CN112507972A - Performance assessment system based on block chain - Google Patents
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Abstract
The invention relates to the technical field of performance assessment, in particular to a performance assessment system based on a block chain, which comprises: the input unit is used for uploading the work record of each employee; the statistical unit is used for the staff to check the work records in the block chain and score according to the work records to obtain a scoring table; the judging unit is used for comparing the effective working time with the preset rated working time to obtain a comparison result, and judging whether the score in the score table is effective or not according to the comparison result; the correcting unit is used for analyzing the reasonable working time length of the monitoring video, the working state of which meets the preset requirement, and correcting the effective score according to the reasonable working time length and the effective working time length to obtain a corrected score table; and the output unit is used for outputting the corrected scoring table in a visual mode. The invention solves the technical problems that the prior art can only qualitatively assess the performance of the staff and can not quantitatively assess the performance of the staff.
Description
Technical Field
The invention relates to the technical field of performance assessment, in particular to a performance assessment system based on a block chain.
Background
Performance assessment is an extremely important ring in human resource management, both for enterprises and factories. The good performance assessment method can effectively play a role in excitation, avoids the waste of human resources and further reduces the human cost. At present, common performance assessment methods comprise a balance scorecard, key performance indicators and the like, and the performance assessment methods are low in transparency, and data are easy to tamper, so that the reliability is low.
The development of the block chain technology provides a new idea for establishing a performance assessment method which is high in transparency and reliability and data are not easy to tamper. For example, chinese patent CN111275395A discloses a decentralized enterprise performance assessment method based on block chain, which includes the steps of: building a private block chain inside a company; each employee becomes a user node in the blockchain; uploading information such as monthly work records, attendance records and the like of each employee to a block chain; the employees mutually check the work records of other people in the block chain, and mutually score the work conditions of other people; and the scoring table is used as a performance assessment score result, is summarized and stored in the block chain and cannot be tampered.
In the technical scheme, the employees mutually score the working conditions of each other, the obtained scoring table is used as a performance assessment score result, and the performance assessment score result is collected and stored in a block chain. However, employees often do not have an accurate understanding of each other's workload, and even if it is known, it is often a rough and approximate understanding, which makes scoring among employees impossible to accurately reflect the corresponding workload. That is, the prior art can only qualitatively assess the performance of the staff, but cannot quantitatively assess the performance of the staff.
Disclosure of Invention
The invention provides a performance assessment system based on a block chain, which solves the technical problem that the prior art can only qualitatively assess the performance of employees and can not quantitatively assess the performance of the employees.
The basic scheme provided by the invention is as follows: a blockchain based performance assessment system comprising:
the input unit is used for uploading the work record of each employee, and the work record comprises the data of punching a card and the monitoring video;
the statistical unit is used for the staff to check the work records in the block chain, score according to the work records to obtain a score table, and store the score table into the block chain; the system is also used for acquiring trace information from the work records of the employees, calculating the effective working duration according to the trace information and storing the effective working duration into the block chain;
the judging unit is used for comparing the effective working time with the preset rated working time to obtain a comparison result, and judging whether the score in the score table is effective according to the comparison result: if the effective working time is longer than or equal to the preset rated working time, judging that the score is effective; if the effective working time is less than the preset rated working time, judging that the scoring is invalid;
the correcting unit is used for extracting the effective scores and the corresponding monitoring videos in the score table, analyzing the reasonable working time of the monitoring videos, the working state of which meets the preset requirement, and correcting the effective scores according to the reasonable working time and the effective working time to obtain a corrected score table;
and the output unit is used for outputting the corrected scoring table in a visual mode.
The working principle and the advantages of the invention are as follows:
(1) if the effective working time of the staff is greater than or equal to the preset rated working time, the work load is over-saturated and saturated, and the grading is meaningful on the basis; conversely, if the employee's effective duration is less than the preset rated duration, indicating that the workload is not saturated, such a score is of no reference value. In such a way, effective scores are selected from the scoring table, and the performance of the staff can be accurately evaluated.
(2) Even if the effective working time of the employee is greater than or equal to the preset rated working time, the employee is difficult to be ensured to be always in a high-quality working state, the low-quality working state is more concealed and is not easy to be found by other colleagues, and the influence of the low-quality working state is difficult to be reflected in the scoring. Therefore, it is necessary to determine the reasonable working time length when the working state meets the preset requirement, that is, the time length of the high-quality working state according to the monitoring video, and to correct the score based on the reasonable working time length. By the mode, the corrected scoring table can accurately reflect the working time corresponding to the high-quality working state, so that the performance assessment is more fair.
The corrected rating table obtained by the invention can accurately reflect the working time corresponding to the high-quality working state, and solves the technical problems that the prior art can only qualitatively assess the performance of the staff and can not quantitatively assess the performance of the staff.
The system further comprises a storage unit, a processing unit and a display unit, wherein the storage unit is used for storing a standard image of the action behavior of the employee when the working state meets the preset requirement; the correcting unit is further used for obtaining the standard image, training the standard image to obtain an effective working state recognition model, recognizing the action behaviors in the monitoring video through the effective working state recognition model, and eliminating the action behaviors which cannot be recognized by the effective working state recognition model in the monitoring video.
Has the advantages that: by the mode, the effective working state recognition model obtained by training the standard image can recognize the action behaviors in the monitoring video, and after the action behaviors which cannot be recognized by the effective working state recognition model in the monitoring video are removed, the reasonable working time length of the monitoring video with the working state meeting the preset requirement can be accurately obtained.
Further, the correcting unit is used for eliminating the video frames which are not in the identification range in the monitoring video in advance, and the video frames which are not in the identification range are the video frames without action behaviors.
Has the advantages that: through the mode, misjudgment can be avoided, and judgment of reasonable working time length when the working state in the monitoring video meets the preset requirement is influenced.
Furthermore, the correction unit is also used for presetting a precision threshold value and filtering out video frames with the precision value smaller than the precision threshold value in the monitoring video through the effective working state identification model.
Has the advantages that: by the method, the video frames in the monitoring video are filtered by presetting the precision threshold, so that the action behaviors identified by the effective working state identification model can be ensured to have higher precision.
Further, the correction unit is also used for extracting the conversation voice from the monitoring video and identifying the content of the conversation voice; and when the content of the conversation voice can not reasonably explain the video frames smaller than the precision threshold in the monitoring video, the video frames smaller than the precision threshold in the monitoring video are removed.
Has the advantages that: by the mode, misjudgment caused by unclear monitoring video shooting can be avoided, and accuracy of correcting the scoring table is improved.
Further, the correcting unit is used for recognizing the number of the action behaviors according to the effective working state recognition model, generating effective workload and correcting the score according to the effective workload.
Has the advantages that: through the mode, the influence of laziness and poor opening can be greatly deducted by counting the effective workload of the action behaviors.
Further, the correction unit is also used for detecting the face of the monitoring video by adopting a face recognition algorithm to obtain face information; and determining the identity of the staff according to the face information, and associating the action behaviors which can be recognized by the effective working state recognition model with the identity of the staff.
Has the advantages that: by the mode, the action behavior corresponds to the employee identity, and subsequent verification is facilitated.
Drawings
Fig. 1 is a block diagram of a system architecture of an embodiment of a performance assessment system based on a block chain according to the present invention.
Detailed Description
The following is further detailed by the specific embodiments:
example 1
The embodiment is basically as shown in the attached figure 1: the method comprises the following steps:
the input unit is used for uploading the work record of each employee, and the work record comprises the data of punching a card and the monitoring video;
the statistical unit is used for the staff to check the work records in the block chain, score according to the work records to obtain a score table, and store the score table into the block chain; the system is also used for acquiring trace information from the work records of the employees, calculating the effective working duration according to the trace information and storing the effective working duration into the block chain;
the judging unit is used for comparing the effective working time with the preset rated working time to obtain a comparison result, and judging whether the score in the score table is effective according to the comparison result: if the effective working time is longer than or equal to the preset rated working time, judging that the score is effective; if the effective working time is less than the preset rated working time, judging that the scoring is invalid;
the correcting unit is used for extracting the effective scores and the corresponding monitoring videos in the score table, analyzing the reasonable working time of the monitoring videos, the working state of which meets the preset requirement, and correcting the effective scores according to the reasonable working time and the effective working time to obtain a corrected score table;
and the output unit is used for outputting the corrected scoring table in a visual mode.
In the embodiment, the input unit, the statistical unit, the judgment unit, the correction unit, the storage unit and the output unit are all integrated on the server, and the functions are realized through software/programs/codes; private block chains inside the company are built on the server, each employee becomes a node in the block chain, and the nodes are communicated and transmitted by using P2P.
The specific implementation process is as follows:
firstly, work records of all employees are uploaded, and each work record of the employee comprises data of work attendance, work leaving, work going out and the like and monitoring videos shot in real time in a work area (such as an office and a workshop). The work records of each employee are packaged into a block, stored to the tail of the block chain and then stored in each node of the private block chain in a distributed mode, and the computer nodes of all the employees can check the work records of all the employees.
And then, the employees mutually check the work records in the block chain, mutually score according to the work records to obtain a score table, and store the score table into the block chain. For example, the employee uses the computer node of the employee to link the private block chain, checks the work records uploaded by other employees in the private block chain, scores the work contribution of other employees, and the score of each employee can generate a scoring table, and calculates the average score of each employee in the scoring table. Meanwhile, trace information is obtained from the work records of the staff, effective working time is calculated according to the trace information, and the effective working time is stored in the block chain. Trace information is left in the working process, for example, a card is punched when going out is finished, and an outwork card is punched when a working place on a certain day is inconsistent with a usual working place; from these time points of the card punching, the effective working hours per day and per month can be obtained.
Then, the effective working duration is compared with the preset rated working duration to obtain a comparison result, and whether the scores in the score table are effective or not is judged one by one according to the comparison result: if the effective working time is longer than or equal to the preset rated working time, judging that the score is effective; and if the effective working time is less than the preset rated working time, judging that the score is invalid. For example, the preset rated working time per day is set to be 7.5 hours, if the effective working time is 8 hours and 7.5 hours and is greater than or equal to the preset rated working time, the workload is over-saturated and saturated, and the score is judged to be effective; on the contrary, if the effective working time is 7.2 hours and is less than the preset rated working time, the workload is not saturated, and the score is judged to be invalid.
And then, extracting the effective scores and the corresponding monitoring videos in the scoring table, analyzing the reasonable working time of the monitoring videos, wherein the working state of the monitoring videos meets the preset requirement, and correcting the effective scores according to the reasonable working time and the effective working time to obtain the corrected scoring table. Specifically, the server stores in advance a standard image of an action behavior of each employee when the working state satisfies a preset requirement, and for example, photographs are taken in advance by a full-body photographing method. And acquiring the standard images, and repeatedly training the standard images by adopting a neural network algorithm to obtain an effective working state recognition model. After an effective working state recognition model is obtained, video frames which are not in a recognition range in a monitoring video, namely video frames without action behaviors, are removed in advance; meanwhile, according to a preset precision threshold value, filtering out video frames with the precision value smaller than the precision threshold value in the monitoring video through an effective working state identification model; and identifying the action behaviors in the monitoring video (video frames without the action behaviors and with the precision value smaller than the precision threshold value are removed) through the effective working state identification model, removing the action behaviors which cannot be identified by the effective working state identification model in the monitoring video, wherein the time length in the monitoring video corresponding to the remaining action behaviors is the reasonable working time length. If the reasonable working time is 7.2 hours, the effective working time is 7.5 hours, and a certain effective score is 8 points, the calculation formula of the effective score after the correction is that the effective score after the correction is 7.2/7.5 × 8 is 7.7 points.
Finally, the revised scoring table, for example, in the form of an Excel table, is output in a visual manner.
Example 2
The difference from the embodiment 1 is that before eliminating the video frames smaller than the precision threshold value in the monitoring video, the conversation voice is extracted from the monitoring video, and the content of the conversation voice is identified; semantic recognition is carried out on the content in the video, and when the content of the dialogue voice can not reasonably explain the video frames smaller than the precision threshold value in the monitoring video, the video frames smaller than the precision threshold value in the monitoring video are removed. For example, the content of the conversation voice shows that the light is insufficient due to the fact that an office is powered off or one lamp is broken in the day, and it is reasonable that some video frames in the monitoring video are smaller than the precision threshold value, so that the video frames are not removed; otherwise, removing.
In addition, the number of action behaviors is identified according to the effective working state identification model, effective workload is generated, and the score is corrected according to the effective workload. For example, if the effective workload is less than the average workload at ordinary times, the score is subtracted on the basis of the score; if the effective workload is more than the average workload at ordinary times, the scoring is performed on the basis of the score. Meanwhile, face information is obtained by adopting a face recognition algorithm to carry out face detection on the monitoring video, the employee identity is determined according to the face information, and the action behaviors which can be recognized by the effective working state recognition model are associated with the employee identity, namely are corresponded to each other, so that subsequent verification and verification are facilitated.
Example 3
The difference from embodiment 2 is only that, in this embodiment, the card punching data of the employee needs to be collected in advance. When the card punching data of the staff is collected, the amount of exercise, the face state and the card punching background of the staff in unit time are gradually collected. Specifically, when the employee walks to the card terminal, first, the amount of movement of the employee per unit time is collected. In this embodiment, the amount of exercise of the employee per unit time is the number of exercise steps of the employee per unit time, and can be calculated by inputting the exercise data on the WeChat by the employee himself. For example, if the time from home to unit is 20 minutes and the number of steps of the exercise is 3600 steps, the amount of exercise of the employee per unit time is 180 steps/minute. If the amount of exercise per unit time exceeds a preset threshold, for example, the preset threshold is 150 steps/minute, the staff is reminded to reasonably plan the travel time in a voice mode. Then, the face state of the employee is collected. In the embodiment, the facial images of the employees are collected through the camera, and the facial states of the employees, namely the facial emotional expressions, are identified through FaceReader software. If the employee's facial state is negative, such as "sad" or angry ", the employee's body temperature is detected by the infrared thermometers: if the body temperature of the staff exceeds a temperature threshold value, for example, the temperature threshold value is 37.2 ℃, the staff is reminded to wear the mask, and body temperature data is reported. And finally, collecting a background picture of the employee's card punching. In this embodiment, a camera is used to capture pictures of a preset frame number, for example, 10 pictures, when the employee makes a card, and a motion recognition algorithm is used to determine whether the body of the employee is still or moving. If the body of the employee is moving, the employee is prompted to punch the card in advance through voice, which indicates that the employee is possibly busy; on the contrary, if the body of the employee is static, which indicates that the employee is not particularly busy, the employee prompts the other person to punch the card in advance through voice.
The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (7)
1. A performance assessment system based on a block chain is characterized by comprising:
the input unit is used for uploading the work record of each employee, and the work record comprises the data of punching a card and the monitoring video;
the statistical unit is used for the staff to check the work records in the block chain, score according to the work records to obtain a score table, and store the score table into the block chain; the system is also used for acquiring trace information from the work records of the employees, calculating the effective working duration according to the trace information and storing the effective working duration into the block chain;
the judging unit is used for comparing the effective working time with the preset rated working time to obtain a comparison result, and judging whether the score in the score table is effective according to the comparison result: if the effective working time is longer than or equal to the preset rated working time, judging that the score is effective; if the effective working time is less than the preset rated working time, judging that the scoring is invalid;
the correcting unit is used for extracting the effective scores and the corresponding monitoring videos in the score table, analyzing the reasonable working time of the monitoring videos, the working state of which meets the preset requirement, and correcting the effective scores according to the reasonable working time and the effective working time to obtain a corrected score table;
and the output unit is used for outputting the corrected scoring table in a visual mode.
2. The performance assessment system based on the block chain as claimed in claim 1, further comprising a storage unit for storing a standard image of the action behavior of the employee when the working state meets the preset requirement; the correcting unit is further used for obtaining the standard image, training the standard image to obtain an effective working state recognition model, recognizing the action behaviors in the monitoring video through the effective working state recognition model, and eliminating the action behaviors which cannot be recognized by the effective working state recognition model in the monitoring video.
3. The blockchain-based performance assessment system according to claim 2, wherein the modifying unit further pre-culls video frames of the surveillance video that are not within the recognition range, and the video frames that are not within the recognition range are video frames without action.
4. The blockchain-based performance assessment system according to claim 3, wherein the modification unit is further configured to preset a precision threshold and filter out video frames with a precision value smaller than the precision threshold from the surveillance video through the effective working state recognition model.
5. The blockchain-based performance assessment system of claim 4, wherein the modification unit is further configured to extract conversational speech from the surveillance video, and identify content of the conversational speech; and when the content of the conversation voice can not reasonably explain the video frames smaller than the precision threshold in the monitoring video, the video frames smaller than the precision threshold in the monitoring video are removed.
6. The blockchain-based performance assessment system of claim 5, wherein the modification unit is further configured to generate an effective workload based on the number of identified action behaviors from the effective work state recognition model, and modify the score based on the effective workload.
7. The blockchain-based performance assessment system of claim 6, wherein the modification unit is further configured to perform face detection on the surveillance video using a face recognition algorithm to obtain face information; and determining the identity of the staff according to the face information, and associating the action behaviors which can be recognized by the effective working state recognition model with the identity of the staff.
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| CN114116886A (en) * | 2021-10-18 | 2022-03-01 | 德明尚品科技集团有限公司 | Access control data management method and system based on block chain |
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| CN110222920A (en) * | 2019-04-19 | 2019-09-10 | 平安科技（深圳）有限公司 | Performance data storage method, device, equipment and readable storage medium storing program for executing |
| CN111275395A (en) * | 2020-01-19 | 2020-06-12 | 重庆科技学院 | Decentralized enterprise performance assessment method based on block chain |
| CN111275323A (en) * | 2020-01-19 | 2020-06-12 | 重庆科技学院 | Performance distribution system based on confidence nonlinear weighting integration operator |
| CN111311067A (en) * | 2020-01-19 | 2020-06-19 | 重庆科技学院 | Performance distribution DApp system based on confidence level weighted integration operator |
| CN111461538A (en) * | 2020-03-31 | 2020-07-28 | 青岛网信信息科技有限公司 | Performance management system based on big data analysis |
| CN111489136A (en) * | 2020-04-16 | 2020-08-04 | 于洁 | Enterprise salary management system |
| CN111885360A (en) * | 2020-07-31 | 2020-11-03 | 贵州东冠科技有限公司 | Intelligent monitoring system for block chain production workshop |
| CN112990646A (en) * | 2020-12-28 | 2021-06-18 | 贵州东冠科技有限公司 | Performance assessment and evaluation method for workers |
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| CN114116886A (en) * | 2021-10-18 | 2022-03-01 | 德明尚品科技集团有限公司 | Access control data management method and system based on block chain |
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