An Internet of Things intelligent clock-in terminal and clock-in reminder method

Abstract

The present invention relates to the technical field of time management, and specifically to an Internet of Things smart clock-in terminal and a clock-in reminder method, which obtains the historical clock-in time of each employee in the prescribed clock-in section of each historical working day in the past set period and the corresponding clock-in-affecting weather data, and determines the time planning regularity index of each employee according to the difference between the historical clock-in time of the employee in the prescribed clock-in section of each historical working day and the prescribed clock-in time; determines the clock-in reminder reference time of each employee in the prescribed clock-in section of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the prescribed clock-in section of all historical working days, and the clock-in-affecting weather data corresponding to the current working day and the prescribed clock-in section of each historical working day, and then performs a clock-in reminder for each employee. The present invention can adaptively determine the clock-in reminder reference time of each employee and perform a clock-in reminder.

Description

Technical Field

[0001] The present invention relates to the technical field of time management, and in particular to an Internet of Things smart clock-in terminal and a clock-in reminder method. Background Art

[0002] The IoT smart clock-in terminal is a device that combines the Internet of Things (IoT) technology to manage and record employees or their attendance. During the working process, the IoT smart clock-in terminal first collects employee identity data based on biometric recognition, such as face recognition, fingerprint recognition and other technologies; transmits the collected employee identity data to the cloud or server through a wireless network for storage and analysis, and processes and counts employee attendance in real time, generating corresponding reports and data analysis; and allows employees to clock in and view personal attendance records through mobile apps or web pages.

[0003] Usually, the IoT smart clock-in terminal also has a reminder function, that is, the smart clock-in terminal will traverse the clock-in information of all employees entered in the terminal within a period of time before the specified clock-in time, determine whether there are employees who have not clocked in before or after the specified time, and remind employees and management through the IoT to avoid the phenomenon of missing cards. Since the existing IoT smart clock-in terminals usually uniformly remind all employees of missed clock-ins before a certain time before the specified clock-in time, some employees who actually arrived earlier will not have time to clock in due to other matters, which will ultimately affect the accuracy of data collection by the IoT smart clock-in terminal. Summary of the invention

[0004] The purpose of the present invention is to provide an Internet of Things smart clock-in terminal and a clock-in reminder method, which are used to solve the problem that the existing Internet of Things smart clock-in terminals usually uniformly remind all employees of missed clock-in a certain time before the specified clock-in time, which may cause some employees who actually arrive at work earlier to be delayed by other matters and have no time to clock in.

[0005] In order to solve the above technical problems, in a first aspect, the present invention provides an Internet of Things smart check-in terminal, comprising:

[0006] The data acquisition module is used to obtain the historical clock-in time of each employee in the specified clock-in period of each historical working day in the past set period and the corresponding clock-in-affecting weather data;

[0007] The work punch-in punctuality acquisition module is used to: determine the overall impact of the punch-in time in the specified punch-in period of each historical working day on the weather data based on the difference between the historical punch-in time of all employees in the specified punch-in period of each historical working day and the specified punch-in time, and determine the work punch-in punctuality of each employee based on the overall impact and the historical punch-in time of each employee in the specified punch-in period of each historical working day;

[0008] A regularity index acquisition module is used to determine the time planning regularity index of each employee according to the work punch-in punctuality and the distribution of each employee's historical punch-in time in the prescribed punch-in period of all historical working days, and the difference between each employee's historical punch-in time and the prescribed punch-in time in the prescribed punch-in period of all historical working days;

[0009] The clock-in reminder reference time acquisition module is used to: obtain the clock-in-affecting weather data of each employee in the specified clock-in period of the current working day, and determine the clock-in reminder reference time of each employee in the specified clock-in period of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the specified clock-in period of all historical working days, and the difference between the clock-in-affecting weather data corresponding to the specified clock-in period of the current working day and each historical working day;

[0010] The clock-in reminder module is used to: remind each employee to clock in according to the clock-in reminder reference time.

[0011] In combination with the first aspect above, in some possible implementations, determining the overall impact of clocking in and out of a specified clocking in and out period on each historical working day on weather data includes:

[0012] According to the difference between the historical punch-in time and the prescribed punch-in time of all employees in the prescribed punch-in period of each historical working day, determine the number of late employees on each historical working day and the punch-in time difference of each employee in the prescribed punch-in period of each historical working day;

[0013] The overall impact of the clocking-in period in each historical working day on weather data is determined based on the proportion of late employees in all employees on each historical working day and the distribution of the clocking-in time differences of all employees in the prescribed clocking-in period on each historical working day.

[0014] In combination with the first aspect above, in some possible implementations, determining the punctuality of each employee in clocking in for work includes:

[0015] Arrange the overall impact degree of the clock-in time in the specified clock-in period on the weather data of all historical working days in order of magnitude to obtain the overall impact degree sequence;

[0016] According to the overall impact degree sequence, the historical punch-in time of each employee in the specified punch-in period of all historical working days is arranged accordingly to obtain the historical punch-in time sequence of each employee;

[0017] The work clocking-in punctuality level of each employee is determined based on the correlation between the overall impact degree series and the historical clocking-in time series.

[0018] In combination with the first aspect above, in some possible implementations, determining the punctuality of each employee in clocking in for work includes:

[0019] Determine the correlation index between the overall impact degree series and the historical punch-in time series;

[0020] The related indicators are subjected to negative correlation mapping processing, so as to obtain the work clocking-in punctuality level of each employee.

[0021] In combination with the first aspect above, in some possible implementations, determining the time planning regularity index of each employee includes:

[0022] Determine the representative value of the historical clock-in time of each employee in the specified clock-in period of all historical working days according to the average distribution of the historical clock-in time of each employee in the specified clock-in period of all historical working days;

[0023] According to the difference between the historical punch-in time and the prescribed punch-in time of each employee in the prescribed punch-in period of all historical working days, determine the number of lateness of each employee in all historical working days, the representative value of lateness time, and the punch-in time difference in the prescribed punch-in period of each historical working day;

[0024] The time planning regularity index of each employee is determined based on the work punching punctuality, historical punching time representative value, number of lateness, lateness time representative value and the difference between the punching time difference of each employee in the specified punching period of different historical working days.

[0025] In combination with the first aspect above, in some possible implementations, determining a reference time for a punch-in reminder for each employee in a specified punch-in period of the current working day includes:

[0026] Determine the weight value of the specified punch-in segment of each historical working day according to the difference between the punch-in-affecting weather data corresponding to the specified punch-in segment of the current working day and each historical working day;

[0027] According to the weight value and the historical clock-in time of each employee in the specified clock-in period of all historical working days, the clock-in time of each employee in the specified clock-in period of the current working day is predicted to obtain the predicted clock-in time of each employee in the specified clock-in period of the current working day;

[0028] According to the time planning regularity index, the predicted value of the clock-in time of each employee in the specified clock-in period of the current working day is corrected to obtain the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

[0029] In combination with the first aspect above, in some possible implementations, the predicted value of the clock-in time of each employee in the specified clock-in period of the current working day is corrected to obtain the clock-in reminder reference time of each employee in the specified clock-in period of the current working day, including:

[0030] Performing positive correlation normalization processing on the time planning regularity index to obtain a correction coefficient of the predicted value of the punch-in time of each employee in the specified punch-in period of the current working day;

[0031] The product of the predicted clock-in time of each employee in the specified clock-in period of the current working day and its correction coefficient is calculated, and the product value is used as the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

[0032] In combination with the first aspect above, in some possible implementations, determining the weight value of the specified punch-in segment of each historical working day includes:

[0033] Determine the difference index value according to the difference between the clock-in-affected weather data corresponding to the specified clock-in period on the current working day and each historical working day;

[0034] The difference index value is negatively mapped to obtain a proximity index value, and the proximity index value corresponding to each historical working day is normalized to obtain the weight value of the specified punch-in segment of each historical working day, and the sum of the weight values ​​of the specified punch-in segments of all historical working days is equal to 1.

[0035] In combination with the first aspect above, in some possible implementations, each employee is reminded to punch in, including:

[0036] For any employee, if the employee does not punch in before the corresponding punch-in reminder reference time, the employee will be reminded to punch in after the corresponding punch-in reminder reference time and before the specified punch-in time.

[0037] In combination with the first aspect above, in some possible implementations, the clock-in reminder for each employee also includes:

[0038] For any employee, if the punch-in reminder reference time corresponding to the employee is after the specified punch-in time, and the employee has not punched in before the set time point before the specified punch-in time, the employee will be reminded to punch in at the set time point before the specified punch-in time.

[0039] In order to solve the above technical problems, in a second aspect, the present invention also provides a method for reminding a smart clock-in terminal of an Internet of Things to clock in, the method comprising:

[0040] Get the historical clock-in time of each employee in the specified clock-in period of each historical working day in the past set period and the corresponding clock-in-affecting weather data;

[0041] Determine the overall impact of clocking in during the prescribed clocking-in period of each historical working day on weather data based on the difference between the historical clocking-in time of all employees during the prescribed clocking-in period of each historical working day and the prescribed clocking-in time, and determine the punctuality of each employee's clocking-in during the prescribed clocking-in period of each historical working day based on the overall impact and the historical clocking-in time of each employee during the prescribed clocking-in period of each historical working day;

[0042] Determine the time planning regularity index of each employee according to the work clocking-in punctuality and the distribution of each employee's historical clocking-in time in the prescribed clocking-in period of all historical working days, and the difference between each employee's historical clocking-in time and the prescribed clocking-in time in the prescribed clocking-in period of all historical working days;

[0043] Obtain the clock-in-affecting weather data of each employee in the prescribed clock-in period of the current working day, and determine the clock-in reminder reference time of each employee in the prescribed clock-in period of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the prescribed clock-in period of all historical working days, and the difference between the clock-in-affecting weather data corresponding to the prescribed clock-in period of the current working day and each historical working day;

[0044] According to the punch-in reminder reference time, each employee is reminded to punch in.

[0045] To solve the above technical problems, in a third aspect, the present invention further provides an IoT smart card-punching terminal, comprising a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above-mentioned first aspect or each module implementation step in any possible implementation of the first aspect.

[0046] To solve the above technical problems, in a fourth aspect, the present invention further provides a computer program product, which includes: a computer program code, when the computer program code runs on a computer, enables the computer to execute the various module implementation steps in the above first aspect or any possible implementation method of the first aspect.

[0047] To solve the above technical problems, in a fifth aspect, the present invention further provides a computer-readable storage medium, which stores a computer program code. When the computer program code runs on a computer, the computer executes the implementation steps of each module in the above-mentioned first aspect or any possible implementation method of the first aspect.

[0048] The present invention has the following beneficial effects: considering that employees may notice a significant delay in their clock-in time compared to normal weather conditions due to the influence of weather factors during their daily work, and because different employees have different clock-in punctuality levels, weather factors have different influences on the clock-in changes of different employees. To this end, the influence of weather factors on the clock-in of all employees is measured according to the difference between the historical clock-in time and the prescribed clock-in time of all employees, so as to obtain the overall influence of the prescribed clock-in period of each historical working day. When employees do not pay enough attention to their work, their clock-in time will not change significantly with the change of the severity of the weather. Therefore, the clock-in punctuality of each employee is determined by combining the overall influence and the historical clock-in time of each employee in the prescribed clock-in period of each historical working day. Since the actual clock-in time of each employee on the historical working day has different degrees of difference, the historical clock-in time fluctuates within a certain range. This difference reflects the regularity of the employee's time planning. For employees who are prone to being late, their regularity of time planning is usually poorer than that of employees who are not prone to being late. Therefore, the time planning regularity index of each employee is determined by combining the punctuality of each employee's work clocking in and out and the distribution of the historical clocking-in time in the prescribed clocking-in section of all historical working days, as well as the difference between the historical clocking-in time and the prescribed clocking-in time of each employee in the prescribed clocking-in section of all historical working days. Furthermore, the possible clocking-in time of the employee is predicted based on the difference between the clocking-in-affecting weather data corresponding to the prescribed clocking-in section of the current working day and each historical working day, and at the same time, combined with the regularity of the employee's time planning, the clocking-in reminder reference time is finally adaptively determined, and each employee is reminded to clock in based on the clocking-in reminder reference time. The present invention adaptively determines a reasonable clocking-in reminder reference time for each employee by combining the historical clocking-in time of the prescribed clocking-in section of the historical working days under the influence of historical weather, as well as the difference between the clocking-in-affecting weather data corresponding to the prescribed clocking-in section of the current working day and each historical working day, thereby performing a clocking-in reminder to avoid the phenomenon of employees forgetting to clock in, thereby improving the accuracy of data collection of the Internet of Things smart clocking-in terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0050] Figure 1 This is a schematic diagram of the module composition of an IoT smart card-punching terminal according to an embodiment of the present invention;

[0051] Figure 2 A flowchart of the steps of determining the overall impact degree of clocking-in at a specified clocking-in period of each historical working day on weather data according to an embodiment of the present invention;

[0052] Figure 3 A flowchart of the steps of determining the punctuality of each employee's work clocking in according to an embodiment of the present invention;

[0053] Figure 4 A flowchart of the steps of determining the time planning regularity index of each employee according to an embodiment of the present invention;

[0054] Figure 5 A flowchart of the steps of determining a reference time for each employee to be reminded of a punch-in time in a specified punch-in period of the current working day according to an embodiment of the present invention;

[0055] Figure 6 A flowchart of a method for reminding a smart clock-in terminal of an Internet of Things according to an embodiment of the present invention;

[0056] Figure 7 The present invention is a schematic diagram of the structure of an IoT smart clock-in terminal according to an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to clearly illustrate the technical features of the present invention, the present invention is described in detail below through specific implementation methods in conjunction with the accompanying drawings.

[0058] Embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments of the present invention are only for exemplary purposes and are not intended to limit the scope of protection of the present invention.

[0059] It should be understood that the various steps described in the method embodiments of the present invention may be performed in different orders and / or in parallel. In addition, the method embodiments may include additional steps and / or omit the steps shown. The scope of the present invention is not limited in this respect.

[0060] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0061] It should be noted that the concepts such as "first" and "second" mentioned in the present invention are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0062] It should be noted that the modifications of "one" and "multiple" mentioned in the present invention are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more". In the description of the present invention, unless otherwise specified, "multiple" refers to two or more than two, and other quantifiers are similar; "at least one item", "one or more items" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one item a can represent any number of a; for another example, one or more items of a, b and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple; "and / or" is a kind of association relationship that describes the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0063] Although operations or steps are described in a specific order in the drawings in the embodiments of the present invention, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or that all the operations or steps shown must be performed to obtain the desired results. In the embodiments of the present invention, these operations or steps may be performed in series; these operations or steps may also be performed in parallel; or some of these operations or steps may be performed.

[0064] At the same time, it is understood that the data involved in the technical solution of the present invention (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of the relevant laws, regulations and relevant provisions. Unless otherwise defined, all technical and scientific terms used in the present invention have the same meanings as those generally understood by technicians in the technical field of the present invention, and all parameters or indicators in the formulas involved in the present invention are normalized values ​​that eliminate the influence of dimensions.

[0065] In order to solve the problem that the existing IoT smart clock-in terminals usually uniformly remind all employees of missing clock-in a certain time before the prescribed clock-in time, which may cause some employees who actually arrive earlier to be delayed by other matters and fail to clock in in time, the embodiment of the present invention provides an IoT smart clock-in terminal and a clock-in reminder method. The clock-in terminal determines the overall impact of weather factor impact data on all employees by calculating the difference between the historical clock-in time of all employees in the prescribed clock-in period of each historical working day and the prescribed clock-in time, and then determines the overall impact of weather factor impact data on all employees based on the overall impact and the historical clock-in time of each employee in the prescribed clock-in period of each historical working day. The punctuality of each employee's work clocking in is quantified; at the same time, by analyzing the change characteristics of each employee's historical clocking in time in the prescribed clocking-in period of each historical working day, and combining each employee's work clocking-in punctuality, the regularity of each employee's time planning is obtained, and then combined with each employee's historical clocking in time in the prescribed clocking-in period of all historical working days, and the difference between the weather factor impact data corresponding to the current working day and the prescribed clocking-in period of each historical working day, the clocking-in reminder reference time of each employee in the prescribed clocking-in period of the current working day is adaptively determined, and each employee is reminded to clock in based on the clocking-in reminder reference time. The clocking-in terminal improves the rationality of clocking-in reminders by adaptively reminding different employees to avoid employees forgetting to clock in, thereby improving the accuracy of data collection of the IoT smart clocking-in terminal.

[0066] An IoT smart clock-in terminal and a clock-in reminder method provided by an embodiment of the present invention will be described in detail below with reference to the accompanying drawings.

[0067] Figure 1 FIG. 1 shows a schematic diagram of the module composition of an IoT smart card-punching terminal provided by an embodiment of the present invention. Figure 1 As shown, the clock-in terminal specifically includes the following modules:

[0068] The data acquisition module is used to obtain the historical clock-in time of each employee in the specified clock-in period of each historical working day within the past set period and the corresponding clock-in-affecting weather data.

[0069] In the process of collecting punch-in data by the IoT smart punch-in terminal, the historical data of the IoT smart punch-in terminal can be used to obtain the historical punch-in time of each employee of the company for the specified punch-in period of each historical working day in the past set time period. The historical punch-in time refers to the punch-in time point of each employee. The length of the past set time period can be reasonably set as needed. In the embodiment of the present invention, the past set time period is set to the most recent past month. The specified punch-in period refers to the punch-in period specified by the company. In the embodiment of the present invention, it refers to the morning work punch-in period. It should be understood that in other feasible methods, the specified punch-in period may also refer to the afternoon work punch-in period.

[0070] At the same time, based on the interconnection between the Internet of Things system and many other devices, the weather condition data of the preset time period centered on the punch-in deadline of the specified punch-in period is obtained, such as obtaining the weather condition data of the corresponding time period of 4 hours, two hours before and after the punch-in deadline of the specified punch-in period. The weather condition data includes key characteristic data characterizing the weather conditions, such as cloudy or sunny, rainfall, snowfall, wind speed and direction, and other data. The weather condition data is scored to distinguish between extreme weather and normal weather, and a score value is obtained, and the score value is used as the weather data affecting the punch-in. In an embodiment of the present invention, when obtaining the score value of the weather condition data, the weather condition data corresponding to the specified punch-in period of each historical working day of each employee in the past set time period is input into a pre-trained classification network, and the pre-trained classification network is used to output the score value of the corresponding weather condition data. The structure of the classification network is a five-layer fully connected neural network model. When training the classification network, first obtain a training sample set. Each training sample in the training sample set is the weather data corresponding to the above preset period in the past. At the same time, use an artificial method to manually formulate a label for each training sample. The label is a score value corresponding to each training sample. The score value ranges from 0 to 1. The higher the score value, the worse the weather is and the less suitable it is for travel. The classification network is trained using the training sample set. The optimization method used in the training process is the gradient descent method, and the loss function used is the cross entropy function, so that a trained classification network is finally obtained.

[0071] According to the above method, the historical clock-in time of each employee of the company in the prescribed clock-in period of each historical working day within the past set period and the corresponding clock-in-affecting weather data can be obtained.

[0072] The work clocking-in punctuality acquisition module is used to: determine the overall impact of the clocking-in in the prescribed clocking-in period of each historical working day on the weather data based on the difference between the historical clocking-in time of all employees in the prescribed clocking-in period of each historical working day and the prescribed clocking-in time; determine the work clocking-in punctuality of each employee based on the overall impact and the historical clocking-in time of each employee in the prescribed clocking-in period of each historical working day.

[0073] During the daily work process, employees may be affected by weather factors, which may cause their clock-in time to be significantly delayed compared to normal weather conditions. As an external influencing factor, the weather has a more obvious and concrete impact on the punctuality of different employees in clocking in for work. That is, when an employee pays more attention to work, he is less affected by the weather, and the employee's clock-in time changes less. When an employee does not pay enough attention to work, he is more affected by the weather, and the employee's clock-in time changes more. Therefore, based on the characteristics of each employee's historical clock-in time in the specified clock-in period of each working day, the impact of weather factors on the change of clock-in time can be analyzed, so as to quantify the punctuality of any employee's clock-in time.

[0074] To this end, the overall impact of clocking in during the prescribed clocking-in period of each historical working day on the weather data is determined based on the difference between the historical clocking-in time and the prescribed clocking-in time of all employees during the prescribed clocking-in period of each historical working day.

[0075] In the embodiment of the present invention, Figure 2 As shown in the figure, the overall impact of the clock-in period of each historical working day on the weather data is determined, and the implementation steps include:

[0076] Step S201: determining the number of late employees on each historical working day and the punch-in time difference of each employee in the prescribed punch-in period on each historical working day according to the difference between the historical punch-in time of all employees in the prescribed punch-in period on each historical working day and the prescribed punch-in time;

[0077] Step S202: Determine the overall impact of the clocking-in period of each historical working day on the weather data based on the proportion of the number of late employees in all employees on each historical working day and the distribution of the clocking-in time differences of all employees in the specified clocking-in period of each historical working day.

[0078] For the above steps, the number of late employees in the prescribed punch-in period of each historical working day can be determined based on the difference between the historical punch-in time of all employees in the prescribed punch-in period of each historical working day and the prescribed punch-in time. At the same time, the punch-in time difference can be determined based on the difference between the historical punch-in time of each employee in the prescribed punch-in period of each historical working day and the prescribed punch-in time. That is, the prescribed punch-in time corresponding to the prescribed punch-in period is taken as the minuend, and the historical punch-in time of each employee in the prescribed punch-in period of each historical working day is taken as the subtrahend. The difference is the punch-in time difference, which may be positive or negative.

[0079] The overall impact of clocking in during the specified clocking-in period on each historical working day on weather data is determined based on the proportion of the number of late employees in the specified clocking-in period of all employees in each historical working day, and the clocking-in time difference of all employees in the specified clocking-in period of each historical working day. The greater the proportion of late employees in the number of all employees, the more late employees there were on that historical working day, and the greater the overall impact of the weather conditions on that historical working day on all employees. The smaller the clocking-in time difference of all employees on that historical working day, the later the employee clocked in, and the greater the overall impact of the weather conditions on that historical working day on all employees.

[0080] In the embodiment of the present invention, the overall impact degree of the clock-in time in the specified clock-in time period on the weather data of each historical working day is determined, and the corresponding calculation formula is:

[0081] ;

[0082] in, Indicates The overall impact of clocking in during the specified clocking-in period on weather data on a historical working day; Indicates The number of employees who were late during the prescribed punch-in period of each historical working day; Indicates The number of all employees on each historical workday; Indicates Employees in The time difference between the clock-in time periods of the specified clock-in periods of the historical working days; Represents an exponential function with the natural constant e as base.

[0083] In the above calculation formula, the punch-in time difference is obtained by calculating the difference between the prescribed punch-in time of the prescribed punch-in period and the historical punch-in time of each employee in the prescribed punch-in period of each historical working day. The smaller the value of the punch-in time difference (including negative values), the greater the impact of the current weather on the punch-in time of the employee. The punch-in time differences corresponding to all employees are accumulated, and the accumulated value is negatively correlated and mapped using an exponential function. At the same time, the number of late employees in the prescribed punch-in period of each historical working day is combined with the proportion of all employees in the number of late employees. The larger the mapping result and the greater the proportion, the greater the overall impact of the weather conditions on the historical working day on all employees.

[0084] Since the above-mentioned overall impact degree is obtained based on the punch-in time difference and lateness of all employees affected by weather factors, and the overall impact degree is different for each employee on the same working day, it is necessary to combine the changes in the overall impact degree and the punch-in information of individual employees to determine the degree of punctuality of each employee in punching in for work.

[0085] In the embodiment of the present invention, Figure 3 As shown in the figure, determine the punctuality of each employee's work clocking in. The implementation steps include:

[0086] Step S211: Arrange the overall impact degree of the clock-in and clock-out periods on the weather data of all historical working days in order of magnitude to obtain an overall impact degree sequence;

[0087] Step S212: according to the overall impact degree sequence, the historical punch-in time of each employee in the specified punch-in period of all historical working days is arranged accordingly to obtain the historical punch-in time sequence of each employee;

[0088] Step S213: Determine the work clocking-in punctuality of each employee according to the correlation between the overall impact degree sequence and the historical clocking-in time sequence.

[0089] For the above steps, the overall impact degree of the clock-in time on the weather data of the prescribed clock-in time slots of all historical working days is arranged in order from small to large to obtain the overall impact degree sequence. At the same time, since the weather conditions of each working day are consistent for all employees, for each employee, the historical clock-in time of the same prescribed clock-in time slots of all historical working days is arranged in the order of the overall impact degree in the overall impact degree sequence to obtain the historical clock-in time sequence. According to the correlation between the overall impact degree sequence and the historical clock-in time series, the relevant indicator is determined, and the relevant indicator can reflect the degree of impact of the clock-in time of the corresponding employee on the weather changes. The larger the value of the relevant indicator, the greater the impact of the clock-in time of the employee on the weather changes.

[0090] In an embodiment of the present invention, the Pearson correlation coefficient between the overall impact degree sequence and the historical punch-in time sequence is determined, and the Pearson correlation coefficient is determined as a related indicator. The value range of the Pearson correlation coefficient is [-1,1]. The larger the value, the closer it is to 1, indicating that the corresponding employee's punch-in is more affected by the weather. On the contrary, the smaller the value, the smaller the impact of the weather on the corresponding employee's punch-in. In other practical ways, the cosine similarity between the overall impact degree sequence and the historical punch-in time sequence can also be determined, and the cosine similarity can be used as a related indicator.

[0091] It should be understood that, in special circumstances, each employee may need to take leave. Therefore, before determining the correlation coefficient between the overall impact degree sequence and the historical punch-in time series, the overall impact degree sequence needs to be corrected, that is, the overall impact degree corresponding to the employee's leave in the overall impact degree sequence is deleted to obtain the corrected overall impact degree sequence, and the correlation coefficient between the corrected overall impact degree sequence and the historical punch-in time series is determined.

[0092] When the employee's clock-in time is affected more by weather factors, it means that the corresponding employee is less punctual for clocking in at work, and vice versa. Therefore, the correlation coefficient between the overall impact degree series and the historical clock-in time series is negatively correlated and mapped to obtain the clock-in punctuality of each employee.

[0093] In the embodiment of the present invention, the calculation formula for determining the punctuality of each employee's work clocking in is:

[0094] ;

[0095] in, Indicates The punctuality of employees in clocking in at work; Indicates The correlation indicator between the historical punch-in time series corresponding to each employee and the overall impact degree series.

[0096] In the above calculation formula, The smaller the value of The less the actual clock-in time of an employee is affected by the weather, the less The more punctual an employee is in clocking in at work, the greater the value of the clocking in punctuality will be.

[0097] The regularity index acquisition module is used to determine the time planning regularity index of each employee based on the work punch-in punctuality and the distribution of each employee's historical punch-in time in the prescribed punch-in period of all historical working days, as well as the difference between each employee's historical punch-in time and the prescribed punch-in time in the prescribed punch-in period of all historical working days.

[0098] Since different employees have different distances to the company and have different plans for their estimated arrival time, and some employees also have different biological clocks, the actual clock-in time of each day in the historical working day for any employee varies to varying degrees, causing the historical clock-in time to fluctuate within a certain range. This difference reflects the regularity of the employee's time planning, that is, the reasonableness and regularity of the employee's time planning. At the same time, different employees have different probabilities of being late. For employees who are prone to being late, their regularity in planning time is usually worse than that of employees who are not prone to being late.

[0099] For each employee, the higher the degree of punctuality in clocking in at work, the less the actual clocking in time is affected by the weather, which indirectly shows that the employee has a stronger sense of time planning. At the same time, the smaller the value of the historical clocking in time in the prescribed clocking-in period of all historical working days, the earlier the employee actually clocks in and the stronger the sense of time planning. The fewer times the employee is late and the smaller the difference between the historical clocking-in time and the prescribed clocking-in time when he is late, it means that the employee is only late occasionally and the lateness is short, and the stronger the sense of time planning. The difference between the historical clocking-in time and the prescribed clocking-in time in the prescribed clocking-in period of all historical working days fluctuates less, which means that the employee's actual clocking-in time every day is more consistent and the stronger the sense of time planning.

[0100] Therefore, the time planning regularity index of each employee can be determined based on the punctuality of each employee's work clocking in and out, the distribution of the historical clocking-in time in the prescribed clocking-in period of all historical working days, and the difference between the historical clocking-in time and the prescribed clocking-in time of each employee in the prescribed clocking-in period of all historical working days.

[0101] In the embodiment of the present invention, Figure 4 As shown, determine the time planning regularity index for each employee. The implementation steps include:

[0102] Step S301: Determine a representative value of the historical clock-in time of each employee in the specified clock-in period of all historical working days according to the average distribution of the historical clock-in time of each employee in the specified clock-in period of all historical working days;

[0103] Step S302: Determine the number of latenesses of each employee on all historical working days, the representative value of lateness time, and the difference of the punch-in time in the specified punch-in period of each historical working day according to the difference between the historical punch-in time of each employee and the specified punch-in time in the specified punch-in period of all historical working days;

[0104] Step S303: Determine the time planning regularity index of each employee based on the work clocking-in punctuality, historical clocking-in time representative value, number of lateness, lateness time representative value, and the difference between the clocking-in time difference of each employee in the specified clocking-in period of different historical working days.

[0105] For the above steps, the average value of the historical punch-in time of each employee in the prescribed punch-in section of all historical working days is determined, and the average value is used as the representative value of the historical punch-in time of each employee in the prescribed punch-in section of all historical working days. According to the difference between the historical punch-in time and the prescribed punch-in time of each employee in the prescribed punch-in section of all historical working days, the number of late arrivals of each employee in all historical working days can be determined. At the same time, for all historical working days when each employee is late, the difference between the prescribed punch-in time and the historical punch-in time in the prescribed punch-in section is determined, and the average value of all the differences is calculated, and the average value is used as the representative value of the late arrival time. In addition, the difference between the historical punch-in time and the prescribed punch-in time of each employee in the prescribed punch-in section of each historical working day is determined to obtain the punch-in time difference of each employee in the prescribed punch-in section of each historical working day. Then, according to the degree of punctuality of work punch-in, the representative value of historical punch-in time, the number of late arrivals, the representative value of late arrival time, and the difference between the punch-in time difference of each employee in the prescribed punch-in section of different historical working days, the time planning regularity index of each employee is determined.

[0106] In the embodiment of the present invention, the time planning regularity index of each employee is determined, and the corresponding calculation formula is:

[0107] ;

[0108] in, Indicates Indicators of regularity in time planning for employees; Indicates The punctuality of employees in clocking in at work; Indicates The representative value of the historical punch-in time of an employee in the specified punch-in period of all historical working days; Indicates The number of times an employee was late on all historical working days; Indicates The representative value of the employee's lateness time in all historical working days, L indicates the occurrence of a lateness mark; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates The total number of historical workdays for each employee.

[0109] In the above calculation formula, the mean of the historical punch-in time of each employee in the prescribed punch-in period of all historical working days is calculated. The smaller the mean, the higher the regularity of the employee's time. At the same time, for the historical working days where lateness occurs, since lateness has occurred, the impact of the employee on his own planning is expressed by the number of late days, that is, the number of latenesses. The more latenesses, the greater the impact. At the same time, the mean of the actual lateness exceeding time on all late days is calculated. The larger the value, the lower the employee's planning of time. Finally, by calculating the difference between the historical punch-in time of each employee in the prescribed punch-in period of adjacent historical working days and the prescribed punch-in time, that is, the punch-in time difference, the smaller the difference, the smaller the difference, indicating that the employee has a smaller difference between the historical punch-in time of the historical working days, and his discipline is higher, and he has better planning for time. In addition, referring to the employee's work punch-in punctuality, the larger the value of the work punch-in punctuality, the less the employee is affected by weather factors, and also the higher the regularity of his time planning.

[0110] The clock-in reminder reference time acquisition module is used to: obtain the clock-in-affecting weather data of each employee in the specified clock-in period of the current working day, and determine the clock-in reminder reference time of each employee in the specified clock-in period of the current working day based on the time planning regularity index and the historical clock-in time of each employee in the specified clock-in period of all historical working days, as well as the difference between the clock-in-affecting weather data corresponding to the specified clock-in period of the current working day and each historical working day.

[0111] In order to avoid the phenomenon that employees actually arrive at work but forget to punch in, the IoT smart punch-in terminal needs to remind employees to punch in, but the existing punch-in reminders are set to fixed reminder time points. Since the actual arrival time of different employees is affected by the employees' own habits and external environmental factors, the actual arrival time of different employees may vary. At this time, the punch-in reminder at a fixed reminder time point is not reasonable enough, which will cause some employees who actually arrive at work earlier to be delayed by other matters and not have time to punch in, which will ultimately affect the accuracy of data collection of the IoT smart punch-in terminal. In order to avoid this situation, the possible arrival time of different employees can be predicted, and the predicted arrival time can be corrected according to the time planning regularity indicators of different employees, and the punch-in reminder reference time of each employee in the specified punch-in period of the current working day can be determined, so as to perform adaptive punch-in reminders for different employees, so as to improve the rationality of the punch-in reminder, avoid the phenomenon of employees forgetting to punch in, and thus improve the accuracy of data collection of the IoT smart punch-in terminal.

[0112] In the embodiment of the present invention, Figure 5 As shown in the figure, determine the reference time for each employee to punch in during the specified punch-in period of the current working day. The implementation steps include:

[0113] Step S401: Determine the weight value of the specified punch-in segment of each historical working day according to the difference between the punch-in-affecting weather data corresponding to the specified punch-in segment of the current working day and each historical working day;

[0114] Step S402: predicting the clock-in time of each employee in the specified clock-in period of the current working day according to the weight value and the historical clock-in time of each employee in the specified clock-in period of all historical working days, and obtaining the predicted clock-in time of each employee in the specified clock-in period of the current working day;

[0115] Step S403: According to the time planning regularity index, the predicted value of the clock-in time of each employee in the specified clock-in period of the current working day is corrected to obtain the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

[0116] For the above steps, consider the exponential weighted moving average method as a commonly used time series prediction method, which can be used to predict the arrival time of different employees. In an embodiment of the present invention, when using the exponential weighted moving average method to predict the arrival time of different employees, determine the absolute value of the difference between the clock-in weather data corresponding to the specified clock-in segment of each historical working day and the clock-in segment, use the absolute value of the difference as the difference index value, perform negative correlation mapping on the difference index value, obtain a negative correlation mapping result, and use the negative correlation mapping result as the proximity index value. In an embodiment of the present invention, calculate the difference between the value 1 and the difference index value, and the difference is the negative correlation mapping result. Perform sum normalization on the proximity index value, and use the normalized value of the proximity index value as the weight value of the specified clock-in segment of each historical working day. Performing sum normalization means calculating the cumulative sum of the proximity index values ​​corresponding to the clock-in weather data corresponding to the specified clock-in segment of the current working day and each historical working day, and dividing the proximity index value by the cumulative sum, thereby obtaining the normalized value of the proximity index value. By normalizing the sum of the values, the sum of the weight values ​​of the specified punch-in segments of all historical working days can be made equal to 1.

[0117] Furthermore, for each employee, based on his / her historical clock-in time in the prescribed clock-in period of all historical working days and the weight value of the prescribed clock-in period of each historical working day, the exponentially weighted moving average method is used to predict the employee's arrival time in the prescribed clock-in period of the current working day. That is, the weight value of the prescribed clock-in period of all historical working days is used to perform weighted addition on the historical clock-in times in the prescribed clock-in period of all historical working days to obtain the predicted clock-in time of the employee.

[0118] The punch-in time prediction value of each employee can be determined in the above manner. However, since the punch-in time prediction value is not combined with the employee's actual behavior, the punch-in time prediction value can be corrected according to the time planning regularity index of each employee to obtain the punch-in reminder reference time, so that the punch-in reminder reference time is ahead of the punch-in time prediction value. The higher the regularity of the employee, the closer the punch-in reminder reference time is to the punch-in time prediction value. Conversely, the lower the regularity of the employee, the earlier the punch-in reminder reference time is, so as to avoid forgetting to punch in.

[0119] In the embodiment of the present invention, the predicted value of the punch-in time of each employee is corrected according to the time planning regularity index of each employee to obtain the punch-in reminder reference time of each employee in the specified punch-in period of the current working day. The corresponding calculation formula is:

[0120] ;

[0121] in, Indicates The reference time for the punch-in reminder of the employee in the specified punch-in period of the current working day; Indicates The predicted time for the employees to clock in during the specified time slots of the current workday; Indicates Indicators of regularity in time planning for employees; Represents the normalization function, which is used to Normalize.

[0122] In the above formula, the correction coefficient is obtained by normalizing the employee's time planning regularity index, and the employee's punch-in time prediction value is corrected using the correction coefficient, that is, the product value between the punch-in time prediction value and the correction coefficient is calculated to obtain the punch-in reminder reference time. When the employee's time planning regularity index is larger, it means that the employee has a stronger time planning, and the corresponding weight value is closer to 1. At this time, the punch-in reminder reference time is closer to the punch-in time prediction value. On the contrary, when the employee's time planning regularity index is smaller, the corresponding weight value is closer to 0. At this time, the punch-in time prediction value should be reduced to make a punch-in reminder in advance. At this time, the punch-in reminder reference time is closer to the punch-in time prediction value.

[0123] The clock-in reminder module is used to: remind each employee to clock in according to the clock-in reminder reference time.

[0124] According to the punch-in reminder reference time of each employee in the specified punch-in section of the current working day determined above, each employee is reminded to punch in. In an embodiment of the present invention, for each employee, if the employee does not punch in before the punch-in reminder reference time (including the punch-in reminder reference time), the employee is reminded to punch in through the Internet of Things after the punch-in reminder reference time and before the specified punch-in time. It should be understood that if the punch-in reminder reference time determined above exceeds the specified punch-in time, that is, the punch-in reminder reference time is after the specified punch-in time, and the employee does not punch in before the set time point before the specified punch-in time, the employee is reminded to punch in at the set time point before the specified punch-in time. In an embodiment of the present invention, the set time point is the first 2 minutes before the specified punch-in time.

[0125] Based on the same inventive concept, the embodiment of the present invention also provides a method for reminding a smart clock-in terminal of the Internet of Things. Figure 6 As shown, the method includes:

[0126] Step S100: Obtain the historical clock-in time of each employee in the specified clock-in period of each historical working day in the past set period and the corresponding clock-in-affecting weather data;

[0127] Step S200: determining the overall impact of the clock-in time in the specified clock-in period of each historical working day on the weather data based on the difference between the historical clock-in time of all employees in the specified clock-in period of each historical working day and the specified clock-in time, and determining the work clock-in punctuality of each employee based on the overall impact and the historical clock-in time of each employee in the specified clock-in period of each historical working day;

[0128] Step S300: determining the time planning regularity index of each employee according to the work clock-in punctuality and the distribution of each employee's historical clock-in time in the prescribed clock-in period of all historical working days, and the difference between each employee's historical clock-in time and the prescribed clock-in time in the prescribed clock-in period of all historical working days;

[0129] Step S400: Obtain the clock-in-affecting weather data of each employee in the specified clock-in section of the current working day, and determine the clock-in reminder reference time of each employee in the specified clock-in section of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the specified clock-in section of all historical working days, and the difference between the clock-in-affecting weather data corresponding to the specified clock-in section of the current working day and each historical working day;

[0130] Step S500: Remind each employee to punch in according to the punch in reminder reference time.

[0131] Based on the same inventive concept, the embodiment of the present invention also provides an IoT smart card-punching terminal, such as Figure 7 As shown, the terminal includes: a memory 101, a processor 102, and a computer program 103 stored in the memory 101 and running on the processor 102, wherein when the processor 102 executes the computer program 103, the system can execute the implementation steps of each module in any one of the IoT smart check-in terminals introduced above.

[0132] Based on the same inventive concept, an embodiment of the present invention also provides a computer program product, which includes: computer program code, when the computer program code runs on a computer, the computer executes the implementation steps of each module in any one of the IoT smart check-in terminals introduced above.

[0133] Based on the same inventive concept, an embodiment of the present invention also provides a computer-readable storage medium, which stores computer program code. When the computer program code runs on a computer, the computer executes the implementation steps of each module in any one of the IoT smart check-in terminals introduced above.

[0134] It should be noted that the above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. An IoT smart check-in terminal, characterized in that: include: The data acquisition module is used to obtain the historical clock-in time of each employee in the specified clock-in period of each historical working day in the past set period and the corresponding clock-in-affecting weather data; The work punch-in punctuality acquisition module is used to: determine the overall impact of the punch-in time in the specified punch-in period of each historical working day on the weather data based on the difference between the historical punch-in time of all employees in the specified punch-in period of each historical working day and the specified punch-in time, and determine the work punch-in punctuality of each employee based on the overall impact and the historical punch-in time of each employee in the specified punch-in period of each historical working day; A regularity index acquisition module is used to determine the time planning regularity index of each employee according to the work punch-in punctuality and the distribution of each employee's historical punch-in time in the prescribed punch-in period of all historical working days, and the difference between each employee's historical punch-in time and the prescribed punch-in time in the prescribed punch-in period of all historical working days; The clock-in reminder reference time acquisition module is used to: obtain the clock-in-affecting weather data of each employee in the specified clock-in period of the current working day, and determine the clock-in reminder reference time of each employee in the specified clock-in period of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the specified clock-in period of all historical working days, and the difference between the clock-in-affecting weather data corresponding to the specified clock-in period of the current working day and each historical working day; A clock-in reminder module is used to: remind each employee to clock in according to the clock-in reminder reference time; Determine the overall impact of the clock-in period on the weather data for each historical working day, including: According to the difference between the historical punch-in time and the prescribed punch-in time of all employees in the prescribed punch-in period of each historical working day, determine the number of late employees on each historical working day and the punch-in time difference of each employee in the prescribed punch-in period of each historical working day; According to the proportion of late employees in all employees on each historical working day and the distribution of the time difference of all employees in the prescribed punch-in period on each historical working day, the overall impact of the punch-in period on the weather data on each historical working day is determined. The corresponding calculation formula is: ； in, Indicates The overall impact of clocking in during the specified clocking-in period on weather data on a historical working day; Indicates The number of employees who were late during the prescribed punch-in period of each historical working day; Indicates The number of all employees on each historical workday; Indicates Employees in The time difference between the clock-in time periods of the specified clock-in periods of the historical working days; It represents the exponential function with the natural constant e as the base; Determine each employee's work clock-in punctuality, including: Arrange the overall impact degree of the clock-in time in the specified clock-in period on the weather data of all historical working days in order of magnitude to obtain the overall impact degree sequence; According to the overall impact degree sequence, the historical punch-in time of each employee in the specified punch-in period of all historical working days is arranged accordingly to obtain the historical punch-in time sequence of each employee; Determine the work clocking-in punctuality of each employee according to the correlation between the overall impact degree series and the historical clocking-in time series; Determine each employee's work clock-in punctuality, including: Determine the correlation index between the overall impact degree series and the historical punch-in time series; Perform negative correlation mapping processing on the related indicators to obtain the work clocking-in punctuality of each employee; Determine each employee's time planning regularity indicators, including: Determine the representative value of the historical clock-in time of each employee in the specified clock-in period of all historical working days according to the average distribution of the historical clock-in time of each employee in the specified clock-in period of all historical working days; According to the difference between the historical punch-in time and the prescribed punch-in time of each employee in the prescribed punch-in period of all historical working days, determine the number of lateness of each employee in all historical working days, the representative value of lateness time, and the punch-in time difference in the prescribed punch-in period of each historical working day; According to the work punch-in punctuality, historical punch-in time representative value, number of lateness, representative value of lateness time and the difference between the punch-in time difference of each employee in the specified punch-in period of different historical working days, the time planning regularity index of each employee is determined, and the corresponding calculation formula is: ； in, Indicates Indicators of regularity in time planning for employees; Indicates The punctuality of employees in clocking in at work; Indicates The representative value of the historical punch-in time of an employee in the specified punch-in period of all historical working days; Indicates The number of times an employee was late on all historical working days; Indicates The representative value of the employee's lateness time in all historical working days, L indicates the occurrence of a lateness mark; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates The total number of historical workdays for employees; Determine the reference time for each employee's punch-in reminder during the specified punch-in period of the current workday, including: Determine the weight value of the specified punch-in segment of each historical working day according to the difference between the punch-in-affecting weather data corresponding to the specified punch-in segment of the current working day and each historical working day; According to the weight value and the historical clock-in time of each employee in the specified clock-in period of all historical working days, the clock-in time of each employee in the specified clock-in period of the current working day is predicted to obtain the predicted clock-in time of each employee in the specified clock-in period of the current working day; According to the time planning regularity index, the predicted value of the clock-in time of each employee in the specified clock-in period of the current working day is corrected to obtain the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

2. The IoT smart card-punching terminal according to claim 1, characterized in that: Correct the predicted time of each employee in the specified punch-in period of the current working day to obtain the punch-in reminder reference time of each employee in the specified punch-in period of the current working day, including: Performing positive correlation normalization processing on the time planning regularity index to obtain a correction coefficient of the predicted value of the punch-in time of each employee in the specified punch-in period of the current working day; The product of the predicted clock-in time of each employee in the specified clock-in period of the current working day and its correction coefficient is calculated, and the product value is used as the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

3. The IoT smart check-in terminal according to claim 1, characterized in that: Determine the weight value of the required punch-in segment for each historical working day, including: Determine the difference index value according to the difference between the clock-in-affected weather data corresponding to the specified clock-in period on the current working day and each historical working day; The difference index value is negatively mapped to obtain a proximity index value, and the proximity index value corresponding to each historical working day is normalized to obtain the weight value of the specified punch-in segment of each historical working day, and the sum of the weight values ​​of the specified punch-in segments of all historical working days is equal to 1.

4. The IoT smart card-punching terminal according to claim 1, characterized in that: Provide punch-in reminders to each employee, including: For any employee, if the employee does not punch in before the corresponding punch-in reminder reference time, the employee will be reminded to punch in after the corresponding punch-in reminder reference time and before the specified punch-in time.

5. A method for reminding a smart clock-in terminal of the Internet of Things, characterized in that: The method includes: Get the historical clock-in time of each employee in the specified clock-in period of each historical working day in the past set period and the corresponding clock-in-affecting weather data; Determine the overall impact of clocking in during the prescribed clocking-in period of each historical working day on weather data based on the difference between the historical clocking-in time of all employees during the prescribed clocking-in period of each historical working day and the prescribed clocking-in time, and determine the punctuality of each employee's clocking-in during the prescribed clocking-in period of each historical working day based on the overall impact and the historical clocking-in time of each employee during the prescribed clocking-in period of each historical working day; Determine the time planning regularity index of each employee according to the work clocking-in punctuality and the distribution of each employee's historical clocking-in time in the prescribed clocking-in period of all historical working days, and the difference between each employee's historical clocking-in time and the prescribed clocking-in time in the prescribed clocking-in period of all historical working days; Obtain the clock-in-affecting weather data of each employee in the prescribed clock-in period of the current working day, and determine the clock-in reminder reference time of each employee in the prescribed clock-in period of the current working day according to the time planning regularity index and the historical clock-in time of each employee in the prescribed clock-in period of all historical working days, and the difference between the clock-in-affecting weather data corresponding to the prescribed clock-in period of the current working day and each historical working day; Remind each employee to punch in based on the punch in reminder reference time; Determine the overall impact of the clock-in period on the weather data for each historical working day, including: According to the difference between the historical punch-in time and the prescribed punch-in time of all employees in the prescribed punch-in period of each historical working day, determine the number of late employees on each historical working day and the punch-in time difference of each employee in the prescribed punch-in period of each historical working day; According to the proportion of late employees in all employees on each historical working day and the distribution of the time difference of all employees in the prescribed punch-in period on each historical working day, the overall impact of the punch-in period on the weather data on each historical working day is determined. The corresponding calculation formula is: ； in, Indicates The overall impact of clocking in during the specified clocking-in period on weather data on a historical working day; Indicates The number of employees who were late during the prescribed punch-in period of each historical working day; Indicates The number of all employees on each historical workday; Indicates Employees in The time difference between the clock-in time periods of the specified clock-in periods of the historical working days; It represents the exponential function with the natural constant e as the base; Determine each employee's work clock-in punctuality, including: Arrange the overall impact degree of the clock-in time in the specified clock-in period on the weather data of all historical working days in order of magnitude to obtain the overall impact degree sequence; According to the overall impact degree sequence, the historical punch-in time of each employee in the specified punch-in period of all historical working days is arranged accordingly to obtain the historical punch-in time sequence of each employee; Determine the work clocking-in punctuality of each employee according to the correlation between the overall impact degree series and the historical clocking-in time series; Determine each employee's work clock-in punctuality, including: Determine the correlation index between the overall impact degree series and the historical punch-in time series; Perform negative correlation mapping processing on the related indicators to obtain the work clocking-in punctuality of each employee; Determine each employee's time planning regularity indicators, including: Determine the representative value of the historical clock-in time of each employee in the specified clock-in period of all historical working days according to the average distribution of the historical clock-in time of each employee in the specified clock-in period of all historical working days; According to the difference between the historical punch-in time and the prescribed punch-in time of each employee in the prescribed punch-in period of all historical working days, determine the number of lateness of each employee in all historical working days, the representative value of lateness time, and the punch-in time difference in the prescribed punch-in period of each historical working day; According to the work punch-in punctuality, historical punch-in time representative value, number of lateness, representative value of lateness time and the difference between the punch-in time difference of each employee in the specified punch-in period of different historical working days, the time planning regularity index of each employee is determined, and the corresponding calculation formula is: ； in, Indicates Indicators of regularity in time planning for employees; Indicates The punctuality of employees in clocking in at work; Indicates The representative value of the historical punch-in time of an employee in the specified punch-in period of all historical working days; Indicates The number of times an employee was late on all historical working days; Indicates The representative value of the employee's lateness time in all historical working days, L indicates the occurrence of a lateness mark; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates Employees in The difference between the clock-in time and the clock-in time of historical working days; Indicates The total number of historical workdays for employees; Determine the reference time for each employee's punch-in reminder during the specified punch-in period of the current workday, including: Determine the weight value of the specified punch-in segment of each historical working day according to the difference between the punch-in-affecting weather data corresponding to the specified punch-in segment of the current working day and each historical working day; According to the weight value and the historical clock-in time of each employee in the specified clock-in period of all historical working days, the clock-in time of each employee in the specified clock-in period of the current working day is predicted to obtain the predicted clock-in time of each employee in the specified clock-in period of the current working day; According to the time planning regularity index, the predicted value of the clock-in time of each employee in the specified clock-in period of the current working day is corrected to obtain the clock-in reminder reference time of each employee in the specified clock-in period of the current working day.

Images