Remote monitoring method, device, electronic device and computer-readable storage medium

Abstract

The present application provides a remote supervision method, device, electronic device and computer-readable storage medium. The method includes: calculating, according to a preset random algorithm, the moment for outputting a prompt message during online education; the prompt message is information for prompting a user to perform a preset behavior, and the online education is online learning or online examination; when the moment is during the online education process, output the prompt message, obtain a user behavior image of the behavior made by the user based on the prompt message, wherein the user behavior image includes a face image; authenticate the user according to the preset user information of the user and the face image; verify the behavior of the user according to the prompt message and the behavior in the user behavior image. By this means, the users undergoing online education can be supervised, thereby improving the problem that online teaching cannot supervise the online teaching objects.

Description

Technical Field

[0001] This application relates to the field of online education, and in particular, to a remote supervision method, device, electronic device, and computer-readable storage medium. Background Art

[0002] Compared with the offline centralized teaching mode, since the online teaching objects are scattered in different places, it is very difficult for teachers to supervise each teaching object. Therefore, during the online teaching process, it is also difficult to guarantee the quality of online teaching for each teaching object. Summary of the Invention

[0003] The purpose of the embodiments of this application is to provide a remote supervision method, device, electronic device, and computer-readable storage medium to improve the problem of "unable to supervise online teaching objects during online teaching".

[0004] The present invention is implemented as follows:

[0005] In a first aspect, the embodiments of this application provide a remote supervision method, and the method includes: calculating, according to a preset random algorithm, the moment to output a prompt message during the online education process; the prompt message is a message for prompting a user to perform a preset behavior, and the online education is online learning or online examination; when the moment is during the online education process, output the prompt message; obtaining a user behavior image of the behavior made by the user based on the prompt message, where the user behavior image includes a face image; authenticating the identity of the user according to the preset user information of the user and the face image; and verifying the behavior of the user according to the prompt message and the behavior in the user behavior image.

[0006] In the embodiments of this application, calculate, according to a preset random algorithm, the moment to output a prompt message during the online education process; and when the moment is during the online education process, output a prompt message for prompting the user to perform a preset behavior, and obtain a user behavior image of the behavior made by the user based on the prompt message. After obtaining the user behavior image, user identity authentication and behavior verification can be performed to determine whether the user is the person himself / herself conducting the online education. Moreover, through the above method, it can also be determined whether the user's attention is focused on the online education. In addition, by outputting the prompt message, enabling the user to perform corresponding actions according to the prompt message to obtain the user behavior image, it can also remind the user during the online education process to keep a good state in the online education.

[0007] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, after authenticating the user's identity and validating the user's behavior, the method further includes: if both the identity authentication and the behavior authentication are passed, then return the operation interface of the online education; if any one of the identity authentication and the behavior authentication fails, then determine whether the number of times of obtaining the user behavior image is less than a preset number n; if so, re-obtain the user behavior image and repeat the above verification operation; if not, end the online education, where n is any positive integer.

[0008] In the embodiment of the present application, if both the user's identity authentication and behavior authentication are passed, then return the operation interface of the online education, enabling the user to continue with online learning or online exams; if any one of the user's identity authentication and behavior authentication fails, then determine whether the number of image acquisitions is less than n times. If so, re-obtain the user behavior image, and based on the face image in the re-obtained user behavior image and the preset user information, authenticate the user's identity, and based on the prompt information and the re-obtained user behavior image, validate the user's behavior, that is, repeat the above verification operation; if not, end the online education. By re-obtaining the user behavior image for users who fail the verification and re-verifying, the accuracy of the verification can be ensured, and it will not be determined that the user's verification fails due to accidental reasons such as the user making the wrong action in the prompt information, thus ending the online education and causing inconvenience to the user. Moreover, by setting the determination that the number of image acquisitions is less than n times, it can also prevent the verification of the user from looping continuously in the case of verification failure, thereby improving the efficiency of verifying the user and reducing power consumption.

[0009] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, the method further includes: when outputting the prompt information, pause the online education.

[0010] When outputting the prompt information, pausing the online education that the user is currently undergoing enables the user to continue learning or taking an exam according to the progress of the online education when the prompt information is output after the identity authentication and behavior authentication are successful, so that the user can enter the learning or exam state as soon as possible after the verification is completed.

[0011] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, obtaining the user behavior image of the behavior made by the user based on the prompt information includes: within a preset time after outputting the prompt information, based on the detected acquisition instruction triggered by the user, acquire the user behavior image of the behavior made by the user based on the prompt information.

[0012] In the embodiments of the present application, within a preset time after the output of the prompt message, after the user triggers the acquisition instruction, the user behavior image of the user will be acquired. By the above method, the user can be made to be prepared and give an acquisition instruction before the user behavior image is acquired, thereby improving the success rate of verification and the user experience.

[0013] Combined with the technical solution provided in the above first aspect, in some possible implementation manners, before the moment of outputting the prompt message during the online education calculated according to the preset random algorithm, the method further includes: obtaining an operation instruction of the user, where the operation instruction includes an instruction to start the online education; responding to the operation instruction and displaying an operation interface corresponding to the online education.

[0014] In the embodiments of the present application, by the above method, the user can start the online education after issuing the operation instruction, thereby improving the user experience of online education.

[0015] Combined with the technical solution provided in the above first aspect, in some possible implementation manners, calculating the moment of outputting the prompt message during the online education according to the preset random algorithm includes: starting timing when the operation interface of the online education is displayed; calculating a first trigger time for the first output of the prompt message according to the preset random algorithm; determining whether the first trigger time is greater than the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the online education process.

[0016] In the embodiments of the present application, when the operation interface of the online education is displayed, timing starts, that is, timing starts when the user starts the online education; calculating a first trigger time for outputting the prompt message according to the preset random algorithm; determining whether the first trigger time is greater than the preset total duration of the online education. If the first trigger time is less than or equal to the preset total duration, it indicates that the above first trigger time is during the online education process. That is, during this online education process, if a prompt message needs to be output, then when the timing reaches the first trigger time, the prompt message is output, and subsequent steps of acquiring the user behavior image and verifying the user are performed. By the above method, it can be determined whether the user will be verified within the preset total duration of the online education. If the first trigger time is less than or equal to the preset total duration of the online education, it can be ensured that the user is verified at least once within the preset total duration of this online education.

[0017] Combined with the technical solution provided in the above first aspect, in some possible implementation manners, the method further includes: if the first trigger time is greater than the preset total duration, the prompt message is not output.

[0018] In this embodiment, if the first trigger time calculated according to the preset random algorithm is greater than the preset total duration of the online education, no prompt message is output during the online education process, that is, the user is not verified during the online education process. In the above manner, the interference to the user in the online education can be reduced, and the use of device peripherals can be reduced, thereby reducing the burden on the device and also reducing the power consumption.

[0019] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, calculating the first trigger time for the first output of the prompt message according to the preset random algorithm includes: obtaining an average probability number according to the total number of timings, a preset trigger moment, a preset coefficient, and a preset random function, where the preset trigger moment is the moment when the output of the prompt message is allowed to start, and the total number of timings is the quotient of the preset total duration and the preset time interval; obtaining a non-average probability distribution sequence according to the total number of timings, the preset duration, a preset probability distribution turning point, and a preset slope, where the start moment of the preset duration is the timing moment, and its end moment is the preset trigger moment, and the preset slope is the slope value of the linear distribution that the preset duration and the preset probability distribution turning point obey; obtaining a trigger moment according to the average probability number and the non-average probability distribution sequence; and determining the first trigger time according to the trigger moment and the preset moment.

[0020] In the embodiment of the present application, the value obtained by multiplying the total number of timings and the preset coefficient and the preset trigger moment are brought into the preset random function to obtain an average probability value; then, according to the total number of timings, the preset duration, the preset probability distribution turning point, and the preset slope, a non-average probability distribution sequence can be obtained; then, the corresponding value in the above non-average probability distribution sequence is selected as the trigger moment according to the above average probability value, and finally, the first trigger time can be obtained by subtracting the preset moment from the trigger moment. In the above manner, the first trigger time can be calculated. Due to the setting of each parameter in the calculation process, the calculated first trigger time must be after the preset trigger moment, so as to ensure that user verification will not be performed within the preset duration in each online education process, and further, the user will not be disturbed in the initial stage of the online education, enabling the user to enter the learning or examination state faster.

[0021] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, calculating the first trigger time for the first output of the prompt message according to the preset random algorithm further includes: when outputting the prompt message each time, calculating the total number of times the prompt message is output; determining whether the total number of output times is less than a preset number of output times, where the preset number of output times is the number of times the prompt message is preset to be output in the online education; if so, according to the total timing count, the preset trigger time, the preset coefficient, and the preset random function, obtaining a new average probability number; according to the newly obtained average probability number and the non-average probability distribution sequence, obtaining a new trigger time; according to the total number of output times, obtaining the currently corresponding preset time; according to the newly obtained trigger time and the currently corresponding preset time, determining the trigger time for the next output of the prompt message.

[0022] In the embodiments of the present application, by calculating the trigger times of the output prompt message, it can be obtained how many times the trigger time has been calculated; by determining whether the trigger times are less than the preset trigger times, it can be determined whether it is necessary to calculate the next trigger time. If the trigger times are less than the preset trigger times, it is necessary to calculate the next trigger time, that is, according to the total timing count, the preset trigger time, the preset coefficient, and the preset random function, obtaining a new average probability number, and then selecting the corresponding value in the non-average probability distribution sequence calculated for the first time as the trigger time according to the newly obtained average probability value. Finally, subtracting the currently corresponding preset time from the trigger time can obtain the next trigger time. In the above manner, it can be determined whether it is necessary to output the prompt message again each time the prompt message is output, that is, to determine whether it is necessary to perform user verification. And after determining that it is necessary to output the prompt message, the next trigger time can be calculated. And if the next trigger time is within the above online education process, when the timing reaches the trigger time, the prompt message is output, that is, the user is verified.

[0023] Combined with the technical solution provided in the first aspect above, in some possible implementation manners, calculating the time for outputting the prompt message during the online education according to the preset random algorithm further includes: if the first trigger time is greater than the preset total duration, stop timing, and restart timing at the moment when the actual online time of the online education exceeds the preset total duration, and determine the moment when the sum of the preset total duration and the overtime timing time is equal to the first trigger time as the time for outputting the prompt message.

[0024] In the embodiment of the present application, if the first trigger time is greater than the preset total duration of the online education, it means that within the preset total duration of the online education, no prompt information will be output to verify the user, so the timing is stopped; the timing restarts at the moment when the actual online time of the user's online education exceeds the preset total duration, and when the sum of the above preset total duration and the overtime timing time is equal to the first trigger time, prompt information is output and the user is verified. In the above manner, supervision of the user within the overtime period of their online education can be achieved.

[0025] Combined with the technical solution provided in the above first aspect, in some possible implementation manners, calculating the moment to output the prompt information during the online education according to the preset random algorithm further includes: if the first trigger time is less than or equal to the preset total duration, the timing restarts at the moment when the actual online time of the online education exceeds the preset total duration, and the overtime trigger time for outputting the prompt information is calculated.

[0026] In the embodiment of the present application, if the first trigger time is less than or equal to the preset total duration of the online education, it means that within the preset total duration of the online education, prompt information has already been output, that is, within the preset total duration, the user has already been verified; the timing restarts at the moment when the actual online time of the user's online education exceeds the preset total duration of the online education, and the overtime trigger time is calculated. When the re-timing time reaches the overtime trigger time, prompt information is output and the user is verified again. In the above manner, supervision of the user within the overtime period of their online education can be achieved.

[0027] Combined with the technical solution provided in the above first aspect, in some possible implementation manners, the method further includes: during the timing process, if it is detected that the user pauses the online education operation, the timing is paused.

[0028] In the embodiment of the present application, in the above manner, the user can pause the timing when pausing the online education, so as to ensure that the timing is carried out while the user is conducting online education, and to avoid verifying the user when the user pauses the online education, resulting in the failure of user verification, ending the online education, and thus reducing the user experience.

[0029] Second aspect, the present application provides a remote supervision device, the device includes: a prompt module, configured to calculate, according to a preset random algorithm, a moment for outputting prompt information during online education; the prompt information is information for prompting a user to perform a preset behavior, and the online education is online learning or online examination; when the moment is during the online education process, the prompt information is output; an image input module, configured to acquire a user behavior image of the behavior made by the user based on the prompt information, where the user behavior image includes a face image; a supervision module, configured to authenticate the user according to the preset user information of the user and the face image; and authenticate the behavior of the user according to the prompt information and the behavior in the user behavior image.

[0030] Third aspect, an embodiment of the present application provides an electronic device, including: a processor and a memory, the processor is connected to the memory; the memory is used for storing a program; the processor is used for calling the program stored in the memory and executing the method provided in the embodiment of the first aspect and / or some possible implementation manners in combination with the embodiment of the first aspect as described above.

[0031] Fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when being run by a processor, executes the method provided in the embodiment of the first aspect and / or some possible implementation manners in combination with the embodiment of the first aspect as described above. Description of the Drawings

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required to be used in the embodiments of the present application will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, and thus should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0033] Figure 1 It is a step flowchart of a remote supervision method provided by an embodiment of the present application.

[0034] Figure 2 It is a module block diagram of a remote supervision device provided by an embodiment of the present application.

[0035] Figure 3 It is a module block diagram of an electronic device provided by an embodiment of the present application. Detailed Embodiments

[0036] Next, the technical solutions in the embodiments of the present application will be described with reference to the drawings in the embodiments of the present application.

[0037] In view of the fact that online teaching cannot supervise the objects of online teaching, the inventors of this application have conducted research and exploration and proposed the following embodiments to solve the above problems.

[0038] Please refer to Figure 1 , Figure 1 which is a flowchart of the steps of a remote supervision method provided by an embodiment of this application.

[0039] The following combines Figure 1 to describe the specific process and steps of a remote supervision method. It should be noted that the remote supervision method provided by the embodiments of this application is not limited to Figure 1 the order shown below.

[0040] Step S101: Calculate the moment to output a prompt message during the online education process according to a preset random algorithm.

[0041] Optionally, before step S101, obtain the user's operation instruction, where the operation instruction includes an instruction to start online education; in response to the operation instruction, display the operation interface corresponding to the online education.

[0042] Obtaining the user's operation instruction can be detecting that the user clicks the button to start online education, or collecting the user's voice related to starting online education, which is not limited here. Also, because the operation instruction includes an instruction to start online education, in response to the operation instruction, display the operation interface corresponding to the online education. By the above method, the user can start online education after issuing the operation instruction, thereby improving the user's experience of online education.

[0043] After obtaining the user's operation instruction and responding to the operation instruction, the moment to output a prompt message during the online education process can be calculated according to a preset random algorithm. Among them, the preset random algorithm can be set according to the actual situation.

[0044] After calculating the moment to output the prompt message, this method can continue to execute step S102.

[0045] Step S102: Output a prompt message when the moment is during the online education process.

[0046] In the embodiments of this application, if the calculated moment to output the prompt message is during the online education process, it means that a prompt message will be output during the online education process.

[0047] Specifically, the output prompt message can be in the form of voice, playing a voice message to prompt the user to perform a preset behavior; it can also be directly displayed on the user's online education interface to prompt the user to perform a preset behavior; or a display page for prompt messages can be superimposed on the user's online education interface, and a message prompting the user to perform a preset behavior is displayed on this display page. Among them, the prompt message is a message prompting the user to perform a preset behavior, such as: prompting the user to turn the head left or right, or reminding the user to blink. Online education is online learning or online examination.

[0048] Optionally, when outputting the prompt message, pause the online education.

[0049] When outputting the prompt message, pausing the online education that the user is performing can enable the user to continue learning the previous content after subsequent user verification, so that the user can enter the learning state faster, thereby improving the user experience.

[0050] After outputting the prompt message, this method can continue to execute step S103.

[0051] Step S103: Obtain a user behavior image of the user's behavior based on the prompt message, where the user behavior image includes a face image.

[0052] Specifically, the user behavior image of the user based on the prompt message can be collected by calling the camera on the electronic device implementing this method.

[0053] A possible implementation manner of collecting images is: after outputting the prompt message to turn the head to the right, start calling the camera to collect the user behavior image of the user.

[0054] Another possible implementation manner of collecting images is: within a preset time after outputting the prompt message, based on the detected collection instruction triggered by the user, collect the user behavior image of the user's behavior based on the prompt message. For example, within 1 minute after outputting the prompt message, if the collection instruction triggered by the user is detected, then collect the user behavior image of the user's behavior based on the prompt message.

[0055] Through the above method, the user can start collecting the user behavior image after being prepared, avoiding collecting the user behavior image when the user is not prepared, which may lead to failure of user verification and thus reduce the user experience.

[0056] In addition, if the collection instruction triggered by the user is not detected within the above preset time, it means that the user is not performing online education in front of the screen. At this time, the online education can be directly ended. Through the above method, the power consumption can be reduced.

[0057] After collecting the user behavior image, this method can continue to execute step S104.

[0058] Step S104: Authenticate the user according to the preset user information and facial image of the user; authenticate the user's behavior according to the prompt information and the behavior in the user behavior image.

[0059] Among them, the preset user information can be the facial image taken by the user when registering the software; it can also be the facial image of the user himself uploaded by the user when registering the software.

[0060] In addition, authenticate the user's behavior according to the prompt information and the behavior in the user behavior image, that is, verify whether the user makes corresponding actions according to the content of the prompt information. For example, if the prompt information is to blink, then judge whether the user makes a blinking action in the user behavior image.

[0061] Through the above method, the user can be authenticated and the behavior can be verified, so as to supervise the user's online education.

[0062] Optionally, after authenticating the user and verifying the behavior, if both the authentication and the behavior verification are passed, the operation interface of the online education is returned. Successful verification means that the user himself is conducting online education. At this time, the operation interface of the online education is returned so that the user can continue with the online education.

[0063] If any one of the authentication and the behavior verification fails, it is judged whether the number of times of obtaining the user behavior image is less than the preset number n; if so, the user behavior image is obtained again, and the above verification operation is repeated (that is, steps S103 and S104 are repeated); if not, the online education ends, where n is any positive integer.

[0064] Through the above method, for users who fail in the authentication and the behavior verification, the user behavior image can be obtained again for re-verification, thus ensuring the accuracy of the verification, that is, it will not be determined that the user verification fails and the online learning or online exam ends due to accidental reasons such as the user making wrong actions in the prompt information, causing inconvenience to the user. And by setting the judgment that the number of image acquisitions is less than n times, it can also prevent the authentication and the behavior verification of the user from looping continuously in the case of verification failure, thereby improving the efficiency of verifying the user.

[0065] In addition, after each acquisition of the user behavior image, the obtained user behavior image can also be displayed so that the user can view his state during the process of taking the user behavior image, so as to facilitate the user to adjust the shooting angle or adjust his actions.

[0066] In summary, during the process of users' online education, by outputting prompt information and authenticating the users' identities and behaviors after obtaining the user behavior images of the users' behaviors based on the prompt information, it can be determined whether it is the user himself / herself conducting the online education, and it can also be determined whether the user's attention is focused on the online education. In addition, by outputting prompt information and enabling the users to perform corresponding actions according to the prompt information, it is also possible to remind the users during the online education and keep the users in a good state during the online education.

[0067] It should be noted that during the process of users' online education, according to whether the moment calculated in step S101 is during the process of online education, user verification can be not performed on the user, that is, steps S102 - S104 are not executed; user verification can also be performed on the user once, that is, steps S102 - S104 are only executed once; user verification can also be performed on the user multiple times, that is, steps S102 - S104 can be executed multiple times.

[0068] Optionally, the moment for calculating and outputting the prompt information in step S101 can calculate all the moments in one execution process, or can be executed multiple times, and only one moment is calculated each time.

[0069] Next, an implementation manner of calculating the time point for outputting the prompt information by a random algorithm will be introduced in detail.

[0070] Specifically, when the operation interface of the online education is displayed, timing starts; the first trigger time for outputting the prompt information for the first time is calculated according to a preset random algorithm; it is determined whether the first trigger time is greater than the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the process of the online education.

[0071] In the embodiment of the present application, by determining whether the calculated first trigger time is greater than the preset total duration of the online education, it can be determined whether to output the prompt information within the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the process of the online education, that is, the prompt information will be output during the process of the online education. Specifically, when the timing reaches the first trigger time, the prompt information is output. By determining that the first trigger time is less than or equal to the preset total duration of the online education, it can be ensured that the user is verified at least once within the preset total duration of the online education.

[0072] Optionally, if the first trigger time is greater than the preset total duration, no prompt information is output.

[0073] In an embodiment of the present application, if the first trigger time is greater than the preset total duration, it means that no prompt information is output during the online education process, that is, the user is not verified during the online education process. In this way, the interference to the user in online education can be reduced, the use of device peripherals can be reduced, thereby reducing the burden on the device, and the power consumption can also be reduced.

[0074] Optionally, during the timing process, if it is detected that the user pauses the online education operation, the timing is paused.

[0075] Among them, the user's operation of pausing the online education can be clicking the button to pause the online education, or collecting the user's voice related to pausing the online education, which is not limited here. By pausing the timing after detecting the user's operation of pausing the online education, the timing can be synchronized with the user's online education, avoiding the situation that after the user pauses the online education, the timing time reaches the first trigger time, prompt information is output, and the user fails the verification in the subsequent verification, thereby reducing the user experience.

[0076] Optionally, calculating the first trigger time for the first output of prompt information according to a preset random algorithm includes: obtaining an average probability number according to the total number of timings, a preset trigger moment, a preset coefficient, and a preset random function, where the preset trigger moment is the moment when it starts to allow the output of prompt information, and the total number of timings is the quotient of the preset total duration and the preset time interval; obtaining a non-average probability distribution sequence according to the total number of timings, a preset duration, a preset probability distribution turning point, and a preset slope, where the starting moment of the preset duration is the timing moment, its ending moment is the preset trigger moment, and the preset slope is the slope value of the linear distribution that the preset duration and the preset probability distribution turning point follow; obtaining a trigger moment according to the average probability number and the non-average probability distribution sequence; and determining the first trigger time according to the trigger moment and the preset moment.

[0077] In an embodiment of the present application, substituting the value obtained by multiplying the total number of timings and the preset coefficient into the preset random function can obtain an average probability value; then, according to the total number of timings, a preset duration, a preset probability distribution turning point, and a preset slope, a non-average probability distribution sequence can be obtained; then, selecting the corresponding value in the non-average probability distribution sequence according to the above average probability value as the trigger moment, and finally subtracting the preset moment from the trigger moment to obtain the first trigger time.

[0078] For example, the preset total duration of the online education is 5 minutes, the system trigger time interval is in minutes, and the preset time interval is 1 minute, then the total number of timings N is 5 times; substituting the preset trigger moment t pSet to 2, that is, at the second moment, the output of prompt information is only allowed to start; set the preset coefficient a to 2, then substitute the above parameters into the preset random function to obtain an average probability number r, r = ([t p :a×N]), that is, r = ([2:10]), and r is any positive integer from 2 to 10. Then, set the preset duration n 0 to 1 minute, that is, within the time period from 0 to 1 minute, the output of prompt information is not allowed; set the preset probability distribution turning point n s to 3, set the preset slope k to 1, then according to the above parameters, a non-average probability sequence s can be obtained, s = [n 0 +1:n s +1:N], that is, s = [2:4:5], and it can be calculated that s = [2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5]. According to the value of the average probability number r, select the corresponding value in the above non-average probability sequence s as the trigger time t s , for example: if r is 6, then take the 6th value in s as the trigger time t s , that is, the trigger time t s is 4; then set the preset time t n to 0~n, where n is the number of times the user has been verified, that is, when calculating the first trigger time, since the user has not been verified before, the preset time t n is 0. Therefore, the first trigger time is t s -t n , that is, the first trigger time is 4 minutes. Therefore, when the online education reaches the 4th minute, the prompt information is output.

[0079] By calculating the first trigger time in the above way, it can be ensured that within the preset duration, no prompt information is output for the online education, so that the user will not be affected by user verification at the initial stage of the online education, so that the user can enter the learning or examination state faster.

[0080] In addition, the preset coefficient a can also be set to a larger value, such as 4. Then, on the basis of the above parameters, the average probability number r = ([2:20]), that is, r is any positive integer from 2 to 20. Since the non-average probability sequence s = [2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5], when r takes any positive integer from 14 to 20, s will have no corresponding value for r. In this case, the timing can be paused, and no prompt information is output during the process of the online education. By setting the preset coefficient to a larger value, it can make the prompt information be output randomly during the process of the online education, that is, it may output prompt information or may not output prompt information, thus improving the working efficiency of the software and reducing the power consumption.

[0081] Optionally, when outputting a prompt message each time, calculate the total number of times the prompt message is output; determine whether the total number of output times is less than a preset number of output times, where the preset number of output times is the preset number of times to output the prompt message in online education; if so, obtain a new average probability number according to the total timing count, preset trigger time, preset coefficient, and preset random function; obtain a new trigger time according to the newly obtained average probability number and the non-average probability distribution sequence; obtain the current corresponding preset time according to the total number of output times; determine the trigger time for the next output of the prompt message according to the newly obtained trigger time and the current corresponding preset time.

[0082] In the embodiments of the present application, by calculating the number of trigger times for outputting the prompt message, it is possible to obtain how many trigger times have been calculated; by determining whether the number of trigger times is less than the preset number of trigger times, it is possible to determine whether it is necessary to calculate the next trigger time. If the number of trigger times is less than the preset number of trigger times, then it is necessary to calculate the next trigger time, that is, obtain a new average probability number according to the total timing count, preset trigger time, preset coefficient, and preset random function, then select the corresponding value in the non-average probability distribution sequence calculated for the first time according to the newly obtained average probability value as the trigger time, and finally subtract the corresponding preset time at this time from the trigger time to obtain the next trigger time.

[0083] Continuing with the example of calculating the first trigger time above, according to the total timing count, preset trigger time, and preset coefficient, an average probability number r can be obtained, r = ([t p :a×N]), that is, r = ([2:10]), and r is any positive integer from 2 to 10. The non-average probability sequence s has been calculated previously, that is, s = [2, 2, 3, 3, 3, 4, 4, 4, 4, 5, 5, 5, 5]. If r is 2, then take the second value in s as the trigger time t s , that is, the trigger time t s is 2; if this is the second calculation of the trigger time, then the preset time t n at this time is 1. Therefore, the first trigger time is t s - t n , that is, the second trigger time is 1 minute. In this example, the preset total duration of the online education is 5 minutes, and the first trigger time is 4 minutes. Therefore, the calculated second trigger time is within the process of this online education. Therefore, 1 minute after the first output of the prompt message, the prompt message is output again.

[0084] In the above manner, it is possible to determine whether it is necessary to output a prompt message again each time a prompt message is output, that is, to determine whether user verification is still required. Moreover, after determining that it is necessary to output a prompt message, the next trigger time can be calculated. In addition, after calculating the next trigger time, it can be determined whether the next trigger time is during the online education process. If the trigger time is during the above-mentioned online education process, a prompt message is output when the timing reaches the trigger time, that is, user verification is performed; if the trigger time is not during the above-mentioned online education process, no prompt message is output during the time period from the moment when the trigger time is calculated to the end time of the online education, that is, user verification is not performed during this time period.

[0085] Optionally, if the first trigger time is greater than the preset total duration, the timing is stopped, and the timing is restarted at the moment when the actual online time of the online education exceeds the preset total duration, and the moment when the sum of the preset total duration and the overtime timing time is equal to the first trigger time is determined as the moment to output the prompt message.

[0086] If the first trigger time is greater than the preset total duration, it means that no prompt message will be output within the preset total duration of the online education, so the timing can be stopped. If the actual online time of the online education exceeds the preset total duration, it means that the user is learning or taking an exam overtime. Then, the timing is restarted at the moment when the actual online duration of the online education exceeds the preset total duration, and a prompt message is output when the sum of the preset total duration and the overtime timing time is equal to the first trigger time.

[0087] In the above manner, a prompt message can be output during the process of the user learning or taking an exam overtime, so as to facilitate the supervision of the part where the user learns or takes an exam overtime.

[0088] Optionally, if the first trigger time is less than or equal to the preset total duration, the timing is restarted at the moment when the actual online time of the online education exceeds the preset total duration, and the overtime trigger time for outputting the prompt message is calculated.

[0089] If the first trigger time is less than or equal to the preset total duration, it means that at least one prompt message has been output within the preset total duration of the online education. If the actual online duration of the online education exceeds the preset total duration, it means that the user is learning or taking an exam overtime. Then, the timing is restarted at the moment when the actual online time of the online education exceeds the preset total duration, and the overtime trigger time is recalculated. A prompt message is output when the restarted timing time reaches the overtime trigger time.

[0090] Specifically, the overtime trigger time t c after the user's online education overtime can be calculated by using a preset random function, the trigger moment t s the total number of timing times N, and a preset coefficient a, that is, t c= ([t s : a × N]), where the trigger time t s is the trigger time t calculated when calculating the trigger time for the last time s .

[0091] In addition, it is also possible to judge whether the calculated timeout trigger time t c is within the interval [t s : N]. If so, when the re-timed time reaches the timeout trigger time t c , a prompt message is output; if not, the timing is stopped, that is, during this timeout process, no prompt message is output, that is, user verification is no longer performed in the subsequent process. Through the above method, the working efficiency of the software can be improved and the power consumption can be reduced.

[0092] Next, an example is used to illustrate a remote supervision method.

[0093] After the user clicks the button to start online education on the display interface, in response to the user's operation instruction, the operation interface corresponding to the online education is displayed so that the user can start online education. And, while displaying the operation interface corresponding to the online education, the timing starts.

[0094] Then, according to the method for calculating the first trigger time described above, calculate the first trigger time t for the first output of the prompt message 1 , and judge whether the first trigger time t 1 is greater than the preset total duration T of the online education. If the first trigger time t 1 is less than or equal to the preset total duration T, then when the timing reaches the first trigger time t 1 , a display page for the prompt message is superimposed on the above operation interface, and information prompting the user to perform a preset behavior is displayed on the display page, and the online education is paused.

[0095] While outputting the prompt message, judge whether the total number of times of outputting the prompt message is less than the preset number of outputs. If so, calculate the second trigger time t according to the method for calculating the trigger time described above 2 . If not, only output the prompt message and do not calculate the second trigger time t 2 .

[0096] Within the preset time after outputting the prompt message, if the user clicks the button to start the detection, that is, if a trigger instruction of the user is detected, the user behavior image of the behavior made by the user based on the prompt message is collected. And, the collected image is displayed in a specific shape on the display page, and at the same time, the prompt message is displayed in the area outside the shape. If the trigger instruction of the user is not detected, the online education ends.

[0097] After collecting the user behavior image, authenticate the user based on the preset user information and facial information of the user; verify the user's behavior according to the prompt information and the behavior in the user behavior image. If the verification of the user's behavior information fails, determine whether the number of times of obtaining the user behavior image is less than the preset number of times. If so, re-collect the user behavior image, and then authenticate the user based on the preset user information of the user and the re-collected facial information; verify the user's behavior according to the prompt information and the behavior in the re-collected user behavior image. If the verification passes, return to the operation interface of the online education that was paused previously, and use the time when the prompt information was first displayed as the second trigger time t 2 as the start time. When the timing reaches the second trigger time t 2 , repeat the above steps to verify the user. If the number of times of obtaining the user behavior image is greater than or equal to the preset number of times, end the online education.

[0098] When the actual online time of the user's online education exceeds the preset total duration T, that is, the user's online education times out, re-time at the moment when the actual online time of the online education exceeds the preset total duration T, and re-calculate the timeout trigger time. When the re-calculated time reaches the timeout trigger time, output the prompt information, and repeat the above steps of authenticating and verifying the user's behavior to verify the user during the timeout period.

[0099] If the first trigger time t 1 is greater than the preset total duration T, stop timing, that is, no prompt information is output within the preset total duration T of the online education. When the actual online time of the user's online education exceeds the preset total duration T, re-time at the moment when the actual online time of the online education exceeds the preset total duration T, and when the sum of the preset total duration T and the timeout timing time is equal to the first trigger time t 1 , output the prompt information, and repeat the above steps of authenticating and verifying the user's behavior to verify the user during the timeout period.

[0100] In addition, during the timing process, if it is detected that the user pauses the operation of the online education, pause the timing.

[0101] Please refer to Figure 2 , based on the same inventive concept, the embodiment of the present application further provides a remote supervision device. The device 100 includes: a prompt module 101, an image input module 102, and a supervision module 103.

[0102] The prompt module 101 is used to calculate, according to a preset random algorithm, the moment to output a prompt message during online education. The prompt message is a message for prompting the user to perform a preset behavior, and the online education is online learning or online examination. When the moment is during the process of online education, the prompt message is output.

[0103] The image input module 102 is used to obtain a user behavior image of the user's behavior based on the prompt message, where the user behavior image includes a face image.

[0104] The supervision module 103 is used to authenticate the user according to the user's preset user information and the face image; and authenticate the user's behavior according to the prompt message and the behavior in the user behavior image.

[0105] Optionally, the supervision module 103 is further used to, after authenticating the user's identity and behavior, if both the identity authentication and the behavior authentication are passed, return to the operation interface of the online education; if any one of the identity authentication and the behavior authentication fails, determine whether the number of times of obtaining the user behavior image is less than a preset number n; if so, re-obtain the user behavior image and repeat the above verification operation; if not, end the online education, where n is any positive integer.

[0106] Optionally, the prompt module 101 is further used to pause the online education when outputting the prompt message.

[0107] Optionally, the image input module 102 is specifically used to, within a preset time after outputting the prompt message, collect a user behavior image of the user's behavior based on the prompt message based on a detected acquisition instruction triggered by the user.

[0108] Optionally, the prompt module 101 is further used to obtain an operation instruction of the user before calculating, according to the preset random algorithm, the moment to output the prompt message during the online education. The operation instruction includes an instruction to start the online education; and in response to the operation instruction, display the operation interface corresponding to the online education.

[0109] Optionally, the prompt module 101 is specifically used to start timing when displaying the operation interface of the online education; calculate a first trigger time for the first output of the prompt message according to the preset random algorithm; determine whether the first trigger time is greater than the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the process of the online education.

[0110] Optionally, the prompt module 101 is further used to, if the first trigger time is greater than the preset total duration, not output the prompt message.

[0111] Optionally, the prompting module 101 is specifically configured to obtain an average probability number according to the total number of timings, a preset triggering moment, a preset coefficient, and a preset random function, where the preset triggering moment is the moment when outputting prompt information is allowed to start, and the total number of timings is the quotient of the preset total duration and the preset time interval; obtain a non-average probability distribution sequence according to the total number of timings, the preset duration, the preset probability distribution turning point, and the preset slope, where the starting moment of the preset duration is the timing moment, and its ending moment is the preset triggering moment, and the preset slope is the slope value of the linear distribution that the preset duration and the preset probability distribution turning point obey; obtain a triggering moment according to the average probability number and the non-average probability distribution sequence; determine the first triggering time according to the triggering moment and the preset moment.

[0112] Optionally, the prompting module 101 is further configured to calculate the total number of outputs of the output prompt information each time the prompt information is output; determine whether the total number of outputs is less than the preset number of outputs, where the preset number of outputs is the number of times of outputting prompt information preset in online education; if so, obtain a new average probability number according to the total number of timings, the preset triggering moment, the preset coefficient, and the preset random function; obtain a new triggering moment according to the newly obtained average probability number and the non-average probability distribution sequence; obtain the currently corresponding preset moment according to the total number of outputs; determine the triggering time for the next output of the prompt information according to the newly obtained triggering moment and the currently corresponding preset moment.

[0113] Optionally, the prompting module 101 is further configured to stop timing if the first triggering time is greater than the preset total duration, and restart timing at the moment when the actual online time in online education exceeds the preset total duration, and determine the moment when the sum of the preset total duration and the overtime timing time is equal to the first triggering time as the moment for outputting prompt information.

[0114] Optionally, the prompting module 101 is further configured to restart timing at the moment when the actual online time in online education exceeds the preset total duration if the first triggering time is less than or equal to the preset total duration, and calculate the overtime triggering time for outputting prompt information.

[0115] Optionally, the prompting module 101 is further configured to pause timing if it detects an operation by the user to pause online education during the timing process.

[0116] Please refer to Figure 3, based on the same inventive concept, the following is a schematic structural block diagram of an electronic device 200 provided by an embodiment of the present application. The electronic device 200 is used for the above-mentioned remote supervision method. In the embodiments of the present application, the electronic device 200 may be, but is not limited to, a personal computer (PC), a smart phone, a tablet computer, a personal digital assistant (PDA), a mobile internet device (MID), etc. Structurally, the electronic device 200 may include a processor 210 and a memory 220.

[0117] The processor 210 is directly or indirectly electrically connected to the memory 220 to achieve data transmission or interaction. For example, these components can be electrically connected to each other through one or more communication buses or signal lines. Among them, the processor 210 may be an integrated circuit chip with signal processing capabilities. The processor 210 may also be a general-purpose processor. For example, it may be a central processing unit (CPU), a digital signal processor (DSP), an application specific integrated circuit (ASIC), discrete gate or transistor logic devices, discrete hardware components, and can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present application. In addition, the general-purpose processor may be a microprocessor or any conventional processor, etc.

[0118] The memory 220 may be, but is not limited to, a random access memory (RAM), a read only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), and an electrically erasable programmable read-only memory (EEPROM). The memory 220 is used to store a program, and the processor 210 executes the program after receiving an execution instruction.

[0119] It should be understood that Figure 3 the structure shown is only schematic, and the electronic device 200 provided by the embodiments of the present application may also have Figure 3 fewer or more components, or have a structure Figure 3The different configurations shown. In addition, Figure 3 Each component shown can be implemented by software, hardware, or a combination thereof.

[0120] It should be noted that, since those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices, and units described above can refer to the corresponding processes in the foregoing method embodiments, and will not be elaborated herein.

[0121] Based on the same inventive concept, an embodiment of the present application also provides a computer-readable storage medium, on which a computer program is stored, and the computer program, when run, executes the method provided in the foregoing embodiments.

[0122] The storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or a data center that integrates one or more available media. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).

[0123] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely illustrative. For example, the division of units is only a logical function division, and there can be other division methods in actual implementation. For another example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point, the displayed or discussed couplings or direct couplings or communication connections to each other can be through some communication interfaces. The indirect couplings or communication connections of the devices or units can be electrical, mechanical, or other forms.

[0124] In addition, the units described as separate components may or may not be physically separated, and the components displayed as units may or may not be physical units, that is, they can be located in one place, or they can be distributed to multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0125] Furthermore, in each embodiment of the present application, the functional modules can be integrated together to form an independent part, or each module can exist alone, or two or more modules can be integrated to form an independent part.

[0126] In this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations.

[0127] The above are only embodiments of the present application and are not intended to limit the protection scope of the present application. For those skilled in the art, various modifications and changes can be made to the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included within the protection scope of the present application.

Claims

1. A remote supervision method, characterized in that, the method includes: Calculating, according to a preset random algorithm, the moment to output a prompt message during online education; the prompt message is a message for prompting the user to perform a preset behavior, and the online education is online learning or online examination; When the moment is during the online education process, output the prompt message; Obtaining a user behavior image of the behavior made by the user based on the prompt message, wherein the user behavior image includes a face image; Authenticating the user according to the preset user information of the user and the face image; verifying the behavior of the user according to the prompt message and the behavior in the user behavior image; Wherein, after outputting the prompt message, the method further includes: determining whether the total number of times of outputting the current prompt message exceeds a preset number of output times; if not, calculating, according to the random algorithm, the moment for the next output of the prompt message during the online education process; Wherein, the calculating, according to a preset random algorithm, the moment to output a prompt message during the online education process includes: When displaying the operation interface of the online education, start timing; calculating, according to the preset random algorithm, the first trigger time for the first output of the prompt message; determining whether the first trigger time is greater than the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the online education process; Wherein, the calculating, according to the preset random algorithm, the first trigger time for the first output of the prompt message includes: Obtaining an average probability number according to the total number of timing times, a preset trigger moment, a preset coefficient, and a preset random function, where the preset trigger moment is the moment when outputting the prompt message is allowed to start, and the total number of timing times is the quotient of the preset total duration and a preset time interval; obtaining a non-average probability distribution sequence according to the total number of timing times, a preset duration, a preset probability distribution turning point, and a preset slope, where the starting moment of the preset duration is the timing moment and its ending moment is the preset trigger moment, and the preset slope is the slope value of the linear distribution followed by the preset duration and the preset probability distribution turning point; obtaining a trigger moment according to the average probability number and the non-average probability distribution sequence; determining the first trigger time according to the trigger moment and the preset moment.

2. The method according to claim 1, characterized in that, after authenticating the user's identity and verifying the behavior, the method further includes: If both the identity authentication and the behavior verification are passed, return to the operation interface of the online education; If any one of the identity verification and the behavior verification fails, determine whether the number of times of obtaining the user behavior image is less than a preset number of times n; if so, re-obtain the user behavior image and repeat the above verification operations; if not, end the online education, where n is any positive integer, and the above verification operations are: perform identity verification on the user according to the preset user information of the user and the face image; perform behavior verification on the user according to the prompt information and the behavior in the user behavior image.

3. The method according to claim 1, wherein, before the moment of outputting the prompt information calculated according to the preset random algorithm during the online education, the method further includes: obtaining an operation instruction of the user, where the operation instruction includes an instruction to start the online education; responding to the operation instruction and displaying an operation interface corresponding to the online education.

4. The method according to claim 1, wherein, the method further includes: if the first trigger time is greater than the preset total duration, then do not output the prompt information.

5. The method according to claim 1, wherein, calculating the first trigger time for the first output of the prompt information according to the preset random algorithm further includes: calculating the total number of outputs of the prompt information each time the prompt information is output; judging whether the total number of outputs is less than a preset number of outputs, where the preset number of outputs is the number of times of outputting the prompt information preset in the online education; if so, re-obtain an average probability number according to the total number of timing times, the preset trigger moment, the preset coefficient, and the preset random function; re-obtain a trigger moment according to the re-obtained average probability number and the non-average probability distribution sequence; obtain the current corresponding preset moment according to the total number of outputs; determine the trigger time for the next output of the prompt information according to the re-obtained trigger moment and the current corresponding preset moment.

6. A remote supervision device, wherein, the device includes: a prompt module, configured to calculate a moment of outputting a prompt information during the online education according to a preset random algorithm; the prompt information is information for prompting the user to perform a preset behavior, and the online education is online learning or online examination; when the moment is during the online education, then output the prompt information; an image input module, configured to obtain a user behavior image of the behavior made by the user based on the prompt information, where the user behavior image includes a face image; a supervision module, configured to perform identity verification on the user according to the preset user information of the user and the face image; perform behavior verification on the user according to the prompt information and the behavior in the user behavior image; wherein, after outputting the prompt information, the prompt module is further configured to: determine whether the total number of outputs of the currently output prompt information exceeds a preset number of outputs; if not, calculate the moment of the next output of the prompt information during the online education according to the random algorithm. Among them, the prompt module calculates the moment to output prompt information during online education according to a preset random algorithm, specifically used for: When displaying the operation interface of the online education, start timing; calculate the first trigger time for the first output of the prompt information according to the preset random algorithm; determine whether the first trigger time is greater than the preset total duration of the online education; if the first trigger time is less than or equal to the preset total duration, it indicates that the first trigger time is during the online education process. Among them, the prompt module calculates the first trigger time for the first output of the prompt information according to the preset random algorithm, specifically used for: Obtain an average probability number according to the total number of timing times, preset trigger moment, preset coefficient, and preset random function. The preset trigger moment is the moment when outputting the prompt information is allowed to start, and the total number of timing times is the quotient of the preset total duration and the preset time interval; obtain a non-average probability distribution sequence according to the total number of timing times, preset duration, preset probability distribution turning point, and preset slope. The starting moment of the preset duration is the timing moment, and its ending moment is the preset trigger moment. The preset slope is the slope value of the linear distribution that the preset duration and the preset probability distribution turning point obey; obtain a trigger moment according to the average probability number and the non-average probability distribution sequence; determine the first trigger time according to the trigger moment and the preset moment.

7. An electronic device Characterized in that It includes: A processor and a memory, the processor is connected to the memory; The memory is used to store programs; The processor is used to run the program stored in the memory and execute the method according to any one of claims 1-5.

8. A computer-readable storage medium Characterized in that A computer program is stored thereon, and the computer program executes the method according to any one of claims 1-5 when run by a computer.

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