Control method of smart device, storage medium, and electronic device

Abstract

The application discloses a control method and device of an intelligent device, a storage medium and an electronic device, relates to the technical field of smart home, and comprises the following steps: predicting parameter demand information of a target object to the intelligent device according to parameter preference information; selecting a plurality of target operating parameters meeting the parameter demand information from an initial parameter set to obtain a target parameter set; constructing a target parameter sequence corresponding to the target parameter set according to parameter switching information; and configuring a target control mode of the intelligent device by using the target parameter sequence. By using the technical solution, the problem of low control efficiency of the intelligent device in the related art is solved.

Description

Technical Field

[0001] This application relates to the field of smart home technology, and more specifically, to a control method, storage medium, and electronic device for a smart device. Background Technology

[0002] With the rapid development of smart home technology, smart home appliances (such as smart air conditioners, smart fans, and smart air purifiers) have been widely used in smart home scenarios. Taking smart air conditioners as an example, users usually need to adjust the device's operating parameters (such as fan speed, temperature, and airflow direction) according to the actual environment and their personal comfort to obtain a comfortable user experience.

[0003] Currently, mainstream smart devices primarily employ a preset enumeration of speed settings for parameter adjustment. For example, in air conditioner fan speed control, devices typically offer fixed speed settings such as "low, medium, high, and super strong," each corresponding to different operating parameters. Smart devices sequentially set these speed settings according to the operating parameters from low to high, allowing users to linearly increase or decrease them via remote control or voice commands. However, the speed switching order in the original linearly changing speed list of smart devices may differ from the user's actual needs. For instance, when adjusting fan speed, a user might expect to switch directly from speed setting 2 to speed setting 5. The current control method requires the user to manually adjust the speed settings multiple times to complete the parameter switch, severely impacting the user experience.

[0004] There is still no effective solution to the problem of low control efficiency of smart devices in related technologies. Summary of the Invention

[0005] This application provides a control method, storage medium, and electronic device for a smart device, which at least solves the problem of low control efficiency of smart devices in related technologies.

[0006] According to one embodiment of this application, a control method for a smart device is provided, comprising: predicting parameter requirement information of a target object for the smart device based on parameter preference information, wherein the parameter preference information is used to indicate the target object's usage preference for operating parameters on the smart device during a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirement for operating parameters on the smart device; filtering multiple target operating parameters that meet the parameter requirement information from an initial parameter set to obtain a target parameter set, wherein the initial parameter set records the operating parameters allowed to be used by the smart device, and the target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device; constructing a target parameter sequence corresponding to the target parameter set based on parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device during the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target operating parameters on the smart device; configuring a target control mode of the smart device using the target parameter sequence, wherein the smart device is used to execute parameter switching instructions initiated by the target object according to the target parameter sequence in the target control mode.

[0007] Optionally, constructing the target parameter sequence corresponding to the target parameter set based on the parameter switching information includes: for each first operating parameter in the target parameter set, determining a target switching probability between the first operating parameter and the second operating parameter based on the number of parameter switching between the first operating parameter and the second operating parameter, wherein the second operating parameter is an operating parameter in the target parameter set other than the first operating parameter, the parameter switching information includes the number of parameter switching, and the target switching probability is used to indicate the probability that the target object currently controls the smart device to switch from the first operating parameter to the second operating parameter; determining the second operating parameter whose target switching probability is greater than or equal to a preset probability threshold as a third operating parameter that has a parameter switching relationship with the first operating parameter; and generating the target parameter sequence based on the parameter switching relationship between each first operating parameter and the corresponding third operating parameter.

[0008] Optionally, generating the target parameter sequence based on the parameter switching relationship between each first operating parameter and the corresponding third operating parameter includes: sorting the operating parameters in the target parameter set according to the parameter switching relationship between all the first operating parameters and the corresponding third operating parameters to obtain an initial parameter sequence; determining a target sequence number interval in the initial parameter sequence based on multiple sequence usage information of the smart device, wherein the probability that the target object currently uses the operating parameters whose sorting sequence number in the initial parameter sequence is within the target sequence number interval is greater than or equal to the target probability, and the multiple sequence usage information is used to reflect the sequence number range of the operating parameters currently used by the target object in the initial parameter sequence from multiple dimensions; and determining the sub-parameter sequence whose sorting sequence number in the initial parameter sequence is within the target sequence number interval as the target parameter sequence.

[0009] Optionally, a target sequence number interval is determined in the initial parameter sequence based on multiple sequence usage information of the smart device, including: calculating the minimum sequence number of the target sequence number interval using the following formula: Order_min_final=w_room1 Order_min_room+w_habit1 Order_min_habit+w_voice1 Order_min_voice; where Order_min_final is the minimum sequence number in the target sequence number range, Order_min_room is the minimum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, the first parameter sequence is a parameter switching sequence configured according to the parameter switching order requirements of the rooms where the smart device is deployed, Order_min_habit is the minimum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, the second parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of the target object during the historical time period, Order_min_voice is the minimum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, the third parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of other objects during the historical time period, w_room1 is the weight parameter of Order_min_room, w_habit1 is the weight parameter of Order_min_habit, and w_voice1 is the weight parameter of Order_min_voice;

[0010] The maximum sequence number of the target sequence number interval is calculated using the following formula: Order_max_final = w_room2 Order_max_room+w_habit2 Order_max_habit+w_voice2 Order_max_voice; where Order_max_final is the maximum sequence number of the target sequence number interval, Order_max_room is the maximum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, Order_max_habit is the maximum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, Order_max_voice is the maximum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, w_room2 is the weight parameter of Order_max_room, w_habit2 is the weight parameter of Order_max_habit, and w_voice2 is the weight parameter of Order_max_voice.

[0011] Optionally, before determining the target sequence number range in the initial parameter sequence based on the multiple sequence usage information of the smart device, the method further includes: obtaining a reference parameter sequence used by the target object to control the device during the historical time period; determining a first sequence number of the operating parameter located in the middle of the reference parameter sequence in the reference parameter sequence; compensating a second sequence number with the first sequence number to obtain a third sequence number, wherein the second sequence number is the sequence number of the operating parameter located in the middle of the initial parameter sequence; taking the operating parameter corresponding to the third sequence number as the starting point in the initial parameter sequence and performing an upward offset step in the initial parameter sequence to obtain the maximum sequence number of the parameter used by the device during the historical time period in the second parameter sequence; taking the operating parameter corresponding to the third sequence number as the starting point in the initial parameter sequence and performing a downward offset step in the initial parameter sequence to obtain the minimum sequence number of the parameter used by the device during the historical time period in the second parameter sequence.

[0012] Optionally, predicting the target object's parameter requirements for the smart device based on parameter preference information includes: selecting multiple reference operating parameters from a reference parameter set whose usage frequency of the operating parameters in the reference parameter set is greater than or equal to the target usage frequency, and / or whose usage duration of the operating parameters in the reference parameter set is greater than or equal to the target duration. The reference parameter set includes operating parameters used by the target object within the historical time period. The parameter preference information includes the parameter usage frequency and usage duration of the operating parameters in the reference parameter set. The parameter requirement information includes multiple reference operating parameters, which are the operating parameters currently preferred by the target object.

[0013] Optionally, the step of selecting multiple target operating parameters that meet the parameter requirement information from the initial parameter set to obtain a target parameter set includes: calculating the intersection of the initial parameter set and multiple reference operating parameters to obtain the multiple target operating parameters, wherein the parameter requirement information includes the multiple reference operating parameters, and the reference operating parameters are the operating parameters currently preferred by the target object.

[0014] Optionally, after configuring the target control mode of the smart device using the target parameter sequence, the method further includes: obtaining a target switching instruction from the target object, wherein the target switching instruction is used to instruct the target object to request switching the operating parameters of the device according to the target control mode; responding to the target switching instruction, determining the reference position of the operating parameters currently used by the device in the target parameter sequence indicated by the target control mode, wherein the target parameter sequence is used to characterize the parameter switching order of the smart device in the target control mode; performing a sequence offset in the target parameter sequence with the reference position as the offset starting point according to the offset step size indicated by the switching instruction, to obtain candidate operating parameters; and controlling the device to operate according to the candidate operating parameters.

[0015] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer-readable storage medium, and the computer program is configured to execute the control method of the above-described smart device when running.

[0016] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the control method of the intelligent device through the computer program.

[0017] In this embodiment, the target object's current parameter requirements for the smart device are detected based on its historical usage preferences for operating parameters. This reflects the target object's current needs for operating parameters. A target parameter set is then generated based on the parameter requirements and an initial parameter set, ensuring that the operating parameters in the target parameter set are those preferred by the target object when controlling the smart device. This avoids unnecessary switching between operating parameters during control. Furthermore, a target parameter sequence is constructed based on parameter switching information, ensuring the order of operating parameters in the target parameter sequence satisfies the target object's parameter switching order requirements when controlling the smart device. This achieves the configuration of a target parameter sequence on the smart device that meets the target object's parameter switching needs based on its historical operating parameter usage data, preventing repeated switching between unnecessary operating parameters. By adopting the above technical solution, the problem of low control efficiency of smart devices in related technologies is solved, achieving a significant improvement in the technical effect of improving the control efficiency of smart devices. Attached Figure Description

[0018] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0019] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0020] Figure 1 This is a schematic diagram of the hardware environment of a control method for a smart device according to an embodiment of this application;

[0021] Figure 2 This is a flowchart of a control method for a smart device according to an embodiment of this application;

[0022] Figure 3 This is a schematic diagram of an optional parameter sequence configuration according to an embodiment of this application;

[0023] Figure 4 This is a structural block diagram of a control device for a smart device according to an embodiment of this application. Detailed Implementation

[0024] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0025] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0026] According to one aspect of the embodiments of this application, a control method for a smart device is provided. This method is widely applicable to whole-house intelligent digital control application scenarios such as smart homes, smart home ecosystems, and intelligencehouse ecosystems. Optionally, in this embodiment, the above method can be applied to, for example... Figure 1 The hardware environment shown consists of terminal device 102 and server 104. For example... Figure 1 As shown, server 104 is connected to terminal device 102 via a network and can be used to provide services (such as application services) to the terminal or clients installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for server 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data processing services for server 104.

[0027] The aforementioned network may include, but is not limited to, at least one of the following: wired network, wireless network. The aforementioned wired network may include, but is not limited to, at least one of the following: wide area network, metropolitan area network, local area network. The aforementioned wireless network may include, but is not limited to, at least one of the following: Wi-Fi (Wireless Fidelity), Bluetooth. The terminal device 102 may not be limited to PC, mobile phone, tablet computer, smart air conditioner, smart range hood, smart refrigerator, smart oven, smart stove, smart washing machine, smart water heater, smart washing equipment, smart dishwasher, smart projector, smart TV, smart clothes rack, smart curtains, smart audio-visual equipment, smart socket, smart speaker, smart speaker box, smart fresh air equipment, smart kitchen and bathroom equipment, smart bathroom equipment, smart robot vacuum cleaner, smart window cleaning robot, smart mopping robot, smart air purifier, smart steam oven, smart microwave oven, smart water heater, smart air purifier, smart water dispenser, smart door lock, etc.

[0028] This embodiment provides a control method for a smart device, applied to the aforementioned device terminal. Figure 2 This is a flowchart of a control method for a smart device according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0029] Step S202: Predict the parameter requirement information of the target object for the smart device based on the parameter preference information, wherein the parameter preference information is used to indicate the target object's usage preference for operating parameters on the smart device in a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirement for operating parameters on the smart device;

[0030] Step S204: Select multiple target operating parameters that meet the parameter requirement information from the initial parameter set to obtain the target operating parameters that the smart device is allowed to use. The initial parameter set records the operating parameters that the smart device is currently allowed to use. The target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device.

[0031] Step S206: Construct a target parameter sequence corresponding to the target parameter set based on the parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device within the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target running parameters on the smart device.

[0032] Step S208: Configure the target control mode of the smart device using the target parameter sequence, wherein the smart device is used to execute the parameter switching command initiated by the target object according to the target parameter sequence in the target control mode.

[0033] Through the above steps, the target object's current parameter requirements for the smart device are detected based on its historical usage preferences for operating parameters. This reflects the target object's current needs for the smart device's operating parameters. Then, a target parameter set is generated based on the parameter requirements and the initial parameter set. The operating parameters in the target parameter set are those preferred by the target object when controlling the smart device, thus avoiding unnecessary switching between operating parameters. Furthermore, a target parameter sequence is constructed based on parameter switching information, ensuring that the order of operating parameters in the target parameter sequence meets the target object's parameter switching requirements when controlling the smart device. This achieves the configuration of a target parameter sequence on the smart device that meets the target object's parameter switching needs based on its historical operating parameter usage data, avoiding repeated switching between unnecessary operating parameters. This technical solution solves the problem of low control efficiency of smart devices in related technologies, achieving a significant improvement in control efficiency.

[0034] In the technical solution provided in step S202 above, the operating parameters are parameters used to adjust the operating status of the air conditioner. The operating parameters may include, but are not limited to, wind speed, temperature, wind direction offset angle, etc. This solution does not limit these parameters.

[0035] Optionally, in this embodiment, the smart device is a device that has the function of adjusting the operating state according to the parameter change sequence. For example, the smart device can be an air conditioner (operating parameters include wind speed, temperature, wind direction offset angle, etc.), a fan (operating parameters include wind speed, wind direction offset angle, etc.), a smart speaker (operating parameters may be, but are not limited to, volume), etc. This application does not limit this.

[0036] Optionally, in this embodiment, the parameter preference information may include, but is not limited to, the frequency of use of each running parameter by the target object in a historical time period and the duration of use each time.

[0037] Optionally, in this embodiment, the parameter requirement information can be the usage characteristics of the target object's currently preferred operating parameters over a historical period. That is, the parameter requirement information is a quantitative representation of the usage characteristics of the target object's currently preferred operating parameters over a historical period. For example, the parameter requirement information may include, but is not limited to, the target usage duration or the target usage frequency. The method for detecting the parameter requirements of a target object for a smart device based on parameter preference information can be as follows: Detect the parameter usage duration of each parameter usage event within a historical time period. Here, a parameter usage event is used to instruct the target object to select a running parameter on the smart device and instruct the smart device to run according to that parameter. The parameter usage duration indicates the length of time the current running parameter is used within the parameter usage event. The parameter preference information includes the parameter usage duration corresponding to each parameter usage event among multiple parameter usage events. Target usage events whose parameter usage duration meets a preset duration condition are selected from the multiple parameter usage events. Multiple target usage events are classified according to running parameters, and the number of target usage events corresponding to each running parameter is counted to obtain a reference usage frequency for each running parameter. A target usage frequency is generated based on the reference usage frequencies of multiple running parameters, where the parameter requirement information includes the target usage frequency. Further, the method for generating a target parameter set based on parameter requirement information and an initial parameter set can be as follows: Extract running parameters whose usage frequency in the initial parameter set is greater than or equal to the target usage frequency within a historical time period, thereby obtaining the target parameter set.

[0038] The preset duration condition can be, but is not limited to, determined based on the target object's habit of switching operating parameters of the smart device within a historical event period. For example, it can be obtained by acquiring the initial duration between two adjacent parameter switching events of the target object within a historical time period; filtering candidate durations with durations greater than a preset threshold from multiple initial time intervals; averaging multiple candidate duration intervals to obtain the target duration; and configuring the preset duration condition according to the target duration, that is, when the usage duration of the operating parameters is greater than or equal to the target duration, the preset duration condition can be considered to be satisfied.

[0039] One method for generating a target usage frequency based on reference usage frequencies of multiple operating parameters is as follows: calculate the dispersion of each reference usage frequency among the multiple reference usage frequencies to obtain the target dispersion of each reference usage frequency. The target dispersion is used to indicate the degree of difference between the current reference usage frequency and other usage frequencies other than the current reference usage frequency among the multiple reference usage frequencies. The reference usage frequencies with a target dispersion less than a preset dispersion threshold are determined as the target usage frequencies.

[0040] In the technical solution provided in step S204 above, when the parameter requirement is used to indicate the target usage frequency of the preferred operating parameters of the target object in the historical time period, the operating parameters whose usage frequency of the operating parameters in the initial parameter set is greater than or equal to the target usage frequency of the target object in the historical time period are extracted to obtain the target parameter set.

[0041] Optionally, in this embodiment, the initial parameter set records the operating parameters that the smart device supports by default. The operating parameters in the initial parameter set are sorted in ascending order on the smart device to obtain the initial parameter sequence corresponding to the initial parameter set. When the smart device is running, it switches parameters by default according to the parameter switching order recorded in the initial parameter sequence, thereby switching parameters according to the current change order of the parameters.

[0042] Optionally, in this embodiment, the target parameter set may include, but is not limited to, some or all of the operating parameters in the initial parameter set. For example, when the target object is currently controlling the smart device, it may need to use all the operating parameters in the initial parameter set for control, but the target object has its own preferred parameter switching order for the operating parameters in the initial parameter set. Or, when the target object is currently controlling the smart device, it may only need some of the operating parameters in the initial parameter set. For example, if the initial parameter set includes seven operating parameters A, B, C, D, E, F, and G that increase sequentially, the target object may currently only need to use operating parameters A, D, and G.

[0043] In the technical solution provided in step S206 above, the sorting of the running parameters in the target parameter sequence is constructed according to the target object's current requirement for the parameter switching order in the target parameter set.

[0044] Optionally, in this embodiment, constructing the target parameter sequence corresponding to the target parameter set based on the parameter switching information includes: for each first operating parameter in the target parameter set, selecting a third operating parameter from multiple second operating parameters corresponding to the current first operating parameter based on the number of parameter switching between the first operating parameter and the second operating parameter, wherein the number of parameter switching is greater than or equal to a preset switching number threshold; and generating the target parameter sequence based on the parameter switching relationship between each first operating parameter and the corresponding third operating parameter.

[0045] In the technical solution provided in step S208 above, the intelligent device may, but is not limited to, be configured with an initial mode set. This initial mode set stores the control modes already possessed by the intelligent device, and the parameter switching methods recorded for different control modes are different. The control modes already possessed by the intelligent device stored in the initial mode set are used to implement the operating parameter switching methods already possessed by the intelligent device.

[0046] Optionally, in this embodiment of the application, after configuring the target control mode, the target control mode can be added to the initial mode set to obtain the target mode set. The control modes already possessed by the smart device stored in the initial mode set are used to implement the operating parameter switching methods already possessed by the smart device. Then, the smart device is used to execute the control command initiated by the target object using the target mode set. The control command is used to request control of the smart device to switch operating parameters.

[0047] As an optional embodiment, constructing the target parameter sequence corresponding to the target parameter set based on the parameter switching information includes:

[0048] For each first operating parameter in the target parameter set, a target switching probability between the first operating parameter and the second operating parameter is determined based on the number of parameter switching between the first operating parameter and the second operating parameter. The second operating parameter is an operating parameter in the target parameter set other than the first operating parameter. The parameter switching information includes the number of parameter switching. The target switching probability is used to indicate the probability that the target object currently controls the smart device to switch from the first operating parameter to the second operating parameter.

[0049] The second operating parameter whose target switching probability is greater than or equal to a preset probability threshold is determined as the third operating parameter that has a parameter switching relationship with the first operating parameter;

[0050] The target parameter sequence is generated based on the parameter switching relationship between each of the first operating parameters and the corresponding third operating parameters.

[0051] Optionally, in this embodiment, the method for determining the target switching probability between the first operating parameter and the second operating parameter based on the number of parameter switching between the first operating parameter and the second operating parameter can be to convert the target switching probability corresponding to the current number of parameter switching from the parameter switching count and switching probability that have a corresponding relationship.

[0052] Optionally, in this embodiment, the target switching probability corresponds one-to-one with the second operating parameter, that is, one second operating parameter corresponds to one target switching probability.

[0053] Optionally, in this embodiment, the parameter switching relationship is used to indicate the switching direction between operating parameters. For example, the parameter switching relationship between the first operating parameter and the third operating sub-parameter includes switching from the first operating parameter to the third operating parameter or switching from the third operating parameter to the first operating parameter.

[0054] In this embodiment, by using the number of parameter switching times between parameters of the target object within a historical event segment, the parameter switching relationship between parameters is detected. This enables the prediction of possible switching relationships during the use of the target object's operating parameters in the target parameter set based on the user's historical parameter habits. Subsequently, a target parameter sequence corresponding to the target parameter set is constructed according to the parameter switching relationship. This target parameter sequence better matches the user's actual switching order requirements for operating parameters on the smart device. When the user needs to switch operating parameters, they can switch to the operating parameters they actually need with the fewest parameter switching actions, thereby improving the user's efficiency in switching operating parameters.

[0055] As an optional embodiment, generating the target parameter sequence based on the parameter switching relationship between each first operating parameter and the corresponding third operating parameter includes:

[0056] The operating parameters in the target parameter set are sorted according to the parameter switching relationship between all the first operating parameters and the corresponding third operating parameters to obtain the initial parameter sequence;

[0057] Based on multiple sequence usage information of the smart device, a target sequence number range is determined in the initial parameter sequence, wherein the probability that the target object currently uses the running parameters whose sorting sequence number in the initial parameter sequence is within the target sequence number range is greater than or equal to the target probability, and the multiple sequence usage information is used to reflect the sequence number range of the running parameters currently used by the target object in the initial parameter sequence from multiple dimensions;

[0058] The sub-parameter sequence whose sorting index is within the target index range in the initial parameter sequence is determined as the target parameter sequence.

[0059] Optionally, in this embodiment, the multiple sequence usage information may include, but is not limited to, a sequence range based on room type, a sequence range based on historical habits, and a sequence range based on object type. The sequence range based on room type is the sequence range of room types corresponding to the current room obtained by clustering on the room type dimension. The sequence range based on historical habits is the sequence range obtained by clustering on the sequence usage range dimension of the target object. The sequence range based on object type is the sequence range obtained by clustering the sequence range of other object preferences with the same object type as the target object.

[0060] Optionally, in this embodiment, after filtering out the target parameter set and constructing the target parameter sequence based on the parameter usage information within the historical event segment of the target object, a small sequence range is further located for the target object from the target parameter sequence based on multi-dimensional sequence usage information. This achieves the goal of narrowing the parameter switching range of the user in the target parameter sequence based on multi-dimensional information used to characterize the user's habit of using the parameter range in the parameter sequence, further avoiding the user from repeatedly performing unnecessary parameter switching and reducing the number of parameter switching times during the use of smart devices.

[0061] As an optional embodiment, the target sequence number range is determined in the initial parameter sequence based on multiple sequence usage information of the smart device, including:

[0062] The minimum index of the target index range is calculated using the following formula:

[0063] Order_min_final=w_room1 Order_min_room+w_habit1 Order_min_habit+w_voice1 Order_min_voice;

[0064] Wherein, Order_min_final is the minimum sequence number of the target sequence number interval, Order_min_room is the minimum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, the first parameter sequence is a parameter switching sequence configured according to the parameter switching order requirements of the rooms where the smart device is deployed, Order_min_habit is the minimum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, the second parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of the target object during the historical time period, Order_min_voice is the minimum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, the third parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of other objects during the historical time period, w_room1 is the weight parameter of Order_min_room, w_habit1 is the weight parameter of Order_min_habit, and w_voice1 is the weight parameter of Order_min_voice.

[0065] The maximum index of the target index range is calculated using the following formula:

[0066] Order_max_final=w_room2 Order_max_room+w_habit2 Order_max_habit+w_voice2 Order_max_voice;

[0067] Wherein, Order_max_final is the maximum sequence number of the target sequence number interval, Order_max_room is the maximum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, Order_max_habit is the maximum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, Order_max_voice is the maximum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, w_room2 is the weight parameter of Order_max_room, w_habit2 is the weight parameter of Order_max_habit, and w_voice2 is the weight parameter of Order_max_voice.

[0068] This embodiment uses a comprehensive weighted adjustment of multi-dimensional sequence usage information to avoid the influence of a single dimension of the target object on the sequence range, making the narrowed target sequence range more in line with the user's actual usage needs.

[0069] As an optional embodiment, before determining the target sequence number range in the initial parameter sequence based on the multiple sequence usage information of the smart device, the method further includes:

[0070] Obtain the sequence of reference parameters used by the target object to control the device during the historical time period;

[0071] Determine the first index of the operating parameter located in the middle of the reference parameter sequence within the reference parameter sequence;

[0072] The first sequence number is used to compensate the second sequence number to obtain the third sequence number, wherein the second sequence number is the sequence number of the running parameter located in the middle position of the initial parameter sequence;

[0073] Starting from the operating parameter corresponding to the third sequence number in the initial parameter sequence, offset processing is performed according to the upward offset step size to obtain the maximum sequence number of the parameter used by the device in the second parameter sequence during the historical time period;

[0074] In the initial parameter sequence, the operating parameter corresponding to the third sequence number is used as the starting point, and the offset is performed according to the downward offset step size. The parameter used by the device during the historical time period is the smallest sequence number in the second parameter sequence.

[0075] Optionally, in this embodiment, the boundary range of the parameter index of the target object is updated by a dynamic update method based on the boundary range of the exponentially weighted moving average. First, the index of the middle position of the current sequence and the index of the middle position of the historical sequence are weighted based on the exponentially weighted moving average to obtain the index of the middle position after weighting, which is used as the center index of the target index interval currently used by the target object in the initial parameter sequence.

[0076] Optionally, in this embodiment, the upward offset step size can be a pre-set fixed offset compensation, or it can be dynamically determined according to the user's usage habits of parameter switching range. This solution does not limit this.

[0077] As an optional embodiment, the step of predicting the target object's parameter requirements for the smart device based on parameter preference information includes:

[0078] Multiple reference running parameters are selected from the reference parameter set if the frequency of use of the running parameters in the reference parameter set is greater than or equal to the target frequency of use, and / or the duration of use of the running parameters in the reference parameter set is greater than or equal to the target duration of use. The reference parameter set includes running parameters used by the target object within the historical time period. The parameter preference information includes the frequency of use of the running parameters in the reference parameter set and the duration of use of the running parameters in the reference parameter set. The parameter requirement information includes multiple reference running parameters, which are the running parameters currently preferred by the target object.

[0079] Through the above embodiments, by filtering the running parameters in the parameter set by the frequency and duration of their use, the target object's actual usage habits can be detected in the historical event segment's records of running parameters, thereby accurately reflecting the target object's actual usage needs for running parameters in the current event segment.

[0080] As an optional embodiment, the step of selecting multiple target operating parameters that meet the parameter requirement information from the initial parameter set to obtain a target parameter set includes:

[0081] The intersection of the initial parameter set and multiple reference operating parameters is calculated to obtain the multiple target operating parameters, wherein the parameter requirement information includes the multiple reference operating parameters, and the reference operating parameters are the operating parameters currently preferred by the target object.

[0082] By performing an intersection operation between the initial parameter set and multiple reference operating parameters, the influence of certain special operating parameters used by the target object on the target object's parameter usage requirement prediction results during the historical period (i.e., operating parameters not in the original initial parameter set, which are often user-defined operating parameters) can be avoided.

[0083] As an optional embodiment, after configuring the target control mode of the smart device using the target parameter sequence, the method further includes:

[0084] Obtain the target switching instruction of the target object, wherein the target switching instruction is used to instruct the target object to request to switch the operating parameters of the device according to the target control mode;

[0085] In response to the target switching command, the reference position of the operating parameters currently used by the device in the target parameter sequence indicated by the target control mode is determined, wherein the target parameter sequence is used to characterize the parameter switching order of the smart device in the target control mode;

[0086] According to the offset step size indicated by the switching instruction, the sequence offset is performed in the target parameter sequence with the reference position as the offset starting point to obtain the candidate running parameters;

[0087] Control the device to operate according to the candidate operating parameters.

[0088] This application aims to construct a user-centric, multi-dimensional perception-driven dynamic operating parameter adjustment system that automatically calculates and recommends the optimal user adjustment sequence for the operating parameters of smart devices, achieving: adaptive transformation of the operating parameter sequence based on user needs; and adaptive adjustment of the switching order of parameters in the operating parameter sequence based on user usage habits.

[0089] This application uses an air conditioning device as an example, with wind speed as the operating parameter. The original enumerated values ​​of the air conditioning wind speed are rearranged from weakest to strongest according to the actual perceived wind speed intensity, and each setting is assigned an adjustment sequence number (Order).

[0090] The default order of the original operating parameters (speed) of the air conditioner is: no fan speed: 0, high fan speed: 1, medium fan speed: 2, low fan speed: 3, light fan speed: 4, automatic: 5, fast fan speed: 6, medium-high fan speed: 7, medium-low fan speed: 8, silent fan speed: 9, super fan speed: 10.

[0091] Table 1 is a table of optional operating parameter sequences according to an embodiment of this application, as shown in Table 1:

[0092] Table 1

[0093]

[0094] As shown in Table 1, the original values ​​correspond to the air conditioner's original fan speed settings. Users sort these settings according to their perceived intensity, resulting in the following order: Silent, Light, Low, Medium, Low-Medium, Medium-High, High, Fast, and Extra Strong. Therefore, when users need to switch operating parameters based on their perceived intensity, they can do so in the order recorded in this sequence.

[0095] In actual use, the parameter mapping method is as follows: given the original wind speed value raw, its adjustment order can be found as order=map_raw_to_order[raw]. During adjustment, order is added or subtracted, and then mapped back to the raw value and sent to the air conditioner.

[0096] Furthermore, this application dynamically adjusts the adjustable range in the parameter sequence.

[0097] The system maintains an adjustable wind speed range independently for each (user, room) pair, represented as the interval [order_min, order_max] for the adjustment order.

[0098] Dynamic adjustment based on historical habits: dynamic boundary updates based on exponentially weighted moving average (EWMA).

[0099] The system records the final fan speed setting the user maintains after each adjustment (i.e., the ending setting of the adjustment session). Let x_t be the adjustment sequence corresponding to the setting after the t-th adjustment. The system maintains an implicit state variable, the current comfort center point μ_t, whose update formula is as follows:

[0100] μ_t=α x_t+(1-α) μ_{t-1};

[0101] Where: μ_t is the estimated center value of user comfort preference after the t-th adjustment (adjustment order unit). α is a smoothing factor (0 < α < 1), for example, α = 0.3 is taken to balance the weights of historical preferences and new behaviors.

[0102] x_t is the adjustment sequence of the t-th actual dwell time.

[0103] μ_{t-1} is the comfort center value after the last adjustment.

[0104] Boundary calculation formula:

[0105] order_min_t=max(ORDER_GLOBAL_MIN,floor(μ_t-ΔL));

[0106] order_max_t=min(ORDER_GLOBAL_MAX,ceil(μ_t+ΔU));

[0107] in:

[0108] ΔL and ΔU are constant parameters that are pre-set based on human comfort experimental data.

[0109] ΔL and ΔU are preset downward and upward offset step sizes. For example, ΔL=2 and ΔU=3 indicate that the user's acceptable comfort range is generally lower for downward (weak wind) and slightly higher for upward (strong wind).

[0110] As an optional extension, Table 2 is an optional ΔL and ΔU configuration table according to an embodiment of this application, and the values ​​of ΔL and ΔU in different rooms are shown in Table 2.

[0111]

[0112] The floor and ceil functions ensure that the boundaries are integers.

[0113] The max and min functions ensure that the boundaries do not exceed the global maximum and minimum values.

[0114] Boundary contraction / expansion rules:

[0115] Statistics show the distribution of fan speed settings used by users in this room over the past 30 days.

[0116] Take the adjustment order corresponding to the 5th percentile as the new order_min (excluding the rarely used weak wind setting).

[0117] Take the adjustment order corresponding to the 95th percentile as the new order_max (excluding the rarely used strong wind setting).

[0118] At the same time, ensure that the interval length is at least 3 (at least 3 adjustable levels).

[0119] Example (living room historical data):

[0120] The user never used the silent wind (1), light wind (2), or medium-low wind (5).

[0121] Commonly used winds include low wind (3), medium wind (4), medium-high wind (6), high wind (7), fast wind (8), and occasionally super strong wind (9).

[0122] Dynamically calculated range: [3, 9] (low wind to very strong wind).

[0123] Voiceprint-based identity recognition:

[0124] When a user issues a "turn up the wind speed" command via voice, the system first extracts the voiceprint features.

[0125] Match the existing voiceprint database to identify the current user ID (such as "child" or "dad").

[0126] If it cannot be identified (such as a visitor), the room's default general scope will be used.

[0127] Comprehensive weighted recommendation range:

[0128] When multiple information sources exist, weighted fusion is used to determine the final scope:

[0129] Order_min_final=w_room Order_min_room+w_habit Order_min_habit+w_voice Order_min_voice;

[0130] Order_max_final=w_room Order_max_room+w_habit Order_max_habit+w_voice Order_max_voice;

[0131] The weights satisfy w_room+w_habit+w_voice=1.

[0132] (Order_min_room, Order_max_room): Prior range based on room type.

[0133] (Order_min_habit, Order_max_habit): Dynamic range based on historical habits.

[0134] (Order_min_voice, Order_max_voice): Preset range of groups based on voiceprint recognition. (e.g., the range for "elderly" is [2,5], and the range for "children" is [1,4]).

[0135] w_room, w_habit, w_voice: Configurable weighting coefficients.

[0136] Weight example:

[0137] Historical habit weight w2 = 0.6;

[0138] Room type weight w1 = 0.3;

[0139] The default weight for voiceprint groups is w3=0.1.

[0140] Wind speed adjustment execution logic:

[0141] Examples of user voice commands: "Turn it up a bit" / "Turn the wind speed up"; "Turn it down a bit" / "Turn the wind speed down".

[0142] Execution process:

[0143] Get the current actual fan speed setting of the air conditioner, current_raw.

[0144] The current physical order is obtained through ordered mapping: current_order = map_raw_to_order[current_raw].

[0145] Find the user's personalized range [order_min, order_max] based on voiceprint + room.

[0146] If the instruction is "increase":

[0147] New order = min(current_order + 1, order_max);

[0148] If the instruction is "lower":

[0149] New order = max(current_order-1, order_min);

[0150] Reverse mapping: new_raw = map_order_to_raw[new order];

[0151] Send new_raw to the air conditioner for execution.

[0152] Voice feedback: "Wind speed has been increased to super strong wind" or "It is already the lowest wind speed".

[0153] Boundary handling:

[0154] When the minimum wind speed (order_min) is reached, reply with "This is the lowest wind speed you usually use".

[0155] When order_max has been reached, reply with "This is already the highest wind speed you usually use".

[0156] Figure 3 This is a schematic diagram of an optional parameter sequence configuration according to an embodiment of this application, such as... Figure 3 As shown, the smart device is configured with a mode set, which stores the control modes that the smart device already possesses. Different control modes are used to implement the switching methods of the operating parameters that the smart device already has, and the parameter switching order indicated by different operating modes is different. Further, before the target object initiates control of the smart device, the smart device obtains the target object's parameter preference information and parameter requirement information within a historical event period. Based on the parameter preference information, it detects the target object's parameter requirement information and generates a target parameter set for the target object based on the parameter requirement information and the smart device's initial parameter set. Then, based on the parameter switching information, it constructs the target parameter sequence corresponding to the target parameter set, thereby obtaining the switching order of the operating parameters required by the target object on the smart device, and uses the target parameter sequence to configure the target control mode for the target object on the smart device. After configuring the target control mode, the smart device adds the target control mode to its mode set. Then, after the smart device receives the control command from the target object, it retrieves the target control mode corresponding to the target object from the mode set and switches the operating parameters according to the parameter switching order indicated by the target control mode.

[0157] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0158] Figure 4 This is a structural block diagram of a control device for a smart device according to an embodiment of this application; as shown below. Figure 4 As shown, it includes:

[0159] The prediction module is used to predict the parameter requirements of a target object for a smart device based on parameter preference information. The parameter preference information is used to indicate the target object's usage preferences for operating parameters on the smart device during a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirements for operating parameters on the smart device.

[0160] A filtering module is used to filter out multiple target operating parameters that meet the parameter requirement information from the initial parameter set, wherein the initial parameter set records the operating parameters allowed to be used by the smart device, and the target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device;

[0161] A construction module is used to construct a target parameter sequence corresponding to the target parameter set based on parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device within the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target running parameters on the smart device.

[0162] A configuration module is used to configure a target control mode of the smart device using the target parameter sequence, wherein the smart device is used to execute a parameter switching instruction initiated by the target object according to the target parameter sequence in the target control mode.

[0163] Through the above embodiments, the target object's current parameter requirements for the smart device are detected based on its historical usage preferences for operating parameters. This reflects the target object's current needs for the smart device's operating parameters. Then, a target parameter set is generated based on the parameter requirements and the initial parameter set. The operating parameters in the target parameter set are those preferred by the target object when controlling the smart device, thus avoiding unnecessary switching between operating parameters. Furthermore, a target parameter sequence is constructed based on parameter switching information, ensuring that the order of operating parameters in the target parameter sequence meets the target object's parameter switching order requirements when controlling the smart device. This achieves the configuration of a target parameter sequence on the smart device that meets the target object's parameter switching needs based on its historical operating parameter usage data, avoiding repeated switching between unnecessary operating parameters. By adopting the above technical solution, the problem of low control efficiency of smart devices in related technologies is solved, achieving a significant improvement in the technical effect of improving the control efficiency of smart devices.

[0164] Optionally, the building module includes:

[0165] The first determining unit is configured to, for each first operating parameter in the target parameter set, determine a target switching probability between the first operating parameter and the second operating parameter based on the number of parameter switching between the first operating parameter and the second operating parameter, wherein the second operating parameter is an operating parameter in the target parameter set other than the first operating parameter, the parameter switching information includes the number of parameter switching, and the target switching probability is used to indicate the probability that the target object currently controls the smart device to switch from the first operating parameter to the second operating parameter;

[0166] The second determining unit is used to determine the second operating parameter whose target switching probability is greater than or equal to a preset probability threshold as a third operating parameter that has a parameter switching relationship with the first operating parameter;

[0167] The generation unit is used to generate the target parameter sequence based on the parameter switching relationship between each of the first operating parameters and the corresponding third operating parameters.

[0168] Optionally, the generation unit is used for:

[0169] The operating parameters in the target parameter set are sorted according to the parameter switching relationship between all the first operating parameters and the corresponding third operating parameters to obtain the initial parameter sequence;

[0170] Based on multiple sequence usage information of the smart device, a target sequence number range is determined in the initial parameter sequence, wherein the probability that the target object currently uses the running parameters whose sorting sequence number in the initial parameter sequence is within the target sequence number range is greater than or equal to the target probability, and the multiple sequence usage information is used to reflect the sequence number range of the running parameters currently used by the target object in the initial parameter sequence from multiple dimensions;

[0171] The sub-parameter sequence whose sorting index is within the target index range in the initial parameter sequence is determined as the target parameter sequence.

[0172] Optionally, the generation unit is used for:

[0173] The minimum index of the target index range is calculated using the following formula:

[0174] Order_min_final=w_room1 Order_min_room+w_habit1 Order_min_habit+w_voice1 Order_min_voice;

[0175] Wherein, Order_min_final is the minimum sequence number of the target sequence number interval, Order_min_room is the minimum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, the first parameter sequence is a parameter switching sequence configured according to the parameter switching order requirements of the rooms where the smart device is deployed, Order_min_habit is the minimum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, the second parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of the target object during the historical time period, Order_min_voice is the minimum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, the third parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of other objects during the historical time period, w_room1 is the weight parameter of Order_min_room, w_habit1 is the weight parameter of Order_min_habit, and w_voice1 is the weight parameter of Order_min_voice.

[0176] The maximum index of the target index range is calculated using the following formula:

[0177] Order_max_final=w_room2 Order_max_room+w_habit2 Order_max_habit+w_voice2 Order_max_voice;

[0178] Wherein, Order_max_final is the maximum sequence number of the target sequence number interval, Order_max_room is the maximum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, Order_max_habit is the maximum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, Order_max_voice is the maximum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, w_room2 is the weight parameter of Order_max_room, w_habit2 is the weight parameter of Order_max_habit, and w_voice2 is the weight parameter of Order_max_voice.

[0179] Optionally, the device further includes:

[0180] The first acquisition module is used to acquire the reference parameter sequence used by the target object to control the device in the historical time period before determining the target sequence interval in the initial parameter sequence based on the multiple sequence usage information of the smart device.

[0181] The first determining module is used to determine the first sequence number of the operating parameter located in the middle of the reference parameter sequence in the reference parameter sequence;

[0182] The compensation module is used to compensate the second number using the first number to obtain the third number, wherein the second number is the number of the running parameter located in the middle of the initial parameter sequence;

[0183] The first offset module is used to offset the operating parameter corresponding to the third sequence number in the initial parameter sequence according to the upward offset step size, so as to obtain the maximum sequence number of the parameter used by the device in the historical time period in the second parameter sequence.

[0184] The second offset module is used to offset the operating parameter corresponding to the third sequence number in the initial parameter sequence according to the downward offset step size, wherein the parameter used by the device during the historical time period is the smallest sequence number in the second parameter sequence.

[0185] Optionally, the prediction module includes:

[0186] A filtering unit is configured to filter from a set of reference parameters multiple reference operating parameters whose usage frequency of the operating parameters in the set of reference parameters is greater than or equal to the target usage frequency, and / or whose usage duration of the operating parameters in the set of reference parameters is greater than or equal to the target duration. The set of reference parameters includes operating parameters used by the target object within the historical time period. The parameter preference information includes the parameter usage frequency and usage duration of the operating parameters in the set of reference parameters. The parameter requirement information includes multiple reference operating parameters, which are the operating parameters currently preferred by the target object.

[0187] Optionally, the filtering module includes:

[0188] A calculation unit is used to calculate the intersection of the initial parameter set and multiple reference operating parameters to obtain the multiple target operating parameters, wherein the parameter requirement information includes the multiple reference operating parameters, and the reference operating parameters are the operating parameters currently preferred by the target object.

[0189] Optionally, the device further includes:

[0190] The second acquisition module is used to acquire a target switching instruction of the target object after configuring the target control mode of the smart device using the target parameter sequence, wherein the target switching instruction is used to instruct the target object to request to switch the operating parameters of the device according to the target control mode;

[0191] The second determining module is used to respond to the target switching command and determine the reference position of the operating parameters currently used by the device in the target parameter sequence indicated by the target control mode, wherein the target parameter sequence is used to characterize the parameter switching order of the smart device in the target control mode;

[0192] The offset module is used to perform sequence offset in the target parameter sequence with the reference position as the offset starting point according to the offset step size indicated by the switching instruction, so as to obtain candidate running parameters;

[0193] The control module is used to control the device to operate according to the candidate operating parameters.

[0194] Embodiments of this application also provide a storage medium including a stored program, wherein the program, when executed, performs the control method of the smart device described above.

[0195] Optionally, in this embodiment, the storage medium may be configured to store program code for performing the following steps:

[0196] Predict the parameter requirements of a target object for a smart device based on parameter preference information, wherein the parameter preference information is used to indicate the target object's usage preferences for operating parameters on the smart device during a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirements for operating parameters on the smart device;

[0197] Multiple target operating parameters that meet the parameter requirements are selected from the initial parameter set to obtain a target parameter set. The initial parameter set records the operating parameters that the smart device is allowed to use, and the target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device.

[0198] Construct a target parameter sequence corresponding to the target parameter set based on parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device within the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target running parameters on the smart device.

[0199] The target control mode of the smart device is configured using the target parameter sequence, wherein the smart device is used to execute the parameter switching instruction initiated by the target object according to the target parameter sequence in the target control mode.

[0200] Embodiments of this application also provide an electronic device, including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above-described embodiments of the control method for a smart device.

[0201] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0202] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0203] Predict the parameter requirements of a target object for a smart device based on parameter preference information, wherein the parameter preference information is used to indicate the target object's usage preferences for operating parameters on the smart device during a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirements for operating parameters on the smart device;

[0204] Multiple target operating parameters that meet the parameter requirements are selected from the initial parameter set to obtain a target parameter set. The initial parameter set records the operating parameters that the smart device is allowed to use, and the target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device.

[0205] Construct a target parameter sequence corresponding to the target parameter set based on parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device within the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target running parameters on the smart device.

[0206] The target control mode of the smart device is configured using the target parameter sequence, wherein the smart device is used to execute the parameter switching instruction initiated by the target object according to the target parameter sequence in the target control mode.

[0207] Optionally, in this embodiment, the storage medium may include, but is not limited to, various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0208] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0209] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0210] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A control method for an intelligent device, characterized in that, include: Predict the parameter requirements of a target object for a smart device based on parameter preference information, wherein the parameter preference information is used to indicate the target object's usage preferences for operating parameters on the smart device during a historical time period, and the parameter requirement information is used to indicate the target object's current usage requirements for operating parameters on the smart device; Multiple target operating parameters that meet the parameter requirements are selected from the initial parameter set to obtain a target parameter set. The initial parameter set records the operating parameters that the smart device is allowed to use, and the target parameter set includes the target operating parameters that the target object currently prefers to use on the smart device. Construct a target parameter sequence corresponding to the target parameter set based on parameter switching information, wherein the parameter switching information is used to indicate the parameter switching operation performed by the target object on the smart device within the historical time period, and the target parameter sequence is used to indicate the switching order required by the target object for the target running parameters on the smart device. The target control mode of the smart device is configured using the target parameter sequence, wherein the smart device is used to execute the parameter switching instruction initiated by the target object according to the target parameter sequence in the target control mode.

2. The method according to claim 1, characterized in that, The step of constructing the target parameter sequence corresponding to the target parameter set based on the parameter switching information includes: For each first operating parameter in the target parameter set, a target switching probability between the first operating parameter and the second operating parameter is determined based on the number of parameter switching between the first operating parameter and the second operating parameter. The second operating parameter is an operating parameter in the target parameter set other than the first operating parameter. The parameter switching information includes the number of parameter switching. The target switching probability is used to indicate the probability that the target object currently controls the smart device to switch from the first operating parameter to the second operating parameter. The second operating parameter whose target switching probability is greater than or equal to a preset probability threshold is determined as the third operating parameter that has a parameter switching relationship with the first operating parameter; The target parameter sequence is generated based on the parameter switching relationship between each of the first operating parameters and the corresponding third operating parameters.

3. The method according to claim 2, characterized in that, The step of generating the target parameter sequence based on the parameter switching relationship between each first operating parameter and the corresponding third operating parameter includes: The operating parameters in the target parameter set are sorted according to the parameter switching relationship between all the first operating parameters and the corresponding third operating parameters to obtain the initial parameter sequence; Based on multiple sequence usage information of the smart device, a target sequence number range is determined in the initial parameter sequence, wherein the probability that the target object currently uses the running parameters whose sorting sequence number in the initial parameter sequence is within the target sequence number range is greater than or equal to the target probability, and the multiple sequence usage information is used to reflect the sequence number range of the running parameters currently used by the target object in the initial parameter sequence from multiple dimensions; The sub-parameter sequence whose sorting index is located within the target index interval in the initial parameter sequence is determined as the target parameter sequence.

4. The method according to claim 3, characterized in that, Based on multiple sequence usage information of the smart device, a target sequence number range is determined in the initial parameter sequence, including: The minimum index of the target index range is calculated using the following formula: Order_min_final=w_room1 Order_min_room+w_habit1 Order_min_habit+w_voice1 Order_min_voice; Wherein, Order_min_final is the minimum sequence number of the target sequence number interval, Order_min_room is the minimum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, the first parameter sequence is a parameter switching sequence configured according to the parameter switching order requirements of the rooms where the smart device is deployed, Order_min_habit is the minimum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, the second parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of the target object during the historical time period, Order_min_voice is the minimum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, the third parameter sequence is a parameter switching sequence configured according to the operating parameter switching requirements of other objects during the historical time period, w_room1 is the weight parameter of Order_min_room, w_habit1 is the weight parameter of Order_min_habit, and w_voice1 is the weight parameter of Order_min_voice. The maximum index of the target index range is calculated using the following formula: Order_max_final=w_room2 Order_max_room+w_habit2 Order_max_habit+w_voice2 Order_max_voice; Wherein, Order_max_final is the maximum sequence number of the target sequence number interval, Order_max_room is the maximum sequence number of the parameter used by the smart device in the first parameter sequence during the historical time period, Order_max_habit is the maximum sequence number of the parameter used by the smart device in the second parameter sequence during the historical time period, Order_max_voice is the maximum sequence number of the parameter used by the smart device in the third parameter sequence during the historical time period, w_room2 is the weight parameter of Order_max_room, w_habit2 is the weight parameter of Order_max_habit, and w_voice2 is the weight parameter of Order_max_voice.

5. The method according to claim 4, characterized in that, Before determining the target sequence number range in the initial parameter sequence based on multiple sequence usage information of the smart device, the method further includes: Obtain the sequence of reference parameters used by the target object to control the device during the historical time period; Determine the first index of the operating parameter located in the middle of the reference parameter sequence within the reference parameter sequence; The first sequence number is used to compensate the second sequence number to obtain the third sequence number, wherein the second sequence number is the sequence number of the running parameter located in the middle position of the initial parameter sequence; Starting from the operating parameter corresponding to the third sequence number in the initial parameter sequence, offset processing is performed according to the upward offset step size to obtain the maximum sequence number of the parameter used by the device in the second parameter sequence during the historical time period; In the initial parameter sequence, the operating parameter corresponding to the third sequence number is used as the starting point, and the offset is performed according to the downward offset step size. The parameter used by the device during the historical time period is the smallest sequence number in the second parameter sequence.

6. The method according to claim 1, characterized in that, The step of predicting the target object's parameter requirements for smart devices based on parameter preference information includes: Multiple reference running parameters are selected from the reference parameter set if the frequency of use of the running parameters in the reference parameter set is greater than or equal to the target frequency of use, and / or the duration of use of the running parameters in the reference parameter set is greater than or equal to the target duration of use. The reference parameter set includes running parameters used by the target object within the historical time period. The parameter preference information includes the frequency of use of the running parameters in the reference parameter set and the duration of use of the running parameters in the reference parameter set. The parameter requirement information includes multiple reference running parameters, which are the running parameters currently preferred by the target object.

7. The method according to claim 1, characterized in that, The process of selecting multiple target operating parameters that meet the parameter requirement information from the initial parameter set yields a target parameter set, including: The intersection of the initial parameter set and multiple reference operating parameters is calculated to obtain the multiple target operating parameters, wherein the parameter requirement information includes the multiple reference operating parameters, and the reference operating parameters are the operating parameters currently preferred by the target object.

8. The method according to claim 1, characterized in that, After configuring the target control mode of the smart device using the target parameter sequence, the method further includes: Obtain the target switching instruction of the target object, wherein the target switching instruction is used to instruct the target object to request to switch the operating parameters of the device according to the target control mode; In response to the target switching command, the reference position of the operating parameters currently used by the device in the target parameter sequence indicated by the target control mode is determined, wherein the target parameter sequence is used to characterize the parameter switching order of the smart device in the target control mode; According to the offset step size indicated by the switching instruction, the sequence offset is performed in the target parameter sequence with the reference position as the offset starting point to obtain the candidate running parameters; Control the device to operate according to the candidate operating parameters.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein the program, when executed, performs the method of any one of claims 1 to 8.

10. An electronic device comprising a memory and a processor, characterized in that, The memory stores a computer program, and the processor is configured to execute the method of any one of claims 1 to 8 through the computer program.

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