Linkage control strategy generation method and device

Abstract

The embodiment of the invention relates to a linkage control strategy generation method and device, and the method is applied to a joint working scene of a plurality of intelligent devices, and comprises the steps: receiving configuration demand information; analyzing the configuration demand information through a preset model, wherein the configuration demand information comprises a target scene and a configuration demand; determining a target intelligent device related to the configuration demand from a device capability set of the plurality of intelligent devices, and determining a behavior rule of the target intelligent device in the target scene; and determining a linkage control strategy according to the behavior rule and the equipment capability set of each piece of target intelligent equipment so as to control the target intelligent equipment to realize the configuration requirement according to the linkage control strategy in the target scene. Therefore, the linkage control strategy can be efficiently and accurately generated while the time cost is saved, and the user experience is improved.

Description

Technical Field

[0001] This application relates to the field of smart home device technology, and in particular to a method and apparatus for generating linkage control strategies. Background Technology

[0002] Today, the pace of intelligent development in various fields is accelerating, and the home living sector is also gradually moving towards intelligentization. As the number of smart devices increases, controlling products in smart homes is becoming increasingly complex and difficult. Users need to remember the functions of each device and the corresponding control methods. Setting up multiple devices simultaneously inevitably leads to omissions, which is not user-friendly. Therefore, it is essential to improve the user experience by using a linkage control strategy to control multiple smart devices in a smart home.

[0003] In existing technologies, linkage control strategies are generally created manually by users. This requires users to fully understand the attributes, services, event lists, and data structures of each smart device in the smart home, as well as learn the control logic of the linkage engine and linkage rules, and set the linkage control strategy according to their own actual needs.

[0004] However, the above methods place high demands on users and require a very high time cost. Since they are manually set, the process of generating the linkage control strategy is lengthy and prone to errors, which affects the user experience.

[0005] Application content

[0006] In view of this, in order to solve the technical problem that the process of manually generating linkage control strategies by users in the prior art is lengthy and prone to errors, which affects the user experience, this application provides a linkage control strategy generation method and apparatus.

[0007] In a first aspect, embodiments of this application provide a method for generating a linkage control strategy, which is applied to a scenario where multiple smart devices work together. The method includes:

[0008] Receive configuration requirement information;

[0009] The configuration requirement information, including the target scenario and configuration requirements, is parsed using a preset model.

[0010] From the set of device capabilities of multiple smart devices, a target smart device related to the configuration requirements is determined, and the behavior rules of the target smart device in the target scenario are determined;

[0011] Based on the behavioral rules and the device capability set of each target smart device, a linkage control strategy is determined to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

[0012] As an optional implementation, determining the target smart device related to the configuration requirements from a set of device capabilities of multiple smart devices includes:

[0013] Determine the device identifier of each of the plurality of smart devices;

[0014] Based on the device identifier, determine the device capability set corresponding to each of the smart devices;

[0015] Determine the installation location of the smart device;

[0016] Based on the device capability set and the installation location, determine whether the smart device is a target smart device related to the configuration requirements.

[0017] As an optional implementation, determining whether the smart device is a target smart device related to the configuration requirements based on the device capability set and the installation location includes:

[0018] Determine the target functionalities included in the configuration requirements;

[0019] Based on the device capability set, determine whether the smart device can achieve the target function;

[0020] If it is determined that the smart device can achieve the target function, it is determined whether the installation location of the smart device is within the target scene;

[0021] If it is determined that the installation location of the smart device is within the target scene, then the smart device is determined to be the target smart device related to the configuration requirements.

[0022] As an optional implementation, determining the behavior rules of the target intelligent device in the target scenario includes:

[0023] Obtain the daily behavior rules of the target smart device in the preset scenario within a preset historical time period, wherein the preset scenario includes at least the target scenario;

[0024] Based on the daily behavior rules under the preset scenario, the behavior rules of the target smart device under the target scenario are determined.

[0025] As an optional implementation, the daily behavior rules of each smart device in the preset scenario are obtained in the following way:

[0026] If a behavioral event is detected in the preset scenario, determine whether the execution object of the behavioral event is a smart device in the preset scenario;

[0027] If the execution object of the behavior event is determined to be a smart device in the preset scenario, the device behavior information corresponding to the behavior event is obtained;

[0028] The device behavior information is stored in a preset database;

[0029] In the absence of detected behavioral events, the device behavior information stored in the database is self-learned to obtain the daily behavior rules of each smart device in the preset scenario.

[0030] As an optional implementation, determining the linkage control strategy based on the behavioral rules and the device capability set of each target intelligent device includes:

[0031] Analyze the configuration requirements to determine the triggering conditions for each target smart device;

[0032] Based on the triggering conditions and the set of capabilities of each target smart device, an initial linkage control strategy is determined;

[0033] Based on the initial linkage control strategy and the behavior rules, a linkage control strategy is determined.

[0034] As an optional implementation, determining the linkage control strategy based on the initial linkage control strategy and the behavior rules includes:

[0035] Based on the initial linkage control strategy and the behavior rules, at least one preset dimension of linkage control conditions is determined. The preset dimension includes one or more of the following: time dimension, device dimension, user dimension, triggering action, and execution action.

[0036] The linkage control conditions are input into a preset linkage control strategy model to obtain the linkage control strategy.

[0037] As an optional implementation, after determining the linkage control strategy based on the behavior rules and the device capability set of each target smart device, the following further step is taken:

[0038] The linkage control strategy is output through a visual interface;

[0039] Upon receiving a user's modification operation on the linkage control strategy, the modified target linkage control strategy is obtained;

[0040] Update the linkage control strategy to the target linkage control strategy.

[0041] As an optional implementation, the preset model is trained in the following way:

[0042] Obtain a set of configuration requirement information samples, which includes multiple configuration requirement information samples, each of which corresponds to a standard scenario and standard configuration requirements;

[0043] The preset initial model is trained using the configuration requirement information sample set to obtain the predicted scenario and predicted configuration requirement corresponding to each configuration requirement information sample output by the initial model.

[0044] For each configuration requirement information sample, a first loss value is determined between the predicted scenario corresponding to the configuration requirement information sample and the corresponding standard scenario, and a second loss value is determined between the predicted configuration requirement corresponding to the configuration requirement information sample and the standard configuration requirement.

[0045] Based on the first loss value and the second loss value corresponding to each configuration requirement information sample, determine whether the preset training stop condition is met.

[0046] If the training stop condition is met, a pre-set model that has completed training is obtained.

[0047] Secondly, embodiments of this application provide a linkage control strategy generation device, which is applied in a scenario where multiple smart devices work together. The device includes:

[0048] The receiving module is used to receive configuration requirement information;

[0049] The parsing module is used to parse the configuration requirement information through a preset model. The configuration requirement information includes the target scenario and configuration requirements.

[0050] The first determining module is used to determine a target smart device related to the configuration requirements from a set of device capabilities of multiple smart devices, and to determine the behavior rules of the target smart device in the target scenario;

[0051] The second determining module is used to determine a linkage control strategy based on the behavior rules and the device capability set of each target smart device, so as to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

[0052] Thirdly, embodiments of this application provide an electronic device, including: a processor and a memory, wherein the processor is configured to execute a linkage control strategy generation program stored in the memory to implement the linkage control strategy generation method described in any one of the first aspects.

[0053] Fourthly, embodiments of this application provide a storage medium storing one or more programs, which can be executed by one or more processors to implement the linkage control strategy generation method described in any one aspect.

[0054] The technical solution provided in this application, upon receiving configuration requirement information input by the user, combines the device capability set and behavior rules of the smart device to automatically generate a linkage control strategy for multiple target smart devices that conforms to the target scenario and configuration requirements included in the configuration requirement information. This achieves automatic generation of linkage control strategies that meet the user's linkage requirements, saving time and costs while generating linkage control strategies efficiently and accurately, thus improving the user experience. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application;

[0056] Figure 2 A flowchart illustrating an embodiment of a linkage control strategy generation method provided in this application;

[0057] Figure 3 A flowchart illustrating an embodiment of another linkage control strategy generation method provided in this application;

[0058] Figure 4 A flowchart illustrating the framework of a linkage control strategy generation method provided in this application embodiment;

[0059] Figure 5 A block diagram illustrating an embodiment of a linkage control strategy generation device provided in this application;

[0060] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0062] The following disclosure provides numerous different embodiments or examples for implementing various structures of this application. To simplify the disclosure, specific examples of components and arrangements are described below. These are merely examples and are not intended to limit the scope of this application. Furthermore, reference numerals and / or letters may be repeated in different examples. Such repetition is for simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or arrangements discussed.

[0063] To address the technical problem that the process of manually generating linkage control strategies by users in existing technologies is lengthy and prone to errors, thus affecting user experience, this application provides a linkage control strategy generation method and apparatus. This method automatically generates linkage control strategies for multiple target smart devices that meet the target scenarios and configuration requirements included in the configuration requirements information by combining the device capability set and behavior rules of the smart devices when receiving configuration requirement information input by the user. This achieves automatic generation of linkage control strategies that meet user linkage needs, saving time and costs while generating linkage control strategies efficiently and accurately, thereby improving user experience.

[0064] To facilitate understanding of the linkage control strategy generation method provided in the embodiments of this application, the application scenarios involved in the embodiments of this application will be described below:

[0065] See Figure 1 This is a schematic diagram illustrating an application scenario provided by an embodiment of this application. For example... Figure 1 As shown, the application scenario may include: control terminal 10, base station 11, smart device 12, smart device 13, smart device 14, and smart device 15.

[0066] The control terminal 10 may include an input module, which may be a voice input module or a text input module. Users can speak configuration requirements to the control terminal 10 through the input module, or input text content corresponding to the configuration requirements to the control terminal 10 through the input module. This application embodiment does not limit this.

[0067] The aforementioned control terminal 10 can be a hardware device or software that supports network connectivity to provide various network services. When the control terminal is hardware, it can be a variety of electronic devices with a display screen, including but not limited to smartphones, tablets, laptops, desktop computers, etc. When the control terminal is software, it can be installed in the electronic devices listed above. Figure 1 The following explanation uses only the control terminal 10 as a computer as an example.

[0068] The input module can be a voice acquisition device connected to the control terminal 10, such as a microphone, or it can be the display screen of the control terminal, which has a text input box so that the user can input text information from the text input box.

[0069] The aforementioned base station 11 can be a type of home control device within the home security product category, serving as the central hub for the product in the home and managing connected devices such as cameras and sensors. It can be used to learn from behavioral information within a preset area (e.g., a user's home area) to derive daily behavioral rules for smart devices.

[0070] Furthermore, the aforementioned base station 11 may include a controller, which may include a receiving module, which may be a data receiving device connected to the controller in the base station 11. That is, the user can upload configuration requirement information through the control terminal 10, and the control terminal can send the configuration requirement information to the receiving module. Therefore, the receiving module can obtain the configuration requirement information input by the user.

[0071] The aforementioned smart devices 12, 13, 14, and 15 are smart devices in home security systems, such as cameras and projectors. They can also be smart home devices installed in the home, such as smart refrigerators, smart air conditioners, and smart TVs. This application embodiment does not impose any limitations on these. The figures illustrate this using smart devices 12 and 13 as cameras, and smart devices 14 and 15 as smart TVs. These smart devices can be smart devices in different scenarios or in the same scenario; for example, smart device 12 can be a camera in the living room, and smart device 13 can be a camera in the yard. This application embodiment does not impose any limitations on these.

[0072] In one embodiment, the execution entity of this application embodiment may be a control terminal 10, which can obtain data (such as the daily behavior rules of smart devices) by interacting with the base station 11, thereby realizing the linkage control strategy generation method provided in this application.

[0073] In another embodiment, the execution subject of this application embodiment may be the controller in the base station 11. The controller can obtain the data sent by the control terminal 10 (such as the configuration requirement information input by the user in the control terminal 10) through the receiving module, thereby realizing the linkage control strategy generation method provided in this application.

[0074] In one embodiment, when a user wants to control smart devices in the home area, they can input the corresponding configuration requirements into the control terminal 10 via the input module using voice commands.

[0075] In another embodiment, when a user wants to control smart devices in a home area, they can input the corresponding configuration requirements into the control terminal 10 via the input module.

[0076] Based on this, when the execution subject of this application embodiment is the control terminal 10, after receiving the above configuration requirement information, the control terminal 10 can obtain the daily behavior rules of the user's home area from the base station 11, and based on this, use the linkage control strategy generation method provided in this application embodiment to determine the linkage control strategy corresponding to the user's needs, and perform linkage control on all or part of the above-mentioned smart devices 12, smart devices 13, smart devices 14, and smart devices 15 according to the linkage control strategy.

[0077] Optionally, when the executing entity in this embodiment is the controller within the base station 11, the control terminal 10, after receiving the configuration requirement information, can send the configuration requirement information to the controller of the base station 11. Then, the controller can use its own receiving module to receive the configuration requirement information sent by the control terminal 10, and use the linkage control strategy generation method provided in this embodiment to determine the linkage control strategy corresponding to the user requirement, and perform linkage control on all or some of the intelligent devices 12, 13, 14, and 15 according to the linkage control strategy.

[0078] The linkage control strategy generation method provided in this application will be further explained and described below with reference to the accompanying drawings and specific embodiments. The embodiments do not constitute a limitation on the embodiments of this application.

[0079] See Figure 2 This is a flowchart illustrating an embodiment of a linkage control strategy generation method provided in this application. In one embodiment, Figure 2 The process shown can be applied to control terminals or base stations, for example. Figure 1 The control terminal 10 or base station 11 in the application scenario shown can be further applied to the joint operation scenario of multiple intelligent devices, as illustrated. Figure 2 As shown, the process may include the following steps:

[0080] Step 201: Receive configuration requirement information.

[0081] The aforementioned configuration requirement information is used to characterize the user's need for the linkage of multiple smart devices, and can also be understood as the effect to be achieved when multiple smart devices are linked. The aforementioned configuration requirement information can be voice information input by the user, for example, if the user wants the smart device to intelligently monitor the security of the backyard, then the user can say the following voice: "Help me protect the security of the backyard on weekdays," or it can be text information input by the user. This application embodiment does not limit this.

[0082] In one embodiment, the executing entity of this application embodiment can receive voice or text information input by the user in real time, and determine the collected voice or text information as configuration requirement information.

[0083] As an exemplary implementation, the input module provided in this application embodiment may include a linkage scene setting page, which contains a linkage button. Based on this, when a user wants to control a smart device in a linkage manner, they can enter the linkage scene setting page, long-press the voice input button, and then speak the corresponding configuration request information to the voice input module of this application embodiment, such as "Help me protect the security of my backyard on weekdays," "When a stranger lingers at my door, help me warn and drive them away," or "I want my house to be cleaned when I come home every day," and other voice requests for different configurations.

[0084] As another exemplary implementation, the input module of this application embodiment may have a linkage scene setting page, which contains linkage buttons. Based on this, when a user wants to control a smart device in a linkage manner, they can enter the linkage scene setting page and input the corresponding configuration requirement text in the input box of the linkage scene setting page, such as inputting configuration requirement text like "protect the security of the backyard on weekdays".

[0085] Step 202: Analyze the above configuration requirement information using a preset model. The configuration requirement information includes the target scenario and configuration requirements.

[0086] The aforementioned preset model is a pre-trained information parsing model that can parse configuration requirement information. It can parse the input text or voice information to obtain the scene and configuration requirements corresponding to the input text or voice information.

[0087] The aforementioned target scenario refers to the scenario where a user wants to control multiple smart devices in a coordinated manner, that is, the scenario corresponding to the configuration requirement information. It can be any sub-scenario of the user's daily work, study, or living environment, such as the living room, front yard, or bedroom in the user's home. For example, if the user's configuration requirement information is to monitor the activities of a baby in the nursery and living room, then the target scenario could be the nursery and living room.

[0088] The above configuration requirements refer to the needs of users for smart devices when they want to achieve coordinated control of multiple smart devices, such as cooling, shooting, or lighting requirements.

[0089] In one embodiment, after receiving configuration requirement information, the execution subject of this application embodiment can parse the received configuration requirement information through a pre-trained preset model in order to more accurately understand the user's linkage control intention, thereby obtaining the target scenario and configuration requirements included in the configuration requirement information.

[0090] In order to more accurately determine the target scenario and configuration requirements of linkage control from the configuration requirement information, the preset model provided in this application embodiment can be a preset model obtained by further training on the basis of an existing model. For example, the preset model can be a large language model, which can be used to parse the input speech text. Such a large language model also exists in the prior art. Therefore, in this application embodiment, the above-mentioned existing large language model can be further trained to obtain the preset model in this application.

[0091] Based on this, when training the above-mentioned preset model, the execution subject of this application embodiment can obtain a set of configuration requirement information samples. The set of configuration requirement information samples may include multiple configuration requirement information samples, and each configuration requirement information sample may correspond to a standard scenario and standard configuration requirements.

[0092] Furthermore, in order to enable the preset model to more comprehensively recognize speech or text in different scenarios, the above-mentioned configuration requirement information sample set may include configuration requirement information samples for different scenarios. Each scenario may correspond to speech configuration requirement information samples with different accents and languages ​​but the same meaning, or each scenario may correspond to text configuration requirement information samples with different expressions but the same text meaning.

[0093] Based on this, the executing entity of this application embodiment can use the aforementioned configuration requirement information sample set to train a preset initial model, thereby obtaining the predicted scenario and predicted configuration requirement corresponding to each configuration requirement information sample output by the initial model. The aforementioned initial model can be a model that already exists in the prior art, or it can be a reconstructed model; this application embodiment does not impose any restrictions on this.

[0094] Then, for each configuration requirement information sample, a first loss value can be determined between the predicted scenario and the corresponding standard scenario, and a second loss value can be determined between the predicted configuration requirement and the standard configuration requirement.

[0095] Then, based on the first and second loss values ​​corresponding to each of the above configuration requirement information samples, it can be determined whether the preset stop training condition is met.

[0096] Optionally, if the above-mentioned conditions for stopping training are met, a pre-set model that has completed training can be obtained.

[0097] Conversely, if it is determined that the above-mentioned conditions for stopping training are not met, the initial model can continue to be trained using the above-mentioned configuration requirement information sample set until the trained model meets the above-mentioned conditions for stopping training, thereby obtaining the preset model that has been trained.

[0098] As an exemplary implementation, the execution entity of this application embodiment can determine whether the first loss value and the second loss value corresponding to each configuration requirement information sample are both less than a preset loss value threshold. Optionally, if the first loss value and the second loss value corresponding to each configuration requirement information sample are both less than the preset loss value threshold, or if the first loss value and the second loss value of configuration requirement information samples greater than a preset number threshold are both less than the preset loss value threshold, then it can be determined that the preset stop training condition is currently met.

[0099] Step 203: Identify the target smart devices related to configuration requirements from the set of device capabilities of multiple smart devices, and determine the behavior rules of the target smart devices in the target scenario.

[0100] Step 204: Determine the linkage control strategy based on the above behavior rules and the device capability set of each target intelligent device, so as to control the target intelligent device to achieve the above configuration requirements in the above target scenario according to the above linkage control strategy.

[0101] The following provides a unified explanation of steps 203 and 204:

[0102] The above set of device capabilities corresponds to the device function of the smart device, that is, what the smart device can do and what role it plays.

[0103] The aforementioned behavioral rules refer to the behavioral rules that the target smart device follows on a daily basis in the aforementioned target scenario. For example, in daily use, the air conditioner in the bedroom typically operates at what time and in what working mode.

[0104] In this embodiment of the application, in order to generate a linkage control strategy that more accurately corresponds to the user's configuration requirements, the execution entity of this embodiment of the application may determine the device capability set of each smart device in a preset scenario, determine the target smart device related to the above configuration requirements, and the behavior rules of the above target smart device in the target scenario, and on this basis determine the linkage control strategy according to the above behavior rules and the device capability set of each target smart device.

[0105] In one embodiment, the executing entity of this application embodiment may determine the device identifier of each of the multiple smart devices, and determine the device capability set corresponding to each smart device based on the device identifier.

[0106] As an exemplary implementation, the executing entity of this application embodiment may pre-store the object model of each smart device in a preset scenario, thereby determining the device capability set of each smart device based on this, and determining the target smart device related to the configuration requirements from multiple device capability sets. The preset scenario may at least include the target scenario.

[0107] The aforementioned object model refers to the digital representation of an entity (such as a camera or sensor) in the physical space corresponding to each type of smart device. It describes what the entity is (attributes), what it can do (services), and what information it can provide (events) from three dimensions: attributes, services, and events. Each object model can correspond to a type of smart device, and the object model for that type of smart device can include different models of smart devices within the same category.

[0108] Based on this, the execution entity of this application embodiment can determine the target object model corresponding to each of the multiple intelligent devices in a preset scenario from a preset object model set. The aforementioned object model set may include multiple object models, and each object model may correspond to a type of intelligent device.

[0109] Based on this, the device identifier of each smart device can be determined, and the device capability set corresponding to each smart device can be determined from the target object model according to the device identifier of each smart device.

[0110] As a feasible implementation, in a preset scenario that includes the target scenario, for each smart device installed, the execution subject of this application embodiment can interact with the smart device to obtain the device identifier of the smart device and store the correspondence between the smart device and the corresponding device identifier in the database.

[0111] Based on this, the executing entity of this application embodiment can directly obtain the device identifier of each smart device from the database.

[0112] Then, the installation location for each smart device can be determined.

[0113] As an exemplary implementation, in a preset scenario including the target scenario, each time a user installs a smart device, the installation location of that smart device can be stored in a preset database via a display interface. Based on this, the execution entity of this application embodiment can directly obtain the installation location of each smart device from the aforementioned database.

[0114] The aforementioned display interface may include a 3D scene diagram of a preset scene. Users can store the installation location of a smart device in the database by clicking on the installation location of the new smart device in the 3D scene diagram and entering information such as the type of smart device.

[0115] As another exemplary implementation, the executing entity of this application embodiment can call a preset image acquisition device to acquire scene images corresponding to multiple smart devices, and identify the scene images to determine the installation location of each smart device.

[0116] Finally, based on the aforementioned equipment capability set and installation location, it can be determined whether the smart device is the target smart device related to the above configuration requirements.

[0117] As an exemplary implementation, the target functions included in the user's configuration requirements can be determined first, and based on the device capability set of each smart device, it can be determined whether the corresponding smart device can achieve the above target functions.

[0118] Optionally, if it is determined that the smart device can achieve the above-mentioned target functions, it means that the smart device meets the functional requirements in the user's configuration requirements. In this case, in order to further determine whether the smart device is a target smart device that is completely related to the configuration requirements, the executing entity of this application embodiment can determine whether the installation location of the smart device is located within the target scenario of the above-mentioned configuration requirements.

[0119] Optionally, when it is determined that the aforementioned smart device is located within the target scenario of the configuration requirements, it indicates that the smart device meets the scenario requirements of the configuration requirements. Therefore, the smart device can be determined as the target smart device related to the aforementioned configuration requirements.

[0120] For example, suppose a user's configuration requirement is "turn on the living room lights and set the living room temperature to 27 degrees Celsius after the child comes home." Then the target scenario for this configuration requirement could be the living room, and the configuration requirement would be: turn on the lights and set the temperature to 27 degrees Celsius after the child comes home.

[0121] Continuing the assumption, the smart devices in a user's home may include: an air conditioner, a television, a refrigerator, a washing machine, smart lights (living room), and smart lights (bedroom), with the air conditioner, television, and refrigerator located in the living room. In this scenario, analyzing the above configuration requirements reveals that the target functions are lighting and cooling. Therefore, based on the device function sets of each smart device, it can be determined that the air conditioner and all smart lights satisfy the aforementioned target functions. Thus, the air conditioner and smart lights can be identified as the initial target smart devices that meet the functional requirements of the configuration.

[0122] Furthermore, in order to determine whether the aforementioned initial target smart devices meet the scenario requirements of the aforementioned configuration requirements, the installation locations of the aforementioned air conditioner and all smart lights can be determined separately, and the initial target smart devices installed in the living room are determined as the target smart devices related to the configuration requirements, namely the air conditioner and the smart lights installed in the living room.

[0123] In one embodiment, in order to determine a linkage control strategy that better conforms to the daily behavior rules of users and devices, the execution entity of this application embodiment can further determine the behavior rules of the target smart device in the target scenario, and then determine the linkage control strategy based on the behavior rules and the device capability set of each target smart device, so as to control the target smart device to achieve the above configuration requirements in the target scenario according to the linkage control strategy.

[0124] As an exemplary implementation, when determining the behavior rules of a target smart device in a target scenario, the executing entity of this application embodiment can obtain the daily behavior rules of the target smart device in a preset scenario within a preset historical time period. These daily behavior rules can be obtained from a base station, which can acquire them through local self-learning. The preset scenario may include at least the target scenario; for example, if the target scenario is a living room, the preset scenario may be the user's home, which may include bedrooms and a living room, etc.

[0125] Then, based on the daily behavior rules of the preset scenario, the behavior rules of the target smart device in the target scenario can be determined.

[0126] As an exemplary implementation, the executing entity of this application embodiment can directly use the daily behavior rules of each target smart device in a preset historical time period and in a preset scenario as the behavior rules of the target smart device in the target scenario.

[0127] In order to obtain daily behavior rules under preset scenarios in real time, the execution subject in this application embodiment can perform AI self-learning through a base station to learn the daily behavior rules under the preset scenarios. This method of obtaining daily behavior rules through local self-learning via a base station protects user privacy because the data does not need to leave the device for learning and improvement. Furthermore, since it does not require network transmission, it reduces network latency and improves response speed.

[0128] Based on this, when the execution subject of this application embodiment obtains the daily behavior rules under the preset scenario, it can obtain the daily behavior rules under the preset scenario from the base station. The base station can obtain the daily behavior rules under the preset scenario through local self-learning.

[0129] The aforementioned base station can obtain daily behavior rules under preset scenarios in the following ways: First, when a behavior event is detected under preset scenarios, it can be determined whether the execution object of the behavior event is a smart device under preset scenarios.

[0130] Optionally, if the execution object of the behavior event is determined to be a smart device in the aforementioned preset scenario, the device behavior information corresponding to the behavior event can be obtained. The aforementioned behavior event refers to an event in which the smart device performs a corresponding function after being triggered in the preset scenario, thereby causing a change in the device state of the smart device, such as a change in the monitoring direction of the camera or a change in the operating state of the air conditioner.

[0131] Then, the device behavior information can be stored in a preset database, and if no behavioral event is detected, the device behavior information stored in the database can be self-learned to obtain the daily behavior rules of the smart device under the preset scenario.

[0132] As to how the executing entity in this application's embodiments specifically determines the linkage control strategy based on behavioral rules and the device capability set of each target intelligent device, it can be explained below. Figure 3 The process shown will be explained in detail here.

[0133] Furthermore, to ensure that the determined linkage control strategy better meets the user's linkage control needs, the executing entity in this embodiment, after determining the linkage control strategy based on the behavior rules and device capability set of each target intelligent device, can output the linkage control strategy through a visual interface. Based on this, the user can modify the linkage control strategy. Upon receiving a user's modification operation regarding the linkage control strategy, the executing entity in this embodiment can obtain the modified target linkage control strategy and update the linkage control strategy accordingly.

[0134] Based on this, the execution entity of this application embodiment can perform linkage control on the smart devices in the preset scenario according to the updated target linkage control strategy described above.

[0135] For example, let's take the user's interaction intent as tracking and removing strangers as an example:

[0136] The linkage control strategy can be generated through the following steps:

[0137] 1. The user enters their own ID into the main controller, starts the calibration process, and slowly circles the house once.

[0138] 2. The main controller determines the relative positional relationship between cameras by identifying the time sequence of users and the pan-tilt rotation angle of each camera.

[0139] 3. When a user opens the APP and starts the voice input function, they can submit a configuration request: "I would like to receive a push notification and help drive away strangers when they linger around my house on weekdays, and then provide me with complete video recording data."

[0140] 4. After a period of processing, the APP will automatically generate the following message on the app interface: "When the sensors and cameras in the yard (front yard / back yard) detect a non-familiar person, a message alarm will be pushed, all recording devices in the yard (front yard / back yard) will be activated to record, and the person will be tagged. At the same time, an alarm will be triggered. The linkage is effective 24 / 7 from Monday to Friday."

[0141] 5. Users can manually adjust the settings to include the effective time on weekdays from 9:00 AM to 6:00 PM, then click save to create a complete set of rules for tracking and removing strangers.

[0142] Furthermore, the following linkage effects can be achieved by following the above linkage control strategy:

[0143] 1. If a stranger intrudes into the perimeter of a house, any camera that detects the stranger will trigger a stranger tracking and removal linkage, and a message will be pushed to the user.

[0144] 2. The main controller collects images returned by each camera and uses AI image algorithms to determine the area the stranger is about to enter based on the direction and speed of movement in the image. It then wakes up the cameras in the designated area to start recording, tracking, and sound and light alarms.

[0145] 3. Once a stranger leaves the perimeter of the home, the camera will stop recording and trigger an alarm.

[0146] 4. The main controller collects recordings from multiple cameras; uses AI face detection algorithms to extract clear facial portraits from multiple recordings; and draws the intrusion trajectory of the stranger based on the order in which the stranger appears in the images of each camera.

[0147] 5. The main controller combines video recordings, facial images, intrusion trajectories, first appearance time, first appearance location, departure time, departure location, and other multimodal key information to form event cards for users to view.

[0148] The technical solution provided in this application receives configuration requirement information, parses the configuration requirement information using a preset model, and determines the target smart devices related to the configuration requirements from a set of device capabilities of multiple smart devices. It also determines the behavior rules of the target smart devices in the target scenario and determines a linkage control strategy based on the behavior rules and the device capability set of each target smart device. This allows the target smart devices to be controlled according to the linkage control strategy to achieve the configuration requirements in the target scenario. This technical solution, by automatically generating linkage control strategies for multiple target smart devices that conform to the target scenario and configuration requirements when receiving configuration requirement information input by the user, combines the device capability set and behavior rules of the smart devices. This achieves automatic generation of linkage control strategies that meet the user's linkage requirements, saving time and costs while efficiently and accurately generating linkage control strategies, thus improving the user experience.

[0149] See Figure 3 This is a flowchart of an embodiment of another linkage control strategy generation method provided in this application. Figure 3 The process shown is in Figure 2 Based on the illustrated process, the specific details of how the linkage control strategy is determined according to behavioral rules and the device capability set of each target intelligent device are described. For example... Figure 3 As shown, the process may include the following steps:

[0150] Step 301: Analyze the configuration requirements and determine the triggering conditions for each target smart device.

[0151] The triggering conditions mentioned above refer to the triggering conditions of the target smart device in the target scenario. For example, if the user's configuration requirement is to monitor the activities of the baby in the nursery and living room, then the target scenario can be the nursery and living room, the target smart device can be the camera in the nursery and living room, and the triggering condition for the camera to take pictures is to identify the baby's activities.

[0152] In one embodiment, after inputting configuration requirements, the user can write their own linkage control requirements into the configuration requirements information. These linkage control requirements encompass the target scene, the target smart devices within the target scene, and the triggering conditions for each target smart device. Based on this, the execution entity of this application embodiment can parse the above configuration requirements to determine the triggering conditions for each target smart device.

[0153] Step 302: Determine the initial linkage control strategy based on the triggering conditions and device capability set of each target intelligent device.

[0154] The aforementioned initial linkage control strategy is a linkage control strategy between target smart devices. It is a preliminary linkage rule set for the target smart devices. For example, if the target smart devices are cameras in the nursery and living room, then the initial linkage control strategy can be that when a camera with recognition function identifies that the baby is active, the camera with specific camera function will take a picture of the baby.

[0155] In one embodiment, when determining the initial linkage control strategy between multiple target intelligent devices, the executing entity of this application embodiment can determine the initial linkage strategy between multiple target intelligent devices based on the triggering conditions and device capability set corresponding to each target intelligent device.

[0156] As an exemplary implementation, the functions that the target smart device can perform can be determined based on the device capability set of the target smart device, and the triggering conditions for triggering each target smart device in the target scenario can be determined based on the triggering conditions.

[0157] Based on this, the target functions that each target smart device needs to achieve in the target scenario can be determined according to the triggering conditions and the functions that each target smart device can achieve, and an initial linkage control strategy between one or more target smart devices can be generated.

[0158] For example, suppose the configuration requirement is "to cool and illuminate the living room upon detecting that any family member has returned home." The preset scenarios corresponding to this configuration requirement could include two air conditioners, a television, multiple smart lights, a washing machine, and a refrigerator located in the living room. Based on this configuration requirement, the target smart devices can be determined to be the two air conditioners and the smart lights located in the living room.

[0159] Assuming that both air conditioners (Air Conditioner 1 and Air Conditioner 2) can perform cooling functions based on their device capabilities, and the smart light can perform illumination functions, then from the above description, we can determine that Air Conditioner 1 will perform the cooling function, and the smart light will perform the illumination function. Furthermore, based on the configuration requirements, the trigger condition for both Air Conditioner 1 and the smart light is that a family member returns home. Therefore, the initial linkage control strategy can be determined as follows: when a family member returns home, Air Conditioner 1 and the smart light in the living room can be turned on.

[0160] Step 303: Determine the linkage control strategy based on the initial linkage strategy and behavior rules described above.

[0161] In one embodiment, after determining the initial linkage control strategy between target smart devices, a linkage control strategy can be determined based on the initial linkage control strategy and the behavior rules of each target smart device.

[0162] As an exemplary implementation, the execution entity of this application embodiment can combine the initial linkage control strategy and behavior rules to determine at least one preset dimension of linkage control conditions. The preset dimensions include, but are not limited to, time dimension, device dimension, user dimension, trigger action, and execution action.

[0163] Then, the linkage control conditions can be input into a preset linkage control strategy model to obtain the linkage control strategy output by the linkage control strategy model. The aforementioned linkage control strategy model can be a pre-stored linkage rule format specification model, through which linkage control strategies conforming to preset format conditions can be generated.

[0164] For example, suppose the received configuration requirement is "monitor the backyard security during the user's work hours and issue a warning after detecting a stranger." Further suppose the target smart devices corresponding to the above configuration requirement include: a human body sensor in the backyard, camera A, camera B, and a speaker. The initial linkage control strategy determined according to the above steps is: when the human body sensor in the backyard is triggered or the camera triggers detection, camera A in the backyard is linked to record video, while camera B performs patrol and flashing. When the target is determined to be a stranger, the speaker is linked to issue a warning.

[0165] Continuing to assume the behavior rules of each target smart device are as follows: the human body sensor in the backyard detects and identifies users from Monday to Friday, specifically at 9:00 AM, 6:00 PM, and 9:00 PM each day; camera A records video upon receiving a signal from the human body sensor; camera B performs patrol and flashing actions upon receiving a signal from the human body sensor; and the speaker issues a warning upon receiving a stranger signal from the human body sensor.

[0166] Based on the initial linkage control strategy and the behavior rules of each target smart device, the following linkage control conditions can be obtained, including but not limited to: Time dimension: Monday to Friday, 9:00 AM to 6:00 PM or 9:00 PM daily; Device dimension: Human body sensor, Camera A, Camera B, and speaker in the backyard; User dimension: Each family member who needs to go to and from get off work; Trigger action: The human body sensor detects an object and determines that the object is a stranger, then the speaker is triggered; Execution action: The human body sensor is used to detect objects and determine whether the detected object is a stranger, Camera A is used for recording, Camera B is used for patrol and flashing light processing, and the speaker is used to issue a warning.

[0167] Then, the above-mentioned linkage control conditions can be input into the preset linkage control strategy model, so that the model generates a linkage control strategy that conforms to the preset format conditions. The resulting linkage control strategy can be as follows: when the human body sensor in the backyard is triggered and detects an object, the camera A in the backyard is linked to record video, while the camera B performs patrol and flashing. The human body sensor is used to identify whether the object is a stranger. If so, the horn will sound a warning. The effective time is from Monday to Friday, from 9:00 am to 6:00 pm or 9:00 pm every day, with a weekly cycle.

[0168] Furthermore, since user configuration requirements are generally set based on themselves and their family members, each configuration requirement can correspond to at least one target user, which can be a family member or a stranger. Based on this, the executing entity in this embodiment can further adjust the obtained linkage control strategy according to the target user's user behavior rules, so that the linkage control strategy better conforms to the user's daily behavior patterns. Here, the aforementioned target user refers to the user involved in the configuration requirement information, who can be a family member with historical behavior rules or a stranger without historical behavior rules; this embodiment does not impose any restrictions on this.

[0169] In one embodiment, when the target user is a pre-recorded family member, meaning the target user has historical behavioral rules in the target scenario, the user behavior rules of the target user in the target scenario can be obtained. The linkage control strategy is then adjusted based on these user behavior rules.

[0170] As an exemplary implementation, when determining the user behavior rules of a target user in a target scenario, the executing entity of this application embodiment may first obtain the daily behavior rules of the target user in a preset scenario within a preset historical time period from the base station. The base station can obtain the daily behavior rules in the preset scenario through local self-learning, and the preset scenario may at least include the target scenario. For example, if the target scenario is a living room, the preset scenario may be the user's home, which may include bedrooms and a living room, etc.

[0171] Then, based on the daily behavior rules of the target users in the preset scenarios, the user behavior rules of the target users in the target scenarios can be determined.

[0172] In order to obtain daily behavior rules under preset scenarios in real time, the execution subject in this application embodiment can perform AI self-learning through a base station to learn the daily behavior rules under the preset scenarios. This method of obtaining daily behavior rules through local self-learning via a base station protects user privacy because the data does not need to leave the device for learning and improvement. Furthermore, since it does not require network transmission, it reduces network latency and improves response speed.

[0173] Based on this, when the execution subject of this application embodiment obtains the daily behavior rules under the preset scenario, it can obtain the daily behavior rules under the preset scenario from the base station corresponding to the preset scenario. The base station can obtain the daily behavior rules of each user under the preset scenario through local self-learning.

[0174] The aforementioned base station can obtain the daily behavior rules of each user in a preset scenario through the following methods: First, when a behavioral event is detected in the preset scenario, it can be determined whether the execution object of the behavioral event is a user in the preset scenario. Optionally, if it is determined that the execution object of the behavioral event is a user in the preset scenario, the user behavior information corresponding to the behavioral event can be obtained. The aforementioned behavioral event refers to the event corresponding to the behavior when the user's state changes in the preset scenario, such as the user entering the camera's shooting range.

[0175] The user behavior information can then be stored in a preset database. If no behavioral event is detected, the user behavior information stored in the database can be self-learned to obtain the user's daily behavior rules under the preset scenario.

[0176] Furthermore, in one embodiment, after determining the linkage control strategy between target smart devices, the linkage control strategy can be adjusted according to the user behavior rules.

[0177] As an exemplary implementation, the execution entity of this application embodiment can combine the linkage control strategy and user behavior rules to redetermine at least one preset dimension of linkage control conditions. The preset dimensions include, but are not limited to, time dimension, device dimension, user dimension, triggering action, and execution action.

[0178] Then, the linkage control conditions can be input into a preset linkage control strategy model to obtain the linkage control strategy output by the linkage control strategy model. The aforementioned linkage control strategy model can be a pre-stored linkage rule format specification model, through which linkage control strategies conforming to preset format conditions can be generated.

[0179] For example, suppose the received configuration requirement is "monitor the backyard security during the user's work hours and issue a warning after detecting a stranger." Further suppose the target smart devices corresponding to the above configuration requirement include: a human body sensor in the backyard, camera A, camera B, and a speaker. The initial linkage control strategy determined according to the above steps is: when the human body sensor in the backyard is triggered or a camera that has moved into the backyard triggers detection, camera A in the backyard is linked to record video, while camera B performs patrol and flashing actions. When the target is determined to be a stranger, the speaker is linked to issue a warning.

[0180] Continuing to assume the behavior rules of each target smart device are as follows: the human body sensor in the backyard detects and identifies users from Monday to Friday, specifically at 9:00 AM, 6:00 PM, and 9:00 PM each day; camera A records video upon receiving a signal from the human body sensor; camera B performs patrol and flashing actions upon receiving a signal from the human body sensor; and the speaker issues a warning upon receiving a stranger signal from the human body sensor.

[0181] Based on the initial linkage control strategy and the behavior rules of each target smart device, the following linkage control conditions can be obtained, including but not limited to: Time dimension: Monday to Friday, 9:00 AM to 6:00 PM or 9:00 PM daily; Device dimension: Human body sensor, Camera A, Camera B, and speaker in the backyard; User dimension: Each family member who needs to go to and from get off work; Trigger action: The human body sensor detects an object and determines that the object is a stranger, then the speaker is triggered; Execution action: The human body sensor is used to detect objects and determine whether the detected object is a stranger, Camera A is used for recording, Camera B is used for patrol and flashing light processing, and the speaker is used to issue a warning.

[0182] Then, the above-mentioned linkage control conditions can be input into the preset linkage control strategy model, so that the model generates a linkage control strategy that conforms to the preset format conditions. The resulting linkage control strategy can be as follows: when the human body sensor in the backyard is triggered and detects an object, the camera A in the backyard is linked to record video, while the camera B performs patrol and flashing. The human body sensor is used to identify whether the object is a stranger. If so, the horn will sound a warning. The effective time is from Monday to Friday, from 9:00 am to 6:00 pm or 9:00 pm every day, with a weekly cycle.

[0183] Continuing to assume that the behavioral rules of the target users are: working from Monday to Friday, starting work at 9:00 am and finishing get off work at 6:00 pm, and taking a walk in the backyard at 9:00 pm.

[0184] Based on this behavioral rule, it can be determined that 9:00 PM is the target user's walking time, not their working hours. Therefore, the above-mentioned linkage control strategy can be adjusted as follows: when the human body sensor in the backyard is triggered and detects an object, it will trigger the backyard camera A to record video, while camera B will patrol and flash its lights. The human body sensor will also identify whether the object is a stranger. If so, it will trigger the horn to issue a warning. This will be effective from Monday to Friday, from 9:00 AM to 6:00 PM, on a weekly cycle.

[0185] The technical solution provided in this application analyzes configuration requirements to determine the triggering conditions for each target smart device. Based on the triggering conditions and device capability set of each target smart device, an initial linkage strategy is determined. Then, based on the initial linkage strategy and behavioral rules, a linkage control strategy is determined. This technical solution first determines the initial linkage control strategy corresponding to the target smart device in terms of functionality, and then generates a corresponding linkage control strategy based on the target smart device's behavioral rules and the initial linkage control strategy. It can accurately and quickly automatically generate linkage control strategies that meet user configuration requirements, saving time and costs while efficiently and accurately generating linkage control strategies, thus improving the user experience.

[0186] See Figure 4 The above is a flowchart of a linkage control strategy generation method provided in an embodiment of this application. Figure 4 The illustrated process explains how the target-linkage control strategy is generated from both user behavior and device behavior perspectives. For example... Figure 4 As shown, the process may include the following steps:

[0187] First, the process of configuring a linkage strategy by a user may include the following steps:

[0188] 1. User behavior: Users open the control terminal APP, enter the linkage scene settings page, and add linkage buttons.

[0189] 2. User Behavior: Enter the Add Linkage page, long press the voice input button, and set up linkages via voice, such as "Help me protect the safety of my backyard on weekdays," "Warn and drive away strangers when they linger at my door," "I want my house to be cleaned when I come home every day," and other different functional requests.

[0190] Based on this, device behavior may include the following steps:

[0191] (1) Device behavior: The APP obtains the user's spoken voice content, communicates with the cloud-based large language model for confirmation, and forms the user's semantic analysis content.

[0192] (2) Device behavior: The local base station combines the bound device combination information, the user's parameter, environment, location, policy configuration information for each device, and the daily triggered behavior of the device, and uses a self-learning algorithm to regulate the daily behavior rules of the user and all devices.

[0193] (3) Equipment behavior: Obtain the complete set of capabilities of various object models and the preset linkage rule format specifications.

[0194] (4) Device behavior: Generate corresponding target linkage control strategies based on the above user semantic parsing content, daily behavior rules, complete set of various object model capabilities, and linkage rule format specifications.

[0195] 3. User Behavior: After a period of waiting, the added linkage page automatically generates suitable linkage configuration conditions, such as "When the human sensor in the backyard is triggered or the camera is triggered by walking, the camera A in the backyard will record, while camera B will patrol and flash. The effective time is from Monday to Friday, with a weekly cycle strategy." The page also asks the user whether to save the final configuration.

[0196] 4. User behavior: The user confirms the linkage strategy content and clicks save, and the strategy is saved successfully.

[0197] The technical solution provided in this application uses a large language model to match user-wide home linkage scenarios and performs localized AI data analysis and processing of home information at the base station to form user behavior rules, thereby generating target linkage control strategies based on user linkage intentions. This technical solution significantly reduces the barrier to establishing device linkage rules, saves user effort, and improves the efficiency of users obtaining information by generating association rules, thus greatly enhancing the user experience.

[0198] See Figure 5 This is a block diagram illustrating an embodiment of a linkage control strategy generation device provided in this application. As an example, the aforementioned linkage control strategy generation device can be applied to a scenario where multiple intelligent devices work together. Figure 5 As shown, the device includes:

[0199] Receiver module 51 is used to receive configuration requirement information;

[0200] The parsing module 52 is used to parse the configuration requirement information through a preset model. The configuration requirement information includes the target scenario and configuration requirements.

[0201] The first determining module 53 is used to determine a target smart device related to the configuration requirements from a set of device capabilities of multiple smart devices, and to determine the behavior rules of the target smart device in the target scenario;

[0202] The second determining module 54 is used to determine a linkage control strategy based on the behavior rules and the device capability set of each target smart device, so as to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

[0203] like Figure 6 The diagram shown is a structural schematic of an electronic device provided in an embodiment of this application, including a processor 61, a communication interface 62, a memory 63, and a communication bus 64. The processor 61, communication interface 62, and memory 63 communicate with each other via the communication bus 64.

[0204] Memory 63 is used to store computer programs;

[0205] In one embodiment of this application, when the processor 61 executes the program stored in the memory 63, it implements the linkage control strategy generation method provided in any of the foregoing method embodiments, including:

[0206] Receive configuration requirement information;

[0207] The configuration requirement information, including the target scenario and configuration requirements, is parsed using a preset model.

[0208] From the set of device capabilities of multiple smart devices, a target smart device related to the configuration requirements is determined, and the behavior rules of the target smart device in the target scenario are determined;

[0209] Based on the behavioral rules and the device capability set of each target smart device, a linkage control strategy is determined to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

[0210] This application also provides a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the linkage control strategy generation method provided in any of the foregoing method embodiments.

[0211] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0212] Through the above description of the embodiments, those skilled in the art can clearly understand that each embodiment can be implemented using software plus a general-purpose hardware platform, or of course, using hardware. Based on this understanding, the above technical solutions, in essence or the parts that contribute to the related technology, can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.

[0213] It should be understood that the terminology used herein is for the purpose of describing particular exemplary embodiments only and is not intended to be limiting. Unless the context clearly indicates otherwise, the singular forms “a,” “an,” and “described” as used herein may also include the plural forms. The terms “comprising,” “including,” “containing,” and “having” are inclusive and therefore indicate the presence of the stated features, steps, operations, elements, and / or components, but do not exclude the presence or addition of one or more other features, steps, operations, elements, components, and / or combinations thereof. The method steps, processes, and operations described herein are not construed as requiring them to be performed in a particular order described or illustrated unless the order of performance is explicitly indicated. It should also be understood that additional or alternative steps may be used.

[0214] The above description is merely a specific embodiment of this application, enabling those skilled in the art to understand or implement this application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this application. Therefore, this application is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for generating a linkage control strategy, characterized in that, The linkage control strategy generation method is applied to scenarios where multiple smart devices work together. The method includes: Receive configuration requirement information; The configuration requirement information, including the target scenario and configuration requirements, is parsed using a preset model. From the set of device capabilities of multiple smart devices, a target smart device related to the configuration requirements is determined, and the behavior rules of the target smart device in the target scenario are determined; Based on the behavioral rules and the device capability set of each target smart device, a linkage control strategy is determined to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

2. The method according to claim 1, characterized in that, The step of determining the target smart device related to the configuration requirements from the set of device capabilities of multiple smart devices includes: Determine the device identifier of each of the plurality of smart devices; Based on the device identifier, determine the device capability set corresponding to each of the smart devices; Determine the installation location of the smart device; Based on the device capability set and the installation location, determine whether the smart device is a target smart device related to the configuration requirements.

3. The method according to claim 2, characterized in that, The step of determining whether the smart device is a target smart device related to the configuration requirements based on the device capability set and the installation location includes: Determine the target functionalities included in the configuration requirements; Based on the device capability set, determine whether the smart device can achieve the target function; If it is determined that the smart device can achieve the target function, it is determined whether the installation location of the smart device is within the target scene; If it is determined that the installation location of the smart device is within the target scene, then the smart device is determined to be the target smart device related to the configuration requirements.

4. The method according to claim 1, characterized in that, The step of determining the behavior rules of the target intelligent device in the target scenario includes: The daily behavior rules of the target smart device in a preset historical time period and under a preset scenario are obtained, wherein the preset scenario includes at least the target scenario; Based on the daily behavior rules under the preset scenario, the behavior rules of the target smart device under the target scenario are determined.

5. The method according to claim 4, characterized in that, The daily behavior rules of each smart device in the preset scenario are obtained through the following methods: If a behavioral event is detected in the preset scenario, determine whether the execution object of the behavioral event is a smart device in the preset scenario; If the execution object of the behavior event is determined to be a smart device in the preset scenario, the device behavior information corresponding to the behavior event is obtained; The device behavior information is stored in a preset database; In the absence of detected behavioral events, the device behavior information stored in the database is self-learned to obtain the daily behavior rules of each smart device in the preset scenario.

6. The method according to claim 1, characterized in that, The step of determining the linkage control strategy based on the behavior rules and the device capability set of each target smart device includes: Analyze the configuration requirements to determine the triggering conditions for each target smart device; Based on the triggering conditions and the set of capabilities of each target smart device, an initial linkage control strategy is determined; Based on the initial linkage control strategy and the behavior rules, a linkage control strategy is determined.

7. The method according to claim 6, characterized in that, The step of determining the linkage control strategy based on the initial linkage control strategy and the behavior rules includes: Based on the initial linkage control strategy and the behavior rules, at least one preset dimension of linkage control conditions is determined. The preset dimension includes one or more of the following: time dimension, device dimension, user dimension, triggering action, and execution action. The linkage control conditions are input into a preset linkage control strategy model to obtain the linkage control strategy.

8. The method according to claim 1, characterized in that, After determining the linkage control strategy based on the behavior rules and the device capability set of each target smart device, the method further includes: The linkage control strategy is output through a visual interface; Upon receiving a user's modification operation on the linkage control strategy, the modified target linkage control strategy is obtained; Update the linkage control strategy to the target linkage control strategy.

9. The method according to claim 1, characterized in that, The preset model is trained in the following way: Obtain a set of configuration requirement information samples, which includes multiple configuration requirement information samples, each of which corresponds to a standard scenario and standard configuration requirements; The preset initial model is trained using the configuration requirement information sample set to obtain the predicted scenario and predicted configuration requirement corresponding to each configuration requirement information sample output by the initial model. For each configuration requirement information sample, a first loss value is determined between the predicted scenario corresponding to the configuration requirement information sample and the corresponding standard scenario, and a second loss value is determined between the predicted configuration requirement corresponding to the configuration requirement information sample and the standard configuration requirement. Based on the first loss value and the second loss value corresponding to each configuration requirement information sample, determine whether the preset training stop condition is met. If the training stop condition is met, a pre-set model that has completed training is obtained.

10. A linkage control strategy generation device, characterized in that, The linkage control strategy generation device is applied in scenarios where multiple intelligent devices work together. The device includes: The receiving module is used to receive configuration requirement information; The parsing module is used to parse the configuration requirement information through a preset model. The configuration requirement information includes the target scenario and configuration requirements. The first determining module is used to determine a target smart device related to the configuration requirements from a set of device capabilities of multiple smart devices, and to determine the behavior rules of the target smart device in the target scenario; The second determining module is used to determine a linkage control strategy based on the behavior rules and the device capability set of each target smart device, so as to control the target smart device to achieve the configuration requirements in the target scenario according to the linkage control strategy.

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