A wake-up method and device

Abstract

The embodiment of the present application discloses a wake-up method and device. The technical solution provided by the embodiment of the present application obtains the user's usage data, and generates usage conditions that match different users respectively according to the usage data. When the usage conditions are met, it further detects whether the preset verification conditions are met. When the preset verification conditions are met, the biometric data of the target user and the learning needs of the target user are obtained, and the comparison is performed with the pre-stored biometric data to obtain the comparison result. When the comparison result is consistent, the learning result matched according to the learning needs is output; combined with the actual usage scenario, the biometric data of the target user is used to determine whether to wake up the scanning pen, so that the user can ask and answer questions without feeling, avoid cumbersome operations, and do not need the user to interrupt the learning process, so that the operation process is more efficient.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of scanning pen technology, and in particular to a wake-up method, device, equipment and storage medium. Background Art

[0002] With the effective combination of educational resources and Internet technology, more and more terminal devices have functions such as answering questions, feedback on difficult problems and intelligent question search. Such terminal devices use a scanning pen to scan the questions to be searched and upload them to the Internet, and obtain the corresponding question analysis from the network and present it to the user.

[0003] Currently, there are usually two ways to wake up the scanner. The first way is to wake up through a wake-up word. The scanner needs to be woken up by the user's voice before each use of the scanner. When the user encounters a problem during operation, frequent wake-ups are required, which is troublesome on the one hand, and there are also problems such as false wake-ups and low wake-up rates that affect the experience on the other hand. The second way to wake up is to long-press the physical voice or click the software icon to wake up. The user needs to interrupt his or her operation process and pick up the scanner to use it, which affects the concentration and efficiency of learning. Summary of the invention

[0004] The embodiments of the present application provide a scanning pen wake-up method, device, equipment and storage medium to achieve seamless question and answer in the user's operation scenario, without interrupting the learning process, and improving learning efficiency.

[0005] In a first aspect, an embodiment of the present application provides a scanning pen wake-up method, comprising:

[0006] Collecting user usage data and biometric data, storing the usage data and biometric data, and generating usage conditions matching the user based on the usage data;

[0007] When the use condition is met, detecting whether a preset verification condition is met;

[0008] When the verification condition is met, biometric data of the target user is collected, and the learning needs of the target user are obtained;

[0009] Comparing the biometric data of the target user with the stored biometric data to obtain a comparison result;

[0010] When the comparison result is consistent, the learning result matched according to the learning requirement is output.

[0011] In a second aspect, an embodiment of the present application provides a scanning pen wake-up device, including:

[0012] User data collection module: used to collect user usage data and biometric data, store the usage data and biometric data, and generate usage conditions matching the user according to the usage data;

[0013] Preset condition comparison module: used to detect whether the preset verification condition is met when the use condition is met;

[0014] Target data acquisition module: used to collect biometric data of a target user and obtain the learning needs of the target user when the verification condition is met;

[0015] Feature data comparison module: used to compare the biometric data of the target user with the stored biometric data to obtain a comparison result;

[0016] Learning result output module: used for outputting the learning result matched according to the learning requirement when the comparison result is consistent.

[0017] In a third aspect, an embodiment of the present application provides a computer device, including: a memory and one or more processors;

[0018] The memory is used to store one or more programs;

[0019] When the one or more programs are executed by the one or more processors, the one or more processors implement the scanning pen wake-up method as described in the first aspect.

[0020] In a fourth aspect, an embodiment of the present application provides a storage medium comprising computer executable instructions, which, when executed by a computer processor, are used to execute the scanning pen wake-up method as described in the first aspect.

[0021] The embodiment of the present application obtains the user's usage data and generates usage conditions that match different users according to the usage data. When the usage conditions are met, it is further detected whether the preset verification conditions are met. When the preset verification conditions are met, the biometric data of the target user and the learning needs of the target user are obtained, and the comparisons are made with the pre-stored biometric data to obtain the comparison results. When the comparison results are consistent, the learning results matched according to the learning needs are output. In combination with the actual usage scenarios, the biometric data of the target user is used to determine whether to wake up the scanning pen, so that users can ask and answer questions without feeling, avoiding cumbersome operations, and there is no need for users to interrupt the learning process, so that the operation process is more efficient. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 This is a flow chart of a scanning pen wake-up method provided in an embodiment of the present application;

[0023] Figure 2 is a flow chart of another scanning pen wake-up method provided in an embodiment of the present application;

[0024] Figure 3 is a flow chart of another scanning pen wake-up method provided in an embodiment of the present application;

[0025] Figure 4 It is a structural schematic diagram of a scanning pen wake-up device provided in an embodiment of the present application;

[0026] Figure 5 It is a structural schematic diagram of a scanning pen wake-up device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] In order to make the purpose, technical scheme and advantages of the present application clearer, the specific embodiments of the present application are further described in detail below in conjunction with the accompanying drawings. It is understood that the specific embodiments described herein are only used to explain the present application, rather than to limit the present application. It should also be noted that, for the convenience of description, only the part related to the present application but not all the contents are shown in the accompanying drawings. Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flow charts. Although the flow chart describes each operation (or step) as a sequential process, many of the operations therein can be implemented in parallel, concurrently or simultaneously. In addition, the order of each operation can be rearranged. The process can be terminated when its operation is completed, but it can also have additional steps not included in the accompanying drawings. The process can correspond to a method, a function, a procedure, a subroutine, a subprogram, etc.

[0028] The embodiment of the present application provides a scanning pen wake-up method, device, equipment and storage medium. The embodiment of the present application obtains the user's usage data, and generates usage conditions that match different users according to the usage data. When the usage conditions are met, it further detects whether the preset verification conditions are met. When the preset verification conditions are met, the target user's biometric data and the target user's learning needs are obtained, and the comparison results are compared with the pre-stored biometric data to obtain the comparison results. When the comparison results are consistent, the learning results matched according to the learning needs are output; combined with the actual usage scenario, the target user's biometric data is used to determine whether to wake up the scanning pen, so that the user can ask questions without feeling, avoid cumbersome operations, and do not need the user to interrupt the learning process, so that the operation process is more efficient.

[0029] The following are detailed descriptions respectively.

[0030] Embodiment 1

[0031] Figure 1A flowchart of a scanning pen wake-up method provided in an embodiment of the present application is given. The scanning pen wake-up method provided in an embodiment of the present application can be executed by a scanning pen wake-up device. The scanning pen wake-up method device can be implemented in hardware and / or software and integrated in the scanning pen wake-up device. The scanning pen wake-up device can be a smart device such as a tutoring machine, a smart phone, etc. that has data collection, data processing and analysis capabilities.

[0032] The following description takes a scanning pen wake-up device executing a scanning pen wake-up method as an example. Figure 1 , the scanning pen wake-up method includes:

[0033] Step 101 : collect usage data and biometric data of a user, store the usage data and biometric data, and generate usage conditions matching the user according to the usage data.

[0034] In the embodiment, users usually refer to different students, and of course, they can also refer to any other person who needs to use the scanning pen. For different users, the application of the scanning pen has different usage times and usage scenarios. Before application, the user's data is collected first to obtain the user's usage data and biometric data. As an example, when a user purchases a new scanning pen, he registers an account for the scanning pen, and then collects his own biometric data. In another example, the user is an old user, and the usage data and biometric data have been collected before. Due to changes in the usage environment, etc., the user's usage data and biometric data are re-collected and the previous data is replaced.

[0035] In the above, the user's usage data can be usage time, usage frequency, etc. Assuming that the usage data is usage frequency, for example, the number of times the user uses the scanning pen in each time period of using the scanning pen is obtained. The number of times the user uses the scanning pen in time period A is 1 time, the number of times the user uses the scanning pen in time period B is 12 times, and the number of times the user uses the scanning pen in time period C is 10 times. Since the number of times the user uses the scanning pen in time period B and time period C is higher, and the number of times the user uses the scanning pen in time period A is very low, the number of times the user uses the scanning pen in time period A is ignored, and time period B and time period C are used as usage conditions.

[0036] Biometric data is data used to represent different user identity characteristics, such as fingerprint data, facial feature data, iris feature data, etc.

[0037] Step 102: When the use condition is met, detect whether a preset verification condition is met.

[0038] The verification condition can be understood as a wake-up condition. When the verification condition is met, the scanner wakes up and can automatically execute other steps. The verification condition is a condition that is personalized and pre-stored in advance according to the user's needs. For example, the verification condition can be to detect the nodding action of the target user, or to detect the clapping sound of the user, etc. When the verification condition is detected to be met in the corresponding time period, the scanner wakes up and starts the scanner. In the embodiment, the application of the scanner can be controlled by voice, so when the verification condition is met, the sound receiving function of the scanner is turned on.

[0039] In this embodiment, taking the biometric data including the user's facial feature data as an example, correspondingly, detecting whether the preset voice question and answer conditions are met specifically includes:

[0040] Step 1021, detecting whether there is a user in the set area.

[0041] The set area can be input by the user. For example, it can be a desk, study table, etc. The user can take a photo of the set area to form image data and store it in the scanning pen, so that the scanning pen can use the image as the background and monitor whether the user appears in the set area in real time through the camera. At this time, the user in the set area is not necessarily the target user.

[0042] Step 1022: collect the user's facial feature data, and compare the user's facial feature data with pre-stored biometric data.

[0043] In the embodiment, the facial feature data of the user is further matched with the pre-stored biometric feature data, and when a match is found, the user in the set area is defined as the target user.

[0044] Step 1023: When the facial feature data of the user is consistent with the pre-stored biometric feature data, define the user as a target user.

[0045] Step 103: When the verification condition is met, biometric data of the target user is collected, and the learning needs of the target user are obtained.

[0046] When the verification conditions are met, based on the above-listed situations, the sound pickup function of the scanner can be turned on, and then the biometric data of the target user can be collected. The target biometric data can be the same data as the biometric data pre-stored in the scanner, or it can be one or more of the multiple pre-stored biometric data. Exemplarily, the biometric data of the user collected in advance includes fingerprint data, voice feature data, and facial feature data. When the verification conditions are met, the facial feature data of the user as the target user is collected. Alternatively, the voice feature data of the target user is collected. Alternatively, the facial feature data and voice feature data of the target user can be collected.

[0047] In the above, the learning needs can be understood as the problems that the target user expects to be solved by the scanning pen. Exemplarily, the target user expects to scan the English words in the book with the scanning pen to obtain the corresponding Chinese translation. In another example, the target user may also expect to scan the exercises in the book with the scanning pen to obtain the answers to the exercises. Obtaining the learning needs of the target user may be scanning the area to be answered with the scanning pen to obtain the learning needs. In other examples, the learning needs may be that the target user outputs the problem in the form of voice expression, the voice is collected by the scanning pen, the voice is processed and analyzed, and the answer corresponding to the processing result is obtained. At this time, obtaining the learning needs of the target user may be receiving the language signal output by the target user. The voice signal contains the specific content of the learning needs.

[0048] Step 104: Compare the target user's biometric data with the stored biometric data to obtain a comparison result.

[0049] In this embodiment, it is first determined whether the use conditions are met. Only when the use conditions are met can the scanner be turned on. When the use conditions are not met, the scanner can be set to standby mode. At this time, even if the pre-stored verification conditions are met, the scanner will not be awakened. When the use conditions are met and the preset verification conditions are met, the target user's biometric data is compared with the stored biometric data to obtain a comparison result. In the embodiment, it is assumed that the biometric data is facial feature data, and the stored biometric data also includes facial feature data. The specific processing method for comparing the two sets of facial feature data can be to calculate the similarity of the two sets of facial feature data. When the similarity reaches a threshold, the comparison result is consistent. On the contrary, when the similarity is lower than the threshold, the comparison result is inconsistent, which is equivalent to verification failure. As an application scenario, the use condition corresponding to the target user is time period B. When time period B is met on the day, it means that the use condition is met, and it is further determined whether the preset verification condition is met. In this scenario, the verification condition is nodding. When it is detected that a user nods, the sound receiving function of the scanner is started, that is, the target user's learning needs can be obtained by collecting the target user's voice information. However, the premise of collecting the target user's voice information is to confirm the identity of the current user, that is, to determine whether the user is the target user. In the application scenario, the facial feature data of the current user is obtained and matched with the previously collected biometric data. When consistent facial feature data is matched, the user is defined as the target user.

[0050] Step 105: When the comparison result is consistent, output the learning result matched according to the learning requirement.

[0051] Continuing with the above application scenario, when the comparison results are consistent, that is, the current user's facial feature data is consistent with the biometric data, the current user is confirmed to be the target user, and the corresponding answer service can be provided for the target user, that is, the learning results are matched with the acquired learning needs. Relative to the learning needs, the learning results can be understood as the answers to the exercises, or the ideas for solving the problems, or the English translation for Chinese, or the Chinese translation for English, and so on.

[0052] Embodiment 2

[0053] Figure 2 A flowchart of a scanning pen wake-up method provided in this embodiment is shown. Figure 2 , the scanning pen wake-up method includes:

[0054] Step 201 : Collect the user's usage time and biometric data, and store the usage time and biometric data.

[0055] Step 202, obtaining all usage time corresponding to the same user.

[0056] In the embodiment, the usage data is the usage time. When the user uses the scanning pen multiple times, the time when the user uses the scanning pen is recorded respectively. The total usage time corresponding to the same user is obtained, that is, for each user, all the time points when the user uses the scanning pen are obtained. The time point at this time can be the timestamp of starting the scanning pen. For example, the first time the scanning pen is used is t1-t2, and the second time the scanning pen is used is t3-t4, then t1 and t2 are obtained.

[0057] Step 203: Obtain the usage time period of the user according to the usage time, and determine whether the duration corresponding to the usage time period meets the preset standard duration.

[0058] For example, t1-t2 and t3-t4 obtained above can generate two usage time periods respectively. The time period calculated according to the user's usage time is from 13:00 to 13:50 in the afternoon, that is, the duration is 50 minutes, and the preset standard duration is 1 hour, which does not meet the preset standard duration. It should be noted that in the embodiment, the preset standard duration can include multiple, for example, the preset standard duration is an integer multiple of 1 hour, and the preset standard duration closest to the duration can be selected as a reference according to the user's usage duration. For example, if the above duration is 50 minutes, the preset standard duration of 1 hour is selected for comparison. If the duration is 110 minutes, the preset standard duration of 2 hours can be selected for comparison.

[0059] Step 204: When the duration does not meet the preset standard duration, the usage time period is adjusted to obtain a new adjusted time period, the duration of the adjusted time period meets the preset standard duration, and the adjusted time period or the usage time period meeting the preset standard duration is used as the target time period for user matching.

[0060] For example, if the above duration is 50 minutes and it is adjusted to one hour, then it is adjusted according to its specific time period from 13:00 to 13:50, and 13:50 can be padded to 14:00. In another embodiment, when the time points corresponding to the user's usage time are all the same or there is only one time point, the time point is used as the reference value, and the preset time interval is moved forward on the basis of the reference value to obtain the starting time point, and the preset time interval is moved backward on the basis of the reference value to obtain the ending time point, and the usage time period matching the user is generated according to the starting time point and the ending time point. The embodiment generates the corresponding time period according to the timestamp of the user using the scanning pen at different times as the usage condition. Among them, it is assumed that the user only uses the scanning pen once in total before collecting the usage time, so there is only one time point corresponding to the usage time. Or, before collecting the usage time, the user uses the scanning pen a total of three times, but the time point of each use of the scanning pen happens to be the same, which is equivalent to only one time point corresponding to the usage time.

[0061] When there are multiple time points corresponding to the usage time of the user, the smallest time point and the latest time point in the usage time are obtained, and a usage time period matching the user is generated according to the smallest time point and the latest time point.

[0062] Before the user's usage time is collected, there is only one time point corresponding to the usage time. In this step, there are multiple time points corresponding to the usage time, such as t1, t2, and t3, among which the smallest time point is t1 and the largest time point is t3. Then t2 is removed and t1 and t3 are used, with t1 as the revelation time of the time period and t3 as the end time of the time period.

[0063] Step 205: When the use condition is met, it is detected whether there is a target user in the set area.

[0064] In this embodiment, the set area is a designated area for detecting the target user, which is usually a range that can be captured by the scanning pen. In this step, it is detected whether the target user exists, for example, by using face recognition or other methods to detect whether the target user appears in the set area.

[0065] Step 206: When there is a target user in the set area, the current action posture of the target user is collected.

[0066] The action gestures are, for example, nodding, raising head, shaking head, waving hands, etc., which are stored in advance in the scanning pen by the user. When the target user is detected in the set area, it is detected whether the target user makes an action corresponding to the pre-stored action gesture.

[0067] Step 207 : Compare the current motion posture with the pre-stored motion posture, and calculate the similarity between the current motion posture and the pre-stored motion posture.

[0068] Step 208, determining whether the similarity is greater than a threshold. When the similarity is greater than the threshold, it indicates that the target user has completed the corresponding action gesture, and the preset verification condition is met. On the contrary, when the similarity is less than the threshold, the preset verification condition is not met.

[0069] Step 209: When the similarity is greater than a threshold, voice information of the target user is collected; and voiceprint feature data and learning requirements of the target user are obtained according to the voice information.

[0070] The voiceprint feature data is biometric data, which is used to indicate the identity information of the target user. When the voiceprint feature data of the target user is detected, it is further compared with the pre-stored biometric data.

[0071] Step 210: Compare the target user's biometric data with the stored biometric data to obtain a comparison result.

[0072] Step 211: When the comparison result is consistent, output the learning result matched according to the learning requirement.

[0073] Embodiment 3

[0074] Figure 3 Another scanning pen wake-up method provided in an embodiment of the present application is shown. Figure 3 As shown, the scanning pen wake-up method includes:

[0075] Step 301, collect the user's usage data and biometric data, store the usage data and biometric data, and generate usage conditions matching the user according to the usage data. The biometric data includes the user's facial feature data and the user's posture feature data.

[0076] Step 302: When the use condition is met, detect whether there is a user in the set area.

[0077] This step is used to determine whether a user appears in a set area. For example, the set area is a certain range area centered on a desk. If any user appears in the area, it means that the user is detected. However, the detected user is not necessarily the target user.

[0078] Step 303: collect the user's facial feature data and user posture feature data, and compare the user's facial feature data with pre-stored biometric feature data.

[0079] In this embodiment, the biometric data includes facial feature data and user posture feature data. The facial feature data may specifically correspond to live face feature data, and the user posture feature data may include sitting posture, or the posture of sitting and holding a pen, etc.

[0080] Step 304: When the facial feature data of the user is consistent with the pre-stored biometric feature data, define the user as a target user.

[0081] The embodiment determines whether a user currently in a set area is a target user through facial feature data of the user.

[0082] Step 305: determine whether a preset verification condition is met based on the user posture feature data.

[0083] In this step, the user posture feature data is compared to see whether the verification condition is met. Specifically, the user posture data of the user in the current set area is detected, and the detected user posture data is compared with the pre-stored user posture data to see whether they are consistent. When the current user is determined to be the target user based on the facial feature data, it is further determined whether the user currently meets the verification condition. Assuming that the current user posture feature data is a posture of sitting and holding a pen, it is detected that the current user's posture is sitting, but not holding a pen, so the preset verification condition is not met. On the contrary, assuming that the current pre-stored user posture feature data is a posture of sitting and holding a pen, and the current user's posture is detected to be sitting and holding a pen, the preset verification condition is met.

[0084] Step 306: When the verification condition is met, the biometric data of the target user is collected, and the learning needs of the target user are obtained.

[0085] Step 307: Compare the target user's biometric data with the stored biometric data to obtain a comparison result.

[0086] Step 308: When the comparison result is consistent, output the learning result matched according to the learning requirement.

[0087] Step 309 , collecting the head posture of the target user, and when it is detected according to the head posture that the head of the target user is facing the display screen, determining whether the iris biometric feature of the target user is detected.

[0088] Step 310: When the iris biometric feature of the target user is detected, the brightness of the display screen is adjusted and the learning result is displayed on the display screen.

[0089] Step 311: when the iris biometric feature of the target user is not detected, turn off the display screen.

[0090] In this embodiment, after the learning results are matched according to the learning needs of the target user, it is further determined whether to display the learning results. Specifically, it is determined whether to display the learning results by detecting the user's head posture and further based on the user's iris biometrics. As an application scenario, the head posture of the target user is detected by the camera on the scanning pen, specifically, whether the target user's head is facing the display screen of the scanning pen. When the target user faces the display screen of the scanning pen, it is further detected whether the target user's eyes are looking at the display screen. When both conditions are met, the brightness of the display screen is adjusted to light up the display screen. Assume that although the target user is facing the display screen of the scanning pen, the target user's eyes are not detected looking at the display screen. At this time, the shielding of the display screen is turned off, that is, the display screen is in a black screen state, and no learning results are presented.

[0091] Embodiment 4

[0092] Figure 4 A scanning pen wake-up device provided in Example 4 of the present application is shown, including a user data collection module 401, a preset condition comparison module 402, a target data acquisition module 403, a feature data comparison module 404 and a learning result output module 405, wherein the user data collection module 401 is used to collect the user's usage data and biometric data, store the usage data and biometric data, and generate usage conditions matching the user according to the usage data; the preset condition comparison module 402 is used to detect whether the preset verification condition is met when the usage condition is met; the target data acquisition module 403 is used to collect the target user's biometric data when the verification condition is met, and obtain the learning needs of the target user; the feature data comparison module 404 is used to compare the target user's biometric data with the stored biometric data to obtain a comparison result; the learning result output module 405 is used to output the learning result matched according to the learning need when the comparison result is consistent.

[0093] Furthermore, the above-mentioned preset condition comparison module 402 may specifically include: when the usage condition is met, an area user detection submodule, used to detect whether there is a user in the set area; a facial feature collection submodule: used to collect facial feature data of the user, and compare the facial feature data of the user with pre-stored biometric data; a user feature comparison submodule, used to define the user as a target user when the facial feature data of the user is consistent with the pre-stored biometric data.

[0094] In another exemplary embodiment, the preset condition comparison module 402 may further include a regional user detection submodule, which is used to detect whether there is a user in the set area when the use condition is met; a motion posture collection submodule, which collects the current motion posture of the target user when there is a target user in the set area. A posture comparison submodule is used to compare the current motion posture with the pre-stored motion posture, calculate the similarity between the current motion posture and the pre-stored motion posture, and determine whether the similarity is greater than a threshold.

[0095] In other exemplary embodiments, the preset condition comparison module 402 may further specifically include an area user detection submodule, which is used to detect whether there is a user in a set area when the usage condition is met; a user feature collection submodule, which is used to collect facial feature data and user posture feature data of the user, and compare the facial feature data of the user with pre-stored biometric data; a facial feature comparison submodule, which is used to define the user as a target user when the facial feature data of the user is consistent with the pre-stored biometric data; and a posture data judgment submodule, which is used to judge whether the preset verification condition is met based on the user posture feature data.

[0096] Furthermore, the usage data is practical time. In the user data collection module 401, usage conditions matching the user are generated according to the usage data, specifically, all usage times corresponding to the same user are obtained. When the time points corresponding to the usage time of the user are all the same or there is only one time point, the time point is used as a reference value, and a preset time interval is shifted forward on the basis of the reference value to obtain a start time point, and a preset time interval is shifted backward on the basis of the reference value to obtain an end time point. A usage time period matching the user is generated according to the start time point and the end time point. When there are multiple time points corresponding to the usage time of the user, the smallest time point and the latest time point in the usage time are obtained, and a usage time period matching the user is generated according to the smallest time point and the latest time point.

[0097] Furthermore, a head posture detection module may be included, which is used to collect the head posture of the target user, and when the target user's head is detected facing the display screen according to the head posture, it is determined whether the iris biometric feature of the target user is detected; when the iris biometric feature of the target user is detected, the display screen brightness is adjusted and the learning result is displayed on the display screen. When the iris biometric feature of the target user is not detected, the display screen is turned off.

[0098] Embodiment 5

[0099] like Figure 5As shown, an embodiment of the present application also provides a scanning pen wake-up device, including: a memory 501 and one or more processors 502; the memory 501 is used to store one or more programs; when the one or more programs are executed by the one or more processors 502, the one or more processors implement the scanning pen voice wake-up method as described in the present application.

[0100] An embodiment of the present application also provides a storage medium containing computer executable instructions, which, when executed by a computer processor, are used to execute the scanning pen wake-up method provided in the above embodiment, and the scanning pen wake-up method includes: collecting user usage data and biometric data, storing the usage data and biometric data, and generating usage conditions matching the user according to the usage data; when the usage conditions are met, detecting whether preset verification conditions are met; when the verification conditions are met, collecting the biometric data of the target user, and obtaining the learning needs of the target user; comparing the biometric data of the target user with the stored biometric data to obtain a comparison result; when the comparison result is consistent, outputting the learning result matched according to the learning need.

[0101] Storage medium - any of various types of memory devices or storage devices. The term "storage medium" is intended to include: installation media, such as CD-ROM, floppy disk or tape device; computer system memory or random access memory, such as DRAM, DDR RAM, SRAM, EDO RAM, Rambus RAM, etc.; non-volatile memory, such as flash memory, magnetic media (such as hard disk or optical storage); registers or other similar types of memory elements, etc. Storage media may also include other types of memory or combinations thereof. In addition, the storage medium may be located in the first computer system in which the program is executed, or may be located in a different second computer system, which is connected to the first computer system via a network (such as the Internet). The second computer system can provide program instructions to the first computer for execution. The term "storage medium" may include two or more storage media that may reside in different locations (for example, in different computer systems connected by a network). The storage medium may store program instructions (for example, embodied as a computer program) that can be executed by one or more processors.

[0102] Of course, the storage medium containing computer executable instructions provided in the embodiment of the present application is not limited to the scanning pen wake-up method described above, and the computer executable instructions can also execute related operations in the scanning pen voice method provided in any embodiment of the present application.

[0103] The scanning pen wake-up device, equipment and storage medium provided in the above embodiments can execute the scanning pen wake-up method provided in any embodiment of the present application. For technical details not described in detail in the above embodiments, please refer to the scanning pen wake-up method provided in any embodiment of the present application.

[0104] The above are only preferred embodiments of the present application and the technical principles used. The present application is not limited to the specific embodiments described herein, and various obvious changes, readjustments and substitutions that can be made by those skilled in the art will not deviate from the scope of protection of the present application. Therefore, although the present application is described in more detail through the above embodiments, the present application is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present application, and the scope of the present application is determined by the scope of the claims.

Claims

1. A scanning pen wake-up method, characterized in that: include: Collecting usage data and biometric data of a user, storing the usage data and biometric data, and generating usage conditions matching the user according to the usage data, wherein the usage data includes usage time, and generating usage conditions matching the user according to the usage time includes: obtaining all usage time corresponding to the same user, obtaining a usage time period of the user according to the usage time, determining whether the duration corresponding to the usage time period meets a preset standard duration, and when the duration does not meet the preset standard duration, adjusting the usage time period to obtain a new adjusted time period, wherein the duration of the adjusted time period meets the preset standard duration, using the adjusted time period or the usage time period meeting the preset standard duration as a target time period for matching the user, and determining the target time period as the usage condition matching the user; When the use condition is met, detecting whether a preset verification condition is met, the detecting whether the preset verification condition is met includes: detecting whether there is a target user in a set area, when there is a target user in the set area, collecting the current motion posture of the target user, comparing the current motion posture with a pre-stored motion posture, calculating the similarity between the current motion posture and the pre-stored motion posture, judging whether the similarity is greater than a threshold, when the similarity is greater than the threshold, the preset verification condition is met, and when the similarity is less than the threshold, the preset verification condition is not met; When the verification condition is met, biometric data of the target user is collected, and the learning needs of the target user are obtained; Comparing the biometric data of the target user with the stored biometric data to obtain a comparison result; When the comparison result is consistent, the learning result matched according to the learning requirement is output.

2. The scanning pen wake-up method according to claim 1, characterized in that: The biometric data includes user facial feature data; Accordingly, the detection of whether the preset verification condition is met includes: Detect whether there is a user in the set area; Collecting facial feature data of the user, and comparing the facial feature data of the user with pre-stored biometric feature data; When the facial feature data of the user is consistent with pre-stored biometric feature data, the user is defined as a target user.

3. The scanning pen wake-up method according to claim 1, characterized in that: The biometric data includes user facial feature data and user posture feature data; Accordingly, the detection of whether the preset verification condition is met includes: Detect whether there is a user in the set area; Collecting facial feature data and user posture feature data of the user, and comparing the facial feature data of the user with pre-stored biometric feature data; When the facial feature data of the user is consistent with the pre-stored biometric feature data, defining the user as a target user; Determine whether a preset verification condition is met based on the user posture feature data.

4. The scanning pen wake-up method according to claim 1, characterized in that: The biometric data includes voiceprint feature data; Accordingly, the collecting of biometric data of a target user and obtaining the learning needs of the target user includes: Collect the target user's voice information; The voiceprint feature data and learning needs of the target user are obtained according to the voice information.

5. The scanning pen wake-up method according to claim 1, characterized in that: Also includes: Collecting the head posture of the target user, and when detecting that the head of the target user is facing the display screen according to the head posture, determining whether the iris biometric feature of the target user is detected; When the iris biometric feature of the target user is detected, adjusting the brightness of the display screen and displaying the learning result on the display screen; When the iris biometric feature of the target user is not detected, the display screen is turned off.

6. A scanning pen wake-up device, characterized in that: include: User data collection module: used to collect user usage data and biometric data, store the usage data and biometric data, and generate usage conditions matching the user according to the usage data, the usage data includes usage time, the user data collection module is specifically used to obtain all usage time corresponding to the same user, obtain the usage time period of the user according to the usage time, determine whether the duration corresponding to the usage time period meets the preset standard duration, when the duration does not meet the preset standard duration, adjust the usage time period to obtain a new adjusted time period, the duration of the adjusted time period meets the preset standard duration, use the adjusted time period or the usage time period meeting the preset standard duration as the target time period for user matching, and determine the target time period as the usage condition matching the user; Preset condition comparison module: used for detecting whether the preset verification condition is met when the use condition is met, the detection of whether the preset verification condition is met includes: detecting whether there is a target user in the set area, when the target user exists in the set area, collecting the current action posture of the target user, comparing the current action posture with the pre-stored action posture, calculating the similarity between the current action posture and the pre-stored action posture, judging whether the similarity is greater than a threshold, when the similarity is greater than the threshold, the preset verification condition is met, when the similarity is less than the threshold, the preset verification condition is not met; Target data acquisition module: used to collect biometric data of a target user and obtain the learning needs of the target user when the verification condition is met; Feature data comparison module: used to compare the biometric data of the target user with the stored biometric data to obtain a comparison result; Learning result output module: used for outputting the learning result matched according to the learning requirement when the comparison result is consistent.

7. A scanning pen wake-up device, characterized in that: include: memory and one or more processors; The memory is used to store one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the scanning pen wake-up method as described in any one of claims 1-5.

8. A storage medium containing computer executable instructions, characterized in that: The computer executable instructions are used to execute the scanning pen wake-up method as described in any one of claims 1-5 when executed by a computer processor.

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