An employee attendance data management system based on a smart park

Abstract

The present invention relates to the field of data management technology, and in particular to an employee attendance data management system based on a smart park, comprising a storage unit, a collection unit, a matching unit, a recording unit, a processing unit, a checking unit, and an analysis unit. The management system uniformly processes the attendance data acquired by the collection unit, wherein the attendance data acquired by the collection unit includes employee attendance information and visitor attendance information. The matching unit matches the attendance information. The processing unit transmits the matched attendance data to corresponding servers for storage and processing. The checking unit regularly verifies the attendance data stored in each server and regularly determines matching parameters. The analysis unit determines whether the operating parameters of the matching unit are qualified based on the matching parameters. When it is determined that the operating parameters of the matching unit are abnormal, the operating parameters of the matching unit are adjusted in time, thereby improving data processing efficiency.

Description

Technical Field

[0001] The present invention relates to the field of data management technology, and in particular to an employee attendance data management system based on a smart park. Background Art

[0002] As industrial parks develop, the number of businesses continues to grow, leading to a surge in both employee and visitor traffic. Traditional clock-in and clock-out methods typically rely on paper forms or simple spreadsheets. This approach is inefficient and prone to data loss, errors, and confusion. Furthermore, manually sorting and organizing large amounts of employee and visitor data requires significant time and effort, making it difficult to meet the demands of efficient modern industrial park management.

[0003] Chinese Patent Publication No. CN117523692A discloses an employee attendance system, comprising an attendance terminal and an employee data management server, wherein an output end of the attendance terminal is connected to the employee data management server via the Internet; the attendance terminal is used to obtain employee information and send the information to the employee data management server; the employee data management server is used to pre-store employee information and compare the employee information obtained by the attendance terminal with the pre-stored employee information; it can be seen that the above technical solution has the following problems: it is unable to process the attendance information of visitors, and does not take into account the regular verification of the data stored in the server, which affects the accuracy of data processing and thus affects the efficiency of data processing. Summary of the Invention

[0004] To this end, the present invention provides an employee attendance data management system based on a smart park to overcome the problem that the existing technology cannot process the attendance information of visitors, does not consider regular verification of the data stored in the server, affects the accuracy of data processing, and thus affects the efficiency of data processing.

[0005] To achieve the above objectives, the present invention provides an employee attendance data management system based on a smart park, comprising:

[0006] A storage unit includes several servers for storing employee information of various enterprises in the park, wherein corresponding servers store several business field labels of corresponding enterprises;

[0007] A collection unit connected to the storage unit for collecting attendance data, the attendance data including information about the person punching in and the location of the person punching in;

[0008] a matching unit, connected to the storage unit and the collection unit, respectively, for matching the attendance data with each of the servers to determine the enterprise corresponding to the attendance data;

[0009] A recording unit connected to the acquisition unit, for recording the time nodes at which the acquisition unit acquires the corresponding attendance data;

[0010] a processing unit connected to the storage unit and the matching unit, respectively, for obtaining the matched attendance data and transmitting the attendance data to a server of a corresponding enterprise;

[0011] a checking unit connected to the storage unit, for determining a matching parameter based on the number of attendance data of employee information belonging to a single enterprise stored in a preset period in a single server and the total number of each attendance data;

[0012] An analysis unit is respectively connected to the storage unit, the acquisition unit, the matching unit and the verification unit, and is used to determine whether the operating parameters of the matching unit are qualified based on the matching parameters, and to adjust the operating parameters of the matching unit when it is determined that the operating parameters of the matching unit are abnormal.

[0013] Furthermore, the matching unit is used to match the attendance data with each of the enterprises stored in the server, including:

[0014] Obtain enterprise tags and location tags for attendance data. Enterprise tags include several field tags.

[0015] The specific method of obtaining the enterprise label of the attendance data is to obtain the keywords of each field in the personnel information and determine the keywords of each field as the field label of the attendance data;

[0016] The specific method of obtaining the location tag of the attendance data is to determine the clock-in floor number and clock-in campus area determined based on the location information as the location tag;

[0017] The matching unit is used to determine the target area range of the enterprise to which the person belongs based on the acquired location tag group, and determine the corresponding enterprise of the person based on the matching situation between the enterprise tag and the business tag group of each enterprise within the target area;

[0018] The field tag matching the business tag in the enterprise tag is recorded as the matching tag for a single enterprise;

[0019] Calculate the ratio of the number of matching tags to the total number of business area tags of the corresponding enterprise, and select enterprises with a ratio higher than a preset ratio as candidate enterprises for corresponding attendance data;

[0020] The matching unit is used to determine a matching method for a single attendance data based on the number of candidate enterprises of the attendance data, including:

[0021] If the number of candidate companies is zero, the attendance data will be divided into visitor data;

[0022] If the number of candidate companies is one, the attendance data is divided into attendance data corresponding to the candidate companies;

[0023] If the number of candidate companies is greater than one, the attendance information is divided into the attendance data of the candidate company corresponding to the largest ratio;

[0024] The maximum ratio is the maximum value among the ratios corresponding to the attendance data.

[0025] Furthermore, for a single enterprise, the checking unit is used to determine a matching parameter by obtaining a ratio of the number of attendance data of employee information belonging to the corresponding enterprise stored in the corresponding server within a preset period to the total number of attendance data to obtain the matching parameter;

[0026] For a single enterprise, the analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the matching parameters, including:

[0027] If the matching parameter is less than or equal to the first preset matching parameter, it is determined that the operating parameter of the matching unit is abnormal, and a processing method for the matching unit is determined based on the matching difference parameter;

[0028] If the matching parameter is less than or equal to the second preset matching parameter and greater than the first preset matching parameter, determining whether the operating parameters of the matching unit are qualified based on the historical average matching parameter;

[0029] If the matching parameter is greater than the second preset matching parameter, it is determined that the operating parameters of the matching unit are qualified, and the matching unit is controlled to continue to operate using the current operating parameters.

[0030] Furthermore, the analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the historical average matching parameters;

[0031] To determine the historical average matching parameter, calculate the average value of each matching parameter in the historical data for a single server to obtain the historical average matching parameter;

[0032] If the historical average matching parameter is less than or equal to the preset historical parameter, the operating parameter of the matching unit is determined to be abnormal, and the processing method for the matching unit is determined based on the matching difference parameter;

[0033] If the historical average matching parameter is greater than the preset historical parameter, a single server is controlled to update the data.

[0034] Furthermore, the analysis unit is used to determine a processing method for the matching unit based on the matching difference parameter, including:

[0035] Solving the difference between the first preset matching parameter and the matching parameter to obtain a matching difference parameter;

[0036] If the matching difference parameter is less than or equal to the preset matching difference parameter, the processing method for the matching unit is determined based on the ratio of the number of visitor data to the total number of attendance data within the preset period;

[0037] If the matching difference parameter is greater than the preset matching difference parameter, the preset ratio is adjusted to a corresponding value based on the matching difference parameter.

[0038] Furthermore, the analysis unit is used to determine a processing method for the matching unit based on the quantity ratio, including:

[0039] If the quantity ratio is greater than the preset quantity ratio, adjusting the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio;

[0040] If the quantity ratio is less than or equal to the preset quantity ratio, the preset ratio is adjusted to a corresponding value based on the matching difference parameter.

[0041] Furthermore, the analysis unit is used to adjust the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio, wherein:

[0042] The reduction range of the first preset matching parameter and the second preset matching parameter determined based on the quantity ratio is proportional to the quantity ratio.

[0043] Furthermore, the analysis unit is used to adjust the preset ratio to a corresponding value based on the matching difference parameter, wherein:

[0044] The increase range of the preset ratio determined based on the matching difference parameter is proportional to the matching difference parameter.

[0045] Compared with the prior art, the beneficial effect of the present invention lies in that the attendance data acquired by the collection unit are uniformly processed, the attendance data acquired by the collection unit includes attendance information belonging to employee information and attendance information of visitors, the matching unit matches the attendance information, the processing unit transmits the matched attendance data to the corresponding servers for storage and processing, the verification unit regularly verifies the attendance data stored in each server and regularly determines the matching parameters, the analysis unit determines whether the operating parameters of the matching unit are qualified based on the matching parameters, and promptly adjusts the operating parameters of the matching unit when it is determined that the operating parameters of the matching unit are abnormal, thereby improving the accuracy of attendance data processing and thus improving data processing efficiency.

[0046] Furthermore, the acquired attendance data is labeled to obtain several labels, including enterprise labels and location labels. The target area of ​​the enterprise to which the personnel belong is preliminarily determined based on the acquired location label group, and the enterprise to which the attendance information belongs is determined based on the matching situation between the enterprise label group and the business field labels of each enterprise in the target area. Based on the ratio of the number of determined matching labels to the total number of business field labels, it is determined whether the attendance information belongs to a visitor, and the attendance information of non-visitors is matched to the corresponding enterprise. The attendance information is unified and the storage area of ​​the attendance information is determined, which effectively improves the data classification accuracy and effectively improves the data processing efficiency.

[0047] Furthermore, for a single enterprise, the ratio of the number of attendance data belonging to employee information in the enterprise server to the total number of attendance data stored in the single server within a preset period is regularly obtained to obtain a matching parameter to determine whether the classification of the attendance data is qualified, and then determine whether the operating parameters of the matching unit are qualified. When the matching parameter is less than or equal to the second preset matching parameter and greater than the first preset matching parameter, the historical average matching parameter is comprehensively used to determine whether the operating parameters of the matching unit are qualified. When the historical average matching parameter is greater than the preset historical parameter, the matching parameters for a single enterprise in the historical data are very high, but there are a small number of matching anomalies within this period. In this case, due to the existence of new employees, the server data in the enterprise has not been updated, and a deviation occurs in the judgment at that time. In this case, it is determined that the single server is updated to improve the timeliness of personnel information processing, improve the monitoring accuracy of the matching unit operation, and further improve the processing efficiency of attendance data.

[0048] Furthermore, the processing method for the matching unit is determined based on the matching difference parameter. When the matching difference parameter is greater than the preset matching difference parameter, the matching parameter is too low in this case, and a large amount of attendance data of non-employee information is stored in the server of a single enterprise. A large number of visitors are mistakenly classified into the server of a single enterprise, which makes the data management of the enterprise complicated. At this time, the preset ratio is adjusted, and the attendance division standard is dynamically determined. While efficiently processing the attendance data, the accuracy of the data division is effectively guaranteed, and the management efficiency of the enterprise for the attendance data is effectively improved; when the matching difference parameter is less than or equal to the preset matching difference parameter, only a small number of visitors are stored in the server. In this case, the processing method for the matching unit is further determined based on the number ratio. The number ratio characterizes the specific situation of the visitor. When the number ratio is greater than the preset number ratio, there is attendance data of a small number of visitors, and the enterprise has a large number of visitors. At this time, the first preset matching parameter and the second preset matching parameter are adjusted, and the monitoring standard for the matching unit is automatically adjusted according to the specific situation of the visitor's visit, and the data of each enterprise server is accurately monitored, which effectively improves the data processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 This is a module block diagram of an employee attendance data management system based on a smart park according to an embodiment of the present invention;

[0050] Figure 2 This is a logic decision diagram for the analysis unit in an embodiment of the present invention to determine whether the operating parameters of the matching unit are qualified based on the matching parameters. DETAILED DESCRIPTION

[0051] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are merely used to explain the present invention and are not intended to limit the present invention.

[0052] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the scope of protection of the present invention.

[0053] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside", and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the accompanying drawings. This is only for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0054] Furthermore, it should be noted that, in the description of the present invention, unless otherwise expressly specified or limited, the terms "mounted," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; mechanical connections or electrical connections; direct connections or indirect connections through an intermediate medium; and internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0055] See also Figure 1 and Figure 2 As shown in the figure, they are respectively a module block diagram of an employee attendance data management system based on a smart park according to an embodiment of the present invention, and a logic determination diagram of whether the operating parameters of the matching unit are qualified based on the matching parameters by the analysis unit; an employee attendance data management system based on a smart park according to an embodiment of the present invention comprises:

[0056] A storage unit includes several servers for storing employee information of various enterprises in the park, wherein corresponding servers store several business field labels of corresponding enterprises;

[0057] A collection unit connected to the storage unit for collecting attendance data, the attendance data including information about the person punching in and the location of the person punching in;

[0058] a matching unit, connected to the storage unit and the collection unit, respectively, for matching the attendance data with each of the servers to determine the enterprise corresponding to the attendance data;

[0059] A recording unit connected to the acquisition unit, for recording the time nodes at which the acquisition unit acquires the corresponding attendance data;

[0060] a processing unit connected to the storage unit and the matching unit, respectively, for obtaining the matched attendance data and transmitting the attendance data to a server of a corresponding enterprise;

[0061] a checking unit connected to the storage unit, for determining a matching parameter based on the number of attendance data of employee information belonging to a single enterprise stored in a preset period in a single server and the total number of each attendance data;

[0062] An analysis unit is respectively connected to the storage unit, the acquisition unit, the matching unit and the verification unit, and is used to determine whether the operating parameters of the matching unit are qualified based on the matching parameters, and to adjust the operating parameters of the matching unit when it is determined that the operating parameters of the matching unit are abnormal.

[0063] Specifically, the attendance data obtained by the collection unit are processed in a unified manner. The attendance data obtained by the collection unit includes attendance information belonging to employee information and attendance information of visitors. The matching unit matches each attendance information. The processing unit transmits the matched attendance data to the corresponding servers for storage and processing. The verification unit regularly verifies the attendance data stored in each server and regularly determines the matching parameters. The analysis unit determines whether the operating parameters of the matching unit are qualified based on the matching parameters. When it is determined that the operating parameters of the matching unit are abnormal, the operating parameters of the matching unit are adjusted in time, thereby improving the accuracy of attendance data processing and thus improving data processing efficiency.

[0064] Specifically, the matching unit is used to match the attendance data with each of the enterprises stored in the server, including:

[0065] Obtain enterprise tags and location tags for attendance data. Enterprise tags include several field tags.

[0066] The specific method of obtaining the enterprise label of the attendance data is to obtain the keywords of each field in the personnel information and determine the keywords of each field as the field label of the attendance data;

[0067] The specific method of obtaining the location tag of the attendance data is to determine the clock-in floor number and clock-in campus area determined based on the location information as the location tag;

[0068] The matching unit is used to determine the target area range of the enterprise to which the person belongs based on the acquired location tag group, and determine the corresponding enterprise of the person based on the matching situation between the enterprise tag and the business tag group of each enterprise within the target area;

[0069] The field tag matching the business tag in the enterprise tag is recorded as the matching tag for a single enterprise;

[0070] Calculate the ratio of the number of matching tags to the total number of business area tags of the corresponding enterprise, and select enterprises with a ratio higher than a preset ratio as candidate enterprises for corresponding attendance data;

[0071] The matching unit is used to determine a matching method for a single attendance data based on the number of candidate enterprises of the attendance data, including:

[0072] If the number of candidate companies is zero, the attendance data will be divided into visitor data;

[0073] If the number of candidate companies is one, the attendance data is divided into attendance data corresponding to the candidate companies;

[0074] If the number of candidate companies is greater than one, the attendance information is divided into the attendance data of the candidate company corresponding to the largest ratio;

[0075] The maximum ratio is the maximum value among the ratios corresponding to the attendance data.

[0076] Specifically, the preset ratio is selected within the interval [0.71, 0.83].

[0077] Specifically, the acquired attendance data is labeled to obtain several labels, including enterprise labels and location labels. The target area of ​​the enterprise to which the personnel belong is preliminarily determined based on the acquired location label group, and the enterprise to which the attendance information belongs is determined based on the matching situation between the enterprise label group and the business field labels of each enterprise in the target area. Based on the ratio of the number of determined matching labels to the total number of business field labels, it is determined whether the attendance information belongs to a visitor, and the attendance information of non-visitors is matched to the corresponding enterprise. The attendance information is unified and the storage area of ​​the attendance information is determined, which effectively improves the data classification accuracy and effectively improves the data processing efficiency.

[0078] Specifically, for a single enterprise, the checking unit is used to determine the matching parameter by obtaining the ratio of the number of attendance data of employee information belonging to the corresponding enterprise stored in the corresponding server within a preset period to the total number of attendance data to obtain the matching parameter;

[0079] For a single enterprise, the analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the matching parameters, including:

[0080] If the matching parameter is less than or equal to the first preset matching parameter, it is determined that the operating parameter of the matching unit is abnormal, and a processing method for the matching unit is determined based on the matching difference parameter;

[0081] If the matching parameter is less than or equal to the second preset matching parameter and greater than the first preset matching parameter, determining whether the operating parameters of the matching unit are qualified based on the historical average matching parameter;

[0082] If the matching parameter is greater than the second preset matching parameter, it is determined that the operating parameters of the matching unit are qualified, and the matching unit is controlled to continue to operate using the current operating parameters.

[0083] Specifically, the first preset matching parameter P1 is selected within the interval [0.81, 0.85], and the second preset matching parameter P2 is selected within the interval [0.95, 0.97].

[0084] Specifically, the analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the historical average matching parameters;

[0085] To determine the historical average matching parameter, calculate the average value of each matching parameter in the historical data for a single server to obtain the historical average matching parameter;

[0086] If the historical average matching parameter is less than or equal to the preset historical parameter, the operating parameter of the matching unit is determined to be abnormal, and the processing method for the matching unit is determined based on the matching difference parameter;

[0087] If the historical average matching parameter is greater than the preset historical parameter, a single server is controlled to update the data.

[0088] Specifically, the preset historical parameters are selected within the interval [0.94, 0.96].

[0089] Specifically, for a single enterprise, the ratio of the number of attendance data belonging to employee information in the enterprise server to the total number of attendance data stored in the single server within a preset period is regularly obtained to obtain a matching parameter to determine whether the classification of the attendance data is qualified, and then determine whether the operating parameters of the matching unit are qualified. When the matching parameter is less than or equal to the second preset matching parameter and greater than the first preset matching parameter, the historical average matching parameter is comprehensively used to determine whether the operating parameters of the matching unit are qualified. When the historical average matching parameter is greater than the preset historical parameter, the matching parameters for a single enterprise in the historical data are very high, but there are a small number of matching anomalies within this period. In this case, due to the existence of new employees, the server data in the enterprise has not been updated, and a deviation occurs in the judgment at that time. In this case, it is determined that the single server is updated to improve the timeliness of personnel information processing, improve the monitoring accuracy of the matching unit operation, and further improve the processing efficiency of attendance data.

[0090] Specifically, the analysis unit is used to determine a processing method for the matching unit based on the matching difference parameter, including:

[0091] Solving the difference between the first preset matching parameter and the matching parameter to obtain a matching difference parameter;

[0092] If the matching difference parameter is less than or equal to the preset matching difference parameter, the processing method for the matching unit is determined based on the ratio of the number of visitor data to the total number of attendance data within the preset period;

[0093] If the matching difference parameter is greater than the preset matching difference parameter, the preset ratio is adjusted to a corresponding value based on the matching difference parameter.

[0094] Specifically, the preset matching difference parameter Y0 is 0.42P1.

[0095] Specifically, the analysis unit is used to determine a processing method for the matching unit based on the quantity ratio, including:

[0096] If the quantity ratio is greater than the preset quantity ratio, adjusting the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio;

[0097] If the quantity ratio is less than or equal to the preset quantity ratio, the preset ratio is adjusted to a corresponding value based on the matching difference parameter.

[0098] Specifically, the preset quantity proportion B0 is selected within the interval [0.27, 0.35].

[0099] Specifically, the processing method for the matching unit is determined based on the matching difference parameter. When the matching difference parameter is greater than the preset matching difference parameter, the matching parameter is too low in this case. A large amount of attendance data of non-employee information is stored in the server of a single enterprise, and a large number of visitors are mistakenly classified into the server of a single enterprise, which makes the data management of the enterprise complicated. At this time, the preset ratio is adjusted and the attendance division standard is dynamically determined. While efficiently processing the attendance data, the accuracy of the data division is effectively guaranteed, and the management efficiency of the enterprise for attendance data is effectively improved; when the matching difference parameter is less than or equal to the preset matching difference parameter, only a small number of visitors are stored in the server. In this case, the processing method for the matching unit is further determined based on the number ratio. The number ratio characterizes the specific situation of the visitor. When the number ratio is greater than the preset number ratio, there is attendance data of a small number of visitors, and the enterprise has a large number of visitors. At this time, the first preset matching parameter and the second preset matching parameter are adjusted, and the monitoring standard for the matching unit is automatically adjusted according to the specific situation of the visitor's visit, and the data of each enterprise server is accurately monitored, which effectively improves the data processing efficiency.

[0100] Specifically, the analysis unit is used to adjust the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio, wherein:

[0101] The reduction range of the first preset matching parameter and the second preset matching parameter determined based on the quantity ratio is proportional to the quantity ratio.

[0102] In this embodiment, optionally,

[0103] Comparing the quantity ratio with a first preset ratio comparison threshold and a second preset ratio comparison threshold;

[0104] If the quantity ratio is less than or equal to the first preset ratio comparison threshold, the first preset matching parameter is adjusted to 0.93 times the initial first preset matching parameter, and the second preset matching parameter is adjusted to 0.92 times the initial second preset matching parameter;

[0105] If the quantity ratio is less than or equal to the second preset ratio comparison threshold and greater than the first preset ratio comparison threshold, the first preset matching parameter is adjusted to 0.87 times the initial first preset matching parameter, and the second preset matching parameter is adjusted to 0.88 times the initial second preset matching parameter;

[0106] If the quantity ratio is greater than the second preset ratio comparison threshold, the first preset matching parameter is adjusted to 0.75 times the initial first preset matching parameter, and the second preset matching parameter is adjusted to 0.75 times the initial second preset matching parameter;

[0107] The first preset ratio comparison threshold is 1.22B0, and the second preset ratio comparison threshold is 1.53B0.

[0108] Specifically, the analysis unit is configured to adjust the preset ratio to a corresponding value based on the matching difference parameter, wherein:

[0109] The increase range of the preset ratio determined based on the matching difference parameter is proportional to the matching difference parameter.

[0110] In this embodiment, optionally,

[0111] Comparing the matching difference parameter with a first preset matching comparison threshold and a second preset matching comparison threshold;

[0112] If the matching difference parameter is less than or equal to the first preset matching comparison threshold, the preset ratio is adjusted to 1.11 times the initial preset ratio;

[0113] If the matching difference parameter is less than or equal to the second preset matching comparison threshold and greater than the first preset matching comparison threshold, the preset ratio is adjusted to 1.19 times the initial preset ratio;

[0114] If the matching difference parameter is greater than the second preset matching comparison threshold, the preset ratio is adjusted to 1.26 times the initial preset ratio;

[0115] The first preset matching comparison threshold is 1.12Y0, and the second preset matching comparison threshold is 1.33Y0.

[0116] Specifically, the analyzing unit adjusts the preset ratio to the first initial preset ratio under the condition that the adjustment of the first preset matching parameter and the second preset matching parameter is completed.

[0117] Specifically, the first initial preset ratio is 1.11 times the initial preset ratio.

[0118] Thus far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it will be readily understood by those skilled in the art that the scope of protection of the present invention is obviously not limited to these specific embodiments. Without departing from the principles of the present invention, those skilled in the art may make equivalent changes or substitutions to the relevant technical features, and the technical solutions after such changes or substitutions will fall within the scope of protection of the present invention.

[0119] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that the present invention is susceptible to various modifications and variations. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. An employee attendance data management system based on a smart park, characterized in that: include: A storage unit includes several servers for storing employee information of various enterprises in the park, wherein corresponding servers store several business field labels of corresponding enterprises; A collection unit connected to the storage unit for collecting attendance data, the attendance data including information about the person punching in and the location of the person punching in; a matching unit, connected to the storage unit and the collection unit, respectively, for matching the attendance data with each of the servers to determine the enterprise corresponding to the attendance data; A recording unit connected to the acquisition unit, for recording the time nodes at which the acquisition unit acquires the corresponding attendance data; a processing unit connected to the storage unit and the matching unit, respectively, for obtaining the matched attendance data and transmitting the attendance data to a server of a corresponding enterprise; a checking unit connected to the storage unit and configured to determine a matching parameter for a single enterprise by obtaining a ratio of the number of attendance data of employee information belonging to a single enterprise stored in a single server within a preset period to the total number of attendance data, thereby obtaining the matching parameter; an analysis unit, connected to the storage unit, the acquisition unit, the matching unit, and the verification unit, respectively, for determining whether the operating parameters of the matching unit are qualified based on the matching parameters, and determining a processing method for the matching unit based on the matching difference parameters when the operating parameters of the matching unit are determined to be abnormal, including: Solving the difference between the first preset matching parameter and the matching parameter to obtain a matching difference parameter; If the matching difference parameter is less than or equal to the preset matching difference parameter, the processing method for the matching unit is determined based on the ratio of the number of visitor data to the total number of attendance data within the preset period; If the matching difference parameter is greater than the preset matching difference parameter, adjusting the preset ratio to a corresponding value based on the matching difference parameter; The analysis unit is used to determine a processing method for the matching unit based on the quantity ratio, including: If the quantity ratio is greater than the preset quantity ratio, adjusting the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio; If the quantity ratio is less than or equal to the preset quantity ratio, the preset ratio is adjusted to a corresponding value based on the matching difference parameter.

2. The employee attendance data management system based on the smart park according to claim 1 is characterized in that: The matching unit is used to match the attendance data with each of the enterprises stored in the server, including: Obtain enterprise tags and location tags for attendance data. Enterprise tags include several field tags. The specific method of obtaining the enterprise label of the attendance data is to obtain the keywords of each field in the personnel information and determine the keywords of each field as the field label of the attendance data; The specific method of obtaining the location tag of the attendance data is to determine the clock-in floor number and clock-in campus area determined based on the location information as the location tag; The matching unit is used to determine the target area range of the enterprise to which the person belongs based on the acquired location tag group, and determine the corresponding enterprise of the person based on the matching between the enterprise tag and the business field tag group of each enterprise within the target area; The tags in the enterprise tag that match the tags in the business field tag group are recorded as matching tags for a single enterprise; Calculate the ratio of the number of matching tags to the total number of business area tags of the corresponding enterprise, and select enterprises with a ratio higher than a preset ratio as candidate enterprises for corresponding attendance data; The matching unit is used to determine a matching method for a single attendance data based on the number of candidate enterprises of the attendance data, including: If the number of candidate companies is zero, the attendance data will be divided into visitor data; If the number of candidate companies is one, the attendance data is divided into attendance data corresponding to the candidate companies; If the number of candidate companies is greater than one, the attendance information is divided into the attendance data of the candidate company corresponding to the largest ratio; The maximum ratio is the maximum value among the ratios corresponding to the attendance data.

3. The employee attendance data management system based on the smart park according to claim 2 is characterized in that: For a single enterprise, the analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the matching parameters, including: If the matching parameter is less than or equal to the first preset matching parameter, it is determined that the operating parameter of the matching unit is abnormal, and a processing method for the matching unit is determined based on the matching difference parameter; If the matching parameter is less than or equal to the second preset matching parameter and greater than the first preset matching parameter, determining whether the operating parameters of the matching unit are qualified based on the historical average matching parameter; If the matching parameter is greater than the second preset matching parameter, it is determined that the operating parameters of the matching unit are qualified, and the matching unit is controlled to continue to operate using the current operating parameters.

4. The employee attendance data management system based on the smart park according to claim 3 is characterized in that: The analysis unit is used to determine whether the operating parameters of the matching unit are qualified based on the historical average matching parameters; To determine the historical average matching parameter, calculate the average value of each matching parameter in the historical data for a single server to obtain the historical average matching parameter; If the historical average matching parameter is less than or equal to the preset historical parameter, the operating parameter of the matching unit is determined to be abnormal, and the processing method for the matching unit is determined based on the matching difference parameter; If the historical average matching parameter is greater than the preset historical parameter, a single server is controlled to update the data.

5. The employee attendance data management system based on the smart park according to claim 4 is characterized in that: The analyzing unit is configured to adjust the first preset matching parameter and the second preset matching parameter to corresponding values ​​based on the quantity ratio, wherein: The reduction range of the first preset matching parameter and the second preset matching parameter determined based on the quantity ratio is proportional to the quantity ratio.

6. The employee attendance data management system based on the smart park according to claim 5 is characterized in that: The analyzing unit is configured to adjust the preset ratio to a corresponding value based on a matching difference parameter, wherein: The increase range of the preset ratio determined based on the matching difference parameter is proportional to the matching difference parameter.

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