An enterprise attendance management system

Abstract

The invention discloses an enterprise attendance management system, which relates to the technical field of attendance management. The enterprise attendance management system comprises an employee punching-in terminal: a mobile terminal for all employees to punch in, which is provided with a mobile terminal attendance app and is responsible for providing positioning data, fingerprint recognition data, facial recognition data and mobile terminal information data. The invention has the advantages of: comparing with the employee's previous punching-in data, comprehensively considering the number of employee punching-in failures, the account password input time, the number of facial and fingerprint biometric recognition times and the number of errors, comprehensively analyzing the current punching-in data and the previous punching-in data, and comprehensively analyzing the current and previous punching-in data through a risk judgment module to judge whether the employee's punching-in data of the day is abnormal. This analysis of the current punching-in situation and the detailed situation of the previous punching-in can greatly improve the supervision and management capabilities of the enterprise's employees' attendance and punching-in.

Description

Technical Field

[0001] The present invention relates to the technical field of attendance management, in particular to an enterprise attendance management system. Background Art

[0002] In today's highly competitive business environment, efficient operation and standardized management of enterprises are crucial. Attendance punching management, as an important part of enterprise human resource management, plays a key role in accurately recording employees' working hours, ensuring the normal production and operation order of enterprises, and reasonably calculating employees' salaries and benefits. With the rapid development of information technology, traditional manual sign-in and paper attendance records have gradually been replaced by digital and intelligent attendance punching management systems. With the popularization of Internet technology and mobile devices, attendance punching systems based on networks and mobile applications have emerged;

[0003] In terms of information collection, existing enterprise attendance management systems often rely on a single clock-in method, such as simple fingerprint clock-in or password clock-in. It is unable to comprehensively obtain employees' multi-dimensional clock-in information and it is difficult to comprehensively consider the employees' actual clock-in situation. Secondly, there is a lack of in-depth analysis and comparison of employees' clock-in data, and the current clock-in data cannot be comprehensively considered with past data, resulting in an inability to accurately judge whether the employee's clock-in is abnormal, making it impossible to timely discover potential cheating or misoperation behaviors, thereby affecting the normal operation and human resource management of the enterprise. To this end, we propose an enterprise attendance management system. Summary of the invention

[0004] The purpose of the present invention is to provide an enterprise attendance management system.

[0005] In order to solve the problems raised in the above background technology, the present invention provides the following technical solutions: an enterprise attendance management system, the enterprise attendance management system comprising:

[0006] Employee clock-in terminal: All employees use mobile terminals to clock in. They are equipped with a mobile terminal attendance app, which is responsible for providing location data, fingerprint recognition data, facial recognition data, and mobile terminal information data, and interacts with the attendance system in real time during the clock-in period.

[0007] Attendance system: used for unified attendance management of all employees of the enterprise, including: employee information storage module, login verification module, liveness verification module, location monitoring module, clock-in data recording module, data analysis module, risk judgment module and management module;

[0008] Employee information storage module: responsible for storing the personal information of all employees of the enterprise, providing basic data support for subsequent identity verification and data analysis;

[0009] Login verification module: responsible for determining the employee's identity based on the account and password transmitted by the employee's mobile terminal;

[0010] Liveness verification module: responsible for confirming employee identity through fingerprint verification and facial verification;

[0011] Positioning monitoring module: responsible for continuously acquiring the Beidou positioning data of the mobile terminal and monitoring its dynamic changes;

[0012] Punch card data recording module: responsible for recording the detailed data of employee punch cards;

[0013] Data analysis module: responsible for preprocessing employee punch-in data and analyzing and summarizing the preprocessed employee punch-in data;

[0014] Risk judgment module: responsible for judging the risk factor of employees' fake clocking in based on the data from the data analysis module;

[0015] Management module: responsible for making corresponding interventions based on the analysis results of the risk judgment module, providing a management window for the company's human resources management personnel, and enjoying system data editing and management permissions.

[0016] As a further solution of the present invention: the employee clock-in terminal is provided with a mobile terminal attendance app, and the mobile terminal attendance app includes a positioning data collection unit, a fingerprint recognition unit, a facial recognition unit and a terminal information collection unit. The mobile terminal attendance app needs to obtain authorization from the mobile terminal to obtain mobile terminal data through the positioning data collection unit, the fingerprint recognition unit, the facial recognition unit and the terminal information collection unit. The positioning data collection unit obtains geographic location information in real time with the help of the Beidou chip and positioning technology built into the mobile terminal. The fingerprint recognition unit can obtain fingerprint verification data of the fingerprint module of the mobile terminal, the facial recognition unit can obtain facial verification data of the facial recognition module of the mobile terminal, and the terminal information collection unit can obtain data of the mobile terminal. When the employee clock-in terminal starts the mobile terminal attendance app, it will interact with the attendance system in real time through the Internet.

[0017] As a further solution of the present invention: the employee information storage module includes an employee basic information storage unit and an employee attendance record storage unit. The employee basic information storage unit adopts relational database technology to store the basic information of the employee, including name, work number, attendance cycle, shift sequence, bound mobile terminal IMEI code, department, position and contact information. The employee attendance record storage unit stores the employee's historical attendance data, including the time point of each clock-in, the number of times the clock-in terminal is rebound, the time since the last change of the clock-in terminal, the clock-in operation duration, location, account password input time, number of incorrect password input times, clock-in method (fingerprint, facial recognition) and number of clock-in failures.

[0018] As a further solution of the present invention: the login verification module is provided with an account and password verification unit, and the account and password verification unit stores the account and password data of the employee. When the employee opens the mobile terminal attendance app in the employee clock-in terminal setting, the account and password will be entered in the mobile terminal attendance app. After the employee enters the exclusive account and password, the mobile terminal attendance app will encrypt the account and password using MD5 technology, and transmit the encrypted account and password to the account and password verification unit, and the account and password verification unit will decrypt the encrypted account and password. When the decrypted account and password match the account and password stored in the account and password verification unit, the account and password verification unit sends a message to the mobile terminal attendance app. When the decrypted account and password do not match the account and password stored in the account and password verification unit, the account and password verification unit sends a Instruction, the login verification module will transmit the account password input time and the number of incorrect password input times to the punch-in data recording module.

[0019] As a further solution of the present invention: the liveness verification module includes a fingerprint verification unit and a facial recognition verification unit, wherein the fingerprint verification unit and the facial recognition verification unit respectively store the employee's fingerprint data and facial data, and the mobile terminal attendance app receives the liveness verification module transmitted When the instruction is given, the mobile terminal attendance app will start one of the fingerprint recognition module and the facial recognition module, and transmit the recognition data to the liveness verification module. The fingerprint verification unit and the facial recognition verification unit will compare the received recognition data with the data stored in themselves. If the match is successful, the verification time data, the number of verification failures data and the verification method data will be transmitted to the punch-in data recording module. If the match is unsuccessful, it will be sent to the management module. instruction.

[0020] As a further solution of the present invention: the positioning monitoring module calls the Beidou positioning data of the mobile terminal in real time through the mobile terminal attendance app. During the period from when the employee starts the mobile terminal attendance app to when he / she successfully clocks in, the positioning monitoring module locates the position of the mobile terminal once every 0.5S. When it is detected that the positioning movement distance exceeds 6m, it is recorded as the number of movements plus 1. The positioning monitoring module transmits the movement number data from when the mobile terminal attendance app is started to when he / she successfully clocks in to the clock-in data recording module. If the positioning monitoring module detects that the positioning data is not within the clock-in range set by the management personnel, the positioning monitoring module sends a message to the management module. instruction.

[0021] In one embodiment of the present invention: the clock-in data recording module is capable of receiving data transmitted by the login verification module, the liveness verification module and the positioning monitoring module, and summarizing the employee clock-in data. The summarized data includes the employee's work number, account and password input time, number of incorrect password inputs, fingerprint / face verification time, number of fingerprint / face verification failures, verification method data and positioning movement number data. The clock-in data recording module transmits the employee's attendance summary data to the data analysis module.

[0022] In one embodiment of the present invention: the data analysis module is capable of receiving the attendance summary data of employees transmitted by the punch-in data recording module, the data analysis module will remove duplicate data, remove abnormal data and unify the data format, and transmit the processed data to the risk judgment module.

[0023] In one embodiment of the present invention, the risk judgment module can receive data transmitted by the employee information storage module and the data analysis module, and calculate the employee fake punch-in risk coefficient. The specific calculation formula of the employee fake punch-in risk coefficient is as follows: ;in: Indicates the risk factor of employees' fake clocking in. , and They represent the time value of employee account password input, fingerprint verification time value and face verification time value respectively. , and They represent the average time for the employee to input the account and password, the average time for fingerprint verification, and the average time for facial verification in the past. A, B, and C represent the coefficients of the account and password input time, fingerprint verification time, and facial verification time set by the administrator. D represents the number of times the employee has changed the bound device. Indicates the time between the employee inputting the account password and the last time the bound device was changed. , and Respectively represent the number of incorrect password inputs, fingerprint verification failures, and facial verification failures. , and They represent the average number of incorrect password inputs, fingerprint verification failures, and facial verification failures of the employee in the past.

[0024] The risk judgment module transmits the fake clock-in risk coefficient data of all employees to the result processing module. The fake clock-in risk coefficient of all employees is ,in, Indicates the number of employees who clock in.

[0025] As a further solution of the present invention: the management module includes an alert unit and a management and editing unit, and the alert unit can receive data transmitted by the risk judgment module and judge the risk range of the employee's fake clock-in risk coefficient K by a formula. The specific judgment formula is as follows:

[0026] when , the system does not make any intervention and regards the employee's clocking in as normal;

[0027] when , the system does not intervene directly, but the background will mark the employee. If the risk factor of the employee's fake clock-in for two consecutive working days is not less than When the alarm unit sends a "punch abnormality" window prompt to the mobile terminal attendance app, if there is still a fake punch-in risk factor of not less than 3 working days after the "punch abnormality" window prompt is issued If the risk factor of fake clocking in is less than 10% for seven consecutive working days, the warning unit will intervene in the investigation through the company's personnel management investigators. After that, the marking process is cancelled;

[0028] when When an employee is found to have a problem, the warning unit will directly stop the employee from clocking in on the mobile terminal attendance app, and will directly notify the company's human resources management investigators to intervene in the investigation;

[0029] When the warning unit receives , and When the instruction is given, the warning unit directly notifies the company's personnel management investigators to intervene in the investigation;

[0030] in: Thresholds for the risk factor of fake clock-in set for managers;

[0031] The management and editing unit has the highest control rights, including modifying and editing the data stored in the employee information storage module, the employee account and password data in the login verification module, the customer fingerprint and facial data in the liveness verification module, editing the A, B and C coefficients in the risk judgment module, and setting the false punch-in risk coefficient threshold in the warning unit;

[0032] The management module transmits the employee punch-in data to the employee information storage module for storage.

[0033] By adopting the above technical solution, compared with the prior art, the beneficial effects of the present invention are:

[0034] 1. The present invention obtains the employee's punch-in information through the employee information storage module, login verification module, liveness verification module and positioning monitoring module, including the input of the employee's account and password and the authorization of fingerprint and face, and compares it with the employee's previous punch-in data, comprehensively considers the number of employee punch-in failures, account and password input time, facial and fingerprint biometric identification times and errors, and comprehensively analyzes the current punch-in data and the previous punch-in data. Through the risk judgment module, the current and previous punch-in data are comprehensively analyzed to determine whether the employee's punch-in data of the day is abnormal. This analysis of the current punch-in situation and the detailed situation of the previous punch-in can greatly improve the supervision and management capabilities of the company's employees' attendance and punch-in;

[0035] 2. The present invention analyzes the clocking-in situations of different employees through the risk judgment module, and makes different types of intervention strategies according to the different clocking-in situations of employees. It is not like the traditional attendance management system that is "one size fits all" and directly intervenes the human resources management personnel when a little abnormality is found. Instead, it conducts a comprehensive analysis, marks and supervises the employees with minor abnormal clocking-in, keeps a close eye on the employees' clocking-in situation, and directly intervenes the employees with obvious abnormal clocking-in. It considers classification and time division, which can not only play a warning role, but also greatly reduce the burden of the company's management personnel, and reduce the company's personnel management costs in disguise;

[0036] 3. Through strict attendance management and risk monitoring, the present invention can encourage employees to comply with the company's attendance system and reduce the occurrence of violations such as lateness, early departure, and absenteeism. The warning unit in the system can issue prompts and warnings in time according to the employee's false clock-in risk coefficient, which has a restraining and warning effect on employees and enhances their self-discipline and sense of responsibility. At the same time, the system can accurately record employees' attendance history data, including clock-in method, time, number of failures, etc., providing strong evidence support for enterprises to deal with labor disputes and compliance issues. When facing possible labor arbitration or legal proceedings, enterprises can rely on these detailed attendance data to safeguard their legitimate rights and interests and ensure the normal operation and development of the enterprise. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 Schematic diagram of the system flow in an embodiment of the present invention. DETAILED DESCRIPTION

[0038] The specific embodiments of the present invention will be further described below in conjunction with the accompanying drawings. It should be noted that the description of these embodiments is used to help understand the present invention, but does not constitute a limitation of the present invention.

[0039] In addition, the technical features involved in the various embodiments of the present invention described below can be combined with each other as long as they do not conflict with each other.

[0040] Please refer to the attached Figure 1 The present invention provides an enterprise attendance management system, which includes:

[0041] Employee clock-in terminal: All employees use mobile terminals to clock in. They are equipped with a mobile terminal attendance app, which is responsible for providing location data, fingerprint recognition data, facial recognition data, and mobile terminal information data, and interacts with the attendance system in real time during the clock-in period.

[0042] Attendance system: used for unified attendance management of all employees of the enterprise, including: employee information storage module, login verification module, liveness verification module, location monitoring module, clock-in data recording module, data analysis module, risk judgment module and management module;

[0043] Employee information storage module: responsible for storing the personal information of all employees of the enterprise, providing basic data support for subsequent identity verification and data analysis;

[0044] Login verification module: responsible for determining the employee's identity based on the account and password transmitted by the employee's mobile terminal;

[0045] Liveness verification module: responsible for confirming employee identity through fingerprint verification and facial verification;

[0046] Positioning monitoring module: responsible for continuously acquiring the Beidou positioning data of the mobile terminal and monitoring its dynamic changes;

[0047] Punch card data recording module: responsible for recording the detailed data of employee punch cards;

[0048] Data analysis module: responsible for preprocessing employee punch-in data and analyzing and summarizing the preprocessed employee punch-in data;

[0049] Risk judgment module: responsible for judging the risk factor of employees' fake clocking in based on the data from the data analysis module;

[0050] Management module: responsible for making corresponding interventions based on the analysis results of the risk judgment module, providing a management window for the company's human resources management personnel, and enjoying system data editing and management permissions.

[0051] In one embodiment of the present invention: the employee clock-in terminal is provided with a mobile terminal attendance app, which includes a positioning data collection unit, a fingerprint recognition unit, a facial recognition unit and a terminal information collection unit. The mobile terminal attendance app obtains mobile terminal data through the positioning data collection unit, the fingerprint recognition unit, the facial recognition unit and the terminal information collection unit, which requires the authorization of the mobile terminal. The positioning data collection unit obtains geographic location information in real time with the help of the Beidou chip and positioning technology built into the mobile terminal. The fingerprint recognition unit can obtain fingerprint verification data of the fingerprint module of the mobile terminal, the facial recognition unit can obtain facial verification data of the facial recognition module of the mobile terminal, and the terminal information collection unit can obtain data of the mobile terminal. When the employee clock-in terminal starts the mobile terminal attendance app, it will interact with the attendance system in real time through the Internet.

[0052] In one embodiment of the present invention: the employee information storage module includes an employee basic information storage unit and an employee attendance record storage unit. The employee basic information storage unit adopts relational database technology to store the basic information of the employee, including name, work number, attendance cycle, shift sequence, bound mobile terminal IMEI code, department, position and contact information. The employee attendance record storage unit stores the employee's historical attendance data, including the time point of each clock-in, the number of times the clock-in terminal has been rebound, the time since the last change of the clock-in terminal, the clock-in operation duration, location, account password input time, number of incorrect password input times, clock-in method (fingerprint, facial recognition) and number of clock-in failures.

[0053] In one embodiment of the present invention: the login verification module is provided with an account and password verification unit, and the account and password verification unit stores the account and password data of the employee. When the employee opens the mobile terminal attendance app in the employee clock-in terminal setting, the employee enters the account and password in the mobile terminal attendance app. After the employee enters the exclusive account and password, the mobile terminal attendance app encrypts the account and password using MD5 technology, and transmits the encrypted account and password to the account and password verification unit. The account and password verification unit decrypts the encrypted account and password. When the decrypted account and password match the account and password stored in the account and password verification unit, the account and password verification unit sends a message to the mobile terminal attendance app. When the decrypted account and password do not match the account and password stored in the account and password verification unit, the account and password verification unit sends a Instruction, the login verification module will transmit the account password input time and the number of incorrect password input times to the punch-in data recording module.

[0054] In one embodiment of the present invention, the liveness verification module includes a fingerprint verification unit and a facial recognition verification unit, which store the employee's fingerprint data and facial data respectively. The mobile terminal attendance app receives the liveness verification module's transmitted liveness verification module. When the instruction is given, the mobile terminal attendance app will start one of the fingerprint recognition module and the facial recognition module, and transmit the recognition data to the liveness verification module. The fingerprint verification unit and the facial recognition verification unit will compare the received recognition data with the data stored in themselves. If the match is successful, the verification time data, the number of verification failures data and the verification method data will be transmitted to the punch-in data recording module. If the match is unsuccessful, it will be sent to the management module. instruction.

[0055] In one embodiment of the present invention: the positioning monitoring module calls the Beidou positioning data of the mobile terminal in real time through the mobile terminal attendance app. During the period from when the employee starts the mobile terminal attendance app to when he / she successfully clocks in, the positioning monitoring module locates the position of the mobile terminal once every 0.5 seconds. When it is detected that the positioning movement distance exceeds 6 meters, it is recorded as the number of movements plus 1. The positioning monitoring module transmits the movement number data from when the mobile terminal attendance app is started to when he / she successfully clocks in to the clock-in data recording module. If the positioning monitoring module detects that the positioning data is not within the clock-in range set by the management personnel, the positioning monitoring module sends a message to the management module. instruction.

[0056] In one embodiment of the present invention: the clock-in data recording module is capable of receiving data transmitted by the login verification module, the liveness verification module and the positioning monitoring module, and summarizing the employee clock-in data. The summarized data includes the employee's work number, account and password input time, number of incorrect password inputs, fingerprint / face verification time, number of fingerprint / face verification failures, verification method data and positioning movement number data. The clock-in data recording module transmits the employee's attendance summary data to the data analysis module.

[0057] In one embodiment of the present invention: the data analysis module is capable of receiving the attendance summary data of employees transmitted by the punch-in data recording module, the data analysis module will remove duplicate data, remove abnormal data and unify the data format, and transmit the processed data to the risk judgment module.

[0058] In one embodiment of the present invention, the risk judgment module can receive data transmitted by the employee information storage module and the data analysis module, and calculate the employee fake punch-in risk coefficient. The specific calculation formula of the employee fake punch-in risk coefficient is as follows: ;in: Indicates the risk factor of employees' fake clocking in. , and They represent the time value of employee account password input, fingerprint verification time value and face verification time value respectively. , and They represent the average time it takes for the employee to input his / her account and password, fingerprint verification, and face verification in the past. A, B, and C represent the average time it takes for the employee to input his / her account and password, fingerprint verification, and face verification in the past. D represents the number of times the employee has changed the bound device. Indicates the time between the employee inputting the account password and the last time the bound device was changed. , and Respectively represent the number of incorrect password inputs, fingerprint verification failures, and facial verification failures. , and They represent the average number of incorrect password inputs, fingerprint verification failures, and facial verification failures of the employee in the past.

[0059] The risk judgment module transmits the fake clock-in risk coefficient data of all employees to the result processing module. The fake clock-in risk coefficient of all employees is , where n represents the number of employees who clock in.

[0060] In one embodiment of the present invention, the management module includes an alert unit and a management and editing unit. The alert unit can receive data transmitted by the risk judgment module and judge the risk range of the employee's fake clock-in risk coefficient K by a formula. The specific judgment formula is as follows:

[0061] when , the system does not make any intervention and regards the employee's clocking in as normal;

[0062] when , the system does not intervene directly, but the background will mark the employee. If the risk factor of the employee's fake clock-in for two consecutive working days is not less than When the alarm unit sends a "punch abnormality" window prompt to the mobile terminal attendance app, if there is still a fake punch-in risk factor of not less than 3 working days after the "punch abnormality" window prompt is issued If the risk factor of fake clocking in is less than 10% for seven consecutive working days, the warning unit will intervene in the investigation through the company's personnel management investigators. After that, the marking process is cancelled;

[0063] when When an employee is found to have a problem, the warning unit will directly stop the employee from clocking in on the mobile terminal attendance app, and will directly notify the company's human resources management investigators to intervene in the investigation;

[0064] When the warning unit receives , and When the instruction is given, the warning unit directly notifies the company's personnel management investigators to intervene in the investigation;

[0065] in: Thresholds for the risk factor of fake clock-in set for managers;

[0066] The management and editing unit has the highest control rights, including modifying and editing the data stored in the employee information storage module, employee account and password data in the login verification module, customer fingerprint and facial data in the liveness verification module, editing the A, B and C coefficients in the risk judgment module, and setting the false clock-in risk coefficient threshold in the warning unit;

[0067] The management module will transfer the employee punch-in data to the employee information storage module for storage.

[0068] Example 1, please refer to the attached Figure 1 The liveness verification module is used to verify whether the employee's clocking in is a text operation. Some mobile terminals may only have one of the functions of face recognition and fingerprint recognition, so in actual application, you can choose one of the two. In actual production application, you can make reasonable adjustments based on actual conditions.

[0069] Example 2, please refer to the attached Figure 1 The mobile terminal information data of the employee's clock-in terminal includes the IMEI code of the mobile terminal. The employee information storage module can bind the IMEI code of the mobile terminal to the employee's work number one-to-one to avoid the situation where employees temporarily use their mobile terminals to clock in on behalf of others.

[0070] Example 3, please refer to the attached Figure 1 The positioning monitoring module can also use the GPS positioning system in the actual production application process. It depends on the accuracy of different positioning systems in the positioning punch-in area set by the enterprise. The positioning monitoring module refreshes the positioning data regularly to prevent employees from automatically punching in through the timed punch-in script.

[0071] Specifically, with the help of the employee information storage module, login verification module, liveness verification module and positioning monitoring module, comprehensive employee punch-in information is obtained, covering the input status of employee account and password, and fingerprint and facial authorization status. At the same time, the employee's current punch-in data is compared with the previous punch-in data, and the number of employee punch-in failures, account and password input time, facial and fingerprint biometric recognition times and errors are comprehensively considered. The current and previous punch-in data are comprehensively analyzed. The risk judgment module makes a comprehensive judgment based on the current and past punch-in data to determine whether there are any abnormalities in the employee's current punch-in data. In this way, the current punch-in status and the detailed punch-in situations of the past are analyzed, which can significantly enhance the supervision and management capabilities of the company's employee attendance and punch-in.

[0072] Specifically, the risk assessment module analyzes the clocking-in situations of different employees, and formulates different types of intervention strategies based on the different clocking-in situations of employees. It is not a "one-size-fits-all" approach like the traditional attendance management system, where human resources management personnel will intervene directly when any abnormality is found. Instead, a comprehensive analysis is conducted, and employees with minor clocking-in abnormalities are marked and supervised in the background, and their clocking-in situations are continuously monitored. Direct intervention is made for employees with clear clocking-in abnormalities. This classification and time-based consideration method not only serves as a warning, but also greatly reduces the workload of company managers, indirectly reducing the company's personnel management costs.

[0073] Specifically, through strict attendance management and risk monitoring, employees can be effectively encouraged to follow the company's attendance system and reduce the probability of violations such as lateness, early departure, and absenteeism. The warning unit in the system can issue prompts and warnings in a timely manner according to the employee's false clock-in risk coefficient, which has a restraining and warning effect on employees and enhances their self-discipline and sense of responsibility. At the same time, the system can accurately record employees' attendance history data, including clock-in method, time, number of failures, etc. When the company faces possible labor arbitration or legal proceedings, the company can rely on these detailed attendance data to safeguard its legitimate rights and interests and ensure the normal operation and development of the company.

[0074] Working principle:

[0075] First, the enterprise attendance management system collects positioning data, fingerprint recognition data, facial recognition data and mobile terminal information data through the mobile terminal attendance app of the employee's clock-in terminal, and interacts with the attendance system in real time. The employee information storage module in the attendance system stores employee personal information, the login verification module determines the identity based on the account and password entered by the employee, the liveness verification module determines the identity through fingerprint and facial verification clock-in, the positioning monitoring module continuously obtains the Beidou positioning data of the mobile terminal and monitors dynamic changes, the clock-in data recording module records the employee clock-in data in detail, the data analysis module pre-processes and analyzes it, and the risk judgment module calculates the employee's false clock-in risk coefficient based on the data analysis results. Then the management module makes corresponding interventions based on the risk judgment results, and transmits the employee clock-in data to the employee information storage module for storage. At this point, the entire workflow ends.

[0076] At the same time, the present application uses specific words to describe the embodiments of the present application. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of the present application. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of the present application can be appropriately combined.

[0077] Some aspects of the present application may be performed entirely by hardware, entirely by software (including firmware, resident software, microcode, etc.), or by a combination of hardware and software. The above hardware or software may be referred to as "data blocks", "modules", "engines", "units", "components" or "systems". The processor may be one or more application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DAPDs), programmable logic devices (PLDs), field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, or combinations thereof. In addition, various aspects of the present application may be represented as computer products located in one or more computer-readable media, which include computer-readable program codes. For example, computer-readable media may include, but are not limited to, magnetic storage devices (e.g., hard disks, floppy disks, tapes ...), optical disks (e.g., compact disks CDs, digital versatile disks DVDs ...), smart cards, and flash memory devices (e.g., cards, sticks, key drives ...).

[0078] A computer-readable medium may include a propagated data signal containing computer program code, such as in baseband or as part of a carrier wave. The propagated signal may have a variety of manifestations, including electromagnetic, optical, etc., or a suitable combination. A computer-readable medium may be any computer-readable medium other than a computer-readable storage medium, which may be connected to an instruction execution system, device or apparatus to communicate, propagate or transmit a program for use. The program code on the computer-readable medium may be propagated through any suitable medium, including radio, cable, fiber optic cable, radio frequency signal, or similar medium, or a combination of any of the above mediums.

[0079] Similarly, it should be noted that in order to simplify the description disclosed in this application, so as to help understand one or more embodiments of the invention, in the above description of the embodiments of the present application, sometimes multiple features are merged into one embodiment, drawings or descriptions thereof. However, this disclosure method does not mean that the features required by the object of the present application are more than the features mentioned in the claims. In fact, the features of the embodiment are less than all the features of the single embodiment disclosed above. In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "approximately", "approximately" or "substantially" in some examples. Unless otherwise specified, "approximately", "approximately" or "substantially" indicate that the number allows a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining the digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of the present application are approximate values, in specific embodiments, such numerical settings are as accurate as possible within the feasible range.

[0080] Although the present invention is disclosed as above in terms of preferred embodiments, it is not intended to limit the present invention. Any person skilled in the art may make possible changes and modifications without departing from the spirit and scope of the present invention. Therefore, any modification, equivalent change and modification made to the above embodiments according to the technical essence of the present invention without departing from the content of the technical solution of the present invention shall fall within the scope of protection defined by the claims of the present invention.

Claims

1. An enterprise attendance management system, characterized in that: The enterprise attendance management system includes: Employee clock-in terminal: A mobile terminal for all employees to clock in, equipped with a mobile terminal attendance app, responsible for providing location data, fingerprint recognition data, facial recognition data, and mobile terminal information data, and interacting with the attendance system in real time during clock-in; Attendance system: Used for unified attendance management of all employees in the enterprise, including: employee information storage module, login verification module, liveness verification module, location monitoring module, clock-in data recording module, data analysis module, risk judgment module, and management module; Employee information storage module: Responsible for storing the personal information of all employees in the enterprise, providing basic data support for subsequent identity verification and data analysis; Login verification module: Responsible for determining the identity of employees based on the account and password transmitted by the employee's mobile terminal; Liveness verification module: Responsible for determining the identity of employees through fingerprint verification clock-in and facial verification clock-in; Location monitoring module: Responsible for continuously obtaining the Beidou positioning data of the mobile terminal and monitoring its dynamic changes; Clock-in data recording module: Responsible for detailed recording of the detailed data of employees' clock-in; Data analysis module: Responsible for preprocessing the employees' clock-in data and analyzing and summarizing the preprocessed employees' clock-in data; Risk judgment module: Responsible for judging the risk coefficient of employees' false clock-in based on the data of the data analysis module; Management module: Responsible for making corresponding interventions according to the analysis results of the risk judgment module, providing a management window for enterprise human resource management personnel, and having system data editing and management permissions; The risk judgment module can receive the data transmitted by the employee information storage module and the data analysis module, and calculate the risk coefficient of employees' false clock-in. The specific calculation formula of the risk coefficient of employees' false clock-in is as follows: Where: K represents the risk factor of employee fake clocking in, T ap , T fv and T zv They represent the time value of employee account password input, fingerprint verification time value and face verification time value respectively. and They represent the average time for the employee to input the account and password, the average time for fingerprint verification, and the average time for facial verification in the past. A, B, and C represent the coefficients of the account and password input time, fingerprint verification time, and facial verification time set by the administrator. D represents the number of times the employee changes the bound device. t It indicates the time from the last time the employee input the account password to the last time the bound device was changed. α0, β0 and γ0 respectively indicate the number of incorrect password inputs, the number of fingerprint verification failures and the number of facial verification failures. α, β and γ respectively indicate the average number of incorrect password inputs, the average number of fingerprint verification failures and the average number of facial verification failures of the employee in the past. The risk judgment module transmits the fake punch-in risk coefficient data of all employees to the result processing module. The fake punch-in risk coefficient of all employees is M={K1, K2, ..., K n }, where n represents the number of employees punching in and out; The management module includes a warning unit and a management editing unit. The warning unit can receive the data transmitted by the risk judgment module and judge the risk range of the risk coefficient K of employees' false clock-in through the formula. The specific judgment formula is as follows: When K < K0, the system does not make any intervention, and it is regarded that the employee's clock-in is normal; When K = K0, the system does not directly make an intervention, but the background marks the employee. When the risk coefficient of false clock-in of an employee's clock-in for two consecutive working days is not less than K0, the warning unit sends a "clock-in abnormal" window prompt to the mobile terminal attendance app. When the situation where the risk coefficient of false clock-in is not less than K0 still occurs three working days after the "clock-in abnormal" window prompt is sent, the warning unit intervenes in the investigation through the company's human resource management investigators. When the risk coefficient of false clock-in of an employee's clock-in is less than K0 for seven consecutive working days, the marking process is cancelled; When K > K0, the warning unit directly stops the clock-in permission of the employee on the mobile terminal attendance app, and the warning unit directly notifies the company's human resource management investigators to intervene in the investigation; When the warning unit receives the Y0, X0, and S0 instructions, the warning unit directly notifies the company's human resource management investigators to intervene in the investigation; Where: K0 is the threshold of the risk coefficient of false clock-in set by the management personnel; The management and editing unit has the highest control rights, including modifying and editing the data stored in the employee information storage module, the employee account and password data in the login verification module, the customer fingerprint and facial data in the liveness verification module, editing the A, B and C coefficients in the risk judgment module, and setting the false punch-in risk coefficient threshold in the warning unit; The management module transmits the employee punch-in data to the employee information storage module for storage.

2. The enterprise attendance management system according to claim 1, characterized in that: The employee clock-in terminal is provided with a mobile terminal attendance app, which includes a positioning data collection unit, a fingerprint recognition unit, a facial recognition unit and a terminal information collection unit. The mobile terminal attendance app needs to obtain authorization from the mobile terminal to obtain mobile terminal data through the positioning data collection unit, the fingerprint recognition unit, the facial recognition unit and the terminal information collection unit. The positioning data collection unit obtains geographic location information in real time with the help of the Beidou chip and positioning technology built into the mobile terminal. The fingerprint recognition unit can obtain fingerprint verification data of the fingerprint module of the mobile terminal, the facial recognition unit can obtain facial verification data of the facial recognition module of the mobile terminal, and the terminal information collection unit can obtain data of the mobile terminal. When the employee clock-in terminal starts the mobile terminal attendance app, it will interact with the attendance system in real time through the Internet.

3. The enterprise attendance management system according to claim 1, characterized in that: The employee information storage module includes an employee basic information storage unit and an employee attendance record storage unit. The employee basic information storage unit adopts relational database technology to store the basic information of employees, including name, work number, attendance cycle, shift sequence, bound mobile terminal IMEI code, department, position and contact information. The employee attendance record storage unit stores the historical attendance data of employees, including the time point of each clock-in, the number of times the clock-in terminal has been rebound, the time since the last change of the clock-in terminal, the clock-in operation duration, location, account password input time, number of incorrect password input times, fingerprint, facial recognition and number of clock-in failures.

4. The enterprise attendance management system according to claim 1, characterized in that: The login verification module is provided with an account and password verification unit, and the account and password verification unit stores the employee's account and password data. When the employee opens the mobile terminal attendance app in the employee clock-in terminal setting, the employee will enter the account and password in the mobile terminal attendance app. After the employee enters the exclusive account and password, the mobile terminal attendance app will encrypt the account and password using MD5 technology, and transmit the encrypted account and password to the account and password verification unit. The account and password verification unit decrypts the encrypted account and password. When the decrypted account and password match the account and password stored in the account and password verification unit, the account and password verification unit sends a Y1 instruction to the mobile terminal attendance app. When the decrypted account and password do not match the account and password stored in the account and password verification unit, the account and password verification unit sends a Y0 instruction to the management module. The login verification module will transmit the account and password input time and the number of incorrect password input data to the clock-in data recording module.

5. The enterprise attendance management system according to claim 1, characterized in that: The liveness verification module includes a fingerprint verification unit and a facial recognition verification unit, which respectively store the fingerprint data and facial data of the employees. When the mobile terminal attendance app receives the Y1 instruction transmitted by the login verification module, the mobile terminal attendance app will start one of the fingerprint recognition module and the facial recognition module, and transmit the identification data to the liveness verification module. The fingerprint verification unit and the facial recognition verification unit will compare the received identification data with the data stored in themselves. When the match is successful, the verification time data, the number of verification failures data and the verification method data will be transmitted to the punch-in data recording module. When the match is unsuccessful, the X0 instruction will be sent to the management module.

6. The enterprise attendance management system according to claim 1, characterized in that: The positioning monitoring module calls the Beidou positioning data of the mobile terminal in real time through the mobile terminal attendance app. During the period from the employee starting the mobile terminal attendance app to the successful clocking in, the positioning monitoring module locates the position of the mobile terminal once every 0.5S. When it is detected that the positioning movement distance exceeds 6m, it is recorded as the number of movements plus 1. The positioning monitoring module will transmit the number of movements from the start of the mobile terminal attendance app to the successful clocking in to the clocking in data recording module. If the positioning monitoring module detects that the positioning data is not in the clocking in range set by the management personnel, the positioning monitoring module will send an S0 instruction to the management module.

7. The enterprise attendance management system according to claim 1, characterized in that: The punch-in data recording module can receive data transmitted by the login verification module, the liveness verification module and the positioning monitoring module, and summarize the employee punch-in data. The summarized data includes the employee's work number, account and password input time, number of incorrect password inputs, fingerprint / face verification time, number of fingerprint / face verification failures, verification method data and positioning movement number data. The punch-in data recording module transmits the employee's attendance summary data to the data analysis module.

8. The enterprise attendance management system according to claim 1, characterized in that: The data analysis module can receive the attendance summary data of employees transmitted by the punch-in data recording module. The data analysis module will remove duplicate data, remove abnormal data and unify the data format, and transmit the processed data to the risk judgment module.

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