Cooking device and control method therefor

Abstract

A cooking device is disclosed. The cooking device comprises: a thermographic camera; a memory for storing one or more instructions; and one or more processors. The one or more processors execute the one or more instructions to: capture a thermal image of food in the cooking device by using the thermographic camera; identify the heat capacity of the food on the basis of the thermal image; identify the thermal conductivity of the food on the basis of the heat capacity of the food; identify component information of the food on the basis of the thermal conductivity of the food; and control the cooking of the food on the basis of the component information of the food.

Description

Cooking device and its control method

[0001] The present disclosure relates to a cooking device and a control method thereof, and more particularly, to a cooking device that cooks food using electromagnetic waves and a control method thereof.

[0002] Advances in electronic technology have led to the development and widespread adoption of various types of electronic devices. In particular, microwave ovens, used in a variety of settings, including homes and restaurants, have seen continuous advancements in recent years.

[0003] In general, a microwave oven is a device that cooks food by heating the moisture in the food stored inside the cooking chamber using electromagnetic waves (or microwaves) generated by a magnetron.

[0004] A cooking device according to one or more embodiments includes a thermographic camera; a memory storing one or more commands; and one or more processors, wherein the one or more processors, by executing the one or more commands, acquire a thermal image of a food item in the cooking device using the thermal imaging camera, identify a heat capacity of the food item based on the thermal image, identify a thermal conductivity of the food item based on the heat capacity of the food item, identify component information of the food item based on the thermal conductivity of the food item, and control cooking of the food item based on the component information of the food item.

[0005] According to one or more embodiments, the one or more processors can, by executing the one or more instructions, identify a type of the food based on ingredient information of the food, identify specific heat information of the food based on the type of the food, identify weight information of the food based on the specific heat information of the food and a heat capacity of the food, and control cooking of the food based on the weight information of the food and the type of the food.

[0006] According to one or more embodiments, the one or more processors may, by executing the one or more commands, identify a heat capacity of the food based on a first thermal image acquired while performing a heating operation for a first preset time period, identify a temperature change amount of the food based on a second thermal image acquired while the heating operation is stopped for a second preset time period, and identify a thermal conductivity of the food based on the heat capacity of the food, the temperature change amount of the food, and the second preset time period.

[0007] According to one or more embodiments, the one or more processors, by executing the one or more commands, identify a heat capacity per pixel of the food based on the thermal image acquired while performing a heating operation for the first preset time period, identify a temperature change per pixel of the food while the heating operation is stopped for the second preset time period, and identify a thermal conductivity per pixel of the food based on the heat capacity per pixel of the food, the temperature change per pixel of the food, and the second preset time period.

[0008] According to one or more embodiments, the one or more processors can identify the pixel-wise heat capacity of the food based on the pixel-wise temperature change amount included in each of the plurality of frames acquired while performing the heating operation for the first preset time and the output intensity of the cooking device by executing the one or more commands.

[0009] According to one or more embodiments, the one or more processors may identify the amount of temperature change per pixel of the food and the amount of temperature change of each pixel surrounding each pixel of the food while the heating operation is stopped for the second preset time by executing the one or more commands, and identify the heat conductivity of each pixel of the food by applying the heat capacity of the food, the amount of temperature change per pixel of the food, the amount of temperature change of the surrounding pixels, and the second preset time to the Fourier law of heat conduction.

[0010] According to one or more embodiments, the one or more processors can, by executing the one or more commands, identify the pixel-specific component information based on the pixel-specific thermal conductivity of the food, identify the component ratio of the food based on the pixel-specific component information, and identify the type of the food based on the component ratio of the food.

[0011] According to one or more embodiments, the memory stores information about the type of the dish according to the ingredient ratio, and the one or more processors can identify the type of the dish based on the ingredient ratio of the dish and the information stored in the memory by executing the one or more commands.

[0012] According to one or more embodiments, the one or more processors can identify thickness information of the food based on weight information of the food and area information of the food by executing the one or more commands, and control cooking of the food based on the thickness information of the food and the type of the food.

[0013] According to one or more embodiments, the one or more processors, by executing the one or more commands, when at least one of defrosting, reheating or fermenting is selected in response to a user command, identify a heat capacity of the food based on a first thermal image acquired while performing a heating operation, and identify a temperature change amount of the food based on a second thermal image acquired while stopping the heating operation and a thermal conductivity of the food based on the heat capacity of the food.

[0014] A method for controlling a cooking device according to one or more embodiments includes: obtaining a thermal image of a food item in the cooking device using a thermal imaging camera; identifying a thermal capacity of the food item based on the thermal image; identifying thermal conductivity of the food item based on the thermal capacity of the food item; identifying component information of the food item based on the thermal conductivity of the food item; and controlling cooking of the food item based on the component information of the food item.

[0015] A non-transitory computer-readable medium storing computer instructions that, when executed by a processor of a cooking device according to one or more embodiments, cause the cooking device to perform an operation, the operation includes: obtaining a thermal image of a food item in the cooking device using a thermal imaging camera; identifying a thermal capacity of the food item based on the thermal image; identifying a thermal conductivity of the food item based on the thermal capacity of the food item; identifying component information of the food item based on the thermal conductivity of the food item; and controlling cooking of the food item based on the component information of the food item.

[0016] The above and other aspects, features and advantages of specific embodiments of the present disclosure will become more apparent from the following description taken in conjunction with the accompanying drawings.

[0017] FIGS. 1A to 1C are drawings for explaining the structure and operation of a microwave oven to help understand the present disclosure.

[0018] FIG. 2A is a block diagram showing the configuration of a cooking device according to one or more embodiments.

[0019] FIG. 2b is a block diagram showing a detailed configuration of a cooking device according to one or more embodiments.

[0020] FIG. 3 is a flowchart illustrating a method for controlling a cooking device according to one or more embodiments.

[0021] FIG. 4 is a drawing for explaining a method for identifying a cooking area according to one or more embodiments.

[0022] FIG. 5 is a flowchart illustrating a method for controlling a cooking device according to one or more embodiments.

[0023] FIG. 6 is a flowchart illustrating a method for identifying thermal conductivity of a cooking material according to one or more embodiments.

[0024] FIGS. 7A to 7C are drawings for explaining a method for identifying heat capacity according to one or more embodiments.

[0025] FIG. 8 is a drawing illustrating a method for identifying thermal conductivity according to one or more embodiments.

[0026] FIG. 9 is a diagram illustrating a method for identifying component information according to one or more embodiments.

[0027] FIG. 10 is a drawing for explaining a method for identifying the type of a food according to one or more embodiments.

[0028] FIG. 11 is a drawing for explaining a method for identifying the specific heat of a cooking material according to one or more embodiments.

[0029] FIG. 12 is a flowchart illustrating a method for identifying an optimal control algorithm for a cooking material according to one or more embodiments.

[0030] FIG. 13 is a flowchart illustrating a method for naturally defrosting a food according to one or more embodiments.

[0031] The terms used in this specification will be briefly explained, and the present disclosure will be described in detail.

[0032] 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 or cases of those skilled in the art, the emergence of new technologies, etc. Furthermore, in certain cases, the applicant may arbitrarily select terms, and in such cases, the meanings thereof 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.

[0033] In this specification, expressions such as “has,” “can have,” “includes,” or “may include” indicate the presence of a feature (e.g., a number, function, operation, or component such as a part), and do not exclude the presence of additional features.

[0034] In this disclosure, expressions such as “A or B,” “at least one of A and / or B,” or “one or more of A or / and B” can 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” can all refer to cases where (1) only A is included, (2) only B is included, or (3) both A and B are included.

[0035] As used herein, the expressions “first,” “second,” “first,” or “second,” etc., may describe various components, regardless of order and / or importance, and are only used to distinguish one component from another, but do not limit the components.

[0036] When it is said that a component (e.g., a first component) is “operatively or communicatively coupled with / to” or “connected to” another component (e.g., a second component), it should be understood that the component may be directly coupled to the other component, or may be connected through another component (e.g., a third component).

[0037] The expression "configured to" as used in the present disclosure may be used interchangeably with, for example, "suitable for," "having the capacity to," "designed to," "adapted to," "made to," or "capable of." The term "configured to" may not necessarily mean only "specifically designed to" in terms of hardware.

[0038] In some contexts, the phrase "a device configured to" may mean that the device, in conjunction with other devices or components, is "capable of" performing A, B, and C. For example, the phrase "a processor configured (or set) to perform A, B, and C" may refer to a dedicated processor (e.g., an embedded processor) for performing those operations, or a general-purpose processor (e.g., a CPU or application processor) that can perform those operations by executing one or more software programs stored in a memory device.

[0039] Singular expressions include plural expressions unless the context clearly dictates otherwise. In this application, terms such as "comprise" or "consist 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.

[0040] In the embodiments, a "module" or "part" performs at least one function or operation and may be implemented as hardware or software, or as a combination of hardware and software. Furthermore, a plurality of "modules" or "parts" may be integrated into at least one module and implemented as at least one processor (not shown), excluding any "module" or "part" that needs to be implemented as specific hardware.

[0041] Meanwhile, the various elements and areas in the drawings are schematically drawn. Therefore, the technical concept of the present invention is not limited by the relative sizes or spacing depicted in the attached drawings.

[0042] An embodiment of the present disclosure will be described in more detail with reference to the attached drawings below.

[0043] FIGS. 1A to 1C are drawings for explaining the structure and operation of a microwave oven to help understand the present disclosure.

[0044] Referring to FIGS. 1A to 1C, the microwave oven (1) is formed in a roughly rectangular parallelepiped shape with a cooking chamber (22) inside, and the two side surfaces and the upper outer surface can be formed by a sub-case (10). The sub-case (10) is formed by bending a plate having a predetermined width and thickness, and can be combined with a rear plate (12) forming the rear outer surface of the microwave oven (1) and a lower plate (14) forming the lower outer surface. A cavity (20) forming a cooking chamber (22), which is a space for cooking food, can be provided on the upper side of the lower plate (14). The cavity (20) can be formed in a rectangular cylindrical shape with an open front having a size that can be accommodated inside the outer case (10). That is, the cavity (20) is formed in a cylindrical shape by joining the plates forming at least one side to each other, and a cooking chamber (22) can be formed in the opened interior.

[0045] A heater (40) may be provided on the ceiling of the cooking chamber (22) to heat food contained in the cooking chamber (22) by radiant heat. The heater (40) is generally a sheath heater, and various types of electric heaters such as a ceramic heater and a halogen heater may be used as needed. The heater (40) may be fixed to a top cavity (24) forming the upper surface of the cavity (20) so as to be exposed to the interior of the cooking chamber (22).

[0046] Meanwhile, a turntable (32) for supporting a container containing food may be provided on the floor of the cooking chamber (22). A turntable motor (33) may be provided on the lower side of the turntable (32). The turntable motor (33) provides driving force for the rotation of the turntable (32) when food is cooked inside the cooking chamber (22). The turntable motor (33) stops when food is kept warm inside the cooking chamber (22), so as to prevent unnecessary power consumption. A cooking chamber lamp (35) may be further provided on the side of the cooking chamber (22). The cooking chamber lamp (35) illuminates the inside of the cooking chamber (22) when food is being cooked inside the cooking chamber so that a user can know the cooking status of the food. The cooking chamber lamp (35) turns off when food is kept warm inside the cooking chamber, so as to prevent unnecessary power consumption.

[0047] In addition, a number of intake holes (28) may be perforated in the center of the back cavity (26) forming the rear of the cooking chamber (22) through which air inside the cooking chamber (22) is sucked in, and a number of discharge holes (29) may be perforated on the inside of the rim of the back cavity (26) through which heat generated by the convection heater (62) is discharged into the cooking chamber (22).

[0048] Meanwhile, a power unit (30) may be provided in the top cavity (24) and the back cavity (26). The power unit (30) is a space where power components for the operation of the microwave oven (1) are provided. The power unit (30) formed in the back cavity (26) may be provided with a magnetron (34) that generates microwaves for heating food, a high-voltage transformer and a high-voltage capacitor for supplying high-voltage current to the magnetron (34), and a convection unit (60) that convectively heats the cooking chamber (22).

[0049] The convection unit (60) may be configured to include a convection heater (62) that generates heat by electrical resistance, and a convection fan (64) that forcibly convects the heat generated by the convection heater (62) into the cooking chamber (22). When the convection function of the microwave oven (1) is performed, power is supplied to the convection heater (62) to generate heat, and the heat generated by the convection heater (62) can circulate inside the cooking chamber (22) by the rotation of the convection fan (64). That is, food stored in the cooking chamber (22) can be cooked through a convection heating process in which the heat generated by the convection heater (62) is introduced into the cooking chamber (22) through the discharge hole (29) and then discharged to the outside of the cooking chamber (22) through the suction hole (28).

[0050] Meanwhile, the electrical room (30) formed on the upper surface of the top cavity (24) may be equipped with a control unit (or processor) (50) that controls the overall operation of the heater (40) and the microwave oven (1), and a fan assembly (70) that forces air flow to cool the electrical room (30).

[0051] The control unit (50) can form a predetermined circuit by a number of circuit components such as a resistor, a capacitor, an IC (Integrated Circuit) chip, and a microcomputer (MICOM).

[0052] The fan assembly (70) sucks in external air of the microwave oven (1) by means of rotational force to cool a number of electrical components provided in the electrical compartment (30), and a portion of this air is introduced into the cooking compartment (22) through an inlet (27) formed on the front side of the top cavity (24) and circulates within the cooking compartment (22). The air circulating within the cooking compartment (22) can be discharged to the outside of the cooking compartment (22) through an intake port (28).

[0053] Meanwhile, a front plate (16) may be formed at the front of the cavity (20). The front plate (16) forms the front outer shape of the cavity (20) and may be coupled to the front end of the outer case (10). A door (80) may be rotatably coupled to the front plate (16). The door (80) is hinge-coupled to the lower end of the front plate (16) to selectively open and close the open front of the cavity (20).

[0054] A viewing window (82) may be formed in the center of the door (80) so that the user can view the cooking status of food in the cooking chamber (22) without rotating the door (80). In addition, a door handle (84) that is gripped by the user may be provided on the front of the door (80) so that the door (80) can be easily opened and closed. Meanwhile, an operation unit (90) may be provided on the upper part of the door (80) so that the user inputs an operation command to cook food or keep food warm using the microwave oven (1). The operation unit (90) may be configured to include a plurality of buttons (92) for operating the microwave oven (1) and a display (94) that indicates the operating status. The display (94) may show the status of the microwave oven (1) set by the buttons (92).

[0055] Meanwhile, there was a problem that the quality of the thawed material deteriorated due to a rapid change in shape when thawing using a microwave oven (1) and that the optimal control algorithm for each thawed material could not be provided as the thawing proceeded without identifying the components of the thawed material.

[0056] Below, various embodiments of identifying the type of food using a thermal imaging camera and performing appropriate cooking control based on the identified type of food will be described.

[0057] FIG. 2A is a block diagram showing the configuration of a cooking device according to one or more embodiments.

[0058] According to FIG. 2a, the cooking device (100) includes a thermal imaging camera (110), a memory (120), and one or more processors (130). As an example, the cooking device (100) may be implemented as a microwave oven as shown in FIG. 1. However, the present invention is not limited thereto, and may also be implemented as a cooking device that cooks food using a heat source, such as an oven, such as a gas oven or an electric oven, or an air fryer.

[0059] A thermal imaging camera (110) is a device that tracks and detects heat and displays it at a glance on a screen. While the human eye or a general camera detects visible light, a thermal imaging camera (110) detects the radiant heat emitted by a hot object to create an image. The thermal imaging camera (110) displays the temperature in different colors so that we can identify the temperature with our eyes. In other words, the thermal imaging camera (110) is a camera that detects thermal radiation emitted from an object and visualizes it in various colors. It can be installed in a location where it can photograph the inside of a cooking chamber. For example, the thermal imaging camera (110) can be installed in a location where it can photograph a turntable from the front. Accordingly, the image acquired through the thermal imaging camera (110) can be a top-view image or an image taken at an angle close to a top-view image.

[0060] The memory (120) can store data required for various embodiments. The memory (120) may be implemented in the form of a memory embedded in the cooking device (100') or may be implemented in the form of a memory detachable from the cooking device (100) depending on the purpose of data storage. For example, data for driving the cooking device (100) may be stored in a memory embedded in the cooking device (100'), and data for expanding the functions of the cooking device (100) may be stored in a memory detachable from the cooking device (100). Meanwhile, in the case of the memory embedded in the cooking device (100), it may be implemented as at least one of volatile memory (e.g., dynamic RAM (DRAM), static RAM (SRAM), or synchronous dynamic RAM (SDRAM)), non-volatile memory (e.g., one time programmable ROM (OTPROM), programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, flash memory (e.g., NAND flash or NOR flash), hard drive, or solid state drive (SSD)). In addition, in the case of the memory that can be detachably attached to the cooking device (100'), it may be implemented as at least one of memory cards (e.g., compact flash (CF), secure digital (SD), micro secure digital (Micro-SD), mini secure digital (Mini-SD), extreme digital (xD), multi-media card (MMC), etc.), external memory that can be connected to a USB port (e.g., USB memory), etc. It can be implemented in the form of.

[0061] As an example, the memory (120) may store a computer program including at least one instruction or instructions for controlling the cooking device (100).

[0062] According to another example, the memory (120) may store an image received from an external device (e.g., a source device), an external storage medium (e.g., USB), an external server (e.g., web hard), etc., i.e., an input image. Alternatively, the memory (120) may store an image acquired through a thermal imaging camera (110) provided in the cooking device (100). Here, the image may be a 2D image, but is not limited thereto.

[0063] According to one embodiment, the memory (120) may be implemented as a single memory that stores data generated from various operations according to the present disclosure. However, according to another embodiment, the memory (120) may be implemented to include multiple memories that each store different types of data or each store data generated at different stages.

[0064] In the above-described embodiment, it has been described that various data are stored in the external memory (120) of the processor (130), but at least some of the above-described data may be stored in the internal memory of the processor (130) depending on the implementation example of at least one of the cooking device (100) or the processor (130).

[0065] One or more processors (130) control the overall operation of the cooking device (100). Specifically, one or more processors (130) may be connected to each component of the cooking device (100) to control the overall operation of the cooking device (100). For example, one or more processors (130) may be electrically connected to the display (110) and the memory (120) to control the overall operation of the cooking device (100). One or more processors (130) may be configured as one or more processors.

[0066] One or more processors (130) can perform operations of the cooking device (100) according to various embodiments by executing at least one instruction stored in the memory (120).

[0067] The one or more processors (130) may include one or more of a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), an Accelerated Processing Unit (APU), a Many Integrated Core (MIC), a Digital Signal Processor (DSP), a Neural Processing Unit (NPU), a hardware accelerator, or a machine learning accelerator. The one or more processors (130) may control one or any combination of other components of the cooking device, and may perform operations related to communication or data processing. The one or more processors (130) may execute one or more programs or instructions stored in the memory (120). For example, the one or more processors may perform a method according to one or more embodiments of the present disclosure by executing one or more instructions stored in the memory.

[0068] When a 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 a first operation, a second operation, and a third operation are performed by a method according to one or more embodiments, 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).

[0069] One or more processors (130) may be implemented as a single core processor including one core, or may be implemented as one or more multicore processors including multiple cores (e.g., homogeneous multicores or heterogeneous multicores). When one or more processors (130) are implemented as a multicore processor, each of the multiple cores included in the multicore processor may include an internal processor memory, such as a cache memory or an on-chip memory, and a common cache shared by the multiple cores may be included in the multicore processor. In addition, each of the multiple cores (or some of the multiple cores) included in the multicore processor may independently read and execute a program instruction for implementing a method according to one or more embodiments of the present disclosure, or all (or some) of the multiple cores may be linked to read and execute a program instruction for implementing a method according to one or more embodiments of the present disclosure.

[0070] When a method according to one or more embodiments of the present disclosure includes a plurality of operations, the plurality of operations may be performed by one core among the plurality of cores included in a multi-core processor, or may be performed by the plurality of cores. For example, when a first operation, a second operation, and a third operation are performed by a method according to one or more embodiments, the first operation, the second operation, and the third operation may all be performed by a first core included in the multi-core processor, or the first operation and the second operation may be performed by a first core included in the multi-core processor, and the third operation may be performed by a second core included in the multi-core processor.

[0071] In the embodiments of the present disclosure, a processor may mean a system on a chip (SoC) in which one or more processors 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, wherein the core may be implemented as a CPU, a GPU, an APU, a MIC, a DSP, an NPU, a hardware accelerator, or a machine learning accelerator, but the embodiments of the present disclosure are not limited thereto. Hereinafter, for the convenience of explanation, one or more processors (130) will be referred to as a processor (130).

[0072] According to one embodiment, the processor (130) may acquire a thermal image of food within the cooking device (100) using a thermal imaging camera (110). For example, since the thermal image has different pixel values ​​depending on temperature, the processor (130) may acquire a temperature value for each pixel based on each pixel value. For example, the thermal image may include a plurality of frames.

[0073] According to one example, the processor (130) may acquire a thermal image of the food when a specific cooking type is selected. For example, the processor (130) may acquire a thermal image of the food when at least one of the defrosting mode, the warming mode, or the fermentation mode is selected according to a user command. For example, the defrosting cooking mode may be subdivided into a heating defrosting mode and a natural defrosting mode. According to one example, in the heating defrosting mode, the cooking device (100) may heat the food according to the method described below to identify the type of the food and provide optimal heating control and corresponding information based on the type of the food. In the natural defrosting mode, the cooking device (100) may identify the type of the food without heating according to the method described below and provide only information on the thawing completion time.

[0074] According to one embodiment, the processor (130) may obtain a temperature value for each pixel area included in each of a plurality of frames. For example, a pixel area may be a single pixel unit, but is not limited thereto, and a plurality of pixels may be identified as a pixel area. When a plurality of pixels are identified as a pixel area, a representative value (e.g., an average value) of the plurality of pixels included in the pixel area may be obtained as the temperature value of the pixel area. However, for the convenience of explanation, it is assumed below that the temperature value is obtained on a pixel-by-pixel basis.

[0075] According to one embodiment, the processor (130) may identify the thermal capacity of the food based on the thermal image. In one example, the processor (130) may identify the thermal capacity of the food based on the first thermal image acquired while performing the heating operation for a first preset period of time. For example, the processor (130) may identify the thermal capacity of the food per pixel based on the first thermal image acquired while performing the heating operation for the first preset period of time. For example, the processor (130) may identify the thermal capacity of the food per pixel based on the temperature change amount per pixel included in each of the plurality of frames acquired while performing the heating operation for the first preset period of time and the output intensity of the cooking device (100). In one example, the output intensity of the cooking device (100) may vary depending on at least one of the size, capacity, and usable function of the cooking device (100). For example, the output intensity of the cooking device (100) may be a value between 200 W and 1500 W. For example, the output intensity of the cooking device (100) may be, but is not limited to, five output levels such as 200W, 400W, 600W, 800W, and 1000W.

[0076] According to one embodiment, the processor (130) can identify the thermal conductivity of the food based on the heat capacity of the food, the temperature change amount of the food, and the preset second time.

[0077] For example, the processor (130) may identify the temperature change of the food based on a second thermal image acquired while the heating operation is stopped for a preset second period of time. For example, the processor (130) may identify the temperature change of each pixel of the food while the heating operation is stopped for a preset second period of time.

[0078] In one example, the processor (130) may identify the thermal conductivity of the food item for each pixel based on the heat capacity of the food item for each pixel, the temperature change amount of the food item for each pixel, and a preset second time. In one example, the processor (130) may identify the temperature change amount of the food item for each pixel and the temperature change amount of the surrounding pixels of each pixel of the food item while the heating operation is stopped for the preset second time, and may identify the thermal conductivity of the food item for each pixel by applying the heat capacity of the food item for each pixel, the temperature change amount of the food item for each pixel, the temperature change amount of the surrounding pixels, and the preset second time to the Fourier law of heat conduction. For example, the surrounding pixels may include adjacent pixels above, below, left, and right of a specific pixel and / or adjacent pixels in a diagonal direction.

[0079] According to one embodiment, the processor (130) can identify ingredient information of a food based on the thermal conductivity of the food. For example, ingredients of the food may include substances such as bones, fat, carbohydrates, and proteins.

[0080] According to one embodiment, the processor (130) can control the cooking of a food based on the ingredient information of the food. In one example, the processor (130) can identify the type of the food based on the ingredient information of the food, and control the cooking of the food based on the type of the food and the weight information (or mass information) of the food. For example, the food type can be classified according to the characteristics of the food, such as meat, bread, rice, vegetables, milk, water, etc. For example, the food type of meat can also be classified according to the detailed type, such as beef, pork, chicken, etc.

[0081] In one example, the processor (130) may identify component information for each pixel based on the thermal conductivity of the food for each pixel, identify the component ratio of the food for each pixel based on the component information for each pixel, and identify the type of the food for each pixel based on the component ratio of the food. In one example, the processor (130) may identify specific heat information of the food for each pixel based on the type of the food, and identify weight information of the food for each pixel based on the specific heat information of the food for each pixel and the heat capacity of the food for each pixel.

[0082] According to one embodiment, the memory (120) may store information regarding the type of food according to the ingredient ratio. According to one example, the processor (130) may identify the type of food based on the ingredient ratio of the food and the information stored in the memory (120).

[0083] According to one embodiment, the processor (130) can identify the thickness information of the food based on the weight information and the area information of the food, and control the cooking of the food based on the thickness information and the type of the food. For example, when the cooking device (100) operates in defrosting mode, the defrosting time may vary depending on the thickness even if the volume of the food is the same. Accordingly, the processor (130) can determine a more optimal control algorithm using not only the weight information of the food but also the thickness information.

[0084] FIG. 2b is a block diagram showing a detailed configuration of a cooking device according to one or more embodiments.

[0085] According to FIG. 2a, the cooking device (100') includes a thermal imaging camera (110), a memory (120), one or more processors (130), a display (140), a communication interface (150), and a user interface (160). Among the configurations illustrated in FIG. 2b, a detailed description of configurations that overlap with those illustrated in FIG. 2a will be omitted.

[0086] The display (140) may be implemented as a display including a self-luminous element or a display including a non-luminous element and a backlight. For example, it may be implemented as various types of displays such as an LCD (Liquid Crystal Display), an OLED (Organic Light Emitting Diodes) display, an LED (Light Emitting Diodes), a micro LED, a Mini LED, a PDP (Plasma Display Panel), a QD (Quantum dot) display, a QLED (Quantum dot light-emitting diodes), etc. The display (140) may also include a driving circuit, a backlight unit, etc., which may be implemented in a form such as an a-si TFT, an LTPS (low temperature poly silicon) TFT, an OTFT (organic TFT), etc. According to an example, the display (140) may be implemented as a flat display, a curved display, a foldable or / and rollable flexible display, etc.

[0087] The communication interface (150) includes a circuit and can communicate with an external device (server or user terminal). For example, the processor (130) can receive various data or information from an external device connected via the communication interface (150) and can also transmit various data or information to the external device.

[0088] The communication interface (150) may include at least one of a WiFi module, a Bluetooth module, a wireless communication module, an NFC module, and a UWB module (Ultra Wide Band). At this time, the wireless communication module may perform communication according to various communication standards such as IEEE, Zigbee, 3G (3rd Generation), 3GPP (3rd Generation Partnership Project), LTE (Long Term Evolution), 5G (5th Generation), etc.

[0089] The user interface (160) may be implemented as a device such as a button, a touch pad, etc., or as a touch screen that can also perform the above-described display function and operation input function.

[0090] The speaker (170) can convert and amplify a digital audio signal processed by the processor (130) into an analog audio signal and output it. For example, the speaker (170) can include at least one speaker unit, a D / A converter, an audio amplifier, etc., which can output at least one channel. For example, the speaker can output various notifications, messages, information, etc. related to information generated by the processor (130).

[0091] In addition, the cooking device (100') may further include a microphone and a sensor.

[0092] A microphone is a component that receives user voice or other sounds and converts them into audio data. In one example, the processor (130) may use audio received through the microphone as context data for the cooking device (100). However, in another embodiment, the cooking device (100') may receive user voice input through an external device through the communication interface (150).

[0093] The sensors may include various types of sensors, such as temperature sensors, light sensors, touch sensors, proximity sensors, humidity sensors, infrared sensors, biosensors, etc.

[0094] FIG. 3 is a flowchart illustrating a method for controlling a cooking device according to one or more embodiments.

[0095] According to FIG. 3, in operation 310, the cooking device (100) can obtain a thermal image of food inside the cooking device (100) using a thermal imaging camera (110).

[0096] In operation 320, the cooking device (100) can identify the heat capacity of the food based on the thermal image. For example, the heat capacity is the amount of heat required to raise the temperature of a substance by 1˚C or 1K, and is a value that indicates how easily the temperature of an object changes when heat is added or removed.

[0097] In operation 330, the cooking device (100) can identify the thermal conductivity of the food based on the heat capacity of the food. For example, thermal conductivity is a numerical value representing the degree to which heat is conducted through a material, and is also called thermal conductivity. In thermal conductivity, it can be a value (J / s · m · K) of thermal energy flowing in unit time through a unit area perpendicular to the heat flow divided by the temperature difference per unit length.

[0098] In operation 340, the cooking device (100) can identify ingredient information of the food based on the thermal conductivity of the food. For example, the ingredient information includes ingredient ratio information, and the ingredient ratio may be ratio information for each pure substance (e.g., bone, fat, carbohydrate, protein, etc.) that constitutes the food. For example, the cooking device (100) can obtain ingredient ratio information of the food area based on ingredient information corresponding to each pixel of the food area. For example, if the thermal conductivity of 40 of the total 100 food area pixels corresponds to the A component and the thermal conductivity of 60 corresponds to the B component, ingredient ratio information such as 40% of the A component and 60% of the B component can be obtained.

[0099] In operation 350, the cooking device (100) can control the cooking of the food based on the ingredient information of the food. For example, the cooking device (100) can estimate the type of the food based on the ingredient ratio information and control the cooking of the food based on the estimated type. For example, if the food type having 40% of ingredient A and 60% of ingredient B is beef and the cooking device (100) operates in the heating defrosting mode, defrosting control corresponding to beef can be performed.

[0100] According to one embodiment, the cooking device (100) can identify a food area in a thermal image in operation 320, and identify a heat capacity of the food area based on a temperature value of the food area. For example, the cooking device (100) can identify the heat capacity of the food area based on a temperature change amount of the food area. According to one example, the temperature value of the food area may be an average temperature value of the food area. In this case, the cooking device (100) can identify the heat capacity of the food area based on the average temperature change amount of the food area. According to another example, the temperature value of the food area may be a temperature value for each pixel of the food area. In this case, the cooking device (100) can identify the heat capacity for each pixel of the food area based on a temperature change amount for each pixel of the food area.

[0101] FIG. 4 is a drawing for explaining a method for identifying a cooking area according to one or more embodiments.

[0102] According to one example, the processor (130) can identify at least one cooking area in a thermal image by clustering pixels based on temperature values ​​per pixel included in each of a plurality of frames. According to one example, the processor (130) can analyze the correlation between the temperature change amount (or thermal change amount) per pixel and the current temperature value in the plurality of frames to obtain a correlation graph, identify a plurality of pixel groups by clustering pixels in the correlation graph, and identify a pixel group corresponding to a preset condition among the plurality of pixel groups as a cooking area. For example, the correlation graph can be a statistical graph for analyzing the correlation (or correlation) between two variables, that is, the temperature change amount per pixel and the current temperature value.

[0103] For example, the cooking device (100) can identify a pixel group (411) including pixels whose temperature change amount is greater than a threshold value as a cooking area, as shown in FIG. 4, and identify the remaining pixel groups (412) as a background area (i.e., an area that is not a cooking area).

[0104] However, the example illustrated in FIG. 4 is merely an example, and pixel groups with different characteristics in the correlation graph may be identified as the food area and / or the background area depending on the cooking mode and / or the state of the food. For example, in defrosting mode, a pixel group with a relatively low current temperature and a relatively high temperature change rate may be identified as the food area. As another example, if the food is frozen, a pixel group with a relatively high temperature change rate as the temperature changes from low to high may be identified as the food area.

[0105] FIG. 5 is a flowchart illustrating a method for controlling a cooking device according to one or more embodiments.

[0106] Among the operations illustrated in Fig. 5, detailed descriptions of operations that overlap with those illustrated in Fig. 3 will be omitted.

[0107] According to FIG. 5, in operation 510, the cooking device (100) can obtain a thermal image of food inside the cooking device using a thermal imaging camera.

[0108] In operation 520, the cooking device (100) can identify the heat capacity of the food based on the thermal image.

[0109] In operation 530, the cooking device (100) can identify the thermal conductivity of the food based on the heat capacity of the food.

[0110] In operation 540, the cooking device (100) can identify the ingredient ratio of the food based on the thermal conductivity of the food.

[0111] In operation 550, the cooking device (100) can identify the type of food based on the ratio of ingredients in the food.

[0112] In operation 560, the cooking device (100) can identify the specific heat information of the food based on the type of the food. For example, the specific heat refers to the ratio of the amount of heat applied to a unit mass and the resulting temperature change. For example, it is also expressed as the amount of heat (energy) required to raise the temperature of 1 g of a substance by 1°C. The standard unit is J / kgㆍK, and cal / g℃ is also used. The ratio of the amount of heat applied to the entire substance and the resulting temperature change is called heat capacity, and the unit is J / K. Accordingly, the heat capacity for a unit mass can be the specific heat.

[0113] In operation 570, the cooking device (100) can identify weight information (or mass information) of the food based on the specific heat information and the heat capacity of the food. For example, the cooking device (100) can identify the weight of the food based on the relationship of "weight = heat capacity / specific heat." For example, mass is the amount of material that an object has and is a unique characteristic of the object itself, and is expressed in units of weight such as kilograms (kg) or grams (g). Weight is expressed as a force that mass exerts due to gravity and is calculated by multiplying the mass of an object by the acceleration of gravity (g), so they have somewhat different meanings. However, in the present disclosure, since it is assumed that there is no change in location, mass and weight can be used with similar meanings.

[0114] In operation 580, the cooking device (100) can control the cooking of the food based on the weight information of the food and the type of the food. For example, if the operation mode is a defrosting mode and the food is 300 g of beef, the cooking device (100) can control the magnetron output to operate at a defrosting temperature appropriate for 300 g of beef.

[0115] FIG. 6 is a flowchart illustrating a method for identifying thermal conductivity of a cooking material according to one or more embodiments.

[0116] According to FIG. 6, in operation 610, the cooking device (100) can identify the pixel-by-pixel heat capacity of the food based on the temperature change amount per pixel included in each of the plurality of frames acquired while performing the heating operation for a preset first time and the output intensity of the cooking device.

[0117] In operation 620, the cooking device (100) can identify the temperature change amount of each pixel of the food and the temperature change amount of each pixel surrounding the pixel of the food while stopping the heating operation for a preset second time.

[0118] In operation 630, the cooking device (100) can identify the pixel-by-pixel thermal conductivity of the food by applying the Fourier law of heat conduction to the heat capacity of the food, the pixel-by-pixel temperature change of the food, the temperature change of the surrounding pixels, and the preset second time.

[0119] FIGS. 7A to 7C are drawings for explaining a method for identifying heat capacity according to one or more embodiments.

[0120] According to one embodiment, the cooking device (100) stores an initial temperature value for each pixel of the food area based on an initial thermal image acquired through a thermal imaging camera (110), and after heating for a preset period of time, identifies the temperature value for each pixel of the food area to calculate the amount of temperature change for each pixel of the food area.

[0121] For example, as illustrated in FIG. 7a, the initial temperature value per pixel of the cooking area can be identified based on the initial thermal image (710).

[0122] For example, as shown in FIG. 7b, the temperature value per pixel of the cooking area can be identified based on the thermal image (720) acquired after heating for a preset period of time.

[0123] For example, as illustrated in FIG. 7c, the temperature change amount (730) per pixel can be identified based on the difference between the initial temperature value per pixel and the temperature value per pixel after heating.

[0124] For example, when the cooking device (100) identifies the amount of temperature change per pixel, the cooking device (100) can estimate the heat capacity per pixel based on the output intensity, output time, and the amount of temperature change per pixel. For example, the cooking device (100) can estimate the heat capacity per pixel based on Q = C * T (Q: heat amount, C: heat capacity, T: temperature change). For example, if the output intensity of the cooking device (100) is Wmw and the output time (or heating time) is △t, Q = Wmw * △t (heating time) can be obtained, and therefore, heat capacity C = Q / T = Wmw * △t / △T is established. Accordingly, the cooking device (100) can estimate the amount of temperature change by heating the food, and thus can ultimately estimate the heat capacity of the food. For example, the cooking device (100) can estimate the amount of temperature change per pixel of the food, and thus can ultimately estimate the heat capacity of the food per pixel.

[0125] FIG. 8 is a drawing illustrating a method for identifying thermal conductivity according to one or more embodiments.

[0126] According to one embodiment, the cooking device (100) can identify the thermal conductivity of the food based on Fourier's law of heat conduction.

[0127] Figure 8 is a graph showing the phenomenon of heat passing through a specific material. Let the cross-sectional area be A, and let us assume that heat is transferred starting from the origin and penetrating a distance of △x.

[0128] In this case, according to the Fourier law of heat conduction, the thermal conductivity is proportional to the product of the area (A) and the temperature difference (T2-T1) and inversely proportional to the length △x, so the following mathematical equation 1 can be established.

[0129] [Mathematical Formula 1]

[0130]

[0131] Here, Wp is the heat transfer rate, k is the proportionality constant, which can be the thermal conductivity (or thermal conductivity coefficient), A is the cross-sectional area, and △T / △x (dT / dx) can be the temperature gradient.

[0132] Since heat moves from areas of high temperature to areas of low temperature, it can have a negative value, meaning that the temperature decreases as x increases. Accordingly, we can put a - in front of the formula to make it positive.

[0133] Since only the thermal conduction energy is the total energy transferred to the pixel without heating the material, the thermal conductivity k can be calculated as in the following mathematical equation 2. The thermal conductivity k may correspond to a characteristic of the material that varies depending on the material.

[0134] [Equation 2]

[0135]

[0136] Here, △L = A / △x, C pixel is the heat capacity per pixel, △T pixel is the temperature change per pixel, △T near is the temperature change of the surrounding pixels, △t can be the conduction time. For example, △L can be the pixel length.

[0137] For example, if thermal conductivity is defined as a relative value, C pixel And at least one of △L can be implemented as a constant. For example, the cooking device (100) can define and store a value for thermal conductivity for identifying a component per pixel as a relative value. In this case, C pixel and △L can be defined as a specific constant, for example, the value “1”, to reduce the computational complexity.

[0138] FIG. 9 is a diagram illustrating a method for identifying component information according to one or more embodiments.

[0139] According to one embodiment, the cooking device (100) can store information on the thermal conductivity of each component that constitutes the food.

[0140] For example, the cooking device (100) can store the thermal conductivity information of each component in a lookup table format as shown in FIG. 9. For example, the cooking device (100) can store the information in memory (120).

[0141] Accordingly, when the cooking device (100) calculates the thermal conductivity of the food per pixel, it can identify the component per pixel corresponding to the thermal conductivity of the food per pixel based on the thermal conductivity information of each component stored in the memory (120), and identify the component ratio of the food based on the component per pixel. For example, the thermal conductivity information of each component stored in the memory (120) may not be an absolute value, but a relative value for identifying the component. However, in some cases, it is also possible to use an absolute value.

[0142] However, this is not limited to this, and the information may be received in real time from an external device. Alternatively, the cooking device (100) may transmit information on the heat conductivity of each pixel of the food to the external device, and receive information on the ingredient ratio of the food from the external device.

[0143] FIG. 10 is a drawing for explaining a method for identifying the type of a food according to one or more embodiments.

[0144] According to one embodiment, the cooking device (100) can estimate the type of food based on the ratio of ingredients in the food.

[0145] For example, the cooking device (100) may store information on the ingredient ratios for each material in the form of a lookup table, as illustrated in FIG. 10. For example, the cooking device (100) may store the information in memory (120).

[0146] Accordingly, when the cooking device (100) identifies the ingredient ratio of the food, it can identify the type of food based on the ingredient ratio information of each substance in the memory (120).

[0147] However, this is not limited to this, and the information may be received in real time from an external device. Alternatively, the cooking device (100) may transmit information on the ingredient ratio of the food to the external device and receive information on the type of the food from the external device.

[0148] FIG. 11 is a drawing for explaining a method for identifying the specific heat of a cooking material according to one or more embodiments.

[0149] According to one embodiment, the cooking device (100) can identify the specific heat information of the food based on the type of the food.

[0150] For example, the cooking device (100) may store specific heat information for each type of food in the form of a lookup table, as illustrated in FIG. 11. For example, the cooking device (100) may store the information in memory (120).

[0151] Accordingly, when the type of food is identified, the cooking device (100) can identify the specific heat information of the food based on the specific heat information of each type of food in the memory (120).

[0152] However, this is not limited to this, and the information may be received in real time from an external device. Alternatively, the cooking device (100) may transmit information on the type of food to an external device and receive information on the specific heat of the food from the external device.

[0153] FIG. 12 is a flowchart illustrating a control method in a heating and thawing mode according to one or more embodiments.

[0154] According to one embodiment, in the heating defrosting mode, the cooking device (100) can heat the food to identify the type of the food, and provide optimal heating control and corresponding information based on the type of the food.

[0155] According to FIG. 12, in operation 1210, the cooking device (100) can identify the heat capacity of the food. For example, if the output of the cooking device (100) is 1000 W, the total output time of the cooking device (100) is 30 s, and the temperature change amount of the food is 1.76°C, the heat capacity can be estimated as 1000 W * 30 s / 1.76°C = approximately 17 KJ / °C by the formula C = Q / T = Wmw * △t / △T. In this case, the cooking device (100) can estimate the heat capacity per pixel based on the temperature change amount of the food per pixel.

[0156] In operation 1220, the cooking device (100) can identify the thermal conductivity of the food. For example, the cooking device (100) can calculate the thermal conductivity of the food per pixel based on the mathematical expression 2 described above.

[0157] In operation 1230, the cooking device (100) can identify the type of the food. For example, the cooking device (100) can estimate a component per pixel based on the thermal conductivity of the food per pixel, estimate a component ratio of the food based on the component per pixel, and estimate the type of the food based on the estimated component ratio, thereby identifying the specific heat of the food. For example, the cooking device (100) can estimate a pixel with a thermal conductivity k=0.2 as Protein, and can estimate a pixel with a thermal conductivity k=0.18 as Fat. For example, if the component ratio of the food is estimated as Protein: 23.6% / Fat: 0.8%, the cooking device (100) can estimate the food as Chicken based on the component ratio information for each material of FIG. 10.

[0158] In operation 1240, the cooking device (100) can identify the specific heat of the food. For example, if the food is estimated to be chicken, the cooking device (100) can identify the specific heat of the chicken when it is frozen as 1.77 kJ / kg°C based on the specific heat information for each material in FIG. 11.

[0159] In operation 1250, the cooking device (100) can estimate the weight (or mass) of the food. For example, since the heat capacity C = c*m (c: specific heat, m: mass) and the mass m = C / c, the mass of the food can be identified based on the heat capacity and specific heat of the food, and the weight of the food can be estimated based on the mass of the food. For example, the cooking device (100) can estimate the weight to be about 9.6 kg based on the heat capacity of 17 KJ / °C obtained in operation 1210 and the specific heat of 1.77 kJ / kg°C obtained in operation 1240.

[0160] In operation 1260, the cooking device (100) can determine an optimal control temperature according to the type and weight of the food. For example, the cooking device (100) can analyze the thawing material to determine the most appropriate thawing control algorithm and thawing end temperature. For example, the cooking device (100) can also provide information on the determined thawing control algorithm and thawing end temperature through the display (140). For example, the cooking device (100) can perform thawing control by determining a minimum control temperature, a maximum control temperature, an average control temperature, etc. according to the type and weight of the food.

[0161] FIG. 13 is a flowchart illustrating a control method in a natural thawing mode according to one or more embodiments.

[0162] According to one embodiment, the cooking device (100) may provide a natural defrosting mode. For example, when a food to be defrosted is placed in the cooking device (100), the cooking device (100) may identify the type of the food without heating and provide only information on the thawing completion time.

[0163] According to FIG. 13, in operation 1310, the cooking device (100) can identify the thermal conductivity of the food.

[0164] In operation 1320, the cooking device (100) can identify the type of food to be cooked.

[0165] In operation 1330, the cooking device (100) can identify the specific heat of the food.

[0166] Actions 1310 to 1330 are similar to actions 1220 to 1240 in Fig. 12, so detailed descriptions are omitted.

[0167] In one embodiment, heat capacity cannot be estimated in natural thawing mode because heating does not occur. However, by treating the portion corresponding to heat capacity in Equation 2 as a constant, thermal conductivity can be estimated. However, since heat capacity cannot be estimated in natural thawing mode, weight may also be difficult to estimate.

[0168] In operation 1340, the cooking device (100) can identify an appropriate thawing completion temperature. For example, the cooking device (100) can identify an appropriate thawing completion temperature based on the type of food to be cooked, i.e., the thawing material. For example, the appropriate thawing completion temperature according to the type of thawing material can be determined based on previously stored information (e.g., a lookup table).

[0169] In operation 1350, the cooking device (100) may provide an estimated completion time. For example, the cooking device (100) may provide the estimated completion time based on an appropriate thawing completion temperature of the thawing material. For example, the cooking device (100) may periodically check the temperature of the thawing material based on a thermal image acquired through a thermal imaging camera (110) to estimate and provide an estimated completion time up to the appropriate thawing completion temperature. For example, the cooking device (100) may provide a UI screen including the estimated thawing completion time through the display (140). For example, if the estimated completion time changes over time, the cooking device (100) may update and provide the estimated thawing completion time.

[0170] According to one embodiment, the cooking device (100) may identify the ingredient ratio of the food and estimate and provide the calorie content of the food based on the identified ingredient ratio. For example, the cooking device (100) may provide a UI screen including calorie information of the food through the display (140).

[0171] Meanwhile, although the above-described embodiment has been described assuming a thawing process of the food, it is obvious that a similar method can be applied to other cooking modes (e.g., reheating, fermentation, etc.) that can be cooked through heating and cooling processes such as reheating. For example, in the case of the fermentation mode, a heating fermentation mode can be provided in a manner similar to FIG. 12, and a natural fermentation mode can be provided in a manner similar to FIG. 13.

[0172] Meanwhile, in the above-described embodiment, the cooking device (100) is described assuming that it is implemented as a microwave oven, but the cooking device (100) may also be implemented as another heating-capable cooking device, such as an oven or an air fryer. For example, ovens can be broadly classified into gas and electric types depending on the type of heat source. The gas type structure generates heat by burning gas with a burner, and the electric type structure can generate heat by an electromagnetic wave generating device (microwave oven) driven by electricity or a heating wire.

[0173] According to the various embodiments described above, the thawing material can be analyzed to provide the most appropriate thawing control algorithm and thawing end temperature. Furthermore, the most appropriate thawing control can be implemented during natural thawing, while providing an estimated thawing completion time. This enhances user convenience.

[0174] Meanwhile, the methods according to the various embodiments of the present disclosure described above can be implemented only with a software upgrade or a hardware upgrade for an existing cooking device.

[0175] Additionally, the various embodiments of the present disclosure described above can also be performed through an embedded server provided in the cooking device or an external server of the cooking device.

[0176] Meanwhile, according to a temporary example of the present disclosure, the various embodiments described above can be implemented as software including commands stored in a machine-readable storage medium that can be read by a machine (e.g., a computer). The machine is a device that can call commands stored from the storage medium and operate according to the called commands, and may include a cooking device (e.g., cooking device (A)) according to the disclosed embodiments. When a command is executed by a processor, the processor can perform a function corresponding to the command directly or by using other components under the control of the processor. The command 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 a signal and is tangible, but does not distinguish between data being stored semi-permanently or temporarily in the storage medium.

[0177] Furthermore, according to one embodiment of the present disclosure, the method according to the various embodiments described above may be provided as included in 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 distributed in the form of a machine-readable storage medium (e.g., compact disc read-only memory (CD-ROM)) or online through an application store (e.g., Play Store™). 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.

[0178] In addition, each of the components (e.g., modules or programs) according to the various embodiments described above may be composed of a single or multiple entities, and some of the corresponding sub-components described above may be omitted, or other sub-components may be further included in various embodiments. Alternatively or additionally, some components (e.g., modules or programs) may be integrated into a single entity, which may perform the same or similar functions as those performed by each of the corresponding components prior to integration. Operations performed by modules, programs or other components according to various embodiments may be executed sequentially, in parallel, iteratively or heuristically, or at least some operations may be executed in a different order, omitted, or other operations may be added.

[0179] Although the preferred embodiments of the present disclosure have been illustrated and described above, the present disclosure is not limited to the specific embodiments described above, and various modifications may be made by a person having ordinary skill in the art to which the present disclosure pertains without departing from the gist of the present disclosure as claimed in the claims, and such modifications should not be understood individually from the technical idea or prospect of the present disclosure.

Claims

1. In the cooking device, thermographic camera; A memory storing one or more instructions; and comprising one or more processors; The one or more processors, by executing the one or more instructions, Obtaining a thermal image of food inside the cooking device using the thermal imaging camera, Identifying the heat capacity of the food based on the thermal image, Identify the thermal conductivity of the food based on the heat capacity of the food, Identifying the ingredient information of the food based on the thermal conductivity of the food, A cooking device that controls cooking of the food based on ingredient information of the food.

2. In paragraph 1, The one or more processors, by executing the one or more instructions, Identifying the type of the dish based on the ingredient information of the dish, Identify the specific heat information of the food based on the type of the food, Identify the weight information of the food based on the specific heat information of the food and the heat capacity of the food, A cooking device that controls cooking of the food based on the weight information of the food and the type of the food.

3. In paragraph 2, The one or more processors, by executing the one or more instructions, Identifying the heat capacity of the food based on a first thermal image acquired while performing a heating operation for a preset first time period, Identify the temperature change amount of the food based on the second thermal image acquired while the heating operation is stopped for a preset second time period, A cooking device that identifies the thermal conductivity of the food based on the heat capacity of the food, the temperature change amount of the food, and the preset second time.

4. In paragraph 2, The one or more processors, by executing the one or more instructions, Identifying the heat capacity of each pixel of the food based on the thermal image acquired while performing the heating operation for the first preset time, Identify the temperature change amount of each pixel of the food while the heating operation is stopped for the above-mentioned second preset time, A cooking device that identifies the pixel-by-pixel thermal conductivity of the food based on the pixel-by-pixel heat capacity of the food, the pixel-by-pixel temperature change amount of the food, and the preset second time.

5. In paragraph 4, The one or more processors, by executing the one or more instructions, A cooking device that identifies the heat capacity of the food pixel by pixel based on the temperature change amount per pixel included in each of a plurality of frames acquired while performing a heating operation for the first preset time and the output intensity of the cooking device.

6. In paragraph 4, The one or more processors, by executing the one or more instructions, While the heating operation is stopped for the above-mentioned second preset time, the temperature change amount of each pixel of the food and the temperature change amount of each pixel surrounding the pixel of the food are identified, A cooking device that identifies the heat conductivity of each pixel of the food by applying the heat capacity of each pixel of the food, the temperature change amount of each pixel of the food, the temperature change amount of the surrounding pixels, and the preset second time to the Fourier law of heat conduction.

7. In paragraph 4, The one or more processors, by executing the one or more instructions, Identifying the pixel-by-pixel component information based on the pixel-by-pixel thermal conductivity of the above food, Identify the ingredient ratio of the dish based on the ingredient information for each pixel, A cooking device that identifies the type of the food based on the ratio of ingredients in the food.

8. In paragraph 7, The above memory is, Stores information about the cooking type according to the ingredient ratio. The one or more processors, by executing the one or more instructions, A cooking device that identifies the type of the food based on the ingredient ratio of the food and the information stored in the memory.

9. In paragraph 2, The one or more processors, by executing the one or more instructions, Identifying the thickness information of the food based on the weight information of the food and the area information of the food, A cooking device that controls cooking of the food based on the thickness information of the food and the type of the food.

10. In paragraph 1, The one or more processors, by executing the one or more instructions, When at least one of defrosting, reheating or fermenting is selected according to a user command, the heat capacity of the food is identified based on a first thermal image acquired while performing the heating operation, A cooking device that identifies the thermal conductivity of the food item based on the change in temperature of the food item and the heat capacity of the food item based on the second thermal image acquired while the heating operation is stopped.

11. In the method of controlling the cooking device, A step of obtaining a thermal image of food inside the cooking device using a thermal imaging camera; A step of identifying the heat capacity of the food based on the thermal image; A step of identifying the thermal conductivity of the food based on the heat capacity of the food; A step of identifying ingredient information of the food based on the thermal conductivity of the food; and A control method, comprising: a step of controlling cooking of the food based on ingredient information of the food.

12. In paragraph 11, The step of controlling the cooking of the above food is: A step of identifying the type of the food based on the ingredient information of the food; A step of identifying specific heat information of the food based on the type of the food; A step of identifying weight information of the food based on the specific heat information of the food and the heat capacity of the food; and A control method, comprising: a step of controlling cooking of the food based on weight information of the food and the type of the food.

13. In paragraph 12, The step of identifying the thermal conductivity of the above food is: A step of identifying a heat capacity of the food based on a first thermal image acquired while performing a heating operation for a preset first time period; A step of identifying the temperature change amount of the food based on a second thermal image acquired while the heating operation is stopped for a preset second time; and A control method, comprising: a step of identifying thermal conductivity of the food based on the heat capacity of the food, the temperature change amount of the food, and the preset second time.

14. In paragraph 12, The step of identifying the thermal conductivity of the above food is: A step of identifying the heat capacity of each pixel of the food based on the thermal image acquired while performing a heating operation for the first preset time; A step of identifying the temperature change amount for each pixel of the food while the heating operation is stopped for the second preset time; and A control method, comprising: a step of identifying a pixel-by-pixel thermal conductivity of the food object based on a pixel-by-pixel heat capacity of the food object, a pixel-by-pixel temperature change amount of the food object, and the preset second time.

15. A non-transitory computer-readable medium storing computer instructions that, when executed by a processor of the cooking device, cause the cooking device to perform an operation, The above actions are, A step of obtaining a thermal image of food inside the cooking device using a thermal imaging camera; A step of identifying the heat capacity of the food based on the thermal image; A step of identifying the thermal conductivity of the food based on the heat capacity of the food; A step of identifying ingredient information of the food based on the thermal conductivity of the food; and A non-transitory computer-readable medium, comprising: a step of controlling cooking of the food based on ingredient information of the food.

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