A Blockchain-Based Attendance Record Method, Device, and Medium

Abstract

The present application discloses an attendance record method, device and medium based on blockchain. The method includes: an attendance node receives an attendance request from an employee and determines the attendance method selected by the employee based on the attendance node; according to the attendance method, identify the employee; according to the historical attendance records of the employee in the pre-created blockchain, determine the personal attendance pattern of the employee; if the identification result of the identity identification does not conform to the personal attendance pattern, determine the group to which the employee belongs; determine the group attendance pattern of the group; if the identification result conforms to the group attendance pattern, use the identification result as the attendance record of the employee on the day and write it into the blockchain. The decentralization and immutability characteristics of the blockchain are used to supervise the attendance information, which effectively avoids the disadvantages of manual supervision. And during the attendance process, it is no longer only based on the established attendance strategy for attendance, but can quickly make adaptive adjustments in case of emergencies.

Description

Technical Field

[0001] The present application relates to the field of blockchain, and specifically to an attendance recording method, device and medium based on blockchain. Background Art

[0002] With the development of technology, people's lives have gradually become information-based, and the attendance management of employees in various companies has also entered an information-based management mode.

[0003] In the prior art, employees use attendance equipment to record their attendance, and then the attendance equipment obtains the employee's attendance record based on factors such as the employee's attendance time, and stores it in a database of the enterprise or a third party.

[0004] However, the existing technology will cause the following two problems:

[0005] 1. The attendance information of employees is stored in a fixed database and needs to be maintained and supervised manually. This makes it easy for some employees to steal information by modifying their attendance information or reporting false attendance information, which results in unfair attendance and even infringes on the interests of the company.

[0006] 2. During the attendance process, employees are often only checked based on the established attendance strategy. When encountering emergencies, it is difficult to make adaptive adjustments in a timely manner, making the attendance strategy inflexible. Summary of the invention

[0007] In order to solve the above problems, the present application proposes a blockchain-based attendance recording method, comprising: an attendance node receives an employee's attendance request, and determines the attendance method selected by the employee based on the attendance node; according to the attendance method, the employee is identified; according to the employee's historical attendance record in a pre-created blockchain, the employee's personal attendance rule is determined; if the identification result of the identity identification does not conform to the personal attendance rule, the group to which the employee belongs is determined according to the label generated in advance for the employee; according to the historical attendance record of the group on the day in the blockchain, the group attendance rule of the group is determined; if the identification result conforms to the group attendance rule, the identification result is written into the blockchain as the employee's attendance record on the day.

[0008] In one example, determining the personal attendance pattern of the employee based on the historical attendance records of the employee in the pre-created blockchain specifically includes: collecting the historical attendance records of the employee within a preset time period in the pre-created blockchain; determining the average attendance time, the selected attendance method, and the selected attendance terminal of the employee according to the historical attendance records; encoding the average attendance time, the selected attendance method, and the selected attendance terminal respectively, and obtaining the personal attendance pattern of the employee according to each encoding result.

[0009] In one example, encoding the average attendance time, the selected attendance method, and the selected attendance terminal respectively specifically includes: calculating the difference between the average attendance time and the specified attendance time, and normalizing the difference to obtain a first encoding result; determining the selected attendance method with the highest usage frequency of the employee, and determining the corresponding second encoding result according to a preset mapping relation table, in which the difference between the encoding results corresponding to different attendance methods is negatively correlated with the similarity degree between the different attendance methods; and determining the most frequently used selected attendance terminal of the employee, and determining the corresponding third encoding result according to the usage ratio of the most frequently used selected attendance terminal.

[0010] In one example, determining the group attendance pattern of the group based on the historical attendance records of the group in the blockchain specifically includes: determining the recognition results of the personal attendance patterns of the employees in the group for themselves in the blockchain; determining the current attendance compliance rate of the group according to the recognition results corresponding to the respective employees, and using the attendance compliance rate as the group attendance pattern of the group; the recognition result conforming to the group attendance pattern specifically includes: if it is determined that the attendance compliance rate is lower than a preset threshold, then it is determined that the recognition result conforms to the group attendance pattern.

[0011] In one example, the method further includes: receiving a make-up card request sent by an employee node through the blockchain; selecting several employee nodes from the employee nodes whose recognition results on the same day already conform to the personal attendance pattern as consensus nodes; broadcasting the make-up card request to the consensus nodes to perform a consensus process on the make-up card request through the consensus nodes; if the make-up card request passes the consensus process, putting the make-up card request into the data pool.

[0012] In one example, after putting the replacement card request into the data pool, the method further includes: determining, during the consensus process, a designated employee node that negates the replacement card request; selecting at least one node from other employee nodes except the designated employee node as the bookkeeping node; and writing the replacement card request in the data pool into the blockchain through the bookkeeping node.

[0013] In one example, the method of selecting several employee nodes as consensus nodes from the employee nodes whose recognition results on the same day already conform to the individual attendance rules through the blockchain specifically includes: determining, through the blockchain, a first employee node whose recognition result on the same day already conforms to the individual attendance rules; and selecting several second employee nodes belonging to different groups from them as consensus nodes according to the labels previously generated for the first employee node.

[0014] In one example, after determining the group attendance rule of the group according to the historical attendance record of the group on the same day in the blockchain, the method further includes: if the recognition result does not conform to the group attendance rule, generating other attendance methods with a higher identity recognition level and performing identity recognition on the employee through the other attendance methods.

[0015] On the other hand, the present application also proposes an attendance record device based on blockchain, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to: receive an attendance request of an employee by an attendance node and determine the attendance method selected by the employee based on the attendance node; perform identity recognition on the employee according to the attendance method; determine the individual attendance rule of the employee according to the historical attendance record of the employee in the pre-created blockchain; if the recognition result of the identity recognition does not conform to the individual attendance rule, determine the group to which the employee belongs according to the label previously generated for the employee; determine the group attendance rule of the group according to the historical attendance record of the group on the same day in the blockchain; and if the recognition result conforms to the group attendance rule, write the recognition result into the blockchain as the attendance record of the employee on the same day.

[0016] On the other hand, the present application also proposes a non-volatile computer storage medium storing computer-executable instructions, and the computer-executable instructions are set as follows: an attendance node receives an attendance request from an employee and determines the attendance method selected by the employee based on the attendance node; performs identity verification on the employee according to the attendance method; determines the personal attendance pattern of the employee according to the historical attendance records of the employee in a pre-created blockchain; if the verification result of the identity verification does not conform to the personal attendance pattern, determines the group to which the employee belongs according to a label pre-generated for the employee; determines the group attendance pattern of the group according to the historical attendance records of the group on the current day in the blockchain; if the verification result conforms to the group attendance pattern, writes the verification result as the attendance record of the employee on the current day into the blockchain.

[0017] The attendance record method based on blockchain proposed by the present application can bring the following beneficial effects:

[0018] Using the decentralized and immutable characteristics of blockchain to supervise attendance information can effectively avoid the drawbacks of manual supervision, prevent operations such as modification or deletion of attendance information by individual personnel, improve the fairness of attendance, strengthen the enterprise's supervision of its employees' attendance, and utilize the sharing nature of blockchain to enable leaders to quickly and deeply understand the attendance situation of their employees. Using the traceable characteristic of blockchain, the attendance records of employees and individuals can be viewed, and the encryption of blockchain effectively prevents the leakage of personal information. And during the attendance process, it is no longer only based on the established attendance strategy for attendance, but when encountering unexpected situations, the attendance records of the group are synchronously considered. If the entire group shows a situation that does not conform to the personal attendance pattern (for example, the enterprise's Wi-Fi fails and employees can only use other methods for attendance), it can also be quickly adjusted adaptively, and there will be no situation where employees have abnormal attendance due to external reasons. Description of the Drawings

[0019] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation of the present application. In the drawings:

[0020] Figure 1 is a schematic flowchart of the attendance record method based on blockchain in an embodiment of the present application;

[0021] Figure 2 is a schematic diagram of the attendance record device based on blockchain in an embodiment of the present application. Detailed Embodiments

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments of this application and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without creative efforts shall fall within the scope of protection of this application.

[0023] The technical solutions provided by each embodiment of this application will be described in detail below in conjunction with the drawings.

[0024] As Figure 1 shown, the embodiment of this application provides an attendance record method based on blockchain, including:

[0025] S101: The attendance node receives the employee's attendance request and determines the attendance method selected by the employee based on the attendance node.

[0026] A blockchain is pre-created. Essentially, it is a shared database. The data or information stored therein has the characteristics of being non-forgeable, leaving a complete trace throughout the process, being traceable, publicly transparent, and collectively maintained. Multiple nodes are deployed in the blockchain, and the attendance device can be deployed as one of the nodes. The attendance node refers to the attendance device used by the employee, which can be the employee's personal smartphone or the face recognition device, fingerprint device, etc. set within the enterprise.

[0027] The attendance method varies according to the different attendance nodes and the choices of employees. It can include: face recognition attendance, fingerprint attendance, Wi-Fi attendance, Bluetooth attendance, location attendance, etc. In addition to the above, the attendance method can also include information such as common attendance devices.

[0028] S102: Identify the employee's identity according to the attendance method.

[0029] The method of identity recognition varies according to the different attendance methods selected by the employee. For example, when the employee selects face recognition attendance, the attendance node collects the employee's face image, and then identifies the employee's identity through face recognition. Finally, the attendance can be achieved through the identity recognition result and the positioning information of the employee.

[0030] S103: Determine the personal attendance pattern of the employee according to the historical attendance record of the employee in the pre-created blockchain.

[0031] When the employee completes the attendance, it is written into the pre-created blockchain. Therefore, the historical attendance record corresponding to the employee can be collected in the blockchain, and the personal attendance pattern of the employee can be determined from it. The personal attendance pattern can include various contents, or be composed of a combination of various contents through coding.

[0032] Specifically, in the blockchain, the historical attendance records of the employee within a preset time period are collected. For example, the historical attendance records in the recent period (within one month, or within one week, etc.) can be collected. Then, based on the historical attendance records, multiple attendance contents of the employee are determined, such as the average attendance time, the selected attendance method, and the selected attendance terminal. The average attendance time refers to the average of each attendance time of the employee within the preset time period. The selected attendance method is the attendance method chosen by the employee, and the selected attendance terminal refers to the attendance node used by the employee for each attendance. If all this information is stored and compared, a large amount of computing resources will be consumed. Therefore, by encoding the average attendance time, the selected attendance method, and the selected attendance terminal respectively to obtain the corresponding encoding results, and then obtaining the personal attendance pattern based on the encoding results, it is possible to reduce the use of computing resources while still reflecting the personal attendance pattern of the employee.

[0033] Furthermore, different encoding processes can be selected for different contents.

[0034] Regarding the average attendance time, first, the difference between the average attendance time and the specified attendance time is determined, and then the difference is normalized to obtain the first encoding result. For example, if the specified attendance time is 9:00 am and the average attendance time is 8:30 am, the difference is 30 minutes at this time. Normalizing it with 1 hour as 1 basic unit, the first encoding result is 0.5.

[0035] Regarding the selected attendance method, according to the usage frequency of various attendance methods, the selected attendance method with the highest usage frequency is first determined, and then the corresponding second encoding result is determined according to the preset mapping relation table. In the mapping relation table, the encoding results between more relevant attendance methods are closer, that is, the difference between the encoding results corresponding to different attendance methods is negatively correlated with the similarity degree between different attendance methods. For example, the second encoding results corresponding to Bluetooth, Wi-Fi, and fingerprint are 0.1, 0.2, and 0.5 respectively. Both Bluetooth and Wi-Fi punching methods can be used to punch the card through the smartphone terminal, while fingerprint can only be used through the relevant fingerprint device, and its similarity to the previous two methods is relatively low, so the difference between the corresponding second encoding results is relatively large.

[0036] Regarding the selected attendance terminal, first, the most frequently used selected attendance terminal of the employee is determined, and then its usage ratio is determined, and this usage ratio can be used as the third encoding result.

[0037] At this time, after three coding results are determined, these three coding results can be used to represent the personal attendance pattern of the employee. When determining whether it conforms, coding can be performed based on the attendance time of this attendance record, the selected attendance method, and the selected attendance terminal (for the selected attendance terminal, if the employee selects the most frequently used attendance terminal, it is coded as 1; otherwise, it is coded as 0), and the differences are obtained respectively according to the coding. If the sum of the three differences exceeds the preset threshold, it is considered that it does not conform to the personal attendance pattern.

[0038] It should be noted that the process corresponding to S103 can be carried out after the employee's identity is recognized, or after the recognition result of the identity recognition triggers a preset condition (for example, the recognition result is successful). Of course, historical attendance records of each employee can also be collected in advance, and the judgment of the personal attendance pattern can be made and stored in the blockchain.

[0039] S104: If the recognition result of the identity recognition does not conform to the personal attendance pattern, determine the group to which the employee belongs according to the label pre-generated for the employee.

[0040] As described above, how to judge whether the recognition result of the identity recognition (the recognition result here not only includes whether the identity recognition of the employee is successful, but also includes the attendance time, the selected attendance method, the selected attendance terminal, etc., all of which are part of the content of the employee's identity recognition) conforms to the personal attendance pattern. If it conforms, the recognition result can be written into the blockchain as an attendance record. If it does not conform, it is not immediately considered that the assessment is not carried out by the employee himself, but the group to which the employee belongs is further judged to reduce the situation where the employee's attendance does not conform to the personal attendance pattern due to external factors.

[0041] The label is pre-generated for the employee and can include various categories. For example, it includes the enterprise to which the employee belongs, the department to which the employee belongs, the range of the family's affiliated area, etc. Generally speaking, the commonality of employees in an enterprise or a department is higher. Therefore, the group to which the employee belongs is determined according to the enterprise, department, etc. where the employee is located.

[0042] S105: Determine the group attendance pattern of the group according to the historical attendance records of the group on the same day in the blockchain.

[0043] When determining the group attendance pattern, instead of relying on the historical attendance records over a period of time, only the historical attendance records on the same day are used as the group attendance pattern of the group on the same day.

[0044] Specifically, the recognition results of each employee in the group regarding their own personal attendance patterns can be determined. The recognition results at least include whether the employee conforms to the personal attendance pattern. Then, the attendance compliance rate of the group on that day can be determined based on this, and this attendance compliance rate can be used as the group attendance pattern.

[0045] S106: If the recognition result conforms to the group attendance pattern, then use the recognition result as the attendance record of the employee on that day and write it into the blockchain.

[0046] When the group attendance pattern is the attendance compliance rate, if the attendance compliance rate is lower than the preset threshold, it is considered that the recognition result of the employee conforms to the group attendance pattern, and it is written into the blockchain as the attendance record on that day.

[0047] Utilize the decentralized and immutable characteristics of the blockchain to supervise attendance information. This effectively avoids the drawbacks of manual supervision, prevents operations such as individual personnel modifying or deleting attendance information, improves the fairness of attendance, strengthens the enterprise's supervision of its employees' attendance. By using the sharing feature of the blockchain, each leader can quickly and deeply understand the attendance situation of their employees. The traceable feature of the blockchain can be used to view the attendance records of employees and individuals, and the encryption feature of the blockchain effectively prevents the leakage of personal information. And during the attendance process, it is no longer only based on the established attendance policy for attendance. Instead, when encountering unexpected situations, the attendance records of the group are considered synchronously. If the entire group fails to conform to the personal attendance pattern (for example, the enterprise's Wi-Fi fails and employees can only use other methods for attendance), it can also be quickly adjusted adaptively, and there will be no situation where employees have abnormal attendance due to external reasons.

[0048] In one embodiment, during the attendance process, if an employee fails to attend due to forgetting or other reasons within the specified time, they can make up the card. At this time, the employee can be used as a node in the blockchain, and the employee node sends a card - making - up request to the blockchain. After the blockchain receives the card - making - up request, among the employee nodes whose recognition results conform to the personal attendance pattern on that day, several employee nodes are selected as consensus nodes. At this time, the practical Byzantine PBFT can be used as the consensus mechanism. Then, the card - making - up request is broadcast to these consensus nodes, and the consensus nodes return the consensus result, thereby realizing the consensus process for the card - making - up request. If the consensus process is passed (for example, more than the preset proportion of employee nodes affirm the card - making - up request), then the card - making - up request is put into the data pool. Using other employee nodes that have already conformed to the personal attendance pattern as consensus nodes can achieve mutual proof among employees and improve the effectiveness of the card - making - up request during proof.

[0049] Further, during the consensus process, not all consensus nodes will affirm the card replacement request. There may be some employee nodes that believe the employee's current card replacement request should not be approved, thus negating the card replacement request (hereinafter referred to as designated employee nodes). However, in the final result, the consensus nodes that affirm the employee's card replacement request still account for a large proportion, and the card replacement request is approved. At this time, among the other employee nodes except the designated employee nodes, at least one node is selected as the accounting node, and the card replacement request in the data pool is written into the blockchain. Thus, it can prevent the employee nodes that express negation from being the accounting nodes, so that the employee who sends the card replacement request can know who negated their own card replacement request, protecting the privacy of the employees and improving the enthusiasm of employees to correct unreasonable card replacement requests.

[0050] In addition, when selecting consensus nodes, the first employee nodes whose recognition results meet the personal attendance rules on the same day can be determined first, and then several second employee nodes belonging to different groups are selected from them as consensus nodes according to the labels of the first employee nodes. If only the employee nodes within one group are selected when selecting consensus nodes, it is easy for the final consensus result to be inaccurate due to human feelings. By expanding the selection range and choosing consensus nodes from different groups, the accuracy of the consensus result can be further ensured.

[0051] In one embodiment, if the recognition result is finally determined not to conform to the group attendance rules, other attendance methods with a higher identity recognition level can be generated to identify the employees. For example, if an employee uses Wi-Fi as the attendance method, which is different from their usual attendance method of fingerprint, there is a risk of someone else impersonating them for attendance, and they also do not conform to the group attendance rules, then other attendance methods with a higher identity recognition level are generated, such as attendance by face recognition or fingerprint recognition, so as to avoid the situation of other employees impersonating for attendance.

[0052] As Figure 2 shown, the embodiment of the present application also provides an attendance record device based on blockchain, including:

[0053] At least one processor; and,

[0054] A memory communicatively connected to the at least one processor; wherein,

[0055] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute:

[0056] The attendance node receives the attendance request of the employee and determines the attendance method selected by the employee based on the attendance node;

[0057] Identify the identity of the employee according to the attendance method;

[0058] Determine the personal attendance pattern of the employee according to the historical attendance records of the employee in the pre-created blockchain;

[0059] If the identification result of the identity identification does not conform to the personal attendance pattern, determine the group to which the employee belongs according to the label pre-generated for the employee;

[0060] Determine the group attendance pattern of the group according to the historical attendance records of the group on the current day in the blockchain;

[0061] If the identification result conforms to the group attendance pattern, write the identification result as the attendance record of the employee on the current day into the blockchain.

[0062] The embodiments of the present application also provide a non-volatile computer storage medium storing computer-executable instructions, and the computer-executable instructions are set as:

[0063] The attendance node receives the attendance request of the employee and determines the attendance method selected by the employee based on the attendance node;

[0064] Identify the identity of the employee according to the attendance method;

[0065] Determine the personal attendance pattern of the employee according to the historical attendance records of the employee in the pre-created blockchain;

[0066] If the identification result of the identity identification does not conform to the personal attendance pattern, determine the group to which the employee belongs according to the label pre-generated for the employee;

[0067] Determine the group attendance pattern of the group according to the historical attendance records of the group on the current day in the blockchain;

[0068] If the identification result conforms to the group attendance pattern, write the identification result as the attendance record of the employee on the current day into the blockchain.

[0069] The various embodiments in the present application are all described in a progressive manner. The same or similar parts among the various embodiments can be referred to each other, and the key points described in each embodiment are the differences from other embodiments. In particular, for the device and medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiments.

[0070] The devices, media, and methods provided by the embodiments of the present application correspond one-to-one. Therefore, the devices and media also have beneficial technical effects similar to those of their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be elaborated here.

[0071] Those skilled in the art should understand that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program code.

[0072] The present application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, such that the instructions executed by the processor of the computer or other programmable data processing devices generate means for implementing the specified functions in Figure 1 one or more of the flows Figure 1 or a combination of multiple flows and / or blocks

[0073] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, such that the instructions stored in the computer-readable memory generate a manufactured article including instruction means that implement the specified functions in Figure 1 one or more of the flows Figure 1 or a combination of multiple flows and / or blocks

[0074] These computer program instructions can also be loaded onto a computer or other programmable data processing device, such that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the specified functions in Figure 1 one or more of the flows Figure 1 or a combination of multiple flows and / or blocks

[0075] In a typical configuration, a computing device includes one or more processors (CPUs), an input / output interface, a network interface, and a memory.

[0076] The memory may include non-permanent memory in the form of computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. The memory is an example of computer-readable media.

[0077] Computer-readable media includes permanent and non-permanent, removable and non-removable media that can store information by any method or technology. The information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transitory media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media, such as modulated data signals and carrier waves.

[0078] It should also be noted that the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device. Without further limitation, an element defined by the statement "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising the element.

[0079] The above description is only for the embodiments of the present application and is not intended to limit the present application. For those skilled in the art, various changes and modifications can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the scope of the claims of the present application.

Claims

1. An attendance record method based on blockchain, characterized in that, Including: The attendance node receives the employee's attendance request and determines the attendance method selected by the employee based on the attendance node; Perform identity verification on the employee according to the attendance method; Determine the personal attendance pattern of the employee according to the historical attendance records of the employee in the pre-created blockchain; If the verification result of the identity verification does not conform to the personal attendance pattern, determine the group to which the employee belongs according to the label pre-generated for the employee; Determine the group attendance pattern of the group according to the historical attendance records of the group on the current day in the blockchain; If the verification result conforms to the group attendance pattern, write the verification result as the attendance record of the employee on the current day into the blockchain; The step of determining the personal attendance pattern of the employee according to the historical attendance records of the employee in the pre-created blockchain specifically includes: In the pre-created blockchain, collect the historical attendance records of the employee within a preset time period; Determine the average attendance time, the selected attendance method, and the selected attendance terminal of the employee according to the historical attendance records; Encode the average attendance time, the selected attendance method, and the selected attendance terminal respectively, and obtain the personal attendance pattern of the employee according to each encoding result; The step of encoding the average attendance time, the selected attendance method, and the selected attendance terminal respectively specifically includes: Calculate the difference between the average attendance time and the specified attendance time, and normalize the difference to obtain the first encoding result; and Determine the attendance method with the highest usage frequency by the employee, and determine the corresponding second encoding result according to the preset mapping relation table; in the mapping relation table, the difference between the encoding results corresponding to different attendance methods is negatively correlated with the similarity degree between the different attendance methods; and Determine the most frequently used attendance terminal of the employee, and determine the corresponding third encoding result according to the usage ratio of the most frequently used attendance terminal; Realize the encoding of the average attendance time, the selected attendance method, and the selected attendance terminal respectively according to the first encoding result, the second encoding result, and the third encoding result; The step of determining the group attendance pattern of the group according to the historical attendance records of the group on the current day in the blockchain specifically includes: In the blockchain, determine the verification results of the personal attendance patterns of the employees in the group for themselves; Determine the current attendance compliance rate of the group according to the verification results corresponding to the respective employees, and use the attendance compliance rate as the group attendance pattern of the group; The verification result conforming to the group attendance pattern specifically includes: If it is determined that the attendance compliance rate is lower than the preset threshold, it is determined that the verification result conforms to the group attendance pattern.

2. The method according to claim 1, characterized in that, The method further includes: Receive the make-up card request sent by the employee node through the blockchain; Among the employee nodes whose verification results on the current day already conform to the personal attendance pattern, select several employee nodes as consensus nodes; Broadcast the card replacement request to the consensus nodes so that the consensus nodes can conduct a consensus process on the card replacement request; If the card replacement request passes the consensus process, put the card replacement request into the data pool.

3. The method according to claim 2, wherein After putting the card replacement request into the data pool, the method further includes: Determine the designated employee nodes that negate the card replacement request during the consensus process; Select at least one node from other employee nodes except the designated employee nodes as the accounting node; Write the card replacement request in the data pool into the blockchain through the accounting node.

4. The method according to claim 2, wherein The method of selecting several employee nodes as consensus nodes from the employee nodes whose recognition results conform to the individual attendance rules on the same day through the blockchain specifically includes: Determine the first employee node whose recognition result conforms to the individual attendance rules on the same day through the blockchain; Select several second employee nodes belonging to different groups as consensus nodes according to the labels pre-generated for the first employee node.

5. The method according to claim 1, characterized in that, After determining the group attendance rules of the group according to the historical attendance records of the group on the same day in the blockchain, the method further includes: If the recognition result does not conform to the group attendance rules, generate other attendance methods with a higher identity recognition level and conduct identity recognition on the employee through the other attendance methods.

6. An attendance record device based on blockchain, characterized in that, including: At least one processor; And, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute: the blockchain-based attendance record method according to claim 1.

7. A non-volatile computer storage medium stores computer-executable instructions, characterized in that, The computer-executable instructions are set to: the blockchain-based attendance record method according to claim 1.

Images