construction site management solution.

[0185] Finally, it should be noted that: the above only describes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent replacements to some technical features, as long as they are within the spirit and principles of the present application. Any modification, equivalent replacement, improvement, etc. made within the scope of the present application shall be included in the protection scope of the present application.

Claims

1. A unified identity management and authentication method, characterized in that, include: Each worker is assigned a unique identifier, which is recorded in an edge computing device. When a worker enters the construction site, the identifier is used to perform initial identification and login verification at the nearest edge computing node. Based on the results of the initial identification, the system dynamically updates the worker's permission level and synchronizes information within the edge network. According to the changes in the permission level, the system adjusts the access permissions of the corresponding job to resources at different construction stages. By adjusting the access permissions, worker operation behavior can be monitored and recorded in real time. With the help of the recorded operation behavior, the work efficiency and safety compliance of each job type can be analyzed regularly and fed back to the edge node. Based on the feedback results, optimize the identity verification process and access control strategy for the next stage to form a closed-loop management. At the end of each construction stage, summarize the data of the closed-loop management and generate a comprehensive report. Based on the initial identification result, the system dynamically updates the worker's permission level and synchronizes information within the edge network. This includes: after a successful comparison, the edge computing node reads the current permission level F associated with the identity identifier ID; based on the latest login time and location information E, the edge computing node assesses the current construction site environment and construction progress, and generates a dynamic adjustment factor G using the formula G=MOD(E,10^3) ​​to reflect changes in permission requirements under the current environment; using the dynamic adjustment factor G, combined with the current permission level F, a new permission level F' is calculated, F'=F+G-INT((F+G) / 10)*10; the edge computing node stores the updated permission level F' in its local database and broadcasts a packet containing the identity identifier ID and the new permission level F' to other nodes through the edge network; the edge computing node receiving the broadcast information verifies the validity of the identity identifier ID and updates the locally stored permission level to F'. The real-time monitoring and recording of worker operation behavior through the adjustment of access permissions includes: creating an operation behavior log file L for each worker with a new access permission set J' in the edge computing node; when a worker accesses a resource, the edge computing node checks the access permission set J' corresponding to its identity identifier ID; if the access request conforms to the provisions of the access permission set J', access is allowed, and the access time and resource identifier M are recorded in the operation behavior log file L, i.e., L = L + access time + M; based on the content of the operation behavior log file L, an operation behavior tracking code N is generated using the formula N = MOD(SUM(ASCII(L[i])), 100), where i is the log value. The position of characters in the file; at fixed time intervals, the edge computing nodes summarize the data in the operation behavior log file L and send the summary information O to the central management system. The summary information O includes the identity identifier ID, the latest operation time, the cumulative number of accesses P, where P=COUNT(L), and the operation behavior tracking code N; after receiving the summary information O, the central management system verifies the validity of the identity identifier ID and stores it in the central database. At the same time, the system evaluates whether the worker's operation behavior complies with safety regulations based on the cumulative number of accesses P and the operation behavior tracking code N; if abnormal operation behavior is found, the central management system immediately sends a warning notification to the relevant edge computing nodes.

2. The unified identity management and authentication method according to claim 1, characterized in that, Assigning a unique identifier to each worker and recording it in the edge computing device includes: Collect basic information about each worker, including name, position, and date of employment, and generate a preliminary file; Based on the preliminary file, a string A is formed by combining the first letter of the name in pinyin, the job code, and the date of employment. A = first letter of name in pinyin + job code + date of employment. Process the string A and calculate the sum of its character ASCII values ​​B, B=SUM(ASCII(A[i])), where i is the position of the character in the string; Using the value B and the current timestamp C, a unique identifier ID is generated using the formula ID=MOD(B+C,10^8) and stored in the nearest edge computing node.

3. The unified identity management and authentication method according to claim 2, characterized in that, When a worker enters the construction site, the identification identifier is used to perform initial identification and login verification at the nearest edge computing node, including: When a worker approaches the construction site entrance, the identification device he wears automatically sends a data packet containing the identification identifier ID to the nearest edge computing node; After receiving the information packet, the edge computing node extracts the identity identifier ID and generates the check code D using the formula D=MOD(ID,10^4); Based on the verification code D, the edge computing node queries the locally stored identity identifier database to find a matching item. After confirming that the verification code D is valid, the edge computing node compares the complete identity identifier ID with the record in the database. If a match is successful, the worker is allowed to enter, and the worker's latest login time and location information E is updated, where E = current time + site location code. The edge computing node sends a notification to the central management system containing the identity identifier ID and the latest login time and location information E.

4. The unified identity management and authentication method according to claim 3, characterized in that, The step of adjusting the access permissions of corresponding work types to resources at different construction stages based on the changes in the permission level includes: When the edge computing node receives the updated permission level F', it reads the job information H associated with the identity identifier ID and the current construction stage I. Based on the permission level F' and the job information H, it generates a resource access adjustment factor K using the formula K=MOD(F'+H,10) to determine the changes in accessible resources under the current permission level. Using the resource access adjustment factor K and the current construction stage I, calculate the new access permission set J', J'=J+K-INT((J+K) / 10)*10; The edge computing node stores the updated access permission set J' in its local database and sends a notification to the resource management system containing the identity identifier ID, job information H, and the new access permission set J' to update the resource access control list; After receiving the notification, the resource management system verifies the validity of the identity identifier ID and adjusts the worker's access permissions to specific resources according to the new access permission set J'. At the same time, it records the change, and all relevant edge computing nodes synchronously receive and apply the new access permission set J'.

5. The unified identity management and authentication method according to claim 4, characterized in that, The process involves periodically analyzing the work efficiency and safety compliance of each job type using the recorded operational behaviors, and feeding this data back to edge nodes, including: The central management system extracts each worker's operation behavior log L, cumulative access count P, and operation behavior tracking code N from the aggregated information O, and generates a preliminary work efficiency index R for each job type, where R = P / time period length; Using the records in the operation behavior log L, calculate the safety compliance score S for each job type, S=100-(SUM(number of abnormal operations)*10), where the number of abnormal operations is obtained by comparing the operation behavior log L with the predefined safety specifications; Based on the work efficiency index R and the safety compliance score S, the central management system generates a comprehensive evaluation report T for each job type. The report includes the identity identifier ID, work efficiency index R, safety compliance score S, and improvement suggestions. The formula is: T = ID + R + S + Improvement Suggestions. At fixed intervals, the central management system sends the comprehensive evaluation report T to the relevant edge computing nodes. After receiving the comprehensive evaluation report T, the edge nodes update the work efficiency and safety compliance records of the relevant job types stored locally. Based on the improvement recommendations in the comprehensive evaluation report T, the edge computing node adjusts the permission level F' and access permission set J' for the corresponding job, including: if the security compliance score S is lower than the threshold, reducing the access permissions for high-risk resources in the access permission set J'; if the work efficiency index R is higher than the set standard, relaxing the access permission set J'. The edge computing node will then rebroadcast the adjusted permission level F' and access permission set J' to the entire edge network.

6. The unified identity management and authentication method according to claim 5, characterized in that, The process of optimizing the identity verification process and access control strategy for the next stage based on feedback results, forming a closed-loop management system, includes: The edge computing node receives a comprehensive evaluation report T from the central management system and extracts the work efficiency index R and security compliance score S for each job type. It generates an optimization weight U for each job type, where U = R + S / 100, which is used to adjust the authentication process and permission management strategy in the future. Using the optimized weight U, the edge computing node re-evaluates the effectiveness of the current authentication process and generates a new verification factor V using the formula V=MOD(U,10). V determines whether additional authentication steps need to be added or the existing process needs to be simplified. Based on the verification factor V, the authentication process in the next stage is adjusted. If V is greater than 5, an additional identity verification step is added during the authentication process. If V is less than or equal to 5, the existing process is simplified and unnecessary verification steps are reduced. Based on the improvement suggestions in the comprehensive evaluation report T and combined with the optimization weight U, the edge computing node update permission management strategy includes: for jobs with a security compliance score S below the threshold, reducing access permissions to high-risk resources in their access permission set J'; for jobs with a work efficiency index R above the set standard, relaxing access permission set J. The edge computing node synchronizes the updated authentication process and permission management policy to the entire edge network, ensuring that all relevant nodes apply the new rules consistently. At the same time, it records the time W and the content of the change X, i.e., W = current time, X = change details; Every fixed period, the edge computing nodes summarize all change records W and X and send a summary report Y to the central management system. The summary report Y contains changes to all authentication processes and access control policies.

7. The unified identity management and authentication method according to claim 6, characterized in that, At the end of each construction phase, the data from the closed-loop management are summarized to generate a comprehensive report, including: At the end of the current construction phase, the edge computing node collects all change records W and X related to the current construction phase and generates a phase summary index Z for each type of work, where Z = SUM(W) + COUNT(X), which is used to quantify the number and frequency of management changes that occurred during the phase. Using the aforementioned stage summary index Z, combined with the work efficiency index R and safety compliance score S for each type of work, a comprehensive performance score AA is calculated. The formula is: AA=(R*0.6+S*0.4) / Z, to measure the comprehensive performance of each type of work throughout the entire construction stage. Based on the overall performance score AA, the edge computing node generates a performance analysis BB for each job type, where BB = job type name + overall performance score AA + performance details + improvement suggestions; Edge computing nodes summarize the performance analysis of all tasks (BB) into a comprehensive report (CC). The report includes a timeline of key events throughout the construction phase, main optimization measures and their effect evaluation. A report digest code (DD) is generated using the formula DD=MOD(SUM(BB),1000) for quick retrieval and verification of the report content. The comprehensive report CC, along with the report digest code DD, is sent to the central management system. After receiving it, the central management system stores it in the central database and performs a global comparative analysis to identify best practice cases and potential areas for improvement. Based on the contents of the comprehensive report CC, the central management system sends the next action guide EE to the relevant edge computing nodes. The guide includes specific optimization suggestions and expected goals for the next construction phase. The edge computing node receives the Action Guide (EE) and adjusts the authentication process and access control strategy for the next construction phase based on its content, forming a new closed-loop management cycle.

8. A unified identity management and authentication system for implementing the method as described in any one of claims 1-7, characterized in that, include: The identity identifier allocation and recognition module is used to assign a unique identity identifier to each worker and record it in the edge computing device. When a worker enters the construction site, the identity identifier is used to perform initial identification and login verification at the nearest edge computing node. The permission level dynamic update and synchronization module is used to dynamically update the worker's permission level based on the initial identification result, and simultaneously synchronize information within the edge network. According to the change in the permission level, the system adjusts the access permissions of the corresponding job to resources at different construction stages. The operation behavior monitoring and analysis module is used to monitor and record worker operation behavior in real time by adjusting the access permissions. With the help of the recorded operation behavior, the work efficiency and safety compliance of each job are analyzed periodically and fed back to the edge node. The optimization and summary module is used to optimize the identity verification process and access control strategy for the next stage based on the feedback results, forming a closed-loop management. At the end of each construction stage, the data of the closed-loop management is summarized to generate a comprehensive report.

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