Multi-terminal control method and system, electronic equipment, device and storage medium

Abstract

The invention provides a multi-terminal control method and system, electronic equipment, a device and a storage medium. The method comprises the following steps: acquiring a candidate behavior habit set of a user side and a candidate switching control event; collecting real-time behavior data of the user side, and identifying a target behavior habit from the candidate behavior habit set so as to determine a target switching control event currently corresponding to the user side from the candidate switching control events; and obtaining a first operation service of the user side, and switching the first operation service to the target side for operation based on the switching control instruction. By analyzing the behavioral habits of the user, the client can be automatically switched according to the behavioral habits of the user, more intelligent, convenient and consistent equipment control experience is provided for the user, so that the efficiency and comfort of digital life are improved, the requirement of manual intervention of the user is reduced through automatic equipment operation, and the user experience is improved. The experience of interaction between the user and the intelligent equipment is improved, and the development and innovation of digital life are promoted.

Description

Technical Field

[0001] The present disclosure relates to the field of data processing technology, and in particular to a multi-terminal control method, system, electronic device, apparatus and storage medium. Background Art

[0002] In today's digital society, the widespread use of smart devices has become a part of daily life. However, the interoperability and synergy between different devices still face many challenges, resulting in inconsistency and cumbersome user experience. In order to solve this problem, cross-device control technology based on artificial intelligence (AI) algorithms has emerged. The background of this technology is that it involves a variety of common smart devices, including but not limited to smart hardware such as mobile phones, tablets, laptops, TVs, speakers, watches, headphones, etc. These devices usually use different operating systems, interaction methods and communication protocols, so it becomes crucial to achieve seamless collaborative operation between them.

[0003] Cross-device control technology based on AI algorithms achieves intelligent collaboration between devices by deeply learning user habits and behavior patterns. This technology can not only automatically identify users' device usage habits, but also predict users' needs and automatically adjust device settings and functions. For example, when users switch from mobile phones to tablets, the technology can automatically adjust the size and arrangement of the application interface to adapt to different screen sizes and ensure that the user's workflow is smooth. Summary of the invention

[0004] The present disclosure aims to solve one of the technical problems in the related art at least to some extent.

[0005] To this end, an object of the present disclosure is to provide a multi-terminal control method.

[0006] The second objective of the present disclosure is to provide a multi-terminal control system.

[0007] The third objective of the present disclosure is to provide a multi-terminal control device.

[0008] A fourth objective of the present disclosure is to provide an electronic device.

[0009] A fifth object of the present disclosure is to provide a non-transitory computer-readable storage medium.

[0010] To achieve the above-mentioned purpose, the first aspect of the present disclosure proposes a multi-terminal control method, including: obtaining a set of candidate behavior habits of a user terminal, and candidate switching control events of the user terminal under each candidate behavior habit in the candidate behavior habit set; collecting real-time behavior data of the user terminal, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event; obtaining the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and switching the first running service to run on the target terminal based on the switching control instruction.

[0011] According to one embodiment of the present disclosure, the method of obtaining a set of candidate behavior habits of a user terminal, and candidate switching control events of the user terminal under each candidate behavior habit in the set of candidate behavior habits, includes: obtaining a trained target behavior habit recognition model; obtaining a set of historical behavior data of the user terminal within a historical time range, and obtaining the candidate behavior habits to which each historical behavior data in the set of historical behavior data belongs through the target behavior habit recognition model to obtain the set of candidate behavior habits of the user terminal; for any candidate behavior habit, obtaining the historical switching control events of the user terminal under the candidate behavior habit as the candidate switching control events under the candidate behavior habit.

[0012] According to one embodiment of the present disclosure, obtaining a trained target behavior habit recognition model includes: obtaining a candidate behavior habit recognition model to be trained, and a training sample of the candidate behavior habit recognition model, wherein the training sample is obtained through sample behavior data and sample behavior habits of the user terminal; training the candidate behavior habit recognition model based on the training sample to obtain an output behavior habit of the candidate behavior habit model based on the sample behavior data in the training sample; obtaining a loss value of the output behavior habit based on the sample behavior habit, and adjusting the model parameters of the candidate behavior habit recognition model based on the loss value, and returning to obtain the next training sample to continue training the candidate behavior habit recognition model after the parameter adjustment, until the training is completed, to obtain a trained target behavior habit recognition model.

[0013] According to one embodiment of the present disclosure, for any candidate behavior habit, obtaining the historical switching control events of the user terminal under the candidate behavior habit as the candidate switching control event under the candidate behavior habit includes: obtaining an initial historical switching control event set of the user terminal under the candidate behavior habit within the historical time range; obtaining the historical occurrence probability of each initial historical switching control event in the initial historical switching control event set within the historical time range; for any initial historical switching control event, in response to the historical occurrence probability of the initial historical switching control event being greater than or equal to a preset probability threshold, determining that the initial historical switching control event is the historical switching control event of the user terminal under the candidate behavior habit.

[0014] According to one embodiment of the present disclosure, the real-time behavior data of the user terminal is collected, and the target behavior habit corresponding to the real-time behavior data is identified from the candidate behavior habit set to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event, including: inputting the real-time behavior data into a trained target behavior habit model, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set through the target behavior habit model; for any candidate switching control event, in response to the candidate behavior habit corresponding to the candidate switching control event being the same as the target behavior habit, determining the candidate switching control event as the target switching control event corresponding to the target behavior habit.

[0015] According to one embodiment of the present disclosure, the method of obtaining a switching control instruction of the user terminal and a first running service to be switched on the user terminal, and switching the first running service to run on the target terminal based on the switching control instruction, includes: obtaining the first running service switched on the user terminal and the second running service switched to run on the target terminal under the target switching control event; based on the switching control instruction, controlling the user terminal to stop the operation of the first running service and controlling the target terminal to start the operation of the second running service.

[0016] According to one embodiment of the present disclosure, the obtaining of the first running service switched on the user terminal and the second running service switched to run on the target terminal under the target switching control event includes: obtaining a terminal set covered by the local area network to which the user terminal belongs; obtaining historical switching control instructions received by the user terminal within a historical time range under the target switching control event, and determining the target terminal to be switched from the terminal set based on the historical switching control instructions; obtaining the first historical service that the historical switching control instructions instruct to stop running on the user terminal and the second historical service that the historical switching control instructions instruct to start running on the target terminal, and determining the first running service to be switched on the user terminal based on the first historical service, and determining the second running service to be switched to run on the target terminal based on the second historical service.

[0017] According to one embodiment of the present disclosure, the step of obtaining the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and before switching the first running service to run on the target terminal based on the switching control instruction, includes: identifying whether the target switching control event satisfies a preset event trigger condition; in response to the relative position relationship between the user terminal and the target terminal satisfying a preset position relationship condition when the real-time behavior data is collected, determining that the target switching control event satisfies the event trigger condition.

[0018] To achieve the above-mentioned purpose, the second aspect of the present disclosure proposes a multi-terminal control system, including: the system includes a behavior data real-time collection component, a behavior habit recognition model, a switching control event recognition component, a control component and a storage component, wherein the behavior data real-time collection component is used to collect real-time behavior data of the user terminal and transmit the real-time behavior data to the storage component; the behavior habit recognition model is used to obtain a set of candidate behavior habits of the user terminal, and determine the target behavior habits of the user terminal based on the real-time behavior data obtained from the storage component, and transmit them to the switching control event recognition component; the switching control event recognition component is used to obtain a set of historical switching control events of the user terminal, and identify the target switching control event to which the user terminal belongs from the historical switching control event set based on the received target behavior habits; the control component is used to generate a corresponding switching control instruction based on the target switching control event, and switch the first running service on the user terminal to the target terminal based on the switching control instruction.

[0019] According to one embodiment of the present disclosure, the system also includes a server interaction component, wherein the server interaction component is used to obtain sample behavior data and sample behavior habits of the user terminal and transmit them to the storage component; the behavior habit recognition model is also used to obtain the sample behavior data and sample behavior habits from the storage component for model training and learning, so as to obtain a trained target behavior habit recognition model.

[0020] According to one embodiment of the present disclosure, the system also includes an encryption component, wherein the encryption component is used to encrypt candidate data to be transmitted to the server by the server interaction component to obtain encrypted target data, wherein the target data is used to be uploaded to the server for archiving through the server interaction component.

[0021] To achieve the above-mentioned purpose, the third aspect embodiment of the present disclosure proposes a multi-terminal control device, including: an acquisition module, used to acquire a set of candidate behavior habits of a user terminal, and candidate switching control events of the user terminal under each candidate behavior habit in the candidate behavior habit set; a collection module, used to collect real-time behavior data of the user terminal, and identify the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event; a control module, used to acquire the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and switch the first running service to run on the target terminal based on the switching control instruction.

[0022] To achieve the above-mentioned purpose, the fourth aspect embodiment of the present disclosure proposes an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to implement the multi-terminal control method as described in the first aspect embodiment of the present disclosure.

[0023] To achieve the above-mentioned purpose, the fifth aspect embodiment of the present disclosure proposes a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to implement the multi-terminal control method as described in the first aspect embodiment of the present disclosure.

[0024] Therefore, by analyzing the user's behavioral habits, the client can automatically switch according to the user's behavioral habits, providing users with a more intelligent, convenient and consistent device control experience, thereby improving the efficiency and comfort of digital life. Through this automated device operation, the need for user manual intervention is reduced, improving the user's experience of interacting with smart devices, and promoting the development and innovation of digital life. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 is a schematic diagram of a multi-terminal control method according to an embodiment of the present disclosure;

[0026] Figure 2 is a schematic diagram of another multi-terminal control method according to an embodiment of the present disclosure;

[0027] Figure 3 is a schematic diagram of another multi-terminal control method according to an embodiment of the present disclosure;

[0028] Figure 4 It is a structural schematic diagram of a multi-terminal control system according to one embodiment of the present disclosure;

[0029] Figure 5 is a schematic diagram of the structure of another multi-terminal control system according to an embodiment of the present disclosure;

[0030] Figure 6 is a schematic diagram of the structure of another multi-terminal control system according to an embodiment of the present disclosure;

[0031] Figure 7 is a schematic diagram of a multi-terminal control device according to one embodiment of the present disclosure;

[0032] Figure 8 is a schematic diagram of an electronic device according to an embodiment of the present disclosure. DETAILED DESCRIPTION

[0033] Embodiments of the present disclosure are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0034] The acquisition, storage, use, and processing of data in the technical solution disclosed in this disclosure are in compliance with the relevant provisions of national laws and regulations.

[0035] Figure 1 is a schematic diagram of a multi-terminal control method according to an embodiment of the present disclosure, such as Figure 1 As shown, the multi-terminal control method includes the following steps:

[0036] S101, obtaining a candidate behavior habit set of a user terminal and a candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set.

[0037] It should be noted that the candidate behavior habits are a collection of operations frequently used by users. For example, when a user is listening to music and finds that there is a speaker on the same local area network nearby, and in this scenario many times, the user performs audio projection through the speaker, then the user's behavior of performing audio projection through the speaker can be considered as a user habit.

[0038] In the embodiment of the present disclosure, the historical operation data of the user terminal can be collected through the AI ​​engine, and the user's habitual operations in the historical operation data can be determined by statistics, and a candidate behavior habit set can be generated by summarizing the historical operation data.

[0039] It should be noted that the above-mentioned user terminal can be a client such as a search page, a browser, a toolbar, a mobile APP, etc. The above-mentioned client can be located on a computer or on a mobile terminal such as a mobile phone.

[0040] In the embodiment of the present disclosure, the candidate behavior habit set may include multiple candidate behavior habits, or may include only one candidate behavior habit, and no limitation is made herein.

[0041] In the disclosed embodiment, the candidate switching control event is an event, instruction or action for the candidate behavior to switch or control the target end. It should be noted that the candidate switching control events corresponding to different candidate behavior habits may be different or the same, and no limitation is made here.

[0042] It should be noted that there is a one-to-one correspondence between the candidate switching control events and the candidate behavior habits.

[0043] S102, collecting real-time behavior data of the user terminal, and identifying target behavior habits corresponding to the real-time behavior data from a set of candidate behavior habits, so as to determine a target switching control event currently corresponding to the user terminal from each candidate switching control event.

[0044] It should be noted that the real-time behavior data of the user end may include many types, which are not limited here. For example, the real-time behavior data may include the user connecting to a local area network that has been connected to in the past, opening a specific application, etc.

[0045] In the embodiments of the present disclosure, there may be multiple methods for collecting real-time behavior data of the user terminal, which are not limited here.

[0046] Optionally, the user's operations on the user terminal may be monitored, and when the user performs operations on the user terminal, operation data may be obtained, thereby generating real-time behavior data of the user terminal.

[0047] Optionally, the user terminal status of the user terminal can also be monitored. The user terminal status can include multiple types, which are not limited here. For example, it can include the local area network to which the user terminal is currently connected, whether the user terminal is in use, the call status of the user terminal, etc.

[0048] After the real-time behavior data of the user end is acquired, the target behavior habit can be determined by matching the real-time behavior data of the user end with each candidate behavior habit in the candidate behavior habit set.

[0049] In the embodiments of the present disclosure, there may be multiple matching methods, which are not limited here.

[0050] Optionally, the real-time behavior data of the user terminal and each candidate behavior habit of the candidate behavior habit set may be input into a matching model to determine a candidate behavior habit that matches the real-time behavior data of the user terminal.

[0051] Optionally, the similarity between the real-time behavior data of the user terminal and each candidate behavior habit in the candidate behavior habit set may be calculated through a natural language algorithm, and the target behavior habit may be determined based on the similarity.

[0052] S103: Acquire a switching control instruction of the user terminal and a first running service to be switched on the user terminal, and switch the first running service to run on the target terminal based on the switching control instruction.

[0053] In the disclosed embodiment, the first running service is a service that the user terminal currently needs to run or switch. For example, when a user is listening to music and finds that there is a speaker on the same local area network nearby, and the target behavior habit is that the user projects audio through the speaker, then the behavior of the user terminal automatically connecting to the speaker at this time is the first running service.

[0054] In the disclosed embodiment, firstly, a set of candidate behavior habits of the user terminal and candidate switching control events of the user terminal under each candidate behavior habit in the candidate behavior habit set are obtained, then the real-time behavior data of the user terminal is collected, and the target behavior habit corresponding to the real-time behavior data is identified from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event, and finally the switching control instruction of the user terminal and the first running service to be switched on the user terminal are obtained, and the first running service is switched to run on the target terminal based on the switching control instruction. Thus, by analyzing the user's behavior habits, the client can be automatically switched according to the user's behavior habits, providing the user with a more intelligent, convenient and consistent device control experience, thereby improving the efficiency and comfort of digital life. Through this automated device operation, the need for manual intervention by the user is reduced, the user's experience of interacting with smart devices is improved, and the development and innovation of digital life is promoted.

[0055] In the above embodiment, the switching control instruction of the user end and the first running service to be switched on the user end are obtained, and the first running service is switched to the target end for operation based on the switching control instruction. First, the first running service switched on the user end under the target switching control event and the second running service switched to run on the target end are obtained, and then based on the switching control instruction, the user end is controlled to stop the operation of the first running service and the target end is controlled to start the operation of the second running service.

[0056] In an embodiment of the present disclosure, to obtain a first running service switched on a user terminal and a second running service switched to run on the target terminal under a target switching control event, the terminal set covered by the local area network to which the user terminal belongs can be first obtained, and then the historical switching control instructions received by the user terminal within a historical time range under the target switching control event are obtained, and the target terminal to be switched is determined from the terminal set based on the historical switching control instructions, and finally the first historical service that the historical switching control instructions instruct to stop running on the user terminal and the second historical service that the historical switching control instructions instruct to start running on the target terminal are obtained, and the first running service to be switched on the user terminal is determined based on the first historical service, and the second running service to be switched to run on the target terminal is determined based on the second historical service.

[0057] It should be noted that before obtaining the switching control instruction of the user end and the first running service to be switched on the user end, and switching the first running service to run on the target end based on the switching control instruction, it is possible to first identify whether the target switching control event meets the preset event trigger condition, and then, in response to the relative position relationship between the user end and the target end meeting the preset position relationship condition when the real-time behavior data is collected, determine that the target switching control event meets the event trigger condition.

[0058] It should be noted that the preset position relationship condition can be multiple, so it can be automatically triggered for multiple scenarios. There can be multiple location conditions, and no limitation is made here. For example, the location condition can be that the distance between the target terminal and the user terminal is within a preset distance range, or that the user terminal is connected to a preset local area network, etc.

[0059] In the above embodiment, the candidate behavior habit set of the user terminal and the candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set are obtained, and the candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set can also be obtained by Figure 2 To explain further, Figure 2 is a schematic diagram of another multi-terminal control method according to an embodiment of the present disclosure, the method comprising:

[0060] S201, obtaining a trained target behavior habit recognition model.

[0061] It can be understood that model training is an iterative process, which is carried out by continuously adjusting the network parameters of the model until the overall loss function value of the model is less than the preset value, or the overall loss function value of the model no longer changes or changes slowly, the model converges, and a trained model is obtained.

[0062] In the disclosed embodiment, the training samples can be input into the model to be trained, and based on the output results, the network parameters of the model to be trained are updated until the loss function value of the model to be trained is less than or equal to the preset value, thereby obtaining a trained target behavior habit recognition model.

[0063] Optionally, during each iterative training process, the loss function value can be calculated based on the output results and the actual results of the training samples, and then the calculated loss function value can be compared with a preset value. If the loss function value is greater than the preset value, the network parameters of the network to be trained are updated. This process is repeated until the loss function value is less than the preset value, thereby obtaining a trained target behavior habit recognition model.

[0064] It should be noted that the preset values ​​are set in advance and can be changed according to actual design needs, and no limitation is made here.

[0065] In one possible implementation method, the candidate behavior habit recognition model to be trained and the training samples of the candidate behavior habit recognition model can be first obtained, wherein the training samples are obtained through the sample behavior data and sample behavior habits of the user end, and then the candidate behavior habit recognition model is trained based on the training samples to obtain the output behavior habits of the candidate behavior habit model based on the sample behavior data in the training samples, and finally the loss value of the output behavior habits based on the sample behavior habits is obtained, and the model parameters of the candidate behavior habit recognition model are adjusted based on the loss value, and the next training sample is returned to continue training the candidate behavior habit recognition model with adjusted parameters until the training is completed to obtain a trained target behavior habit recognition model.

[0066] S202, obtaining a historical behavior data set of the user terminal within a historical time range, and obtaining candidate behavior habits to which each historical behavior data in the historical behavior data set belongs through a target behavior habit recognition model to obtain a candidate behavior habit set of the user terminal.

[0067] In the embodiment of the present disclosure, the historical time range is set in advance and can be changed according to actual design needs, and no limitation is made here. For example, the historical time range can be 1 month, 3 months, 1 week, etc. before the current time.

[0068] It should be noted that since the user's behavior habits may be periodic, it is necessary to set a historical time range to limit it. In this way, the availability and practicality of the final generated historical behavior data set can be improved.

[0069] S203, for any candidate behavior habit, obtaining historical switching control events of the user terminal under the candidate behavior habit as candidate switching control events under the candidate behavior habit.

[0070] In an embodiment of the present disclosure, to obtain a candidate switching control event, the user terminal can first obtain a set of initial historical switching control events under the candidate behavior habits within a historical time range, and then obtain the historical occurrence probability of each initial historical switching control event in the set of initial historical switching control events within the historical time range. For any initial historical switching control event, in response to the historical occurrence probability of the initial historical switching control event being greater than or equal to a preset probability threshold, the initial historical switching control event is determined to be a historical switching control event of the user terminal under the candidate behavior habits.

[0071] It should be noted that the historical time range in the present disclosure is the same as the historical time range corresponding to the historical behavior data set obtained from the user terminal, so as to ensure consistency in subsequent data matching and processing.

[0072] The historical occurrence probability of each initial historical switching control event in the initial historical switching control event set within the historical time range is the ratio of each initial historical switching control event to the total number of events in the initial historical switching control event set.

[0073] It should be noted that the preset probability threshold can be changed according to actual design needs and is not limited here.

[0074] In the disclosed embodiment, firstly, a trained target behavior habit recognition model is obtained, then a historical behavior data set of the user terminal within a historical time range is obtained, and the candidate behavior habits to which each historical behavior data in the historical behavior data set belongs are obtained through the target behavior habit recognition model to obtain a candidate behavior habit set of the user terminal, and for any candidate behavior habit, the historical switching control events of the user terminal under the candidate behavior habit are obtained as candidate switching control events under the candidate behavior habit. Thus, by training the target behavior habit recognition model, the user's historical behaviors are classified, and a candidate behavior habit set is generated, providing a data basis for the subsequent determination of the target switching control event currently corresponding to the user terminal.

[0075] In the above embodiment, the real-time behavior data of the user terminal is collected, and the target behavior habit corresponding to the real-time behavior data is identified from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event. Figure 3 To explain further, Figure 3 is a schematic diagram of another multi-terminal control method according to an embodiment of the present disclosure, the method comprising:

[0076] S301, inputting the real-time behavior data into the trained target behavior habit model, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set through the target behavior habit model.

[0077] It can be understood that model training is an iterative process, which is carried out by continuously adjusting the network parameters of the model until the overall loss function value of the model is less than the preset value, or the overall loss function value of the model no longer changes or changes slowly, the model converges, and a trained model is obtained.

[0078] In the disclosed embodiment, the trained target behavior habit model can be obtained by inputting training samples into the model to be trained and updating the network parameters of the model to be trained based on the output results until the loss function value of the model to be trained is less than or equal to a preset value.

[0079] Optionally, during each iterative training process, the loss function value can be calculated based on the output results and the actual results of the training samples, and then the calculated loss function value can be compared with a preset value. If the loss function value is greater than the preset value, the network parameters of the network to be trained are updated. This process is repeated until the loss function value is less than the preset value, thereby obtaining a trained target behavior habit model.

[0080] It should be noted that the preset values ​​are set in advance and can be changed according to actual design needs, and no limitation is made here.

[0081] S302 : For any candidate switching control event, in response to a candidate behavior habit corresponding to the candidate switching control event being the same as a target behavior habit, determining the candidate switching control event as a target switching control event corresponding to the target behavior habit.

[0082] In the disclosed embodiment, the real-time behavior data is first input into the trained target behavior habit model, and the target behavior habit corresponding to the real-time behavior data is identified from the candidate behavior habit set through the target behavior habit model, and then for any candidate switching control event, in response to the candidate behavior habit corresponding to the candidate switching control event being the same as the target behavior habit, the candidate switching control event is determined to be the target switching control event corresponding to the target behavior habit. Thus, by training the target behavior habit model, the target behavior habit can be determined quickly and accurately, and by comparing with the candidate behavior habit, the target switching control event can be determined, providing a data basis for subsequent switching.

[0083] Figure 4is a schematic diagram of a multi-terminal control system according to an embodiment of the present disclosure. Figure 4 As shown, the multi-terminal control system includes: a behavior data real-time collection component 410, a behavior habit recognition model 420, a switching control event recognition component 430, a control component 440 and a storage component 450.

[0084] The behavior data real-time collection component 410 is used to collect the real-time behavior data of the user terminal and transmit the real-time behavior data to the storage component 450. The specific implementation process can refer to the content in the above embodiment, which will not be repeated here.

[0085] The behavior habit recognition model 420 is used to obtain the candidate behavior habit set of the user terminal, and determine the target behavior habit of the user terminal according to the real-time behavior data obtained from the storage component 450, and transmit it to the switching control event recognition component 430. The specific implementation process can refer to the content of the above embodiment, which will not be repeated here.

[0086] The switching control event identification component 430 is used to obtain the historical switching control event set of the user terminal, and identify the target switching control event belonging to the user terminal from the historical switching control event set according to the received target behavior habits. The specific implementation process can refer to the content of the above embodiment, which will not be repeated here.

[0087] The control component 440 is used to generate a corresponding switching control instruction according to the target switching control event, and switch the first running service on the user terminal to the target terminal for running based on the switching control instruction.

[0088] In the embodiments of the present disclosure, Figure 5 As shown, Figure 5 It is a structural diagram of another multi-terminal control system of an embodiment of the present disclosure. The system also includes a server interaction component 560: the server interaction component 560 is used to obtain sample behavior data and sample behavior habits of the user terminal and transmit them to the storage component 550.

[0089] The behavior habit recognition model 520 is also used to obtain sample behavior data and sample behavior habits from the storage component 550 to perform model training and learning to obtain a trained target behavior habit recognition model 520.

[0090] It should be noted that Figure 5 For detailed information of the behavior data real-time collection component 510, the behavior habit recognition model 520, the switching control event recognition component 530, the control component 540 and the storage component 550, please refer to the above Figure 4 The relevant details in the embodiments are not repeated here.

[0091] In the embodiments of the present disclosure, Figure 6 As shown, Figure 6 : is a schematic diagram of the structure of another multi-terminal control system according to an embodiment of the present disclosure, wherein the system further comprises an encryption component, wherein the encryption component 670 is used to encrypt the candidate data to be transmitted to the server by the server interaction component 660 to obtain the encrypted target data, wherein the target data is uploaded to the server for archiving through the server interaction component 660. Thus, the encryption component 670 can improve the security of data transmission and storage and reduce the possibility of data leakage.

[0092] It should be noted that Figure 6 For detailed information of the behavior data real-time collection component 610, the behavior habit recognition model 620, the switching control event recognition component 630, the control component 640, the storage component 650 and the server interaction component 660, please refer to the above Figure 4 and Figure 5 The relevant details in the embodiments are not repeated here.

[0093] In the disclosed embodiment, firstly, a set of candidate behavior habits of the user terminal and candidate switching control events of the user terminal under each candidate behavior habit in the candidate behavior habit set are obtained, then the real-time behavior data of the user terminal is collected, and the target behavior habit corresponding to the real-time behavior data is identified from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event, and finally the switching control instruction of the user terminal and the first running service to be switched on the user terminal are obtained, and the first running service is switched to run on the target terminal based on the switching control instruction. Thus, by analyzing the user's behavior habits, the client can be automatically switched according to the user's behavior habits, providing the user with a more intelligent, convenient and consistent device control experience, thereby improving the efficiency and comfort of digital life. Through this automated device operation, the need for manual intervention by the user is reduced, the user's experience of interacting with smart devices is improved, and the development and innovation of digital life is promoted.

[0094] Corresponding to the multi-terminal control methods provided in the above-mentioned embodiments, an embodiment of the present disclosure also provides a multi-terminal control device. Since the multi-terminal control device provided in the embodiment of the present disclosure corresponds to the multi-terminal control methods provided in the above-mentioned embodiments, the implementation methods of the above-mentioned multi-terminal control methods are also applicable to the multi-terminal control device provided in the embodiment of the present disclosure and will not be described in detail in the following embodiments.

[0095] Figure 7 is a schematic diagram of a multi-terminal control device according to an embodiment of the present disclosure. Figure 7 As shown, the multi-terminal control device 700 includes: an acquisition module 710, a collection module 720 and a control module 730.

[0096] The acquisition module 710 is used to acquire the candidate behavior habit set of the user terminal and the candidate switching control events of the user terminal under each candidate behavior habit in the candidate behavior habit set.

[0097] The collection module 720 is used to collect the real-time behavior data of the user terminal, and identify the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event.

[0098] The control module 730 is used to obtain the switching control instruction of the user end and the first running service to be switched on the user end, and switch the first running service to run on the target end based on the switching control instruction.

[0099] In one embodiment of the present disclosure, the acquisition module 720 is also used to: obtain a trained target behavior habit recognition model; obtain a historical behavior data set of the user terminal within a historical time range, and obtain the candidate behavior habits to which each historical behavior data in the historical behavior data set belongs through the target behavior habit recognition model to obtain a candidate behavior habit set of the user terminal; for any candidate behavior habit, obtain the historical switching control events of the user terminal under the candidate behavior habit as candidate switching control events under the candidate behavior habit.

[0100] In one embodiment of the present disclosure, the acquisition module 720 is also used to: obtain a candidate behavior habit recognition model to be trained, and training samples of the candidate behavior habit recognition model, wherein the training samples are obtained through sample behavior data and sample behavior habits of the user end; train the candidate behavior habit recognition model based on the training samples to obtain output behavior habits of the candidate behavior habit model based on the sample behavior data in the training samples; obtain a loss value of the output behavior habits based on the sample behavior habits, and adjust the model parameters of the candidate behavior habit recognition model based on the loss value, and return to obtain the next training sample to continue training the candidate behavior habit recognition model after the parameters are adjusted, until the training is completed, to obtain a trained target behavior habit recognition model.

[0101] In one embodiment of the present disclosure, the acquisition module 720 is also used to: obtain a set of initial historical switching control events of the user terminal under the candidate behavior habits within a historical time range; obtain the historical occurrence probability of each initial historical switching control event in the set of initial historical switching control events within the historical time range; for any initial historical switching control event, in response to the historical occurrence probability of the initial historical switching control event being greater than or equal to a preset probability threshold, determine that the initial historical switching control event is a historical switching control event of the user terminal under the candidate behavior habits.

[0102] In one embodiment of the present disclosure, the acquisition module 720 is also used to: input the real-time behavior data into a trained target behavior habit model, and identify the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set through the target behavior habit model; for any candidate switching control event, in response to the candidate behavior habit corresponding to the candidate switching control event being the same as the target behavior habit, determine that the candidate switching control event is the target switching control event corresponding to the target behavior habit.

[0103] In one embodiment of the present disclosure, the control module 730 is also used to: obtain the first running service switched on the user end and the second running service switched on the target end under the target switching control event; based on the switching control instruction, control the user end to stop the operation of the first running service and control the target end to start the operation of the second running service.

[0104] In one embodiment of the present disclosure, the control module 730 is also used to: obtain a terminal set covered by the local area network to which the user terminal belongs; obtain historical switching control instructions received by the user terminal within a historical time range under a target switching control event, and determine the target terminal for switching from the terminal set based on the historical switching control instructions; obtain the first historical service that the historical switching control instructions indicate to stop running on the user terminal, and the second historical service that the historical switching control instructions indicate to start running on the target terminal, and determine the first running service to be switched on the user terminal based on the first historical service, and determine the second running service to be switched to run on the target terminal based on the second historical service.

[0105] In one embodiment of the present disclosure, the control module 730 is also used to: identify whether the target switching control event satisfies a preset event trigger condition; in response to the relative position relationship between the user terminal and the target terminal satisfying the preset position relationship condition when the real-time behavior data is collected, determine that the target switching control event satisfies the event trigger condition.

[0106] Therefore, by analyzing the user's behavioral habits, the client can automatically switch according to the user's behavioral habits, providing users with a more intelligent, convenient and consistent device control experience, thereby improving the efficiency and comfort of digital life. Through this automated device operation, the need for user manual intervention is reduced, improving the user's experience of interacting with smart devices, and promoting the development and innovation of digital life.

[0107] In order to implement the above embodiment, the present disclosure further provides an electronic device 800, Figure 8 is a schematic diagram of an electronic device according to an embodiment of the present disclosure, such as Figure 8As shown, the electronic device 800 includes: a processor 801 and a memory 802 that is communicatively connected to the processor, the memory 802 stores instructions that can be executed by at least one processor, and the instructions are executed by at least one processor 801 to implement the present disclosure. Figure 1-Figure 3 A multi-terminal control method according to an embodiment.

[0108] In order to implement the above embodiments, the present disclosure also provides a non-transitory computer-readable storage medium storing computer instructions, wherein the computer instructions are used to enable the computer to implement the above embodiments. Figure 1-Figure 3 A multi-terminal control method according to an embodiment.

[0109] In order to implement the above embodiments, the present disclosure also provides a computer program product, including a computer program. When the computer program is executed by a processor, the computer program implements the above embodiments. Figure 1-Figure 3 A multi-terminal control method according to an embodiment.

[0110] In the description of the present disclosure, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present disclosure and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as a limitation on the present disclosure.

[0111] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features. In the description of the present disclosure, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0112] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, without contradiction.

[0113] Although the embodiments of the present disclosure have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A multi-terminal control method, characterized in that: The method comprises: Acquire a candidate behavior habit set of the user terminal and a candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set; Collecting the real-time behavior data of the user terminal, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event; A switching control instruction of the user terminal and a first running service to be switched on the user terminal are obtained, and the first running service is switched to run on the target terminal based on the switching control instruction.

2. The method according to claim 1, characterized in that The step of obtaining a candidate behavior habit set of the user terminal and a candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set includes: Obtain the trained target behavior habit recognition model; Acquire a historical behavior data set of the user terminal within a historical time range, and acquire a candidate behavior habit to which each historical behavior data in the historical behavior data set belongs through the target behavior habit recognition model, so as to obtain the candidate behavior habit set of the user terminal; For any candidate behavior habit, a historical switching control event of the user terminal under the candidate behavior habit is obtained as the candidate switching control event under the candidate behavior habit.

3. The method according to claim 2, characterized in that The step of obtaining a trained target behavior habit recognition model includes: Acquire a candidate behavior habit recognition model to be trained, and a training sample of the candidate behavior habit recognition model, wherein the training sample is obtained through sample behavior data and sample behavior habits of the user terminal; Training the candidate behavior habit recognition model based on the training sample to obtain output behavior habits obtained by the candidate behavior habit model based on the sample behavior data in the training sample; Obtain the loss value of the output behavior habit based on the sample behavior habit, and adjust the model parameters of the candidate behavior habit recognition model based on the loss value, and return to obtain the next training sample to continue training the candidate behavior habit recognition model with adjusted parameters until the training is completed, thereby obtaining a trained target behavior habit recognition model.

4. The method according to claim 2, characterized in that: The acquiring, for any candidate behavior habit, a historical switching control event of the user terminal under the candidate behavior habit as the candidate switching control event under the candidate behavior habit includes: Acquire a set of initial historical switching control events of the user terminal under the candidate behavior habit within the historical time range; Obtaining the historical occurrence probability of each initial historical switching control event in the initial historical switching control event set within the historical time range; For any initial historical switching control event, in response to the historical occurrence probability of the initial historical switching control event being greater than or equal to a preset probability threshold, the initial historical switching control event is determined to be the historical switching control event of the user terminal under the candidate behavior habit.

5. The method according to claim 1, characterized in that The collecting of the real-time behavior data of the user terminal and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event, includes: Inputting the real-time behavior data into a trained target behavior habit model, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set through the target behavior habit model; For any candidate switching control event, in response to a candidate behavior habit corresponding to the candidate switching control event being the same as the target behavior habit, the candidate switching control event is determined to be the target switching control event corresponding to the target behavior habit.

6. The method according to claim 1, characterized in that The obtaining of the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and switching the first running service to run on the target terminal based on the switching control instruction, includes: Acquire the first running service switched on the user terminal and the second running service switched on the target terminal under the target switching control event; Based on the switching control instruction, the user end is controlled to stop the operation of the first operation service and the target end is controlled to start the operation of the second operation service.

7. The method according to claim 6, characterized in that The obtaining of the first running service switched on the user terminal and the second running service switched on the target terminal under the target switching control event includes: Obtaining a terminal set covered by the local area network to which the user terminal belongs; Acquire historical switching control instructions received by the user terminal within a historical time range under the target switching control event, and determine the target terminal to be switched from the terminal set based on the historical switching control instructions; Obtain the historical switching control instruction to instruct the first historical service to stop running on the user end, and to instruct the second historical service to start running on the target end, and determine the first running service to be switched on the user end based on the first historical service, and determine the second running service to be switched to run on the target end based on the second historical service.

8. The method according to claim 1, characterized in that The step of obtaining the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and switching the first running service to run on the target terminal based on the switching control instruction, includes: Identify whether the target switching control event meets a preset event trigger condition; In response to the relative position relationship between the user terminal and the target terminal satisfying a preset position relationship condition when the real-time behavior data is collected, it is determined that the target switching control event satisfies the event triggering condition.

9. A multi-terminal control system, characterized in that: The system includes a behavior data real-time collection component, a behavior habit recognition model, a switching control event recognition component, a control component and a storage component, wherein: The behavior data real-time collection component is used to collect the real-time behavior data of the user terminal and transmit the real-time behavior data to the storage component; The behavior habit recognition model is used to obtain a candidate behavior habit set of the user terminal, and determine a target behavior habit of the user terminal according to the real-time behavior data obtained from the storage component, and transmit the target behavior habit to the switching control event recognition component; The switching control event identification component is used to obtain a historical switching control event set of the user terminal, and identify a target switching control event to which the user terminal belongs from the historical switching control event set according to the received target behavior habit; The control component is used to generate a corresponding switching control instruction according to the target switching control event, and switch the first running service on the user terminal to the target terminal for running based on the switching control instruction.

10. The system according to claim 9, characterized in that The system also includes a server interaction component, wherein: The server interaction component is used to obtain the sample behavior data and sample behavior habits of the user terminal and transmit them to the storage component; The behavior habit recognition model is also used to obtain the sample behavior data and sample behavior habits from the storage component to perform model training and learning to obtain a trained target behavior habit recognition model.

11. The system according to claim 10, characterized in that The system also includes an encryption component, wherein the encryption component is used to encrypt candidate data to be transmitted to the server by the server interaction component to obtain encrypted target data, wherein the target data is used to be uploaded to the server for archiving via the server interaction component.

12. A multi-terminal control device, characterized in that: The device comprises: An acquisition module, used to acquire a candidate behavior habit set of a user terminal and a candidate switching control event of the user terminal under each candidate behavior habit in the candidate behavior habit set; A collection module, used to collect the real-time behavior data of the user terminal, and identify the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set, so as to determine the target switching control event currently corresponding to the user terminal from each candidate switching control event; The control module is used to obtain the switching control instruction of the user terminal and the first running service to be switched on the user terminal, and switch the first running service to run on the target terminal based on the switching control instruction.

13. The device according to claim 12, characterized in that The acquisition module is also used for: Obtain the trained target behavior habit recognition model; Acquire a historical behavior data set of the user terminal within a historical time range, and acquire a candidate behavior habit to which each historical behavior data in the historical behavior data set belongs through the target behavior habit recognition model, so as to obtain the candidate behavior habit set of the user terminal; For any candidate behavior habit, a historical switching control event of the user terminal under the candidate behavior habit is obtained as the candidate switching control event under the candidate behavior habit.

14. The device according to claim 13, characterized in that The acquisition module is also used for: Acquire a candidate behavior habit recognition model to be trained, and a training sample of the candidate behavior habit recognition model, wherein the training sample is obtained through sample behavior data and sample behavior habits of the user terminal; Training the candidate behavior habit recognition model based on the training sample to obtain an output behavior habit obtained by the candidate behavior habit model based on the sample behavior data in the training sample; Obtain the loss value of the output behavior habit based on the sample behavior habit, and adjust the model parameters of the candidate behavior habit recognition model based on the loss value, and return to obtain the next training sample to continue training the candidate behavior habit recognition model with adjusted parameters until the training is completed, thereby obtaining a trained target behavior habit recognition model.

15. The device according to claim 13, characterized in that The acquisition module is also used for: Acquire a set of initial historical switching control events of the user terminal under the candidate behavior habit within the historical time range; Obtaining the historical occurrence probability of each initial historical switching control event in the initial historical switching control event set within the historical time range; For any initial historical switching control event, in response to the historical occurrence probability of the initial historical switching control event being greater than or equal to a preset probability threshold, the initial historical switching control event is determined to be the historical switching control event of the user terminal under the candidate behavior habit.

16. The device according to claim 12, characterized in that The acquisition module is also used for: Inputting the real-time behavior data into a trained target behavior habit model, and identifying the target behavior habit corresponding to the real-time behavior data from the candidate behavior habit set through the target behavior habit model; For any candidate switching control event, in response to a candidate behavior habit corresponding to the candidate switching control event being the same as the target behavior habit, the candidate switching control event is determined to be the target switching control event corresponding to the target behavior habit.

17. The device according to claim 1, characterized in that The control module is also used for: Acquire the first running service switched on the user terminal and the second running service switched on the target terminal under the target switching control event; Based on the switching control instruction, the user end is controlled to stop the operation of the first operation service and the target end is controlled to start the operation of the second operation service.

18. The device according to claim 17, characterized in that The control module is also used for: Obtaining a terminal set covered by the local area network to which the user terminal belongs; Acquire historical switching control instructions received by the user terminal within a historical time range under the target switching control event, and determine the target terminal to be switched from the terminal set based on the historical switching control instructions; Obtain the historical switching control instruction to instruct the first historical service to stop running on the user end, and to instruct the second historical service to start running on the target end, and determine the first running service to be switched on the user end based on the first historical service, and determine the second running service to be switched to run on the target end based on the second historical service.

19. The device according to claim 1, characterized in that The control module is also used for: Identify whether the target switching control event meets a preset event trigger condition; In response to the relative position relationship between the user terminal and the target terminal satisfying a preset position relationship condition when the real-time behavior data is collected, it is determined that the target switching control event satisfies the event triggering condition.

20. An electronic device, characterized in that: Including memory and processor; The processor runs a program corresponding to the executable program code by reading the executable program code stored in the memory, so as to implement the method according to any one of claims 1 to 8.

21. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

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