CN114333133A - Entrance guard-based commuting authentication method, device, equipment and storage medium - Google Patents
Entrance guard-based commuting authentication method, device, equipment and storage medium Download PDFInfo
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Abstract
The application discloses a commuting authentication method, a commuting authentication device, commuting authentication equipment and a storage medium based on entrance guard, wherein the method comprises the following steps: when a target user carries out commute verification, acquiring biological characteristic information to be verified of the target user, and determining a target commute time period to which the current time belongs; determining a target biological characteristic information identification sub-library based on the target commute time period; the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model; comparing the biological characteristic information to be verified with biological characteristic information in a target biological characteristic information identification sub-library to obtain a comparison result; and if the comparison is successful, determining that the result of the commute verification of the target user is successful. The method and the device avoid the long time consumed by the user in commuting.
Description
Technical Field
The present application relates to the field of communication computers, and in particular, to a commute authentication method, apparatus, device, and storage medium based on an access control.
Background
At present, an access control management system needs to perform commuting management (office time management) on a user entering an access control, and when the commuting management is performed on the user, the current access control management system firstly collects biological characteristics of the user such as a human face in real time, then compares the obtained biological characteristic information with biological characteristics in a whole biological characteristic library, and if the user is qualified, further performs commuting authority confirmation and the like on the user.
However, when the office workers (in the morning) are queuing for commuting, the obtained biological feature information is compared with the biological features in all the biological feature libraries, which results in that the biological feature identification process is long-consuming and affects the commuting state of the user.
Disclosure of Invention
In view of this, embodiments of the present application provide a commute authentication method, apparatus, device and storage medium based on an access control, which aim to solve the technical problem in the prior art that a user commutes for a long time.
The embodiment of the application provides a commuting authentication method based on entrance guard, which comprises the following steps:
when a target user carries out commute verification, collecting biological characteristic information to be verified of the target user, and determining a target commute time period to which the current time belongs;
determining a target biological characteristic information identification sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
comparing the biological characteristic information to be verified with biological characteristic information in a target biological characteristic information identification sub-library to obtain a comparison result;
and if the comparison is successful, determining that the result of the commute verification of the target user is successful.
In one possible embodiment of the present application, the method comprises:
after the target commuting time period to which the current moment belongs is determined, authority verification is carried out on a target user before the biological characteristic information to be verified is compared with each biological characteristic information in the target biological characteristic information identification sub-library, and a first authority verification result is obtained;
saving the first permission verification result;
wherein, if the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method comprises the following steps:
and if the first authority verification result is that the verification is passed, responding to the authority corresponding to the first authority verification result.
In one possible embodiment of the present application, the method comprises:
when a target user carries out commute verification, before the step of collecting the biological characteristic information to be verified of the target user, carrying out authority verification on the target user to obtain a second authority verification result;
saving the second permission verification result;
wherein, if the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method comprises the following steps:
and if the second permission verification result is that the verification is passed, responding to the permission corresponding to the second permission verification result.
In one possible embodiment of the present application, the predicted commute time is updated daily, the one or more biometric information recognition sub-libraries are updated daily, and the step of determining a target biometric information recognition sub-library based on the target commute time period is preceded by the method comprising:
acquiring training data with a commute time label, wherein the training data comprises a plurality of items of data in biological feature data of training personnel, prior commute time, prior off-duty time and weather information;
and performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model.
In a possible embodiment of the present application, the step of performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model includes:
inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time;
comparing the predicted commuting time with the commuting time label to obtain a comparison result;
based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and updating the preset basic model based on the adjusted weight of each item of data;
determining whether the updated preset basic model meets a preset iteration ending condition;
if the updated preset basic model meets the preset iteration ending condition, taking the updated preset basic model as the preset commute prediction model;
if the updated preset basic model does not meet the iteration ending condition, continuously carrying out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commute prediction model.
In a possible implementation manner of the present application, after the step of comparing the biometric information to be verified with each biometric information in the target biometric information identification sub-library, the method includes:
if the comparison fails, comparing the biological characteristic information to be verified with the biological characteristic information in the preset biological characteristic information identification library;
and if the biological characteristic information to be verified is the biological characteristic in the preset biological characteristic information recognition library, determining that the commute verification result of the target user is successful in commute verification.
The application still provides a certification device that commutes based on entrance guard, certification device that commutes based on entrance guard includes:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring biological characteristic information to be verified of a target user when the target user carries out commute verification and determining a target commute time period to which the current time belongs;
a first determination module for determining a target biometric information identification sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
the comparison module is used for comparing the biological characteristic information to be verified with each biological characteristic information in the target biological characteristic information identification sub-library;
and the second determining module is used for determining that the result of the commute verification of the target user is successful if the comparison is successful.
In one possible embodiment of the present application, the apparatus further comprises: the first authority verification module is used for verifying the authority of the target user to obtain a first authority verification result before the biological characteristic information to be verified is compared with each biological characteristic information in the target biological characteristic information identification sub-library after the target commuting time period to which the current time belongs is determined; the first storage module is used for storing the first authority verification result; the first response module is used for responding the authority corresponding to the first authority verification result if the first authority verification result is that the first authority verification result passes the verification;
and/or, the device further comprises: the first authority verification module is used for performing authority verification on a target user before collecting biological characteristic information to be verified of the target user when the target user performs commute verification to obtain a second authority verification result; the second storage module is used for storing the second authority verification result; the second response module is used for responding the authority corresponding to the second authority verification result if the second authority verification result is that the second authority verification result passes the verification;
and/or the predicted commute time is updated daily, the one or more biometric information recognition sub-libraries are updated daily, the apparatus further comprising: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring training data with a commute time label, and the training data comprises a plurality of items of data in the biological characteristic data, the prior commute time, the prior off-duty time and the weather information of training personnel; the iterative training module is used for performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model;
and/or the iterative training module is used for realizing: inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time; comparing the predicted commuting time with the commuting time label to obtain a comparison result; based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and updating the preset basic model based on the adjusted weight of each item of data; determining whether the updated preset basic model meets a preset iteration ending condition; if the updated preset basic model meets the preset iteration ending condition, taking the updated preset basic model as the preset commute prediction model; if the updated preset basic model does not meet the iteration ending condition, continuing to carry out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commute prediction model;
and/or the second determination module is configured to implement: if the comparison fails, comparing the biological characteristic information to be verified with biological characteristic information in a preset biological characteristic information identification library; and if the biological characteristic information to be verified is the biological characteristic in the preset biological characteristic information recognition library, determining that the commute verification result of the target user is successful in commute verification.
The application still provides a certification equipment that commutes based on entrance guard, certification equipment that commutes based on entrance guard is entity node equipment, certification equipment that commutes based on entrance guard includes: the system comprises a memory, a processor and a program of the entrance guard-based commute authentication method stored on the memory and capable of running on the processor, wherein the program of the entrance guard-based commute authentication method can realize the steps of the entrance guard-based commute authentication method when being executed by the processor.
In order to achieve the above object, there is also provided a storage medium having stored thereon a commute authentication program based on an access control, wherein the commute authentication program based on the access control is executed by a processor to implement any one of the steps of the commute authentication method based on the access control.
Compared with the current commuting access control system which compares the acquired biological characteristic information with the biological characteristic information in all biological characteristic libraries to cause long commuting time consumption of a user, the commuting authentication method, the commuting authentication device and the storage medium based on the access control system have the advantages that when a target user conducts commuting authentication, the biological characteristic information to be authenticated of the target user is collected, and a target commuting time period to which the current time belongs is determined; determining a target biological characteristic information identification sub-library based on the target commute time period; the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model; comparing the biological characteristic information to be verified with biological characteristic information in a target biological characteristic information identification sub-library to obtain a comparison result; and if the comparison is successful, determining that the result of the commute verification of the target user is successful. In the application, the predicted commute time is determined after the predicted commute time is accurately predicted based on the preset commute prediction model, so that the commute time period of each user can be accurately determined, further, the target biological characteristic information recognition sub-library can be accurately determined when the user commutes, in addition, the biological characteristic information recognition sub-library obtained after the range of the preset biological characteristic information recognition sub-library is reduced based on different commute time periods, the number of corresponding biological characteristic information can be less than that of the preset biological characteristic information recognition sub-library, therefore, when the target user commutes and verifies, the biological characteristic information in the target biological characteristic information recognition sub-library corresponding to the target commute time period of the target user is compared, the response speed can be improved, and the long time consumed for the user commute is avoided.
Drawings
Fig. 1 is a schematic flowchart of a first embodiment of a commute authentication method based on an access control according to the present application;
fig. 2 is a schematic flow chart of a second embodiment of the entrance guard-based commuting authentication method according to the present application;
fig. 3 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application.
Detailed Description
It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application.
The embodiment of the application provides a commuting authentication method based on an entrance guard, and in the first embodiment of the commuting authentication method based on the entrance guard, referring to fig. 1, the commuting authentication method based on the entrance guard comprises the following steps:
step S10, when a target user carries out commute verification, collecting biological characteristic information to be verified of the target user, and determining a target commute time period to which the current time belongs;
step S20, determining a target biological characteristic information recognition sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
step S30, comparing the biological characteristic information to be verified with the biological characteristic information in the target biological characteristic information identification sub-library to obtain a comparison result;
and step S40, if the comparison is successful, determining that the result of the commute verification of the target user is successful.
In the present embodiment, the development backgrounds for the following are:
when the conventional access control management system is used for commuting management of a user, the biological characteristics of the user are firstly collected in real time, and then the obtained biological characteristic information is compared with the biological characteristic information in all biological characteristic libraries. However, when the office workers (in the morning) are queuing for commuting, the commuting access control system compares the acquired biological characteristic information with the biological characteristic information in all the biological characteristic databases, so that the biological characteristic identification process is time-consuming.
In this embodiment, the target biometric information recognition sub-library is obtained after the scope of the biometric information recognition library is reduced, so that the commute response speed can be increased, and the long time consumed by commute is avoided.
The method comprises the following specific steps:
step S10, when a target user carries out commute verification, collecting biological characteristic information to be verified of the target user, and determining a target commute time period to which the current time belongs;
as an example, the entrance guard-based commute authentication method may be applied to an entrance guard-based commute authentication system (entrance guard management system) subordinate to an entrance guard-based commute authentication device.
As an example, the commute authentication system based on the entrance guard has both the function of commute management (attendance management) and the function of entrance guard.
As an example, the target users may be different levels of employees of a company that have different commuting requirements.
As an example, the commute authentication method based on entrance guard is applicable to companies or organizations that flexibly perform commute management.
As an example, the biometric feature may be a human face or a fingerprint.
As an example, when a target user performs commute verification, a face of the target user to be verified is collected, and a target commute time period to which the current time belongs is determined.
As an example, when a target user performs commute verification, a fingerprint to be verified of the target user is collected, and a target commute time period to which the current time belongs is determined.
In this embodiment, for convenience of explanation, a biological feature is taken as an example to specifically describe the human face, and therefore, the target biological feature information recognition sub-library is a target human face recognition sub-library, the biological feature information recognition sub-library is a human face recognition sub-library, and the target biological feature information recognition sub-library is a human face feature recognition sub-library, but the biological feature of the present application is not limited to the human face.
As an example, when the face of the target user is in the acquisition box of the door access or is close to the acquisition box, it is determined that the target user is performing commute verification.
As an example, the entrance guard determines a target commuting time period to which the current time belongs by a division manner of the current commuting time period, wherein the division of the commuting time period may be different every day.
Step S20, determining a target biological characteristic information recognition sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
in this embodiment, the preset commute prediction model is a model that can accurately determine the predicted commute time after training.
In this embodiment, since the predicted commute time is determined based on the preset commute prediction model after accurate prediction, the commute time period of each user can be accurately determined based on the predicted commute time.
As an example, the predicted commute time may also include a commute period reserved by a visitor (target user).
In this embodiment, the target biometric information recognition sub-library is determined based on the accurately determined target commute time period.
As an example, the biometric information recognition sub-library may be one or more.
As an example, the commute period per day is divided into M levels, e.g., on the first day, commute (attendance) between 8 and half to 9 am is the first level, commute between 9 and 10 am is the second level, and if the user's predicted commute time is 9 and 20 minutes in the morning on that day, the user's commute period is the second level.
In this embodiment, each commute time period corresponds to one face recognition library, and as long as the predicted commute time of the user is within a certain level, the face of the user is added to the face recognition sub-library at the level (the face recognition sub-library corresponding to the second level).
As an example, the face recognition sub-library is dynamically adjusted based on the predicted commute time for each day. For example, on a certain day, the commute (attendance) between 8 o 'clock and 40 o' clock and 9 o 'clock and 20 o' clock in the morning is of a first grade, the commute between 9 o 'clock and 20 o' clock and 9 o 'clock and 50 o' clock in the morning is of a second grade, and if the predicted commute time of the user is 9 o 'clock and 20 o' clock in the morning, the commute time period of the user is of the first grade, the face of the user is added into the face recognition sub-library (the face recognition sub-library corresponding to the first grade) under the grade.
In this embodiment, the face recognition sub-library is obtained by narrowing the range of the preset biometric information recognition library based on each commute time period divided by the predicted commute time.
As an example, the preset biometric information recognition library is a database local to the entrance guard-based commute authentication device.
As an example, the preset face recognition library is a face database local to the commute authentication device based on the entrance guard.
It is obvious that, in this embodiment, the preset face recognition library is divided into a plurality of recognition sub-libraries (constituting a face recognition sub-library), and each face recognition sub-library does not include all faces, that is, the range of any face recognition library in the biometric information recognition sub-library is smaller than that of the preset face recognition library, so that the response speed can be improved.
As an example, the preset face recognition library is composed of 100 face data, and the a face recognition sub-library is composed of only 10 face data. It is apparent that the response speed can be improved when the user commutes.
Step S30, comparing the biological characteristic information to be verified with the biological characteristic information in the target biological characteristic information identification sub-library to obtain a comparison result;
in this embodiment, the face to be verified is compared with the face in the target face recognition sub-library to obtain a comparison result.
As an example, the alignment result is: the face to be verified is a face stored in the target face recognition sub-library.
As an example, the alignment result is: the face to be verified is not a face stored in the target face recognition sub-library.
And step S40, if the comparison is successful, determining that the result of the commute verification of the target user is successful.
As an example, if the comparison result is that the face to be verified is the face stored in the target face recognition sub-library, it is determined that the commute verification result of the target user is successful.
As an example, if the target user commutes successfully, the attendance is successful or the check-in is successful.
As an example, if the commute verification of the target user is successful, the entrance guard may be controlled to open for the user to enter the company.
As an example, if the comparison result is that the face to be verified is not a face stored in the target face recognition sub-library, further determination is required.
If the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method includes the following steps S50-S60:
step S50, if the comparison fails, comparing the biological characteristic information to be verified with the biological characteristic information in the preset biological characteristic information identification library;
and step S60, if the biometric feature information to be verified is the biometric feature in the preset biometric feature information identification library, determining that the result of the commute verification of the target user is successful.
In this embodiment, if the comparison result is that the face to be verified is not the face in the target face recognition sub-library (comparison failure), the face to be verified is compared with the face in the preset face recognition sub-library, if the face to be verified is the face in the preset biological feature information recognition library, it is determined that the result of the commuting verification of the target user is successful, and if the face to be verified is not the biological feature in the preset face recognition sub-library, it is determined that the result of the commuting verification of the target user is commuting verification failure.
In this embodiment, when the face to be verified is not the face in the target face recognition sub-library, the commuting verification of the user is not considered to be failed at all, but is further determined, so that an erroneous determination is avoided.
Compared with the current commuting access control system which compares the acquired biological characteristic information with the biological characteristic information in all biological characteristic libraries to cause long commuting time consumption of a user, the commuting authentication method, the commuting authentication device and the storage medium based on the access control system have the advantages that when a target user conducts commuting authentication, the biological characteristic information to be authenticated of the target user is collected, and a target commuting time period to which the current time belongs is determined; determining a target biological characteristic information identification sub-library based on the target commute time period; the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model; comparing the biological characteristic information to be verified with biological characteristic information in a target biological characteristic information identification sub-library to obtain a comparison result; and if the comparison is successful, determining that the result of the commute verification of the target user is successful. In the application, because the predicted commute time is determined after the prediction is accurately performed based on the preset commute prediction model, the commute time period of each user can be accurately determined, and then the target biological characteristic information recognition sub-library can be accurately determined when the user commutes, in addition, each biological characteristic information recognition sub-library obtained after the range of the preset biological characteristic information recognition sub-library is reduced based on different commute time periods, the number of corresponding biological characteristic information can be less than that of the preset biological characteristic information recognition sub-library, therefore, when the target user commutes and verifies, the biological characteristic information in the target biological characteristic information recognition sub-library corresponding to the target commute time period of the target user is compared, the response speed can be improved, and the long time consumption of the user commute is avoided.
Further, based on the first embodiment in the present application, another embodiment of the present application is provided, in which the development context is as follows:
the existing access control system identifies the user, and manages authority verification, authority response and the like in real time, for example, the existing access control system collects the face of the user in real time, then compares the obtained face information with the face information in the total face database, and if the user is qualified personnel after comparison, the authority module based on the access control system further performs authority identification on the user, and after the authority identification (attendance authority or access authority), the user is responded, and if the authority of the user is determined to open the door.
However, when the office workers (in the morning) are on the duty or attendance, the access control system sequentially identifies, authenticates the authority, responds to the authority and the like in real time, which takes a long time and affects the commuting or work of the user.
In the embodiment, the user is not sequentially managed in real time, such as identification, authority verification, authority response and the like, but the authority verification is performed on the user before the commuting verification is performed on the target user, so that the access control response time is shortened, and the commuting efficiency of the user is improved.
The method comprises the following specific steps:
referring to fig. 2, the method includes:
step A1, after determining a target commuting time period to which the current time belongs, performing authority verification on a target user before comparing the biological characteristic information to be verified with each biological characteristic information in a target biological characteristic information identification sub-library to obtain a first authority verification result;
step A2, saving the first authority verification result;
in this embodiment, after the target commuting time period to which the current time belongs is determined, before the biometric information to be verified is compared with the biometric information in the target biometric information identification sub-library, the system performs permission verification on the target user to obtain a permission verification result, and stores the permission verification result.
As an example, after a target commuting time period to which the current time belongs is determined, before the face to be verified is compared with the face in the target face recognition sub-library, the system firstly verifies the door opening authority of the target user to obtain an authority verification result.
As an example, after a target commuting time period to which the current time belongs is determined, before the face to be verified is compared with the face in the target face recognition sub-library, the system verifies the sign-in authority of the target user to obtain a first authority verification result.
In this embodiment, after obtaining the authorization verification result, the authorization verification result is saved, and the purpose of saving is to: and the permission verification is carried out after the face user is identified. Therefore, after face recognition, the corresponding authority can be responded, and the situation that the target user needs to wait for too long time to influence commuting due to the fact that the authority recognition is needed after the face recognition of the target user is avoided.
As an example, the permission verification result stored by the system has time validity, and abuse of the permission verification result is avoided.
Wherein, the result of the commute verification includes that the commute verification succeeds, if the comparison succeeds, it is determined that the result of the commute verification of the target user is after the successful step of the commute verification, including:
step S70, if the first permission verification result is that the verification passes, responding to the permission corresponding to the first permission verification result.
As an example, if the first permission verification result is that the verification is passed (with permission), a permission (door opening permission) corresponding to the first permission verification result is responded, such as directly performing door opening operation of an access door.
As an example, the method further comprises:
step B1, when the target user is subjected to commute verification, before the step of collecting the biological characteristic information to be verified of the target user, performing authority verification on the target user to obtain a second authority verification result;
step B2, saving the second authority verification result;
in this embodiment, when a target user performs commute verification, before the step of collecting biometric information to be verified of the target user, the system performs permission verification on the target user to obtain a second permission verification result, and stores the second permission verification result.
As an example, when a target user performs commute verification, before the step of collecting biometric information to be verified of the target user, the system performs verification of the door opening permission of the target user to obtain a permission verification result.
As an example, when a target user performs commute verification, before the step of collecting biometric information to be verified of the target user, the system performs verification of the sign-in authority on the target user to obtain a first authority verification result.
Wherein, if the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method comprises the following steps:
and if the second permission verification result is that the verification is passed, responding to the permission corresponding to the second permission verification result.
As an example, if the second permission verification result is that the verification is passed (has permission), a permission (check-in permission) corresponding to the second permission verification result is responded, such as directly generating a check-in record.
In the embodiment, the authority verification is performed first, so that the commuting time of the user is shortened.
Further, based on the first and second embodiments herein, there is provided another embodiment herein, wherein the step of determining a target biometric information identification sub-library based on the target commute time period is preceded by the steps of C1-C2:
step C1, acquiring training data with a commute time label, wherein the training data comprises a plurality of items of data in the biological characteristic data, the previous commute time, the previous off-duty time and the weather information of a training person;
and step C2, performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model.
In this embodiment, how to train to obtain the preset commute prediction model is described to accurately obtain the predicted commute time of each user.
In this embodiment, training data is obtained with a commute time tag that is used to determine whether the predicted commute time is accurate.
In the present embodiment, the training data includes a plurality of items of data among biometric data (face data) of a training person, a previous commute time (commute time of the previous day), a previous off-duty time (off-duty time of the previous day), and weather information.
As an example, the training data (input data) includes biometric data of a training person (face data, the system has a face recognition function, and can directly obtain the face data), previous commute time (commute time of the previous day, the system can record the attendance condition of the person to the local, and can directly call if necessary), and weather information (the system integrates a weather forecast crawling function, and obtains the weather condition of the day).
As an example, training data collects data for various situations, including data for different weather conditions and different hours of work and work.
As one example, the training data includes a training set and a test set.
As an example, the training set is used to train the model and the test set is used to test the model.
As an example, the training set is 70% and the test set is 30%.
As an example, the training data is shown in table 1 below.
TABLE 1
In this embodiment, based on the training data, a preset basic model is iteratively trained to obtain the preset commute prediction model, where termination conditions of the iterative training may be: the preset loss function converges or the training times reach the preset times.
The step of performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model comprises the following steps D1-D6:
step D1, inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time;
step D2, comparing the predicted commute time with the commute time label to obtain a comparison result;
step D3, based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and based on the adjusted weight of each item of data, updating the preset basic model;
step D4, determining whether the updated preset basic model meets a preset iteration end condition;
step D5, if the updated preset basic model meets the preset iteration end condition, taking the updated preset basic model as the preset commuting prediction model;
and D6, if the updated preset basic model does not meet the iteration ending condition, continuing to carry out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commuting prediction model.
In the embodiment, the weight of each item of data is continuously trained according to the self-learning of the algorithm, namely the weight proportion or the importance degree of each item of data on the predicted communication time is trained.
In this embodiment, it is determined whether the updated preset basic model meets a preset iteration end condition, and if the updated preset basic model does not meet the iteration end condition, the weight of each item of data is continuously adjusted until the iteration end condition is met (a preset loss function is converged, or an error is within a preset acceptance range), and the preset commute prediction model is obtained. In the embodiment, the preset commute prediction model is accurately determined, and a foundation is laid for reducing commute time consumption.
Referring to fig. 3, fig. 3 is a schematic device structure diagram of a hardware operating environment according to an embodiment of the present application.
As shown in fig. 3, the entrance guard-based commute authentication device may include: a processor 1001, a memory 1005, and a communication bus 1002. The communication bus 1002 is used to enable connection communication between the processor 1001 and the memory 1005.
Optionally, the entrance guard-based commute authentication device may further include a user interface, a network interface, a camera, an RF (Radio Frequency) circuit, a sensor, a WiFi module, and the like. The user interface may comprise a Display screen (Display), an input sub-module such as a Keyboard (Keyboard), and the optional user interface may also comprise a standard wired interface, a wireless interface. The network interface may include a standard wired interface, a wireless interface (e.g., WI-FI interface).
Those skilled in the art will appreciate that the access control-based commute authentication device configuration shown in fig. 3 does not constitute a limitation of access control-based commute authentication devices, and may include more or fewer components than those shown, or some components in combination, or a different arrangement of components.
As shown in fig. 3, a memory 1005, which is a storage medium, may include an operating system, a network communication module, and a gate entry based commute authentication program therein. The operating system is a program that manages and controls the hardware and software resources of the entrance guard-based commute authentication device, supporting the operation of the entrance guard-based commute authentication program and other software and/or programs. The network communication module is used for realizing communication among components in the memory 1005 and communication with other hardware and software in the entrance guard-based commute authentication system.
In the gate-based commute authentication device shown in fig. 3, the processor 1001 is configured to execute a gate-based commute authentication program stored in the memory 1005, and implement any one of the steps of the gate-based commute authentication method described above.
The specific implementation mode of the commuting authentication equipment based on the entrance guard is basically the same as that of each embodiment of the commuting authentication method based on the entrance guard, and is not repeated here.
The application still provides a certification device that commutes based on entrance guard, certification device that commutes based on entrance guard includes:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring biological characteristic information to be verified of a target user when the target user carries out commute verification and determining a target commute time period to which the current time belongs;
a first determination module for determining a target biometric information identification sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
the comparison module is used for comparing the biological characteristic information to be verified with each biological characteristic information in the target biological characteristic information identification sub-library;
and the second determining module is used for determining that the result of the commute verification of the target user is successful if the comparison is successful.
In one possible embodiment of the present application, the apparatus further comprises: the first authority verification module is used for verifying the authority of the target user to obtain a first authority verification result before the biological characteristic information to be verified is compared with each biological characteristic information in the target biological characteristic information identification sub-library after the target commuting time period to which the current time belongs is determined; the first storage module is used for storing the first authority verification result; the first response module is used for responding the authority corresponding to the first authority verification result if the first authority verification result is that the first authority verification result passes the verification;
and/or, the device further comprises: the first authority verification module is used for performing authority verification on a target user before collecting biological characteristic information to be verified of the target user when the target user performs commute verification to obtain a second authority verification result; the second storage module is used for storing the second authority verification result; the second response module is used for responding the authority corresponding to the second authority verification result if the second authority verification result is that the second authority verification result passes the verification;
and/or the predicted commute time is updated daily, the one or more biometric information recognition sub-libraries are updated daily, the apparatus further comprising: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring training data with a commute time label, and the training data comprises a plurality of items of data in the biological characteristic data, the prior commute time, the prior off-duty time and the weather information of training personnel; the iterative training module is used for performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model;
and/or the iterative training module is used for realizing: inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time; comparing the predicted commuting time with the commuting time label to obtain a comparison result; based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and updating the preset basic model based on the adjusted weight of each item of data; determining whether the updated preset basic model meets a preset iteration ending condition; if the updated preset basic model meets the preset iteration ending condition, taking the updated preset basic model as the preset commute prediction model; if the updated preset basic model does not meet the iteration ending condition, continuing to carry out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commute prediction model;
and/or the second determination module is configured to implement: if the comparison fails, comparing the biological characteristic information to be verified with biological characteristic information in a preset biological characteristic information identification library; and if the biological characteristic information to be verified is the biological characteristic in the preset biological characteristic information recognition library, determining that the commute verification result of the target user is successful in commute verification.
The specific implementation mode of the commuting authentication device based on the entrance guard is basically the same as that of each embodiment of the commuting authentication method based on the entrance guard, and is not repeated here.
The embodiment of the application provides a storage medium, and the storage medium stores one or more programs, and the one or more programs can be further executed by one or more processors to implement the steps of the entrance guard-based commute authentication method.
The specific implementation of the storage medium of the present application is substantially the same as that of each embodiment of the aforementioned entrance guard-based commuting authentication method, and is not described herein again.
The present application also provides a computer program product, comprising a computer program, which when executed by a processor implements the steps of the above-mentioned access control-based commute authentication method.
The specific implementation of the computer program product of the present application is substantially the same as each embodiment of the aforementioned entrance guard-based commuting authentication method, and is not described herein again.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments may be implemented by a software plus hardware platform, or may be implemented by hardware, but in many cases, the former is a better embodiment. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, an air conditioner, or a network device) to execute the method according to the embodiments of the present invention.
The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.
Claims (10)
1. A commute authentication method based on entrance guard is characterized by comprising the following steps:
when a target user carries out commute verification, collecting biological characteristic information to be verified of the target user, and determining a target commute time period to which the current time belongs;
determining a target biological characteristic information identification sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on a forecast commuting time, and the forecast commuting time is determined after the commuting time of each user is forecasted based on a preset commuting forecasting model;
comparing the biological characteristic information to be verified with each biological characteristic information in a target biological characteristic information identification sub-library;
and if the comparison is successful, determining that the result of the commute verification of the target user is successful.
2. The access control-based commuting authentication method of claim 1, wherein the method comprises:
after the target commuting time period to which the current moment belongs is determined, authority verification is carried out on a target user before the biological characteristic information to be verified is compared with each biological characteristic information in the target biological characteristic information identification sub-library, and a first authority verification result is obtained;
saving the first permission verification result;
wherein, if the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method comprises the following steps:
and if the first authority verification result is that the verification is passed, responding to the authority corresponding to the first authority verification result.
3. The access control-based commuting authentication method of claim 1, wherein the method comprises:
when a target user carries out commute verification, before the step of collecting the biological characteristic information to be verified of the target user, carrying out authority verification on the target user to obtain a second authority verification result;
saving the second permission verification result;
wherein, if the comparison is successful, after the step of determining that the result of the commute verification of the target user is successful, the method comprises the following steps:
and if the second permission verification result is that the verification is passed, responding to the permission corresponding to the second permission verification result.
4. The access control-based commute authentication method of claim 1, wherein the predicted commute time is updated daily, the one or more biometric information identification sub-libraries are updated daily, and wherein the step of determining a target biometric information identification sub-library based on the target commute time period is preceded by the method comprising:
acquiring training data with a commute time label, wherein the training data comprises a plurality of items of data in biological feature data of training personnel, prior commute time, prior off-duty time and weather information;
and performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model.
5. The entrance guard-based commute authentication method according to claim 4, wherein the step of iteratively training a preset base model based on the training data to obtain the preset commute prediction model comprises:
inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time;
comparing the predicted commuting time with the commuting time label to obtain a comparison result;
based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and updating the preset basic model based on the adjusted weight of each item of data;
determining whether the updated preset basic model meets a preset iteration ending condition;
if the updated preset basic model meets the preset iteration ending condition, taking the updated preset basic model as the preset commute prediction model;
if the updated preset basic model does not meet the iteration ending condition, continuously carrying out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commute prediction model.
6. The entrance guard-based commute authentication method of any one of claims 1 to 5, wherein after the step of comparing the biometric information to be verified with each biometric information in the target biometric information recognition sub-base, the method comprises:
if the comparison fails, comparing the biological characteristic information to be verified with the biological characteristic information in the preset biological characteristic information identification library;
and if the biological characteristic information to be verified is the biological characteristic information in a preset biological characteristic information identification library, determining that the commute verification result of the target user is successful.
7. The utility model provides a commute authentication device based on entrance guard, a serial communication port, commute authentication device based on entrance guard includes:
the system comprises an acquisition module, a verification module and a verification module, wherein the acquisition module is used for acquiring biological characteristic information to be verified of a target user when the target user carries out commute verification and determining a target commute time period to which the current time belongs;
a first determination module for determining a target biometric information identification sub-library based on the target commute time period;
the biological characteristic information identification sub-library is obtained by narrowing the range of a preset biological characteristic information identification library based on a commuting time period, wherein the commuting time period is determined based on the predicted commuting time; the predicted commute time is determined after the commute time of each user is predicted based on a preset commute prediction model;
the comparison module is used for comparing the biological characteristic information to be verified with each biological characteristic information in the target biological characteristic information identification sub-library;
and the second determining module is used for determining that the result of the commute verification of the target user is successful if the comparison is successful.
8. The access-based commute authentication device of claim 7, further comprising: the first authority verification module is used for verifying the authority of the target user to obtain a first authority verification result before the biological characteristic information to be verified is compared with each biological characteristic information in the target biological characteristic information identification sub-library after the target commuting time period to which the current time belongs is determined; the first storage module is used for storing the first authority verification result; the first response module is used for responding the authority corresponding to the first authority verification result if the first authority verification result is that the first authority verification result passes the verification;
and/or, the device further comprises: the first authority verification module is used for performing authority verification on a target user to obtain a second authority verification result before the step of collecting the biological characteristic information to be verified of the target user when the target user performs commute verification; the second storage module is used for storing the second authority verification result; the second response module is used for responding the authority corresponding to the second authority verification result if the second authority verification result is that the second authority verification result passes the verification;
and/or the predicted commute time is updated daily, the one or more biometric information recognition sub-libraries are updated daily, the apparatus further comprising: the system comprises an acquisition module, a processing module and a processing module, wherein the acquisition module is used for acquiring training data with a commute time label, and the training data comprises a plurality of items of data in the biological characteristic data, the prior commute time, the prior off-duty time and the weather information of training personnel; the iterative training module is used for performing iterative training on a preset basic model based on the training data to obtain the preset commute prediction model;
and/or the iterative training module is used for realizing: inputting the training data into the preset basic model, and predicting the training data based on the preset basic model to obtain predicted commuting time; comparing the predicted commuting time with the commuting time label to obtain a comparison result; based on the comparison result, adjusting the weight of each item of data in the multiple items of data in the preset basic model, and updating the preset basic model based on the adjusted weight of each item of data; determining whether the updated preset basic model meets a preset iteration ending condition; if the updated preset basic model meets the preset iteration ending condition, taking the updated preset basic model as the preset commute prediction model; if the updated preset basic model does not meet the iteration ending condition, continuing to carry out iteration training on the updated preset basic model based on the training data set until the iteration ending condition is met, and obtaining the preset commute prediction model;
and/or the second determination module is configured to implement: if the comparison fails, comparing the biological characteristic information to be verified with the biological characteristic information in the preset biological characteristic information identification library; and if the biological characteristic information to be verified is the biological characteristic in the preset biological characteristic information recognition library, determining that the commute verification result of the target user is successful in commute verification.
9. An entrance guard-based commute authentication device, comprising a memory, a processor and an entrance guard-based commute authentication program stored in the memory and operable on the processor, wherein the processor implements the entrance guard-based commute authentication program by implementing the entrance guard-based commute authentication method of any one of claims 1 to 6.
10. A storage medium having stored thereon an entrance guard-based commute authentication program, which when executed by a processor, performs the steps of the entrance guard-based commute authentication method as claimed in any one of claims 1 to 6.
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