Electronic device for controlling humidifier using artificial intelligence model, humidifier, and methods therefor

Abstract

Disclosed are an electronic device for controlling a humidifier using an artificial intelligence model, a humidifier, and a method therefor. In the device and method, the electronic device receives information on a plurality of control factors related to a humidification operation by means of a communication unit, generates a control signal for controlling the humidification operation using the plurality of control factors and an artificial intelligence model so that the humidifier can humidify to a target humidity in a power saving state within a preset allowable time range, and transmits the control signal to the humidifier. Accordingly, energy can be effectively saved, and thus electricity bills can be reduced or a contribution may be made to environmental protection.

Description

Electronic devices and humidifiers and methods for controlling humidifiers using artificial intelligence models

[0001] The present invention relates to an electronic device for controlling the operation of a humidifier using an artificial intelligence model, a humidifier, and a method thereof.

[0002] Humidifiers are widely used to control indoor humidity. Thanks to technological advancements, humidifiers can now communicate with electronic devices like smartphones, extending beyond simple humidification functions. Apps installed on these devices enable more precise control.

[0003] In conventional technology, humidifiers operate at maximum power while turned on. Therefore, the need for technology that can efficiently control humidifiers by considering various variables related to their operation, such as indoor humidity, temperature, and residual water level, has emerged.

[0004] According to at least one embodiment of the present disclosure, an electronic device,

[0005] The communication unit includes memory and processors where artificial intelligence models are stored.

[0006] The processor, when information on a plurality of control factors related to a humidifying operation of the humidifier is received through the communication unit, transmits a control signal to the humidifier through the communication unit to control the humidifying operation of the humidifier so that the humidifier can humidify to a target humidity in a power-saving state within a preset allowable time range using the plurality of control factors and the artificial intelligence model, and the artificial intelligence model is a model learned by data on power consumption for each combination of a plurality of control factors.

[0007] According to at least one embodiment of the present disclosure, a humidifier comprises a memory storing information on a preset target humidity, a processor, at least one sensor, and

[0008] It includes a humidifying module for performing humidification using water collected in a water collecting tank,

[0009] The processor identifies temperature and humidity based on the sensing values ​​of the at least one sensor, calculates the time required to humidify to the target humidity, and controls the operation of the humidifying module to humidify to the target humidity in a power-saving state within a preset allowable time range based on information about control factors including the target humidity, temperature, humidity, the time required, and the amount of residual water in the water tank.

[0010] According to at least one embodiment of the present disclosure, a power-saving operation method using a server device comprises: a step of receiving information on a plurality of control factors related to a humidifying operation of a humidifier through the communication unit; a step of executing an artificial intelligence model; a step of generating a control signal for controlling a humidifying operation of the humidifier so that the humidifier can humidify to a target humidity in a power-saving state within a preset allowable time range using the plurality of control factors and the artificial intelligence model; and

[0011] It includes a step of transmitting the control signal to the humidifier through the communication unit.

[0012] FIG. 1 is a drawing for explaining the operation of an electronic device according to at least one embodiment of the present disclosure.

[0013] FIG. 2 is a block diagram illustrating a configuration of an electronic device according to at least one embodiment of the present disclosure.

[0014] FIG. 3 is a graph showing a heater split control mode in a rated heating section of a heated humidifier according to at least one embodiment of the present disclosure.

[0015] FIG. 4 is a table showing heating modes of a heated humidifier classified according to the range of a plurality of control factors related to a humidifying operation according to at least one embodiment of the present disclosure.

[0016] FIG. 5 is a table that classifies the target humidity reaching time by heater capacity of a heated humidifier according to at least one embodiment of the present disclosure according to the size of the space.

[0017] FIG. 6 is a graph showing the correlation between temperature and target humidification reaching time according to at least one embodiment of the present disclosure.

[0018] FIG. 7 is a graph showing the correlation between indoor temperature and required humidification amount according to at least one embodiment of the present disclosure.

[0019] FIG. 8 is a diagram illustrating an electronic device that receives a plurality of control factors related to a humidifying operation from a plurality of external devices and a humidifier according to at least one embodiment of the present disclosure.

[0020] FIG. 9 is a drawing showing a UI displayed on a terminal device according to at least one embodiment of the present disclosure, which allows a user to control a humidifier, and an operation of the terminal device.

[0021] FIG. 10 is a block diagram illustrating a configuration of a heating humidifier according to at least one embodiment of the present disclosure.

[0022] FIG. 11 is a flowchart of a method for an electronic device according to at least one embodiment of the present disclosure to process a plurality of control factors associated with a humidifying operation.

[0023] FIG. 12 is a flowchart of a method for controlling a humidifier using an artificial intelligence model according to at least one embodiment of the present disclosure.

[0024] The terms used in this specification will be briefly explained, and the present disclosure will be described in detail.

[0025] The terms used in the embodiments of this disclosure have been selected from widely used, current terms, taking into account the functions of this disclosure. However, these terms may vary depending on the intentions of those skilled in the art, precedents, the emergence of new technologies, etc. Furthermore, in certain cases, terms may be arbitrarily selected by the applicant, and in such cases, their meanings will be described in detail in the description of the relevant disclosure. Therefore, the terms used in this disclosure should not be defined simply as names of terms, but rather based on the meanings of the terms and the overall content of this disclosure.

[0026] The embodiments of the present disclosure may be modified and have various embodiments. Specific embodiments are illustrated in the drawings and described in detail in the detailed description. However, this is not intended to limit the scope of the present disclosure to specific embodiments, but rather to encompass all modifications, equivalents, and alternatives falling within the scope of the disclosed concepts and techniques. In describing the embodiments, detailed descriptions of related known technologies will be omitted if they are deemed to obscure the main point.

[0027] Terms such as "first" and "second" may be used to describe various components, but the components should not be limited by these terms. These terms are used solely to distinguish one component from another.

[0028] Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "comprises" or "consists of" are intended to indicate the presence of a feature, number, step, operation, component, part, or combination thereof described in the specification, but should be understood not to preclude the presence or addition of one or more other features, numbers, steps, operations, components, parts, or combinations thereof.

[0029] Below, with reference to the attached drawings, embodiments of the present disclosure are described in detail so that those skilled in the art can easily implement the present disclosure. However, the present disclosure may be implemented in various different forms and is not limited to the embodiments described herein. In addition, in the drawings, parts irrelevant to the description are omitted for clarity of description of the present disclosure, and similar parts are designated with similar reference numerals throughout the specification.

[0030] FIG. 1 is a drawing for explaining the operation of an electronic device according to at least one embodiment of the present disclosure.

[0031] According to FIG. 1, the electronic device (100) can communicate with a humidifier (200) or other various external devices.

[0032] The electronic device (100) can receive temperature, humidity, and residual water level sensed from the humidifier (200) itself or external devices surrounding the humidifier. The electronic device (100) can be implemented as various devices such as a server device, a desktop PC, a laptop PC, a mobile phone, a tablet PC, a kiosk, or an electronic whiteboard.

[0033] The electronic device (100) includes an artificial intelligence model. The electronic device (100) can control the operation of the humidifier (200) based on various information received from the humidifier (200) or an external device. Specifically, the electronic device (100) can obtain a plurality of control factors related to the humidification operation. The electronic device (100) can directly receive information on at least some of the plurality of control factors from various external devices, or can calculate at least some of the plurality of control factors based on information received from the external device. The electronic device (100) generates a signal for controlling the humidification operation of the humidifier (200) using the plurality of control factors related to the humidification operation and the artificial intelligence model.

[0034] The multiple control factors associated with humidification operations can be various pieces of information required by the humidifier to perform the humidification operation. For example, the multiple control factors include values ​​such as humidity before the humidification operation is performed, target humidity, temperature, humidification time to reach the target humidity, residual water content, space shape, and space size. Among the multiple control factors, the humidity information can be a humidity value measured in the space where the humidifier is placed. The target humidity can be a user-set value for the humidity level in the space where the humidifier is placed. The humidification time can be the time required to raise the current humidity to the target humidity. Maintaining the humidifier's humidification operation at its highest setting will reduce the humidification time, but will also increase power consumption. Conversely, maintaining the humidifier's humidification operation at its lowest setting will reduce power consumption, but will significantly increase the humidification time. The humidifier can determine the humidification time as an appropriate value to reach the target humidity within an appropriate time range. The residual water content indicates the amount of water remaining in the water tank that stores water in the humidifier. The shape and size of the space can be information indicating the shape and size of the space where the humidifier is placed (e.g., living room).

[0035] The artificial intelligence model of the electronic device (100) comprehensively considers these various control factors and controls the humidification operation of the humidifier (200) so that the humidifier can humidify to the target humidity in a power-saving state within a preset allowable time range. In other words, the electronic device (100) can control the humidification operation of the humidifier in various ways so that the time required to adjust the humidity to the target humidity does not become too long while using the minimum amount of power.

[0036] Control factors such as the shape and size of the space may be additionally considered to optimize the control efficiency of the electronic device (100). For example, when comparing a typical house and an apartment, the degree of airtightness of a typical house may be relatively lower than that of an apartment. Therefore, even if the humidification operation is performed at the same intensity for the same period of time, the humidity change in a typical house may differ from that in an apartment. Furthermore, even within the same residential environment, the humidity conditions in an open environment such as a living room and a closed environment such as a room may differ. Specifically, assuming that the same humidifier (200) is used in a house and an apartment with the same floor area, the humidity conditions may differ as shown in Table 1 below.

[0037]

[0038] Table 1 shows the humidifier's usage time per unit area. Referring to Table 1, for a floor area of ​​33.1 m2 and a water tank of 4 L, it takes 6.4 hours in a house and 8.5 hours in an apartment to fully use the water in one tank for humidification. Referring to the remaining cases in Table 1, the usage time per unit area is longer in apartments than in houses, and as the space size increases, the time required for humidification increases.

[0039] This means that the shape and size of the space affect the humidification time. Therefore, when information on the shape and size of the space is additionally considered in addition to the multiple control factors described above, the electronic device (100) can produce a result by varying the humidification time (allowable time) range.

[0040] Types of humidifiers (200) include heating humidifiers, ultrasonic humidifiers, and natural evaporation humidifiers.

[0041] Heated humidifiers heat water to create steam. Ultrasonic humidifiers use ultrasonic waves to spray water into a fine mist. Natural evaporation humidifiers absorb water through a built-in filter and utilize the principle of natural evaporation.

[0042] Although at least one embodiment of the present disclosure is applicable to all humidifiers that utilize electricity, a heating type humidifier is described below as an example.

[0043] When the humidifier (200) is implemented as a heating type humidifier, the electronic device (100) operates the heater of the humidifier during a preset initial heating period when the operation of the humidifier (200) is started, and can selectively change the multiple heating modes of the humidifier based on the output values ​​of the artificial intelligence model during the rated heating period after the initial heating period. The initial heating period may be an initial period in which the humidifier (200) heats water to a temperature at which steam is generated. The length of the initial heating period may be determined in various ways depending on the size of the water collection tank provided in the humidifier (200), the location of the heater, the type of heater, the type of the humidifier (200), etc. The rated heating period may be a period in which the heating operation of the humidifier (200) is controlled after the initial heating period to adjust the degree of steam generation. During the rated heating period, the electronic device (100) can selectively change the multiple heating modes of the humidifier based on the output values ​​of the artificial intelligence model. The heating mode may be an operation mode in which the humidifier heats water using a heater to generate steam. The heating mode may also be referred to as an operation mode, a control mode, a humidification state mode, etc., but in the present disclosure, it is uniformly described as a heating mode. The plurality of heating modes may be classified according to various criteria such as the amount of moisture generated, the level of noise generated, the level of power consumption, etc. For example, the plurality of heating modes may include at least one of various modes such as a strongest mode, a strong mode, a medium mode, a weak mode, a power-saving mode, a night mode, a low-noise mode, etc. In the above, it has been described that the electronic device (100) controls the operation of the humidifier (200) based on an artificial intelligence model and a control factor. However, according to another embodiment of the present disclosure, the electronic device (100) may control the operation of the humidifier (200) based on a preset control logic or program without using an artificial intelligence model.These various embodiments are described in detail again in the following sections.

[0044] FIG. 2 is a block diagram illustrating a configuration of an electronic device according to at least one embodiment of the present disclosure.

[0045] According to FIG. 2, the electronic device (100) includes a communication unit (110), a memory (130), and a processor (120).

[0046] The communication unit (110) is configured to communicate with various external devices. In an environment such as Fig. 1, the communication unit (110) can communicate with at least one humidifier or external devices.

[0047] The communication unit (110) can transmit and receive various signals and data with the humidifier (200) or other external devices through various wired and wireless communication methods such as Bluetooth, AP-based Wi-Fi (Wireless LAN network), Zigbee, wired / wireless LAN (Local Area Network), WAN (Wide Area Network), Ethernet, IEEE 1394, HDMI (High-Definition Multimedia Interface), USB (Universal Serial Bus), MHL (Mobile High-Definition Link), AES / EBU (Audio Engineering Society / European Broadcasting Union), optical, coaxial, etc.

[0048] The processor (120) is a configuration for controlling the overall operation of the electronic device (100).

[0049] The processor (120) may include one or more of a digital signal processor (DSP), a microprocessor, a central processing unit (CPU), a micro controller unit (MCU), a micro processing unit (MPU), a controller, an application processor (AP), a communication processor (CP), an ARM processor, or an artificial intelligence (AI) processor, or may be defined by the terms thereof. In addition, the processor (120) may be implemented as a system on chip (SoC) or large scale integration (LSI) having a built-in processing algorithm, or may be implemented in the form of a field programmable gate array (FPGA). The processor (120) may perform various functions by executing computer executable instructions stored in the memory (130).

[0050] Specifically, when the processor (120) receives information on a plurality of control factors related to the humidifying operation of the humidifier through the communication unit (110), the processor (120) can store the information in the memory (130). The processor (120) can control the humidifying operation of the humidifier (200) using the received information and the artificial intelligence model so that the humidifier (200) can humidify to the target humidity in a power-saving state within a preset allowable time range. Specifically, the processor (120) can generate a control signal for controlling the operation of the humidifier (200). The control signal may include various identification information such as an IP address corresponding to the humidifier (200), a product serial number, a product name, a product code, an SSID (Session ID), and various control information such as a digital control code corresponding to the humidifier (200), but is not limited thereto and may be configured in various forms according to a communication standard method. The processor (120) transmits the generated control signal to the humidifier through the communication unit (110).

[0051] For example, in the case of a heated humidifier, when the operation of the humidifier (200) is started, the heater of the humidifier is driven at the highest output during a preset initial heating period, and in the rated heating period when the water starts to boil, a control signal for selectively changing the multiple heating modes of the humidifier (200) based on the output value of the artificial intelligence model is generated and transmitted to the humidifier (200). For example, the processor (120) may generate a control signal including a control code for operating in medium mode for a certain period of time after the initial heating period ends, and then sequentially changing the mode in various orders such as strong, weak, medium, strong, and strongest.

[0052] The processor (120) can execute the artificial intelligence model stored in the memory (130) to perform the above-described operation. That is, the processor (120) uses information on a plurality of control factors as input values ​​of the artificial intelligence model stored in the memory (130). The processor (120) can be implemented as an artificial intelligence-dedicated processor. The artificial intelligence-dedicated processor can be designed with a hardware structure specialized for processing a specific artificial intelligence model. The artificial intelligence model can be trained using various data. For example, the artificial intelligence model can be trained using data on power consumption for each combination of a plurality of control factors.

[0053] The creation of an artificial intelligence model through learning means that the basic artificial intelligence model is trained using a learning algorithm using a plurality of learning data, thereby enabling it to perform a desired characteristic (or purpose). This learning may be performed in the electronic device (100) itself on which the artificial intelligence according to the present disclosure is performed, or may be first performed through a separate server and / or system and then loaded into the memory (130) of the electronic device (100). Examples of learning algorithms include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the examples described above.

[0054] An artificial intelligence model may be composed of multiple neural network layers. Each of the multiple neural network layers has multiple weight values ​​and performs neural network operations by calculating the results of previous layers and the multiple weights. The multiple weights of the multiple neural network layers can be optimized based on the learning results of the artificial intelligence model. For example, the multiple weights may be updated during the learning process to reduce or minimize the loss or cost values ​​obtained by the artificial intelligence model.

[0055] Artificial neural networks may include deep neural networks (DNNs), such as, but not limited to, convolutional neural networks (CNNs), deep neural networks (DNNs), recurrent neural networks (RNNs), restricted boltzmann machines (RBMs), deep belief networks (DBNs), bidirectional recurrent deep neural networks (BRDNNs), generative adversarial networks (GANs), or deep Q-networks.

[0056] When executed by the processor (120), the artificial intelligence model identifies a top priority factor among multiple control factors received via the communication unit based on preset priority information, and selects a heating mode corresponding to the identified top priority factor. Furthermore, if the heating modes corresponding to a certain number or more of factors are identical, the same heating mode may be selected. A control method for controlling the operation of the humidifier (200) according to the execution of the artificial intelligence model will be described in detail again with reference to the drawings in the following section.

[0057] In the above, the description is based on the case where the processor (120) uses an artificial intelligence model. However, it is not necessarily limited thereto, and the processor (120) can perform calculations on its own based on mathematical formulas and data previously stored in the memory (130) without using an artificial intelligence model, thereby generating a signal for controlling the operation of the humidifier (200).

[0058] For example, the processor (120) can determine the operation of the humidifier (200) based on the following mathematical formula.

[0059] [Mathematical Formula 1]

[0060]

[0061] In mathematical expression 1 is the required humidity (L / h) needed to raise the current humidity to the target humidity, and V is the volume of the indoor space ( ), Xi is the indoor absolute humidity (kg / kg) after operating the humidifier (200), and Vi is the specific volume of Xi ( ), Xo is the absolute humidity (kg / kg) of the external space where the humidifier (200) is placed, and Vo is the specific volume of Xo ( ), n represents the number of ventilations per hour.

[0062] In mathematical expression 1, the indoor conditions before heating are assumed to be the same as the outdoor conditions, and the indoor temperature after heating is assumed to be 20℃ and the humidity is assumed to be 60%.

[0063] The processor (120) can control the operation of the humidifier (200) based on the size of the required humidification amount calculated by mathematical expression 1. For example, if the required humidification amount is equal to or greater than a preset first threshold value, the humidifier (200) can be operated in the strongest mode. If the required humidification amount is less than the first threshold value but greater than or equal to a second threshold value, the humidifier (200) can be operated in the strong mode. If the required humidification amount is less than the second threshold value, the humidifier (200) can be operated in the medium mode. The processor (120) can update the required humidification amount by performing calculations based on mathematical expression 1 from time to time or periodically. The processor (120) can readjust the heating mode of the humidifier (200) based on the updated required humidification amount.

[0064] Mathematical expression 1 is an operation expression set assuming that a humidity value is used among multiple control factors. In the case where control is to be performed based on another control factor among multiple control factors or based on a greater number of control factors, an operation expression different from Mathematical Expression 1 may be configured and stored in the memory (130).

[0065] The memory (130) is a configuration for storing various software, commands, control codes, and data required for the operation of the electronic device (100). The memory (130) may be implemented as at least one of various memories, such as DRAM (dynamic RAM), SRAM (static RAM), SDRAM (synchronous dynamic RAM), OTPROM (one time programmable ROM), PROM (programmable ROM), EPROM (erasable and programmable ROM), EEPROM (electrically erasable and programmable ROM), mask ROM, flash ROM, flash memory, hard drive, or solid state drive (SSD).

[0066] In FIG. 2, only one processor (120) and one memory (130) are illustrated, but this is not limited to the above, and the processor (120) and memory (130) may be implemented in various numbers and forms.

[0067] In addition, although in FIG. 2, the memory (130) is depicted as being a separate configuration from the processor (120), at least a portion of the memory (130) may be formed integrally with the processor (120).

[0068] As described above, when data is received from a humidifier (200) or other external devices connected through a communication unit (110), the memory (130) can store the received information under the control of the processor (120). The memory (130) stores information on sensing values ​​received from the humidifier (200) or other external devices and a plurality of control factors related to the humidifying operation.

[0069] Additionally, the memory (130) may store information related to the user account of the refrigerator. For example, if the electronic device (100) is implemented as a server device, the user can access the electronic device (100) using his or her mobile phone, computer, etc. The user can register a user account on the electronic device (100). When registering a user account, the user can input various information such as the user's name, age, model name of the humidifier being used, ID, and password. The processor (120) can create an account for the user using the information entered by the user and store information about the account in the memory (130).

[0070] In this state, when a sensing value is transmitted from a humidifier or other external devices owned by the user, the processor (120) can receive it through the communication unit (110) and store it in the memory (130) by matching it to the user's account. In addition, the memory (130) can also store information on a plurality of control factors related to the humidifying operation calculated by the processor (120) through the sensing value.

[0071] FIG. 3 is a graph for explaining a control method of a heating type humidifier according to at least one embodiment of the present disclosure, and FIG. 4 is a table showing an example of classifying heating modes according to the range of a plurality of control factors.

[0072] According to FIG. 3, the heated humidifier operates at a constant intensity during the initial heating period when operation is initiated, and then can selectively operate in multiple heating modes during the rated heating period after the initial heating period ends.

[0073] Referring to Fig. 3, the initial heating period may last approximately 3 hours after the humidifier is turned on or a user command is input to initiate humidification operation. During the initial heating period, the humidifier operates in an operating mode (e.g., the highest mode) that consumes a certain amount of power (e.g., 1000 W). The length of the initial heating period may be determined based on various criteria. For example, the period until water begins to boil may be determined as the initial heating period. In this case, the rated heating period may be switched from the point at which the water begins to boil and turns into steam.

[0074] When the humidifier operates in AI mode, it can perform humidification operation by selectively controlling the heater in multiple heating modes according to the judgment of the artificial intelligence model in the rated heating section.

[0075] For example, when the humidifying water temperature is less than 99 degrees (i.e., in the initial heating section), the humidifier (200) may not perform a heating mode switch. The heating mode may be implemented in various ways as described above. For example, the strongest mode may be a mode that operates at 1000 W, the strong mode at 700 W (42% of the heater capacity), the medium mode at 500 W (27% of the heater capacity), and the weak mode at 300 W (12% of the heater capacity). When the humidifier performs a humidifying operation in the rated heating section and the remaining water amount in the humidifier becomes insufficient, the user must replenish water. When the water is replenished, the temperature of the water decreases, so the humidifier can heat the water again while operating in the strongest mode (1000 W) for a certain section.

[0076] FIG. 4 is a diagram illustrating a method for determining a heating mode based on a plurality of control factors. Each of the plurality of control factors may be divided into a plurality of numerical ranges, and may be set to correspond to a plurality of heating modes for each numerical range and stored in advance in the memory (130) of the electronic device (100). The division of the numerical values ​​of each control factor and the setting of the corresponding heating mode for each numerical range may be automatically performed by an artificial intelligence model, or the optimal value may be found through a separate experiment and stored directly by the manufacturer or user.

[0077] Referring to Fig. 4, a case is shown where a total of five control factors are used, namely, a. indoor temperature, b. difference between target humidity value and current humidity value, c. target humidity, d. target humidification time, and e. residual water amount. The priority may be preset for each control factor. Fig. 4 shows a case where the priorities are in the order of b. difference between target humidity value and current humidity value, c. desired humidity, d. target humidification time, e. residual water amount, and a. indoor temperature.

[0078] Among these, a. In the case of indoor temperature, it can be seen that the numerical range of 18℃ or less is classified as weak, the numerical range of between 18℃ and 24℃ is classified as medium, and the numerical range of over 24℃ is classified as strong. In addition, b. In the case of the difference between the target humidity value and the current humidity value, it can be seen that the numerical range of over 10% is classified as weak, the numerical range of between 10% and over 5% is classified as medium, and the numerical range of under 5% is classified as strong. In addition, each control factor can be divided into multiple numerical ranges. The priority can be preset and stored for each control factor. The artificial intelligence model can check the combination conditions of each control factor and ultimately determine the heating mode.

[0079] For example, the artificial intelligence model identifies a top priority factor among multiple control factors received through the communication unit (110) based on preset priority information. The artificial intelligence model can select a heating mode corresponding to the identified top priority factor. Referring to FIG. 4,

[0080] If a is strong, b is weak, and c is medium, the artificial intelligence model determines the heating mode of the humidifier to be “weak” because b, which is the most important factor among these, is “weak.” The processor (120) generates a control signal for operating in the heating mode determined by the artificial intelligence model and transmits it to the humidifier (200) through the communication unit (110).

[0081] Meanwhile, according to another embodiment, even if there is a priority for each control factor, if a certain number of heating modes corresponding to a plurality of control factors are the same, the artificial intelligence model may ultimately select the heating mode determined by the plurality of control factors.

[0082] That is, the artificial intelligence model identifies a heating mode corresponding to each of a plurality of control factors received through the communication unit (110), and if the heating modes corresponding to a certain number or more of factors are the same, the same heating mode can be selected.

[0083] The processor (120) transmits a control signal to the humidifier through the communication unit (110) to operate in the heating mode selected by the artificial intelligence model.

[0084] For example, under the factor combination condition, if there are three or more “medium” factors, even if the highest priority factor is “weak,” the processor (120) transmits a control signal to drive in “medium” or “strong.”

[0085] Or, if a is strong, b is weak, c is weak, d is medium, and e is medium, then the highest priority factor b is “weak”, but a, d, and e have values ​​greater than medium, and there are two “mediums”, so the AI ​​model will select “medium”, which is the factor with the largest number, as the heating mode.

[0086] As another example, if a is strong, b is weak, c is weak, d is medium, and e is strong, there are three or more factors with values ​​greater than medium, and “strong” has the largest number of 2, so the AI ​​model will select “strong” as the heating mode.

[0087] As described above, the AI ​​model can determine the heating mode of the humidifier based on multiple control factors. The heating mode for each numerical range described in Figure 4 is merely an example, and the numerical range of the control factors and the corresponding heating mode can be configured in various ways.

[0088] Meanwhile, as described above, the time required to reach the target humidity may vary depending on various conditions such as the size of the space and the capacity of the heater. Even if power consumption is minimized using an artificial intelligence model, user satisfaction may decrease if it takes too long to reach the desired target humidity. In other words, the artificial intelligence model needs to control the operation of the humidifier so that the target humidity is reached within a certain tolerable time range. The tolerable time range can be experimentally measured based on user satisfaction and stored in advance in memory (130).

[0089] Fig. 5 is an example of a table that classifies the time it takes for a heated humidifier to reach the target humidity according to the heater capacity according to the space size. According to Fig. 5, the time it takes to reach the final humidity of 60%, 55%, and 50%, starting from 30% humidity, is indicated in minutes. This is an experimentally derived value, and the larger the space, the longer it takes for water vapor to fill the air, confirming that the time it takes to reach the target humidity is proportional to the space size. In Fig. 5, only three heating modes of the humidifier are shown, such as Mode 1 (heater capacity 42%), Mode 2 (heater capacity 27%), and Mode 3 (heater capacity 12%), but this is only an example, and the number of modes and their heater capacities may be changed in various ways.

[0090] A manufacturer of a humidifier or electronic device can train an artificial intelligence model to selectively determine a heating mode to reach a target humidity within an acceptable time range based on experimental data such as that in FIG. 5.

[0091] For example, if a humidifier is placed in a 10-pyeong space, the target humidity is 60%, the current humidity is 30%, and the allowable time range is approximately 120 minutes, the artificial intelligence model can alternately select mode 2 and mode 3. The processor (120) can generate a control signal to alternately change mode 2 and mode 3 based on the output value of the artificial intelligence model, and transmit the control signal to the humidifier.

[0092] FIG. 6 is a graph showing the correlation between temperature and target humidification reaching time according to at least one embodiment of the present disclosure.

[0093] According to Figure 6, the higher the temperature, the longer the humidification time. Human perception of "humidity" or "dryness" is related to relative humidity. Relative humidity is a value that represents the ratio of the amount of water vapor contained in the air compared to the saturation state at the current temperature. This is represented by the abbreviation "RH."

[0094] A relative humidity of 50% means the air currently contains half the amount of water vapor as saturated air. People perceive low relative humidity as dry, and high relative humidity as humid.

[0095] The higher the temperature, the more water vapor the atmosphere can hold.

[0096] As described above, the plurality of control factors may include temperature information. When the temperature information is received, the processor (120) may calculate the time required to reach the target humidity from the current temperature based on data such as that in FIG. 6. For example, if the current temperature is 23 degrees in FIG. 6, the time required to reach the target humidity may be calculated to be approximately 200 minutes in Mode 1 (humidification amount per hour of 400 ml / h), 120 minutes in Mode 2 (humidification amount per hour of 250 ml / h), and 75 minutes in Mode 3 (humidification amount per hour of 150 ml / h). If the allowable time range is 100 minutes, the artificial intelligence model may alternately select Mode 2 and Mode 3 to humidify to the target humidity within the allowable time range while minimizing power consumption. FIG. 7 is a graph showing that the required humidification amount increases as the indoor temperature increases. As described above, as the temperature increases, the amount of water vapor that the atmosphere can contain increases. Therefore, to maintain relative humidity, the atmosphere must contain more water vapor at higher temperatures than at lower temperatures. Based on indoor temperature information and data such as those shown in Figure 7, among the control factors, the AI ​​model can calculate the required amount of humidification and select a heating mode appropriate for that amount.

[0097] As described above, the electronic device (100) can control the humidifier (200) based on a plurality of control factors related to the humidifying operation of the humidifier (200). Information on each control factor can be received from the humidifier (200), but is not necessarily limited thereto, and at least one of the plurality of control factors can be received from another device.

[0098] FIG. 8 is a diagram for explaining a case where an electronic device according to at least one embodiment of the present disclosure receives a plurality of control factors related to a humidifying operation from a plurality of external devices (400-1 to 400-n) and a humidifier (200).

[0099] According to FIG. 8, the electronic device (100) can receive sensing values ​​related to a plurality of control factors related to the humidifying operation from an external device (400-1 to 400-n) as well as sensing values ​​of the humidifier through the communication unit (110).

[0100] Specifically, the external devices (400-1 to 400-n) may be different types of devices placed in the same space as the humidifier (200). Specifically, they may be air conditioners, air purifiers, refrigerators, robot vacuum cleaners, mobile projectors, etc., but various other electronic devices may also be included. Home appliances such as air conditioners, air purifiers, and refrigerators sometimes include sensors that can sense temperature or humidity. In this case, the electronic device (100) can receive information on external humidity and temperature from these types of external devices (e.g., 400-1). In addition, the robot vacuum cleaner (e.g., 400-n) or mobile projector can sense the shape or size of the space, etc., while driving within the space where the humidifier is placed, using a lidar sensor, etc. The electronic device (100) can receive information on the shape or size of the space where the humidifier is placed from these types of external devices.

[0101] A user can register information about various external devices (400-1 to 400-n) used together in a space where a humidifier (200) is placed in a server device (100) using his / her terminal device. Specifically, the user can access the electronic device (100) through an APP installed on a terminal device such as his / her mobile phone and create a unique account. The user can register information about the humidifier (200) and external devices (400-1 to 400-n) in his / her account. Based on this information, the electronic device (100) can receive information about a plurality of control factors from the humidifier (200) and external devices.

[0102] Accordingly, the electronic device (100) can control the operation of the humidifier using multiple control factors and an artificial intelligence model as described in the above-described section.

[0103] Meanwhile, the user can access the server device (100) using his / her terminal device and directly control devices such as a humidifier using the UI displayed on the terminal device.

[0104] FIG. 9 is a drawing for explaining the operation of a terminal device according to at least one embodiment of the present disclosure.

[0105] Referring to FIG. 9, the terminal device (400) can display a UI screen for controlling the operation of the humidifier. The terminal device (400) may be a mobile phone or tablet PC held by the user, but may also be implemented as various other types of display devices.

[0106] When an application for controlling the operation of various electronic products, including a humidifier, is executed by a user's selection, the terminal device (400) executes the application. When the application is executed, the terminal device (400) displays a UI screen generated by the application. Referring to FIG. 9, the UI screen may include a section (410) indicating various control factors such as the remaining water level of the humidifier, humidity, target humidity, temperature, etc., and a section (420) including a plurality of menus (421, 422, 423, 424) for selecting an operation mode of the humidifier. When the user selects one of these menus, the terminal device (400) may transmit a control signal corresponding to the selected menu to the electronic device (100) or the humidifier (200). Among the plurality of menus (421, 422, 423, 424), an AI mode menu (424) for automatically controlling operation using an artificial intelligence model may also be included.

[0107] When the AI ​​mode menu (424) is selected, the electronic device (100) or the humidifier (200) can automatically control the humidification operation of the humidifier (200) by changing the humidification operation in various ways using a plurality of control factors and an artificial intelligence model related to the humidification operation as described in the various embodiments described above.

[0108] Meanwhile, according to another embodiment of the present disclosure, when the AI ​​mode menu (424) is selected, the electronic device (100) or the humidifier (200) can determine whether the current state is a state in which operation in the AI ​​mode is possible. For example, when the remaining water amount is insufficient, or the current humidity is higher than the target humidity or there is little difference, even if operation in the AI ​​mode may not be much different from the general mode. In this case, the electronic device (100) or the humidifier (200) can determine that the current state is a state in which operation in the AI ​​mode is not possible. If it is determined that operation in the AI ​​mode is not possible, the electronic device (100) or the humidifier (200) can transmit a message to the terminal device (400) notifying that operation in the AI ​​mode is not possible. The terminal device (400) can display such a message on the UI screen.

[0109] If the AI ​​mode is not possible, the electronic device (100) or the humidifier (200) may operate in the normal mode. The normal mode refers to a mode in which it continues to operate in one arbitrarily set heating mode (e.g., medium mode). In the normal mode, the humidifier (200) may operate in the default heating mode (e.g., medium mode), or may continue to operate in the last operating mode based on information about the last operating heating mode (e.g., weak mode). Alternatively, when the user selects another menu (421, 422, 423) after checking a message on the UI screen of the terminal device (400), the humidifier (200) may operate in a mode corresponding to that menu.

[0110] The terminal device (400) may include various components such as a memory, a communication unit, a processor, and a display to perform the operation described in FIG. 9, but the illustration and description of these components are omitted.

[0111] Meanwhile, in the above-described embodiments, the electronic device (100) mainly describes a case in which the operation of the humidifier is controlled using an artificial intelligence model, but the humidifier may also directly perform the operations described in the above-described embodiments.

[0112] FIG. 10 is a block diagram showing the configuration of a humidifier (200) according to at least one embodiment of the present disclosure.

[0113] According to FIG. 10, the humidifier (200) includes a memory (230), a processor (220), at least one sensor (241-1 to 240-n), and a humidifying module (210).

[0114] The embodiment of Fig. 9 is a method in which the humidifier (200) does not communicate with an electronic device (100) or an external device (400-1 to 400-n), but has an artificial intelligence model built into the memory (230) of the humidifier (200), and the operation is controlled by the humidifier (200) itself.

[0115] The humidifying module (210) is a configuration for directly performing a humidifying operation. The humidifying module (210) may include a water collecting tank (211) for storing water, a heater (212) for heating the water in the water collecting tank (211), etc. In FIG. 10, only the water collecting tank (211) and the heater (212) are illustrated, but various other configurations may be further included, such as a heating plate or heating tube for transmitting heat generated from the heater (212), a water supply tube for supplying water in the water collecting tank (211) to the heating plate or heating tube, and a discharge port for discharging steam generated by heating of the heater (212). The shape of the humidifying module (210) may be modified in various ways depending on the size or appearance of the humidifier (200), and thus a specific illustration is omitted.

[0116] The sensors (240-1 to 240-n) are configured to sense various sensing items related to the humidifying operation of the humidifier (200). Specifically, the sensors (240-1 to 240-n) may include a temperature sensor and a humidity sensor. The temperature sensor and the humidity sensor may be implemented as an integrated unit. In addition, the sensors (240-1 to 240-n) may include a residual water level detection sensor for sensing the amount of water in the water collection tank (211). The residual water level detection sensor may be implemented as a level sensor that outputs an electric signal that varies depending on a magnetic body floating on the surface of water and a distance from the magnetic body, but is not necessarily limited thereto. For example, the residual water level detection sensor may be implemented as a sensor that is attached to a location a certain distance from the floor inside the water collection tank and outputs a different electric signal depending on whether or not it is in contact with water.

[0117] The processor (220) is configured to control the overall operation of the humidifier (200).

[0118] Specific examples of the processor (220) have been described in other embodiments described above, so redundant description is omitted.

[0119] The processor (220) identifies temperature and humidity based on values ​​sensed by at least one sensor (240-1 to 240-n), and calculates the time required to humidify to the target humidity. In addition, the processor (220) controls the operation of the humidifying module (210) to humidify to the target humidity in a power-saving state within a preset allowable time range based on information on a plurality of control factors including target humidity, temperature, humidity, time required, and the amount of residual water in the water collecting tank (211).

[0120] The processor (220) drives the humidifying module (210) during a preset initial heating period, and controls the humidifying module (210) to selectively change multiple heating modes based on the output values ​​of the artificial intelligence model during the rated heating period after the initial heating period. The algorithm of the artificial intelligence model used at this time and the multiple heating modes are as described above.

[0121] In addition, if the processor (220) detects that the remaining water level in the water tank (211) is below a standard value based on the sensing value of the sensor, the processor (220) may provide a message to the user through the display to fill the water in the water tank to a level above the standard value. Alternatively, the processor (220) may output a notification signal through a speaker to inform the user of the remaining water level.

[0122] The memory (230) stores an artificial intelligence model learned by data on power consumption for each combination of a plurality of control factors, and also stores a plurality of control factors related to sensing values ​​and humidifying operations. Since specific examples of the memory (230) have been described in other embodiments described above, redundant descriptions are omitted.

[0123] Meanwhile, compared to electronic devices that can be implemented as server devices, etc., the capacity of the processor (220) and memory (230) mounted on the humidifier (200) may be insufficient to load and execute an artificial intelligence model.

[0124] In this case, data such as the mathematical expression 1 described above may be stored in the memory (230). The processor (220) may perform an operation based on the mathematical expression 1 stored in the memory (230) and a plurality of control factors, and select a heating mode based on the operation result. Since the specific operation method and the heating mode selection method for the same have been specifically described in the above-described section, a duplicate description will be omitted.

[0125] FIG. 11 is a flowchart illustrating a control method for controlling a humidifier by an electronic device according to at least one embodiment of the present disclosure.

[0126] According to FIG. 11, an electronic device can receive information on a plurality of control factors related to a humidifying operation of a humidifier (S1110). The information on the plurality of control factors can be received directly from the humidifier or from an external device other than the humidifier. The electronic device generates a control signal for controlling the humidifying operation of the humidifier so that the humidifier can humidify to a target humidity in a power-saving state within a preset allowable time range using the plurality of control factors and an artificial intelligence model (S1120). The electronic device transmits the generated control signal to the humidifier (S1130).

[0127] The control method of FIG. 11 can be performed by an electronic device (100) having the configuration described in FIGS. 1 and 2, but is not necessarily limited thereto, and can also be performed by a device having a different configuration from that of FIG. 2.

[0128] FIG. 12 is a flowchart for explaining a method for controlling a humidifier according to at least one embodiment of the present disclosure.

[0129] According to Fig. 12, when the humidifier is powered on (S1210), it can wait for a user command. This state can be referred to as a standby state. In the standby state, the humidifier can receive user commands through various buttons or a touchscreen provided on the main body, or receive control signals from a server device or other terminal device and perform corresponding operations.

[0130] For example, if a user selects the AI ​​mode (S1220), the humidifier determines whether it can operate in the AI ​​mode (S1230). The AI ​​mode may be an operation mode in which an artificial intelligence model adaptively controls the operation of the humidifier, as described in the various embodiments described above. The humidifier can determine whether it can operate in the AI ​​mode by checking the values ​​of each control factor. Since the state in which it cannot operate in the AI ​​mode has been specifically described in the above-described section, a duplicate description will be omitted.

[0131] The humidifier operates in normal mode unless AI mode is required or can be operated in AI mode (S1240). Normal mode can be a state in which humidification is performed according to the heating mode selected by the user. For example, if the user selects the strongest mode, the humidifier can operate by applying an electric signal corresponding to the strongest mode to the heater so that the heater heats water as quickly as possible and produces as much moisture as possible after heating.

[0132] If the humidifier determines that it can operate in AI mode, it acquires multiple control factors (S1250). Examples of multiple control factors and methods for acquiring them have been specifically described in the above-described section, so a duplicate description will be omitted. If multiple control factors are acquired, the humidifier operates in AI mode, which performs a heating operation based on the output values ​​of the artificial intelligence model (S1260). Specifically, the humidifier operates the heater during a preset initial heating period, and selectively changes the multiple heating modes of the humidifier based on the output values ​​of the artificial intelligence model during a rated heating period after the initial heating period.

[0133] The control method described in Fig. 12 can be executed by a humidifier having the configuration of Fig. 9, but is not necessarily limited thereto, and may be executed by a humidifier having a different configuration.

[0134] Although various embodiments for controlling the operation of a humidifier have been individually described above, each embodiment may be implemented in whole or in part in combination with other embodiments in one electronic device, terminal device, humidifier, etc.

[0135] Additionally, the programs or commands for performing the various humidifier control methods described above may be provided stored on a non-transitory readable medium. The non-transitory readable medium may be loaded and used in a device capable of recalling the commands stored therein and performing operations according to the recalled commands. Accordingly, when the programs or commands stored on the non-transitory readable medium are executed by a processor, the processor may directly, or under the control of the processor, utilize other components to perform the operations described in the various embodiments described above.

[0136] A non-transitory computer-readable medium refers to a medium that permanently stores data and can be read by a device, rather than a medium that stores data for a short period of time, such as a register, cache, or memory. Specific examples of non-transitory computer-readable media include CDs, DVDs, hard disks, Blu-ray discs, USBs, memory cards, and ROMs.

[0137] Instructions may include code generated or executed by a compiler or interpreter. The machine-readable storage medium may be provided in the form of a non-transitory storage medium. Here, "non-transitory" means that the storage medium does not contain signals and is tangible, but does not distinguish between whether data is stored semi-permanently or temporarily on the storage medium.

[0138] Furthermore, according to one embodiment of the present disclosure, the method according to the various embodiments described above may be provided as a computer program product. The computer program product may be traded as a product between a seller and a buyer. The computer program product may be implemented as a product distributed online through an application store, in addition to the non-transitory readable recording medium described above. In the case of online distribution, at least a portion of the computer program product may be temporarily stored or temporarily generated in a storage medium such as the memory of a manufacturer's server, an application store's server, or a relay server.

[0139] While the present invention has been described with reference to the attached drawings, the scope of the present invention is determined by the claims described below and should not be construed as being limited to the aforementioned embodiments and / or drawings. Furthermore, it should be clearly understood that improvements, modifications, and variations apparent to those skilled in the art, as defined in the claims, are also included within the scope of the present invention.

Claims

1. In electronic devices, Department of Communications; Memory where the artificial intelligence model is stored; and Processor; including; The above processor, When information on multiple control factors related to the humidifying operation of the humidifier is received through the communication unit, By using the above plurality of control factors and the artificial intelligence model, a control signal for controlling the humidification operation of the humidifier is transmitted to the humidifier through the communication unit so that the humidifier can humidify to the target humidity in a power-saving state within a preset allowable time range. An electronic device, wherein the above artificial intelligence model is a model learned by data on power consumption for each combination of multiple control factors.

2. In paragraph 1, The above multiple control factors are, An electronic device comprising at least one control factor among humidity before the humidifying operation is performed, target humidity, temperature, humidifying time required to reach the target humidity, and residual water amount.

3. In paragraph 2, The above multiple control factors are, Further including information on the shape or size of the space in which the above humidifier is placed, The above processor is an electronic device that changes the allowable time range differently depending on the shape or size of the space.

4. In paragraph 1, The above humidifier is a heated humidifier, The above processor, When the operation of the humidifier is initiated, the heater of the humidifier is operated during a preset initial heating period, and a control signal for selectively changing multiple heating modes of the humidifier based on the output value of the artificial intelligence model during a rated heating period after the initial heating period is generated and transmitted to the humidifier. Electronic devices.

5. In paragraph 1, Each of the above plurality of control factors is divided into a plurality of numerical ranges, and is set to correspond to a plurality of heating modes for each numerical range and stored in the memory. The above artificial intelligence model, Among the plurality of control factors received through the above communication unit, the highest priority factor is identified based on preset priority information, and a heating mode corresponding to the identified highest priority factor is selected. The above processor is an electronic device that transmits a control signal to the humidifier through the communication unit for operating in the heating mode selected by the artificial intelligence model.

6. In paragraph 1, Each of the above plurality of control factors is divided into a plurality of numerical ranges, and is set to correspond to a plurality of heating modes for each numerical range and stored in the memory. The above artificial intelligence model, The heating mode corresponding to each of the plurality of control factors received through the above communication unit is identified, and if the heating modes corresponding to a certain number or more of factors are the same, the same heating mode is selected. The above processor is an electronic device that transmits a control signal to the humidifier through the communication unit for operating in the heating mode selected by the artificial intelligence model.

7. In the humidifier, Memory that stores information about the preset target humidity; processor; at least one sensor; and A humidifying module for performing humidification using water collected in a water collecting tank; The above processor, Identifying the temperature and humidity based on the sensing values ​​of at least one sensor, and calculating the time required to humidify to the target humidity, A humidifier that controls the operation of the humidifying module to humidify to the target humidity in a power-saving state within a preset allowable time range based on information about a plurality of control factors including the target humidity, temperature, humidity, the required time, and the amount of remaining water in the water tank.

8. In paragraph 7, The above memory stores an artificial intelligence model learned by data on power consumption for each combination of the above multiple control factors, The above humidifying module can operate in multiple heating modes, The above processor, A humidifier that operates the humidifying module during a preset initial heating period and controls the humidifying module to selectively change the plurality of heating modes based on output values ​​of the artificial intelligence model during a rated heating period after the initial heating period.

9. In a method for controlling a humidifier in an electronic device, A step of receiving information on a plurality of control factors related to the humidifying operation of the humidifier; A step of generating a control signal for controlling the humidification operation of the humidifier so that the humidifier can humidify to a target humidity in a power-saving state within a preset allowable time range by using the plurality of control factors and the artificial intelligence model; and A method for controlling a humidifier, comprising: a step of transmitting the control signal to the humidifier.

10. In paragraph 9, The above multiple control factors are, A humidifier control method comprising at least one control factor among humidity before the humidifying operation is performed, target humidity, temperature, humidifying time required to reach the target humidity, and residual water amount.

11. In paragraph 10, The above multiple control factors are, Further including information on the shape or size of the space in which the above humidifier is placed, The above humidifier control method is, A humidifier control method further comprising a step of differently changing the allowable time range according to the shape or size of the space.

12. In paragraph 9, The step of generating a control signal for controlling the humidifying operation of the above humidifier is: A humidifier control method, wherein, if the humidifier is a heating-type humidifier, the heater of the humidifier is driven during a preset initial heating period, and a control signal is generated for selectively changing a plurality of heating modes of the humidifier based on the output values ​​of the artificial intelligence model during a rated heating period after the initial heating period.

13. In paragraph 9, Each of the above plurality of control factors is divided into a plurality of numerical ranges, and is set to correspond to a plurality of heating modes for each numerical range and is stored in advance in the electronic device. The step of generating a control signal for controlling the humidifying operation of the above humidifier is: The above artificial intelligence model Identifying the highest priority factor among the received plurality of control factors based on preset priority information, A step of selecting a heating mode corresponding to the numerical value of the identified priority factor; A method for controlling a humidifier, comprising: a step of generating a control signal for operating in the selected heating mode.

14. In paragraph 9, Each of the above plurality of control factors is divided into a plurality of numerical ranges, and is set to correspond to a plurality of heating modes for each numerical range and is stored in advance in the electronic device. The step of generating a control signal for controlling the humidifying operation of the above humidifier is: The above artificial intelligence model, Identifying a heating mode corresponding to each numerical value of the received plurality of control factors, If the heating modes corresponding to a certain number or more of factors are the same, a step of selecting the same heating mode; and A method for controlling a humidifier, comprising the step of transmitting a control signal to the humidifier for operating in the selected heating mode.

15. In a non-transitory computer-readable medium storing one or more instructions executed by a control unit of an electronic device to cause a humidifier to perform an operation, The above actions are, A step of receiving information on a plurality of control factors related to the humidifying operation of the humidifier; A step of generating a control signal for controlling the humidification operation of the humidifier so that the humidifier can humidify to a target humidity in a power-saving state within a preset allowable time range by using the plurality of control factors and the artificial intelligence model; and A computer-readable recording medium comprising: a step of transmitting the control signal to the humidifier.

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