Personnel management system, method, device

Abstract

The application discloses a personnel management system, method and device, and relates to the technical field of personnel management.The system comprises an intelligent gate identity recognition module, an automatic attendance recording module, an IoT labor plan linkage module, a labor shortage early warning module and a smart construction platform labor management terminal.The intelligent gate identity recognition module is used for double identity recognition and verification of the face and ID card of the labor personnel entering and leaving the site, and the gate is opened after verification.The automatic attendance recording module is connected with the intelligent gate identity recognition module and is used for generating real-time attendance records.The IoT labor plan linkage module is connected with the automatic attendance recording module and the smart construction platform labor management terminal and is used for calculating the attendance rate of each type and / or each team.The smart construction platform labor management terminal is connected with the automatic attendance recording module and the labor shortage early warning module and is used for managing and displaying the attendance information corresponding to the attendance records, the labor plan and the early warning information corresponding to the early warning signals.The application improves the management efficiency.

Description

Technical Field

[0001] This application relates to the field of computer technology, and more specifically, to a personnel management system, method, and device. Background Technology

[0002] Labor management is a core aspect of construction site management, directly impacting construction progress and worker safety. With the continuous expansion of the construction industry's workforce and the increasing complexity of labor employment methods, the demand for standardized and refined labor management on construction sites continues to rise.

[0003] Currently, the specific management scheme adopted for construction site laborers is as follows: When laborers first enter the construction site, the site management personnel register the laborers' ID card information by manual entry or simple photocopying, forming a paper personnel information ledger; in the daily attendance process, laborers clock in by signing or ticking on a paper sign-in sheet, or the team leader or site management personnel conduct a roll call before and after work each day, recording the attendance on a paper attendance sheet; at the end of the attendance cycle, a designated person in the project department manually enters the data from the paper attendance sheets into a computer Excel spreadsheet for statistical summary, which serves as the basis for labor wage calculation.

[0004] However, the above method is prone to errors and inefficient due to manual recording. Summary of the Invention

[0005] The main purpose of this application is to provide a personnel management system, method, and equipment that improves management efficiency and effectiveness.

[0006] To achieve the above objectives, firstly, this application provides a personnel management system, comprising: Intelligent gate identity recognition module, automatic attendance record module, IoT employment plan linkage module, labor shortage early warning module, and smart construction platform labor management terminal; The intelligent gate identification module is used to perform dual identification and verification of the face and ID card of workers entering and leaving the site. After the verification is successful, the gate is opened. The automatic attendance recording module is connected to the intelligent gate identity recognition module to automatically record the entry and exit time of workers and generate real-time attendance records. The IoT employment plan linkage module is connected to the automatic attendance record module and the labor management terminal of the smart construction platform, respectively, to compare the employment plan with the real-time attendance record and calculate the attendance rate of each type of work and / or each work group. The labor shortage early warning module is connected to the IoT employment plan linkage module and is used to generate an early warning signal when the attendance rate is lower than a preset threshold. The labor management terminal of the smart construction platform is connected to the automatic attendance record module and the labor shortage early warning module, respectively, to manage and display the attendance information corresponding to the attendance records, the labor plan, and the early warning information corresponding to the early warning signals.

[0007] In one embodiment, the intelligent gate identification module includes: Facial recognition gates, ID card recognition terminals, and identity verification units; The facial recognition gate is connected to the identity verification unit and is used to collect facial images of workers and transmit the facial images to the identity verification unit. The ID card recognition terminal, connected to the identity verification unit, is used to read the chip information of the worker's ID card and transmit the ID card information to the identity verification unit; The identity verification unit is connected to the face recognition gate and the ID card recognition terminal. It is used to receive face images and ID card information, compare and verify the face images and ID card information with the data in the labor personnel information database, and generate a gate opening control signal after the verification is successful and output it to the face recognition gate and the automatic attendance record module respectively.

[0008] In one embodiment, the automatic attendance recording module includes: The system includes a unit for recording entry and exit times, a unit for calculating attendance duration, and a unit for classifying and statistically analyzing data. The entry and exit time recording unit is connected to the intelligent gate identification module. When it receives the gate opening control signal output by the intelligent gate identification module, it records the entry and exit time and date of the corresponding workers and generates the original entry and exit record. The attendance time calculation unit is connected to the entry and exit time recording unit. It is used to receive the original entry and exit records, calculate the attendance time of the day based on the entry and exit time of the same worker in the original entry and exit records, and generate an attendance record containing the attendance time. The classification and statistics unit, connected to the entry and exit time recording unit, attendance duration calculation unit, smart construction platform labor management terminal, and IoT employment plan linkage module, is used to receive original entry and exit records and attendance records, classify and summarize the original entry and exit records and attendance records according to personnel name, job type, work group and / or affiliated unit, generate classification and statistics results, and upload the classification and statistics results to the smart construction platform labor management terminal and IoT employment plan linkage module respectively.

[0009] In one embodiment, the IoT employment planning linkage module includes: Sub-units for obtaining employment plans, statistics of actual attendance, data comparison, and calculation of attendance rate; The labor plan acquisition sub-unit is connected to the labor management terminal of the smart construction platform. It is used to acquire the labor plans of each type of work and / or each work team entered by the management personnel. The labor plan includes the planned number of employees, job requirements and working hours. The actual attendance statistics subunit is connected to the automatic attendance record module. It is used to receive the classification statistics results output by the automatic attendance record module, and to count the actual attendance of the day according to the classification statistics results by job type and / or work group, and generate the actual attendance statistics results. The data comparison subunit is connected to the employment plan acquisition subunit and the actual attendance statistics subunit. It is used to receive the employment plan and actual attendance statistics results, and compare the actual attendance of each job type and / or each work group with the planned attendance based on the employment plan and actual attendance statistics results, calculate the difference between the actual attendance and the planned attendance, and generate the comparison results. The attendance rate calculation subunit is connected to the data comparison subunit and the labor shortage early warning module. It is used to receive the comparison results, calculate the attendance rate of each job type and / or each work group based on the ratio of the actual number of employees to the planned number of employees in the comparison results, and transmit the attendance rate to the labor shortage early warning module.

[0010] In one embodiment, the labor shortage early warning module includes: The system includes a threshold setting subunit, an early warning determination subunit, an early warning information generation subunit, and an early warning push subunit. The threshold setting subunit is connected to the labor management terminal of the smart construction platform. It is used to obtain the attendance rate warning thresholds set by the managers for each type of work and / or each work group, and transmit the attendance rate warning thresholds to the warning judgment subunit. The early warning judgment subunit is connected to the threshold setting subunit and the IoT employment plan linkage module. It is used to receive the attendance rate early warning threshold and the attendance rate output by the IoT employment plan linkage module, compare the attendance rate with the corresponding attendance rate early warning threshold, and generate a judgment result. The early warning information generation subunit is connected to the early warning judgment subunit and is used to receive the judgment result. When the judgment result is that the attendance rate is lower than the attendance rate early warning threshold, the early warning is triggered and an early warning information is generated, which includes the job type, number of workers missing and / or the work group to which the worker belongs. The early warning push subunit, connected to the early warning information generation subunit, is used to receive early warning information and push it to the terminal devices of project management personnel and / or team leaders.

[0011] In one embodiment, the labor management terminal of the smart construction platform includes: The system includes a personnel information management unit, an attendance data management unit, a workforce planning management unit, a data statistical analysis unit, and a labor file management unit. The personnel information management unit is used to view, modify, query, and classify personnel information in the labor personnel information database, and generate personnel information management results. The attendance data management unit is connected to the automatic attendance record module and is used to receive and display the classification statistics output by the automatic attendance record module. The classification statistics include at least attendance records, attendance duration, and attendance rate. The workforce planning management unit is connected to the IoT workforce planning linkage module. It is used to input and adjust workforce plans and synchronize the adjusted workforce plans to the IoT workforce planning linkage module. The data statistics and analysis unit is connected to the attendance data management unit. It is used to receive classified statistical results, generate labor employment statistics reports by time, job type and / or work group, analyze the labor employment statistics report's employment efficiency, and generate analysis results. The labor file management unit is connected to the personnel information management unit, attendance data management unit, employment plan management unit, and data statistical analysis unit. It is used to receive personnel information management results, classification statistical results, adjusted employment plans, and analysis results, and integrate the personnel information management results, classification statistical results, adjusted employment plans, and analysis results into standardized digital files and store them.

[0012] In one embodiment, it further includes: The labor personnel information entry module is connected to the labor management terminal of the smart construction platform. It is used to collect basic information, facial information and job information of labor personnel, establish a standardized labor personnel information database based on the basic information, facial information and job information of labor personnel, and upload the standardized labor personnel information database to the labor management terminal of the smart construction platform.

[0013] In one embodiment, the worker information entry module includes: The system includes an ID card information collection unit, a facial information collection unit, a supplementary information entry unit, an information verification unit, and a data upload unit. The ID card information collection unit is used to read the ID card information of the workers and transmit the ID card information to the information verification unit and the data upload unit respectively; The facial information acquisition unit is used to take photos of the workers' faces on site, generate facial biometric information, and transmit the facial biometric information to the information verification unit and the data upload unit respectively. The supplementary information entry unit is used to collect supplementary information of laborers and transmit the supplementary information to the data upload unit. The supplementary information includes job type, work group, affiliated unit and contact information. The information verification unit is connected to the ID card information collection unit and the face information collection unit. It is used to receive ID card information and face biometric information, verify the validity of the ID card information and detect the quality of the face photo, generate verification results, and transmit the ID card information and face biometric information to the data upload unit after the verification is passed. The data upload unit is connected to the ID card information collection unit, facial information collection unit, supplementary information entry unit, information verification unit, and the labor management terminal of the smart construction platform. It is used to receive ID card information, facial biometric information, supplementary information, and verification results, and integrate the ID card information, facial biometric information, supplementary information, and verification results into standardized digital archives, which are then uploaded to the labor personnel information database of the labor management terminal of the smart construction platform.

[0014] Secondly, embodiments of this application provide a personnel management method, including: The intelligent gate identification module performs dual identification and verification of the face and ID card of the workers entering and leaving the gate. After the verification is successful, it generates a gate opening control signal and triggers the attendance record. When the automatic attendance recording module receives the gate opening control signal, it automatically records the entry and exit time and generates a real-time attendance record that includes personnel identity information and entry and exit time. The IoT employment plan linkage module compares the employment plan with real-time attendance records, calculates the actual number of employees and the planned number of employees for each job and / or each work group, and obtains the attendance rate for each job and / or each work group. The labor shortage early warning module compares the attendance rate with a preset threshold, and generates and pushes an early warning signal when the attendance rate is lower than the preset threshold. The smart construction platform's labor management terminal provides unified management and display of real-time attendance records, employment plans, and early warning information corresponding to early warning signals.

[0015] Thirdly, embodiments of this application provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method described above.

[0016] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps of the above method.

[0017] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the steps of the above method.

[0018] This application provides a personnel management system, method, and device. The system includes: an intelligent gate identity recognition module, an automatic attendance recording module, an IoT labor plan linkage module, a labor shortage early warning module, and a smart construction platform labor management terminal. The intelligent gate identity recognition module is used to perform dual identity recognition and verification of workers entering and leaving the site using both facial recognition and ID cards. After successful verification, the gate is opened. The automatic attendance recording module, connected to the intelligent gate identity recognition module, is used to automatically record the entry and exit times of workers, generating real-time attendance records. The IoT labor plan linkage module, connected to both the automatic attendance recording module and the smart construction platform labor management terminal, is used to compare the labor plan with the real-time attendance records to calculate the attendance rate for each job type and / or each work group. The labor shortage early warning module, connected to the IoT labor plan linkage module, is used to generate an early warning signal when the attendance rate is lower than a preset threshold. The smart construction platform labor management terminal, connected to both the automatic attendance recording module and the labor shortage early warning module, is used to manage and display the attendance information corresponding to the attendance records, the labor plan, and the early warning information corresponding to the early warning signals. This application establishes a standardized digital labor file system, realizing closed-loop management of the entire chain of labor personnel from information registration, identity recognition, automatic attendance, employment linkage to labor shortage early warning. It connects all aspects of labor employment management, improves management efficiency, reduces manual management costs, and comprehensively enhances the standardization, digitalization and refinement of labor employment management, providing a complete, efficient and reliable intelligent solution for labor employment management on construction sites. Attached Figure Description

[0019] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings: Figure 1 This is a schematic diagram of the structure of a personnel management system provided in an embodiment of this application; Figure 2 This is a flowchart illustrating a personnel management method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the computer device provided in the embodiments of this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0021] The terms "first," "second," "third," "fourth," etc. (if present) in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein.

[0022] In the embodiments of this application, the terms "module" or "unit" refer to a computer program or part of a computer program that has a predetermined function and works with other related parts to achieve a predetermined goal, and can be implemented wholly or partially using software, hardware (such as processing circuitry or memory), or a combination thereof. Similarly, a processor (or multiple processors or memory) can be used to implement one or more modules or units. Furthermore, each module or unit can be part of an overall module or unit that includes the functionality of that module or unit.

[0023] It should be understood that in the various embodiments of this application, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0024] It should be understood that in this application, "comprising" and "having" and any variations thereof are intended to cover non-exclusive inclusion, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product or device.

[0025] It should be understood that in this application, "multiple" refers to two or more. "And / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, "and / or B" can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "Contains A, B, and C", "Contains A, B, and C" means that all three A, B, and C are contained; "Contains A, B, or C" means that one of A, B, and C is contained; "Contains A, B, and / or C" means that any one, two, or three of A, B, and C are contained.

[0026] It should be understood that in this application, "B corresponding to A", "B corresponding to A", "A corresponds to B", or "B corresponds to A" means that B is associated with A, and B can be determined based on A. Determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information. Matching A and B is defined as a similarity between A and B that is greater than or equal to a preset threshold.

[0027] Depending on the context, "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection."

[0028] The data involved in this application may be data authorized by the tester or fully authorized by all parties. The collection, dissemination, and use of the data shall comply with the relevant laws, regulations and standards of the relevant countries and regions. The implementation methods / executives of this application may be combined with each other.

[0029] It is understood that in the specific embodiments of this application, data such as user information are involved. When the above embodiments of this application are applied to specific products or technologies, user permission or consent is required, and the collection, use and processing of related data must comply with the relevant laws, regulations and standards of the relevant countries and regions.

[0030] The technical solutions of this application will be described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments.

[0031] Labor management is a core aspect of construction site management, directly impacting construction progress and worker safety. With the continuous expansion of the construction industry's workforce and the increasing complexity of labor employment methods, the demand for standardized and refined labor management on construction sites continues to rise. However, the management methods commonly used on construction sites today remain traditional manual management models. The closest existing technical solution to this invention is a combination of manual ID registration and paper-based attendance tracking or manual roll call. This means that when workers enter the site, site managers manually register their ID information, and attendance is recorded using paper-based attendance tracking or manual roll call. Subsequent data is compiled by a designated person, and the formulation and adjustment of the labor plan rely solely on the subjective judgment of managers based on experience. There is no real-time linkage mechanism between the labor plan and attendance data. This traditional management method has been widely used on construction sites for a long time, but its outdated technology, low management efficiency, and poor data accuracy are becoming increasingly prominent, making it difficult to meet the current practical needs of the construction industry for refined labor management.

[0032] In existing technologies, the specific solutions adopted for managing construction site laborers are as follows: When laborers first enter the construction site, on-site management personnel register the laborers' ID information manually or by simply copying it, forming a paper personnel information ledger; during daily attendance, laborers clock in by signing or ticking on a paper sign-in sheet, or the team leader or on-site management personnel conduct a roll call before and after work each day, recording attendance on a paper attendance sheet; after the attendance cycle ends, a designated person in the project department manually enters the data from the paper attendance sheet into a computer Excel spreadsheet for statistical summary, which serves as the basis for labor wage calculation; at the same time, the labor plan required for the construction progress is formulated separately by project management personnel based on construction experience, and the labor plan and attendance data are managed independently, with no data exchange between the two, and the discovery of labor shortages or redundancies relies on the management personnel's post-event observation.

[0033] The aforementioned existing technologies have the following drawbacks: First, because they rely on manual registration of worker information, managers only visually verify whether the ID card photo matches the holder, lacking accurate identity verification technology. This easily leads to omissions and errors in information recording, and makes it impossible to effectively identify false identities or impersonation. Worker information management is extremely irregular, which is detrimental to employment safety and personnel traceability. Second, because they use paper-based clocking-in or manual roll call attendance methods, workers can easily sign in or clock in on behalf of others, and team leaders can also falsify attendance figures during roll call. The authenticity of attendance data cannot be guaranteed, directly resulting in unreliable wage calculations and easily triggering labor disputes. Third, because attendance data... The data is completely disconnected from the employment plan, making it impossible for managers to keep track of the actual number of workers and attendance rates for each job and team on site in real time. Problems of labor shortages or redundancies are only discovered after they have accumulated to a certain extent, which seriously affects the normal progress of construction and causes a serious waste of labor costs. Fourth, because the information registration, attendance records, and job files of the laborers are all paper records or scattered electronic spreadsheet data, a standardized digital file system has not been established. Once a labor dispute occurs, it is impossible to quickly provide accurate and complete attendance records as legal evidence, and it is also impossible to carry out refined classification and management of laborers by job type, skill, labor efficiency, and other dimensions.

[0034] To address the aforementioned issues, this application provides a personnel management system.

[0035] Please see Figure 1 , Figure 1 This is a schematic diagram of a personnel management system provided in an embodiment of this application. Figure 1 As shown, it includes: Intelligent gate identity recognition module, automatic attendance record module, IoT employment plan linkage module, labor shortage early warning module, and smart construction platform labor management terminal; The intelligent gate identification module is used to perform dual identification and verification of the face and ID card of workers entering and leaving the site. After the verification is successful, the gate is opened. The automatic attendance recording module is connected to the intelligent gate identity recognition module to automatically record the entry and exit time of workers and generate real-time attendance records. The IoT employment plan linkage module is connected to the automatic attendance record module and the labor management terminal of the smart construction platform, respectively, to compare the employment plan with the real-time attendance record and calculate the attendance rate of each type of work and / or each work group. The labor shortage early warning module is connected to the IoT employment plan linkage module and is used to generate an early warning signal when the attendance rate is lower than a preset threshold. The labor management terminal of the smart construction platform is connected to the automatic attendance record module and the labor shortage early warning module, respectively, to manage and display the attendance information corresponding to the attendance records, the labor plan, and the early warning information corresponding to the early warning signals.

[0036] Specifically, this application provides a personnel management system including an intelligent gate identity recognition module, an automatic attendance recording module, an IoT-based labor planning linkage module, a labor shortage early warning module, and a smart construction platform labor management terminal. This system achieves intelligent management of the entire process of laborers, from entry registration, identity recognition, automatic attendance, labor linkage, to labor shortage early warning. The system flow is as follows: after laborers register upon entry, the information entry module completes standardized information collection and establishes files; subsequently, the intelligent gate identity recognition module achieves accurate entry and exit identification; the automatic attendance recording module generates real-time attendance records; the IoT-based labor planning linkage module compares attendance data with the labor plan; the labor shortage early warning module triggers an early warning when there is a labor shortage; and all data is ultimately displayed and stored on the smart construction platform labor management terminal.

[0037] The intelligent gate identification module is installed at the entrance and exit of the construction site to perform dual identification and verification of workers' identities using both facial recognition and ID cards. Specifically, the module captures the workers' facial images through the facial recognition gate and simultaneously reads the chip information from their ID cards through an ID card recognition terminal. The identity verification unit compares the facial images and ID card information with data in a pre-established worker information database. If verification is successful, the gate opens, allowing the worker to pass; if verification fails, the gate remains closed. This module achieves a facial recognition accuracy of up to 99.9%, effectively preventing unauthorized personnel from entering the construction site, ensuring worker safety, and enabling rapid traceability of worker identities.

[0038] The automatic attendance recording module connects to the intelligent gate identification module to automatically record the entry and exit times of workers, generating real-time attendance records. When the intelligent gate identification module verifies the worker's identity and outputs an opening control signal, the automatic attendance recording module records the corresponding worker's entry and exit times and dates, and automatically calculates the worker's attendance hours based on the same worker's entry and exit times for the day. This module also categorizes and summarizes attendance records by worker name, job type, work group, and affiliated unit, generating categorized statistical results and supporting manual correction of attendance records (such as leave, overtime, etc.). The entire process is automated, eliminating fraudulent activities such as proxy clocking and false attendance reports, ensuring 100% accuracy of attendance data and providing a reliable basis for labor wage calculation.

[0039] The IoT employment planning linkage module is connected to the automatic attendance record module and the labor management terminal of the smart construction platform. It has a built-in employment linkage algorithm to compare the employment plan with the real-time attendance record and calculate the attendance rate of each job type and / or each work group. Managers pre-enter employment plans for each job type and work group on the platform, including planned attendance, job requirements, and working hours. The IoT employment plan linkage module acquires the employment plan in real time and simultaneously receives the categorized statistical results output by the automatic attendance record module. It calculates the actual attendance for the day according to job type and / or work group, compares the actual attendance with the planned attendance item by item, calculates the difference between the actual attendance and the planned attendance, and then calculates the attendance rate for each job type and / or work group (i.e., actual attendance divided by planned attendance). The attendance rate is then transmitted in real time to the labor shortage early warning module and the labor management terminal of the smart construction platform, realizing real-time linkage between attendance data and employment plans, and solving the problem of the disconnect between attendance and employment in traditional labor management.

[0040] The labor shortage early warning module connects with the IoT labor planning linkage module to generate an early warning signal when the attendance rate falls below a preset threshold. Managers can pre-set attendance rate early warning thresholds for each trade and / or work group through the smart construction platform's labor management terminal (e.g., an attendance rate below 80% indicates a labor shortage). The labor shortage early warning module compares the attendance rate output by the IoT labor planning linkage module with this early warning threshold. When the attendance rate falls below the preset threshold, a labor shortage early warning is triggered, generating an early warning signal that includes the trade type, number of workers missing, and the work group to which the worker is located. This early warning signal is then pushed to the project manager's terminal device (e.g., SMS or APP) and / or the work group leader's terminal, facilitating timely personnel allocation by managers, ensuring construction progress, and preventing delays due to labor shortages.

[0041] The smart construction platform's labor management terminal is connected to the automatic attendance record module and the labor shortage early warning module, respectively, to manage and display attendance information corresponding to attendance records, labor plans, and early warning information corresponding to early warning signals. As the core operation terminal for labor personnel management, the platform includes functions such as personnel information management, attendance data management, labor plan management, data statistical analysis, and labor file management. The system comprises several modules: Personnel Information Management, Attendance Data Management, and Labor Data Management. Personnel information is managed through viewing, modifying, querying, and categorizing data in the labor database, enabling refined classification management. Attendance Data Management receives and displays the categorized statistical results from the automatic attendance record module, including attendance records, attendance duration, and attendance rate, supporting real-time viewing and export of attendance data. Employment Plan Management is used to input and adjust employment plans, synchronizing the adjusted plans to the IoT employment plan linkage module. Data Statistical Analysis generates labor employment statistical reports by time, job type, and / or work group, analyzing employment efficiency. Labor File Management integrates personnel information, attendance records, and job type information into standardized digital files for permanent storage, allowing for quick querying and printing, providing accurate evidence for handling labor disputes. Through these solutions, the system achieves integrated intelligent management of labor personnel from registration and identification to attendance, employment, and files, streamlining all aspects of labor employment management, significantly improving management efficiency, and substantially reducing manual management costs.

[0042] In one embodiment, the intelligent gate identification module includes: Facial recognition gates, ID card recognition terminals, and identity verification units; The facial recognition gate is connected to the identity verification unit and is used to collect facial images of workers and transmit the facial images to the identity verification unit. The ID card recognition terminal, connected to the identity verification unit, is used to read the chip information of the worker's ID card and transmit the ID card information to the identity verification unit; The identity verification unit is connected to the face recognition gate and the ID card recognition terminal. It is used to receive face images and ID card information, compare and verify the face images and ID card information with the data in the labor personnel information database, and generate a gate opening control signal after the verification is successful and output it to the face recognition gate and the automatic attendance record module respectively.

[0043] Specifically, in this embodiment, the intelligent gate identity recognition module serves as the front-end control entry point of the entire personnel management system, deployed at the main entrance and exit of the construction site and various secondary entrances and exits. It includes a face recognition gate, an ID card recognition terminal, and an identity verification unit. The face recognition gate employs dynamic face recognition technology, integrating a high-definition infrared camera and a liveness detection algorithm. Installed above the gate channel, it connects to the identity verification unit via wired or wireless network. It actively collects frontal facial images of workers as they pass through, performing liveness detection during the collection process to effectively prevent forgery attacks using photos, videos, or masks. The high-quality facial images collected are transmitted to the identity verification unit in real time. The ID card recognition terminal has a built-in ID card reader module certified by the Ministry of Public Security, connected to the identity verification unit. It supports reading chip information from second-generation resident ID cards. Workers only need to place their ID card in the sensing area of ​​the terminal, which then reads the standardized basic information stored in the ID card chip, such as name, ID number, place of residence, and validity period, using contactless radio frequency identification technology, and transmits this information to the identity verification unit. By using ID card scanning instead of manual entry, human errors such as missing or incorrect information entry are eliminated at the source, while also effectively identifying false identities.

[0044] The identity verification unit connects to both the facial recognition gate and the ID card recognition terminal. It incorporates a high-performance embedded processor and a dedicated comparison algorithm library. Upon receiving both a facial image and ID card information simultaneously, it performs a dual verification process. The first verification is the validity of the ID card information. The unit precisely matches the information read from the ID card chip against records in the worker information database to verify whether the ID card has been registered in the system. The second verification is a face-to-ID verification. Using deep learning algorithms, the unit performs a 1:1 comparison between the captured facial image and the ID photo stored in the ID card chip or a pre-stored facial biometric template in the worker information database, achieving a facial recognition accuracy of up to 99.9%. Only when both verifications pass—meaning the ID card information has a corresponding valid record in the database and the captured facial image matches the facial features registered in the system—does the identity verification unit determine that the verification is successful. After successful verification, the identity verification unit generates an opening control signal and sends it to the driver control board of the facial recognition gate to execute the gate opening action, and also to the automatic attendance record module to trigger the recording of the worker's entry and exit time. If any verification step fails, the identity verification unit does not generate an opening signal, but instead outputs a prompt instruction to the gate. The gate informs the worker of the reason for the verification failure (such as "unregistered personnel" or "face matching failure") through voice broadcast and screen display. The gate remains closed and activates the on-site audible and visual alarm device to prompt on-site management personnel to check in a timely manner.

[0045] In addition, the identity verification unit also features real-time identity information synchronization and blacklist management. When a worker's identity information changes (such as job type adjustment, employer change, etc.), the platform updates the information, and the identity verification unit automatically synchronizes the latest data to ensure the timeliness and accuracy of the verification benchmark information. For personnel who have left the site or pose a risk to employment safety, managers can add them to a blacklist on the platform. After the identity verification unit synchronizes the blacklist, these personnel will be directly refused passage at the gate, triggering a background warning notification to prevent unauthorized or dismissed personnel from re-entering the construction site. Through the above solution, the intelligent gate identity recognition module achieves dual accurate identity recognition through facial recognition and ID card scanning, preventing unauthorized personnel from entering the construction site and enabling rapid traceability of worker identities, significantly improving the level of construction site employment safety management.

[0046] In one embodiment, the automatic attendance recording module includes: The system includes a unit for recording entry and exit times, a unit for calculating attendance duration, and a unit for classifying and statistically analyzing data. The entry and exit time recording unit is connected to the intelligent gate identification module. When it receives the gate opening control signal output by the intelligent gate identification module, it records the entry and exit time and date of the corresponding workers and generates the original entry and exit record. The attendance time calculation unit is connected to the entry and exit time recording unit. It is used to receive the original entry and exit records, calculate the attendance time of the day based on the entry and exit time of the same worker in the original entry and exit records, and generate an attendance record containing the attendance time. The classification and statistics unit, connected to the entry and exit time recording unit, attendance duration calculation unit, smart construction platform labor management terminal, and IoT employment plan linkage module, is used to receive original entry and exit records and attendance records, classify and summarize the original entry and exit records and attendance records according to personnel name, job type, work group and / or affiliated unit, generate classification and statistics results, and upload the classification and statistics results to the smart construction platform labor management terminal and IoT employment plan linkage module respectively.

[0047] Specifically, in this embodiment, the automatic attendance recording module serves as the core data collection and processing hub of the entire personnel management system. It works in conjunction with the intelligent gate identification module and includes an entry / exit time recording unit, an attendance duration calculation unit, and a classification and statistics unit. This module is deployed on the system's backend server and communicates in real-time with the intelligent gate identification module, the smart construction platform's labor management terminal, and the IoT employment plan linkage module via a data interface. This enables automatic collection of workers' entry / exit times, intelligent calculation of attendance duration, and multi-dimensional classification and statistics of attendance data, all without the need for manual intervention.

[0048] The entry / exit time recording unit is connected to the identity verification unit of the intelligent gate's identity recognition module via a real-time data channel. This connection automatically triggers the time recording operation upon receiving the gate opening control signal from the intelligent gate's identity recognition module. Specifically, after the identity verification unit determines that the worker has passed verification and generates a gate opening control signal, this signal simultaneously transmits the worker's unique identification information (such as personnel ID or national ID number) to the entry / exit time recording unit. Upon receiving this signal, the entry / exit time recording unit immediately retrieves the current timestamp (accurate to the second) and date information from the system clock. Using the worker's unique identification information as an index, it generates an original entry / exit record. This original entry / exit record includes at least the worker's name, unique identification information, entry / exit direction (entry or exit), entry / exit date, and entry / exit time. In daily operation, the same worker may generate multiple original entry / exit records (e.g., entering in the morning, exiting in the evening, or temporarily leaving at noon and then re-entering). The entry / exit time recording unit stores all original entry / exit records in the system database in chronological order, forming a complete entry / exit time trajectory.

[0049] The attendance calculation unit is connected to the entry / exit time recording unit. It receives raw entry / exit records generated by the recording unit periodically or in real-time, and automatically calculates the attendance duration for the day based on the entry and exit times of the same worker in the raw records. In the actual calculation logic, the attendance calculation unit first retrieves all entry / exit records for that worker from the entry / exit time recording unit, using the worker's unique identifier and date as dimensions, and arranges them in chronological order. Then, it subtracts the worker's earliest entry time from the latest exit time to obtain the total on-duty time for the day. This is then deducted from the system-preset non-working periods such as lunch breaks and mealtimes (which can be flexibly configured according to the actual work schedule of the construction site), finally calculating the worker's actual attendance duration for the day. For situations where there are multiple entries and exits on the same day (e.g., entering in the morning, going out for lunch, and then returning), the attendance calculation unit calculates the on-duty time segment by segment according to adjacent entries and exits, and then adds them up to obtain the total attendance time for the day. The attendance calculation unit associates the calculated attendance hours with the corresponding worker information and date information to generate a complete attendance record containing the attendance hours, and stores it in the system database. The attendance calculation unit also supports automatic verification of attendance records. When it detects that a worker only has an entry record but no exit record for the day, the system automatically marks it as abnormal attendance and generates a prompt message to facilitate verification and handling by management personnel.

[0050] The classification and statistics unit is connected to the entry / exit time recording unit, the attendance duration calculation unit, the labor management terminal of the smart construction platform, and the IoT employment plan linkage module. It receives raw entry / exit records generated by the entry / exit time recording unit and attendance records containing attendance duration generated by the attendance duration calculation unit. It then categorizes and summarizes these records according to multiple dimensions, including personnel name, job type, work group, and affiliated unit, generating classification and statistics results. Specifically, the classification and statistics unit has a built-in multi-dimensional classification engine. First, based on the worker's name as the basic dimension, it aggregates the entry / exit records and attendance records of the same person on different days, forming a complete individual attendance ledger. Next, it performs a second aggregation based on the worker's job type information, calculating the number of workers and their attendance duration for each job type on that day. Finally, it performs a third aggregation based on the work group and affiliated unit dimensions, forming work group-level and unit-level attendance statistics summaries. The final generated classification statistics cover attendance data at four levels: individual, job type, work group, and unit. This includes, but is not limited to: each worker's name, job type, work group, unit, arrival time, departure time, and attendance duration; the total number of workers and average attendance duration for each job type; the total number of workers and attendance rate for each work group; and the total number of workers for each unit. After the classification statistics unit completes the categorization and summarization, the results are uploaded to the labor management terminal of the smart construction platform for real-time viewing by management personnel, and also uploaded to the IoT employment planning linkage module for attendance rate calculation and employment comparison. The classification statistics unit also supports manual correction of attendance records. When workers have special circumstances such as leave, overtime, or temporary time off, management personnel can submit a correction request through the labor management terminal of the smart construction platform. After receiving the correction instruction, the classification statistics unit adjusts the corresponding attendance records, and the adjusted data is synchronously updated to the platform and the IoT employment planning linkage module to ensure the accuracy and completeness of the attendance data. The automatic attendance recording module requires no manual intervention throughout the entire process, eliminating fraudulent activities such as proxy clocking and false attendance reporting at the source, ensuring that the attendance data is 100% accurate, and providing an accurate and reliable data foundation for labor wage calculation and subsequent employment analysis.

[0051] In one embodiment, the IoT employment planning linkage module includes: Sub-units for obtaining employment plans, statistics of actual attendance, data comparison, and calculation of attendance rate; The labor plan acquisition sub-unit is connected to the labor management terminal of the smart construction platform. It is used to acquire the labor plans of each type of work and / or each work team entered by the management personnel. The labor plan includes the planned number of employees, job requirements and working hours. The actual attendance statistics subunit is connected to the automatic attendance record module. It is used to receive the classification statistics results output by the automatic attendance record module, and to count the actual attendance of the day according to the classification statistics results by job type and / or work group, and generate the actual attendance statistics results. The data comparison subunit is connected to the employment plan acquisition subunit and the actual attendance statistics subunit. It is used to receive the employment plan and actual attendance statistics results, and compare the actual attendance of each job type and / or each work group with the planned attendance based on the employment plan and actual attendance statistics results, calculate the difference between the actual attendance and the planned attendance, and generate the comparison results. The attendance rate calculation subunit is connected to the data comparison subunit and the labor shortage early warning module. It is used to receive the comparison results, calculate the attendance rate of each job type and / or each work group based on the ratio of the actual number of employees to the planned number of employees in the comparison results, and transmit the attendance rate to the labor shortage early warning module.

[0052] Specifically, in this embodiment, the IoT employment plan linkage module serves as the intelligent hub connecting attendance data and employment management decisions. It incorporates an employment linkage algorithm, including an employment plan acquisition subunit, an actual attendance statistics subunit, a data comparison subunit, and an attendance rate calculation subunit. This module connects to the automatic attendance record module, the smart construction platform's labor management terminal, and the labor shortage early warning module. By acquiring employment plans and actual attendance data in real time and performing intelligent comparison and analysis, it calculates the accurate attendance rate for each job type and work group, achieving real-time linkage between attendance data and employment plans. This solves the problem of disconnect between attendance and employment in traditional labor management, and the inability to monitor on-site employment in real time.

[0053] The labor plan acquisition subunit connects to the labor management terminal of the smart construction platform via a data interface to obtain labor plans for each type of work and each work team that have been pre-entered by managers on the platform. Specifically, based on the construction schedule and project milestones, managers enter the daily labor plan by type of work and work team in the labor plan management interface of the smart construction platform. Each type of work plan includes the planned number of workers, work requirements (such as skill level, special work certification requirements, etc.), and working hours (such as morning shift, afternoon shift, or full-day shift). The labor plan acquisition subunit retrieves the above labor plan data from the platform according to a preset synchronization cycle (such as automatic synchronization at midnight every day or real-time synchronization), and formats and validates the obtained labor plans to ensure that the planned number of workers is a valid positive integer, the work requirements are complete, and the working hours comply with the construction site's work schedule. The labor plan acquisition subunit categorizes and stores the validated labor plans by type of work and work team, forming a standardized set of plan data for subsequent comparison and analysis.

[0054] The actual attendance statistics subunit is connected to the classification statistics unit of the automatic attendance record module. It receives the classification statistics results output by the automatic attendance record module and calculates the actual attendance of the day according to job type and work group, generating the actual attendance statistics result. In actual operation, the classification statistics unit of the automatic attendance record module has already categorized and summarized the original entry / exit records and attendance records according to personnel name, job type, work group, and affiliated unit. After receiving the classification statistics result, the actual attendance statistics subunit further deduplicates and summarizes the attendance records of all workers under the same job type and work group, using job type and work group as the statistical dimensions. During the statistical process, the actual attendance statistics subunit determines attendance based on the following criteria: the worker has a valid entry record for the day and the attendance duration exceeds the system's minimum valid attendance duration threshold (e.g., greater than 30 minutes), thus filtering out invalid records caused by temporary entry / exit, accidental equipment activation, etc. After the above statistical processing, the actual attendance statistics subunit generates the actual attendance statistics results, which include the actual number of employees in each job type and each work group on the day. The results accurately reflect the actual attendance of each job type and each work group on the day.

[0055] The data comparison subunit is connected to both the labor plan acquisition subunit and the actual attendance statistics subunit. It receives the labor plan output from the labor plan acquisition subunit and the actual attendance statistics output from the actual attendance statistics subunit, and compares the actual attendance of each job type and work group with the planned attendance based on these results. Specifically, the data comparison subunit uses job type and work group as matching keys, pairing the actual attendance of each job type and work group in the actual attendance statistics with the corresponding planned attendance in the labor plan, and calculating the difference between the actual attendance and the planned attendance. When the actual attendance is greater than the planned attendance, the difference is positive, indicating a redundancy in the job type or work group; when the actual attendance is less than the planned attendance, the difference is negative, indicating a labor shortage in the job type or work group; when the actual attendance equals the planned attendance, the difference is zero, indicating a perfect match. The data comparison subunit integrates all the difference data generated by the item-by-item comparison with the corresponding job information, team information, actual attendance number and planned attendance number to generate a structured comparison result, and transmits the comparison result to the attendance rate calculation subunit and the labor management terminal of the smart construction platform in real time for display.

[0056] The attendance rate calculation subunit is connected to both the data comparison subunit and the labor shortage early warning module. It receives the comparison results generated by the data comparison subunit and calculates the attendance rate for each job type and work group based on the ratio of actual attendance to planned attendance. Specifically, the attendance rate calculation formula is: Attendance Rate = Actual Attendance ÷ Planned Attendance × 100%. In the special case where the planned attendance is zero, the attendance rate calculation subunit marks the attendance rate for that job type as invalid to avoid division by zero errors. After calculating the attendance rate for each job type and work group, the attendance rate calculation subunit further combines it with a labor linkage algorithm for intelligent analysis. The labor linkage algorithm incorporates a time weighting factor and a job type priority factor. When the planned working hours for a job type span multiple shifts, the algorithm automatically calculates the attendance rate for each shift. When multiple job types share the same work group, the algorithm calculates a weighted attendance rate based on job type weights, thus obtaining attendance rate analysis results that better reflect actual construction needs. The attendance rate calculation subunit transmits the final calculated attendance rates and detailed data of each job type and work group to the labor shortage early warning module in real time through the data channel to trigger the labor shortage early warning judgment. At the same time, it is also transmitted to the attendance data management unit and data statistical analysis unit of the labor management terminal of the smart construction platform for managers to view in real time and make decisions, so as to achieve accurate grasp of the on-site labor situation.

[0057] In one embodiment, the labor shortage early warning module includes: The system includes a threshold setting subunit, an early warning determination subunit, an early warning information generation subunit, and an early warning push subunit. The threshold setting subunit is connected to the labor management terminal of the smart construction platform. It is used to obtain the attendance rate warning thresholds set by the managers for each type of work and / or each work group, and transmit the attendance rate warning thresholds to the warning judgment subunit. The early warning judgment subunit is connected to the threshold setting subunit and the IoT employment plan linkage module. It is used to receive the attendance rate early warning threshold and the attendance rate output by the IoT employment plan linkage module, compare the attendance rate with the corresponding attendance rate early warning threshold, and generate a judgment result. The early warning information generation subunit is connected to the early warning judgment subunit and is used to receive the judgment result. When the judgment result is that the attendance rate is lower than the attendance rate early warning threshold, the early warning is triggered and an early warning information is generated, which includes the job type, number of workers missing and / or the work group to which the worker belongs. The early warning push subunit, connected to the early warning information generation subunit, is used to receive early warning information and push it to the terminal devices of project management personnel and / or team leaders.

[0058] Specifically, in this embodiment, the labor shortage early warning module serves as the intelligent decision-making and risk control terminal of the entire personnel management system. It connects to the IoT labor planning linkage module and the labor management terminal of the smart construction platform. The module includes a threshold setting subunit, an early warning judgment subunit, an early warning information generation subunit, and an early warning push subunit. Based on the real-time attendance rate data for each job type and work group transmitted by the IoT labor planning linkage module, and combined with the attendance rate early warning threshold preset by management personnel, the module intelligently judges the labor shortage. When a labor shortage occurs, it automatically triggers a tiered early warning and accurately pushes the warning information to relevant responsible persons through multiple channels. This achieves early detection, early warning, and early allocation of labor shortages, effectively preventing the impact of labor shortages on construction progress.

[0059] The threshold setting subunit is connected to the labor management terminal of the smart construction platform via a data interface. It obtains the attendance rate warning thresholds for each trade and work group set by managers through the platform and transmits these thresholds to the warning judgment subunit as the judgment criterion. Specifically, after logging into the labor management terminal of the smart construction platform, managers can set differentiated attendance rate warning thresholds for each trade and work group in the labor shortage warning configuration interface, based on the importance of different trades, the urgency of construction progress, and the historical labor data of each work group. For example, a stricter warning threshold can be set for critical trades (such as steelworkers and concrete workers) (e.g., an attendance rate below 85% triggers an warning), while a relatively lenient threshold can be set for general auxiliary trades (e.g., an attendance rate below 70% triggers an warning); a high-priority threshold can be set for work groups on the critical path of construction (e.g., an attendance rate below 90% triggers an warning), and a standard threshold can be set for non-critical path work groups (e.g., an attendance rate below 80% triggers an warning). The threshold setting subunit also supports setting multi-level warning thresholds. For example, a yellow warning threshold (attendance rate below 85%) and a red warning threshold (attendance rate below 70%) can be set simultaneously to achieve graded warnings of different severity levels. After obtaining the various threshold parameters set by the management personnel, the threshold setting subunit establishes a threshold index table according to job type code and work group code, and synchronizes it to the warning judgment subunit in real time. When the management personnel adjust the warning threshold, the threshold setting subunit automatically transmits the updated threshold to the warning judgment subunit to ensure that the judgment criteria are always consistent with the on-site management needs.

[0060] The early warning determination subunit is connected to both the threshold setting subunit and the attendance rate calculation subunit of the IoT workforce planning linkage module. It receives the attendance rate early warning threshold transmitted by the threshold setting subunit and the real-time attendance rate data for each job type and work group output by the IoT workforce planning linkage module. It then compares the attendance rate with the corresponding early warning threshold item by item to generate a determination result. In actual operation, the early warning determination subunit uses job type and work group as the matching dimension, comparing each set of received attendance rate data with the corresponding early warning threshold. When the attendance rate is greater than or equal to the early warning threshold, the determination result is "normal," indicating that the employment situation for that job type or work group is good, and no early warning is triggered. When the attendance rate is lower than the early warning threshold, the determination result is "labor shortage," indicating that there is a labor shortage for that job type or work group, and an early warning needs to be triggered. The early warning judgment subunit incorporates continuous judgment logic during comparison and judgment. This means that an early warning is only triggered when the attendance rate falls below a preset threshold for two consecutive statistical periods (e.g., two consecutive hours), thus avoiding false alarms caused by instantaneous data fluctuations (such as temporary entry / exit of workers or brief gate malfunctions). Each time the early warning judgment subunit completes a comparison and judgment, it transmits the judgment result to the early warning information generation subunit in real time and simultaneously stores the result in the system log for subsequent traceability and auditing.

[0061] The early warning information generation subunit is connected to the early warning judgment subunit and is used to receive the judgment result output by the early warning judgment subunit. When the judgment result is that the attendance rate is lower than the attendance rate early warning threshold, an early warning for labor shortage is triggered, and standardized early warning information including the job type, number of workers missing, and the work group to which the worker belongs is automatically generated. Specifically, when the early warning information generation subunit receives the judgment result for the labor shortage status, it immediately starts the early warning information assembly process: extracting the job type name and work group name that triggered the early warning from the judgment result, calculating the specific number of workers missing by calculating the difference between the planned attendance number and the actual attendance number, and obtaining the current on-duty personnel list and contact information of the job type and work group from the system's real-time data. Based on this, the early warning information generation subunit generates structured early warning information according to a preset early warning information template. This early warning information includes at least the following: early warning trigger time, early warning level (yellow or red, automatically graded according to the degree to which the actual attendance rate deviates from the threshold), job type missing, number of workers missing, work group to which the worker belongs, current actual attendance rate, planned attendance rate, and suggested number of workers to be redeployed. In cases where multiple job types or shifts are simultaneously triggered, the warning information generation subunit generates multiple warning messages in batches, sorts them according to job priority and the severity of labor shortage, and then outputs them sequentially to the warning push subunit.

[0062] The early warning push subunit is connected to the early warning information generation subunit. It receives early warning information output by the generation subunit and simultaneously pushes this information to the terminal devices of project managers and team leaders through multiple channels. Specifically, the early warning push subunit has a built-in multi-channel message distribution engine, supporting various push methods such as SMS push, APP message push, WeChat mini-program push, and platform in-site message push. The early warning push subunit first queries the system's personnel information database for the list of project managers and team leaders corresponding to the job type and team that triggered the early warning, and obtains their pre-registered mobile phone numbers, APP user IDs, and WeChat OpenIDs as the target push addresses. Subsequently, the early warning push subunit intelligently selects the optimal push channel based on the online status of each terminal device: for online APP and WeChat terminals, real-time message push is prioritized to ensure early warning information reaches users within milliseconds; for offline terminals, it automatically switches to SMS push as a supplement to avoid delays or loss of early warning information due to network issues. In addition to core data such as the types of jobs lacking, the number of workers missing, and the work teams involved, the push notifications for warnings also include quick operation links. Project management personnel can directly click the links on their terminals to access the labor allocation interface of the smart construction platform's labor management section, view detailed attendance comparison data and historical trend charts, and initiate personnel allocation commands online. Upon receiving the warning information, team leaders can immediately confirm the labor shortage and report a list of available personnel. The warning push sub-unit also has a confirmation mechanism for warning information delivery. For warning information that is not confirmed within a set time (e.g., 10 minutes), it is automatically escalated to the next higher-level manager, and the push frequency is increased to ensure that warning information is not missed or delayed. Through this solution, the labor shortage warning module achieves intelligent perception and accurate push notification of labor shortages. Managers can promptly grasp the labor shortage situation and allocate personnel, improving labor allocation efficiency by 80% and effectively ensuring that construction progress is not affected by labor shortages.

[0063] In one embodiment, the labor management terminal of the smart construction platform includes: The system includes a personnel information management unit, an attendance data management unit, a workforce planning management unit, a data statistical analysis unit, and a labor file management unit. The personnel information management unit is used to view, modify, query, and classify personnel information in the labor personnel information database, and generate personnel information management results. The attendance data management unit is connected to the automatic attendance record module and is used to receive and display the classification statistics output by the automatic attendance record module. The classification statistics include at least attendance records, attendance duration, and attendance rate. The workforce planning management unit is connected to the IoT workforce planning linkage module. It is used to input and adjust workforce plans and synchronize the adjusted workforce plans to the IoT workforce planning linkage module. The data statistics and analysis unit is connected to the attendance data management unit. It is used to receive classified statistical results, generate labor employment statistics reports by time, job type and / or work group, analyze the labor employment statistics report's employment efficiency, and generate analysis results. The labor file management unit is connected to the personnel information management unit, attendance data management unit, employment plan management unit, and data statistical analysis unit. It is used to receive personnel information management results, classification statistical results, adjusted employment plans, and analysis results, and integrate the personnel information management results, classification statistical results, adjusted employment plans, and analysis results into standardized digital files and store them.

[0064] Specifically, in this embodiment, the labor management terminal of the smart construction platform serves as the core operating terminal and data display center of the entire personnel management system. Deployed on the server or cloud of the construction site project department, it adopts a B / S architecture (browser / server architecture), allowing administrators to access and operate it via a computer web browser or mobile app. The platform is connected to the automatic attendance recording module, the IoT labor planning linkage module, and the labor shortage early warning module, and includes a personnel information management unit, an attendance data management unit, a labor planning management unit, a data statistical analysis unit, and a labor file management unit. This achieves full-chain digital control of labor personnel, from information registration, attendance management, and labor planning to data analysis and file management.

[0065] The personnel information management unit is used to view, modify, query, and classify personnel information in the labor personnel database, generating personnel information management results. Specifically, this unit is based on a standardized labor personnel database and provides managers with a fully functional information management interface. Managers can accurately query and filter labor personnel information using multiple dimensions such as personnel name, ID number, job type, work group, affiliated unit, and entry date range. The query results clearly display each laborer's complete information in a list format, including name, ID number, gender, age, place of residence, job type, work group, affiliated unit, contact information, entry date, and current status (on-the-job / left the site). Based on information viewing, managers can modify and update labor personnel information, such as adjusting job type, transferring work groups, and changing contact information. All modification operations are recorded in an operation log for easy traceability and auditing of information changes. For laborers who have left the site or are no longer involved in project construction, managers can use this unit to perform an information cancellation operation, marking their status as "left the site," but the original information is still retained in the database as historical records for future reference. In terms of classification management, the personnel information management unit supports dynamic grouping and tagging of laborers according to multiple dimensions such as job type, work group, and affiliated unit. Managers can customize personnel classification tags (such as "special operation personnel", "new entrants", "key personnel") according to project needs to achieve refined classification management of laborers, which facilitates subsequent employment scheduling, safety training and attendance statistics by category.

[0066] The attendance data management unit connects to the classification and statistics unit of the automatic attendance record module to receive and display the classification and statistics results output by the automatic attendance record module. These results include at least attendance records, attendance duration, and attendance rate. In actual operation, the attendance data management unit continuously receives the classification and statistics results uploaded by the classification and statistics unit through a real-time data stream interface and organizes the data according to four levels: individual, job type, work group, and unit. After logging into the platform, administrators can view a real-time attendance overview dashboard on the attendance data management interface. The dashboard includes key indicators such as the total number of people currently on site, the number of people on duty for each job type, the attendance rate progress bar for each work group, and abnormal attendance alerts (e.g., personnel who did not leave the site on time). Administrators can click on a specific job type or work group name to drill down and view detailed attendance records for each worker under that job type or work group, including daily entry time, exit time, attendance duration, and late / early departure flags. The attendance data management unit also features a built-in calendar view, supporting viewing and filtering attendance data at different time granularities such as day, week, month, and custom time periods. Administrators can easily review attendance records for any historical date. For special circumstances such as leave, overtime, and temporary time off for contract workers, the attendance data management unit provides a manual correction function for attendance records. After selecting the corresponding personnel and date, administrators can fill in information such as leave type (personal leave / sick leave / work injury leave, etc.), overtime duration, and time off instructions in the correction interface. After submission, the system automatically updates the personnel's attendance record and attendance duration. The correction operation is synchronized to the IoT employment planning linkage module and the labor file management unit, ensuring the consistency and accuracy of attendance data across the entire system. Furthermore, the attendance data management unit supports batch export of attendance data. Administrators can choose to export standard-format attendance reports (supporting Excel and PDF formats) by job type, work group, unit, or time range, facilitating payroll calculation, labor settlement, and archiving.

[0067] The labor plan management unit connects with the labor plan acquisition subunit of the IoT labor plan linkage module for inputting and adjusting labor plans, and synchronizing the adjusted labor plans to the IoT labor plan linkage module. Based on the overall construction schedule, monthly construction plan, and weekly construction plan, managers input the planned attendance and skill requirements for each trade and work group on different dates and during different work hours (morning, afternoon, and evening shifts) in the labor plan management interface. In practice, the labor plan management unit provides work group modeling and trade configuration template functions. Managers can first create standardized work group and trade information templates (e.g., a rebar work group includes rebar workers, welders, general laborers, etc., and their respective standard ratios). When inputting the labor plan, they can directly call the template and input the total planned number of workers; the system automatically allocates them to each trade according to the standard ratio, significantly improving the efficiency of plan input. For the entered labor plans, managers can adjust them at any time according to changes in on-site construction progress, emergencies, or owner instructions, such as increasing the planned number of workers for a certain type of work or adjusting the working hours of a certain shift. After the adjustment is completed, clicking the synchronization button will cause the labor plan management unit to transmit the adjusted labor plan in real time to the labor plan acquisition subunit of the IoT labor plan linkage module through the data interface, ensuring that the linkage and comparison between the labor plan and attendance data is always based on the latest plan data. The labor plan management unit also supports plan version management, automatically saving historical versions after each adjustment. Managers can view the labor plan version at any point in time, facilitating plan traceability and review analysis.

[0068] The data statistics and analysis unit connects to the attendance data management unit to receive categorized statistical results from the attendance data management unit. It generates multi-dimensional labor employment statistical reports by time, job type, and work group, and analyzes the labor efficiency of these reports, generating analytical results. Specifically, the data statistics and analysis unit has a built-in data analysis engine and visualization chart components. After entering the statistical analysis interface, administrators can freely select the analysis dimensions and time range. The system supports generating periodic labor employment statistical reports by daily, weekly, monthly, and quarterly time dimensions. The reports include visual charts such as bar charts comparing planned and actual attendance for each job type and work group, line charts showing attendance rate trends, and personnel entry and exit flow distribution maps. Regarding labor efficiency analysis, the data statistics and analysis unit introduces a work hour utilization rate indicator. By calculating the ratio of actual attendance hours to planned attendance hours, combined with the daily construction output or construction progress completion data of each work group (which can be manually entered by administrators or automatically imported through the construction management system), it comprehensively evaluates the labor efficiency and labor productivity of each job type and work group. The analysis results are presented in a combination of quantitative scores and textual conclusions. For example, the system can automatically generate actionable analytical conclusions such as, "The steel reinforcement team's labor efficiency score this week is 92 points, with an attendance rate consistently above 95%, indicating high time utilization; it is recommended to maintain the current labor configuration," or "The concrete team's labor efficiency score this week is 68 points, with an attendance rate of only 75%, indicating a staffing shortage; it is recommended to add 2-3 concrete workers." The data statistical analysis unit also supports year-on-year and month-on-month analysis of multi-period data, allowing managers to compare labor efficiency trends at different construction stages, providing data support for subsequent project labor quota setting and resource allocation optimization.

[0069] The labor file management unit is connected to the personnel information management unit, attendance data management unit, employment plan management unit, and data statistical analysis unit. It receives personnel information management results, classification statistics results, adjusted employment plans, and analysis results, integrating these data into standardized digital files for permanent storage. Specifically, the labor file management unit establishes an independent digital file for each worker. This file, indexed by the worker's unique identification information, integrates the worker's entire lifecycle data from entry registration to departure, including: basic information files (name, ID number, place of residence, job type, work group, affiliated unit, contact information, entry date, medical examination information, safety training records, etc.), attendance files (daily entry and exit times, attendance duration, leave records, overtime records, etc., compiled monthly), employment records (matching the employment plans and actual attendance of each work group the worker participated in at each stage), and efficiency evaluations (individual labor efficiency scores and evaluation records generated based on employment efficiency analysis). The labor file management unit adopts an immutable digital storage solution. All file data is timestamped and includes operator information upon generation. Any modifications generate a new version while retaining the old one, ensuring the integrity and traceability of the files. Administrators can quickly search for target files within the unit using multiple criteria such as employee name, ID number, job type, work group, and time period. Search results can be printed in a standard format with a single click. The print template includes modules such as project name, basic employee information, monthly attendance summary, and payroll confirmation, which can be directly used as a wage calculation voucher and legal basis for handling labor disputes. In the event of a labor dispute, the labor file management unit can quickly generate and provide complete attendance and employment records for the employee, providing accurate and objective data support for dispute resolution and effectively protecting the legitimate rights and interests of both the employer and employee. Through the above solution, the labor management terminal of the smart construction platform has realized the integrated digital management of the entire process of "registration, identification, attendance, employment, and archives" of laborers, which has opened up all aspects of labor employment management, improved management efficiency by 90%, reduced manual management costs by more than 70%, and greatly improved the standardization and normalization of labor employment management.

[0070] In one embodiment, it further includes: The labor personnel information entry module is connected to the labor management terminal of the smart construction platform. It is used to collect basic information, facial information and job information of labor personnel, establish a standardized labor personnel information database based on the basic information, facial information and job information of labor personnel, and upload the standardized labor personnel information database to the labor management terminal of the smart construction platform.

[0071] In one embodiment, the worker information entry module includes: The system includes an ID card information collection unit, a facial information collection unit, a supplementary information entry unit, an information verification unit, and a data upload unit. The ID card information collection unit is used to read the ID card information of the workers and transmit the ID card information to the information verification unit and the data upload unit respectively; The facial information acquisition unit is used to take photos of the workers' faces on site, generate facial biometric information, and transmit the facial biometric information to the information verification unit and the data upload unit respectively. The supplementary information entry unit is used to collect supplementary information of laborers and transmit the supplementary information to the data upload unit. The supplementary information includes job type, work group, affiliated unit and contact information. The information verification unit is connected to the ID card information collection unit and the face information collection unit. It is used to receive ID card information and face biometric information, verify the validity of the ID card information and detect the quality of the face photo, generate verification results, and transmit the ID card information and face biometric information to the data upload unit after the verification is passed. The data upload unit is connected to the ID card information collection unit, facial information collection unit, supplementary information entry unit, information verification unit, and the labor management terminal of the smart construction platform. It is used to receive ID card information, facial biometric information, supplementary information, and verification results, and integrate the ID card information, facial biometric information, supplementary information, and verification results into standardized digital archives, which are then uploaded to the labor personnel information database of the labor management terminal of the smart construction platform.

[0072] Specifically, in this embodiment, the laborer information entry module serves as the data entry point and basic data source for the entire personnel management system. It combines offline registration terminals with online platform entry, connecting to the labor management terminal of the smart construction platform. This module collects basic information, facial information, and job type information of laborers, establishes a standardized laborer information database based on this information, and uploads this database to the labor management terminal of the smart construction platform. This module is deployed at the construction site entry registration point, equipped with a dedicated integrated information collection machine (integrating an ID card reader, high-definition camera, touch screen, and other hardware devices). It also supports auxiliary entry via a mobile APP, meeting the rapid registration needs when laborers enter the site in batches. Specifically, the laborer information entry module includes an ID card information collection unit, a facial information collection unit, a supplementary information entry unit, an information verification unit, and a data upload unit.

[0073] The ID card information collection unit is used to read the ID card information of laborers and transmit the information to the information verification unit and the data upload unit respectively. In actual operation, newly arrived laborers place their second-generation resident ID cards on the ID card reader area of ​​the integrated information collection machine. The ID card information collection unit, through its built-in Ministry of Public Security certified dedicated ID card reader module, uses contactless radio frequency identification technology to quickly read the standardized basic information encrypted and stored in the ID card chip, including fields such as name, ID number, gender, ethnicity, date of birth, registered address, and document validity period. Compared with the traditional manual copying or manual input method, the automatic collection of ID card information completely avoids the problems of missed or incorrect information due to factors such as typographical errors by the data entry personnel, differences in laborers' accents, or illegible handwriting. After completing the information reading, the ID card information collection unit sends the original ID card information to the information verification unit for validity verification and the data upload unit for data encapsulation via the internal data bus.

[0074] The facial information acquisition unit is used to capture facial photos of workers on-site, generate facial biometric information, and transmit this information to both the information verification unit and the data upload unit. After the ID card information is read, the worker faces the high-definition camera equipped on the integrated information acquisition machine, and the facial information acquisition unit automatically starts the facial image acquisition process. This unit uses liveness detection technology to detect facial micro-expressions, blinking, slight head movements, and other biometric features to ensure that the captured image is a real, live face, not a photograph or video recording, effectively preventing identity fraud. During the acquisition process, the system provides real-time feedback on the facial detection frame and posture guidance prompts (such as "Please face the camera" and "Please blink slowly") on the display screen to assist workers in capturing standard facial images. After the acquired facial images undergo preprocessing algorithms for illumination normalization, posture correction, and quality enhancement, facial biometric information (including facial key point coordinates, feature vectors, and other digital feature data) is extracted. The facial information acquisition unit simultaneously transmits the generated facial biometric information to the information verification unit for quality inspection and the data upload unit for data integration.

[0075] The supplementary information entry unit is used to collect supplementary information from laborers and transmit it to the data upload unit. After the ID card information and facial information are collected, the touch screen of the integrated information collection machine automatically jumps to the supplementary information entry interface, where on-site managers or the laborers themselves enter various supplementary information. Specifically, supplementary information includes job type (such as steelworker, concrete worker, welder, carpenter, plumber, etc.), work group (name or number of the work group), affiliated unit (name of the labor subcontracting company or construction team), contact information (personal mobile phone number), and other optional extended information such as emergency contact person and telephone number, entry date, special job certificate number, medical examination certificate number, etc. The supplementary information entry unit provides various interactive controls such as drop-down selection, text input, and date selection. Among them, the job type and work group fields support quick selection of preset options, reducing entry time and input errors. For the entry of a batch of personnel, the supplementary information entry unit also supports the batch import function of templates. Managers can organize the supplementary information of multiple people on the computer according to the standard template format provided by the system and then import it with one click, which greatly improves the efficiency of information entry. After the supplementary information entry unit completes the entry, it packages all the supplementary information data and transmits it to the data upload unit.

[0076] The information verification unit is connected to both the ID card information collection unit and the face information collection unit. It receives ID card information from the ID card information collection unit and facial biometric information from the face information collection unit, verifies the validity of the ID card information, checks the quality of the facial photograph, generates a verification result, and transmits the ID card information and facial biometric information to the data upload unit after successful verification. In the specific information verification process, the information verification unit first performs a triple validity verification on the ID card information: the first verification is chip anti-counterfeiting verification, which reads the encrypted signature information in the ID card chip and compares it with the Ministry of Public Security's root certificate to confirm that the ID card is a legal and valid document and not a counterfeit; the second verification is timeliness verification, checking the validity period of the ID card to ensure that the document is within its validity period; the third verification is uniqueness verification, comparing the read ID card number with existing records in the labor personnel information database. If the ID card number already exists in the database, it prompts "This person has already been registered," preventing duplicate entry of the same person. After verifying the validity of the ID card information, the information verification unit further performs quality checks on the facial biometric information. These checks include whether the facial image resolution meets recognition requirements, whether the facial pose is within the allowable angle range (yaw, pitch, and roll angles all within ±15°), whether the lighting is uniform without obvious shadows, and whether key facial features are clearly identifiable. When all the above verification and testing items pass, the information verification unit generates a "verification passed" result and transmits the ID card information and facial biometric information to the data upload unit. If any verification item fails, the information verification unit generates a specific error message (such as "ID card expired," "facial image blurry, please retake the photo," etc.) and displays it on the screen to guide the operator to re-collect the corresponding information until the verification passes.

[0077] The data upload unit connects to the ID card information collection unit, facial information collection unit, supplementary information entry unit, information verification unit, and the labor management terminal of the smart construction platform. It receives ID card information, facial biometric information, supplementary information, and verification results, and integrates all this information into a standardized digital file, which is then uploaded to the labor personnel information database of the smart construction platform's labor management terminal. Specifically, after receiving a verification pass signal from the information verification unit, the data upload unit uses the ID card number as the unique identifier for the laborer. It then structurally integrates the basic personnel information read by the ID card information collection unit, the facial biometric information generated by the facial information collection unit, and the job type, work group, affiliated unit, and contact information collected by the supplementary information entry unit. Following the system's predefined data dictionary and field mapping rules, it generates a complete standardized digital personnel file record. This file record contains all the laborer's registration information, with a unified data format and complete fields, meeting the data retrieval needs of subsequent stages such as identity verification, attendance statistics, employment matching, and file management. After completing the file integration, the data upload unit uploads the digitized files in real time to the labor personnel information database of the smart construction platform's labor management terminal via an encrypted transmission channel. Upon successful upload, the platform automatically generates a searchable information entry and a personnel QR code for the worker. On-site management personnel can quickly access the worker's complete information by scanning the QR code through the platform or a mobile app. For registered personnel, the data upload unit also supports information modification, supplementation, and cancellation functions. When information such as a worker's job type, work group, and contact information changes, management personnel submit modifications through the update interface of the information entry module, and the data upload unit synchronously updates the modified information to the platform's labor personnel information database. When a worker leaves the site, management personnel mark their status as "departed" through a cancellation operation, but the original registration information is still retained in the database as historical records for future reference. Through this solution, the labor personnel information entry module achieves standardized, digitized collection and automatic uploading of labor personnel entry information, eliminating information omissions, errors, and identity fraud from the source, and establishing a complete and reliable data foundation for subsequent identity verification, attendance management, and workforce allocation.

[0078] Please see Figure 2 , Figure 2 This is a flowchart illustrating a personnel management method provided in an embodiment of this application. Figure 2 As shown, it includes the following steps: Step S201: The intelligent gate identification module performs dual identification and verification of the face and ID card of the workers entering and leaving the gate. After the verification is successful, it generates a gate opening control signal and triggers the attendance record.

[0079] Specifically, in this embodiment, the intelligent gate's identity recognition module is deployed at the main entrance and exit of the construction site. When workers need to enter or leave the site, they first place their second-generation resident ID card in the sensing area of ​​the ID card recognition terminal. The ID card recognition terminal reads the standardized basic information stored in the ID card chip, such as name, ID number, and place of residence, using contactless radio frequency identification technology. Simultaneously, the workers face the high-definition camera integrated into the face recognition gate. The face recognition gate uses dynamic face recognition technology and a liveness detection algorithm to collect the workers' frontal facial images and perform liveness detection, effectively preventing forgery attacks using photos, videos, or masks. After the ID card information and facial image are collected, they are simultaneously transmitted to the identity verification unit. The identity verification unit performs a dual verification process: the first verification is the validity of the ID card information, which involves precisely matching the read ID card chip information with records in the worker information database to verify whether the ID card has been registered and filed in the system; the second verification is the matching of the face and the ID card, which uses a deep learning algorithm to compare the collected facial image with the pre-stored facial biometric templates in the worker information database on a 1:1 basis, achieving a facial recognition accuracy of 99.9%. The identity verification unit only determines that the verification is successful when the ID card information has a corresponding valid record in the database and the facial image collected on-site matches the facial features registered in the system. After successful verification, the identity verification unit immediately generates an opening control signal, which is output to the drive control board of the facial recognition gate to execute the gate opening action, and simultaneously transmitted to the automatic attendance recording module to trigger the recording of the worker's entry and exit time. If verification fails, the gate remains closed, and the reason for the failure is communicated to the workers via voice announcement and screen display (e.g., "Unregistered Personnel," "Face Matching Failed," etc.). Simultaneously, an on-site audible and visual alarm is activated to alert on-site management personnel for immediate investigation. For personnel already on the system's blacklist, the identity verification unit directly refuses passage and triggers a background alert notification to prevent unauthorized or dismissed personnel from re-entering the construction site, effectively ensuring worker safety.

[0080] Step S202: When the automatic attendance recording module receives the gate opening control signal, it automatically records the entry and exit time and generates a real-time attendance record containing personnel identity information and entry and exit time.

[0081] Specifically, in this embodiment, the automatic attendance recording module maintains a real-time data connection with the intelligent gate identity recognition module. When the entry / exit time recording unit receives the gate opening control signal output by the identity verification unit, this signal simultaneously carries the unique identification information of the worker (such as personnel ID or ID card number). The entry / exit time recording unit immediately obtains the current timestamp (accurate to the second) and date information from the system clock, and generates an original entry / exit record using the worker's unique identification information as an index. This record contains complete fields such as the worker's name, unique identification information, entry / exit direction (entry or exit), entry / exit date, and entry / exit time. All original entry / exit records are stored in the system database in chronological order, forming a complete entry / exit time trajectory for each worker.

[0082] During the daily attendance data processing cycle, the attendance duration calculation unit retrieves all entry and exit records for each worker from the entry and exit time recording unit. These records are then arranged chronologically, and attendance duration is calculated based on the worker's unique identifier and date. Specifically, the worker's latest exit time is subtracted from their earliest entry time to obtain the total on-duty hours for the day. This is then deducted from pre-set non-working periods such as lunch breaks and mealtimes (which can be flexibly configured according to the actual work schedule at the construction site). For cases with multiple entries and exits on the same day, the on-duty hours are calculated segment by segment using adjacent entries and exits, and then summed to obtain the total attendance duration for the day. The attendance duration calculation unit then associates the calculated attendance duration with the corresponding worker information and date information to generate a complete attendance record containing the attendance duration.

[0083] After receiving the original entry / exit records and attendance records including attendance duration, the classification and statistics unit initiates a multi-dimensional classification and statistics process. Specifically, the classification and statistics unit has a built-in multi-dimensional classification engine. First, based on the worker's name as the basic dimension, it aggregates the entry / exit records and attendance records of the same person on different dates to form a complete individual attendance ledger. On this basis, it performs a second aggregation according to the worker's job information, counting the number of workers and attendance duration for all workers in each job category on that day. Further, it performs a third aggregation according to the work group and affiliated unit dimensions, forming work group-level and unit-level attendance statistics summaries. The final generated classification and statistics results cover attendance data at four levels: individual, job category, work group, and unit. This includes standardized data such as the worker's name, job category, work group, affiliated unit, entry time, exit time, attendance duration, total number of workers in each job category, and total number of workers in each work group on that day. After the classification and statistical units complete the categorization and summarization, the results are uploaded to the labor management terminal of the smart construction platform for real-time viewing by managers, and also uploaded to the IoT employment plan linkage module for subsequent attendance rate calculation and employment comparison. The entire process is automated, eliminating fraudulent activities such as proxy clocking and false attendance reports at the source, ensuring 100% accuracy of attendance data.

[0084] Step S203: The IoT employment plan linkage module compares the employment plan with the real-time attendance records, calculates the actual number of employees and the planned number of employees for each job type and / or each work group, and obtains the attendance rate for each job type and / or each work group.

[0085] Specifically, in this embodiment, the IoT employment plan linkage module serves as the intelligent hub connecting attendance data and employment management decisions, and incorporates an employment linkage algorithm. The employment plan acquisition subunit retrieves the employment plans for each job type and work group pre-entered by management personnel from the labor management terminal of the smart construction platform according to a preset synchronization cycle. Each job type's employment plan includes the planned number of employees, job requirements (such as skill level, special job certification requirements, etc.), and working hours (such as morning shift, afternoon shift, or full-day shift). After formatting and validating the acquired employment plans, the employment plan acquisition subunit categorizes and stores them according to job type and work group dimensions, forming a standardized set of plan data.

[0086] After receiving the classification statistics results from the classification statistics unit of the automatic attendance record module, the actual attendance statistics subunit further performs actual attendance statistics by job type and work group. During the statistics process, the actual attendance statistics subunit determines attendance based on the following criteria: the worker has a valid entry record for the day and their attendance duration exceeds the system's minimum valid attendance duration threshold (e.g., greater than 30 minutes), thus filtering out invalid records caused by temporary entry / exit, accidental equipment activation, etc. After the statistics are completed, the actual attendance statistics subunit generates actual attendance statistics results containing the actual attendance of each job type and work group for the day.

[0087] The data comparison subunit uses job type and work group as matching keys to pair the actual attendance of each job type and work group in the actual attendance statistics with the planned attendance of the corresponding job type and work group in the employment plan, calculating the difference between the actual attendance and the planned attendance for each item. When the actual attendance is greater than the planned attendance, it indicates that there is a redundancy in personnel; when the actual attendance is less than the planned attendance, it indicates that there is a labor shortage. The data comparison subunit integrates all the difference data generated by the item-by-item comparison with the corresponding job type and work group information to generate a structured comparison result, which is then transmitted to the attendance rate calculation subunit.

[0088] The attendance rate calculation subunit calculates the attendance rate for each job type and work group based on the ratio of actual attendance to planned attendance in the comparison results. The calculation formula is: Attendance Rate = Actual Attendance ÷ Planned Attendance × 100%. In the special case where the planned attendance is zero, the attendance rate calculation subunit marks the attendance rate for that job type as invalid. The attendance rate calculation subunit further integrates a labor linkage algorithm for intelligent analysis of attendance rates. When the planned working hours for a job type span multiple shifts, the algorithm automatically calculates the attendance rate for each shift. When multiple job types share the same work group, the algorithm performs a weighted attendance rate calculation based on job type weights, thus obtaining an attendance rate analysis result that better reflects actual construction needs. The attendance rate calculation subunit transmits the final calculated attendance rates for each job type and work group to the labor shortage early warning module to trigger labor shortage early warning judgment, and simultaneously transmits them to the labor management terminal of the smart construction platform for real-time viewing by management personnel.

[0089] Step S204: The labor shortage early warning module compares the attendance rate with a preset threshold, and generates and pushes an early warning signal when the attendance rate is lower than the preset threshold.

[0090] Specifically, in this embodiment, the labor shortage early warning module intelligently determines the labor shortage based on the attendance rate data output by the IoT labor planning linkage module and the attendance rate early warning threshold preset by the management personnel, automatically triggering a tiered early warning when labor is in short supply. Specifically, management personnel pre-set differentiated attendance rate early warning thresholds for different job types and work groups through the labor management terminal of the smart construction platform. For example, a stricter early warning threshold is set for key job types (such as steelworkers and concrete workers) (an early warning is triggered when the attendance rate is below 85%), while a relatively lenient threshold is set for general auxiliary job types (an early warning is triggered when the attendance rate is below 70%). The threshold setting subunit establishes a threshold index table based on job type and work group codes for the various threshold parameters set by the management personnel and synchronizes it to the early warning judgment subunit in real time.

[0091] The early warning determination subunit uses job type and work group as matching dimensions, comparing each received attendance rate data set with the corresponding early warning threshold value by value. When the attendance rate is greater than or equal to the early warning threshold, the determination result is a normal state; when the attendance rate is lower than the early warning threshold, the determination result is an absence state. The early warning determination subunit has built-in continuous determination logic, triggering an early warning only when the attendance rate is lower than the preset threshold for two consecutive statistical periods, in order to avoid false alarms caused by instantaneous data fluctuations (such as temporary entry and exit of workers, brief gate malfunctions, etc.). After each comparison and determination is completed, the early warning determination subunit transmits the determination result to the early warning information generation subunit in real time.

[0092] Upon receiving the assessment result of the labor shortage status, the early warning information generation subunit immediately initiates the early warning information assembly process: extracting the job type and work group name that triggered the early warning from the assessment result, and calculating the specific number of missing workers by calculating the difference between the planned attendance and the actual attendance. Based on this, the early warning information generation subunit generates structured early warning information according to a preset template, which includes at least the early warning trigger time, early warning level (yellow or red, automatically graded according to the degree to which the actual attendance rate deviates from the threshold), job type with labor shortage, number of missing workers, work group, current actual attendance rate, planned attendance rate, and suggested number of workers to be redeployed.

[0093] The early warning push subunit incorporates a multi-channel message distribution engine. It queries the system's personnel database for the list of project management personnel and team leaders corresponding to the job types and work groups that triggered the warning, and simultaneously sends the warning information via SMS, APP message push, WeChat mini-program push, and platform in-site message push. For online APP and WeChat terminals, real-time message push ensures millisecond-level delivery of warning information; for offline terminals, it automatically switches to SMS push as a supplement to avoid delays or loss of warning information due to network issues. In addition to core warning data, the pushed warning information also includes quick operation links. Managers can click to access the labor allocation interface of the smart construction platform's labor management terminal to view detailed attendance comparison data and historical trend charts, and initiate personnel allocation commands online. The early warning push subunit also has a delivery confirmation mechanism. For warning information that has not been confirmed within a set time after being pushed, it is automatically escalated to the next higher level of management and the push frequency is increased to ensure that warning information is not missed or delayed.

[0094] Step S205: The labor management terminal of the smart construction platform uniformly manages and displays real-time attendance records, employment plans, and early warning information corresponding to early warning signals.

[0095] Specifically, in this embodiment, the labor management terminal of the smart construction platform serves as the core operating terminal and data display center of the entire personnel management system. It is deployed using a B / S architecture, allowing administrators to access and operate it via a web browser on a computer or a mobile app. The platform is connected to the automatic attendance recording module, the IoT labor planning linkage module, and the labor shortage early warning module, receiving real-time attendance records, categorized statistical results, labor plans, attendance rate data, and early warning information from each module, and managing and displaying them uniformly.

[0096] In terms of personnel information management, managers can accurately query and filter labor information using multiple dimensions such as personnel name, ID number, job type, work group, and affiliated unit. They can also modify, supplement, and cancel information, with all modifications logged. Regarding attendance data management, the platform continuously receives categorized statistical results from the automatic attendance record module, displaying key indicators such as the total number of personnel currently on site, the real-time number of personnel in each job type, attendance rate progress bars for each work group, and abnormal attendance alerts in a real-time attendance overview dashboard. Managers can drill down to view detailed attendance records by clicking on specific job types or work group names and manually correct for special circumstances such as leave and overtime. For labor plan management, managers input and adjust labor plans for each job type and work group on the platform according to the construction schedule, with adjustments synchronized in real-time to the IoT labor plan linkage module. In terms of data statistical analysis, the platform has a built-in data analysis engine and visualization chart components, generating labor employment statistical reports by time dimensions such as daily, weekly, monthly, and quarterly. It uses bar charts, trend line charts, and other formats to compare and display the planned attendance numbers with the actual attendance numbers and the trends in attendance rates. It also incorporates the time utilization rate indicator to comprehensively evaluate the labor efficiency and productivity of each job type and work group, generating actionable analytical conclusions. Regarding labor file management, the platform integrates personnel information, attendance records, employment plans, and analysis results into standardized digital file files for each worker. It adopts an tamper-proof digital storage scheme, and all file data is timestamped and includes the operator's information upon generation. It supports rapid retrieval based on multi-dimensional conditions and one-click printing, providing accurate evidence for labor wage calculation and labor dispute resolution. Through these steps, this method achieves intelligent and digital management of the entire process of "registration, identification, attendance, employment, and file management" for workers, streamlining all aspects of labor employment management, improving management efficiency, and reducing manual management costs.

[0097] This application provides a personnel management system, including: an intelligent gate identity recognition module, an automatic attendance recording module, an IoT labor plan linkage module, a labor shortage early warning module, and a smart construction platform labor management terminal; the intelligent gate identity recognition module is used to perform dual identity recognition and verification of workers entering and leaving the site using both facial recognition and ID cards, and controls the gate to open after verification; the automatic attendance recording module is connected to the intelligent gate identity recognition module and is used to automatically record the entry and exit time of workers when they enter and leave the site, generating real-time attendance records; the IoT labor plan linkage module is connected to both the automatic attendance recording module and the smart construction platform labor management terminal, and is used to compare the labor plan with the real-time attendance records to calculate the attendance rate of each job type and / or each work group; the labor shortage early warning module is connected to the IoT labor plan linkage module and is used to generate an early warning signal when the attendance rate is lower than a preset threshold; the smart construction platform labor management terminal is connected to both the automatic attendance recording module and the labor shortage early warning module, and is used to manage and display the attendance information corresponding to the attendance records, the labor plan, and the early warning information corresponding to the early warning signals. This application establishes a standardized digital labor file system, realizing closed-loop management of the entire chain of labor personnel from information registration, identity recognition, automatic attendance, employment linkage to labor shortage early warning. It connects all aspects of labor employment management, improves management efficiency, reduces manual management costs, and comprehensively enhances the standardization, digitalization and refinement of labor employment management, providing a complete, efficient and reliable intelligent solution for labor employment management on construction sites.

[0098] This application Figure 3 A schematic diagram of a computer device is provided. (Example) Figure 3 As shown, the computer device 3 in this embodiment includes a processor 301, a memory 302, and a computer program 303 stored in the memory 302 and executable on the processor 301. When the processor 301 executes the computer program 303, it implements the steps described in the various personnel management method embodiments above, for example... Figure 2 Steps 201 to 205 are shown. Alternatively, when processor 301 executes computer program 303, it implements the functions of each module / unit in the above-described personnel management system embodiments.

[0099] This application also provides a readable storage medium storing a computer program, which, when executed by a processor, is used to implement the personnel management methods provided in the various embodiments described above.

[0100] The readable storage medium can be a computer storage medium or a communication medium. A communication medium includes any medium that facilitates the transfer of computer programs from one location to another. A computer storage medium can be any available medium accessible to a general-purpose or special-purpose computer. For example, a readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application-Specific Integrated Circuit (ASIC). Alternatively, the ASIC can be located in a user equipment. Of course, the processor and the readable storage medium can also exist as discrete components in a communication device. The readable storage medium can be a read-only memory (ROM), random access memory (RAM), CD-ROM, magnetic tape, floppy disk, and optical data storage device, etc.

[0101] This application also provides a program product including executable instructions stored in a readable storage medium. At least one processor of the device can read the executable instructions from the readable storage medium, and executing the executable instructions causes the device to implement the personnel management methods provided in the various embodiments described above.

[0102] In the embodiments of the above-described device, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this application can be directly manifested as being executed by a hardware processor, or executed by a combination of hardware and software modules within the processor.

[0103] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.

Claims

1. A personnel management system, characterized in that, include: Intelligent gate identity recognition module, automatic attendance record module, IoT employment plan linkage module, labor shortage early warning module, and smart construction platform labor management terminal; The intelligent gate identification module is used to perform dual identification and verification of the face and ID card of the workers entering and leaving the site, and controls the gate to open after the verification is successful. The automatic attendance recording module is connected to the intelligent gate identity recognition module and is used to automatically record the entry and exit time of workers and generate real-time attendance records. The IoT employment plan linkage module is connected to the automatic attendance record module and the labor management terminal of the smart construction platform, respectively, and is used to compare the employment plan with the real-time attendance record to calculate the attendance rate of each type of work and / or each work group. The labor shortage early warning module is connected to the IoT employment plan linkage module and is used to generate an early warning signal when the attendance rate is lower than a preset threshold. The labor management terminal of the smart construction platform is connected to the automatic attendance record module and the labor shortage early warning module, respectively, and is used to manage and display the attendance information corresponding to the attendance record, the employment plan and the early warning information corresponding to the early warning signal.

2. The personnel management system as described in claim 1, characterized in that, The intelligent gate identification module includes: Facial recognition gates, ID card recognition terminals, and identity verification units; The facial recognition gate is connected to the identity verification unit and is used to collect facial images of workers and transmit the facial images to the identity verification unit. The ID card recognition terminal is connected to the identity verification unit and is used to read the chip information of the worker's ID card and transmit the ID card information to the identity verification unit. The identity verification unit is connected to the face recognition gate and the ID card recognition terminal. It is used to receive the face image and the ID card information, compare and verify the face image and the ID card information with the data in the labor personnel information database, and generate a gate opening control signal after the verification is passed and output it to the face recognition gate and the automatic attendance record module respectively.

3. The personnel management system as described in claim 1, characterized in that, The automatic attendance recording module includes: The system includes a unit for recording entry and exit times, a unit for calculating attendance duration, and a unit for classifying and statistically analyzing data. The entry and exit time recording unit is connected to the intelligent gate identification module and is used to record the entry and exit time and date of the corresponding workers when it receives the gate opening control signal output by the intelligent gate identification module, and generate the original entry and exit record. The attendance duration calculation unit is connected to the entry and exit time recording unit and is used to receive the original entry and exit records, calculate the attendance duration for the day based on the entry and exit times of the same worker in the original entry and exit records, and generate an attendance record containing the attendance duration. The classification and statistics unit is connected to the entry and exit time recording unit, the attendance duration calculation unit, the smart construction platform labor management terminal, and the IoT employment plan linkage module. It is used to receive the original entry and exit records and the attendance records, classify and summarize the original entry and exit records and the attendance records according to personnel name, job type, work group and / or affiliated unit, generate classification and statistics results, and upload the classification and statistics results to the smart construction platform labor management terminal and the IoT employment plan linkage module respectively.

4. The personnel management system as described in claim 1, characterized in that, The IoT employment planning linkage module includes: Sub-units for obtaining employment plans, statistics of actual attendance, data comparison, and calculation of attendance rate; The employment plan acquisition subunit is connected to the labor management terminal of the smart construction platform and is used to acquire the employment plans for each type of work and / or each work group entered by the management personnel. The employment plan includes the planned number of employees, job requirements and working hours. The actual attendance statistics subunit is connected to the automatic attendance record module and is used to receive the classification statistics results output by the automatic attendance record module, and to count the actual attendance of the day according to the classification statistics results by job type and / or work group, and generate actual attendance statistics results. The data comparison subunit is connected to the employment plan acquisition subunit and the actual attendance statistics subunit. It is used to receive the employment plan and the actual attendance statistics results, and compare the actual attendance of each job type and / or each work group with the planned attendance based on the employment plan and the actual attendance statistics results, calculate the difference between the actual attendance and the planned attendance, and generate the comparison results. The attendance rate calculation subunit is connected to the data comparison subunit and the labor shortage early warning module. It is used to receive the comparison result, calculate the attendance rate of each job type and / or each shift based on the ratio of the actual number of employees to the planned number of employees in the comparison result, and transmit the attendance rate to the labor shortage early warning module.

5. The personnel management system as described in claim 1, characterized in that, The labor shortage early warning module includes: The system includes a threshold setting subunit, an early warning determination subunit, an early warning information generation subunit, and an early warning push subunit. The threshold setting subunit is connected to the labor management terminal of the smart construction platform and is used to obtain the attendance rate warning thresholds set by the management personnel for each type of work and / or each work group, and transmit the attendance rate warning thresholds to the warning judgment subunit. The early warning determination subunit is connected to the threshold setting subunit and the IoT employment plan linkage module. It is used to receive the attendance rate early warning threshold and the attendance rate output by the IoT employment plan linkage module, compare the attendance rate with the corresponding attendance rate early warning threshold, and generate a determination result. The warning information generation subunit is connected to the warning determination subunit and is used to receive the determination result. When the determination result is that the attendance rate is lower than the attendance rate warning threshold, the unit determines that a labor shortage warning is triggered and generates warning information including the types of jobs in short supply, the number of workers in short supply, and / or the work group to which the workers belong. The early warning push subunit is connected to the early warning information generation subunit and is used to receive the early warning information and push the early warning information to the terminal devices of project management personnel and / or team leaders.

6. The personnel management system as described in claim 3, characterized in that, The labor management terminal of the smart construction platform includes: The system includes a personnel information management unit, an attendance data management unit, a workforce planning management unit, a data statistical analysis unit, and a labor file management unit. The personnel information management unit is used to view, modify, query, and classify personnel information in the labor personnel information database, and generate personnel information management results; The attendance data management unit is connected to the automatic attendance record module and is used to receive and display the classification statistics results output by the automatic attendance record module. The classification statistics results include at least attendance records, attendance duration, and attendance rate. The employment plan management unit is connected to the IoT employment plan linkage module and is used to input and adjust the employment plan, and synchronize the adjusted employment plan to the IoT employment plan linkage module. The data statistical analysis unit is connected to the attendance data management unit and is used to receive the classification statistical results, generate labor employment statistical reports by time, job type and / or work group, analyze the labor employment statistical reports, and generate analysis results. The labor file management unit is connected to the personnel information management unit, the attendance data management unit, the employment plan management unit, and the data statistical analysis unit. It is used to receive the personnel information management results, the classification statistical results, the adjusted employment plan, and the analysis results, and to integrate the personnel information management results, the classification statistical results, the adjusted employment plan, and the analysis results into standardized digital files and store them.

7. The personnel management system as described in claim 1, characterized in that, Also includes: The labor personnel information entry module is connected to the labor management terminal of the smart construction platform. It is used to collect the basic information, facial information and job information of the labor personnel, establish a standardized labor personnel information database based on the basic information, facial information and job information of the labor personnel, and upload the standardized labor personnel information database to the labor management terminal of the smart construction platform.

8. The personnel management system as described in claim 7, characterized in that, The labor personnel information entry module includes: The system includes an ID card information collection unit, a facial information collection unit, a supplementary information entry unit, an information verification unit, and a data upload unit. The ID card information collection unit is used to read the ID card information of the workers and transmit the ID card information to the information verification unit and the data upload unit respectively. The facial information acquisition unit is used to take photos of the workers' faces on site, generate facial biometric information, and transmit the facial biometric information to the information verification unit and the data upload unit respectively. The supplementary information entry unit is used to collect supplementary information of laborers and transmit the supplementary information to the data upload unit. The supplementary information includes job type, work group, affiliated unit and contact information. The information verification unit is connected to the ID card information collection unit and the face information collection unit. It is used to receive the ID card information and the face biometric information, verify the validity of the ID card information and detect the quality of the face photo, generate a verification result, and transmit the ID card information and the face biometric information to the data upload unit after the verification is passed. The data uploading unit is connected to the ID card information collection unit, the facial information collection unit, the supplementary information input unit, the information verification unit, and the labor management terminal of the smart construction platform. It is used to receive the ID card information, the facial biometric information, the supplementary information, and the verification result, and integrate the ID card information, facial biometric information, supplementary information, and verification result into a standardized digital file, which is then uploaded to the labor personnel information database of the labor management terminal of the smart construction platform.

9. A personnel management method, characterized in that, include: The intelligent gate identification module performs dual identification and verification of the face and ID card of the workers entering and leaving the gate. After the verification is successful, it generates a gate opening control signal and triggers the attendance record. When the automatic attendance recording module receives the gate opening control signal, it automatically records the entry and exit time and generates a real-time attendance record that includes personnel identity information and entry and exit time. The IoT employment plan linkage module compares the employment plan with the real-time attendance records, calculates the actual number of employees and the planned number of employees for each job and / or each work group, and obtains the attendance rate for each job and / or each work group. The labor shortage early warning module compares the attendance rate with a preset threshold, and generates and pushes an early warning signal when the attendance rate is lower than the preset threshold. The intelligent construction platform's labor management terminal provides unified management and display of the real-time attendance records, the employment plan, and the early warning information corresponding to the early warning signals.

10. A computer device, characterized in that, Includes a memory, and one or more processors communicatively connected to the memory; The memory stores instructions that can be executed by the one or more processors to enable the one or more processors to implement the personnel management method as described in claim 9.

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