Cooking control method, device and system and storage medium

Abstract

The invention provides a cooking control method, device and system and a storage medium. The cooking control method comprises the following steps: acquiring image information of a cooking utensil in which a target cooking food material is placed; determining initial nutritional ingredient information of the target cooking food material based on an image recognition result of the image information; in the cooking process, the current operation parameter information of the cooking utensil and the current state parameter information of the target cooking food material are monitored; performing nutrient loss prediction based on the initial nutrient information, the current operation parameter information and the current state parameter information to obtain estimated nutrient information; and adjusting a preset cooking strategy based on the target nutrition information and the estimated nutritional ingredient information to obtain a target cooking strategy. According to the invention, image recognition can be carried out on the target cooking food material, the target cooking food material is automatically monitored and the nutritional ingredients are tracked and predicted, the prediction accuracy is high, and the content of the residual nutritional ingredients after cooking can be increased.

Description

Technical Field

[0001] The present invention relates to the technical field of health management, and particularly to a cooking control method, device, system and storage medium. Background Art

[0002] Smart homes can provide users with health management and nutrition tracking services. However, in existing health management and nutrition tracking systems, the diet system mainly relies on users to manually input information about ingredients and their intake amounts. This is inconvenient for users and lacks accurate monitoring and analysis of the nutritional components in the ingredients and the loss of nutrients during the cooking process. As a result, it is impossible to precisely adjust the cooking strategy to meet the nutritional needs of users during actual use, and the user experience is poor. Summary of the Invention

[0003] In view of the problems existing in the above-mentioned prior art, the present invention provides a cooking control method, device, system and storage medium; the technical solutions are as follows:

[0004] On the one hand, the present invention provides a cooking control method, including:

[0005] Obtaining image information of a cooking appliance on which target cooking ingredients are placed;

[0006] Determining initial nutritional component information of the target cooking ingredients based on the image recognition result of the image information; the initial nutritional component information is used to indicate the types and respective contents of the nutritional components possessed by each of the target cooking ingredients;

[0007] Controlling the cooking appliance to cook based on a preset cooking strategy;

[0008] During the cooking process, monitoring the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredients;

[0009] Performing nutritional component loss prediction based on the initial nutritional component information, the current operating parameter information and the current state parameter information to obtain predicted nutritional component information; the predicted nutritional component information is used to indicate the types and respective contents of the nutritional components remaining in the target cooking ingredients after cooking;

[0010] Adjusting the preset cooking strategy based on the difference between the target nutritional information and the predicted nutritional component information to obtain a target cooking strategy, and controlling the cooking appliance to operate based on the target cooking strategy; the target nutritional information is used to indicate the types and respective contents of the target nutritional component contents that need to be retained in the target cooking ingredients after cooking.

[0011] Further, after adjusting the preset cooking strategy based on the difference between the target nutritional information and the estimated nutritional component information to obtain a target cooking strategy, and controlling the cooking appliance to operate based on the target cooking strategy, the method further includes:

[0012] During the cooking process, the steps of monitoring the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredients and the step of predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information are cyclically executed to update the estimated nutritional component information and obtain updated estimated nutritional component information;

[0013] Periodically adjust the target cooking strategy based on the difference between the target nutritional information and the updated estimated nutritional component information, and control the cooking appliance to operate based on the periodically adjusted target cooking strategy until the updated estimated nutritional component information matches the target nutritional information.

[0014] Further, determining the initial nutritional component information of the target cooking ingredients based on the image recognition result of the image information includes:

[0015] Performing image recognition on the image information to obtain the image recognition result, where the image recognition result is used to indicate the types of the target cooking ingredients and the quantity of each type of ingredient;

[0016] Determining the nutritional data information corresponding to each type of ingredient based on a first correspondence relationship; the first correspondence relationship is used to indicate the types of nutritional components, the unit content of the nutritional components, and the nutritional component characteristics corresponding to various ingredients;

[0017] Performing data statistics based on the quantity of the ingredients and the nutritional data information corresponding to each type of ingredient to obtain the initial nutritional component information.

[0018] Further, predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain estimated nutritional component information includes:

[0019] Predicting the loss state of the nutritional components corresponding to the current operating parameter information and the current state parameter information during the cooking process based on a second correspondence relationship to obtain predicted nutritional loss information; the second correspondence relationship is used to indicate the correspondence relationship between the loss states of various nutritional components, various operating parameters of the cooking appliance, and various state parameter information of the ingredients;

[0020] Obtaining the estimated nutritional component information based on the initial nutritional component information and the predicted nutritional loss information.

[0021] Further, before predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain the predicted nutritional component information, the method further includes:

[0022] Search for the predicted nutritional component information corresponding to the initial nutritional component information, the current operating parameter information, and the current state parameter information from the historical dataset; the historical dataset is used to store the historical predicted nutritional component information obtained by predicting based on the historically monitored historical initial nutritional component information, historical current operating parameter information, and historical current state parameter information during historical cooking processes.

[0023] If not found, execute the step of predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain the predicted nutritional component information.

[0024] If found, use the historical predicted nutritional component information as the predicted nutritional component information.

[0025] Further, after predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain the predicted nutritional component information, the method further includes:

[0026] Obtain the status information of the edible object; the status information is used to indicate the dietary preferences, eating habits, and physical status of the edible object.

[0027] Generate dietary advice information based on the status information and the predicted nutritional component information.

[0028] On the other hand, the present invention also provides a cooking control device, including:

[0029] An image acquisition module, configured to acquire image information of a cooking utensil on which a target cooking ingredient is placed.

[0030] A nutritional component determination module, configured to determine the initial nutritional component information of the target cooking ingredient based on the image recognition result of the image information; the initial nutritional component information is used to indicate the types and respective contents of the nutritional components possessed by each of the target cooking ingredients.

[0031] A cooking module, configured to control the cooking utensil to cook based on a preset cooking strategy.

[0032] A monitoring module, configured to monitor the current operating parameter information of the cooking utensil and the current state parameter information of the target cooking ingredient during the cooking process.

[0033] A prediction module, configured to predict nutrient loss based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information, so as to obtain predicted nutrient composition information; the predicted nutrient composition information is used to indicate the types and respective contents of the nutrients remaining in the target cooking ingredient after cooking.

[0034] An adjustment module, configured to adjust the preset cooking strategy based on the difference between the target nutrient information and the predicted nutrient composition information, so as to obtain a target cooking strategy, and control the cooking appliance to operate based on the target cooking strategy; the target nutrient information is used to indicate the types and respective contents of the target nutrient contents that need to be retained in the target cooking ingredient after cooking.

[0035] On the other hand, the present invention further provides a cooking control system, including a cooking appliance, an image acquisition device, and the cooking management device as described above, wherein the image acquisition device is disposed inside the cooking appliance and is configured to acquire image information of the cooking appliance with the target cooking ingredient placed therein.

[0036] Furthermore, the cooking control system further includes a plurality of information acquisition devices, the plurality of information acquisition devices are disposed in the cooking appliance, and the plurality of information acquisition devices are configured to acquire the current operating information in the cooking appliance and the current state parameter information of the target cooking ingredient.

[0037] On the other hand, the present invention provides a storage medium, in which at least one instruction or at least one program segment is stored, and the at least one instruction or the at least one program segment is loaded and executed by a processor to implement the cooking control method as described in any one of the above.

[0038] Implementing the present invention has the following beneficial effects:

[0039] The present invention determines the initial nutrient composition information by performing image recognition on the target cooking ingredient, monitors the current operating parameter information of the cooking appliance and the current state information of the target cooking ingredient during the cooking process, predicts the nutrient loss according to the initial nutrient composition information, the current operating parameter information, and the current state information, so as to obtain predicted nutrient composition information, with a high degree of automation, and can automatically monitor, track, predict, and analyze the nutrients of the target cooking ingredient, improving the prediction accuracy and reliability; and adjusts the preset cooking strategy according to the difference between the target nutrient information and the predicted nutrient composition information to obtain a target cooking strategy, so that after cooking based on the target cooking strategy, the nutrients of the target cooking ingredient can be retained as much as possible, and it is also convenient to provide personalized nutrient tracking and healthy diet suggestions for the edible object later, improving the user experience. Description of the Drawings

[0040] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can be obtained based on these drawings.

[0041] Figure 1 It is a logical structure diagram of a cooking control method provided by an embodiment of the present invention;

[0042] Figure 2 It is a logical structure diagram of a periodic adjustment method of a target cooking strategy provided by an embodiment of the present invention;

[0043] Figure 3 It is a logical structure diagram of a method for determining initial nutritional component information provided by an embodiment of the present invention;

[0044] Figure 4 It is a logical structure diagram of a nutritional component loss prediction method provided by an embodiment of the present invention;

[0045] Figure 5 It is a logical structure diagram of a method for calling historical estimated nutritional component information provided by an embodiment of the present invention;

[0046] Figure 6 It is a logical structure diagram of a diet advice method provided by an embodiment of the present invention;

[0047] Figure 7 It is a structural block diagram of a cooking control device provided by an embodiment of the present invention;

[0048] Figure 8 It is a hardware structural block diagram of an electronic device for executing the cooking control method provided by an embodiment of the present invention. Detailed implementation manners

[0049] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, rather than all embodiments, and thus should not be construed as a limitation to the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0050] It should be noted that the terms "first", "second", etc. in the specification, claims and drawings of the present invention are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present invention can be implemented in an order other than the following diagrams or the following descriptions. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or server that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0051] In view of the problem that the health management system in the prior art needs manual operation and cannot automatically monitor, analyze and predict the loss of nutrients during the cooking process, the embodiments of the present invention provide a cooking control method, device, system and storage medium. The cooking control method is based on the cooking control device provided by the embodiments of the present invention and is applied to the cooking control system provided by the embodiments of the present invention. First, image information of the cooking utensil on which the target cooking ingredients are placed is acquired; initial nutritional component information of the target cooking ingredients is determined based on the image recognition result of the image information; the initial nutritional component information is used to indicate the types and respective contents of the nutritional components of each target cooking ingredient; then the cooking utensil is controlled to cook based on a preset cooking strategy, and the operating parameter information of the cooking utensil and the current state parameter information of the target cooking ingredients are monitored during the cooking process; then, based on the initial nutritional component information, the current operating parameter information and the current state parameter information, the cooking utensil is controlled to cook based on the preset cooking strategy. The target cooking food is then fed with a food processor and the cooking control method is used to predict the loss of nutrients based on the image information and obtain estimated nutrient information, wherein the estimated nutrient information is used to indicate the types and respective contents of nutrients remaining in the target cooking food after cooking; finally, the preset cooking strategy is adjusted based on the difference between the target nutrient information and the estimated nutrient information to obtain the target cooking strategy, and the cooking appliance is controlled to operate based on the target cooking strategy to retain the content of nutrients remaining in the target cooking food after cooking as much as possible; the cooking control method predicts the loss of nutrients based on the acquired image information and the current operating parameter information and the current state parameter information monitored during the cooking process, and can realize accurate monitoring, analysis and prediction of the nutrients in the target cooking food and their loss during the cooking process, so as to provide personalized healthy diet suggestions and nutrition tracking for the edible subject based on the estimated nutrient information in the subsequent process, thereby improving the use experience of the edible subject.

[0052] The cooking control method of the embodiment of the present invention is described in detail below. Figure 1 , the method comprising:

[0053] S101, acquiring image information of a cooking utensil on which target cooking ingredients are placed.

[0054] Among them, the cooking appliance is used to cook the target cooking ingredients to obtain the target food for the edible object to consume; the target cooking ingredients include a variety of ingredients placed in the cooking appliance before the start of cooking; in some exemplary embodiments, the image information may include at least one of static pictures, dynamic pictures, and video clips, and the picture content included in the image information includes the picture content of the target cooking ingredients, so as to ensure the accuracy and reliability of the subsequent image recognition result, the initial nutritional component information, and the adjusted target cooking strategy.

[0055] The image information can be obtained by at least one image acquisition device. In some exemplary embodiments, the image information is obtained by one image acquisition device. In some other exemplary embodiments, the image information is obtained by multiple image acquisition devices, so as to improve the sufficiency of the information of the target cooking ingredients included in the image information and improve the accuracy of subsequent image recognition and determination of the initial nutritional component information; exemplarily, the image acquisition device is used to obtain an initial image with the target cooking ingredients through shooting and imaging. The image acquisition device may include a camera or other imaging devices. In some specific embodiments, the image acquisition device may be a high-definition camera, which is convenient and clear for shooting images, occupies little space, and has a low cost.

[0056] S103, determine the initial nutritional component information of the target cooking ingredients based on the image recognition result of the image information.

[0057] The image recognition result is obtained by performing image recognition on the image information. In some exemplary embodiments, the image information with the target cooking ingredients can be analyzed and recognized through an image processing algorithm to determine the types and respective quantities of the target cooking ingredients included in the image information. The image recognition result is used to indicate the ingredient types of each target cooking ingredient and the ingredient quantity of each ingredient type.

[0058] Among them, each ingredient includes a variety of nutritional components, and the variety of nutritional components includes at least one of protein, carbohydrates, fat, vitamins, and trace elements; based on the ingredient types of each target cooking ingredient and the ingredient quantity of each ingredient type, the total content of the nutritional components included in each target cooking ingredient can be obtained. The initial nutritional component information is used to indicate the types and respective contents of the nutritional components of each target cooking ingredient, that is, the initial nutritional component information includes the information of the types of various nutritional components and the total content of each of the various nutritional components of each target cooking ingredient existing in the cooking appliance.

[0059] S105, control the cooking appliance to cook based on a preset cooking strategy.

[0060] Among them, the preset cooking strategy can be any cooking strategy pre-configured for processing any one of the target cooking ingredients. Exemplarily, it can be a cooking strategy determined based on a recipe for processing any one of the target cooking ingredients. The present invention does not make specific limitations thereto.

[0061] S107. During the cooking process, monitor the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredient.

[0062] Among them, the current operating parameter information is used to indicate the current operating parameters inside the cooking appliance during the cooking process. The operating parameters can reflect the internal environment of the cooking appliance, and the change of the operating parameters can reflect the change of the internal environmental conditions of the cooking appliance. The loss situation of nutrients is affected by the environmental conditions, so the loss status of the nutrients corresponding to the current acquisition node can be inferred and predicted through the current operating parameter information.

[0063] In some exemplary embodiments, the current operating parameter includes at least one of the current operating temperature and the current operating humidity. Correspondingly, the current operating parameter information includes at least one of the current operating temperature information and the current operating humidity information. In some exemplary embodiments, the current operating parameter information can be obtained through a variety of information acquisition devices. Exemplarily, the current operating temperature information can be obtained through a temperature acquisition device to monitor the temperature change inside the cooking appliance during the cooking process in real time. For example, a temperature sensor is convenient for monitoring, has good real-time performance, high accuracy, and small occupied space. Exemplarily, the current operating humidity information can be obtained through a humidity acquisition device to monitor the humidity change inside the cooking appliance during the cooking process in real time. For example, a humidity sensor is convenient for monitoring, has good real-time performance, high accuracy.

[0064] The current state parameter information is used to indicate the current state of the target cooking ingredient during the cooking process. Among them, the loss situation of nutrients is affected by the current operating parameters. That is, during the cooking process, the current state of the target cooking ingredient changes in real time. Then, through the current state parameter information of the target cooking ingredient, the rate and degree of loss of nutrients changing with the current operating parameters and other states can be reflected, so as to facilitate predicting the types of nutrients remaining after cooking and the respective contents of each nutrient.

[0065] In some exemplary embodiments, the current state parameter information includes at least one of current solubility information, current pH value information, and current conductivity information, and is used to indicate at least one of the current solubility, current pH value, and current conductivity of the target cooking ingredient during the cooking process, which is the current state corresponding to the current acquisition moment; in some exemplary embodiments, the current state parameter information can be obtained by multiple information acquisition devices, and the multiple information acquisition devices include at least one of a solubility acquisition device, a pH value acquisition device, and a conductivity acquisition device.

[0066] In some exemplary embodiments, some nutrients will dissolve in water or oil as the temperature rises during the cooking process. The current solubility information can be obtained through a solubility acquisition device to monitor the dissolution of nutrients in real time during the cooking process. For example, a solubility sensor is convenient to monitor, has good real-time performance, and high accuracy.

[0067] In some exemplary embodiments, the stability of some nutrients is affected by the environmental pH value. Through a pH value acquisition device, such as a pH value sensor, the acidity and alkalinity in the cooking appliance can be detected, thereby inferring the stability of the nutrients, which is beneficial to improving the prediction accuracy of nutrient loss in the subsequent step S109.

[0068] In some exemplary embodiments, some nutrients will undergo electrolysis as the temperature rises during the cooking process. Through a conductivity acquisition device, such as a conductivity sensor, the current conductivity information can be obtained to monitor the change in the conductivity of the food solution in real time during the cooking process, thereby inferring the loss of nutrients, which is beneficial to improving the prediction accuracy of the subsequent step S109.

[0069] S109, perform a prediction of nutrient loss based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information to obtain predicted nutrient composition information.

[0070] Among them, the predicted nutrient composition information is used to indicate the types of nutrients remaining in the target cooking ingredient after cooking and the respective contents of the remaining nutrients. The contents of the nutrients indicated by the predicted nutrient composition information are not greater than the respective contents of the nutrients indicated by the initial nutrient composition information, so as to facilitate feedback adjustment according to the predicted nutrients, adjust the preset cooking strategy, and retain as many nutrients as possible to reduce the loss of nutrients during the cooking process.

[0071] In addition, since the characteristics of various nutrients are different and the loss situations caused by the same current operating parameter information are also different, for various different nutrients, the loss situation of one nutrient can be predicted in sequence. Exemplarily, the loss situation of protein can be predicted first, and then the loss situation of carbohydrates can be predicted, and so on, to improve the prediction accuracy of each nutrient; alternatively, the loss prediction of multiple nutrients can be performed synchronously in multiple threads to improve the prediction efficiency.

[0072] In some exemplary embodiments, a prediction model can also be introduced. Based on the prediction model, predictions are made according to the initial nutrient components, current operating parameter information, and current state parameter information; Exemplarily, a machine learning model or a deep learning model can be used as the prediction model, such as models like linear regression, decision tree, random forest, support vector machine (SVM), or artificial neural network. The obtained initial nutrient components, current operating parameter information, and current state parameter information are imported into the prediction model to predict the loss situation of the nutrient components and obtain the estimated nutrient component information; In addition, in some exemplary embodiments, the prediction model can also be evaluated and optimized by methods such as cross-validation to improve the prediction accuracy of the prediction model; In the subsequent prediction process, this optimized prediction model obtains the initial nutrient components, current operating parameter information, and current state parameter information for prediction, which can greatly simplify the prediction process and improve the prediction accuracy and real-time performance.

[0073] Taking protein as an example, according to the current operating parameter information and current state parameter information such as the monitored temperature, humidity, pH value, and conductivity, combined with the characteristics such as the thermal stability and solubility of the protein, the loss situation of the protein under the current operating parameters and current state parameters is predicted; For example, according to the change rate of the monitored temperature and the thermal stability data of the food ingredient, the loss rate of the protein at different temperatures is predicted; According to the change rate of the humidity and the solubility data of the food ingredient, the dissolution situation of the protein at different humidities is predicted; According to the change rate of the pH value and the acid-base data of the food ingredient, the stability change situation of the protein at different pH values is predicted; According to the change rate of the conductivity, the electrolysis situation of the protein under different food solution conductivities is predicted; In addition, the combined influence of the above various factors can also be considered to synergistically analyze and predict the loss situation of the protein under different environmental conditions.

[0074] S111, adjust the preset cooking strategy based on the difference between the target nutrient information and the estimated nutrient component information to obtain a target cooking strategy, and control the cooking appliance to operate based on the target cooking strategy.

[0075] The target nutritional information is used to indicate the types of target nutritional components to be retained after cooking the target cooking ingredients and the respective contents of various target nutritional components; in some exemplary embodiments, the target nutritional information can be preset; in other exemplary embodiments, the target nutritional information can also be determined by obtaining the physical state of the edible object and combining nutritional requirements, so as to improve the target cooking strategy and the matching degree with the edible object, which is beneficial to providing more personalized services and enhancing the usage experience of the edible object.

[0076] The ways to adjust the preset cooking strategy can include adding, removing, and replacing at least some of the ingredients (or nutritional components) in the target cooking ingredients, and can also include adjusting the cooking appliance to obtain the current operating parameter information, such as increasing or decreasing the cooking time, raising or lowering the cooking temperature, increasing or decreasing the humidity inside the cooking appliance, etc., and can also replace the cooking recipe to obtain the target cooking strategy. Correspondingly, the target cooking strategy is used to indicate the cooking parameters that match the target nutritional information, including cooking temperature, cooking time, cooking humidity, etc., so as to retain the nutritional components as much as possible and reduce the loss of nutritional components during cooking.

[0077] Exemplarily, an image of the cooking appliance containing the target cooking ingredients is captured by a high-definition camera, and image recognition is performed on the image information to obtain an image recognition result. Based on the image recognition result, the types and quantities of the ingredients in the target cooking ingredients are determined. Then, based on the types and quantities of the ingredients, according to the first correspondence relationship and the types and quantities of the ingredients, the initial protein information is calculated, including the total content of the initial protein. Then, in the cooking appliance, the temperature and humidity changes during the cooking process are monitored in real time through a temperature sensor and a humidity sensor, and protein loss prediction is performed according to the total content of the initial protein, temperature, and humidity to obtain the estimated protein content. Based on the estimated protein content and the target protein content, the cooking strategy is adjusted. If excessive protein loss is predicted, the cooking temperature or time can be reduced, or a gentler cooking control method, such as steaming or simmering, can be adopted to retain the protein in the target cooking ingredients as much as possible.

[0078] Exemplarily, the prediction process of the vitamin can be synchronized and divided into multiple threads for execution in the same way as the prediction process of the above-mentioned protein; based on the types and quantities of the food ingredients, the initial vitamin information, including the total content of the initial vitamin, is calculated according to the first correspondence relationship and the types and quantities of the food ingredients; then, in the cooking appliance, through the temperature sensor, humidity sensor, solubility sensor, pH sensor and conductivity sensor, the changes in the environmental conditions during the cooking process are monitored in real time, and the vitamin loss is predicted based on the total content, temperature and humidity of the initial vitamin, including predicting the dissolution and stability changes of the vitamin, to obtain the estimated vitamin content; based on the estimated vitamin content and the target vitamin content, the cooking strategy is adjusted. If excessive vitamin loss is predicted, the cooking temperature or time can be reduced, or a milder cooking control method, such as steaming or simmering, can be adopted to retain the vitamins in the target cooking ingredients as much as possible.

[0079] Specifically, in some exemplary embodiments, the target cooking strategy can be determined in one go through steps S101 to S111; in some other exemplary embodiments, the target cooking strategy can be obtained through multiple rounds of iterative optimization. As Figure 2 shown, after adjusting the preset cooking strategy based on the difference between the target nutrition information and the estimated nutrition component information to obtain the target cooking strategy, and controlling the cooking appliance to operate based on the target cooking strategy, that is, after S111, the method further includes:

[0080] S202, during the cooking process, repeatedly execute the steps of monitoring the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredient, and the step of predicting the loss of nutrition components based on the initial nutrition component information, the current operating parameter information and the current state parameter information, so as to update the estimated nutrition component information and obtain the updated estimated nutrition component information.

[0081] S204, periodically adjust the target cooking strategy based on the difference between the target nutrition information and the updated estimated nutrition component information, and control the cooking appliance to operate based on the periodically adjusted target cooking strategy until the updated estimated nutrition component information matches the target nutrition information.

[0082] That is, after initially obtaining a target cooking strategy, during the cooking process, periodically return to step S107 to periodically monitor the current operating parameter information and the current state parameter information, so as to continue to predict the loss of nutrition components according to the updated operating parameter information and the updated state parameter information, obtain the updated estimated nutrition component information, realize the periodic adjustment of the target cooking strategy, and further optimize the accuracy and reliability of the target cooking strategy.

[0083] Further, when the time of the periodic cycle approaches infinitesimal, that is, the current operating parameter information and the current state parameter information are monitored in real time to obtain the estimated nutrient composition information updated in real time, and further, based on the target nutrient information and the estimated nutrient composition information updated in real time, the target cooking strategy is adjusted in real time, and the cooking appliance is controlled to operate based on the target cooking strategy obtained by the real-time adjustment, so as to improve the adjustability, real-time performance and accuracy.

[0084] Specifically, as Figure 3 shown, step S103, that is, determining the initial nutrient composition information of the target cooking ingredient based on the image recognition result of the image information includes:

[0085] S301, performing image recognition on the image information to obtain the image recognition result; the image recognition result is used to indicate the ingredient types of the target cooking ingredient and the ingredient quantity of each ingredient type.

[0086] In some exemplary embodiments, the image recognition is performed by an image processing algorithm, and the image processing algorithm includes at least one of image denoising, image transformation, image analysis, image compression, image enhancement, and image blurring processing on the image information to improve the accuracy of the image recognition result.

[0087] In some exemplary embodiments, the original information of multiple ingredients can also be pre-stored, and the original information is used to indicate at least one characteristic identifier of the shape, color, and size of each ingredient. Then, the image information can be compared and recognized with the original information, and the image recognition result can be determined through the matching degree between the two, with high recognition efficiency and good accuracy.

[0088] S303, determining the nutritional data information corresponding to each of the ingredient types based on the first correspondence.

[0089] Wherein, the first correspondence is used to indicate the types of nutrient components, the unit content of the nutrient components, and the characteristics of the nutrient components corresponding to multiple ingredients. Among them, the unit content represents the content of each nutrient component contained in the ingredient per unit mass, and the characteristics of the nutrient components include characteristics such as the thermal stability, solubility, and acid-base properties of each nutrient component. Exemplarily, vitamin C will be destroyed at high temperatures, fat-soluble vitamins will dissolve in water or oil during cooking, and some vitamins have better stability in an acidic environment and are easily degraded in an alkaline environment, etc.; in some exemplary embodiments, the first correspondence can be a nutritional database or a nutritional data table of multiple ingredients. When the ingredient types of the target cooking ingredient are determined by obtaining the image recognition result, the nutritional data information corresponding to each ingredient in the target cooking ingredient can be directly determined by searching or looking up the table, and the nutritional data information is used to indicate the unit content and the characteristics of the nutrient components of this ingredient.

[0090] S305, perform data statistics based on the quantity of the food ingredients and the nutritional data information corresponding to each type of the food ingredients, so as to obtain the initial nutritional component information.

[0091] Then, according to the quantity of the food ingredients and the unit content indicated in the nutritional data information of the food ingredients, the total content of various nutritional components of a single food ingredient in the target cooking food ingredients can be statistically calculated, and further, the total content of the nutritional components of each food ingredient in the target cooking food ingredients can be statistically calculated, so that the initial nutritional component information can be obtained. In this process, image recognition is convenient and accurate, the statistical process of the nutritional component content is simple and fast, the accuracy of the obtained initial nutritional component information is good, and there is no need to manually input the food ingredient information and quantity, with a high degree of automation, which is beneficial to the convenience of use.

[0092] Specifically, as Figure 4 shown, the step S109, that is, the step of predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information and the current state parameter information to obtain the predicted nutritional component information includes:

[0093] S402, predict the loss state of the nutritional components corresponding to the current operating parameter information and the current state parameter information during the cooking process based on the second corresponding relationship, so as to obtain the predicted nutritional loss information.

[0094] S404, obtain the predicted nutritional component information based on the initial nutritional component information and the predicted nutritional loss information.

[0095] Among them, the second corresponding relationship is used to indicate the corresponding relationship between the loss states of various nutritional components, various operating parameters of the cooking appliance and various state parameter information of the food ingredients, including characteristics such as the thermal stability, solubility and acid-base property of each nutritional component, and can also include the loss rate of each nutritional component under various environmental conditions (such as temperature and humidity, etc.). In some exemplary embodiments, the second corresponding relationship can be a nutritional database or a nutritional data table of various nutritional components. When the current operating parameter information and the current state parameter information are obtained, the loss states of each nutritional component can be directly analyzed and predicted based on the search result by searching or looking up the table, and the prediction is accurate and controllable.

[0096] In some exemplary embodiments, the second correspondence relationship can be determined based on the nutritional component characteristics in the first correspondence relationship, and the nutritional component characteristics can characterize the loss of each nutritional component as the operating parameters and the state parameters of the food ingredients change; in addition, in some exemplary embodiments, the second correspondence relationship can be stored so that when the same current operating parameter information and current state parameter information are obtained again, the second correspondence relationship can be directly called to obtain the predicted nutritional loss information, improving the prediction efficiency.

[0097] The predicted nutritional loss information is used to indicate the types of nutritional components lost by the target cooking food ingredients at the current collection moment and the loss amounts of each nutritional component during the cooking process; after the initial nutritional component information and the predicted nutritional loss information are determined, the predicted nutritional component information can be determined based on the residual amount of the nutritional component being equal to the initial amount minus the loss amount, and the prediction accuracy of the predicted nutritional component information is high and the reliability is good.

[0098] Specifically, as Figure 5 shown, before predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain the predicted nutritional component information, that is, before step S109, the method further includes:

[0099] S501, searching in the historical dataset for the predicted nutritional component information corresponding to the initial nutritional component information, the current operating parameter information, and the current state parameter information.

[0100] S503, if not found, perform the step of predicting the loss of nutritional components based on the initial nutritional component information, the current operating parameter information, and the current state parameter information to obtain the predicted nutritional component information;

[0101] S505, if found, use the historical predicted nutritional component information as the predicted nutritional component information.

[0102] Among them, the historical dataset is used to store the historical estimated nutrient composition information obtained by predicting based on the historical initial nutrient composition information, historical current operating parameter information, and historical current status parameter information monitored during the historical cooking process. If the corresponding historical estimated nutrient composition information is found, it indicates that the same cooking conditions occurred during the historical cooking process. Then, the historical estimated nutrient composition information corresponding to the initial nutrient composition information, current operating parameter information, and current status parameter information can be directly called as the estimated nutrient composition information for this time, greatly reducing the complexity of prediction, improving the prediction accuracy and real-time performance, and having good prediction reliability. If the corresponding historical estimated nutrient composition information is not found, it indicates that the initial nutrient composition information, current operating parameter information, and current status parameter information appear for the first time. Then, step S109 is executed to predict nutrient loss and obtain the estimated nutrient composition information. Correspondingly, after obtaining the estimated nutrient composition information, the corresponding relationship between the estimated nutrient composition information, its initial nutrient composition information, current operating parameter information, and current status parameter information can also be stored in the historical dataset, so that when the same situation occurs later, the historical estimated nutrient composition information can be directly called as the estimated nutrient composition information, greatly simplifying the prediction process.

[0103] Specifically, as Figure 6 shown, after predicting nutrient loss based on the initial nutrient composition information, the current operating parameter information, and the current status parameter information to obtain the estimated nutrient composition information, that is, after step S109, the method further includes:

[0104] S602, obtaining the status information of the edible object.

[0105] S604, generating diet recommendation information based on the status information and the estimated nutrient composition information.

[0106] Among them, the status information is used to indicate the diet preference, eating habit, and physical status of the edible object; in some exemplary embodiments, the target cooking ingredients can be selected and determined according to the status information, such as the target cooking ingredients of the diet preference or the target cooking ingredients with a higher frequency of occurrence in the statistically analyzed eating habits. Based on the target cooking ingredients, steps S101 to S111 described above are executed for prediction and cooking strategy adjustment to meet the nutritional requirements that the edible object needs to satisfy.

[0107] In some exemplary embodiments, the status information may further include nutritional requirement information, which is used to indicate the nutritional requirements of the user. Then, the target nutritional information can be determined based on dietary preferences, eating habits, physical condition, and nutritional requirements. Correspondingly, the target cooking ingredients and cooking strategies are adjusted according to the status information (dietary preferences, eating habits, physical condition, and nutritional requirements) so that the estimated nutritional component information meets the target nutritional component content indicated by the nutritional requirement information. After actual cooking and consumption by the edible object, the nutritional requirements of the edible object can be met.

[0108] Moreover, based on the status information and the estimated nutritional components, dietary advice information can be generated. The dietary advice information includes information such as adjusting the target cooking ingredients, suggesting adjusting the cooking strategy, and suggesting supplementary nutritional components, etc., so as to fully consider the personal status information of the edible object, provide personalized healthy diet advice, and improve the user experience.

[0109] In addition, the cooking control method can also be applied to a health management system. According to the status information, the status information and the estimated nutritional component information are updated regularly, so as to update the nutritional tracking data regularly according to the status information and the estimated nutritional component information, and provide regular nutritional assessment and feedback services.

[0110] Corresponding to the cooking control method provided in the above embodiments of the present invention, the cooking control device provided in the embodiments of the present invention can implement the cooking control method in the above method embodiments. Among them, as Figure 7 shown, the cooking control device may include:

[0111] An image acquisition module 710, configured to acquire image information of a cooking utensil on which target cooking ingredients are placed;

[0112] A nutritional component determination module 720, configured to determine the initial nutritional component information of the target cooking ingredients based on the image recognition result of the image information; the initial nutritional component information is used to indicate the types and respective contents of the nutritional components of each of the target cooking ingredients;

[0113] A cooking module 730, configured to control the cooking utensil to cook based on a preset cooking strategy;

[0114] A monitoring module 740, configured to monitor the current operating parameter information of the cooking utensil and the current status parameter information of the target cooking ingredients during the cooking process;

[0115] A prediction module 750, configured to perform a prediction of nutrient loss based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information, so as to obtain predicted nutrient composition information; the predicted nutrient composition information is used to indicate the types and respective contents of the nutrients remaining in the target cooking ingredient after cooking.

[0116] An adjustment module 760, configured to adjust the preset cooking strategy based on the difference between the target nutrient information and the predicted nutrient composition information, so as to obtain a target cooking strategy, and control the cooking appliance to operate based on the target cooking strategy; the target nutrient information is used to indicate the types and respective contents of the target nutrient component contents that need to be retained in the target cooking ingredient after cooking.

[0117] Specifically, the cooking control device may further include:

[0118] A circulation module, configured to, during the cooking process, repeatedly execute the steps of monitoring the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredient, and performing a prediction of nutrient loss based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information, so as to update the predicted nutrient composition information and obtain updated predicted nutrient composition information.

[0119] A periodic adjustment module, configured to periodically adjust the target cooking strategy based on the difference between the target nutrient information and the updated predicted nutrient composition information, and control the cooking appliance to operate based on the periodically adjusted target cooking strategy until the updated predicted nutrient composition information matches the target nutrient information.

[0120] Specifically, the nutrient composition determination module 720 may further include:

[0121] An identification module, configured to perform image recognition on the image information to obtain an image recognition result, and the image recognition result is used to indicate the types of the target cooking ingredient and the respective quantities of each type of ingredient.

[0122] A nutrient data determination module, configured to determine the respective corresponding nutrient data information for each type of ingredient based on a first correspondence relationship; the first correspondence relationship is used to indicate the types of nutrient components, the unit content of the nutrient components, and the nutrient component characteristics corresponding to various ingredients.

[0123] A statistics module, configured to perform data statistics based on the ingredient quantity and the respective corresponding nutrient data information for each type of ingredient to obtain the initial nutrient composition information.

[0124] Specifically, the prediction module 750 may include:

[0125] The loss information prediction module is used to predict the loss status of the nutrient components corresponding to the current operating parameter information and the current state parameter information during the cooking process based on the second corresponding relationship, so as to obtain predicted nutrient loss information; the second corresponding relationship is used to indicate the corresponding relationship between the loss status of multiple nutrient components, multiple operating parameters of the cooking appliance, and multiple state parameter information of the food ingredients;

[0126] The calculation module is used to obtain the estimated nutrient component information based on the initial nutrient component information and the predicted nutrient loss information.

[0127] Specifically, the cooking control device may further include:

[0128] The historical search module is used to search for the estimated nutrient component information corresponding to the initial nutrient component information, the current operating parameter information, and the current state parameter information from the historical dataset; the historical dataset is used to store the historical estimated nutrient component information obtained by prediction based on the historically monitored historical initial nutrient component information, historical current operating parameter information, and historical current state parameter information during the historical cooking process;

[0129] The prediction module is used to, in the case of not finding, perform the steps of predicting the loss of nutrient components based on the initial nutrient component information, the current operating parameter information, and the current state parameter information, so as to obtain the estimated nutrient component information;

[0130] The calling module is used to, in the case of finding, use the historical estimated nutrient component information as the estimated nutrient component information.

[0131] Specifically, the cooking control device may further include:

[0132] The status information acquisition module is used to acquire the status information of the edible object; the status information is used to indicate the dietary preferences, eating habits, and physical status of the edible object;

[0133] The suggestion generation module is used to generate dietary suggestion information based on the status information and the estimated nutrient component information.

[0134] It should be noted that for the cooking control device provided in the above embodiments, when realizing its functions, only the division of the above functional modules is used for illustration. In actual applications, the above functions may be allocated to different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. In addition, the cooking control device provided in the above embodiments and the method embodiments belong to the same concept, and the specific implementation process thereof can be seen in the method embodiments, which will not be elaborated here.

[0135] The cooking control device includes a processor and a memory. Among them, the processor (or CPU (Central Processing Unit)) is the core component, and its main functions are to interpret the memory instructions and process the data fed back by each module of the cooking control device. The structure of the processor is roughly divided into an arithmetic logic unit and a register unit, etc. The arithmetic logic unit mainly performs relevant logical calculations (such as shift operations, logical operations, fixed-point or floating-point arithmetic operations, and address operations, etc.), and the register unit is used to temporarily store instructions, data, and addresses.

[0136] The memory is a memory device and can be used to store software programs and modules. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory. The memory mainly includes a program storage area and a data storage area. Among them, the program storage area can store an operating system, which can include, but is not limited to: Windows system (an operating system), Linux (an operating system), etc. The present invention does not make any limitations in this regard. In addition, it can also store application programs required for functions. For example, at least one instruction suitable for being loaded and executed by the processor is also stored in the storage space of this memory. These instructions can be one or more computer programs (including program codes). And the data storage area can store data created according to the use of the device, etc. Correspondingly, the memory can also include a memory controller to provide the processor with access to the memory.

[0137] The method embodiments provided in the embodiments of the present application can be executed in electronic devices such as mobile terminals, computer terminals, servers, or similar computing devices. Figure 8 It is a hardware structure block diagram of an electronic device that executes the cooking control method provided in the embodiments of the present application. As Figure 8As shown, the electronic device 800 can vary significantly due to different configurations or performances. It may include one or more central processing units (CPUs) 810 (the processor 810 may include, but is not limited to, processing devices such as a microprocessor MCU or a field-programmable gate array FPGA), a memory 830 for storing data, and one or more storage media 820 for storing application programs 823 or data 822 (such as one or more mass storage devices). Among them, the memory 830 and the storage media 820 can be transient storage or persistent storage. The program stored in the storage media 820 may include one or more modules, and each module may include a series of instruction operations for the electronic device. Further, the central processor 810 can be configured to communicate with the storage media 820 and execute a series of instruction operations in the storage media 820 on the electronic device 800. The electronic device 800 may also include one or more power supplies 860, one or more wired or wireless network interfaces 850, one or more input / output interfaces 840, and / or one or more operating systems 821, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, and so on.

[0138] The input / output interface 840 can be used to receive or send data via a network. Specific examples of the above network may include the wireless network provided by the communication provider of the electronic device 800. In one example, the input / output interface 840 includes a network interface controller (NIC), which can be connected to other network devices through a base station and thus communicate with the Internet. In one example, the input / output interface 840 can be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0139] Those of ordinary skill in the art can understand that Figure 8 the structure shown is only schematic and does not limit the structure of the above electronic device. For example, the electronic device 800 may also include more or fewer components than Figure 8 shown, or have a different configuration from Figure 8 shown.

[0140] An embodiment of the present invention further provides a cooking control system, including a cooking appliance, an image acquisition device, and the cooking management device as described above, for acquiring image information of the cooking appliance on which the target cooking ingredient is placed; in some exemplary embodiments, the image acquisition device is disposed inside the cooking appliance; in some other exemplary embodiments, the image acquisition device is disposed above the cooking appliance; exemplarily, the image acquisition device may be a camera, which is convenient for acquisition and occupies a small space; the image acquisition device can accurately acquire the image of the target cooking ingredient placed inside the cooking appliance, facilitating image analysis and recognition of the target cooking ingredient, improving the accuracy of subsequent adjustment of the cooking strategy, and also facilitating generation of personalized dietary advice information for the target cooking ingredient and the physical state of the edible object itself, enhancing the user experience.

[0141] Specifically, the cooking control system further includes a plurality of information acquisition devices, the plurality of information acquisition devices are disposed in the cooking appliance, and the plurality of information acquisition devices are used for acquiring the current operating information in the cooking appliance and the current state parameter information of the target cooking ingredient; in some exemplary embodiments, the plurality of information acquisition devices include at least one of a temperature acquisition device, a humidity acquisition device, a solubility acquisition device, a pH value acquisition device, and a conductivity acquisition device, so as to fully reflect the state in the current cooking appliance and improve the accuracy and reliability of subsequent prediction.

[0142] An embodiment of the present invention further provides a storage medium, in which at least one instruction or at least one program segment is stored, and the at least one instruction or the at least one program segment is loaded and executed by a processor to implement the cooking control method described above; optionally, the storage medium may be located in at least one of a plurality of network servers in a computer network; in addition, the storage medium may include, but is not limited to, various storage media capable of storing program codes such as random access memory (RAM, Random Access Memory), read-only memory (ROM, Read-Only Memory), non-volatile memory (NVM), USB flash drives, mobile hard disks, magnetic disk storage devices, flash memory devices, and other volatile solid-state storage devices.

[0143] According to one aspect of the present invention, there is provided a computer program product or a computer program, the computer program product or the computer program includes computer instructions, and the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device executes the cooking control method provided in the above various optional implementation manners.

[0144] It should be noted that the above order of the embodiments of the present invention is only for description and does not represent the superiority or inferiority of the embodiments. And the above description of specific embodiments of this specification has been made. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the drawings do not necessarily require the specific order or sequential order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0145] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. The key point of each embodiment is to illustrate the differences from other embodiments.

[0146] The above description is only some embodiments of the present invention and is not intended to limit the present invention. Those skilled in the art should understand that the present invention will have various changes and improvements, and any modifications, equivalent replacements, and improvements made in accordance with the present invention fall within the scope of protection required by the present invention.

Claims

1. A cooking control method, characterized in that, Including: Obtaining image information of a cooking appliance on which target cooking ingredients are placed; Determining initial nutrient composition information of the target cooking ingredients based on an image recognition result of the image information; the initial nutrient composition information is used to indicate the types and respective contents of the nutrients possessed by each of the target cooking ingredients; Controlling the cooking appliance to cook based on a preset cooking strategy; During the cooking process, monitoring current operating parameter information of the cooking appliance and current state parameter information of the target cooking ingredients; Performing nutrient loss prediction based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information to obtain predicted nutrient composition information; the predicted nutrient composition information is used to indicate the types and respective contents of the nutrients remaining in the target cooking ingredients after cooking; Adjusting the preset cooking strategy based on the difference between target nutrient information and the predicted nutrient composition information to obtain a target cooking strategy, and controlling the cooking appliance to operate based on the target cooking strategy; the target nutrient information is used to indicate the types and respective contents of the target nutrient contents to be retained in the target cooking ingredients after cooking.

2. The cooking control method according to claim 1, wherein After adjusting the preset cooking strategy based on the difference between the target nutrient information and the predicted nutrient composition information to obtain a target cooking strategy and controlling the cooking appliance to operate based on the target cooking strategy, the method further includes: During the cooking process, repeatedly executing the steps of monitoring the current operating parameter information of the cooking appliance and the current state parameter information of the target cooking ingredients and performing nutrient loss prediction based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information to update the predicted nutrient composition information and obtain updated predicted nutrient composition information; Periodically adjusting the target cooking strategy based on the difference between the target nutrient information and the updated predicted nutrient composition information, and controlling the cooking appliance to operate based on the periodically adjusted target cooking strategy until the updated predicted nutrient composition information matches the target nutrient information.

3. The cooking control method according to claim 1, wherein The determining the initial nutrient composition information of the target cooking ingredients based on the image recognition result of the image information includes: Performing image recognition on the image information to obtain the image recognition result, the image recognition result being used to indicate the types of the target cooking ingredients and the respective quantities of each type of ingredient; Determining respective corresponding nutrient data information for each of the types of ingredients based on a first correspondence relationship; the first correspondence relationship is used to indicate the types of nutrients corresponding to various ingredients, the unit contents of the nutrients, and the nutrient characteristics; Performing data statistics based on the quantities of the ingredients and the respective corresponding nutrient data information for each of the types of ingredients to obtain the initial nutrient composition information.

4. The cooking control method according to claim 1, wherein The performing nutrient loss prediction based on the initial nutrient composition information, the current operating parameter information, and the current state parameter information to obtain predicted nutrient composition information includes: Based on the second correspondence relationship, predict the loss status of the nutrient components corresponding to the current operating parameter information and the current status parameter information during the cooking process, to obtain predicted nutrient loss information; the second correspondence relationship is used to indicate the correspondence relationship between the loss statuses of multiple nutrient components, multiple operating parameters of the cooking appliance, and multiple status parameter information of the food ingredients; Based on the initial nutrient component information and the predicted nutrient loss information, obtain the estimated nutrient component information.

5. The cooking control method according to claim 1, wherein Before predicting the nutrient component loss based on the initial nutrient component information, the current operating parameter information, and the current status parameter information to obtain the estimated nutrient component information, the method further includes: Search for the estimated nutrient component information corresponding to the initial nutrient component information, the current operating parameter information, and the current status parameter information from the historical dataset; the historical dataset is used to store the historical estimated nutrient component information obtained by predicting based on the historically monitored historical initial nutrient component information, historical current operating parameter information, and historical current status parameter information during the historical cooking process; If not found, execute the step of predicting the nutrient component loss based on the initial nutrient component information, the current operating parameter information, and the current status parameter information to obtain the estimated nutrient component information; If found, use the historical estimated nutrient component information as the estimated nutrient component information.

6. The cooking control method according to claim 1, wherein, After predicting the nutrient component loss based on the initial nutrient component information, the current operating parameter information, and the current status parameter information to obtain the estimated nutrient component information, the method further includes: Obtain the status information of the edible object; the status information is used to indicate the dietary preferences, eating habits, and physical status of the edible object; Based on the status information and the estimated nutrient component information, generate dietary advice information.

7. A cooking control device, characterized in that, It includes: An image acquisition module, configured to acquire image information of a cooking appliance on which target cooking food ingredients are placed; A nutrient component determination module, configured to determine the initial nutrient component information of the target cooking food ingredients based on the image recognition result of the image information; the initial nutrient component information is used to indicate the types and respective contents of the nutrient components possessed by each of the target cooking food ingredients; A cooking module, configured to control the cooking appliance to cook based on a preset cooking strategy; A monitoring module, configured to monitor the current operating parameter information of the cooking appliance and the current status parameter information of the target cooking food ingredients during the cooking process; A prediction module, configured to predict the nutrient component loss based on the initial nutrient component information, the current operating parameter information, and the current status parameter information to obtain the estimated nutrient component information; The estimated nutrient component information is used to indicate the types and respective contents of the nutrient components remaining after the target cooking food ingredients are cooked; An adjustment module, configured to adjust the preset cooking strategy based on the difference between the target nutritional information and the estimated nutritional component information to obtain a target cooking strategy, and control the cooking appliance to operate based on the target cooking strategy; the target nutritional information is used to indicate the types and respective contents of the target nutritional components required to be retained after cooking the target cooking ingredients.

8. A cooking control system, characterized in that, It includes a cooking appliance, an image acquisition device, and the cooking management device according to claim 7, wherein the image acquisition device is arranged inside the cooking appliance and is used to acquire the image information of the cooking appliance with the target cooking ingredients placed therein.

9. The cooking control system according to claim 8, wherein The cooking control system further includes a plurality of information acquisition devices, the plurality of information acquisition devices are arranged in the cooking appliance, and the plurality of information acquisition devices are used to acquire the current operation information in the cooking appliance and the current state parameter information of the target cooking ingredients.

10. A storage medium, characterized in that, At least one instruction or at least one segment of program is stored in the storage medium, and the at least one instruction or the at least one segment of program is loaded and executed by a processor to implement the cooking control method according to any one of claims 1-6.

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