CN113531818B - Running mode pushing method and device for air conditioner and air conditioner - Google Patents
Running mode pushing method and device for air conditioner and air conditioner Download PDFInfo
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- CN113531818B CN113531818B CN202110686217.2A CN202110686217A CN113531818B CN 113531818 B CN113531818 B CN 113531818B CN 202110686217 A CN202110686217 A CN 202110686217A CN 113531818 B CN113531818 B CN 113531818B
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/64—Electronic processing using pre-stored data
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- F—MECHANICAL ENGINEERING; LIGHTING; HEATING; WEAPONS; BLASTING
- F24—HEATING; RANGES; VENTILATING
- F24F—AIR-CONDITIONING; AIR-HUMIDIFICATION; VENTILATION; USE OF AIR CURRENTS FOR SCREENING
- F24F11/00—Control or safety arrangements
- F24F11/62—Control or safety arrangements characterised by the type of control or by internal processing, e.g. using fuzzy logic, adaptive control or estimation of values
- F24F11/63—Electronic processing
- F24F11/65—Electronic processing for selecting an operating mode
Abstract
The application relates to the technical field of intelligent household appliances and discloses an operation mode pushing method for an air conditioner. The method comprises the following steps: in response to a starting instruction, determining a target user and a preference model for air conditioner control corresponding to the target user; determining an air conditioner target operation mode corresponding to the current moment, and adjusting operation parameters of the air conditioner target operation mode according to the preference model; and pushing the adjusted operating parameters to a target user so that the target user can use the operating parameters when the air conditioner is set. So, through the use habit and the regulation preference of study air conditioner user in the use, carry out the propelling movement of air conditioner operational mode automatically to create the comfortable living environment who is fit for the user, and solved the problem of user frequent operation, effectively improve the convenience of air conditioner operation, further improved user's experience. The application also discloses an operation mode pushing device for the air conditioner and the air conditioner.
Description
Technical Field
The application relates to the technical field of intelligent household appliances, in particular to an air conditioner and an operation mode pushing method and device for the same.
Background
At present, the air conditioner basically belongs to essential electric appliances for family life. The main operation mode of the air conditioner is to control the operation of each mode of the air conditioner according to a control instruction sent by a user, such as the modes of heating, refrigerating or dehumidifying and the like according to the instruction.
With the improvement of the intelligent degree of the household appliance, part of the air conditioners can adapt to the use habits of users through autonomous learning, for example, the common operation mode or temperature setting scheme after the household appliance is started can be learned within a period of time, the operation mode corresponding to the user is formed, and when the user starts the air conditioner, the air conditioner can operate according to the operation mode.
In the process of implementing the embodiments of the present disclosure, it is found that at least the following problems exist in the related art: when the air conditioner runs in the running mode corresponding to the user, the running mode is generated only according to the running scheme with higher running frequency in the use record, but the running mode cannot be adjusted according to the parameter preference of the user to the indoor environment, and the comfort level is reduced.
Disclosure of Invention
The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosed embodiments. This summary is not an extensive overview nor is intended to identify key/critical elements or to delineate the scope of such embodiments but rather as a prelude to the more detailed description that is presented later.
The embodiment of the disclosure provides an operation mode pushing method and device for an air conditioner and the air conditioner, and aims to solve the technical problem that when an operation scheme with high operation frequency is pushed according to a use record of a user, the operation mode cannot be adjusted according to the parameter preference of the user to an indoor environment, and the comfort level is reduced.
In some embodiments, the operation mode push method for an air conditioner includes: in response to a starting instruction, determining a target user and a preference model for air conditioner control corresponding to the target user; determining an air conditioner target operation mode corresponding to the current moment, and adjusting operation parameters of the air conditioner target operation mode according to the preference model; and pushing the adjusted operation parameters to the target user for the target user to use when the target user sets the air conditioner.
In some embodiments, the operation mode push device for an air conditioner includes: a processor and a memory storing program instructions, the processor being configured to execute the above-described operation mode push method for an air conditioner when executing the program instructions.
In some embodiments, the air conditioner includes the operation mode pushing device for the air conditioner.
The operation mode pushing method and device for the air conditioner and the air conditioner provided by the embodiment of the disclosure can achieve the following technical effects:
when a starting instruction is received, the target operation mode of the air conditioner corresponding to the starting setting habit of the target user at the current moment is determined, and the operation parameters in the target operation mode are adjusted according to the preference model of the target user for controlling the air conditioner, so that the operation mode of the air conditioner which best accords with the use habit of the user at the current moment and under the indoor environment condition is obtained and pushed to the user. So, through learning user's use habit and regulation preference in the air conditioner use, carry out the propelling movement of air conditioner operational mode automatically to create the comfortable living environment who is fit for the user, and solved the problem of user's frequent operation, effectively improve the convenience of air conditioner operation, further improved user's experience.
The foregoing general description and the following description are exemplary and explanatory only and are not restrictive of the application.
Drawings
One or more embodiments are illustrated by way of example in the accompanying drawings, which correspond to the accompanying drawings and not in limitation thereof, in which elements having the same reference numeral designations are shown as like elements and not in limitation thereof, and wherein:
fig. 1 is a schematic system environment diagram of an operation mode push method for an air conditioner according to an embodiment of the present disclosure;
fig. 2 is a schematic flowchart of an operation mode pushing method for an air conditioner according to an embodiment of the present disclosure;
fig. 3 is a schematic flowchart of another operation mode pushing method for an air conditioner according to an embodiment of the present disclosure;
fig. 4 is a schematic device diagram of an operation mode pushing device for an air conditioner according to an embodiment of the present disclosure.
Detailed Description
So that the manner in which the features and elements of the disclosed embodiments can be understood in detail, a more particular description of the disclosed embodiments, briefly summarized above, may be had by reference to the embodiments, some of which are illustrated in the appended drawings. In the following description of the technology, for purposes of explanation, numerous details are set forth in order to provide a thorough understanding of the disclosed embodiments. However, one or more embodiments may be practiced without these details. In other instances, well-known structures and devices may be shown in simplified form in order to simplify the drawing.
Fig. 1 is a system environment schematic diagram of an operation mode pushing method for an air conditioner according to an embodiment of the present disclosure. The implementation environment comprises an air conditioner 11, a wireless router 12, a terminal device 13 and a home cloud platform 14.
The air conditioner 11 is used for adjusting indoor air in a home scene. The air conditioner 11 can access a WiFi network in a home through the wireless router 12 to communicate with the terminal device 13, or access the home cloud platform 14 to receive an operation instruction. The user may also control the air conditioner 11 to automatically perform an air conditioning operation through an application program in the terminal device 13.
And the terminal equipment 13 is used for communicating with the air conditioner 11 and the home cloud platform 14. Here, the terminal device refers to a smart device in a smart home application scenario, such as a smart phone, a wearable device, a smart mobile device, a virtual display device, and the like, and may also be a smart home appliance, such as a smart refrigerator, a smart television, a smart washing machine, an air conditioner, a smart speaker, a smart lamp, a smart curtain, and the like, or any combination thereof.
And the home cloud platform 14 is used for realizing communication between the wireless router 12 and the outside, receiving air conditioner real-time state data for subscribing the big data platform and the application program service, and receiving and issuing air conditioner regulation and control instructions from other service servers, the big data platform and the application program terminal.
Optionally, the implementation environment further includes a big data platform 15, configured to receive real-time data subscribed at the home cloud platform, so as to perform calculation and instruction issue of a real-time service. In the big data platform 15, the mass data acquired by the big data platform is stored in a bottom database for data statistics and presentation and service analysis.
Fig. 2 is a schematic diagram of an operation mode pushing method for an air conditioner according to an embodiment of the present disclosure. The operation mode pushing method for the air conditioner is applied to the environment shown in fig. 1, can be executed in the air conditioner shown in fig. 1, and can also be executed in a control terminal of the air conditioner, such as a remote controller or an operation panel on a wall of a room; the method can also be executed in a server, such as a home cloud platform communicating with an air conditioner; the method can also be executed in terminal equipment, such as a control terminal of a smart phone, a smart household appliance or a smart home system. In the embodiments of the present disclosure, the scheme is explained with an air conditioner as an execution subject.
Referring to fig. 2, the method for pushing the operation mode of the air conditioner includes:
in step S21, in response to the power-on instruction, the air conditioner determines a target user and a preference model for air conditioner control corresponding to the target user.
Here, the starting instruction may be an instruction issued by a user, or an instruction issued when the intelligent air conditioner determines that the intelligent air conditioner is suitable for operation.
In some application scenarios, the intelligent air conditioner may obtain the start-up instruction according to a voice instruction of a user. Or obtaining the starting-up instruction through the operation intention of the user, such as: keys, touch screen, knobs, set gestures, etc. The intelligent air conditioner can also obtain a starting instruction issued by a user through an application program of the intelligent mobile phone through communication with the intelligent mobile phone.
In other application scenarios, a startup program operation information table is stored in the intelligent air conditioner, and when the operation condition is met, the intelligent air conditioner acquires the startup instruction. Here, the operation condition may be related to a difference between the current ambient temperature and the set temperature, or may be related to the number of indoor users.
The target user can be the user who issues the starting instruction, or the user who is associated with the intelligent air conditioner and has the highest control authority in a plurality of indoor users.
The preference model is obtained according to the operation of the user for adjusting the operation parameters in the operation process of the air conditioner and is used for reflecting the temperature adjustment preference of the user in the operation process of the air conditioner.
And S22, the air conditioner determines an air conditioner target operation mode corresponding to the current moment, and adjusts the operation parameters of the air conditioner target operation mode according to the preference model.
The current moment is the moment of obtaining the starting instruction for the intelligent air conditioner, and the intelligent air conditioner can be obtained from a cloud end by connecting indoor WiFi equipment and can also be obtained by communicating with a mobile phone of a user. The current time at least comprises a time period to which the starting instruction belongs when the starting instruction is acquired.
Since the air conditioner is not a household appliance used for 24 hours, the air conditioner on time of the user is not uniformly distributed within 24 hours of the day, for example: the night sleep time is the peak of the air conditioner, and the noon time is also provided with a small peak of the air conditioner, so that the use of the air conditioner can change along with the activity characteristics and weather factors of users. In this embodiment, in combination with the use characteristics of the air conditioner, the time period of one day is divided into 3 segments, namely a day daily activity segment, a night rest segment and a night sleep segment, so as to realize the sectional learning of the operation condition of the air conditioner according to the activity characteristics of the user. For example, the daily activity period during the day is 8-00, the rest period during the night is 17-00, and the sleep period during the night is 21. The setting of the time period can also be adjusted according to the starting frequency of the air conditioner in the corresponding time period.
The air-conditioning target operation mode refers to a startup use mode corresponding to the startup time period. The determination of the target operation mode of the air conditioner can be obtained through historical use data of the air conditioner, for example, the use data of the air conditioner is obtained through a big data platform, denoising analysis is carried out on the data, and different target operation modes of the air conditioner, which are labeled with the starting time period of the air conditioner, are obtained after summary statistics.
Furthermore, the air conditioner target operation mode determined according to the current moment is adjusted through the preference model, so that the operation parameters pushed to the user are more in line with the use habit of the user.
And step S23, the air conditioner pushes the adjusted operation parameters to a target user so that the target user can use the adjusted operation parameters when the air conditioner is set.
Therefore, when a starting instruction is received, the target operation mode of the air conditioner corresponding to the starting setting habit of the target user at the current moment is determined, and the operation parameters in the target operation mode are further adjusted according to the preference model used by the target user for controlling the air conditioner, so that the operation mode of the air conditioner which is most consistent with the use habit of the user at the current moment and under the indoor environment condition is obtained and pushed to the user. So, through the use habit and the regulation preference of study air conditioner user in the use, carry out the propelling movement of air conditioner operational mode automatically to create the comfortable living environment who is fit for the user, and solved the problem of user frequent operation, effectively improve the convenience of air conditioner operation, further improved user's experience.
Optionally, adjusting the operation parameters of the target operation mode of the air conditioner according to the user preference model includes: acquiring current environmental parameters, and inputting the current environmental parameters into a preference model to output corresponding operation parameter adjustment values; and adjusting the corresponding operation parameters in the target operation mode of the air conditioner according to the operation parameter adjustment values.
Here, the current environmental parameter includes one or more of a current indoor temperature, a current outdoor temperature, and a current indoor humidity. By inputting the current environment parameters, the air conditioning preference condition of the user in the current environment is obtained through the preference model, so that the operation parameters more in line with the habit of the user are obtained.
Optionally, the determining of the target operation mode of the air conditioner includes:
acquiring a plurality of pieces of historical operating data of the air conditioner matched with the current time information; each historical operation data comprises an operation mode of the air conditioner and the using time of the air conditioner;
determining the recommendation degree of each operation mode according to the historical time and/or the air conditioner use duration corresponding to one or more pieces of historical operation data with the same operation mode;
and acquiring one or more operation modes with the highest recommendation degree as the target operation modes of the air conditioner.
Here, the historical operation data matched with the current time information includes at least historical operation data of the air conditioner belonging to the same time period as the current time information in the current month. Historical operating data of the air conditioner in the same month of the last year may also be included.
Due to seasonal influence, the use of the air conditioner is discontinuous and is not used every day, the use behaviors of the cooling, heating and users are changed, but the use behaviors in the same month do not have great difference, so that the operation mode which is consistent with the use habit of the users can be determined according to the air conditioner data in the current month or the data in the same month in the last year.
Further, each historical operating data comprises an operating mode and an air conditioner use duration of the air conditioner, and the operating mode comprises a set target temperature, a set wind speed, a set humidity and a set function mode of the air conditioner; the air conditioner service time comprises a starting time point, a distance starting time and a set duration.
And classifying the operation modes corresponding to the historical operation data so as to determine the recommendation degree of the operation mode according to multiple times of historical operation data of the same operation mode, thereby obtaining the target operation mode of the air conditioner.
Specifically, the determining of the recommendation degree of the operation mode includes:
determining date influence factors of the historical operating data according to the historical time corresponding to each historical operating data;
determining behavior influence factors of historical operating data according to the air conditioner service duration of each historical operating data;
and determining the recommendation degree of the operation mode according to the sum of the products of the date influence factor and the behavior influence factor of one or more pieces of historical operation data with the same operation mode.
And the historical time corresponding to the historical operating data used for determining the date influence factor is used for representing the occurrence time of the historical operating data, and the influence of the historical operating data on the current behavior is smaller if the distance between the occurrence time of the historical operating data and the current time information is longer.
For example, the corresponding relationship between the date difference and the date influence factor is prestored in the air conditioner, and after the date difference corresponding to the historical operating data and the current time is determined, the date influence factor corresponding to the date difference is further acquired by calling the corresponding relationship, so as to determine the recommendation degree of the operating mode. Further, the corresponding relationship may be pre-stored in the air conditioner in the form of a corresponding information table.
Further, the determination of the date impact factor comprises:
when the difference value between the historical time corresponding to the historical operating data and the date corresponding to the current moment is larger than the date threshold value, the date influence factor corresponding to the historical operating data is a first date influence factor;
when the difference value between the historical time corresponding to the historical operating data and the date corresponding to the current time is smaller than or equal to the date threshold value, the date influence factor corresponding to the historical operating data is a second date influence factor;
wherein the first date impact factor has a value less than the second date impact factor.
Specifically, the determination of the date influence factor comprises the following steps:
wherein, x is the difference between the historical time corresponding to the historical operating data and the date corresponding to the current moment, and n is the total days for obtaining the historical operating data.
In this way, after a plurality of pieces of historical operating data within a set time length (the total days of the historical operating data) are acquired, the corresponding date influence factors are determined by acquiring the date difference from the occurrence date of the historical operating data to the current time, so that under the condition that a plurality of pieces of historical operating data correspond to the same operating mode, the recommendation degree influence of each piece of historical operating data on the operating mode is weighted according to the date influence factors corresponding to multiple times of operation, and the operating mode recommendation more suitable for the use habit of a user is obtained.
The air conditioner use duration of the historical operation data used for determining the behavior influence factors is used for representing the length of the air conditioner use time of a user in the historical operation data, the longer the use time is, the more comfortable the historical operation data is for the user, and the higher the score of the corresponding behavior influence factor is. In the embodiment, the air conditioner usage duration of the historical operation data has a non-linear positive correlation with the value of the behavior influencing factor.
For example, the corresponding relationship between the air conditioner use duration and the behavior impact factor is prestored in the air conditioner, and after the air conditioner use duration in the historical operation data is obtained, the behavior impact factor corresponding to the air conditioner use duration is obtained by calling the corresponding relationship, so as to determine the recommendation degree of the operation mode. Further, the correspondence may be pre-stored in the air conditioner in the form of a correspondence information table.
Further, the determining of the behavior influencing factor comprises:
when the air conditioner using time of historical operating data is within a first time interval, the behavior influence factor is a first behavior influence factor;
when the air conditioner using time of the historical operating data is within a second time interval, the behavior influence factor is a second behavior influence factor;
wherein, the upper limit value of the first time length interval is smaller than the lower limit value of the second time length interval; the value of the first behavior influencing factor is smaller than the value of the second behavior influencing factor.
Specifically, the behavior-affecting factor is determined as follows:
wherein x is the air conditioner service time of the historical operating data, and the unit is hour.
Therefore, after the air conditioner use duration corresponding to the historical operation data is obtained, the corresponding behavior influence factors are determined by obtaining the interval where the air conditioner use duration is located, and therefore under the condition that a plurality of historical operation data correspond to the same operation mode, the recommendation degree influence of each historical operation data on the operation mode is weighted according to the behavior influence factors corresponding to multiple times of operation, and operation mode recommendation more fitting the use habits of users is obtained.
The obtaining of the recommendation degree of the operation mode may include: acquiring the sum of date influence factors of one or more historical operating data in the same operating mode as a first recommendation degree of the date influence factors; acquiring the sum of the behavior influence factors of one or more historical operation data in the same operation mode as a second recommendation degree of the behavior influence factors; and determining the recommendation degree of the operation mode according to the product of the first recommendation degree and the second recommendation degree.
Alternatively, the obtaining of the recommendation degree of the operation mode may include: acquiring one or more historical operating data of the same operating mode, and respectively determining the product of the date influence factor and the behavior influence factor of each historical operating data; and determining the recommendation degree of the operation mode according to the sum of the products of the date influence factors and the behavior influence factors of one or more historical operation data. The higher the recommendation level of the operation mode, the more likely the user is to use the operation mode, and therefore, the push is performed to the user.
Therefore, by adopting the operation mode pushing method for the air conditioner provided by the embodiment of the disclosure, when the starting instruction is received, the air conditioner target operation mode corresponding to the starting setting habit of the target user at the current time is determined, and further, the operation parameters in the target operation mode are adjusted according to the preference model used by the target user for controlling the air conditioner, so that the air conditioner operation mode which best meets the use habit of the user at the current time and under the indoor environment condition is obtained and pushed to the user. So, through the use habit and the regulation preference of study air conditioner user in the use, carry out the propelling movement of air conditioner operational mode automatically to create the comfortable living environment who is fit for the user, and solved the problem of user frequent operation, effectively improve the convenience of air conditioner operation, further improved user's experience.
Fig. 3 is a schematic diagram of another operation mode pushing method for an air conditioner according to an embodiment of the present disclosure. The operation mode pushing method for the air conditioner is applied to the environment shown in fig. 1, can be executed in the air conditioner shown in fig. 1, and can also be executed in a control terminal of the air conditioner, such as a remote controller or an operation panel on a wall of a room; the method can also be executed in a server, such as a family cloud platform communicated with an air conditioner; the method can also be executed in terminal equipment, such as a smart phone, a smart household appliance or a control terminal of a smart home system. In the embodiments of the present disclosure, the scheme is explained with an air conditioner as an execution subject.
As shown in fig. 3, the operation mode push method for an air conditioner includes:
in step S21, in response to the power-on instruction, the air conditioner determines a target user and a preference model for air conditioner control corresponding to the target user.
And S22, the air conditioner determines an air conditioner target operation mode corresponding to the current moment, and adjusts the operation parameters of the air conditioner target operation mode according to the preference model.
And step S23, the air conditioner pushes the adjusted operation parameters to a target user so that the target user can use the operation parameters when the air conditioner is set.
And step S34, acquiring the adjustment state of the air conditioner operation parameters in the set operation duration under the condition that the target user receives the adjusted operation parameters and controls the air conditioner to operate according to the adjusted operation parameters.
Step S35, if the operation parameters of the air conditioner are adjusted within the set operation time, acquiring the adjustment times of the operation parameters of the air conditioner within the set historical time before the adjustment time; and under the condition that the adjusting times are larger than the set times, taking the adjusted operation parameters as training samples of the preference model of the target user.
And S36, if the operation parameters of the air conditioner are not adjusted within the set operation time, taking the adjusted operation parameters as training samples of the preference model of the target user.
Here, when the air conditioner operates according to the adjusted operating parameters, it is considered that the target operating mode determined according to the historical operating data and the control instruction formed according to the adjustment scheme of the user preference model are successfully issued, and at this time, the operating data of the air conditioner and the behavior data of the user are continuously monitored, and it is determined whether the user intervenes in the current air conditioner operation, so as to determine whether the current operation is successful.
If the user adjusts the operation parameters of the air conditioner within the set operation duration, the operation data of the air conditioner at this time cannot be taken into the historical operation data for operation mode recommendation due to user intervention. If the adjusting times of the operation parameters are larger than the set times within the set historical duration, the adjusting behaviors of the operation parameters are used as training samples of the user preference model so as to output the operation parameter adjusting values which are consistent with the expected values according to the adjusting preferences of the user.
If the user does not adjust the operation parameters of the air conditioner within the set operation duration, the operation data of the air conditioner at this time accords with the use habit of the user, and the operation parameters after the adjustment at this time are used as training samples of a preference model of the target user so as to output the operation parameter adjustment value which accords with the expected value according to the adjustment preference of the user.
Therefore, by adopting the operation mode pushing method for the air conditioner provided by the embodiment of the disclosure, when the starting instruction is received, the air conditioner target operation mode corresponding to the starting setting habit of the target user at the current moment is determined, and the operation parameters in the target operation mode are adjusted according to the preference model used by the target user for controlling the air conditioner, so that the air conditioner operation mode which best meets the use habit of the user at the current moment and under the indoor environment condition is obtained and pushed to the user. Furthermore, after the operation parameters are adjusted through the operation of the air conditioner, the adjustment behavior of the user further learns the adjustment preference of the user, so that the operation parameters which are more in line with the requirements of the user are output after data training. Therefore, the pushing of the air conditioner operation mode is automatically carried out by learning the use habits and the adjustment preferences of the user in the use process of the air conditioner, so that a comfortable living environment suitable for the user is created, and the problem of frequent operation of the user is solved.
The embodiment of the present disclosure provides an operation mode pushing device for an air conditioner, the structure of which is shown in fig. 4, including:
a processor (processor) 40 and a memory (memory) 41, and may also include a Communication Interface (Communication Interface) 42 and a bus 43. The processor 40, the communication interface 42 and the memory 41 can communicate with each other through the bus 43. Communication interface 42 may be used for information transfer. The processor 40 may call logic instructions in the memory 41 to perform the operation mode push method for the air conditioner of the above-described embodiment.
In addition, the logic instructions in the memory 41 may be implemented in the form of software functional units and stored in a computer readable storage medium when the logic instructions are sold or used as independent products.
The memory 41 is a computer-readable storage medium, and can be used for storing software programs, computer-executable programs, such as program instructions/modules corresponding to the methods in the embodiments of the present disclosure. The processor 40 executes the functional application and data processing by executing the program instructions/modules stored in the memory 41, that is, implements the operation mode push method for the air conditioner in the above-described method embodiment.
The memory 41 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the terminal device, and the like. Further, the memory 41 may include a high-speed random access memory, and may also include a nonvolatile memory.
The embodiment of the disclosure provides an air conditioner, which comprises the operation mode pushing device for the air conditioner.
The embodiment of the present disclosure provides a computer-readable storage medium storing computer-executable instructions configured to perform the above-mentioned operation mode push method for an air conditioner.
An embodiment of the present disclosure provides a computer program product including a computer program stored on a computer-readable storage medium, the computer program including program instructions that, when executed by a computer, cause the computer to perform the above-described operation mode push method for an air conditioner.
The computer-readable storage medium described above may be a transitory computer-readable storage medium or a non-transitory computer-readable storage medium.
The technical solution of the embodiments of the present disclosure may be embodied in the form of a software product, where the computer software product is stored in a storage medium and includes one or more instructions to enable a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method of the embodiments of the present disclosure. And the aforementioned storage medium may be a non-transitory storage medium comprising: a U-disk, a portable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other media capable of storing program codes, and may also be a transient storage medium.
The above description and the drawings sufficiently illustrate embodiments of the disclosure to enable those skilled in the art to practice them. Other embodiments may incorporate structural, logical, electrical, process, and other changes. The examples merely typify possible variations. Individual components and functions are optional unless explicitly required, and the sequence of operations may vary. Portions and features of some embodiments may be included in or substituted for those of others. The scope of the disclosed embodiments includes the full ambit of the claims, as well as all available equivalents of the claims. As used in this application, although the terms "first," "second," etc. may be used in this application to describe various elements, these elements should not be limited by these terms. These terms are only used to distinguish one element from another. For example, a first element could be termed a second element, and, similarly, a second element could be termed a first element, provided that all occurrences of the first element are renamed consistently and all occurrences of the second element are renamed consistently. The first and second elements are both elements, but may not be the same element. Furthermore, the words used in the specification are words of description only and are not intended to limit the claims. As used in the description of the embodiments and the claims, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. Similarly, the term "and/or" as used in this application is meant to encompass any and all possible combinations of one or more of the associated listed. Furthermore, the terms "comprises" and/or "comprising," when used in this application, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. Without further limitation, an element defined by the phrase "comprising one of 8230," does not exclude the presence of additional like elements in a process, method or device comprising the element. In this document, each embodiment may be described with emphasis on differences from other embodiments, and the same and similar parts between the respective embodiments may be referred to each other. For methods, products, etc. of the embodiment disclosure, reference may be made to the description of the method section for relevance if it corresponds to the method section of the embodiment disclosure.
Those of skill in the art would appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software may depend upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the disclosed embodiments. It can be clearly understood by the skilled person that, for convenience and brevity of description, the specific working processes of the system, the apparatus and the unit described above may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the embodiments disclosed herein, the disclosed methods, products (including but not limited to devices, apparatuses, etc.) may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units may be merely a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to implement the present embodiment. In addition, functional units in the embodiments of the present disclosure may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). In some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. In the description corresponding to the flowcharts and block diagrams in the figures, operations or steps corresponding to different blocks may also occur in different orders than disclosed in the description, and sometimes there is no specific order between the different operations or steps. For example, two sequential operations or steps may in fact be executed substantially concurrently, or they may sometimes be executed in the reverse order, depending upon the functionality involved. Each block of the block diagrams and/or flowchart illustrations, and combinations of blocks in the block diagrams and/or flowchart illustrations, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
Claims (8)
1. An operation mode push method for an air conditioner, comprising:
in response to a starting instruction, determining a target user and a preference model for air conditioner control corresponding to the target user;
determining an air conditioner target operation mode corresponding to the current moment, and adjusting operation parameters of the air conditioner target operation mode according to the preference model;
pushing the adjusted operation parameters to the target user for the target user to use when the target user sets an air conditioner;
wherein the determination of the air conditioner target operation mode comprises the following steps:
acquiring a plurality of pieces of historical operating data of the air conditioner matched with the current time information; each historical operation data comprises an operation mode and an air conditioner use time length of the air conditioner;
determining date influence factors of the historical operating data according to the historical time corresponding to each historical operating data;
determining a behavior influence factor of the historical operation data according to the air conditioner service life of each historical operation data; the air conditioner use time of the historical operation data and the numerical value of the behavior influence factor form a non-linear positive correlation;
determining the recommendation degree of the operation mode according to the sum of the products of the date influence factor and the behavior influence factor of one or more pieces of historical operation data with the same operation mode;
and acquiring one or more operation modes with the highest recommendation degree as the air conditioner target operation mode.
2. The method of claim 1, wherein the adjusting the operating parameters of the air conditioning target operating mode according to the user preference model comprises:
acquiring current environment parameters, and inputting the current environment parameters into the preference model to output corresponding operation parameter adjustment values;
and adjusting the corresponding operating parameters in the target operating mode of the air conditioner according to the operating parameter adjusting values.
3. The method of claim 1, wherein the determining of the date impact factor comprises:
when the difference value between the historical time corresponding to the historical operating data and the date corresponding to the current time is larger than the date threshold value, the date influence factor corresponding to the historical operating data is a first date influence factor;
when the difference value between the historical time corresponding to the historical operating data and the date corresponding to the current time is smaller than or equal to the date threshold value, the date influence factor corresponding to the historical operating data is a second date influence factor;
wherein the first date impact factor has a value less than the second date impact factor.
4. The method of claim 1, wherein the determining of the behavior impact factor comprises:
when the air conditioner using time of historical operating data is within a first time interval, the behavior influence factor is a first behavior influence factor;
when the air conditioner using time of historical operating data is within a second time interval, the behavior influence factor is a second behavior influence factor;
wherein, the upper limit value of the first time length interval is smaller than the lower limit value of the second time length interval; the value of the first behavior influencing factor is smaller than the value of the second behavior influencing factor.
5. The method of any of claims 1 to 4, further comprising:
under the condition that the target user receives the adjusted operation parameters and controls the air conditioner to operate according to the adjusted operation parameters, obtaining the adjustment state of the operation parameters of the air conditioner within a set operation duration;
if the operation parameters of the air conditioner are adjusted within the set operation time, acquiring the adjustment times of the operation parameters of the air conditioner within the set historical time before the adjustment time;
and under the condition that the adjusting times are larger than the set times, taking the adjusted operating parameters as training samples of the preference model of the target user.
6. The method according to claim 5, wherein if the operation parameters of the air conditioner are not adjusted within the set operation time period, the adjusted operation parameters are used as training samples of the preference model of the target user.
7. An operation mode push apparatus for an air conditioner, comprising a processor and a memory storing program instructions, wherein the processor is configured to execute the operation mode push method for an air conditioner according to any one of claims 1 to 6 when executing the program instructions.
8. An air conditioner characterized by comprising the operation mode push device for an air conditioner according to claim 7.
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202110686217.2A CN113531818B (en) | 2021-06-21 | 2021-06-21 | Running mode pushing method and device for air conditioner and air conditioner |
| PCT/CN2022/088661 WO2022267671A1 (en) | 2021-06-21 | 2022-04-24 | Air conditioner operation mode pushing method and apparatus, and air conditioner |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
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| CN202110686217.2A CN113531818B (en) | 2021-06-21 | 2021-06-21 | Running mode pushing method and device for air conditioner and air conditioner |
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| CN113531818A CN113531818A (en) | 2021-10-22 |
| CN113531818B true CN113531818B (en) | 2022-12-23 |
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| CN113531818B (en) * | 2021-06-21 | 2022-12-23 | 青岛海尔空调器有限总公司 | Running mode pushing method and device for air conditioner and air conditioner |
| CN114322212A (en) * | 2021-12-28 | 2022-04-12 | 青岛海尔空调器有限总公司 | Air conditioner control method and device, electronic equipment, storage medium and air conditioner |
| CN114811822A (en) * | 2022-03-14 | 2022-07-29 | 青岛海尔空调器有限总公司 | Method and device for controlling air conditioner, terminal equipment and storage medium |
| CN115390466A (en) * | 2022-07-29 | 2022-11-25 | 青岛海尔科技有限公司 | Behavior preference table generation method and device, storage medium and electronic device |
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| CN103982982B (en) * | 2014-05-05 | 2016-10-19 | 美的集团股份有限公司 | The control method of air-conditioner and air-conditioner |
| CN107816781A (en) * | 2017-10-31 | 2018-03-20 | 珠海格力电器股份有限公司 | The control method and device of air-conditioning |
| CN109974248B (en) * | 2019-04-01 | 2020-08-11 | 珠海格力电器股份有限公司 | Control method of air conditioner and air conditioner operation system |
| CN109974246B (en) * | 2019-04-17 | 2020-04-24 | 珠海格力电器股份有限公司 | Control method and control device of air conditioner and air conditioner |
| CN112325450A (en) * | 2019-08-05 | 2021-02-05 | 青岛海尔空调器有限总公司 | Method for acquiring control parameters of intelligent air conditioner and control equipment |
| CN110500728A (en) * | 2019-08-26 | 2019-11-26 | 宁波奥克斯电气股份有限公司 | A kind of control method of air-conditioning, system, readable storage medium storing program for executing and air-conditioning |
| CN110595012B (en) * | 2019-09-23 | 2021-08-31 | 海信（广东）空调有限公司 | Recommendation method and device for air conditioner operation mode |
| CN111442501B (en) * | 2020-03-30 | 2022-09-13 | 广东美的制冷设备有限公司 | Air conditioning equipment and control method and device thereof |
| CN113531818B (en) * | 2021-06-21 | 2022-12-23 | 青岛海尔空调器有限总公司 | Running mode pushing method and device for air conditioner and air conditioner |
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| WO2022267671A1 (en) | 2022-12-29 |
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