Control method and device of electronic equipment

Abstract

The invention discloses a control method and device of electronic equipment, and belongs to the technical field of electronic equipment. The control method of the electronic equipment comprises the following steps: acquiring multi-dimensional scene data when a user uses the electronic equipment in a first time period and use data when the user uses the electronic equipment in the first time period; based on a use habit analysis model, performing fusion processing on the multi-dimensional scene data and the use data to obtain use habit information of using the electronic equipment by the user; determining a control strategy of the electronic equipment according to the use habit information; and controlling the electronic equipment based on the control strategy.

Description

Technical Field

[0001] The present application belongs to the technical field of electronic equipment, and specifically relates to a control method and device for electronic equipment. Background Art

[0002] With the widespread use of smart electronic devices, the ownership rate of smart devices, such as mobile phones, among minors has shown a significant increase. According to relevant surveys, the mobile phone usage rate among children aged 6-12 has reached 67.8%. To guide children in the correct and appropriate use of mobile phones, it is necessary to regulate their mobile phone behavior.

[0003] Currently, age is the primary factor used for control. For example, users under the age of 6 can only use specific applications (Applications, Apps) and for a predetermined period of time. This control strategy considers relatively few factors and has poor control effects. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a method and device for controlling an electronic device, which can effectively solve the problem of poor control effect caused by the single factor considered in the control strategy when controlling the behavior of child users using smart electronic devices in related technologies.

[0005] In a first aspect, an embodiment of the present application provides a method for controlling an electronic device, comprising:

[0006] Acquire multi-dimensional scene data when the user uses the electronic device during a first period of time and usage data of the user using the electronic device during the first period of time;

[0007] Based on the usage habit analysis model, multi-dimensional scene data and usage data are integrated and processed to obtain the user's usage habit information of electronic devices;

[0008] Determine the control strategy of electronic devices based on usage habit information;

[0009] Based on the control strategy, control the electronic equipment.

[0010] In a second aspect, an embodiment of the present application provides a control device for an electronic device, comprising:

[0011] an acquisition module, configured to acquire multi-dimensional scene data when a user uses the electronic device during a first period of time and usage data of the user using the electronic device during the first period of time;

[0012] A processing module is used to integrate the multi-dimensional scene data and the usage data based on the usage habit analysis model to obtain the user's usage habit information of the electronic device;

[0013] a determination module, configured to determine a control strategy for the electronic device based on usage habit information;

[0014] The control module is used to control the electronic equipment based on the control strategy.

[0015] In a third aspect, an embodiment of the present application provides an electronic device comprising a processor and a memory, wherein the memory stores programs or instructions that can be run on the processor, and when the programs or instructions are executed by the processor, the steps of the method described in the first aspect are implemented.

[0016] In a fourth aspect, an embodiment of the present application provides a readable storage medium, on which a program or instruction is stored, and when the program or instruction is executed by a processor, the steps of the method described in the first aspect are implemented.

[0017] In a fifth aspect, an embodiment of the present application provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the steps of the method described in the first aspect.

[0018] In a sixth aspect, an embodiment of the present application provides a computer program product, which is stored in a storage medium and executed by at least one processor to implement the steps of the method described in the first aspect.

[0019] In an embodiment of the present application, multi-dimensional scene data of a user using an electronic device during a first period of time and usage data of the user using the electronic device during the first period of time are obtained; based on a usage habit analysis model, the multi-dimensional scene data and usage data are fused and processed to obtain usage habit information of the user using the electronic device; a control strategy for the electronic device is determined based on the usage habit information; and the electronic device is controlled based on the control strategy. That is, this embodiment comprehensively considers the multi-dimensional scene data of the user using the electronic device during the first period of time and the usage data of the electronic device, that is, comprehensively considers multiple factors, so that the usage habit information of the child user for the electronic device can be more accurately determined, and further, when determining the control strategy of the electronic device based on the usage habits, the control strategy can be more accurately determined, thereby effectively controlling the child user and improving the control effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] Figure 1 A flowchart of a method for controlling an electronic device provided in an embodiment of the present application;

[0021] Figure 2 A flowchart of another method for controlling an electronic device provided in an embodiment of the present application;

[0022] Figure 3 A flowchart of another method for controlling an electronic device provided in an embodiment of the present application;

[0023] Figure 4 A flowchart of another method for controlling an electronic device provided in an embodiment of the present application;

[0024] Figure 5 A schematic structural diagram of a control device for an electronic device provided in an embodiment of the present application;

[0025] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application;

[0026] Figure 7 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The following will be combined with the accompanying drawings in the embodiments of the present application to clearly describe the technical solutions in the embodiments of the present application. Obviously, the embodiments described are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field are within the scope of protection of this application.

[0028] The terms "first," "second," and the like in the specification of this application are used to distinguish similar objects, and are not used to describe a specific order or precedence. It should be understood that the terms used in this manner are interchangeable where appropriate, so that the embodiments of this application can be implemented in an order other than that illustrated or described herein, and that the objects distinguished by "first," "second," and the like are generally of the same type, and do not limit the number of objects; for example, the first object can be one or more. Furthermore, the term "and / or" in this specification indicates at least one of the connected objects, and the character " / " generally indicates that the objects connected are in an "or" relationship.

[0029] When related technologies control users' behavior in using smart electronic devices, they mainly use age as a factor. The factors considered are relatively simple, and the control strategies are relatively simple, resulting in poor control effects.

[0030] In order to improve the control effect of users' behavior in using smart electronic devices, the embodiments of the present application provide a control method and device for electronic devices, which can effectively solve the problem that the related technology has poor control effect due to the single factor considered in the control strategy when controlling users' behavior in using smart electronic devices.

[0031] The control method and device of the electronic device provided in the embodiments of the present application will be described in detail below with reference to the accompanying drawings through specific embodiments.

[0032] Figure 1The flowchart of a control method for an electronic device provided in an embodiment of the present application is provided. The electronic device can be a mobile phone, tablet computer, laptop computer, or other electronic device that is easily addictive to the user. These electronic devices typically contain various apps, including but not limited to teaching apps, entertainment apps, shopping apps, etc. In particular, when a user is accustomed to using entertainment apps, the solution provided in an embodiment of the present application can effectively control the user's usage behavior to prevent the user from becoming addicted to such apps, which may affect their physical and mental health and academic performance. In some embodiments, the user may be a user with poor self-control, such as a child, a teenager, or an adult.

[0033] like Figure 1 As shown, the control method of the electronic device may include the following steps:

[0034] S110: Acquire multi-dimensional scene data when a user uses an electronic device in a first time period and usage data of the user using the electronic device in the first time period.

[0035] S120 : Based on the usage habit analysis model, the multi-dimensional scene data and the usage data are integrated and processed to obtain the usage habit information of the user using the electronic device.

[0036] S130: Determine a control strategy for the electronic device based on the usage habit information.

[0037] S140: Control the electronic device based on the control strategy.

[0038] In an embodiment of the present application, multi-dimensional scene data of a user using an electronic device during a first period of time and usage data of the user using the electronic device during the first period of time are obtained; based on a usage habit analysis model, the multi-dimensional scene data and usage data are integrated and processed to determine the user's usage habit information for the electronic device; based on the usage habit information, a control strategy for the electronic device is determined; and based on the control strategy, the electronic device is controlled. That is, this embodiment comprehensively considers the multi-dimensional scene data of the user using the electronic device during the first period of time and the usage data of the electronic device, that is, comprehensively considers multiple factors, so that the user's usage habit information for the electronic device can be determined more accurately, and then when the control strategy of the electronic device is determined based on the usage habit, the control strategy can be determined more accurately, thereby effectively controlling the user and improving the control effect.

[0039] The above steps are explained in detail below:

[0040] In S110 , the first time period may be a historical time period, for example, the day, two days, or one week closest to the current time. This embodiment does not limit the length of the first time period.

[0041] The multi-dimensional scene data may be scene data of a user using an electronic device, for example, including but not limited to the time period during which the electronic device is used, the location where the electronic device is used, and the intensity of ambient light when the electronic device is used.

[0042] The usage period can be determined based on the system clock in the electronic device. The system clock can record the start and end times of the user's use of the electronic device to obtain the usage period. For example, when the electronic device detects that the user starts using the electronic device, it can record the start time, and when the user stops using the electronic device, it can record the end time. The electronic device can also identify the user's identity through facial recognition, fingerprints, etc. to determine the time period when the user uses the electronic device, so that the user's usage habits can be more accurately determined later.

[0043] The usage location of the electronic device can be determined based on the Global Positioning System (GPS) in the electronic device, or by means of a base station, Wireless Fidelity (Wi-Fi), Bluetooth, etc.

[0044] For example, the usage location of the electronic device may be determined once every certain period of time, for example, once every 10 seconds.

[0045] The usage scenario of the electronic device can be determined based on the location where the electronic device is used. The usage scenario may include, but is not limited to, school scenario, home scenario, tutoring institution scenario, internet cafe scenario, etc.

[0046] For example, the spectral characteristics of the voice signal in the environment of the electronic device can also be analyzed using a Fourier transform to determine whether background noise is present in the environment, and thus determine the scene the electronic device is in. For example, if a lot of background noise is detected in the environment, it can be preliminarily determined that the user is in a scene such as an internet cafe. Further determination can then be made using other means, such as combining the recognized voice to further determine whether the user is in an internet cafe. For example, if game-related voice is further recognized, it can be determined that the user is in an internet cafe.

[0047] The intensity of ambient light in an electronic device can be determined by a light sensor in the electronic device. The light sensor can monitor the light intensity in the electronic device's environment in real time. Based on the ambient light intensity measured by the light sensor, it can be determined whether the user is using the electronic device in a dimly lit environment or a brightly lit environment. For example, the light sensor can sample at a frequency of 50 Hz.

[0048] The user's usage data of the electronic device during the first time period may include, but is not limited to, the applications used, usage duration, and operation behaviors. The electronic device may record each application used by the user, the usage duration, and operation behaviors. Operation behaviors herein may include, but are not limited to, click operations, swipe operations, and interactive operations on the application used, and may also include click frequency, swipe frequency, and interaction frequency.

[0049] By analyzing the usage data of users' electronic devices in different scenarios, we can more accurately understand the users' usage habits of electronic devices, thereby more accurately determining the control strategies of electronic devices and achieving effective management and control of users' behavior in using electronic devices.

[0050] In some embodiments, the electronic device may include a Trusted Execution Environment (TEE), and each sensor may send the obtained multi-dimensional scene data and usage data of the user to the TEE for storage to ensure the security of the private data.

[0051] In S120, the usage habit analysis model is used to analyze the user's usage habits of the electronic device. The usage habit analysis model may be, for example, a deep learning model, a machine learning model, etc.

[0052] The usage habit analysis model takes multidimensional scene data and usage data as input and outputs usage habit information. The model fuses these multidimensional scene data and usage data to derive information about a user's usage habits. For example, by fusing multidimensional scene data and usage data, we can determine when, where, and for how long the user watched the video, thereby deriving information about the user's usage habits. For example, a user might watch videos on their electronic device at home between 9:30 PM and 11:00 PM every Monday through Friday.

[0053] For example, a usage habit analysis model can be used in TEE to combine multi-dimensional scenario data and usage data to analyze the user's usage habit information in the first time period.

[0054] By analyzing user usage habits, we can more accurately understand their usage and develop appropriate control strategies for their electronic device usage. This allows for more effective management of user behavior and reduces the impact of excessive use. Furthermore, specific control strategies are developed based on the user's specific electronic device usage, taking into account individual differences in cognitive development and enabling differentiated management and control for different users.

[0055] In S130, different usage habit information may correspond to different control strategies, that is, this embodiment may dynamically determine the control strategy based on the user's different usage habit information, thereby more effectively managing the user's behavior in using the electronic device and preventing the user from becoming addicted to the electronic device.

[0056] For example, if a user has the habit of using electronic devices every day during winter and summer vacations, the corresponding control strategy may be to remind the user when the daily usage time of the electronic device during winter and summer vacations exceeds a first duration. The usage duration here can be the continuous usage time per day or the total usage time per day.

[0057] For another example, for a user's habit of using electronic devices every day on school days, the corresponding control strategy may be: when the duration of the user's use of a preset application of the electronic device on school days exceeds a second duration, the user's access to the application is turned off. Among them, if the duration of use of video application A on a certain school day exceeds the second duration, the electronic device may turn off the user's access to video application A, that is, the user will no longer be able to use video application A on subsequent school days. The user's access to the video application may also be restored within a period of time after being turned off, for example, after being turned off for a week or two days. For another example, the user's access to the video application may also be restored only during the winter and summer vacations. Specific strategies can be dynamically set and adjusted according to actual needs.

[0058] In S140, the electronic device may be controlled based on the control strategy. For example, the control strategy may include prompting the user when the daily usage time of the electronic device during winter or summer vacation exceeds a first time period. When the electronic device detects that the user has used the electronic device for a day during winter or summer vacation for a time period exceeding the first time period, the electronic device may output a prompt message to the user.

[0059] The output method of the prompt information may include, but is not limited to, text prompts, voice prompts, etc. The content of the prompt information may include, for example, "Your usage time today has reached the required time, please stop using the electronic device immediately." Alternatively, it may include: "Your usage time today has reached the required time, please stop using the electronic device immediately. If you continue to use it, the electronic device will be forced to lock the screen or your permission to use the electronic device will be revoked."

[0060] In order to obtain a usage habit analysis model, in some embodiments, the method for controlling the electronic device may further include the following steps:

[0061] The following operations are performed repeatedly until a usage habit analysis model is obtained:

[0062] Performing machine learning model training based on training samples stored in the electronic device to obtain a usage habit analysis sub-model, wherein the training samples include multidimensional scenario data samples when the sample user uses the electronic device, usage data samples of the sample user using the electronic device, and usage habit labels corresponding to the multidimensional scenario data samples and the usage data samples;

[0063] The usage habit analysis sub-model is sent to the service node, so that the service node aggregates the usage habit analysis sub-models obtained by training multiple electronic devices to obtain a usage habit analysis model.

[0064] The usage habit analysis sub-model is a model obtained by training each electronic device based on locally stored training samples. Different electronic devices can be trained based on different training samples to obtain corresponding usage habit analysis sub-models. In actual application, the usage habit analysis sub-models can include at least two.

[0065] The training samples used by different electronic devices may include data of the same user in different time periods, data of different users in the same time period, or data of different users in different time periods.

[0066] For example, when different electronic devices use training samples based on the same user's data over different time periods, the user's usage habits can be more accurately analyzed. When different electronic devices use training samples based on data from different users over different time periods, the cognitive development differences between different users can be fully accounted for, making the control strategies developed subsequently universally applicable.

[0067] Each training sample includes known multi-dimensional scenario data and usage data, as well as corresponding usage habit labels. The usage habit labels here are used to represent the user's actual usage habit information.

[0068] Taking the example of all training samples corresponding to the same user, illustratively, each electronic device can input the locally stored multi-dimensional scene data samples and usage data samples into the machine learning model, output the predicted usage habit labels, and then calculate the loss function value of the usage habit loss function based on the predicted usage habit labels and the actual usage habit labels, and train the above-mentioned machine learning model based on the loss function value to obtain the usage habit analysis sub-model. Exemplarily, the machine learning model can adopt a lightweight model such as the MobileNetV3-Small model. The usage habit loss function can, for example, adopt the mean square error loss function, the mean absolute error loss function, etc.

[0069] In some embodiments, the parameters of the machine learning model may also be updated based on a stochastic gradient descent algorithm.

[0070] In some embodiments, the machine learning model may also first vectorize the multidimensional scene data and usage data to obtain vectors corresponding to the multidimensional scene data and usage data, and then normalize each vector to obtain a normalized vector, thereby reducing the differences between the data due to different dimensions, etc.

[0071] In some embodiments, when normalizing a vector, the initially obtained vector may be first subjected to dimensionality reduction processing to reduce the amount of computation and improve the training efficiency of the model. For example, the initially obtained vector may be subjected to dimensionality reduction processing using principal component analysis (PCA) to obtain a low-dimensional vector. The low-dimensional vector is then normalized to obtain a normalized vector.

[0072] For example, the initial vector obtained is 128-dimensional, which can be reduced to 32 dimensions through PCA. This can greatly reduce the subsequent calculation amount, save model training time, and improve training efficiency.

[0073] The service node here can be a border router node. Each electronic device and the border router node are in the same network, thereby preventing private data from being leaked to the external network.

[0074] For example, each electronic device can be trained once at regular intervals to continuously improve the effectiveness of the usage habit analysis sub-model. For example, the electronic device can be trained once every day at 23:00, or once every week or month. For example, after the training is completed, the trained usage habit analysis sub-model can be tested using test samples. The ratio of test samples to training samples can be 1:4, and test samples can be selected from training samples or from other time periods.

[0075] The service node can aggregate the usage habit analysis sub-models trained on multiple electronic devices to obtain a usage habit analysis model.

[0076] For example, the usage habit analysis model can be obtained by weighted summing up each usage habit analysis sub-model. For example, the service node can perform weighted summing up every period of time to continuously update the usage habit analysis model.

[0077] After the service node obtains the usage habit analysis model, it can be distributed to each electronic device. Subsequently, the electronic device can determine the user's usage habit information over a period of time based on the usage habit analysis model. The weight of each usage habit analysis sub-model can be the same, or the weight of each usage habit analysis sub-model can be dynamically determined based on the accuracy of each usage habit analysis sub-model. For example, the higher the accuracy of the usage habit analysis sub-model, the greater the corresponding weight.

[0078] In order to ensure the security of data transmission, for example, when each electronic device sends its trained usage habit analysis sub-model to the service node, it can first encrypt the usage habit analysis sub-model and then send the encrypted usage habit analysis sub-model to the service node.

[0079] This embodiment does not limit the specific encryption algorithm. For example, a hybrid encryption algorithm such as the AES-256-CBC encryption algorithm may be used, or an asymmetric encryption algorithm, a symmetric encryption algorithm, etc. may be used.

[0080] This embodiment combines federated learning technology to aggregate the usage habit analysis sub-models trained on multiple electronic devices to obtain a usage habit analysis model, thereby improving the generalization ability and accuracy of the usage habit analysis model. In this way, when analyzing the user's usage habit information over a period of time based on the usage habit analysis model, the accuracy of the analysis results can be improved, and then accurate electronic device control strategies can be determined, thereby improving the management and control effect of users' behavior in using electronic devices.

[0081] In order to determine the control strategy of electronic equipment, Figure 2 A method for controlling an electronic device is exemplarily provided. Figure 2 and Figure 1 The difference is that Figure 1 The S130 in the Figure 2 Medium S210.

[0082] S210: When the usage habit information indicates that the continuous usage time of the electronic device exceeds a first preset time, determining that the control strategy includes at least one of the following: turning off the electronic device, and periodically outputting a first prompt message.

[0083] The first preset duration can be set according to actual needs, for example, it can be set to 0.5 hours.

[0084] The continuous usage duration here can be the duration of continuous use of the same application or the total duration of continuous use of multiple applications. When the electronic device determines that the user's usage habits have exceeded a first preset duration, it can periodically output a first prompt message or shut down the electronic device. Alternatively, the electronic device can be directly shut down when the first prompt message is output a preset number of times.

[0085] For example, when it is determined that the user's continuous use time exceeds a first preset time, a first prompt message may be output. If it is detected that the user is still using the electronic device after a period of time (e.g., two minutes), the first prompt message may continue to be output, and the number of outputs of the first prompt message is increased by 1. Similarly, if the user is still using the electronic device after the number of prompts reaches the preset number, the electronic device may be directly shut down. The preset number of times may be set to 3, for example.

[0086] This embodiment takes into account the difference between a user's continuous usage behavior and fragmented usage behavior. When it is determined that the user's usage habit is to use an electronic device for a continuous period exceeding a first preset period, a first prompt message can be output and / or the electronic device can be turned off, thereby avoiding the impact of long-term continuous use of the electronic device on the user's physical and mental health, academic performance, etc.

[0087] In order to determine the control strategy of electronic equipment, Figure 3 A method for controlling an electronic device is exemplarily provided. Figure 3 and Figure 1 The difference is that Figure 1 The S130 in the Figure 3 Medium S310.

[0088] S310. When the usage habit information shows that the duration of use of the preset application per unit time exceeds a second preset duration, determine that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message; or, when the usage habit information shows that the number of times the preset application is used per unit time exceeds a preset number, determine that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message; or, when the usage habit shows that the duration of use of the preset application per unit time exceeds the second preset duration, and the number of times the preset application is used per unit time exceeds a preset number, determine that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message.

[0089] The unit time here can be one day, two days, six hours, 12 hours, etc. The preset applications can be games, videos, shopping, social networking, and other applications that are easy for users to become addicted.

[0090] The usage duration here can be the total time the user uses the preset application in a unit of time. The second preset duration can be the same as or different from the first preset duration. For example, the second preset duration can be set to 0.5 hours.

[0091] The number of times a user uses a preset application within a unit time may include the total number of times the preset application is used within the unit time. For example, for the same application, after the user uses and exits, the number of times is incremented by 1.

[0092] For example, when the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, the control strategy is determined to be closing the user's permission to use the preset application.

[0093] For example, when the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, the control strategy is determined to periodically output the second prompt information.

[0094] For example, when the usage habit information shows that the usage time of the preset application per unit time exceeds the second preset time, the control strategy is determined to periodically output the second prompt information, and when the number of prompts reaches a certain threshold, the user's permission to use the preset application is closed.

[0095] For example, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, the control strategy is determined to be closing the user's permission to use the preset application.

[0096] For example, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, the control strategy is determined to be periodically outputting the second prompt information.

[0097] For example, when the usage habit information shows that the number of times a preset application is used per unit time exceeds a preset number, the control strategy is determined to periodically output a second prompt message, and when the number of prompts reaches a certain threshold, the user's permission to use the preset application is closed.

[0098] This embodiment can dynamically determine the control strategy of the electronic device based on the user's usage habits of preset applications, which can prevent the user from becoming addicted to games, videos, shopping, social applications, etc., and reduce the impact on the user's physical and mental health, academic performance, etc.

[0099] In actual application, the above control strategy can also be dynamically adjusted based on the user's task plan information and task completion data in the first period. Figure 4 A flowchart of a method for controlling an electronic device is exemplarily provided. Figure 4 and Figure 1 The difference is that Figure 4 Also includes S410-S420, and Figure 1 The S140 in the Figure 4 S430 in.

[0100] S410: Obtain task plan information and task completion data of the user in the first period.

[0101] S420: Adjust the control strategy based on the task plan information and the task completion data to obtain an adjusted control strategy.

[0102] S430: Control the electronic device based on the adjusted control strategy.

[0103] The task plan information here may include study plans such as reading, reciting, previewing, and reviewing, and may also include plans for extracurricular activities, handicrafts, etc. Task completion data is completion data of the task plan information, for example, which plans have been completed.

[0104] The control strategy can be dynamically adjusted based on task plan information and task completion data. For example, if the task plan information is completed well or completely, the preset duration in the control strategy can be adjusted appropriately. For example, if the user completes all the task plan information ahead of schedule during the winter vacation, the preset duration in the control strategy corresponding to the winter vacation can be appropriately extended to extend the user's electronic device usage time.

[0105] If the user's planned task information has not yet started or has been completed less than halfway through the winter vacation, the preset duration of the control policy corresponding to the winter vacation can be appropriately shortened to reduce the user's use of electronic devices and enable the task information to be completed as soon as possible. This achieves dynamic adjustment of the control policy.

[0106] In some embodiments, when controlling the electronic device based on the adjusted control strategy, the electronic device may output the reason for the preset time adjustment, which may include that your use time of the electronic device is extended because you completed the task planning information ahead of time, or that your use time of the electronic device is shortened because you completed less of the task planning information.

[0107] This embodiment can dynamically adjust the control strategy based on the user's task plan and task completion data in the first time period, and control the electronic device based on the adjusted control strategy, thereby motivating the user to complete the task plan as soon as possible and reduce parenting conflicts.

[0108] In some embodiments, the above S420 may include the following steps:

[0109] Determine the completion ratio of the task plan information based on the task plan information and task completion data;

[0110] When the completion ratio is less than a preset ratio, the control strategy is adjusted to reduce the usage time and / or usage frequency of the electronic device by the user.

[0111] When the completion ratio is greater than or equal to a preset ratio, the control strategy is adjusted to increase the usage time and / or usage frequency of the electronic device by the user.

[0112] For example, the completion ratio of the task plan information can be determined based on the ratio of the task plan information to which the task completion data belongs to all the task plan information. For example, if there are a total of 3 task plan information and only one task plan information has been completed, the completion ratio of the task plan can be determined to be 33%.

[0113] For example, the completion ratio of the task plan information can be determined by combining the task plan information and the task completion data through a task plan prediction model. The task plan prediction model can be, for example, a deep learning model or a machine learning model.

[0114] For example, a weight for the task completion data can be determined based on factors such as the time spent on the task completion data, complexity, and priority, and the corresponding completion ratio for the task completion data can be determined based on the weight. For example, an initial ratio can be determined based on the proportion of the task completion data, and then a final completion ratio can be determined based on the weight of the task completion data. For example, the product of the initial ratio and the weight can be used as the completion ratio for the task completion data.

[0115] For example, if the completion ratio is less than a preset ratio, the user's single usage duration or the total usage duration per unit time of the electronic device is reduced. Alternatively, if the completion ratio is less than a preset ratio, the user's usage frequency of the electronic device is reduced. Alternatively, if the completion ratio is less than a preset ratio, the user's usage frequency of the electronic device and the single usage duration are reduced.

[0116] For example, if the completion ratio is greater than or equal to a preset ratio, the user's single usage duration or the total usage duration per unit time of the electronic device may be increased. Alternatively, if the completion ratio is greater than or equal to a preset ratio, the user's usage frequency of the electronic device may be increased. Alternatively, if the completion ratio is greater than or equal to a preset ratio, the user's usage frequency of the electronic device and the single usage duration may be increased.

[0117] This embodiment can dynamically adjust the user's usage time and / or usage frequency of the electronic device according to the user's completion ratio of the task plan information, thereby mobilizing the user's enthusiasm and completing the task plan in a timely manner.

[0118] It should be noted that the control method of the electronic device provided in the embodiments of the present application can be executed by a control device of the electronic device, or a control module in the control device of the electronic device for executing the control method of the electronic device. In the embodiments of the present application, the control device of the electronic device provided in the embodiments of the present application is described by taking the control device of the electronic device executing the control method of the electronic device as an example.

[0119] Figure 5 A schematic structural diagram of a control device of an electronic device provided in an embodiment of the present application.

[0120] like Figure 5 As shown, the control device 500 of the electronic device may include:

[0121] An acquisition module 501 is configured to acquire multi-dimensional scene data when a user uses an electronic device during a first period of time and usage data of the user using the electronic device during the first period of time;

[0122] Processing module 502, configured to fuse the multi-dimensional scene data and the usage data based on the usage habit analysis model to obtain the user's usage habit information of the electronic device;

[0123] A determination module 503 is used to determine a control strategy for the electronic device based on the usage habit information;

[0124] The control module 504 is configured to control the electronic device based on a control strategy.

[0125] In an embodiment of the present application, multi-dimensional scene data of a user using an electronic device during a first period of time and usage data of the user using the electronic device during the first period of time are obtained; based on a usage habit analysis model, the multi-dimensional scene data and usage data are fused and processed to obtain usage habit information of the user using the electronic device; a control strategy for the electronic device is determined based on the usage habit information; and the electronic device is controlled based on the control strategy. That is, this embodiment comprehensively considers the multi-dimensional scene data of the user using the electronic device during the first period of time and the usage data of the electronic device, that is, comprehensively considers multiple factors, so that the user's usage habit information of the electronic device can be determined more accurately, and then when determining the control strategy of the electronic device based on the usage habit information, the control strategy can be determined more accurately, thereby effectively controlling the user and improving the control effect.

[0126] In some possible implementations of the embodiments of the present application, the control device 500 of the electronic device may further include:

[0127] The training module is used to loop the following operations until a usage habit analysis model is obtained:

[0128] Performing machine learning model training based on training samples stored in the electronic device to obtain a usage habit analysis sub-model, wherein the training samples include multidimensional scenario data samples when the sample user uses the electronic device, usage data samples of the sample user using the electronic device, and usage habit labels corresponding to the multidimensional scenario data samples and the usage data samples;

[0129] The sending module is used to send the usage habit analysis sub-model to the service node, so that the service node aggregates the usage habit analysis sub-models obtained by training multiple electronic devices to obtain a usage habit analysis model.

[0130] In some possible implementations of the embodiment of the present application, the determining module 503 is specifically configured to:

[0131] When the usage habit information indicates that the continuous usage time of the electronic device exceeds a first preset time, determining the control strategy includes at least one of the following: turning off the electronic device, and periodically outputting the first prompt information.

[0132] In some possible implementations of the embodiment of the present application, the determining module 503 is specifically configured to:

[0133] When the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, determining the control strategy includes at least one of the following: disabling the usage permission of the preset application, and periodically outputting the second prompt information;

[0134] Alternatively, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, determining that the control strategy includes at least one of the following: disabling the use permission of the preset application, and periodically outputting a second prompt message;

[0135] Alternatively, when the usage habit is that the usage time of the preset application per unit time exceeds the second preset time, and the number of times the preset application is used per unit time exceeds the preset number of times, determining that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message.

[0136] In some possible implementations of the embodiment of the present application, the acquisition module 501 is further configured to acquire the user's task plan information and task completion data within the first period;

[0137] The control device 500 of the electronic device may further include:

[0138] An adjustment module is used to adjust the control strategy based on the task plan information and the task completion data to obtain the adjusted control strategy;

[0139] The control module 504 is specifically configured to:

[0140] Based on the adjusted control strategy, the electronic device is controlled.

[0141] The control device of the electronic device in the embodiment of the present application can be a device or a component in the electronic device, such as an integrated circuit or chip. For example, the electronic device can be a mobile phone, a tablet computer, a laptop computer, a PDA, an in-vehicle electronic device, a mobile Internet device (MID), an augmented reality (AR) / virtual reality (VR) device, a robot, a wearable device, an ultra-mobile personal computer (UMPC), a netbook or a personal digital assistant (PDA), etc. It can also be a server, a network attached storage (NAS), a personal computer (PC), a television (TV), an ATM or an kiosks, etc., and the embodiment of the present application does not specifically limit it.

[0142] The electronic device in the embodiment of the present application may be a terminal having an operating system. The operating system may be an Android operating system, an iOS operating system, or other possible operating systems, which are not specifically limited in the embodiment of the present application.

[0143] The control device of the electronic device provided in the embodiment of the present application can achieve Figures 1 to 4 The various processes in the embodiment of the control method of the electronic device can achieve the same technical effect. To avoid repetition, they will not be described here.

[0144] like Figure 6 As shown, an embodiment of the present application also provides an electronic device 600, including a processor 601 and a memory 602, wherein the memory 602 stores programs or instructions that can be run on the processor 601. When the program or instructions are executed by the processor 601, the various steps of the control method embodiment of the above-mentioned electronic device are implemented, and the same technical effect can be achieved. To avoid repetition, they will not be repeated here.

[0145] It should be noted that the electronic devices in the embodiments of the present application include the above-mentioned mobile terminals and non-mobile terminals.

[0146] Figure 7 A schematic diagram of the hardware structure of an electronic device provided in an embodiment of the present application.

[0147] The electronic device 700 includes but is not limited to components such as a radio frequency unit 701 , a network module 702 , an audio output unit 703 , an input unit 704 , a sensor 705 , a display unit 706 , a user input unit 707 , an interface unit 708 , a memory 709 , and a processor 710 .

[0148] Those skilled in the art will understand that the electronic device 700 may also include a power source (such as a battery) to power each component, and the power source may be logically connected to the processor 710 through a power management system, thereby implementing functions such as charging, discharging, and power consumption management through the power management system. Figure 7 The structure of the electronic device 700 shown in the figure does not constitute a limitation on the electronic device 700. The electronic device 700 may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently, which will not be repeated here.

[0149] The processor 710 is configured to obtain multidimensional scenario data when a user uses the electronic device during a first period of time and usage data of the electronic device during the first period of time; fuse the multidimensional scenario data and the usage data based on a usage habit analysis model to obtain usage habit information of the user using the electronic device; and determine a control strategy for the electronic device based on the usage habit information.

[0150] Based on the control strategy, control the electronic equipment.

[0151] In an embodiment of the present application, multi-dimensional scene data of a user using an electronic device during a first period of time and usage data of the user using the electronic device during the first period of time are obtained; based on a usage habit analysis model, the multi-dimensional scene data and usage data are fused and processed to obtain usage habit information of the user using the electronic device; a control strategy for the electronic device is determined based on the usage habit information; and the electronic device is controlled based on the control strategy. That is, this embodiment comprehensively considers the multi-dimensional scene data of the user using the electronic device during the first period of time and the usage data of the electronic device, that is, comprehensively considers multiple factors, so that the user's usage habits of the electronic device can be determined more accurately, and then when the control strategy of the electronic device is determined based on the usage habits, the control strategy can be determined more accurately, thereby effectively controlling the user and improving the control effect.

[0152] In some possible implementations of the embodiments of the present application, the processor 710 is further configured to:

[0153] The following operations are performed repeatedly until a usage habit analysis model is obtained:

[0154] Performing machine learning model training based on training samples stored in the electronic device to obtain a usage habit analysis sub-model, wherein the training samples include multidimensional scenario data samples when the sample user uses the electronic device, usage data samples of the sample user using the electronic device, and usage habit labels corresponding to the multidimensional scenario data samples and the usage data samples;

[0155] The usage habit analysis sub-model is sent to the service node, so that the service node aggregates the usage habit analysis sub-models obtained by training multiple electronic devices to obtain a usage habit analysis model.

[0156] In some possible implementations of the embodiments of the present application, the processor 710 is specifically configured to:

[0157] When the usage habit information indicates that the continuous usage time of the electronic device exceeds a first preset time, determining the control strategy includes at least one of the following: turning off the electronic device, and periodically outputting the first prompt information.

[0158] In some possible implementations of the embodiments of the present application, the processor 710 is specifically configured to:

[0159] When the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, determining the control strategy includes at least one of the following: disabling the usage permission of the preset application, and periodically outputting the second prompt information;

[0160] Alternatively, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, determining that the control strategy includes at least one of the following: disabling the use permission of the preset application, and periodically outputting a second prompt message;

[0161] Alternatively, when the usage habit is that the usage time of the preset application per unit time exceeds the second preset time, and the number of times the preset application is used per unit time exceeds the preset number of times, determining that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message.

[0162] In some possible implementations of the embodiment of the present application, the processor 710 is further configured to obtain task plan information and task completion data of the user in the first time period;

[0163] Adjust the control strategy based on the task plan information and task completion data to obtain an adjusted control strategy;

[0164] Based on the adjusted control strategy, the electronic device is controlled.

[0165] It should be understood that in an embodiment of the present application, the input unit 704 may include a graphics processing unit (GPU) 7041 and a microphone 7042, and the graphics processor 7041 processes the image data of a static picture or video obtained by an image capture device (such as a camera) in a video capture mode or an image capture mode. The display unit 706 may include a display panel 7061, and the display panel 7061 may be configured in the form of a liquid crystal display, an organic light emitting diode, etc. The user input unit 707 includes a touch panel 7071 and at least one of other input devices 7072. The touch panel 7071 is also called a touch screen. The touch panel 7071 may include two parts: a touch detection device and a touch controller. Other input devices 7072 may include, but are not limited to, a physical keyboard, function keys (such as volume control keys, switch keys, etc.), a trackball, a mouse, and an operating stick, which will not be repeated here.

[0166] The memory 709 can be used to store software programs and various data. The memory 709 may mainly include a first storage area for storing programs or instructions and a second storage area for storing data, wherein the first storage area may store an operating system, applications or instructions required for at least one function (such as a sound playback function, an image playback function, etc.). In addition, the memory 709 may include a volatile memory or a non-volatile memory, or the memory 709 may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), a static random access memory (SRAM), a dynamic random access memory (DRAM), a synchronous dynamic random access memory (SDRAM), a double data rate synchronous dynamic random access memory (DDRSDRAM), an enhanced synchronous dynamic random access memory (ESDRAM), a synchronous link dynamic random access memory (SLDRAM), and a direct memory bus random access memory (DRRAM). The memory 709 in the embodiment of the present application includes but is not limited to these and any other suitable types of memory.

[0167] Processor 710 may include one or more processing units. Optionally, processor 710 integrates an application processor and a modem processor. The application processor primarily handles operations related to the operating system, user interface, and application programs, while the modem processor primarily processes wireless communication signals, such as a baseband processor. It is understood that the modem processor may not be integrated into processor 710.

[0168] An embodiment of the present application also provides a readable storage medium, on which a program or instruction is stored. When the program or instruction is executed by a processor, the various processes of the control method embodiment of the above-mentioned electronic device are implemented and the same technical effect can be achieved. To avoid repetition, it will not be repeated here.

[0169] The processor is the processor in the electronic device described in the above embodiment. The readable storage medium includes a computer readable storage medium, such as a computer read-only memory ROM, a random access memory RAM, a magnetic disk or an optical disk.

[0170] An embodiment of the present application further provides a chip, which includes a processor and a communication interface, the communication interface and the processor are coupled, and the processor is used to run programs or instructions to implement the various processes of the above-mentioned electronic device control method embodiment, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0171] It should be understood that the chip mentioned in the embodiments of the present application can also be called a system-level chip, a system chip, a chip system or a system-on-chip chip, etc.

[0172] An embodiment of the present application provides a computer program product, which is stored in a storage medium. The program product is executed by at least one processor to implement the various processes of the control method embodiment of the electronic device as described above, and can achieve the same technical effect. To avoid repetition, it will not be repeated here.

[0173] It should be noted that, in this article, the terms "comprise", "include" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, an element defined by the statement "comprises a ..." does not exclude the presence of other identical elements in the process, method, article or device comprising the element. In addition, it should be noted that the scope of the methods and devices in the embodiments of the present application is not limited to performing functions in the order shown or discussed, and may also include performing functions in a substantially simultaneous manner or in the opposite order according to the functions involved. For example, the described method may be performed in an order different from that described, and various steps may also be added, omitted, or combined. In addition, the features described with reference to certain examples may be combined in other examples.

[0174] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus the necessary general hardware platform, and of course can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application, or the part that contributes to the relevant technology, can be embodied in the form of a computer software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for enabling a terminal (which can be a mobile phone, computer, server, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0175] The embodiments of the present application are described above in conjunction with the accompanying drawings, but the present application is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of this application, ordinary technicians in this field can also make many forms without departing from the purpose of this application and the scope of protection of the claims, all of which are within the protection of this application.

Claims

1. A method for controlling an electronic device, characterized in that: include: Acquire multi-dimensional scene data when a user uses an electronic device during a first period of time and usage data of the electronic device used by the user during the first period of time; Based on a usage habit analysis model, the multi-dimensional scene data and the usage data are integrated to obtain usage habit information of the user using the electronic device; determining a control strategy for the electronic device based on the usage habit information; Based on the control strategy, the electronic device is controlled.

2. The method according to claim 1, characterized in that The method further comprises: The following operations are performed in a loop until the usage habit analysis model is obtained: Performing machine learning model training based on training samples stored in the electronic device to obtain a usage habit analysis sub-model, the training samples including multidimensional scenario data samples when a sample user uses the electronic device, usage data samples of the sample user using the electronic device, and usage habit labels corresponding to the multidimensional scenario data samples and the usage data samples; The usage habit analysis sub-model is sent to a service node, so that the service node aggregates the usage habit analysis sub-models obtained by training the plurality of electronic devices to obtain the usage habit analysis model.

3. The method according to any one of claims 1-2, characterized in that Determining a control strategy for the electronic device based on the usage habit information includes: When the usage habit information indicates that the continuous usage time of the electronic device exceeds a first preset time, determining that the control strategy includes at least one of the following: turning off the electronic device, and periodically outputting a first prompt message.

4. The method according to any one of claims 1 to 2, characterized in that Determining a control strategy for the electronic device based on the usage habit information includes: If the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, determining that the control strategy includes at least one of the following: disabling the usage permission of the preset application, and periodically outputting a second prompt message; Alternatively, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, determining that the control strategy includes at least one of the following: disabling the use permission of the preset application, and periodically outputting a second prompt message; Alternatively, when the usage habit is that the usage time of the preset application per unit time exceeds a second preset time, and the number of times the preset application is used per unit time exceeds a preset number, it is determined that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message.

5. The method according to any one of claims 1-2, characterized in that The method further comprises: Obtaining the task plan information and task completion data of the user during the first time period; Adjusting the control strategy based on the task plan information and the task completion data to obtain an adjusted control strategy; The controlling the electronic device based on the control strategy includes: The electronic device is controlled based on the adjusted control strategy.

6. A control device for an electronic device, characterized in that: include: an acquisition module, configured to acquire multi-dimensional scene data when a user uses an electronic device during a first period of time and usage data of the electronic device when the user uses the electronic device during the first period of time; a processing module, configured to fuse the multi-dimensional scenario data and the usage data based on a usage habit analysis model to obtain usage habit information of the user using the electronic device; a determination module, configured to determine a control strategy for the electronic device based on the usage habit information; A control module is used to control the electronic device based on the control strategy.

7. The device according to claim 6, characterized in that The device further comprises: The training module is used to loop through the following operations until the usage habit analysis model is obtained: Performing machine learning model training based on training samples stored in the electronic device to obtain a usage habit analysis sub-model, the training samples including multidimensional scenario data samples when a sample user uses the electronic device, usage data samples of the sample user using the electronic device, and usage habit labels corresponding to the multidimensional scenario data samples and the usage data samples; The sending module is used to send the usage habit analysis sub-model to the service node, so that the service node aggregates the usage habit analysis sub-models trained by multiple electronic devices to obtain the usage habit analysis model.

8. The device according to any one of claims 6 to 7, characterized in that: The determining module is specifically configured to: When the usage habit information indicates that the continuous usage time of the electronic device exceeds a first preset time, determining that the control strategy includes at least one of the following: turning off the electronic device, and periodically outputting a first prompt message.

9. The device according to any one of claims 6-7, characterized in that The determining module is specifically configured to: If the usage habit information indicates that the usage time of the preset application per unit time exceeds a second preset time, determining that the control strategy includes at least one of the following: disabling the usage permission of the preset application, and periodically outputting a second prompt message; Alternatively, when the usage habit information indicates that the number of times a preset application is used per unit time exceeds a preset number, determining that the control strategy includes at least one of the following: disabling the use permission of the preset application, and periodically outputting a second prompt message; Alternatively, when the usage habit is that the usage time of the preset application per unit time exceeds a second preset time, and the number of times the preset application is used per unit time exceeds a preset number, it is determined that the control strategy includes at least one of the following: closing the usage permission of the preset application, and periodically outputting a second prompt message.

10. The device according to any one of claims 6 to 7, characterized in that: The acquisition module is further configured to acquire the task plan information and task completion data of the user during the first time period; The device further comprises: An adjustment module, configured to adjust the control strategy based on the task plan information and the task completion data to obtain an adjusted control strategy; The control module is specifically used to: The electronic device is controlled based on the adjusted control strategy.

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