CN117812770A - Intelligent induction cooker cooking method, system, electronic equipment and medium - Google Patents
Intelligent induction cooker cooking method, system, electronic equipment and medium Download PDFInfo
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Abstract
An intelligent induction cooker cooking method, an intelligent induction cooker cooking system, electronic equipment and a medium relate to the technical field of data processing. The method comprises the following steps: acquiring basic food material information and cooking mode information; determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information; generating a corresponding control instruction according to the heating scheme of the induction cooker; and sending the control instruction to an induction cooker control end to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation. According to the scheme, the induction cooker heating scheme is automatically generated according to the food material information provided by the user and the cooking mode selected, so that the effect of assisting the user in cooking and heating the food material to improve the cooking quality and improving the user experience is achieved.
Description
Technical Field
The application relates to the technical field of induction cookers, in particular to an intelligent induction cooker cooking method, an intelligent induction cooker cooking system, electronic equipment and a medium.
Background
With the acceleration of the pace of social life, people are increasingly demanding fast and convenient cooking modes. The induction cooker is a cooking tool which is very suitable for the modern life rhythm. The electromagnetic oven utilizes the principle of electromagnetic induction heating, a metal cooker is placed on the electromagnetic oven surface, and when the electromagnetic oven surface is electrified, a changing magnetic field is generated, eddy current is induced at the bottom of the cooker, so that the cooker is heated rapidly, and food is heated. Compared with the traditional heating modes such as a gas furnace, an electric heating wire and the like, the electromagnetic oven has the advantages of high heating speed, high efficiency, no open fire, safety and reliability.
At present, the traditional induction cooker cooking method mainly depends on manual adjustment of temperature and heating time of a user, which not only requires the user to have certain cooking knowledge and experience, but also requires the user to continuously monitor the whole cooking process so as to ensure that the food reaches ideal doneness.
However, in practical applications, most users cannot know about cooking of different food materials, and the traditional manual adjustment of temperature and time often causes the situation that the food materials are excessively heated or still not cooked due to negligence of the users, so that the cooking effect of the food materials is poor and the user experience is low. Thus, there is a need for improvements in current methods for induction cooker cooking.
Disclosure of Invention
The application provides an intelligent induction cooker cooking method, system, electronic equipment and medium, which have the effects of automatically generating an induction cooker heating scheme to cook food according to food information provided by a user and a cooking mode selected by the user, and assisting the user in improving cooking quality.
In a first aspect, the present application provides an intelligent induction cooker cooking method, comprising:
acquiring basic food material information and cooking mode information;
determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information;
generating a corresponding control instruction according to the heating scheme of the induction cooker;
and sending the control instruction to an induction cooker control end to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation.
Through adopting above-mentioned technical scheme, the system obtains the basis food material information and the culinary art mode information of selection that the user will cook through predetermineeing APP. The system then determines the appropriate induction cooker heating scheme, such as heating temperature, time, etc. parameters, based on the obtained food material and cooking mode information. And then generating a corresponding control instruction according to the determined heating scheme, and sending the control instruction to the control end of the induction cooker through a network. And the control end of the electromagnetic oven controls the electromagnetic oven to enter different working modes to perform intelligent heating operation according to the received control instruction. The intelligent cooking control based on different food materials and cooking modes can be realized, the uncertainty of experience required by manual cooking is eliminated, and an automatic and intelligent cooking process is realized, so that the cooking efficiency and the cooking effect are improved, and an integrated cooking experience is provided for a user.
Optionally, according to a preset APP, establishing a communication connection between the user terminal and the induction cooker control terminal; the basic food material information and the cooking mode information input by a user are acquired through the preset APP, the basic food material information comprises food material names, food material weights and food material types, and the cooking mode information comprises dish names and cooking method keywords.
By adopting the technical scheme, according to the application program preset on the user terminal, such as a smart phone, namely the preset APP, the user terminal is in communication connection with the system, and through the graphical interface of the preset application program, the user can input basic food material information, such as food material names, food material weights, food material types and the like. In addition, the user can also input cooking mode information such as dish names, key cooking method words and the like. The system acquires basic food material information and cooking mode information input by a user through the preset APP. The accuracy of information acquisition is effectively improved.
Optionally, inputting the food material names, the food material weights, the food material types, the dish names and the cooking method keywords into a preset scheme decision model to obtain the corresponding induction cooker heating scheme, wherein the induction cooker heating scheme comprises a heating duration adjusting scheme and a temperature adjusting scheme.
By adopting the technical proposal, the utility model has the advantages that,
the system inputs food material names, food material weights, food material types, dish names and cooking method keywords input by a user through a preset APP into a preset scheme decision model. The preset scheme decision model is a model trained by a machine learning algorithm based on a large amount of historical cooking data, and can be used for carrying out matching inquiry in a database containing rich cooking modes according to input food materials and cooking requirement information, wherein the cooking modes obtained by matching inquiry comprise heating time length adjustment schemes and temperature adjustment schemes aiming at different food materials and modes. The system searches and obtains an induction cooker heating scheme suitable for the current food materials and cooking requirements through a scheme decision model, and the induction cooker heating scheme comprises a heating time length and a temperature setting scheme, so that more intelligent and efficient cooking scheme exploration is realized, and personalized cooking experience is provided for a user.
Optionally, acquiring a plurality of pieces of historical basic food material information, historical cooking mode information, a plurality of corresponding actual induction cooker heating time length adjusting schemes and actual induction cooker temperature adjusting schemes; dividing the plurality of historical basic food material information, the historical cooking mode information, the corresponding plurality of actual induction cooker heating time length adjusting schemes and the corresponding actual induction cooker temperature adjusting schemes into training set data and verification set data according to preset proportions; according to the training set data and the verification set data, training an initial neural network model to enable a model scheme prediction result to be converged to a corresponding actual induction cooker heating time length adjustment scheme and an actual induction cooker temperature adjustment scheme; and taking the trained initial neural network model as the preset scheme decision model.
By adopting the technical scheme, the system collects a large amount of historical food material information, cooking modes and data corresponding to the actual heating time length and temperature regulation scheme of the induction cooker as training samples. The system then randomly divides the data into training and validation sets at a predetermined ratio. The system adopts a neural network model in deep learning as an initial model. And continuously adjusting parameters of each layer of the neural network model by utilizing training set data, so that the model prediction result is converged with the actual scheme of the verification set to be consistent, and training of the initial model is completed. After training for a plurality of iteration cycles, the model prediction capability is stronger and stronger. And storing the trained deep learning model as a preset scheme decision model for the system. In actual control, the decision model can provide an accurate cooking scheme conforming to historical practice by utilizing hidden complex cooking rules according to input food materials and mode information. The self-learning capability of deep learning is adopted, the intelligent degree of a system scheme is greatly improved, and better cooking experience is brought to users.
Optionally, recording the heating time of the induction cooker; judging whether the heating time length of the induction cooker reaches a target preheating time length corresponding to the heating time length adjusting scheme or not; if yes, judging that the induction cooker finishes the preheating operation and adjusting the heating power to a preset target heating power.
By adopting the technical scheme, the system collects the heating duration data through the sensor arranged on the induction cooker and compares the heating duration data with the target preheating duration. When the actual heating time acquired by the sensor is consistent with the target preheating time given by the decision model, the system judges that the preheating stage is finished, at the moment, the system automatically sends an instruction to the induction cooker, adjusts the heating power to the preset target heating power, enters the main heating stage, and can more accurately control the whole cooking process through full-range monitoring and real-time feedback. Through preheating the process, cook and detect food material, can effectively improve electromagnetism stove culinary art effect.
Optionally, acquiring the bottom temperature of the induction cooker through a temperature sensor; judging whether the temperature of the bottom of the induction cooker reaches a preset target temperature threshold corresponding to the temperature regulation scheme or not; if yes, heating power is adjusted to a preset first heating power threshold value, and the induction cooker is heated so as to maintain the bottom temperature of the induction cooker to the preset target temperature; if not, adjusting the heating power to a preset second heating power threshold value to heat the induction cooker until the bottom temperature of the induction cooker reaches the preset target temperature.
By adopting the technical scheme, the furnace bottom temperature of the induction cooker acquired by the system is compared with a target temperature threshold value given by a preset scheme decision model in real time. If the temperature of the bottom of the induction cooker reaches the target temperature, the system automatically adjusts the power of the induction cooker to a preset first heating power threshold value so as to maintain the temperature state. If the temperature of the bottom of the induction cooker does not reach the standard, the system adjusts the power to a preset second heating power threshold value, provides more heating energy at one time and accelerates the temperature rise to the target value. The temperature information is comprehensively collected, double-threshold type dynamic power adjustment is carried out, the cooking temperature can be accurately controlled, and the temperature difference problem is avoided to influence the cooking quality.
Optionally, judging whether the heating time length of the induction cooker reaches a target cooking time length corresponding to the heating time length adjusting scheme; if yes, stopping the heating operation of the induction cooker, and generating prompt information to prompt a user to finish the heating operation.
By adopting the technical scheme, the system compares the recorded heating time of the induction cooker with the target cooking time obtained by the preset scheme decision model. When the actual heating time of the induction cooker is equal to or longer than the target cooking time given by the decision model, the system judges that the food is completely cooked. At this time, the system automatically sends an instruction to the induction cooker to stop the heating operation. Meanwhile, the system can pop up prompt information to prompt the user that cooking is completed, and food can be started to be enjoyed. By setting the lower limit of the heating time, the over-baking is prevented, and the cooking quality of food is ensured. And a prompt is provided for the user when the user finishes, the user is reminded to take the meal in time, and the user experience is improved.
In a second aspect of the present application, a system for a smart induction cooker cooking method is provided.
The information acquisition module is used for acquiring basic food material information and cooking mode information;
the scheme acquisition module is used for determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information;
the instruction conversion module is used for generating corresponding control instructions according to the heating scheme of the induction cooker;
and the operation execution module is used for sending the control instruction to the induction cooker control end so as to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation.
In a third aspect of the present application, an electronic device is provided.
A system for a smart induction cooker cooking method comprising a memory, a processor, and a program stored on the memory and executable on the processor, the program being capable of implementing a smart induction cooker cooking method when loaded and executed by the processor.
In a fourth aspect of the present application, a computer-readable storage medium is provided.
A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to implement a smart induction cooker cooking method.
In summary, one or more technical solutions provided in the embodiments of the present application at least have the following technical effects or advantages:
1. according to the method and the device, basic food material information to be cooked and selected cooking mode information of a user are acquired through the preset APP. The system then determines the appropriate induction cooker heating scheme, such as heating temperature, time, etc. parameters, based on the obtained food material and cooking mode information. And then generating a corresponding control instruction according to the determined heating scheme, and sending the control instruction to the control end of the induction cooker through a network. And the control end of the electromagnetic oven controls the electromagnetic oven to enter different working modes to perform intelligent heating operation according to the received control instruction. The intelligent cooking control based on different food materials and cooking modes can be realized, the uncertainty of experience required by manual cooking is eliminated, and an automatic and intelligent cooking process is realized, so that the cooking efficiency and the cooking effect are improved, and an integrated cooking experience is provided for a user.
2. According to the method, the preset scheme decision model is obtained through training by adopting the initial neural network model, the induction cooker heating scheme is intelligently matched for the food material and dishes selected by the user, so that the cooking quality of the food material is improved, the problem that the cooking effect of the food material is poor due to the fact that the user knows about the food material and the cooking is avoided.
3. According to the intelligent induction cooker heating power control method and device, the heating time of the induction cooker is recorded in real time, the heating power of the induction cooker is intelligently adjusted so that the temperature of the induction cooker is matched with the cooking stage of food materials, the cooking effect of the induction cooker can be effectively improved, and the user experience is improved.
Drawings
Fig. 1 is a schematic flow chart of a cooking method of an intelligent induction cooker according to an embodiment of the present application.
Fig. 2 is a schematic diagram of a temperature adjustment flow of an intelligent induction cooker cooking method according to an embodiment of the present application.
Fig. 3 is a schematic system structure diagram of an intelligent induction cooker cooking method according to an embodiment of the present application.
Fig. 4 is a schematic structural diagram of an electronic device according to the disclosure in an embodiment of the present application.
Reference numerals illustrate: 301. an information acquisition module; 302. a scheme acquisition module; 303. an instruction conversion module; 304. an operation execution module; 400. an electronic device; 401. a processor; 402. a memory; 403. a user interface; 404. a network interface; 405. a communication bus.
Detailed Description
In order to make those skilled in the art better understand the technical solutions in the present specification, the technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present application, but not all embodiments.
In the description of embodiments of the present application, words such as "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described herein as "such as" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Rather, the use of words such as "or" for example "is intended to present related concepts in a concrete fashion.
In the description of the embodiments of the present application, the term "plurality" means two or more. For example, a plurality of systems means two or more systems, and a plurality of screen terminals means two or more screen terminals. Furthermore, the terms "first," "second," and the like, are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implicitly indicating an indicated technical feature. Thus, a feature defining "a first" or "a second" may explicitly or implicitly include one or more such feature. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
In order to facilitate understanding of the methods and systems provided in the embodiments of the present application, a description of the background of the embodiments of the present application is provided before the description of the embodiments of the present application.
At present, the traditional induction cooker cooking method mainly depends on manual adjustment of temperature and heating time of a user, which not only requires the user to have certain cooking knowledge and experience, but also requires the user to continuously monitor the whole cooking process so as to ensure that the food reaches ideal doneness.
The embodiment of the application discloses an intelligent induction cooker cooking method, basic food material information and selected cooking method information input by a user in a preset APP are utilized to automatically obtain an induction cooker heating scheme, then a corresponding control instruction is generated according to the induction cooker heating scheme and is sent to an induction cooker control terminal to control induction cooker heating duration and temperature, so that an intelligent cooking effect is achieved, and the intelligent induction cooker cooking method is mainly used for solving the problems that the conventional method is utilized to manually adjust temperature and time, so that excessive or still immature food material heating occurs due to negligence of the user, the food material cooking effect is poor, and user experience is low.
Those skilled in the art will appreciate that the problems associated with the prior art are solved by the foregoing background description, and a detailed description of the technical solutions in the embodiments of the present application is provided below, with reference to the drawings in the embodiments of the present application, where the described embodiments are only some embodiments of the present application, but not all embodiments.
Referring to fig. 1, an intelligent induction cooker cooking method includes S10 to S40, specifically includes the following steps:
s10: basic food material information and cooking mode information are acquired.
Specifically, the user is through presetting intelligent culinary art APP promptly, presets APP, connects domestic intelligent induction cooker's control terminal. The user inputs basic food material information in this intelligent culinary art APP, and this basic food material information includes food material name, weight, kind etc.. The user selects a cooking dish and inputs keywords of a cooking method, for example, dishes and cooking methods such as "shredded fish and pork", "quick-fry". The system acquires basic food material information and cooking method information input by a user through the intelligent cooking APP.
S20: and determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information.
Specifically, the system takes the acquired information such as the name, weight, type and the like of the food material and the cooking mode information as model input features to input a preset cooking decision model, namely a preset scheme decision model. And the preset scheme decision model is trained in advance to obtain the mapping relation of relevant food parameters corresponding to various adjusting parameters of the induction cooker under different dishes. The heating scheme includes a heating duration adjustment scheme and a temperature adjustment scheme. The model can dynamically generate an optimal scheme according to the characteristics of food materials, dish requirements and the like, for example, when a certain dish needs 5 minutes of high temperature and then 3 minutes of low-fire cooked soybean, the scheme of the system output heating time length comprises the following steps: 5 minutes 220 degrees, 3 minutes 160 degrees; the temperature regulation scheme is as follows: the temperature is 220 ℃ in 0 to 5 minutes, and the temperature is reduced to 160 ℃ in 5 to 8 minutes. And outputting the decided heating scheme by the system, and controlling the induction cooker to execute according to the scheme. Intelligent heating control based on cooking knowledge is achieved, and operation is simplified to improve cooking effect.
In a preferred embodiment of the present application, the training process of the preset scheme decision model specifically includes: the system collects a large amount of historical cooking data including food material information, cooking modes and corresponding actual heating schemes, then preprocesses the collected data, filters abnormal data and completes characteristic engineering. And then, the visual characteristics of the food material image are extracted by using a convolutional neural network, a text menu and food material numerical value characteristics are converted by using a word vector technology to serve as model training data, and a deep neural network model comprising a convolutional layer and a full-connection layer, namely an initial neural network model is constructed by the system. Then, the system divides the model training data into a training set and a verification set according to a preset proportion. The system trains the initial neural network decision model based on training set data, and compares the heating scheme output by model prediction with the actual scheme. And the accuracy of scheme prediction is gradually improved through repeated training and adjustment of model parameters. And when the prediction effect of the model on the verification set reaches the preset precision, locking the model and storing the model. Obtaining a final preset scheme decision model. The system trains a high-performance decision model through intelligent learning historical data, and realizes automatic and accurate decision of the cooking scheme.
It should be noted that, the user may create a custom menu in the preset APP to perform personalized food cooking, and the process specifically includes: the system provides a menu template, and a user can input contents such as a custom menu name, a food material name, components and the like in the template to construct a personalized menu. After the user inputs the menu, the menu may be saved to a system database. When a user selects a stored personalized menu to cook, the system can automatically call the menu, analyze the names and the component information of food materials in the menu, and calculate the optimal cooking parameters of the corresponding menu according to an intelligent algorithm, including preheating temperature, preheating time, cooking temperature, cooking time and the like. The system automatically sets the calculated optimal cooking parameters to the induction cooker, and controls the induction cooker to perform intelligent cooking according to the parameters. After cooking is completed, the current cooking parameters can be selected and stored so as to further perfect menu information. Through the system, a user can customize a menu and intelligently cook, the system can automatically calculate and set optimal cooking parameters, the cooking process is simplified, and personalized and intelligent cooking experience is realized. The user still accessible mobile terminal is last to predetermine APP, remote control electromagnetism stove food material heating mode, and this process specifically includes: when the user needs to go out, the user can enter the remote control interface of the induction cooker through the APP on the mobile terminal. The user can preset heating parameters of the induction cooker at the APP interface, such as a preheating temperature of 180 ℃, a preheating time of 10 minutes, a cooking temperature of 220 ℃, a cooking time of 20 minutes and the like. After the user sets the parameters, the user confirms the submission, and the preset APP transmits the set parameters to a system background server in real time through a WIFI (wireless fidelity) and other networks. And the system background server immediately pushes the received control parameters to an induction cooker connected at home. The induction cooker automatically starts preheating and cooking operations at preset time according to the received remote control parameters. After the cooking is finished, the induction cooker is automatically powered off and is synchronized with the APP in a power-off state, so that a user can conveniently master the induction cooker at any time. Through the remote intelligent control function of this system, the user can easily control the electromagnetism stove in home through APP intelligence when going out, realizes the automatic heating culinary art that long-range unmanned carelessly, simplifies the culinary art operation by a wide margin, promotes user experience.
S30: and generating a corresponding control instruction according to the heating scheme of the induction cooker.
Specifically, the system obtains an induction cooker heating scheme generated by a decision model. The heating scheme includes temperature parameters, time parameters, energy distribution and other control parameters. And the system call instruction generation module is used for converting the heating scheme into an executable control instruction of the induction cooker, for example, converting the temperature parameter into a corresponding electric power output control instruction and converting the time parameter into a timing execution control instruction. Then, according to different heating disk areas, generating control instructions for energy distribution, packaging the control instructions and sending the control instructions to an induction cooker control terminal.
S40: and sending a control instruction to the control end of the induction cooker to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation.
Specifically, the system sends the acquired control instruction to an induction cooker control terminal through a wireless network, and the induction cooker control terminal drives each zone heater and each temperature sensor to implement according to the received instruction and executes heating control according to the instruction sequence and parameters so that the induction cooker can sequentially complete the identified heating tasks at different time periods, and the whole cooking process is realized. The intelligent cooking control system and the intelligent cooking control method have the advantages that through the end-to-end intelligent control, the intelligent cooking degree and the experience degree are remarkably improved.
In an alternative embodiment of the present application, the system records the heating time in real time during the heating process of the induction cooker, and the specific steps of the process include: after the induction cooker starts to heat, the system records the heating duration time of the induction cooker since the induction cooker starts to heat, and then the system judges whether the recorded heating duration time reaches the preset target preheating time; if the target preheating time is reached, the system determines that the induction cooker completes the preheating operation, and automatically adjusts the heating power of the induction cooker to the preset target heating power so as to enter a normal heating mode. By the mode, the system can intelligently control the preheating and heating processes of the induction cooker according to the preset preheating time and heating power requirements, so that the induction cooker is heated according to an optimized mode, and a safe and efficient heating effect is achieved.
Referring to FIG. 2, in an alternative embodiment of the present application, the system detects the hearth temperature of the induction cooker in real time through a temperature sensor, and then the system determines whether the detected hearth temperature reaches a preset target temperature threshold; if the target temperature threshold is reached, the system automatically adjusts the heating power of the induction cooker to a preset first heating power threshold, and heats the induction cooker with smaller power, so that the temperature of the furnace bottom is kept to stably run near the target temperature; if the target temperature threshold is not reached, the system automatically adjusts the heating power of the induction cooker to a preset second heating power threshold, wherein the power threshold is larger than the first power threshold, and the induction cooker is heated with larger power until the temperature of the furnace bottom reaches the preset target temperature. By the mode, the system can intelligently adjust heating power according to real-time furnace bottom temperature feedback of the induction cooker, so that the furnace bottom temperature is accurately controlled, and an accurate temperature control effect is realized.
In yet another alternative embodiment of the present application, the system records the heating duration of the induction cooker in real time during the induction cooker heating process; the system judges whether the recorded heating duration reaches a preset target cooking duration; if the target cooking time is reached, the system automatically stops the heating operation of the induction cooker; at the same time, the system may generate a prompt, such as a voice prompt to "heat complete" to prompt the user that the heating process has been completed. By the method, the system can accurately calculate the heating time, and automatically close the induction cooker at the optimal time point when food is completely cooked, so that the need of manual operation of a user is avoided, and the cooking efficiency and experience are improved. Meanwhile, the voice prompt of the system also enables a user to know that the heating is finished in time, and the problems of food overripening or burnt and the like caused by continuous heating are avoided.
The following are system embodiments of the present application that may be used to perform method embodiments of the present application. For details not disclosed in the platform embodiments of the present application, reference is made to the method embodiments of the present application.
Referring to fig. 3, a system for an intelligent induction cooker cooking method according to an embodiment of the present application includes: an information acquisition module 301, a scheme acquisition module 302, an instruction conversion module 303, and an operation execution module 304, wherein:
an information acquisition module (301) for acquiring basic food material information and cooking mode information;
the scheme acquisition module (302) is used for determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information;
the instruction conversion module (303) is used for generating corresponding control instructions according to an induction cooker heating scheme;
and the operation execution module (304) is used for sending a control instruction to the induction cooker control end so as to control the induction cooker to adjust to a working mode corresponding to an induction cooker heating scheme for heating operation.
It should be noted that: in the device provided in the above embodiment, when implementing the functions thereof, only the division of the above functional modules is used as an example, in practical application, the above functional allocation may be implemented by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules, so as to implement all or part of the functions described above. In addition, the embodiments of the apparatus and the method provided in the foregoing embodiments belong to the same concept, and specific implementation processes of the embodiments of the method are detailed in the method embodiments, which are not repeated herein.
The application also discloses electronic equipment. Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic device according to the disclosure in an embodiment of the present application. The electronic device 400 may include: at least one processor 401, at least one network interface 404, a user interface 403, a memory 402, at least one communication bus 405.
Wherein a communication bus 405 is used to enable connected communications between these components.
The user interface 403 may include a Display screen (Display) and a Camera (Camera), and the optional user interface 403 may further include a standard wired interface and a standard wireless interface.
The network interface 404 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface), among others.
Wherein the processor 401 may include one or more processing cores. The processor 401 connects the various parts within the entire server using various interfaces and lines, performs various functions of the server and processes data by executing or executing instructions, programs, code sets, or instruction sets stored in the memory 402, and calling data stored in the memory 402. Alternatively, the processor 401 may be implemented in at least one hardware form of digital signal processing (Digital Signal Processing, DSP), field programmable gate array (Field-Programmable Gate Array, FPGA), programmable logic array (Programmable Logic Array, PLA). The processor 401 may integrate one or a combination of several of a central processing unit (Central Processing Unit, CPU), an image processor (Graphics Processing Unit, GPU), a modem, etc. The CPU mainly processes an operating system, a user interface diagram, an application program and the like; the GPU is used for rendering and drawing the content required to be displayed by the display screen; the modem is used to handle wireless communications. It will be appreciated that the modem may not be integrated into the processor 401 and may be implemented by a single chip.
The Memory 402 may include a random access Memory (Random Access Memory, RAM) or a Read-Only Memory (Read-Only Memory). Optionally, the memory 402 includes a non-transitory computer readable medium (non-transitory computer-readable storage medium). Memory 402 may be used to store instructions, programs, code sets, or instruction sets. The memory 402 may include a stored program area and a stored data area, wherein the stored program area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playing function, an image playing function, etc.), instructions for implementing the above-described various method embodiments, etc.; the storage data area may store data or the like involved in the above respective method embodiments. The memory 402 may also optionally be at least one storage device located remotely from the aforementioned processor 401. Referring to fig. 4, an operating system, a network communication module, a user interface module, and an application program of an intelligent induction cooker cooking method may be included in a memory 402 as a computer storage medium.
In the electronic device 400 shown in fig. 4, the user interface 403 is mainly used as an interface for providing input for a user, and obtains data input by the user; and processor 401 may be used to invoke an application program in memory 402 that stores an intelligent induction cooker cooking method, which when executed by one or more processors 401, causes electronic device 400 to perform the method as in one or more of the embodiments described above. It should be noted that, for simplicity of description, the foregoing method embodiments are all expressed as a series of action combinations, but it should be understood by those skilled in the art that the present application is not limited by the order of actions described, as some steps may be performed in other order or simultaneously in accordance with the present application. Further, those skilled in the art will also appreciate that the embodiments described in the specification are all preferred embodiments, and that the acts and modules referred to are not necessarily required in the present application.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and for parts of one embodiment that are not described in detail, reference may be made to related descriptions of other embodiments.
In the several embodiments provided herein, it should be understood that the disclosed apparatus may be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative, such as a division of units, merely a division of logic functions, and there may be additional divisions in actual implementation, such as multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed with each other may be through some service interface, device or unit indirect coupling or communication connection, electrical or otherwise.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed over a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
In addition, each functional unit in each embodiment of the present application may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit. The integrated units may be implemented in hardware or in software functional units.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable memory. Based on such understanding, the technical solution of the present application may be embodied in essence or a part contributing to the prior art or all or part of the technical solution in the form of a software product stored in a memory, including several instructions for causing a computer device (which may be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the methods of the embodiments of the present application. And the aforementioned memory includes: various media capable of storing program codes, such as a U disk, a mobile hard disk, a magnetic disk or an optical disk.
The above are merely exemplary embodiments of the present disclosure and are not intended to limit the scope of the present disclosure. That is, equivalent changes and modifications are contemplated by the teachings of this disclosure, which fall within the scope of the present disclosure. Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure.
This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with the scope and spirit of the disclosure being indicated by the claims.
Claims (10)
1. An intelligent induction cooker cooking method, comprising:
acquiring basic food material information and cooking mode information;
determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information;
generating a corresponding control instruction according to the heating scheme of the induction cooker;
and sending the control instruction to an induction cooker control end to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation.
2. The intelligent induction cooker cooking method according to claim 1, wherein the acquiring basic food material information and cooking mode information comprises:
according to a preset APP, establishing communication connection between a user terminal and the induction cooker control terminal;
the basic food material information and the cooking mode information input by a user are acquired through the preset APP, the basic food material information comprises food material names, food material weights and food material types, and the cooking mode information comprises dish names and cooking method keywords.
3. The intelligent induction cooker cooking method according to claim 2, wherein determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information comprises:
inputting the food material names, the food material weights, the food material types, the dish names and the cooking method keywords into a preset scheme decision model to obtain the corresponding induction cooker heating scheme, wherein the induction cooker heating scheme comprises a heating time length adjusting scheme and a temperature adjusting scheme.
4. The intelligent induction cooker cooking method according to claim 3, wherein the preset scheme decision model is a neural network model, and the training process comprises:
acquiring a plurality of historical basic food material information, historical cooking mode information, a plurality of corresponding actual induction cooker heating time length adjusting schemes and actual induction cooker temperature adjusting schemes;
dividing the plurality of historical basic food material information, the historical cooking mode information, the corresponding plurality of actual induction cooker heating time length adjusting schemes and the corresponding actual induction cooker temperature adjusting schemes into training set data and verification set data according to preset proportions;
according to the training set data and the verification set data, training an initial neural network model to enable a model scheme prediction result to be converged to a corresponding actual induction cooker heating time length adjustment scheme and an actual induction cooker temperature adjustment scheme;
and taking the trained initial neural network model as the preset scheme decision model.
5. The intelligent induction cooker cooking method according to claim 1, wherein the sending the control command to the induction cooker control end to control the induction cooker to adjust to the working mode corresponding to the induction cooker heating scheme for heating operation includes:
recording the heating time of the induction cooker;
judging whether the heating time length of the induction cooker reaches a target preheating time length corresponding to the heating time length adjusting scheme or not;
if yes, judging that the induction cooker finishes the preheating operation and adjusting the heating power to a preset target heating power.
6. The intelligent induction cooker cooking method according to claim 5, wherein after the control command is sent to the induction cooker control end, the intelligent induction cooker cooking method further comprises:
acquiring the bottom temperature of the induction cooker through a temperature sensor;
judging whether the temperature of the bottom of the induction cooker reaches a preset target temperature threshold corresponding to the temperature regulation scheme or not;
if yes, heating power is adjusted to a preset first heating power threshold value, and the induction cooker is heated so as to maintain the bottom temperature of the induction cooker to the preset target temperature;
if not, adjusting the heating power to a preset second heating power threshold value to heat the induction cooker until the bottom temperature of the induction cooker reaches the preset target temperature.
7. The intelligent induction cooker cooking method according to claim 6, wherein after the heating power is adjusted to a preset first heating power threshold value to heat the induction cooker, the intelligent induction cooker cooking method further comprises:
judging whether the heating time length of the induction cooker reaches a target cooking time length corresponding to the heating time length adjusting scheme or not;
if yes, stopping the heating operation of the induction cooker, and generating prompt information to prompt a user to finish the heating operation.
8. A system based on the intelligent induction cooker cooking method of claims 1-7, characterized in that the system comprises:
an information acquisition module (301) for acquiring basic food material information and cooking mode information;
the scheme acquisition module (302) is used for determining a corresponding induction cooker heating scheme according to the basic food material information and the cooking mode information;
the instruction conversion module (303) is used for generating a corresponding control instruction according to the induction cooker heating scheme;
and the operation execution module (304) is used for sending the control instruction to the induction cooker control end so as to control the induction cooker to adjust to a working mode corresponding to the induction cooker heating scheme for heating operation.
9. An electronic device comprising a processor (401), a memory (402), a user interface (403) and a network interface (404), the memory (402) being configured to store instructions, the user interface (403) and the network interface (404) being configured to communicate to other devices, the processor (401) being configured to execute the instructions stored in the memory (402) to cause the electronic device (400) to perform a method of cooking in an intelligent induction cooker according to any one of claims 1-7.
10. A computer readable storage medium storing instructions which, when executed, perform a method of intelligent induction cooker cooking as claimed in any one of claims 1 to 7.
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| CN202311844976.2A CN117812770A (en) | 2023-12-29 | 2023-12-29 | Intelligent induction cooker cooking method, system, electronic equipment and medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118021187A (en) * | 2024-04-10 | 2024-05-14 | 福州爱国者之星光电科技有限公司 | Cooking device heating control method, cooking device and storage medium |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN118021187A (en) * | 2024-04-10 | 2024-05-14 | 福州爱国者之星光电科技有限公司 | Cooking device heating control method, cooking device and storage medium |
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