Unified identity management and authentication method and system

Abstract

The invention belongs to the technical field of intelligent construction sites, and particularly relates to a unified identity management and authentication method and system, which realize distributed identification and real-time authority management of worker identities through edge computing equipment, reduce dependence on a central server and improve response speed and reliability of the system. According to the method, the authority level and the resource access authority can be dynamically adjusted according to different construction stages and work type requirements, and the accuracy and the high efficiency of authority management are ensured. Meanwhile, through monitoring, analysis and feedback of operation behaviors, an identity verification process and an authority management strategy are continuously optimized, and a complete closed-loop management mechanism is formed, so that the efficiency and safety of intelligent construction site management are remarkably improved. The innovation effectively solves the problem of insufficient real-time performance and flexibility in the prior art, and provides a safer and more efficient construction site management solution.

Description

Technical Field

[0001] The present invention belongs to the technical field of smart construction sites, and in particular relates to a unified identity management and authentication method and system. Background Art

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

[0003] Bottlenecks of centralized management: Since all authentication and permission management tasks are centralized on the central server, large construction sites or large numbers of workers can easily lead to excessive system load, slow response times, and even the risk of single point failures.

[0004] Insufficient real-time performance and flexibility: Traditional methods make it difficult to achieve efficient adjustment of dynamic access control between different types of work at different construction stages. Especially when edge devices are widely distributed, it becomes difficult to update permission levels and access control in real time.

[0005] Security and efficiency issues: In large-scale construction sites, frequent authentication and permission adjustments can increase network latency and impact work efficiency. Furthermore, if the security of a single central server is compromised, the security of the entire system will be seriously threatened.

[0006] In summary, existing centralized identity management and authentication methods, without relying on a central server, struggle to achieve distributed identification and real-time permissions management for workers on smart construction sites. This is particularly problematic for dynamic access control across different types of workers during different construction phases. This not only impacts site management efficiency but also poses potential safety risks. Summary of the Invention

[0007] The purpose of the present invention is to provide a unified identity management and authentication method and system. By introducing edge computing devices and a dynamic permission management mechanism, it effectively solves the problems of insufficient real-time and flexibility in the existing technology and improves the efficiency and security of smart construction site management.

[0008] To achieve the above objectives, the present invention provides a unified identity management and authentication method, including: Each worker is assigned a unique identity identifier and recorded in the edge computing device. When a worker enters the construction site, the identity identifier is used for 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. Based on the changes in the permission level, the system adjusts the corresponding worker's access rights to resources at different construction stages. By adjusting the access rights, workers' operating behaviors are monitored and recorded in real time. With the help of the records of the operating behaviors, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge node; Based on the feedback results, the identity authentication process and permission management strategy for the next stage are optimized to form 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.

[0009] Preferably, the step of assigning a unique identity identifier to each worker and recording it in the edge computing device includes: Collect basic information of each worker, including name, position and employment date, and generate a preliminary file; Based on the preliminary file, a character string A is formed by combining the first letter of the name in Pinyin, the position code and the date of employment, where A = the first letter of the name in Pinyin + the position code + the date of employment; Process the string A and 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; Use the B value combined with the current timestamp C to generate a unique identifier ID through the formula ID=MOD(B+C,10^8) and store it in the nearest edge computing node.

[0010] Preferably, 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, including: When a worker approaches the construction site entrance, the identification device he wears automatically sends an information packet containing the identity 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 through the formula D=MOD(ID,10^4); Based on the verification code D, the edge computing node queries the locally stored identity identifier database for a match. 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 the 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 + 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.

[0011] Preferably, based on the result of the first identification, the system dynamically updates the worker's authority level and synchronizes information within the edge network, including: After the comparison is successful, 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 evaluates 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 in the current environment. Using the dynamic adjustment factor G and the current permission level F, calculate the new permission level F', F'=F+G-INT((F+G) / 10)*10; The edge computing node stores the updated permission level F' in the local database and broadcasts an information packet containing the identity identifier ID and the new permission level F' to other nodes through the edge network. The edge computing node that receives the broadcast information verifies the validity of the identity identifier ID and updates the locally stored permission level to F'.

[0012] Preferably, adjusting the access rights of corresponding types of work to resources at different construction stages according to the change of the authority level includes: When the edge computing node receives the updated permission level F', it reads the work type information H associated with the identity identifier ID and the current construction stage I. Based on the permission level F' and the work type information H, it generates a resource access adjustment factor K using the formula K=MOD(F'+H,10) to determine the change 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 the local database and sends a notification containing the identity identifier ID, job type information H and the new access permission set J' to the resource management system 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 rights to specific resources based on the new access permission set J'. It also records the change and all relevant edge computing nodes synchronously receive and apply the new access permission set J'.

[0013] Preferably, the real-time monitoring and recording of workers' operating behaviors through adjustment of the access rights includes: In the edge computing node, an operation behavior log file L is created for each worker with the new access permission set J'; When a worker accesses a resource, the edge computing node checks the access permission set J' corresponding to the worker's identity identifier ID. If the access request meets the requirements of the access permission set J', the worker is allowed to access the resource and records the access time and resource identifier M 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 position of the character in the log file; At regular intervals, the edge computing node aggregates the data in the operation behavior log file L and sends the aggregate information O to the central management system. The aggregate information O includes the identity identifier ID, the latest operation time, the cumulative number of visits 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 operating behavior complies with safety regulations based on the cumulative number of visits P and the operation behavior tracking code N; If any abnormal operation behavior is detected, the central management system will immediately send a warning notification to the relevant edge computing node.

[0014] Preferably, the operation behavior records are used to regularly analyze the work efficiency and safety compliance of each type of work and provide feedback to the edge node, including: The central management system extracts each worker's operation behavior log L, cumulative access times P, and operation behavior tracking code N during the working period from the summary 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 type of work, S = 100 - (SUM (number of abnormal operations) * 10), where the number of abnormal operations is obtained by comparing the operation behavior log L with predefined safety regulations; 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 type of work. The report includes the identity identifier ID, the work efficiency index R, the safety compliance score S, and improvement suggestions. The formula is: T = ID + R + S + improvement suggestions; At regular intervals, the central management system sends the comprehensive assessment report T to the relevant edge computing nodes. After receiving the comprehensive assessment report T, the edge nodes update the work efficiency and safety compliance records of the relevant work types stored locally. The edge computing node adjusts the permission level F' and access permission set J' of the corresponding job type based on the improvement suggestions in the comprehensive assessment report T, including: if the security compliance score S is lower than the threshold, reducing the access permissions of 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 broadcasts the adjusted permission level F' and access permission set J' to the entire edge network again.

[0015] Preferably, the optimization of the identity authentication process and authority management strategy for the next stage based on the feedback results to form a closed-loop management includes: The edge computing node receives the comprehensive assessment report T from the central management system and extracts the work efficiency index R and security compliance score S for each job type. It then generates an optimization weight U for each job type, where U = R + S / 100. This weight is then used to adjust the authentication process and permission management policy. 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 for the next stage is adjusted. If V is greater than 5, an additional identity confirmation step is added to the authentication process. If V is less than or equal to 5, the existing process is simplified to reduce unnecessary verification steps. Based on the improvement suggestions in the comprehensive assessment report T and the optimization weight U, the edge computing node updates the permission management policy, including: for jobs with a security compliance score S below a threshold, reducing the high-risk resource access rights in their access permission set J'; and for jobs with a work efficiency index R above a set standard, relaxing the access permission set J. The edge computing node synchronizes the updated authentication process and permission management policy to the entire edge network to ensure that all relevant nodes consistently apply the new rules. At the same time, it records the time W and the content X of the change, where W = current time and X = change details. At regular intervals, the edge computing node summarizes all change records W and X and sends a summary report Y to the central management system. The summary report Y includes changes in all authentication processes and permission management policies.

[0016] Preferably, at the end of each construction phase, the closed-loop management data is 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 indicator 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 stage summary indicator Z, combined with each type of work's work efficiency indicator R and safety compliance score S, an overall performance score AA is calculated using the formula: AA = (R*0.6+S*0.4) / Z, to measure the overall performance of each type of work throughout the construction phase. Based on the comprehensive performance score AA, the edge computing node generates a performance analysis BB for each job type, where BB = job type name + comprehensive performance score AA + performance details + improvement suggestions; The edge computing node aggregates the performance analysis (BB) of all work types into a comprehensive report (CC). The report includes a timeline of key events throughout the construction phase, key optimization measures, and their effectiveness evaluation. A report summary code (DD) is generated using the formula DD=MOD(SUM(BB),1000) for quick retrieval and verification of report content. The comprehensive report CC together with the report summary code DD is sent to the central management system. After receiving it, the central management system stores it in the central database and conducts a global comparative analysis to identify best practice cases and potential areas for improvement; Based on the content of the comprehensive report CC, the central management system sends the next action guide EE to the relevant edge computing nodes. The guide contains 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 permission management strategy for the next construction phase according to its content, forming a new closed-loop management cycle.

[0017] In another aspect, the present invention provides a unified identity management and authentication system, comprising: An identity identifier allocation and identification 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 for initial identification and login verification at the nearest edge computing node; A permission level dynamic update and synchronization module is used to dynamically update the worker's permission level based on the results of the initial identification, synchronize information within the edge network, and adjust the corresponding worker's access rights to resources at different construction stages according to the changes in the permission level; An operation behavior monitoring and analysis module is used to monitor and record workers' operation behaviors in real time by adjusting the access rights. With the help of the operation behavior records, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge node; The optimization and summary module is used to optimize the identity authentication process and permission management strategy of 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.

[0018] Technical effects and advantages of the present invention: Compared with the existing technology, the unified identity management and authentication method and system proposed by the present invention has the following advantages: The present invention uses edge computing devices to achieve distributed identification of worker identities and real-time rights management, reducing dependence on central servers and improving the system's response speed and reliability. This method can dynamically adjust permission levels and resource access rights according to different construction phases and work requirements, ensuring the accuracy and efficiency of rights management. At the same time, through monitoring, analysis, and feedback on operational behaviors, the identity authentication process and rights management strategy are continuously optimized to form a complete closed-loop management mechanism, thereby significantly improving the efficiency and security of smart construction site management. This innovation effectively solves the problems of insufficient real-time performance and flexibility in existing technologies, and provides a safer and more efficient construction site management solution. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a flow chart of the unified identity management and authentication method of the present invention; Figure 2 A block diagram of the unified identity management and authentication system of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. The specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0021] The present invention provides Figure 1 The unified identity management and authentication method shown here uses edge computing devices to achieve distributed identification of worker identities and real-time permission management, reducing dependence on central servers and improving system response speed and reliability. The unified identity management and authentication method in this embodiment includes: Step 1: Assign a unique identifier to each worker and record it in the edge computing device; specifically: Collect basic information of each worker, including name, position and employment date, to generate a preliminary file; this information is the basic data source for generating a unique identity identifier, ensuring that each worker has clear identity information in the system.

[0022] Based on the preliminary profile, the worker's first name, position code, and start date are combined to form a string A: A = first name + position code + start date. This combination of the first name, position code, and start date makes each worker's identifier highly unique and readable. For example, if Zhang San is an electrician (position code 01) and started on January 1, 2023 (20230101), the string A is "ZS0120230101."

[0023] Process the string A and calculate the sum B of its character ASCII values, 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 identifier, increasing the uniqueness of the identifier. For example, for the string A "ZS0120230101": The ASCII value of Z is 90; The ASCII value of S is 83; The ASCII value of 0 is 48; The ASCII value of 1 is 49; The ASCII value of 2 is 50; The ASCII value of 3 is 51. B=90+83+48+49+50+51+48+49+48+49+50+51+48+49+48+49=768.

[0024] The unique identifier (ID) is generated using the formula ID=MOD(B+C,10^8) using the value B and the current timestamp C. This identifier is then stored in the nearest edge computing node. ID=MOD(B+C,10^8) generates the unique identifier by adding the sum of the ASCII values ​​(B) to the current timestamp (C) and then taking the modulo 10^8. This method ensures that even if two workers have the same initials, position code, and start date, the resulting identifiers will still be different due to the different timestamps.

[0025] For example, assuming the current timestamp C is 1673952360 (in seconds), then: B=768 (calculated from the previous step); C=1673952360; ID=MOD(768+1673952360,10^8)=MOD(1673953128,100000000)=3953128; The final unique identifier ID generated is 3953128.

[0026] By combining the sum of the ASCII character values ​​(B) and the current timestamp (C), a highly unique identifier (ID) is generated. This approach not only ensures that each worker's identifier is unique but also enables efficient storage and retrieval of these identifiers within edge computing nodes, improving system reliability and efficiency. Furthermore, the use of timestamps ensures unique identifiers even when multiple workers register at the same time.

[0027] Step 2: When a worker enters the construction site, the worker uses the identity identifier to perform initial identification and login verification at the nearest edge computing node. This includes: When a worker approaches the construction site entrance, the identification device he wears (such as a smart card or mobile device) automatically sends an information packet containing the identity identifier ID to the nearest edge computing node; After receiving the information packet, the edge computing node extracts the identity identifier (ID) and generates a check code (D) using the formula D=MOD(ID,10^4). D=MOD(ID,10^4) generates a four-digit check code (D) by taking the ID modulo 10^4. This method can quickly generate a short check code for preliminary verification of the identity identifier's validity.

[0028] For example, if the ID is 3953128, then D = MOD(3953128, 10000) = 3128; the resulting check code D is 3128. Generating the check code D allows for quick verification of the ID's validity at the initial stage, reducing unnecessary database queries and improving system response speed.

[0029] Based on the verification code D, the edge computing node queries the locally stored identity identifier database for a match. After confirming that the verification code D is valid, the edge computing node compares the full identity identifier ID with the records in the database. This method ensures that only legitimate workers can enter the construction site and improves the accuracy of identity authentication through dual verification (verification code and full identity identifier).

[0030] If a match is successful, the worker is allowed in and their latest login time and location information, E, is updated, where 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. The central management system can use this information for further analysis and decision-making, such as generating comprehensive reports and optimizing permission management policies. This ensures data consistency and reliability across all edge computing nodes.

[0031] Step 3: Based on the results of the initial identification, the system dynamically updates the worker's permission level and synchronizes the information within the edge network. This includes: 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 and avoids errors or inconsistencies.

[0032] Based on the latest login time and location information E, the edge computing node assesses the current construction site environment and progress. It generates a dynamic adjustment factor G using the formula G=MOD(E,10^3) ​​to reflect changes in permission requirements under the current environment. G=MOD(E,10^3) ​​generates a three-digit dynamic adjustment factor G by taking the modulo 10^3 of the latest login time and location information E. This method simplifies complex login time and location information into a smaller value, enabling quick adjustment of permission levels.

[0033] 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: G=MOD(202503171010001,1000)=1, and the final generated dynamic adjustment factor G is 1.

[0034] By generating a dynamic adjustment factor G, the system can flexibly adjust worker permissions based on the latest site conditions and construction progress. This dynamic adjustment mechanism makes permission management more adaptable to actual work needs, improving the system's flexibility and responsiveness.

[0035] The dynamic adjustment factor G is used in conjunction with the current permission level F to calculate the new permission level F': F' = F + G - INT((F + G) / 10) * 10. This is achieved by adding the current permission level F to the dynamic adjustment factor G, subtracting the integer portion after dividing by 10, and multiplying the result by 10. This ensures that the new permission level F' remains within a reasonable range (e.g., 0 to 9). This method ensures that permission level adjustments do not exceed the preset range while maintaining a certain degree of flexibility.

[0036] For example, assuming the current permission level F is 5 and the dynamic adjustment factor G is 1, then: F'=5+1-INT((5+1) / 10)*10=6-INT(6 / 10)*10=6-0*10=6. The final generated new permission level F' is 6.

[0037] By calculating the new permission level F', the system can make appropriate adjustments based on existing permissions, ensuring that permission levels always meet the needs of the current site environment and construction schedule. This adjustment mechanism not only increases the flexibility of permission management but also enhances the security and efficiency of the system.

[0038] The edge computing node stores the updated permission level F' in the local database and broadcasts an information packet containing the identity identifier ID and the new permission level F' to other nodes through the edge network. The edge computing node that receives the broadcast information verifies the validity of the identity identifier ID and updates the locally stored permission level to F'.

[0039] Step 4: Adjust the access rights of the corresponding types of work to resources at different construction stages according to the changes in the permission levels; specifically, When the edge computing node receives the updated permission level F', it reads the work type information H associated with the identity identifier ID and the current construction stage I. Based on the permission level F' and the work type information H, it generates a resource access adjustment factor K using the formula K=MOD(F'+H,10) to determine the change in accessible resources under the current permission level. K=MOD(F'+H,10) generates a resource access adjustment factor, K, by adding the permission level F' and the job type information H, modulo 10. This method simplifies complex permission level and job type information into a smaller value, allowing for quick adjustment of resource access rights.

[0040] For example, assuming the updated permission level F' is 6 and the job type information H is 3 (e.g. electrician), then: K=MOD(6+3,10)=MOD(9,10)=9; The final resource access adjustment factor K is 9.

[0041] By generating a resource access adjustment factor, K, the system can flexibly adjust resource access permissions based on the current permission level and job type information. This dynamic adjustment mechanism makes resource access control more adaptable to actual work needs, improving the system's flexibility and responsiveness.

[0042] Using the resource access adjustment factor K and the current construction phase I, a new access permission set J' is calculated: J' = J + K - INT((J + K) / 10) * 10. This is done by adding the current access permission set J to the resource access adjustment factor K, subtracting the integer portion after dividing by 10, and multiplying the result by 10. This ensures that the new access permission set J' remains within a reasonable range (e.g., 0 to 9). This method ensures that access permission set adjustments do not exceed the preset range while maintaining a certain degree of flexibility.

[0043] For example, assuming the current access permission set J is 4 and the resource access adjustment factor K is 9, then: J'=4+9-INT((4+9) / 10)*10=13-INT(13 / 10)*10=13-1*10=13-10=3; The new access permission set J' finally generated is 3.

[0044] By calculating the new access permission set J', the system can make appropriate adjustments based on the existing access permissions to ensure that resource access permissions always meet the requirements of the current permission level, work type information and construction stage.

[0045] 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 type information H and the new access permission set J' to the resource management system to update the resource access control list; Upon receiving the notification, the resource management system verifies the validity of the ID and adjusts the worker's access rights to specific resources based on the new access rights set J'. It also records this change and all relevant edge computing nodes simultaneously receive and apply the new access rights set J', ensuring consistent resource access rights across all nodes. This step further enhances the security and reliability of the system, preventing unauthorized access and manipulation.

[0046] Step 5: By adjusting the access rights, workers' operating behaviors are monitored and recorded in real time; specifically, the following steps are included: 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 their identity identifier ID. If the access request meets the requirements 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, that is, L = L + access time + M. This mechanism ensures the security and compliance of resource access while providing detailed access records. For example: Worker Zhang San (ID=3953128) accesses resource R1 at 10:20 on March 17, 2025. The resource identifier M is "R1".

[0047] The operation behavior log file L is updated to: "202503171020R1".

[0048] Based on the contents 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 summing the ASCII values ​​of each character in the operation behavior log file L and then taking the sum modulo 100. This method can simplify complex operation behavior logs into a smaller value, which can be used to quickly retrieve and verify operation records within a specific time period.

[0049] For example, assuming the operation behavior log file L is "202503171020R1", then: The ASCII values ​​are: 50, 48, 50, 53, 48, 51, 49, 55, 49, 48, 50, 48, 82, 49; SUM(ASCII(L[i]))=50+48+50+53+48+51+49+55+49+48+50+48+82+49=683 N=MOD(683,100)=83; The final generated operation behavior tracking code N is 83.

[0050] By generating an operation tracking code N, the system can quickly retrieve and verify operation records within a specific time period based on the operation log. This mechanism improves the system's response speed and query efficiency, facilitating subsequent audits and analysis.

[0051] At regular intervals, the edge computing node aggregates the data in the operation behavior log file L and sends summary information O to the central management system. Summary information O includes the identity identifier ID, the latest operation time, the cumulative number of visits P, where P = COUNT(L), and the operation behavior tracking code N. For example, if the identity identifier ID is 3953128, the latest operation time is 10:20 on March 17, 2025, the cumulative number of visits P is 14, and the operation behavior tracking code N is 83, the summary information O is: "3953128,202503171020,14,83".

[0052] 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. Simultaneously, the system assesses whether the worker's operating behavior complies with safety regulations based on the cumulative number of visits P and the operation tracking code N. If any abnormal operation behavior is detected, the central management system immediately sends a warning notification to the relevant edge computing node. This mechanism can promptly detect and address potential safety hazards, enhancing system security.

[0053] Step 6: Using the records of the aforementioned operational behaviors, regularly analyze the work efficiency and safety compliance of each type of work and provide feedback to the edge node. This includes: The central management system extracts each worker's operational behavior log L, cumulative access count P, and operational behavior tracking code N from the summary information O during the work period. It then generates a preliminary work efficiency index R for each job type, where R = P / time period length. This index is calculated by dividing the cumulative access count P by the time period length (e.g., hours). This method quantifies the work efficiency of each job type within a specific time period.

[0054] For example, assuming that the cumulative number of visits P for a certain type of work within an 8-hour working period is 40, then R = 40 / 8 = 5, and the final work efficiency index R is 5.

[0055] Using the records in the operational behavior log L, a safety compliance score S is calculated for each job type: S = 100 - (SUM (number of abnormal operations) * 10). The number of abnormal operations is determined by comparing the operational behavior log L with predefined safety regulations. The safety compliance score S is calculated by summing the number of abnormal operations, multiplying by 10, and subtracting this value from 100. This method can quantify the safety compliance level of each job type.

[0056] For example, if a certain type of work has three abnormal operations within a period of time, then: SUM(number of abnormal operations) = 3; S=100-(3*10)=100-30=70; The final security compliance score S is 70.

[0057] By calculating the safety compliance score S, the system can quantify the safety compliance level of each type of work, making it easier to identify potential safety hazards and take corresponding improvement measures.

[0058] 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 type of work. The report includes the identity identifier ID, the work efficiency index R, the safety compliance score S, and improvement suggestions. The formula is: T = ID + R + S + improvement suggestions; At regular intervals, the central management system sends the comprehensive assessment report T to the relevant edge computing nodes. After receiving the comprehensive assessment report T, the edge nodes update the work efficiency and safety compliance records of the relevant work types stored locally. Based on the improvement recommendations in the comprehensive assessment report T, the edge computing node adjusts the permission level F' and access permission set J' for the corresponding job type. This includes: if the security compliance score S is below a threshold, access permissions to high-risk resources in access permission set J' are reduced; if the work efficiency index R is above a set standard, access permission set J' is relaxed. The edge computing node then broadcasts the adjusted permission level F' and access permission set J' to the entire edge network. This distributed synchronization mechanism improves system reliability and consistency, avoiding security risks caused by asynchronous permission information.

[0059] Step 7: Based on the feedback, optimize the authentication process and permission management strategy for the next phase to form a closed-loop management system. This includes: The edge computing node receives the comprehensive assessment report T from the central management system, extracts the work efficiency index R and security compliance score S for each job type, and generates an optimized weight U for each job type, where U=R+S / 100, which is used for subsequent adjustments to the authentication process and permission management strategy. This method can comprehensively consider work efficiency and security compliance to generate a weight value for subsequent adjustments.

[0060] For example, assuming the work efficiency index R of a certain type of work 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.

[0061] Using the optimized weight U, the edge computing node reassesses 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 are needed or the existing process is simplified. Based on this verification factor V, the authentication process for the next stage is adjusted. V=MOD(U,10) generates a verification factor V by taking the optimized weight U modulo 10. This method simplifies complex optimization weights into a smaller value, allowing for quicker determination of whether authentication processes need adjustment.

[0062] For example: Assuming the optimization weight U is 4.55, then: V=MOD(4.55,10)=4.55; The final verification factor V is 4.55 (rounded to 4). If V is greater than 5, an additional identity confirmation step is added to the identity verification 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 assessment report T and the optimization weight U, the edge computing node updates the permission management policy, including: for jobs with a security compliance score S below a threshold, reducing the high-risk resource access rights in their access permission set J'; and for jobs with a work efficiency index R above a set standard, relaxing the access permission set J. The edge computing node synchronizes the updated authentication process and permission management policy to the entire edge network to ensure that all relevant nodes consistently apply the new rules. At the same time, it records the time W and the content X of the change, where W = current time and X = change details. At regular intervals, the edge computing node summarizes all change records W and X and sends a summary report Y to the central management system. The summary report Y includes changes in all authentication processes and permission management policies.

[0063] Step 8: At the end of each construction phase, summarize the closed-loop management data and generate a comprehensive report; specifically including: At the end of the current construction phase, the edge computing node collects all change records W and X related to the current phase and generates a phase summary indicator Z for each type of work, where Z = SUM(W) + COUNT(X). This indicator is used to quantify the number and frequency of management changes that occurred during the phase. Z is generated by summing the timestamps W of all change records and adding the number of changes X. This method can quantify the number and frequency of management changes that occurred during the phase.

[0064] For example, suppose a certain type of work has two change records in the current construction phase, with the change times being 10:30 on March 17, 2025 and 11:00 on March 18, 2025, respectively. The change contents are "reducing unnecessary identity verification steps" and "adding SMS verification code steps." Then: SUM(W)=202503171030+202503181100=405006352130; COUNT(X)=2; Z=405006352130+2=405006352132; The final stage summary indicator Z is 405006352132.

[0065] By generating the stage summary indicator Z, the system can quantify the number and frequency of management changes occurring within each construction stage, facilitating subsequent performance evaluation and optimization.

[0066] Using the stage summary indicator Z, combined with each type of work's work efficiency indicator R and safety compliance score S, an overall performance score AA is calculated using the formula: AA = (R*0.6+S*0.4) / Z. This measures the overall performance of each type of work throughout the construction phase. The overall score AA is generated by multiplying the work efficiency indicator R by 0.6 and the safety compliance score S by 0.4, adding them together, and dividing the result by the stage summary indicator Z. This approach comprehensively considers work efficiency and safety compliance, while also accounting for the frequency of management changes.

[0067] For example, if the work efficiency index R of a certain type of work is 3.75, the safety compliance score S is 80, and the stage summary index Z is 405006352132, then: AA=(3.75*0.6+80*0.4) / 405006352132; AA=(2.25+32) / 405006352132; AA=34.25 / 405006352132≈8.46e-10; The final comprehensive performance score AA is approximately 8.46e-10 (usually, this value will be adjusted to a reasonable range based on actual conditions).

[0068] By calculating the comprehensive performance score AA, the system can comprehensively evaluate the overall performance of each type of work throughout the entire construction phase, making it easier to identify potential problems and take corresponding improvement measures.

[0069] Based on the comprehensive performance score AA, the edge computing node generates a performance analysis BB for each work type. BB = work type name + comprehensive performance score AA + performance details + improvement suggestions. The edge computing node then compiles the performance analysis BB for all work types into a comprehensive report CC. This report includes a timeline of key events throughout the construction phase, key optimization measures, and their effectiveness evaluation. A report summary code DD is generated using the formula DD = MOD(SUM(BB), 1000) for quick retrieval and verification of report content. This code is generated by summing the contents of all performance analysis BBs and taking the sum modulo 1000. This method simplifies report content and facilitates quick retrieval and verification of report information within a specific time period.

[0070] For example, if the sum of the performance analysis BBs for all jobs is a certain value (e.g. 123456), then: DD=MOD(123456,1000)=456; the final report summary code DD is 456.

[0071] By generating a report summary code DD, the system can quickly retrieve and verify the report content within a specific time period, improving the query efficiency and reliability of the system.

[0072] The comprehensive report CC together with the report summary code DD is sent to the central management system. After receiving it, the central management system stores it in the central database and conducts a global comparative analysis to identify best practice cases and potential areas for improvement;

[0073] 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 contains specific optimization suggestions and expected goals for the next construction phase. The edge computing nodes receive the action guide EE and adjust the authentication process and permission management strategy for the next construction phase based on its content, forming a new closed-loop management cycle and improving the overall level of smart construction site management.

[0074] On the other hand, the present invention proposes a unified identity management and authentication system, such as Figure 2 As shown, including: An identity identifier allocation and identification 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 for initial identification and login verification at the nearest edge computing node; A permission level dynamic update and synchronization module is used to dynamically update the worker's permission level based on the results of the initial identification, synchronize information within the edge network, and adjust the corresponding worker's access rights to resources at different construction stages according to the changes in the permission level; An operation behavior monitoring and analysis module is used to monitor and record workers' operation behaviors in real time by adjusting the access rights. With the help of the operation behavior records, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge node; The optimization and summary module is used to optimize the identity authentication process and permission management strategy of 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.

[0075] In addition, when executed, each of the above modules is also used to implement other steps of the above unified identity management and authentication method, which will not be described in detail here.

[0076] In summary, this invention uses edge computing devices to achieve distributed identification of worker identities and real-time permissions management, reducing reliance on central servers and improving system responsiveness and reliability. This method can dynamically adjust permission levels and resource access rights based on different construction phases and work types, ensuring accurate and efficient permission management.

[0077] At the same time, through monitoring, analysis, and feedback on operational behavior, authentication processes and permission management strategies are continuously optimized, forming a complete closed-loop management mechanism, significantly improving the efficiency and security of smart construction site management. This innovation effectively addresses the real-time and flexibility limitations of existing technologies, providing a safer and more efficient construction site management solution.

[0078] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or make equivalent substitutions for some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A unified identity management and authentication method, characterized in that: include: Each worker is assigned a unique identity identifier and recorded in the edge computing device. When a worker enters the construction site, the identity identifier is used for 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. Based on the changes in the permission level, the system adjusts the corresponding worker's access rights to resources at different construction stages. By adjusting the access rights, workers' operating behaviors are monitored and recorded in real time. With the help of the records of the operating behaviors, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge node; Based on the feedback results, the identity authentication process and permission management strategy for the next stage are optimized to form 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.

2. A unified identity management and authentication method according to claim 1, characterized in that: Each worker is assigned a unique identity identifier and recorded in the edge computing device, including: Collect basic information of each worker, including name, position and employment date, and generate a preliminary file; Based on the preliminary file, a character string A is formed by combining the first letter of the name in Pinyin, the position code and the date of employment, where A = the first letter of the name in Pinyin + the position code + the date of employment; Process the string A and 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; Use the B value combined with the current timestamp C to generate a unique identifier ID through the formula ID=MOD(B+C,10^8) and store it in the nearest edge computing node.

3. A unified identity management and authentication method according to claim 2, characterized in that: 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, including: When a worker approaches the construction site entrance, the identification device he wears automatically sends an information packet containing the identity 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 through the formula D=MOD(ID,10^4); Based on the verification code D, the edge computing node queries the locally stored identity identifier database for a match. 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 the 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 + 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.

4. A unified identity management and authentication method according to claim 3, characterized in that: Based on the result of the initial identification, the system dynamically updates the worker's authority level and synchronizes information within the edge network, including: After the comparison is successful, 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 evaluates 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 in the current environment. Using the dynamic adjustment factor G and the current permission level F, calculate the new permission level F', F'=F+G-INT((F+G) / 10)*10; The edge computing node stores the updated permission level F' in the local database and broadcasts an information packet containing the identity identifier ID and the new permission level F' to other nodes through the edge network. The edge computing node that receives the broadcast information verifies the validity of the identity identifier ID and updates the locally stored permission level to F'.

5. A unified identity management and authentication method according to claim 4, characterized in that: Adjusting the access rights of corresponding types of work to resources at different construction stages according to the change in the authority level includes: When the edge computing node receives the updated permission level F', it reads the work type information H associated with the identity identifier ID and the current construction stage I. Based on the permission level F' and the work type information H, it generates a resource access adjustment factor K using the formula K=MOD(F'+H,10) to determine the change 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 the local database and sends a notification containing the identity identifier ID, job type information H and the new access permission set J' to the resource management system 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 rights to specific resources based on the new access permission set J'. It also records the change and all relevant edge computing nodes synchronously receive and apply the new access permission set J'.

6. A unified identity management and authentication method according to claim 5, characterized in that: By adjusting the access rights, workers' operation behaviors are monitored and recorded in real time, including: In the edge computing node, an operation behavior log file L is created for each worker with the new access permission set J'; When a worker accesses a resource, the edge computing node checks the access permission set J' corresponding to the worker's identity identifier ID. If the access request meets the requirements of the access permission set J', the worker is allowed to access the resource and records the access time and resource identifier M 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 position of the character in the log file; At regular intervals, the edge computing node aggregates the data in the operation behavior log file L and sends the aggregate information O to the central management system. The aggregate information O includes the identity identifier ID, the latest operation time, the cumulative number of visits 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 operating behavior complies with safety regulations based on the cumulative number of visits P and the operation behavior tracking code N; If any abnormal operation behavior is detected, the central management system will immediately send a warning notification to the relevant edge computing node.

7. A unified identity management and authentication method according to claim 6, characterized in that: By means of the records of the operation behaviors, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge nodes, including: The central management system extracts each worker's operation behavior log L, cumulative access times P, and operation behavior tracking code N during the working period from the summary 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 type of work, S = 100 - (SUM (number of abnormal operations) * 10), where the number of abnormal operations is obtained by comparing the operation behavior log L with predefined safety regulations; 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 type of work. The report includes the identity identifier ID, the work efficiency index R, the safety compliance score S, and improvement suggestions. The formula is: T = ID + R + S + improvement suggestions; At regular intervals, the central management system sends the comprehensive assessment report T to the relevant edge computing nodes. After receiving the comprehensive assessment report T, the edge nodes update the work efficiency and safety compliance records of the relevant work types stored locally. The edge computing node adjusts the permission level F' and access permission set J' of the corresponding job type based on the improvement suggestions in the comprehensive assessment report T, including: if the security compliance score S is lower than the threshold, reducing the access permissions of 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 broadcasts the adjusted permission level F' and access permission set J' to the entire edge network again.

8. A unified identity management and authentication method according to claim 7, characterized in that: The feedback results are used to optimize the authentication process and permission management strategy for the next stage to form a closed-loop management, including: The edge computing node receives the comprehensive assessment report T from the central management system and extracts the work efficiency index R and security compliance score S for each job type. It then generates an optimization weight U for each job type, where U = R + S / 100. This weight is then used to adjust the authentication process and permission management policy. 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 for the next stage is adjusted. If V is greater than 5, an additional identity confirmation step is added to the authentication process. If V is less than or equal to 5, the existing process is simplified to reduce unnecessary verification steps. Based on the improvement suggestions in the comprehensive assessment report T and the optimization weight U, the edge computing node updates the permission management policy, including: for jobs with a security compliance score S below a threshold, reducing the high-risk resource access rights in their access permission set J'; and for jobs with a work efficiency index R above a set standard, relaxing the access permission set J. The edge computing node synchronizes the updated authentication process and permission management policy to the entire edge network to ensure that all relevant nodes consistently apply the new rules. At the same time, it records the time W and the content X of the change, where W = current time and X = change details. At regular intervals, the edge computing node summarizes all change records W and X and sends a summary report Y to the central management system. The summary report Y includes changes in all authentication processes and permission management policies.

9. A unified identity management and authentication method according to claim 8, characterized in that: At the end of each construction phase, the closed-loop management data is 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 indicator 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 stage summary indicator Z, combined with each type of work's work efficiency indicator R and safety compliance score S, an overall performance score AA is calculated using the formula: AA = (R*0.6+S*0.4) / Z, to measure the overall performance of each type of work throughout the construction phase. Based on the comprehensive performance score AA, the edge computing node generates a performance analysis BB for each job type, where BB = job type name + comprehensive performance score AA + performance details + improvement suggestions; The edge computing node aggregates the performance analysis (BB) of all work types into a comprehensive report (CC). The report includes a timeline of key events throughout the construction phase, key optimization measures, and their effectiveness evaluation. A report summary code (DD) is generated using the formula DD=MOD(SUM(BB),1000) for quick retrieval and verification of report content. The comprehensive report CC together with the report summary code DD is sent to the central management system. After receiving it, the central management system stores it in the central database and conducts a global comparative analysis to identify best practice cases and potential areas for improvement; Based on the content of the comprehensive report CC, the central management system sends the next action guide EE to the relevant edge computing nodes. The guide contains 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 permission management strategy for the next construction phase according to its content, forming a new closed-loop management cycle.

10. A unified identity management and authentication system for implementing the method according to any one of claims 1 to 9, characterized in that: include: An identity identifier allocation and identification 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 for initial identification and login verification at the nearest edge computing node; A permission level dynamic update and synchronization module is used to dynamically update the worker's permission level based on the results of the initial identification, synchronize information within the edge network, and adjust the corresponding worker's access rights to resources at different construction stages according to the changes in the permission level; An operation behavior monitoring and analysis module is used to monitor and record workers' operation behaviors in real time by adjusting the access rights. With the help of the operation behavior records, the work efficiency and safety compliance of each type of work are regularly analyzed and fed back to the edge node; The optimization and summary module is used to optimize the identity authentication process and permission management strategy of 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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