Electronic device for controlling heating temperature based on temperature change of food and method for controlling same

Abstract

An electronic device is disclosed. The electronic device includes: a heating unit that heats food; a communication interface receiving a sensing value from an external sensor; a memory storing at least one instruction; and at least one processor connected with the memory and controlling the electronic device. The at least one processor executes at least one instruction to acquire information about a temperature of the food product from the external sensor, identify a heating temperature corresponding to a change pattern of the temperature of the food product, and control the heating unit to heat the food product at the heating temperature.

Description

Technical Field

[0001] The present disclosure relates to an electronic device and a control method thereof, and more particularly, to an electronic device and a control method thereof for controlling a heating temperature based on a temperature change of a cooking object. Background Art

[0002] The cooking apparatus may perform various cooking functions such as grilling, frying, boiling, etc. Generally speaking, a conventional cooking apparatus may cook a cooking object at a heating temperature set by a user.

[0003] In this case, when heating the cooking object, there is a problem in that the user must manually set the heating temperature according to the cooking object so that the cooking object does not overflow from the cooking container. Summary of the invention

[0004] Technical Solutions

[0005] According to one or more embodiments of the present disclosure, an electronic device includes: a heating component that heats a cooking object; a communication interface that receives a sensing value from an external sensor; a memory that stores at least one instruction; and at least one processor that is connected to the memory and controls the electronic device, wherein the at least one processor is configured to: obtain information about the temperature of the cooking object from the external sensor by executing at least one instruction, identify a heating temperature corresponding to a change pattern of the temperature of the cooking object, and control the heating component to heat the cooking object at the heating temperature.

[0006] A control method of an electronic device according to one or more embodiments of the present disclosure includes acquiring information about a temperature of a cooking object from an external sensor, identifying a heating temperature corresponding to a variation pattern of the temperature of the cooking object, and heating the cooking object at the heating temperature.

[0007] In a non-transitory computer-readable recording medium including a program for executing a control method for an electronic device according to one or more embodiments of the present disclosure, the control method includes the following steps: acquiring information about the temperature of a cooking object from an external sensor, identifying a heating temperature corresponding to a change pattern of the temperature of the cooking object, and heating the cooking object at the heating temperature. BRIEF DESCRIPTION OF THE DRAWINGS

[0008] The above and other aspects, features and advantages of certain embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the accompanying drawings, in which:

[0009] Figure 1 is a block diagram showing a configuration of an electronic device according to one or more embodiments of the present disclosure;

[0010] Figure 2is a perspective view showing an electronic device and an external sensor according to one or more embodiments of the present disclosure;

[0011] Figure 3 is a flow chart showing a method for an electronic device to heat a cooking object according to one or more embodiments of the present disclosure;

[0012] Figure 4a and Figure 4b is a diagram showing information for the temperature of a cooking object according to one or more embodiments of the present disclosure;

[0013] Figure 5 is a flowchart illustrating a method for an electronic device to identify a change pattern of a temperature of a cooking object according to one or more embodiments of the present disclosure;

[0014] Figure 6 is a flowchart illustrating a method for an electronic device to identify a heating temperature of a cooking object according to one or more embodiments of the present disclosure;

[0015] Figure 7a and Figure 7b is a diagram illustrating a method for an electronic device to recognize a change pattern of a temperature of a cooking object according to one or more embodiments of the present disclosure;

[0016] Figure 8 is a flowchart illustrating a method for an electronic device to identify a change pattern of a temperature of a cooking object according to one or more embodiments of the present disclosure;

[0017] Figures 9a to 9c is a diagram illustrating a method for an electronic device to recognize a change pattern of a temperature of a cooking object according to one or more embodiments of the present disclosure;

[0018] Fig.10 is a flowchart illustrating a method for an electronic device to heat a cooking object based on a water level of the cooking object according to one or more embodiments of the present disclosure; and

[0019] Fig.11 is a sequence diagram illustrating a method for an electronic device to control an external cooking device according to one or more embodiments of the present disclosure. DETAILED DESCRIPTION

[0020] Various modifications may be made to the embodiments of the present disclosure, and there may be one or more types of embodiments. Accordingly, specific embodiments will be shown in the drawings, and the embodiments will be described in detail in the specific description. However, it should be noted that one or more embodiments are not intended to limit the scope of the present disclosure to specific embodiments, but should be interpreted as including all modifications, equivalents or alternatives of the embodiments of the present disclosure. In addition, with respect to the detailed description of the drawings, similar components may be designated by similar reference numerals.

[0021] Furthermore, in describing the present disclosure, in the case where it is determined that a detailed description of a related known function or feature may unnecessarily obscure the gist of the present disclosure, the detailed description will be omitted.

[0022] In addition, the embodiments herein can be modified in various forms, and the scope of the technical ideas of the present disclosure is not limited to the embodiments herein. On the contrary, these embodiments are provided to make the present disclosure more complete and comprehensive, and to fully convey the technical ideas of the present disclosure to those skilled in the art.

[0023] In addition, the terms used in the present disclosure are only used to describe specific embodiments and are not intended to limit the scope of the present disclosure. In addition, unless clearly defined differently in the context, a singular expression includes a plural expression.

[0024] Furthermore, in the present disclosure, expressions such as “have”, “may have”, “include”, and “may include” indicate the presence of such characteristics (for example, elements such as numbers, functions, operations, and components), and do not exclude the presence of additional features.

[0025] In addition, in the present disclosure, expressions such as "A or B", "at least one of A and / or B", or "one or more of A and / or B" may include all possible combinations of the listed items. For example, "A or B", "at least one of A and B", or "at least one of A or B" may refer to all of the following situations: (1) including at least one A, (2) including at least one B, or (3) including at least one A and at least one B.

[0026] In addition, the expressions "first", "second", etc. used in the present disclosure may describe various elements, regardless of their order and / or importance. In addition, these expressions are only used to distinguish one element from another element, and are not intended to limit the elements.

[0027] Meanwhile, the description in the present disclosure that one element (e.g., a first element) is “(operably or communicatively) coupled” to another element (e.g., a second element) and / or is “(operably or communicatively) coupled to” another element (e.g., the second element), or is “connected to” another element (e.g., the second element) should be interpreted as including the following two cases: the case where the one element is directly coupled to the other element, and the case where the one element is coupled to the other element via another element (e.g., a third element).

[0028] In contrast, description that one element (eg, a first element) is “directly coupled” or “directly connected” to another element (eg, a second element) may be interpreted to mean that another element (eg, a third element) does not exist between the one element and the other element.

[0029] Furthermore, the expression "configured to" used in the present disclosure may be used interchangeably with other expressions such as "suitable for", "capable of", "designed to", "suitable for", "manufactured to", and "capable of" depending on the situation. Meanwhile, the term "configured to" does not necessarily mean that a device is "specially designed to" in terms of hardware.

[0030] On the contrary, in some cases, the expression "a device configured to..." may mean that the device is "capable" of performing an operation together with another device or component. For example, the phrase "a processor configured to perform A, B, and C" may mean a dedicated processor (e.g., an embedded processor) for performing the corresponding operations, or a general-purpose processor (e.g., a CPU or an application processor) that can perform the corresponding operations by executing one or more software programs stored in a memory device.

[0031] In addition, in the embodiments of the present disclosure, a "module" or "component" may perform at least one function or operation, and may be implemented as hardware or software, or a combination of hardware and software. In addition, multiple "modules" or "components" may be integrated into at least one module and implemented as at least one processor, excluding "modules" or "components" that need to be implemented as specific hardware.

[0032] Meanwhile, various elements and regions in the drawings are schematically shown. Accordingly, the technical concept of the present disclosure is not limited by the relative sizes or intervals shown in the drawings.

[0033] Hereinafter, embodiments according to the present disclosure will be described in detail so that a person having ordinary skill in the technical field to which the present disclosure pertains can easily implement the embodiments with reference to the accompanying drawings.

[0034] Figure 1 is a block diagram illustrating a configuration of an electronic device according to one or more embodiments of the present disclosure.

[0035] The electronic device 100 may include a memory 110, a communication interface 120, a user interface 130, a heating member 140, and at least one processor 150. In the electronic device 100, some of the above components may be omitted, and other components may be further included.

[0036] In addition, the electronic device 100 may be a cooking device for heating a cooking object. Figure 2 The induction device shown is, however, only an example, and the electronic device 100 may be a strong light device, a gas oven, an electric oven, a microwave oven, a gas stove, etc.

[0037] Alternatively, the electronic device 100 may be a device for controlling a cooking device. For example, the electronic device 100 may be implemented as a smart phone, a mobile phone, a server, a personal digital assistant (PDA), a laptop computer, a media player, an e-book reader, a terminal for digital broadcasting, a navigation, a self-service terminal, an MP3 player, a wearable device, a home appliance, and other mobile or non-mobile computing devices, and communicate with the cooking device via a wired or wireless manner to control the cooking device.

[0038] The memory 110 may store at least one instruction regarding the electronic device 100. In addition, the memory 110 may store an operating system (O / S) for driving the electronic device 100. In addition, the memory 110 may store various types of software programs or applications for the electronic device 100 to operate according to one or more embodiments of the present disclosure. In addition, the memory 110 may include a semiconductor memory (e.g., a flash memory) or a magnetic storage medium (e.g., a hard disk).

[0039] Specifically, the memory 110 may store various types of software modules for the electronic device 100 to operate according to one or more embodiments of the present disclosure, and the processor 150 may control the operation of the electronic device 100 by executing the various types of software modules stored in the memory 110. That is, the memory 110 may be accessed by the processor 150, and the processor 150 may perform reading / recording / correction / deletion / update of data, etc.

[0040] Meanwhile, in the present disclosure, the term “memory 110 ” may be used as a meaning including the memory 110 , a ROM or RAM inside the processor 150 , or a memory card (eg, micro SD card, memory stick) mounted on the electronic device 100 .

[0041] In addition, the communication interface 120 includes a circuit, and it is a component capable of communicating with an external device or server. The communication interface 120 can perform communication with an external device or server based on a wired or wireless communication method. The communication interface 120 may include a Bluetooth module, a Wi-Fi module, an infrared (IR) module, a local area network (LAN) module, an Ethernet module, etc. Here, each communication module may be implemented as at least one hardware chip. The wireless communication module may include at least one communication chip, which performs communication according to various wireless communication protocols (e.g., Zigbee, Universal Serial Bus (USB), Mobile Industry Processor Interface Camera Serial Interface (MIPICSI), third generation (3G), third generation partnership project (3GPP), long term evolution (LTE), advanced LTE (LTE-A), fourth generation (4G), fifth generation (5G), etc.) in addition to the aforementioned communication methods.

[0042] refer to Figure 2 , the electronic device 100 may acquire a sensing value of the external sensor 200 from the external sensor 200 through the communication interface 120. Here, the external sensor 200 may be a sensor that is held on the cooking container 220 and is used to measure the temperature or water level of the cooking object 210. That is, the electronic device 100 may acquire information about the temperature of the cooking object 210 and information about the water level of the cooking object 210 inside the cooking container 220 from the external sensor 200. Here, the cooking object 210 may be water or water containing foreign matter (e.g., soup). In addition, the cooking object 210 may be contained in the cooking container 220 (e.g., a pot).

[0043] The user interface 130 is a component for receiving user command input for controlling the electronic device 100. The user interface 130 may be implemented as a device such as a button, a touch pad, a mouse, a keyboard, or as a touch screen capable of performing both a display function and a manipulation input function. Here, the button may be various types of buttons formed in any area (front surface portion or side surface portion, rear surface portion, etc.) outside the main body of the electronic device 100, such as a mechanical button, a touch pad, a scroll wheel, etc. The electronic device 100 may obtain various user inputs through the user interface 130. In addition, the electronic device 100 may obtain user input for heating a cooking object through the user interface 130. Here, the user input for heating a cooking object may be a user input for setting at least one of a heating temperature, a heating degree, a heating level, or a heating mode.

[0044] The heating component 140 may include a component for heating a cooking object or a cooking container and a driving circuit that drives the component for heating the cooking object or the cooking container. For example, the heating component 140 may include a coil that generates a magnetic field and a driving circuit that drives the coil. Alternatively, the heating component 140 may include a heating wire that generates heat and a driving circuit that drives the heating wire.

[0045] At least one processor 150 may control the overall operation and functions of the electronic device 100. Specifically, the at least one processor 150 is connected to components of the electronic device 100 (including the memory 110), and controls the overall operation of the electronic device 100 by executing at least one instruction stored in the memory 110 as described above.

[0046] At least one processor 150 may include one or more of a central processing unit (CPU), a graphics processing unit (GPU), an accelerated processing unit (APU), a majority integrated core (MIC), a digital signal processor (DSP), a neural processing unit (NPU), a hardware accelerator, or a machine learning accelerator. At least one processor may control one or a random combination of other components of the electronic device and perform operations related to communication or data processing. In addition, at least one processor may execute one or more programs or instructions stored in a memory. For example, at least one processor may execute a method according to one or more embodiments of the present disclosure by executing at least one instruction stored in a memory.

[0047] When the method according to one or more embodiments of the present disclosure includes multiple operations, the multiple operations may be performed by one processor, or by multiple processors. For example, when the method according to one or more embodiments performs the first operation, the second operation, and the third operation, the first operation, the second operation, and the third operation may all be performed by the first processor, or the first operation and the second operation may be performed by the first processor (e.g., a general-purpose processor), and the third operation may be performed by the second processor (e.g., an artificial intelligence-specific processor).

[0048] At least one processor may be implemented as a single-core processor including one core, or may be implemented as at least one multi-core processor including multiple cores (e.g., multi-cores of the same type or multi-cores of different types). In the case where at least one processor is implemented as a multi-core processor, each of the multiple cores included in the multi-core processor may include an internal memory of the processor (e.g., a buffer memory, an on-chip memory, etc.), and a common cache shared by the multiple cores may be included in the multi-core processor. In addition, each of the multiple cores (or some of the multiple cores) included in the multi-core processor may independently read a program instruction for implementing the method according to one or more embodiments of the present disclosure and execute the instruction, or all (or some) of the multiple cores may be linked to each other and read a program instruction for implementing the method according to one or more embodiments of the present disclosure and execute the instruction.

[0049] In the case where the method according to one or more embodiments of the present disclosure includes multiple operations, the multiple operations may be performed by one of the multiple cores included in the multi-core processor, or by multiple cores. For example, when the first operation, the second operation, and the third operation are performed by the method according to one or more embodiments of the present disclosure, the first operation, the second operation, and the third operation may all be performed by the first core included in the multi-core processor, or the first operation and the second operation may be performed by the first core included in the multi-core processor, and the third operation may be performed by the second core included in the multi-core processor.

[0050] In one or more embodiments of the present disclosure, a processor may mean a system on a chip (SoC) on which at least one processor and other electronic components are integrated, a single-core processor, a multi-core processor, or a core included in a single-core processor or a multi-core processor. In addition, here, the core may be implemented as a CPU, a GPU, an APU, a MIC, a DSP, an NPU, a hardware accelerator, a machine learning accelerator, etc., but the embodiments of the present disclosure are not limited thereto.

[0051] The operations of at least one processor 150 for implementing one or more embodiments of the present disclosure may be implemented through a plurality of modules.

[0052] Specifically, data about multiple modules according to the present disclosure can be stored in the memory 110, and at least one processor 150 can access the memory 110 and load the data about the multiple modules into the memory or buffer inside the at least one processor 150, and then implement one or more embodiments according to the present disclosure by using the multiple modules.

[0053] Meanwhile, at least one of the plurality of modules of the present disclosure may be implemented as hardware and may be included inside at least one processor 150 in the form of a system on chip.

[0054] Alternatively, at least one of the plurality of modules according to the present disclosure may be implemented as a separate external device, and the electronic device 100 and each module may perform the operation according to the present disclosure by communicating with each other.

[0055] Hereinafter, the operation of the processor according to the present disclosure will be described in detail.

[0056] refer to Figure 3 In operation S310, the at least one processor 150 may obtain a user input for heating a cooking object through the user interface 130. Here, the user input for heating a cooking object may be a user input for setting at least one of a heating temperature, a heating degree, a heating level, or a heating mode.

[0057] When a user input for heating a cooking object is acquired, the at least one processor 150 may control the heating part 140 to heat the cooking object in operation S320.

[0058] Furthermore, while the cooking object is being heated, in operation S330, the at least one processor 150 may acquire information about the temperature of the cooking object from the external sensor 200 through the communication interface 120. Specifically, when a user input for heating the cooking object is acquired, the at least one processor 150 may transmit a request signal for acquiring information about the temperature of the cooking object to the external sensor 200. Then, while the cooking object is being heated, the at least one processor 150 may acquire information about the temperature of the cooking object from the external sensor 200.

[0059] Here, the information about the temperature of the cooking object may be represented as a graph indicating the temperature value of the cooking object according to the heating time, such as Figure 4a and Figure 4b shown. Figure 4a It may mean, in the case where the cooking object is water, a change 410 in the temperature of water while the water is being heated. Figure 4b It may mean a change 420 in the temperature of the water containing foreign matter when the cooking object is water containing foreign matter.

[0060] Then, when acquiring information about the temperature of the cooking object, at least one processor 150 may identify a heating temperature corresponding to a change pattern of the temperature of the cooking object in operation S340. When the heating temperature is identified, at least one processor 150 may control the heating part 140 to heat the cooking object at the identified heating temperature in operation S350. In this case, the heating temperature corresponding to the change pattern of the temperature of the cooking object may refer to a temperature for preventing a phenomenon in which the cooking object overflows outside the cooking container.

[0061] Meanwhile, according to one or more embodiments of the present disclosure, at least one processor 150 may monitor information about the temperature of a cooking object while the cooking object is being heated, and identify a heating temperature corresponding to a change pattern of the temperature of the cooking object based on whether the temperature of the cooking object becomes a specific temperature.

[0062] Specifically, refer to Figure 5 , in operation S510, the at least one processor 150 may heat the cooking object at a heating temperature set based on a user input for heating the cooking object.

[0063] Then, in operation S520, the at least one processor 150 may acquire information about the temperature of the cooking object while the cooking object is being heated. Then, in operation S530, the at least one processor 150 may identify whether the temperature of the cooking object is higher than or equal to a specific temperature. Here, the information about the specific temperature may be stored in the memory 110.

[0064] If it is identified in operation S530-N that the temperature of the cooking object is lower than the specific temperature, in operation S510, the at least one processor 150 may continuously heat the cooking object.

[0065] If it is identified in operation S530-YES that the temperature of the cooking object is higher than or equal to the specific temperature, in operation S540, the at least one processor 150 may identify a change pattern of the temperature of the cooking object.

[0066] Then, in operation S550, the at least one processor 150 may identify a heating temperature corresponding to a variation pattern of the temperature of the cooking object.

[0067] Meanwhile, the change pattern of the temperature of the cooking object may mean the degree to which the temperature of the cooking object changes while the temperature of the cooking object rises. That is, the at least one processor 150 may recognize a value indicating the degree to which the temperature of the cooking object changes while the temperature of the cooking object rises.

[0068] Here, the at least one processor 150 may identify the heating temperature by comparing the degree of temperature change of the cooking object with a predetermined value. Figure 6 , in operation S610, the at least one processor 150 may acquire a value indicating a degree of temperature change of a cooking object.

[0069] Then, in operation S620, the at least one processor 150 may identify whether a value indicating a degree of temperature change of the cooking object is less than or equal to a predetermined value.

[0070] If the value indicating the degree of temperature change of the cooking object is less than or equal to the predetermined value in operation S620-Yes, the at least one processor 150 may identify the first temperature as the heating temperature in operation S630. Meanwhile, if the value indicating the degree of temperature change of the cooking object exceeds the predetermined value in operation S620-No, the at least one processor 150 may identify the second temperature lower than the first temperature as the heating temperature in operation S640. Here, information about the predetermined value and the first and second temperatures may be stored in the memory 110.

[0071] Alternatively, the at least one processor 150 may identify a heating temperature corresponding to a value indicating a degree of temperature change of the cooking object. Here, information about the heating temperature corresponding to the value indicating a degree of temperature change of the cooking object may be stored in the memory 110. That is, as the value indicating a degree of temperature change of the cooking object increases or decreases, the heating temperature corresponding to the value indicating a degree of temperature change of the cooking object may change linearly or nonlinearly.

[0072] Furthermore, when the heating temperature is identified, in operation S650, the at least one processor 150 may control the heating part 140 to heat the cooking object at the identified heating temperature.

[0073] At the same time, reference will be made to Figure 7a and Figure 7b A detailed method for the at least one processor 150 to identify a value indicating a degree of temperature change of a cooking object is described below.

[0074] According to one or more embodiments of the present disclosure, at least one processor 150 may obtain information about Figure 7a The information of the straight line 740 in the diagram 710 (i.e., the temperature data set) of the temperature change of the cooking object shown, the straight line 740 connects the point 720 indicating the temperature value of the cooking object at the first time point and the point 730 indicating the temperature value of the cooking object at the second time point. Here, the first time point may mean the starting point of heating or the initial time point when the temperature of the cooking object is obtained. In addition, the second time point may mean the time point when the temperature of the cooking object is a specific temperature. Here, the information about the specific temperature may be stored in the memory 110.

[0075] Then, the at least one processor 150 may acquire a value indicating a deviation between the graph 710 of the temperature data set reflecting the temperature change of the cooking object and the acquired straight line 740. Then, the at least one processor 150 may identify a heating temperature corresponding to the acquired value indicating the deviation.

[0076] Specifically, the at least one processor 150 may acquire a mean absolute error (MAE) value between the graphical representation 710 of the temperature variation of the cooking object and the straight line 740. Then, the at least one processor 150 may identify a heating temperature corresponding to the acquired MAE value.

[0077] Here, if the acquired MAE value is less than or equal to a predetermined value, the at least one processor 150 may identify the first temperature as a heating temperature. Meanwhile, if the acquired MAE value exceeds a predetermined value, the at least one processor 150 may identify a second temperature lower than the first temperature as a heating temperature.

[0078] According to one or more embodiments of the present disclosure, at least one processor 150 may Figure 7b The temperature change of the cooking object between the first time point 720 and the second time point 730 in the diagram 710 of the temperature change of the cooking object shown in the figure is subjected to regression analysis to obtain the straight line 750. For example, the at least one processor 150 may obtain the straight line 750 by using a linear regression analysis method using a least square method, but this is only an example, and the at least one processor 150 may obtain the straight line 750 by using various regression analysis methods.

[0079] Then, the at least one processor 150 may acquire a value of a deviation between the graph 710 indicating the temperature change of the cooking object and the acquired straight line 750. Then, the at least one processor 150 may identify a heating temperature corresponding to the acquired value indicating the deviation.

[0080] Specifically, the at least one processor 150 may obtain a mean absolute error (MAE) value between the straight line 750 obtained by performing regression analysis on the temperature change of the cooking object and the temperature change of the cooking object. Then, the at least one processor 150 may obtain a heating temperature corresponding to the MAE value.

[0081] That is, if the acquired MAE value is less than or equal to the predetermined value, the at least one processor 150 may identify the first temperature as the heating temperature. Meanwhile, if the acquired MAE value exceeds the predetermined value, the at least one processor 150 may identify the second temperature lower than the first temperature as the heating temperature.

[0082] Meanwhile, in the present disclosure, a value indicating the degree of change in the temperature of the cooking object or a value indicating the deviation between the graph of the temperature of the cooking object and the acquired straight line may be a MAE value. However, this is only an example, and these values ​​may be implemented as various values ​​for indicating the degree of change in the temperature of the cooking object or for indicating the deviation between the temperature of the cooking object and the acquired straight line, such as a mean square error (MSE) value, etc.

[0083] Meanwhile, when the cooking object is heated based on the recognized heating temperature, the type of the cooking object may be changed. For example, after heating water to a specific temperature, various food ingredients may be introduced into the water. Here, if the type of the cooking object is changed, the at least one processor 150 may re-recognize the heating temperature. Then, the at least one processor 150 may control the heating component 140 to heat the cooking object at the re-recognized heating temperature.

[0084] Specifically, refer to Figure 8 In operation S810, at least one processor 150 may recognize that the temperature of the cooking object decreases by T between the first time point and the second time point. Here, the first time point may mean a time point when the temperature of the cooking object starts to decrease. Meanwhile, the second time point may mean a time point when the temperature of the cooking object starts to increase.

[0085] Then, in operation S820, the at least one processor 150 may identify whether T is greater than or equal to a predetermined value. If in operation S820-Yes, T is greater than or equal to the predetermined value (i.e., if the temperature of the cooking object decreases from the first time point to the second time point by greater than or equal to the predetermined value), then in operation S830, the at least one processor 150 may identify a change pattern of the temperature of the cooking object starting from the second time point. Then, in operation S850, the at least one processor 150 may identify a heating temperature corresponding to the change pattern of the temperature of the cooking object starting from the second time point.

[0086] If T is less than the predetermined value in operation S820-No (i.e., if the temperature of the cooking object decreases less than the predetermined value from the first time point to the second time point), in operation S840, the at least one processor 150 may identify a change pattern of the temperature of the cooking object starting from the first time point. Then, in operation S850, the at least one processor 150 may identify a change pattern of the temperature of the cooking object starting from the first time point.

[0087] Specifically, at least one processor 150 may obtain information about Figure 9a The information (i.e., temperature data set) of the graphical representation 910 of the temperature change of the cooking object shown. Here, at the first time point 920, foreign matter may be introduced into the cooking object, and the temperature of the cooking object may have been decreasing before the second time point 930. Here, the difference between the temperature value of the cooking object at the first time point 920 and the temperature value of the cooking object at the second time point 930 may be T. Here, if T is greater than or equal to a predetermined value, the at least one processor 150 may exclude the temperature of the cooking object before the second time point 930, and identify a heating temperature corresponding to a change pattern of the temperature of the cooking object starting from the second time point 930.

[0088] That is, the at least one processor 150 may acquire a value indicating the degree to which the temperature of the cooking object has changed from the second time point 930. Then, the at least one processor 150 may identify a heating temperature corresponding to the value indicating the degree to which the temperature of the cooking object has changed from the second time point 930. Here, a method for the at least one processor 150 to identify a value indicating the degree to which the temperature of the cooking object has changed from the second time point 930 may be the same as the method described above.

[0089] According to one or more embodiments of the present disclosure, Figure 9b As shown, the at least one processor 150 may acquire information about a straight line 960 connecting the second time point 930 and the third time point 940. Then, the at least one processor 150 may acquire information about a deviation between a graphical representation 950 of a temperature change of a cooking object between the second time point 930 and the third time point 940 and the acquired straight line 960. Specifically, the at least one processor 150 may acquire a MAE value between the graphical representation 950 of a temperature change of a cooking object between the second time point 930 and the third time point 940 and the straight line 960. Then, the at least one processor 150 may identify a heating temperature corresponding to the acquired MAE value.

[0090] Alternatively, according to one or more embodiments of the present disclosure, Fig.9c As shown, the at least one processor 150 may acquire information about the straight line 970 by performing a regression analysis on the graphical representation 950 of the temperature change of the cooking object between the second time point 930 and the third time point 940 .

[0091] Then, the at least one processor 150 may acquire information about a deviation between the graphical representation 950 of the temperature change of the cooking object between the second time point 930 and the third time point 940 and the acquired straight line 970. Specifically, the at least one processor 150 may acquire a MAE value between the graphical representation 950 of the temperature change of the cooking object between the second time point 930 and the third time point 940 and the straight line 970. Then, the at least one processor 150 may identify a heating temperature corresponding to the acquired MAE value.

[0092] Meanwhile, according to one or more embodiments of the present disclosure, the at least one processor 150 may identify whether to identify a heating temperature corresponding to a variation pattern of the temperature of the cooking object based on information about the water level of the cooking object.

[0093] Specifically, refer to Fig.10 , in operation S1010, the at least one processor 150 may acquire information about a water level of a cooking object from the external sensor 200.

[0094] Then, in operation S1020, the at least one processor 150 may identify whether the water level of the cooking object is greater than or equal to a predetermined value.

[0095] If the water level of the cooking object is less than the predetermined value in operation S1020-No, the at least one processor 150 may heat the cooking object based on a pre-acquired user input in operation S1030.

[0096] Meanwhile, if the water level of the cooking object is greater than or equal to the predetermined value in operation S1020-Yes, the at least one processor 150 may identify a change pattern of the temperature of the cooking object in operation S1040. Then, in operation S1050, the at least one processor 150 may identify a heating temperature corresponding to the change pattern of the temperature of the cooking object. Then, in operation S1060, the at least one processor 150 may control the heating part 140 to heat the cooking object at the identified heating temperature.

[0097] That is, if the water level of the cooking object is greater than or equal to a predetermined value, the at least one processor 150 may identify a heating temperature corresponding to a change pattern of the temperature of the cooking object. Meanwhile, if the water level of the cooking object is less than a predetermined value, the at least one processor 150 may control the heating component 140 to heat the cooking object at a predetermined heating temperature based on a predetermined user input.

[0098] Meanwhile, according to one or more embodiments of the present disclosure, the electronic device 100 may acquire information about the type of a cooking object or a heating temperature corresponding to the type of the cooking object by using an artificial intelligence model.

[0099] The memory 110 may store at least one artificial intelligence model. Among them, the at least one processor 150 may input a change pattern of the temperature of the cooking object (i.e., a value indicating the variability of the temperature of the cooking object, such as the MAE value obtained according to the aforementioned method) into the at least one artificial intelligence model, and obtain information about the type of the cooking object or the heating temperature corresponding to the type of the cooking object.

[0100] Among them, the type of the cooking object may be water, water containing a first foreign object, or water containing a second foreign object, etc. Here, the memory 110 may store information about the heating temperature according to the type of the cooking object, and the at least one processor 150 may control the heating component 140 to heat the cooking object at a heating temperature corresponding to the type of the cooking object. For example, if the cooking object type is water, the at least one processor 150 may identify the heating temperature as 97°C. At the same time, if the cooking object type is water containing a first foreign object, the at least one processor 150 may identify the heating temperature as 95°C. In addition, if the cooking object type is water containing a second foreign object, the at least one processor 150 may identify the heating temperature as 93°C.

[0101] Here, at least one artificial intelligence model may be a model trained by using a change pattern of the temperature of the cooking object as an independent variable and using a cooking object type or a heating temperature corresponding to the cooking object type as a dependent variable.

[0102] Meanwhile, the electronic device 100 according to the present disclosure may obtain information about the temperature of the cooking object by using the sensing value obtained via the external sensor 200, but this is only an example, and the electronic device 100 may include a sensor for detecting the temperature of the cooking object. Here, the sensor may directly detect the temperature of the cooking object, or detect the temperature of the heating member 140 in contact with the cooking container.

[0103] Meanwhile, the electronic device 100 according to the present disclosure may be implemented as a cooking device and acquire information about the temperature of the cooking object, and recognize the heating temperature by recognizing the change pattern of the temperature of the cooking object. However, this is only an example, and the electronic device 100 may be implemented as a device for controlling an external cooking device.

[0104] Meanwhile, in the present disclosure, the electronic device 100 may identify the heating temperature and control the heating component 140 or the external cooking device to heat the cooking object at the identified heating temperature. However, this is only an example, and the electronic device 100 may identify at least one of the heating degree, heating level, or heating mode and control the heating component 140 or the external cooking device to cook the cooking object based on at least one of the identified heating degree, heating level, or heating mode.

[0105] refer to Fig.11 , in operation S1110, the electronic device 100 may transmit a signal for controlling the external cooking device 1100 to heat a cooking object to the external cooking device 1100 based on a user input.

[0106] Then, in operation S1120 , the electronic device 100 may acquire information about the temperature of the cooking object heated by the external cooking device 1100 or the water surface of the cooking object from the external sensor 200 .

[0107] Then, based on the acquired information about the temperature of the cooking object and the water surface of the cooking object, the electronic device 100 may identify a change pattern of the temperature of the cooking object, and in operation S1130, identify a heating temperature corresponding to the change pattern of the temperature of the cooking object. Here, a method for the electronic device 100 to identify a change pattern of the temperature of the cooking object or to identify a heating temperature based on the information about the temperature of the cooking object or the water surface of the cooking object may be the same as the above method.

[0108] Then, in operation S1140, the electronic device 100 may transmit a control signal for controlling the external electronic device 1100 to heat the cooking object at the identified heating temperature to the external cooking device 1100.

[0109] The artificial intelligence-related functions according to the present disclosure are operated by the processor and memory of the electronic device.

[0110] The processor may be composed of one or more processors. Here, the one or more processors may include at least one of a central processing unit (CPU), a graphics processing unit (GPU), or a neural processing unit (NPU), but the processor is not limited to the aforementioned examples of processors.

[0111] The CPU is a general-purpose processor that can perform not only general operations but also artificial intelligence operations, and it can efficiently execute complex programs through a multi-layer cache structure. The CPU is conducive to a serial processing method that realizes a systematic link between the previous calculation result and the next calculation result through sequential calculation. At the same time, the general-purpose processor is not limited to the aforementioned example unless it is specified as the case of the aforementioned CPU.

[0112] A GPU is a processor for large-scale operations such as floating-point operations for graphics processing, and it can perform large-scale operations in parallel through large-scale integrated cores. Specifically, compared with a CPU, a GPU can facilitate parallel processing methods such as convolution operations, etc. In addition, a GPU can be used as a coprocessor to supplement the functions of a CPU. Meanwhile, the processor for large-scale operations is not limited to the aforementioned example unless it is specified as the case of the aforementioned GPU.

[0113] NPU is a processor dedicated to AI operations using artificial neural networks, and it can implement each layer that constitutes the artificial neural network as hardware (e.g., silicon). Here, NPU is specially designed according to the specifications required by the company, so it has a lower degree of freedom compared to CPU or GPU, but it can efficiently process the AI ​​operations required by the company. At the same time, as a processor dedicated to AI operations, NPU can be implemented in various forms such as tensor processing unit (TPU), intelligent processing unit (IPU), visual processing unit (VPU), etc. At the same time, the AI ​​processor is not limited to the aforementioned example unless it is specified as the aforementioned NPU.

[0114] In addition, one or more processors may be implemented as a system on chip (SoC). Here, in addition to one or more processors, the SoC may also include a memory and a network interface (eg, a bus for data communication between the processor and the memory, etc.).

[0115] In the case where a system on chip (SoC) included in an electronic device includes multiple processors, the electronic device may perform operations related to artificial intelligence (e.g., operations related to learning or reasoning of an artificial intelligence model) by using some of the multiple processors. For example, the electronic device may perform operations related to artificial intelligence by using at least one of a GPU, NPU, VPU, TPU, or a hardware accelerator dedicated to artificial intelligence operations (e.g., convolution operations, matrix product calculations, etc.) among the multiple processors. However, this is only an example, and the electronic device may process operations related to artificial intelligence by using a general-purpose processor (e.g., a CPU, etc.).

[0116] In addition, the electronic device can perform operations related to artificial intelligence functions by using multiple cores (e.g., dual cores, quad cores, etc.) included in one processor. Specifically, the electronic device can perform artificial intelligence operations such as convolution operations, matrix product calculations, etc. in parallel by using multiple cores included in the processor.

[0117] One or more processors execute control to process input data according to predefined operating rules or artificial intelligence models stored in the memory. The predefined operating rules or artificial intelligence models are characterized in that they are formed through learning.

[0118] Here, forming by learning means applying a learning algorithm to a plurality of learning data to form a predefined operating rule or artificial intelligence model with desired characteristics. Such learning can be performed in the device itself that performs artificial intelligence according to the present disclosure, or by a separate server / system.

[0119] The artificial intelligence model may be composed of multiple neural network layers. At least one layer has at least one weight value, and the operation of the layer is performed by the operation result of the previous layer and at least one defined operation. As examples of neural networks, there are convolutional neural networks (CNN), deep neural networks (DNN), recurrent neural networks (RNN), restricted Boltzmann machines (RBM), deep belief networks (DBN), bidirectional recurrent deep neural networks (BRDNN), deep Q networks, and converters, but the neural networks in the present disclosure are not limited to the aforementioned examples, excluding specified cases.

[0120] A learning algorithm is a method of training a specific object device (e.g., a robot) by using a plurality of learning data so that the specific object device makes a decision or makes a prediction by itself. As examples of the learning algorithm, there are supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but the learning algorithm in the present disclosure is not limited to the aforementioned examples, excluding the specified cases.

[0121] Meanwhile, the term "component" or "module" used in the present disclosure may include a unit composed of hardware, software or firmware, and may be used interchangeably with terms such as logic, logic block, component or circuit, for example. In addition, a "component" or "module" may be a minimum unit or component of a component constituting an integrated body or a component performing one or more functions. For example, a module may be configured as an application specific integrated circuit (ASIC).

[0122] In addition, one or more embodiments of the present disclosure may be implemented as software, which includes instructions stored in a machine-readable storage medium, which can be read by a machine (e.g., a computer). A machine refers to a device that calls instructions stored in a storage medium and can operate according to the called instructions, and the device may include an electronic device 100 according to the aforementioned embodiment. In the case where the instruction is executed by a processor, the processor may perform a function corresponding to the instruction by itself or by using other components under its control. The instruction 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, the term "non-transitory" only means that the storage medium does not include a signal and is tangible, but does not indicate whether the data is stored in the storage medium semi-permanently or temporarily.

[0123] In addition, according to one or more embodiments, the method according to one or more embodiments disclosed herein may be provided when included in a computer program product. A computer program product refers to a product, and it can be traded between a seller and a buyer. The computer program product may be distributed in the form of a machine-readable storage medium (e.g., a compact disk read-only memory (CD-ROM)), or through an application store (e.g., Play Store TM) Online distribution. In the case of online distribution, at least a part of the computer program product may be at least temporarily stored in a storage medium (such as a memory of a manufacturer's server, an application store's server, and a relay server), or may be temporarily generated.

[0124] In addition, each component (e.g., module or program) according to one or more embodiments may be composed of a single entity or multiple entities, and among the aforementioned corresponding subcomponents, some subcomponents may be omitted, or one or more embodiments may also include other subcomponents. Alternatively or additionally, some components (e.g., modules or programs) may be integrated as objects, and the functions performed by each component before the integration is performed are performed in the same or similar manner. According to one or more embodiments, the operations performed by modules, programs or other components may be performed sequentially, in parallel, repeatedly or heuristically. Alternatively, at least some operations may be performed in a different order or omitted, or other operations may be added.

Claims

1. An electronic device, comprising: a heating component configured to heat a cooking object; a communication interface configured to communicate with an external sensor; at least one memory storing at least one instruction; as well as at least one processor connected to the at least one memory and configured to execute the at least one instruction to: acquiring information about the temperature of the cooking object from the external sensor, identifying a heating temperature corresponding to a change pattern of the temperature of the cooking object, and The heating component is controlled to heat the cooking object at the heating temperature.

2. The electronic device according to claim 1, in, The at least one processor is further configured to: identifying a first value indicating a degree of change in the temperature of the cooking object based on recognizing that the change pattern of the temperature of the cooking object corresponds to a temperature rise of the cooking object, and Based on the first value, the heating temperature is identified.

3. The electronic device according to claim 2, in, The at least one processor is further configured to: identifying a first temperature as the heating temperature based on the first value being less than or equal to a predetermined value, and Based on the first value exceeding the predetermined value, a second temperature lower than the first temperature is identified as the heating temperature.

4. The electronic device according to claim 1, in, The at least one processor is further configured to: acquiring a mean absolute error (MAE) value between a line defined by a first point and a second point and a temperature data set, wherein the first point indicates a temperature value of the cooking object at a first time point, the second point indicates a temperature value of the cooking object at a second time point, and wherein the temperature data set includes data reflecting a temperature change of the cooking object from the first time point to the second time point, and Based on the MAE value, the heating temperature is identified.

5. The electronic device according to claim 1, in, The at least one processor is further configured to: acquiring a mean absolute error (MAE) value between a temperature data set and a line acquired by performing regression analysis on the temperature data set, wherein the temperature data set includes data reflecting a temperature change of the cooking object over a period of time, and Based on the MAE value, the heating temperature is identified.

6. The electronic device according to claim 1, in, The at least one processor is further configured to: Based on recognizing that the temperature of the cooking object decreases by more than or equal to a predetermined value from a first time point to a second time point, a second heating temperature corresponding to a change pattern of the temperature of the cooking object from the second time point is identified.

7. The electronic device according to claim 1, in, The at least one processor is further configured to: acquiring information about the water level of the cooking object from the external sensor, and The heating temperature is identified based on the water level based on the information about the water level indicating that the water level is greater than or equal to a predetermined value.

8. The electronic device according to claim 7, in, The at least one processor is further configured to: The heating part is controlled to heat the cooking object at a predetermined heating temperature based on the information about the water level indicating that the water level is lower than the predetermined value.

9. The electronic device according to claim 1, in, The at least one processor is further configured to: The heating temperature is identified by inputting a value indicating a variation pattern of the temperature of the cooking object into an artificial intelligence model.

10. A method for controlling an electronic device, the method comprising: obtaining information about the temperature of the cooking object from an external sensor; identifying a heating temperature corresponding to a change pattern of the temperature of the cooking object; as well as The cooking object is heated at the heating temperature.

11. The method according to claim 10, in, Identifying the heating temperature further includes: identifying a first value indicating a degree of change in the temperature of the cooking object based on recognizing that the change pattern of the temperature of the cooking object corresponds to a temperature rise of the cooking object; and Based on the first value, the heating temperature is identified.

12. The method according to claim 11, in, Identifying the heating temperature further includes: identifying a first temperature as the heating temperature based on the first value being less than or equal to a predetermined value; and Based on the first value exceeding the predetermined value, a second temperature lower than the first temperature is identified as the heating temperature.

13. The method according to claim 10, in, Identifying the heating temperature further includes: acquiring a mean absolute error (MAE) value between a line defined by a first point and a second point and a temperature data set, wherein the first point indicates a temperature value of the cooking object at a first time point, the second point indicates a temperature value of the cooking object at a second time point, and wherein the temperature data set includes data reflecting a temperature change of the cooking object from the first time point to the second time point, and Based on the MAE value, the heating temperature is identified.

14. The method according to claim 10, in, Identifying the heating temperature further includes: acquiring a mean absolute error (MAE) value between a temperature data set and a line acquired by performing regression analysis on the temperature data set, wherein the temperature data set includes data reflecting a temperature change of the cooking object over a period of time, and Based on the MAE value, the heating temperature is identified.

15. A non-transitory computer-readable medium having at least one instruction stored therein, wherein when the at least one instruction is executed by at least one processor, the at least one processor executes a method of controlling an electronic device, the method comprising: obtaining information about the temperature of the cooking object from an external sensor; identifying a heating temperature corresponding to a change pattern of the temperature of the cooking object; as well as The cooking object is heated at the heating temperature.

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