Cookware category identification method and intelligent cooking device

Abstract

The embodiments of the present application provide a method for identifying the category of a cookware and a smart cooking device. The method comprises: acquiring a light signal; determining whether the light signal is a reflected light signal reflected back by the cookware; and if the light signal is a reflected light signal, identifying the category of the cookware based on the light signal. The technical solution provided by the embodiments of the present application enables the smart cooking device to autonomously identify the category to which the cookware belongs, thereby enabling the smart cooking device to automatically start a cooking mode that is adapted to the category of the cookware, recommend digital recipes that are adapted to the cookware to the user, etc. This helps to improve the intelligence level of the smart cooking device and enhance the user experience.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method for identifying the category of pots and pans and an intelligent cooking device. Background Art

[0002] With the rapid development of artificial intelligence (AI), more and more intelligent machines are being used in our daily lives. For example, smart cooking devices often come standard with multiple functional pots, such as a wok and steamer.

[0003] The purpose of a smart cooking device being compatible with multiple different types of pots is to allow different types of pots to be used for different cuisines. In practice, users are required to select the appropriate cooking mode for the pot type on the smart cooking device's control panel. However, in some cases, users may select the wrong cooking mode due to operational errors or memory errors, resulting in cooking failure or poor results. Summary of the Invention

[0004] In view of the above problems, embodiments of the present application provide a method for identifying the category of cookware and an intelligent cooking device.

[0005] In one embodiment of the present application, a method for identifying the type of cookware is provided. The method includes:

[0006] Acquire optical signals;

[0007] determining whether the light signal is a reflected light signal reflected back by the cookware;

[0008] When the light signal is a reflected light signal, the category of the cookware is identified based on the light signal.

[0009] In another embodiment of the present application, a smart cooking device is provided. The smart cooking device includes:

[0010] Cookware;

[0011] a base, on which an optical receiver is provided for receiving optical signals;

[0012] A processor is electrically connected to the optical receiver and is configured to obtain an optical signal through the receiver; determine whether the optical signal is a reflected light signal reflected back by the cookware; and if the optical signal is a reflected light signal, identify the category of the cookware based on the optical signal.

[0013] The technical solutions provided by the various embodiments of the present application, by providing a light receiver on the base, can identify the category of the cookware based on the light signal after the light receiver acquires the light signal and determines that the light signal is a reflected light signal reflected by the cookware. This allows the smart cooking device to autonomously identify the category of the cookware, thereby enabling the smart cooking device to automatically activate a cooking mode that matches the category of the cookware and recommend digital recipes that match the cookware to the user. This helps to improve the intelligence of the smart cooking device and enhance the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0015] Figure 1 A schematic diagram of the specific structure of the intelligent cooking device provided in one embodiment of the present application;

[0016] Figure 2 A partially enlarged schematic diagram of a fool-proof structure on a base provided in one embodiment of the present application;

[0017] Figure 3 A partially enlarged schematic diagram of a mounting structure for mounting a Hall element on a base provided in one embodiment of the present application;

[0018] Figure 4a A schematic diagram of multiple contact points provided on a base according to an embodiment of the present application;

[0019] Figure 4b A schematic diagram of circuits corresponding to multiple contact points provided on a base according to an embodiment of the present application;

[0020] Figure 5 A schematic diagram of a flow chart of a method for identifying the category of a cookware provided in one embodiment of the present application;

[0021] Figure 6 This is a flowchart of a method for identifying the category of a cookware provided in another embodiment of the present application. DETAILED DESCRIPTION

[0022] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0023] Some processes described in the specification, claims, and figures of this application include multiple operations that appear in a specific order. These operations may be executed in a different order than the order in which they appear in this document, or in parallel. Operation numbers, such as 101 and 102, are merely used to distinguish between different operations and do not imply any order of execution. Furthermore, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that terms such as "first" and "second" are used to distinguish between different messages, devices, modules, etc., and do not imply a sequential order, nor do they limit "first" and "second" to different types. It should also be noted that the terms "comprise," "include," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a product or system comprising a set of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such product or system. Without further limitation, the phrase "comprises a..." does not preclude the presence of other identical elements in the product or system comprising the elements. Furthermore, the following embodiments are merely some of the embodiments of this application, and are not exhaustive. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making any creative work shall fall within the scope of protection of this application.

[0024] Before introducing the cookware category identification method provided in this application, the hardware device on which the method provided in this application can be implemented is described.

[0025] The hardware devices required to implement the method provided in this application are specially designed hardware devices that serve specific fields, such as Figure 1 The smart cooking device shown. The smart cooking device can be, but is not limited to, a cooking machine, a food processor, a chef machine, etc., and this embodiment does not limit this. Figure 1 The example shows a case where the intelligent cooking device is a stir-fry machine.

[0026] See also Figure 1The diagram shows the structure of a smart cooking device according to one embodiment of the present application. The smart cooking device includes a pot 10, a base 20, and a processor (not shown). The pot 10 is used to hold and cook food, and works with the functional components arranged on the base 20 to cook the food. The base 20 may include an operating platform for placing the pot 10 and providing support for the pot. Furthermore, the base 20 may also include other functional components, such as a heater, which may include a resonant circuit composed of a coil and a resonant capacitor, providing heat for the pot to heat the food inside; a display area for users to operate and control the smart cooking device, and displaying operation steps, cooking process parameters, and an operation area. The operation area may be integrated with the display area and allows users to operate and control the smart cooking device, such as inputting human-computer interaction control commands, selecting a digital recipe for the desired dish, and selecting a corresponding cooking mode (such as stir-fry, steam, boil, or stew). Figure 1 Other functional components that may be provided on the base 20 described in the above examples are not specifically shown or indicated.

[0027] In view of the multiple cooking modes on the base 20, a base 20 is often paired with multiple types of pots, such as a wok, a stew pot (such as a pressure cooker), and a steamer. Different types of pots generally have different manufacturing materials, processing techniques, and external coatings, which will result in different reflectivity of the same light. Based on this, in order to achieve intelligent identification of the type of pot, automatically activate the corresponding cooking mode based on the identification result, and automatically match digital recipes adapted to the pot type for user selection, in some embodiments, the lid opening mechanism 210 of the base 20 is further provided with a light emitter 2101 and a light receiver 2102. The light emitter 2101 is used to emit a detection light signal, such as infrared light, so that a subsequent processor can use the reflected light signal reflected by the pot 10 to identify the type of pot 10. The light receiver 2102 is used to obtain light signals, such as reflected light signals or ambient light signals reflected by the pot 10, and transmit the light signals to the processor. For an introduction to the specific locations of the optical transmitter 2101 and the optical receiver 2102 , please refer to the relevant contents of the following embodiments, which will not be described in detail here.

[0028] However, considering that different types of cookware may have the same material or outer coating, simply using the cookware's own characteristic light reflection ability cannot accurately identify the cookware's category. To address this issue, in some embodiments, the cookware 10 may also be provided with a marking element. The marking elements provided on different types of cookware 10 have different properties such as material, processing technology, or color. For example, a yellow marking element may be provided on a frying pan, and a blue marking element may be provided on a stew pot (such as a pressure cooker). The different light reflection abilities of the different colored marking elements can be used to achieve intelligent identification of the cookware's category.

[0029] The aforementioned processor is electrically connected to the optical transmitter 2101 and the optical receiver 2102. It can control the optical transmitter 2101 to emit a detection light signal and receive the light signal through the optical receiver 2102. Based on the received light signal, it executes a corresponding program pre-written into the processor to control and implement the logic of the cookware type identification method provided in this application. For details on how to control and implement the logic of the cookware type identification method provided in this application, please refer to the relevant content below and will not be repeated here.

[0030] In a specific implementation, the processor may be a single-chip microcomputer with data processing capabilities, a microcontroller unit (MCU), a central processing unit (CPU), a graphics processing unit (GPU), a processing chip based on a field programmable gate array (FPGA) or a complex programmable logic device (CPLD), etc., which is not limited in this embodiment.

[0031] Furthermore, in some other embodiments, the cookware 10 may be provided with a triggering member, and correspondingly, the base 20 may be provided with a sensing member. The triggering member and the sensing member may be any components that can cooperate to generate an induction signal. For example, the triggering member may be a magnetic member, and the sensing member may be a Hall effect element. Magnetic members with different magnetic strengths may be provided on different types of cookware. Magnetic members with different magnetic strengths will generate induction signals of varying strengths with the Hall effect element. The processor identifies the type of cookware 10 based on the inductive signal detected between the triggering member and the Hall effect element.

[0032] In addition to the above-mentioned light emitter, light receiver, processor, or trigger and sensor hardware structures, the smart cooking device may also be provided with some basic components of the smart cooking device. For example, the base 20 may also be provided with a foolproof structure 220 (such as Figure 2 As shown), memory, multiple contact points 240 (as Figure 4a As shown), a weight sensor, a power supply, an audio component, a display component, and so on. The foolproof structure 220 is used to ensure that the cookware is securely mounted on the base 20. A memory may be located within the base 20 and primarily stores one or more computer instructions. These instructions are executed by the processor, causing the processor to control the intelligent cooking device to perform corresponding functions and complete corresponding actions or tasks. In addition to storing computer instructions, the memory may also be configured to store various other data to support operations on the intelligent cooking device, such as characteristic information corresponding to the detection light signal emitted by the light emitter (such as light intensity and wavelength), light signals received by the light receiver (such as ambient light signals and reflected light signals from the cookware), and preset information related to the cookware (such as the properties of the cookware itself and the properties of the markings on the cookware). The markings are markings used to identify the type of cookware, such as marking tape. By executing the computer instructions stored in the memory and accessing various other data stored in the memory, the processor controls the intelligent cooking device to perform functions such as identifying the type of cookware and completing corresponding cooking tasks.

[0033] The plurality of contact points 240 may be provided on the top of the base 20, and the plurality of contact points are all circuits corresponding to the interior of the base 20 (eg Figure 4b In the technical solution provided in this embodiment, in addition to identifying the cookware category using the aforementioned methods of detecting light signals, sensing signals from the sensor and trigger components, etc., the processor can also identify the cookware category based on the impedance between any two of the multiple contact points detected. For the specific implementation of identifying the cookware category based on the impedance between any two contact points, please refer to the relevant content in the following embodiments and will not be detailed here.

[0034] It should be noted here that the specific interactions between the functional hardware structures of the smart cooking device and how the processor implements the function of identifying the category of the cookware based on the structural functional components arranged on the smart cooking device will be described in detail in the following embodiments.

[0035] Based on the hardware device structure described above, the following describes an embodiment of the cookware category identification method provided in this application.

[0036] Figure 5 FIG1 shows a flow chart of a method for identifying the type of cookware provided by an embodiment of the present application. The execution subject of the method is the processor described above. Figure 5 As shown, the method provided in this embodiment includes the following steps:

[0037] 101. Obtain an optical signal;

[0038] 102. Determine whether the light signal is a reflected light signal reflected by the cookware;

[0039] 103. When the light signal is a reflected light signal, identify the category of the cookware based on the light signal.

[0040] In actual applications, in a specific application scenario, such as Figure 1 In the cooking scenario shown, to detect the type of cookware, the base 20 is equipped with a light emitter 2101 and a light receiver 2102. Specifically, to ensure that when the cookware 10 is placed on the base 20, the detection light signal emitted by the light emitter 2101 is projected onto the cookware 10, and the light receiver 2102 is able to receive the reflected light signal from the cookware 10, the light emitter 2101 and the light receiver 2102 are arranged side by side on the lid opening mechanism 210, aligned with the side wall of the cookware 10, with a certain distance h1 between them. This distance h1 can be approximately 5 to 15 mm. When the user activates the smart cooking device to prepare food, the light emitter 2101 and the light receiver 2102 are simultaneously activated. The light emitter 2101 emits a detection light signal along the detection direction, and the light receiver 2102 collects the light signal in real time.

[0041] In a specific implementation, the light signal collected by the optical receiver 2102 may be an ambient light signal or a reflected light signal from the detection light signal reflected from the cookware 10. This depends on the placement of the cookware 10 on the base 20. For example, when the cookware 10 is not placed on the base 20, the detection light signal emitted by the light emitter 2101 is difficult to reflect due to the absence of obstacles in the detection direction. Therefore, the optical receiver 2102 cannot collect the reflected light signal from the detection light signal reflected from the cookware. However, because ambient light in the scene (such as sunlight, light from light sources such as lamps, etc.) acts on the surfaces of all objects in the scene, the optical receiver 2102 will collect the ambient light signal. For another example, when the cookware 10 is placed on the base 20, the detection light signal is projected onto the cookware 10 and reflected. The reflected light can be collected by the optical receiver 2102. At the same time, due to the presence of ambient light in the scene, the optical receiver 2102 may also collect the ambient light signal while collecting the reflected light signal from the detection light signal reflected from the cookware 10. That is, when the cookware 10 is placed on the base 20, the light signal collected by the optical receiver 2102 is the reflected light signal from the detection light signal reflected by the cookware 10. However, this reflected light signal may include the ambient light signal in the current environment and the reflected light signal from the actual and effective detection light signal reflected by the cookware. For ease of description, the reflected light signal from the actual and effective detection light signal reflected by the cookware is referred to as the effective reflected light signal.

[0042] It should be noted that when the cookware 10 is placed on the base 20, the foolproof structure 220 secures the cookware 10 to the base 20. Furthermore, the sidewall of the cookware 10 opposite the lid opening mechanism 210 is located at a distance h2 from the light emitter and light receiver. This distance h2 can be approximately 30 to 100 mm, ensuring that the detection light signal reflected from the cookware 10 and the reflected light signal can be received by the light receiver. Furthermore, to reduce the influence of ambient light and secondary reflected light signals, the housing of the lid opening mechanism 210 surrounding the light emitter 2101 and light receiver 2102 can be black to minimize the absorption of light incident on the light emitter and light receiver. Secondary reflected light signals refer to light signals reflected from the cookware 10 or ambient light signals projected onto other locations around the light receiver 2102, resulting from multiple reflections. If this secondary reflected light signal is collected by optical receiver 2102, the light signal collected by optical receiver 2102 will contain not only the ambient light signal in the current environment and the effective reflected light signal, but also the secondary reflected light signal. This interference from the secondary reflected light signal will further reduce the accuracy of subsequent identification of the cookware category using the optical signal. However, the black housing has a strong light absorption effect, which can completely or largely absorb the light projected to other locations around the location of optical receiver 2102, thereby reducing the occurrence of secondary reflections. Therefore, when the cookware category is subsequently identified using the optical signal, the impact of the secondary reflected light signal on the identification result can be reduced.

[0043] Based on the above description, the optical signal in step 101 can be acquired by an optical receiver. In specific implementations, the optical signal can be an ambient light signal acquired by the optical receiver, or it can be a reflected light signal from the cookware reflected by the detection light signal acquired by the optical receiver. The reflected light signal may also contain ambient light. Therefore, to identify the type of cookware using the optical signal, it is necessary to first determine whether the optical signal is a reflected light signal from the cookware.

[0044] Here, continue to see Figure 1 Considering that the weight of the base 20 is different when a cookware is placed on it and when it is not, the weight of the base 20 can be determined by using a sensor to monitor the weight of the base 20 and provide a feedback signal. Furthermore, the weight of the base can be used to determine whether the light signal is a reflected light signal from the cookware. That is, in a specific implementation, the above-mentioned step 102 of "determining whether the light signal is a reflected light signal from the cookware" can specifically include:

[0045] The weight of the base is collected; when it is determined that a cookware is placed on the base according to the weight, the light signal is determined to be a reflected light signal reflected back by the cookware.

[0046] In a specific implementation, a weight sensor can be installed on the base. When the weight sensor detects that the weight of the base 20 is greater than a preset threshold, it is determined that a cookware is placed on the base 20. The preset threshold can be flexibly set based on the corresponding weight of the base 20 when no cookware is placed (hereinafter referred to as the reference weight). For example, the preset threshold can be the reference weight, or it can be slightly greater than the reference weight, but the degree of excess is less than the weight of the cookware, etc., which is not limited here.

[0047] In another specific achievable technical solution, the above-mentioned step 102 of “determining whether the light signal is a reflected light signal reflected back by the cookware” may specifically include:

[0048] Collecting state data of the resonant circuit in the base; and determining that a cookware is placed on the base based on the state data, determining that the light signal is a reflected light signal reflected back by the cookware.

[0049] When implementing it specifically, Figure 1 In the illustrated cooking scenario, the base 20 provides heat to the cookware 10 via IH (induction heating) technology. IH electromagnetic heating is achieved through a resonant circuit (not shown) within the base 20, consisting of a coil and a resonant capacitor. The resonant circuit generates different operating status data (such as oscillation duration, energy decay time, and number of pulses) when no load (i.e., without the cookware 10) is present versus when loaded (i.e., with the cookware present). Specifically, for example, when the cookware is absent, the resonant circuit typically undergoes a longer damped oscillation (with a resonant period of approximately 40 μs). Consequently, the energy decay time is also longer, and the number of pulses per unit time is lower. Conversely, when the cookware is present, the damping effect of the cookware reduces the resonant circuit's damped oscillation time to almost zero (here, the total time it can resonate is almost zero, meaning that once the cookware is placed on the base 20, the resonant circuit immediately stops oscillating). Energy decay is also faster, and the number of pulses per unit time is significantly higher than when the cookware is absent. To this end, it is possible to collect operating status data of the resonant circuit within the base 20 and, based on this data, determine whether a cookware is placed on the base 20. If the collected status data shows a damped oscillation time that is almost zero, energy decay is accelerated, and the number of pulses per unit time is high, it can be determined that a cookware is placed on the base 20, and thus it can be determined that the optical signal collected by the optical receiver is a reflected light signal reflected from the cookware.

[0050] In order to improve the accuracy of the recognition results, this embodiment sets markers with different attribute characteristics on the side walls of different types of cookware, and uses the different reflective capabilities of the markers with different attribute characteristics to detect light signals to achieve the purpose of identifying the category of the cookware. Figure 1 As shown, the marking member 110 is provided on the side wall of the pot 10 opposite to the lid opening mechanism 210. Specifically, the position of the marking member 110 corresponds to the position of the light emitter 2101 and the light receiver 2102, so as to ensure that the detection light signal can be projected onto the marking member 110, and after being reflected by the marking member 110, the reflected light signal can be received by the light receiver 2102. Based on this, when it is determined that the light signal collected by the light receiver 2102 is the reflected light signal reflected by the pot 10, the light signal is specifically the reflected light signal reflected by the marking member 110 on the pot 10. Among them, the marking member 110 can be, but is not limited to, Figure 1 The marking tape shown in the figure may be in a rectangular, polygonal, elliptical, etc. shape, which is not limited here.

[0051] When it is determined that the light signal is a reflected light signal reflected by the cookware, the category of the cookware can be identified based on the attribute characteristics corresponding to the light signal and the relevant preset information. That is, one possible implementation of "identifying the category of the cookware based on the light signal" in the above 103 is:

[0052] 1031. Obtain a first attribute feature corresponding to the optical signal;

[0053] 1032. Determine whether there is target preset information matching the first attribute feature among multiple preset information; wherein one preset information corresponds to one type of cookware;

[0054] 1033. When the target preset information exists, use the cookware type corresponding to the target preset information as the category to which the cookware belongs.

[0055] In step 1031 above, the first attribute characteristic corresponding to the optical signal may include, but is not limited to, wavelength, frequency, color, and light intensity. Wavelength, frequency, and color are correlated. Therefore, when acquiring the attribute characteristic corresponding to the optical signal, only one of wavelength, frequency, and color may be acquired, and this embodiment does not impose a limitation thereto.

[0056] In the above 1032, the plurality of preset information is set for a plurality of different types of cookware, that is, one preset information corresponds to one type of cookware. When setting the plurality of preset information, it is specifically set based on the reflectivity of the detection light signal of the different marking members set on the different types of cookware.

[0057] For example, see Figure 1As shown, assuming that the intelligent cooking device includes two types of cookware, a frying pan and a stew pot (such as a pressure cooker), markers 110 with different materials, processing techniques, or colors can be provided on the frying pan and the stew pot, respectively. For example, the frying pan can be provided with a yellow marker made of aluminum alloy, while the stew pot can be provided with a blue marker made of stainless steel. The markers on the frying pan and the stew pot also have different surface smoothness due to their different processing techniques. If the markers provided on the frying pan and the stew pot have different materials, processing techniques, and colors, the energy loss generated by the detection light signal when projected onto the markers on the frying pan and the stew pot will also be different. Since light energy e is calculated by multiplying the frequency f of light and Planck's constant h, and the wavelength λ of light is calculated as the speed of light c / the frequency f of light, and the energy e of light is proportional to the intensity of light, when the detection light signal is projected onto the marker 110, energy loss occurs, causing the light energy corresponding to the reflected light signal reflected by the marker 110 to be less than the light energy corresponding to the detection light signal. This, in turn, causes changes in the frequency f, wavelength λ, color, and intensity of the reflected light signal. Based on this, when initially setting the corresponding preset information for frying pans and stew pots, extensive experimental research and analysis were conducted. First, the energy losses caused by the respective markers on the frying pans and stew pots were determined. Then, based on the corresponding properties of the detection light signals, the corresponding preset information for the frying pans and stew pots was set. The preset information includes the range of possible properties (such as wavelength, frequency, color, and intensity) of the reflected light signal after the detection light signal is projected onto the marker on the corresponding pot. The preset information and the corresponding cookware may be associated and stored in the data storage format shown in Table 1 so as to be called when needed.

[0058] Table 1

[0059]

[0060] It should be noted that the features in the preset information are represented using a feature range format. This is because, in the process of determining the different energy losses caused by the detection light signal based on the attribute characteristics corresponding to the marking members of different types of cookware, the energy loss results determined are generally subject to error due to various factors. Using a feature range representation improves error tolerance. Thus, if the first attribute characteristic corresponding to the light signal acquired in step 1031, such as wavelength, falls within a wavelength range specified in the preset information, the cookware category corresponding to the preset information can be considered to be the category of the cookware currently placed on the base 20.

[0061] However, in specific implementations, in order to reduce the impact of the ambient light signal on the results of the category to which the cookware belongs, different strategies will be adopted for different ambient light signals to determine whether there is target preset information that matches the first attribute feature in multiple preset information. Specifically, when the ambient light signal in the current environment is strong, the light signal collected by the optical receiver may contain the ambient light signal in the current environment and the reflected light signal (i.e., the effective reflected light signal) reflected back by the marker on the cookware from the real and effective detection light signal, and the ambient light signal may have a greater impact on the effective reflected light signal. Therefore, in order to eliminate the influence of the ambient light signal, a difference method can be used to determine whether there is target preset information that matches the first attribute feature in multiple preset information. Specifically, it is determined whether there is target preset information that matches the difference feature between the attribute feature corresponding to the first attribute feature and the ambient light signal in multiple preset information. Conversely, if the ambient light signal is weak, even if the ambient light signal exists in the light signal, its impact on the effective reflected light signal is relatively small, or even negligible. In this case, it is possible to directly determine whether there is target preset information that matches the first attribute feature in multiple preset information. Based on this,

[0062] The above-mentioned step 1032 of “determining whether there is target preset information matching the first attribute feature among the plurality of preset information” can be specifically implemented by the following steps:

[0063] 10321. Determine the matching strategy;

[0064] 10322. Determine corresponding matching parameters based on the first attribute characteristics according to the matching strategy;

[0065] 10323. Search the plurality of preset information for a feature range in which the matching parameter is located; wherein one preset information includes at least one feature range;

[0066] 10324. Use the preset information corresponding to the feature range of the found matching parameter as the target preset information.

[0067] In one feasible technical solution, the above step 10321 “determining a matching strategy” may specifically include the following steps:

[0068] A11. Obtain a second attribute characteristic of the detection light signal and a third attribute characteristic of the ambient light signal;

[0069] A12. Perform data analysis on the second attribute feature and the third attribute feature to determine one of the first strategy and the second strategy as the matching strategy.

[0070] In a specific implementation, if it is determined that the light intensity corresponding to the current ambient light signal is greater than or equal to the light intensity corresponding to the detection light signal, the ambient light signal is considered to be too strong and has a significant impact on the effective reflected light signal. In this case, the first strategy can be determined to be adopted, specifically, the matching parameter is determined based on the difference between the first attribute feature corresponding to the light signal and the third attribute feature corresponding to the ambient light signal. Conversely, if it is determined that the light intensity corresponding to the ambient light signal is less than the light intensity corresponding to the detection light signal, the ambient light signal is considered to be weak and has a smaller impact on the effective reflected light signal. In this case, the second strategy can be determined to be adopted, namely, the first attribute feature corresponding to the light signal is directly used as the matching parameter. Of course, in addition to comparing light intensity to determine whether the ambient light signal is in an excessively strong state, other features, such as the wavelength and frequency of light, can also be used. This embodiment does not limit this. The specific process of using other features to determine whether the ambient light signal is in an excessively strong state can refer to the above-mentioned process of determining using light intensity, and will not be described in detail here.

[0071] Based on the above content, the above step 10322 "determining corresponding matching parameters based on the first attribute characteristics according to the matching strategy" may specifically include the following steps:

[0072] A21. When determining the matching parameters according to the first strategy, specifically: determining the matching parameters based on a difference between the first attribute feature and the third attribute feature;

[0073] A22. When determining matching parameters according to the second strategy, specifically: using the first attribute feature as the matching parameter.

[0074] The matching parameter determined based on the difference between the first attribute feature and the third attribute feature may specifically refer to the difference feature between the first attribute feature corresponding to the light signal and the third attribute feature corresponding to the ambient light signal.

[0075] In the above steps 10323 and 10324, each preset information includes at least one feature range. Therefore, after determining the matching parameters according to the corresponding matching strategy, the feature range where the matching parameters are located can be searched in multiple preset information, and the preset information corresponding to the feature range where the matching parameters are located can be used as the target preset information.

[0076] For example, referring to Table 1, assuming that the determined matching parameter is the first attribute feature corresponding to the light signal, the first attribute feature includes multiple features such as light wavelength λ, light frequency f, light color value c and light intensity L, if at least one feature of the first attribute feature is within at least one feature range corresponding to the preset information corresponding to the cooking pot, for example, the light wavelength λ is within the wavelength range [λ 11 ,λ12 ], it can be determined that the preset information corresponding to the frying pan is the target preset information matching the first attribute feature.

[0077] In the above step 1033, when it is determined that there is target preset information matching the first attribute feature among the multiple preset information, the cookware category corresponding to the target preset information can be used as the category to which the cookware 10 currently placed on the base 20 belongs. For example, continuing the example in the above step 10323 and participating in Figure 1 When it is determined that the preset information corresponding to the frying pan is the target preset information that matches the first attribute feature, it can be explained that the pot 10 currently placed on the base 20 is a frying pan.

[0078] The above mainly introduces the method of setting corresponding preset information by taking advantage of the different reflective capabilities of the markers provided on different types of cookware to the detection light signal, so that when the light signal is determined to be a reflected light signal reflected back by the marker on the cookware, the category of the cookware currently placed on the base 20 is identified based on the light signal. In other embodiments, it is also possible not to provide a marker on the cookware, but to take advantage of the fact that different types of cookware have different reflective capabilities to the detection light signal due to their own characteristics, and set corresponding preset information, so that when the light signal is determined to be a reflected light reflected back by the cookware itself, the category of the cookware currently placed on the base 20 is identified based on the light signal. Specifically,

[0079] For example, see Figure 1 As shown, assume that the intelligent cooking device includes two types of pots: a frying pan and a stew pot. Typically, the frying pan has a black coating on its outer surface, while a stew pot, such as a pressure cooker, has a metallic stainless steel coating on its outer surface. Furthermore, the frying pan and the pressure cooker are made of different materials, processing techniques, or outer coatings. Given these differences in materials, processing techniques, or outer coatings, the energy loss generated by the detection light signal when projected onto the frying pan and the pressure cooker, respectively, will also differ. This difference in energy loss will also cause the frequency f, wavelength λ, color c, and intensity L of the reflected light signal, respectively, to differ after reflection from the frying pan and the pressure cooker. Consequently, the type of pot currently placed on the base 20 can be identified based on the light signal and corresponding preset information. Specifically, in the process of using the different characteristics of different types of cookware to detect the different reflection capabilities of the light signal to realize the process of identifying the category of the cookware currently placed on the base 20, the corresponding preset information setting involved, and the specific implementation process of identifying the category of the cookware based on the light signal when it is determined that the light signal is a reflected light signal reflected back by the cookware itself, etc., can be referred to the process of using the marking member to complete the category identification of the cookware as described above, and will not be described in detail here.

[0080] As the preferred method for identifying the category of cookware in this embodiment, it is preferred to use a marking part to complete the identification of the category to which the cookware belongs. This can avoid the situation where different types of cookware, such as a frying pan and a boiling pot (such as a soup pot), have the same material, outer surface coating or processing technology, and it is impossible to accurately identify whether the cookware is a frying pan or a boiling pot.

[0081] The technical solution provided by this embodiment can, based on the acquired light signal, identify the category of the cookware based on the light signal if the light signal is determined to be a reflected light signal reflected by the cookware. Therefore, the technical solution provided by this embodiment can enable the smart cooking device to autonomously identify the category of the cookware, thereby enabling the smart cooking device to automatically activate the cooking mode adapted to the category of the cookware and recommend digital recipes adapted to the cookware to the user, thereby improving the intelligence level of the smart cooking device and enhancing the user experience.

[0082] Furthermore, considering that the color and surface smoothness of the marking element on the cookware (or the cookware itself) may change with the number of times or total usage of the cookware, this will cause the marking element (or the cookware itself) to change its ability to reflect the detection light signal. Therefore, to ensure that the category of the cookware can be accurately determined, the method provided in this embodiment may further include the following steps:

[0083] 104. Obtain monitoring data obtained by monitoring any one of the multiple types of cookware;

[0084] 105. Based on the monitoring data, modify the preset information corresponding to the type of cookware.

[0085] In the above 104, the monitoring data may refer to the data related to the type of pot obtained after monitoring any type of pot among multiple types of pots. In specific implementation, the monitoring data may refer to the data related to the pot currently placed on the base obtained after determining the type to which the pot currently placed on the base belongs. For example, the pot currently placed on the base belongs to a frying pan, and the monitoring data is the data related to the frying pan. The above monitoring data may include but is not limited to at least one of the following: the number of times it has been used, the total usage time, the interval between the current time and the production time, etc. Correspondingly, the above 105 "based on the monitoring data, the preset information corresponding to the type of pot is corrected" may specifically include:

[0086] 1051. Determine, based on the monitoring data, whether the preset information corresponding to the type of cookware satisfies a correction condition;

[0087] 1052. When the modification condition is met, determining the degree of change based on at least one of the number of times used, the total usage time, and the interval between the current time and the production time;

[0088] 1053. Modify the preset information corresponding to the type of cookware according to the change degree and the matching parameters.

[0089] In the above 1051, a corresponding judgment parameter can be first determined based on at least one of the number of times the cookware has been used, the total usage time, and the interval between the current time and the production time in the monitoring data; wherein the total usage time can be obtained by statistically analyzing the duration of each use of the cookware. When it is determined that the judgment parameter meets the preset condition, it is determined that the target preset information meets the update condition. The above-mentioned determined judgment parameter can be any one of the number of times the cookware has been used, the total usage time, and the interval between the current time and the production time, or any two, or all of them are judgment parameters, which are not limited here. In the case where there is only one judgment parameter, if the judgment parameter meets the corresponding preset condition, it can be considered that the preset information corresponding to the type of cookware meets the correction condition; in the case where there are multiple judgment parameters, if all judgment parameters meet the corresponding preset condition or any one of the multiple judgment parameters meets the corresponding preset condition, it can be considered that the preset information corresponding to the type of cookware meets the correction condition, which is not limited here.

[0090] For example, the determined judgment parameters include: the number of times used and the total usage time. If the number of times used is greater than or equal to the preset number of times and the total usage time is greater than or equal to the preset time, it can be considered that the preset information corresponding to the type of cookware meets the correction conditions, otherwise it is not satisfied.

[0091] In step 1052 above, after determining that the preset information corresponding to the type of cookware meets the update conditions, the degree of change can be determined based on at least one of the number of times the cookware has been used, the total usage time, and the interval between the current time and the production time. In a specific implementation, for example, if the degree of change is determined based on the total usage time and the interval between the current time and the production time, the corresponding degree of change can be determined based on the degree of influence of the total usage time and the interval time on changes in the marking on the cookware (or the cookware itself), as determined through extensive experimental research.

[0092] In the above step 1053, the upper and lower limits of the corresponding feature range in the preset information corresponding to the type of cookware can be determined based on the change degree and the matching parameter, thereby updating the preset information corresponding to the type of cookware. For example, continuing the example in steps 10323 and 10324 above, and referring to Table 1, assuming that the determined matching parameter is the first attribute feature corresponding to the optical signal, and the wavelength of the light in the attribute feature is λ, and λ is within the wavelength range [λ 11 ,λ 12], that is, the preset information corresponding to the type of cookware is the preset information corresponding to the cooking pot shown in Table 1. If the determined change degree is Δ, it can be concluded that the upper and lower limits of the wavelength range in the preset information corresponding to the cooking pot should be λ-Δ and λ+Δ. Based on this, the wavelength range in the original preset information corresponding to the cooking pot is modified, that is, the wavelength range is changed from the original [λ 11 ,λ 12 ] will be corrected to [λ-Δ, λ+Δ] so that when the category of the cookware is identified again in the future, it can be identified based on the corrected target preset information.

[0093] In summary, the method for identifying the category of cookware provided in this embodiment can be summarized as follows: Figure 6 The process shown is as follows. That is, the intelligent cooking device is turned on, the light emitter emits a detection light signal along the detection direction, and the light receiver monitors in real time (i.e., collects the light signal in real time). It detects whether a pot is placed on the base. When a pot is detected on the base, the light signal collected by the light receiver is determined to be an ambient light signal, and the ambient light signal is recorded and stored. Furthermore, it is determined whether the light intensity of the ambient light signal is too strong. If the ambient light signal is too strong, the difference strategy (i.e., the first strategy described above) will be adopted to complete the identification of the category of the pot when the pot is subsequently detected on the base. Conversely, if the ambient light signal is weak, the general strategy (i.e., the second strategy described above) will be adopted to complete the identification of the category of the pot when the pot is subsequently detected on the base. In addition, before the pot is detected on the base, the stored ambient light signal will be continuously updated based on the ambient light signal collected in real time by the light receiver.

[0094] When a pot is detected on the base, the light signal collected by the optical receiver is determined to be a reflected light signal reflected by the pot from the detection light signal. If, based on the ambient light signal, a difference strategy is determined to be used to identify the pot's category, the difference between the attribute characteristics corresponding to the light signal and the attribute characteristics corresponding to the ambient light signal is calculated. The pot's category is identified by determining whether the difference characteristics are within a feature range in preset information. If, based on the ambient light signal, a general strategy is determined to be used to identify the pot's category, the pot's category is identified by directly determining whether the attribute characteristics corresponding to the light signal are within a feature range in preset information. If it is determined that the difference characteristics (or the attribute characteristics corresponding to the light signal) are within a feature range in preset information, the category of the pot currently placed on the base can be determined based on the pot category associated with the preset information, and the corresponding preset information can be updated. If the difference feature (or the attribute feature corresponding to the light signal) is determined to be outside the feature range in the preset information, it is determined that the category of the cookware cannot be identified. At this time, the above identification process can be repeated until the category of the cookware is identified. Alternatively, other identification methods can be combined, such as identifying the category of the cookware based on the impedance between two of the multiple contact points. Of course, if the category of the cookware can be identified, in order to improve the identification accuracy, the final category of the cookware can also be comprehensively identified based on the impedance between two of the multiple contact points. This is not limited here.

[0095] Based on this, further, the method provided in this embodiment may also include the following steps:

[0096] 106. Obtain impedance between any two of a plurality of contact points; wherein the plurality of contact points are in contact with the cookware;

[0097] 107. Determine a final category to which the cookware belongs based on the impedance and a result of identifying the category of the cookware based on the optical signal.

[0098] In the above 106, see Figure 1 、 4a and Figure 4b As shown, a plurality of contact points 240 are provided on the top of the base 20, and the plurality of contact points are all circuits corresponding to the inside of the base 20 (such as Figure 4bThe plurality of contact points 240 are convex contact points, and are made of a conductive material, such as an aluminum alloy. When the cookware 10 is fixedly mounted on the base 20, the plurality of contact points 240 will be in full contact with the cookware 10, so that the circuit between any two of the plurality of contact points can be connected. Due to the differences in materials or outer coatings of different types of cookware 10, the impedance formed between any two contact points when they come into contact with different cookware 10 will also be different. For example, stainless steel has good conductivity, so when two contact points come into contact with a stainless steel cookware (such as a pressure cooker), a smaller impedance will be detected between the two contact points. For another example, since the black layer is an insulating material, when the two contact points come into contact with a cookware with an outer protective black layer (such as a frying pan), a larger impedance will be detected between the two contact points, and so on. Therefore, the type of the cookware can be identified based on the impedance between any two contact points.

[0099] Figure 4a FIG shows a case where three contact points (ie, contact point A, contact point B, and contact point C) are provided on the base 20. Figure 4b Shown in Figure 4a The circuit diagram corresponding to the three contact points shown in FIG. 1 shows the impedance calculation process between any two of the three contact points as follows: When it is detected that the pot 10 is placed on the base 20, the pot is in contact with the three contact points on the base 20. Assume that the processor first detects that contact point A and contact point B are in contact with the pot, and the impedance formed between the two is R AB , the processor will first control S A and S B Switch closed, S C The switch is disconnected, and the set voltage (such as 3.3V) is output to the A contact point, and the ADC (Analog-to-Digital Converter) mode is set to the B contact point to collect the voltage of the B contact point; according to the voltage V B And the resistance R connected to the ground of contact B B , the current I in the circuit between contact point A and contact point B can be calculated AB =V B / R B At the same time, the voltage V at contact point A can be A And the voltage V at contact B B , calculate the voltage V of the circuit between contact point A and contact point B AB =V A -V B ; Further, the voltage V of the circuit between contact point A and contact point B AB and Circuit I AB , we can get the impedance R between contact point A and contact point BAB =V AB / I AB Similarly, the impedance R between contact point B and contact point C can also be calculated separately. BC , the impedance R between contact point A and contact point C AC The specific calculation process can be found in the calculation of the impedance R between contact point A and contact point B. AB The process will not be described in detail here.

[0100] In the above 107, based on the impedance between each of the multiple contact points calculated in step 106, the category of the pot currently placed on the base can also be determined based on the impedance between each of the contact points. For example, continuing the example in step 106, taking a frying pan with a black coating and a pressure cooker made of stainless steel as examples, if the impedance between any two contact points is less than a first threshold (the first threshold is a smaller threshold, such as 0.5K), the pot currently placed on the base can be determined to be a pressure cooker; conversely, if the impedance between any two contact points is greater than the first threshold (the second threshold is a larger threshold, such as 20K), the pot currently placed on the base can be determined to be a frying pan.

[0101] Based on this, if the category of the pot currently placed on the base cannot be identified based on the optical signal, the result of impedance recognition between each pair of the multiple contact points can be directly used as the final category of the pot. If the category of the pot currently placed on the base can be identified based on the optical signal, the result of the pot's category recognition based on the optical signal can be directly used as the final category of the pot. Alternatively, the final category of the pot can be determined by combining the results of the pot's category recognition based on the optical signal and the results of the pot's category recognition based on impedance recognition between each pair of the multiple contact points, which is not limited in this embodiment. However, considering that the circuits between multiple contact points are prone to short circuiting when exposed to water, as a preferred example of this embodiment, if the category of the pot can be identified based on the optical signal, the result of the pot's category recognition based on the optical signal is preferentially used as the final category of the pot.

[0102] The above mainly describes how to identify the category of the cookware by detecting light signals and impedance between two of the multiple contact points. In addition, in some other embodiments, the following methods can also be used to identify the category of the cookware. Specifically,

[0103] Method 1: Identify the category of the cookware based on the induction signals obtained from the trigger component and the sensor component.

[0104] For specific implementation, see Figures 1 to 3As shown, the sensor is a Hall effect element and the trigger is a magnetic element. When the cookware 10 is placed on the base 20, the cookware is fixed to the base 20 due to the foolproof structure 220. In this embodiment, different types of cookware 10 are equipped with magnetic elements (not shown) of different magnetic strengths. Accordingly, the base 20 is provided with a mounting structure 230, which has a Hall effect element (not shown) embedded therein. The Hall effect element is electrically connected to the processor. When the cookware 10 is placed on the base 20, the positional relationship between the magnetic element on the cookware and the Hall effect element on the base is fixed, for example, the magnetic element and the Hall effect element are positioned in a corresponding manner. Since different types of cookware are placed on the base, the induction signals generated between the magnetic element and the Hall effect element will also be different. The induction signals between the magnetic element and the Hall effect element of different types of cookware are pre-associated and stored with the corresponding cookware type. This allows the type of cookware currently placed on the base 20 to be identified based on the acquired induction signals between the magnetic element and the Hall effect element.

[0105] Method 2: Identify the category of the cookware based on the collected status data of the resonant circuit in the base; wherein the resonant circuit is a circuit composed of a coil disk and a resonant capacitor.

[0106] For specific implementation, see Figure 1 In the cooking scenario shown, different types of cookware typically have different materials. When a cookware 10 of different materials is placed on a base 20, the processor controls a resonant circuit (not shown) within the base 20, consisting of a coil disk and a resonant capacitor, to perform IH electromagnetic heating on the cookware 10, providing a heat source for the cookware 10. The resonant circuit's corresponding state data, such as oscillation time and energy decay time, will also vary depending on the material of the cookware. Therefore, different types of cookware can be distinguished by collecting the corresponding state data of the resonant circuit. For specific implementations, please refer to the prior art and will not be described in detail here.

[0107] From the above, it can be seen that the technical solution provided in this embodiment can enable the smart cooking device to have the ability to identify the category to which the cookware belongs, so that the smart cooking device can autonomously run the corresponding cooking mode according to the category to which the cookware belongs, and recommend digital recipes that are suitable for the cookware to the user, etc. These are all conducive to improving the intelligence of the smart cooking device and lowering the user usage threshold.

[0108] In the above, the technical solution provided by the embodiment of the present application is mainly introduced from the software perspective. The following describes the technical solution provided by the embodiment of the present application from the hardware perspective.

[0109] An embodiment of the present application provides a smart cooking device. Figure 1 and Figure 4aAs shown, the intelligent cooking device may specifically include: a pot 10, a base 20 and a processor (not shown in the figure).

[0110] The base 20 is provided with an optical receiver 2102 for receiving optical signals;

[0111] The processor is electrically connected to the optical receiver 2102 and is used to obtain an optical signal through the optical receiver; determine whether the optical signal is a reflected light signal reflected back by the cookware; and when the optical signal is a reflected light signal, identify the category of the cookware based on the optical signal.

[0112] Furthermore, the base 20 is provided with a plurality of contact points 240, which are in contact with the cookware 10. Accordingly, the processor is further configured to obtain impedances between any two of the plurality of contact points; and determine a final category of the cookware based on the impedances and the result of identifying the category of the cookware based on the optical signal.

[0113] Furthermore, a marking member is provided on the cookware 10, and a light emitter 2101 is also provided on the base 20; accordingly, the reflected light signal is a signal reflected back by the marking member from the detection light signal emitted by the light emitter.

[0114] In addition to the above-mentioned components such as the pot, base, light receiver, and processor, the intelligent cooking device provided in this embodiment may also have other basic components. For example, the base 20 may also be provided with foolproof parts, memory, display, audio components, human-computer interaction devices (such as touch screens, control keys, semantic interaction devices, etc.), etc. The above-mentioned memory is mainly used to store one or more computer instructions, which can be executed by the processor, so that the processor controls the intelligent cooking device to achieve corresponding functions and complete corresponding actions or tasks. For example, the processor is coupled to the memory, and by executing one or more computer instructions stored in the memory, it can implement the steps in the above-mentioned method for identifying the category of the pot.

[0115] In addition, the memory can also be configured to store various other data to support operations on the processor. Examples of such data include property characteristics corresponding to the detected light signal, preset information corresponding to different types of cookware, and so on. The memory can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk.

[0116] It should be noted that any steps not fully described in the intelligent cooking device provided in this embodiment can be referred to in the corresponding sections of the aforementioned embodiments and will not be further elaborated here. Furthermore, in addition to the aforementioned steps, the intelligent cooking device provided in this embodiment may also include some or all of the other steps in the aforementioned embodiments. For details, please refer to the corresponding sections of the aforementioned embodiments and will not be further elaborated here.

[0117] Accordingly, an embodiment of the present application further provides a computer-readable storage medium storing a computer program, which, when executed by a computer, can implement the steps or functions of the method for identifying the category of the cookware provided in the above embodiments.

[0118] Finally, the technical solutions provided in the embodiments of this application are described in conjunction with several specific application scenarios.

[0119] Scene 1

[0120] See also Figure 1 In the cooking scene shown, it is assumed that the intelligent cooking device is equipped with two types of cookware 10, a frying pan and a pressure cooker. The frying pan is provided with a yellow marking piece, and the pressure cooker is provided with a blue marking piece, and the marking pieces provided on the frying pan and the pressure cooker are made of different materials and processed. In addition, it is assumed that the wavelength of the detection light signal emitted by the light emitter provided on the base 20 is L0. After experimental research and analysis, it is found that the wavelength of the reflected light signal initially reflected by the marking pieces on the frying pan and the pressure cooker is in the range of [L 11 , L 12 ]、[L 21 , L 22 ] range, the initial preset wavelength characteristic range corresponding to the frying pan can be set to [L 11 , L 12 ], and set the preset wavelength characteristic range corresponding to the pressure cooker to [L 21 , L 22 ].

[0121] Subsequently, when a pot is detected to be placed on the base 20, if the matching parameter is determined to be the wavelength L1 corresponding to the reflected light signal reflected by the marker on the pot according to the corresponding matching strategy, and the wavelength L1∈[L 11 , L 12 ], it can be determined that the pot currently placed on the base 20 is a frying pan, and the subsequent intelligent cooking device can automatically start the cooking mode adapted to the frying pan to cook delicious food. In addition, further, if the update conditions are met, the wavelength characteristic range corresponding to the original preset frying pan can be [L 11 , L 12 ] to update, that is, the preset wavelength characteristic range is [L 11 , L12 ] is updated to [L1-Δ, L1+Δ].

[0122] Scene 2

[0123] Continue to see Figure 1 In the cooking scenario shown, it is assumed that the smart cooking device is equipped with two types of cookware 10, a frying pan and a pressure cooker. The frying pan and the pressure cooker have different materials, processing technologies, and outer coatings. In addition, it is assumed that the wavelength of the detection light signal emitted by the light emitter on the base 20 is L0. After experimental research and analysis, the wavelength of the reflected light signal initially reflected by the frying pan and the pressure cooker is [L 11 ', L 12 ']、[L 21 ', L 22 '] range, the initial preset wavelength characteristic range corresponding to the frying pan can be set to [L 11 ', L 12 '], and set the preset wavelength characteristic range corresponding to the pressure cooker to [L 21 ', L 22 '].

[0124] Subsequently, when a pot is detected to be placed on the base 20, if the matching parameter is determined according to the corresponding matching strategy to be the difference wavelength ΔL between the wavelength L1 corresponding to the reflected light signal reflected by the pot and the wavelength L2 corresponding to the ambient light signal, and the difference wavelength ΔL∈[L 21 ', L 22 '], it can be determined that the cookware currently placed on the base 20 is a pressure cooker. Further, if the update condition is met at this time, the wavelength characteristic range corresponding to the original preset pressure cooker can be updated based on the determined change degree Δ' and the difference wavelength ΔL, that is, the preset wavelength characteristic range can be changed to [L 21 ', L 22 '] is updated to [ΔL-Δ', ΔL+Δ'].

[0125] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, i.e., they may be located in one location or distributed across multiple network units. Some or all of the modules may be selected based on actual needs to achieve the objectives of the present embodiment. Persons of ordinary skill in the art will be able to understand and implement the present invention without inventive effort.

[0126] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, or of course, by means of hardware. Based on this understanding, the essence of the above technical solution or the part that contributes to the prior art can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a magnetic disk, an optical disk, etc., and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or certain parts of the embodiments.

[0127] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for identifying the type of cookware, characterized in that: include: Acquire optical signals; determining whether the light signal is a reflected light signal of the detection light signal reflected back by the cookware; When the light signal is a reflected light signal and the light intensity corresponding to the ambient light signal is greater than or equal to the light intensity corresponding to the detection light signal, determining a matching parameter based on a difference between a first attribute characteristic corresponding to the light signal and a third attribute characteristic corresponding to the ambient light signal; When the light signal is a reflected light signal and the light intensity corresponding to the ambient light signal is less than the light intensity corresponding to the detection light signal, the first attribute feature corresponding to the light signal is used as the matching parameter; Searching for a characteristic range of the matching parameter in a plurality of preset information; wherein one preset information corresponds to one type of cookware; Identifying the category of the cookware based on preset information corresponding to the feature range within which the found matching parameters are located; Based on the recognition result, the corresponding cooking mode is started and a digital recipe suitable for the category of the cookware is matched.

2. The method according to claim 1, characterized in that Also includes: Acquiring monitoring data obtained by monitoring any one of multiple types of cookware; According to the monitoring data, the preset information corresponding to the type of cookware is modified.

3. The method according to claim 2, characterized in that The monitoring data includes at least one of the following: the number of times used, the total usage time, and the interval between the current time and the production time; as well as According to the monitoring data, the preset information corresponding to the type of cookware is modified, including: Based on the monitoring data, determining whether the preset information corresponding to the type of cookware meets the correction condition; When the correction condition is met, determining the degree of change based on at least one of the number of times used, the total usage time, and the interval between the current time and the production time; According to the degree of change and the matching parameters, the preset information corresponding to the type of cookware is modified.

4. The method according to any one of claims 1 to 3, characterized in that Also includes: Obtaining impedance between any two of a plurality of contact points; wherein the plurality of contact points are in contact with the cookware; The final category of the cookware is determined according to the impedance and the result of the identification of the category of the cookware based on the optical signal.

5. The method according to any one of claims 1 to 3, characterized in that Determining whether the light signal is a reflected light signal reflected back by the cookware includes: collecting the weight of the base; and when determining that a cookware is placed on the base based on the weight, determining that the light signal is a reflected light signal reflected back by the cookware; or Collecting state data of the resonant circuit in the base; and determining that a cookware is placed on the base based on the state data, determining that the light signal is a reflected light signal reflected back by the cookware.

6. The method according to any one of claims 1 to 3, characterized in that When the optical signal is a reflected light signal, the optical signal is specifically a reflected light signal reflected back by a marking member on the cookware.

7. An intelligent cooking device, characterized in that: include: Cookware; a base, on which an optical receiver is provided for receiving optical signals; A processor is electrically connected to the optical receiver and is used to obtain an optical signal through the optical receiver; determine whether the optical signal is a reflected optical signal reflected back by the detection optical signal from the cookware; when the optical signal is a reflected optical signal and the light intensity corresponding to the ambient light signal is greater than or equal to the light intensity corresponding to the detection optical signal, determine a matching parameter based on the difference between the first attribute feature corresponding to the optical signal and the third attribute feature corresponding to the ambient light signal; when the optical signal is a reflected optical signal and the light intensity corresponding to the ambient light signal is less than the light intensity corresponding to the detection optical signal, use the first attribute feature corresponding to the optical signal as the matching parameter; search for a feature range in which the matching parameter is located in multiple preset information; wherein one preset information corresponds to a type of cookware; identify the category of the cookware based on the preset information corresponding to the feature range in which the matching parameter is located; start a corresponding cooking mode based on the identification result, and match a digital recipe adapted to the category of the cookware.

8. The intelligent cooking device according to claim 7, characterized in that: The base is further provided with a plurality of contact points, and the plurality of contact points are in contact with the cookware; and The processor is further configured to obtain impedances between any two of the plurality of contact points; and determine a final category to which the cookware belongs based on the impedances and an identification result of the category to which the cookware belongs based on the optical signal.

9. The intelligent cooking device according to claim 8 or 7, characterized in that: The cookware is provided with a marking piece; A light emitter is also provided on the base; The reflected light signal is a signal that is reflected back by the marking component from the detection light signal emitted by the light emitter.

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