Cooking parameter determination method and device, electronic equipment and storage medium

Abstract

The invention provides a cooking parameter determination method and apparatus, an electronic device and a storage medium. The method comprises the steps of obtaining geographic position information of a cooking device, and staple food material information and first nutritional ingredient information of a to-be-cooked staple food material; generating a side dish recommendation list based on the geographical location information, the staple food material information and the first nutritional ingredient information; generating a cooking mode recommendation list based on the geographic position information, and obtaining a target cooking mode in the cooking mode recommendation list; acquiring second nutritional ingredient information of a target side dish in the side dish recommendation list; generating target cooking parameters based on the first nutritional ingredient information, the second nutritional ingredient information and the target cooking mode; generating a nutrition evaluation result based on the first nutritional ingredient information, the second nutritional ingredient information and the target cooking parameters; and determining whether to cook according to the target cooking parameters based on the nutrition evaluation result. According to the method, the taste, the sense organ and the nutritional value are neutralized, and the efficiency and the flexibility of determining the cooking parameters are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of kitchen appliances, and in particular to a cooking parameter determination method, device, electronic device and storage medium. Background Art

[0002] With the rapid development of smart home technology, kitchen appliances, as an important part of smart homes, are also showing a trend of intelligence. Due to the improvement of people's living standards and differences in regional culture, consumers' demand for kitchen appliances is diverse and personalized. Consumers have higher expectations for smart kitchen appliances that can automatically adjust cooking parameters according to personal needs (such as nutritional value, taste and sensory needs) and regional characteristics.

[0003] However, current kitchen appliances generally cook using pre-set default cooking parameters, which not only have few options and cannot be flexibly configured according to actual needs, but also require users to click on the default cooking parameters of the cooking method one by one to select and confirm when determining the cooking parameters, wasting the user's time and resulting in inefficiency. Summary of the invention

[0004] In view of this, an object of the present invention is to provide a cooking parameter determination method, device, electronic device and storage medium to improve the efficiency and flexibility of cooking parameter determination.

[0005] In a first aspect, a method for determining cooking parameters is provided, the method comprising:

[0006] Acquire geographic location information of the cooking device and main ingredient information and first nutrient component information of the main ingredient to be cooked;

[0007] Generate a recommended list of side dishes based on the geographic location information, the main ingredient information, and the first nutritional component information;

[0008] Generate a cooking method recommendation list based on the geographic location information, and obtain a target cooking method from the cooking method recommendation list;

[0009] Obtain the second nutritional component information of the target side dish in the side dish recommendation list;

[0010] generating target cooking parameters based on the first nutrient component information, the second nutrient component information and the target cooking method;

[0011] generating a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameter;

[0012] Whether to cook with target cooking parameters is determined based on the nutritional evaluation result.

[0013] Optionally, obtaining the main ingredient information and the first nutrient component information of the main ingredient to be cooked includes:

[0014] Capturing images of the main food to be cooked by an image acquisition device;

[0015] Inputting the image of the main ingredient to be cooked into the pre-built large model for image recognition to obtain the main ingredient information, where the main ingredient at least includes the name of the main ingredient;

[0016] Based on the name of the main ingredient, first nutritional component information of the main ingredient to be cooked is searched in a preset ingredient nutrition database, where the first nutritional component information at least includes a nutritional component type and a nutritional component content.

[0017] Optionally, generating a recommended side dish list based on the geographical location information, the main ingredient information and the first nutritional component information includes:

[0018] Generate a local recommended recipe list containing the main ingredients according to the main ingredient information and the geographical location information;

[0019] Obtain target recipes from the local recommended recipe list;

[0020] The other ingredients in the target recipe except the main ingredients are determined as side dishes, and a side dish recommendation list is generated.

[0021] Optionally, generating a cooking method recommendation list based on geographic location information includes:

[0022] Based on the geographic location information, search for climate and food culture data of the user's region in a preset regional feature database;

[0023] Based on the climate and food culture data of the region, a preset number of cooking method recommendation lists are generated through a pre-built large model.

[0024] The first nutrient information and the second nutrient information both include nutrient type and nutrient content. The nutrient evaluation result generated based on the first nutrient information, the second nutrient information and the target cooking method includes:

[0025] Obtaining the reserved amount of the nutrient content corresponding to each nutrient type under the target cooking parameters;

[0026] The nutritional evaluation result is generated based on the retained amount of the nutritional component content corresponding to each nutritional component type.

[0027] Optionally, determining whether to cook with target cooking parameters based on the nutritional evaluation result includes:

[0028] Obtaining operation information for the nutrition evaluation results, including satisfactory operations and unsatisfactory operations;

[0029] If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters;

[0030] If the operation information is an unsatisfactory operation, the target cooking parameters are adjusted;

[0031] The adjusted target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the adjusted target cooking parameters.

[0032] Optionally, determining whether to cook with target cooking parameters based on the nutritional evaluation result includes:

[0033] Obtaining operation information for the nutrition evaluation results, including satisfactory operations and unsatisfactory operations;

[0034] If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters;

[0035] If the operation information is an unsatisfactory operation, the target side dish in the side dish recommendation list is adjusted;

[0036] re-obtaining the adjusted second nutritional component information of the target side dish;

[0037] The nutrition evaluation result and the target cooking parameter are regenerated based on the reacquired second nutrition component information.

[0038] In a second aspect, a cooking parameter determination device is provided, the device comprising:

[0039] A first acquisition unit, used to acquire geographical location information of the cooking device and main ingredient information and first nutrient component information of the main ingredient to be cooked;

[0040] A first generating unit, configured to generate a side dish recommendation list based on the geographical location information, the main ingredient information and the first nutritional component information;

[0041] A second generating unit, configured to generate a cooking method recommendation list based on the geographical location information;

[0042] A second acquiring unit, configured to acquire a target cooking method from a cooking method recommendation list;

[0043] A third obtaining unit is used to obtain second nutritional component information of a target side dish in the side dish recommendation list;

[0044] a third generating unit, configured to generate a target cooking parameter based on the first nutrient component information, the second nutrient component information and the target cooking method;

[0045] a fourth generating unit, configured to generate a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameter;

[0046] A determination unit is used to determine whether to cook with target cooking parameters based on the nutrition evaluation result.

[0047] In a third aspect, an electronic device is provided, comprising a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other via the communication bus;

[0048] Memory, used to store computer programs;

[0049] The processor is used to implement any method step of the first aspect when executing the program stored in the memory.

[0050] According to a fourth aspect, a computer-readable storage medium is provided, wherein a computer program is stored in the computer-readable storage medium, and when the computer program is executed by a processor, any method step of the first aspect is implemented.

[0051] The embodiments of the present invention provide a cooking parameter determination method, device, electronic device and storage medium. Since geographical location information can be used to obtain food culture data with local characteristics, the local food culture data reflects the eating habits, taste and sensory needs of local users. Therefore, the target cooking parameters are generated by integrating geographical location information and nutritional information, thereby achieving the neutralization of taste, sensory and nutritional value. The generated target cooking parameters are closer to user needs, reducing the time for users to repeatedly select and modify cooking parameters, and improving the efficiency of determining cooking parameters. Compared with the method of selecting cooking parameters in a fixed manner in the prior art, the present application combines nutritional information and geographical location information to determine cooking parameters, and the method is more flexible.

[0052] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 A schematic diagram showing the structure of a kitchen appliance control system provided by an embodiment of the present invention is shown;

[0055] Figure 2 A flow chart showing another cooking parameter determination method provided by an embodiment of the present invention;

[0056] Figure 3 A schematic diagram showing the structure of a cooking parameter determination device provided by an embodiment of the present invention is shown;

[0057] Figure 4 A schematic structural diagram of an electronic device provided by an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0058] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0059] Considering that the current methods for determining cooking parameters of kitchen appliances are relatively fixed, single, and inefficient, based on this, an embodiment of the present invention provides a method and device for determining cooking parameters, which are described below through embodiments.

[0060] The embodiment of the present invention provides a cooking parameter determination method, which is applied to a kitchen appliance control system, such as Figure 1 As shown, the kitchen appliance control system consists of kitchen appliances, a mobile phone APP and a server. The kitchen appliance is connected to the server and APP through wireless communication methods such as WiFi to achieve data interaction.

[0061] Among them, the kitchen appliances are provided with a button operation area and a display area. The button operation area is used for networking, setting regions, power switches, function selection, setting parameters, etc.; the display area can be a color screen, Android, IOS and other control screens, or it can be an OLED screen that can partially refresh the font library. The display area has the functions of dynamically displaying recipes, cooking parameters and reminders.

[0062] The embodiment of the present invention provides a cooking parameter determination method, which is applied to a server side, such as Figure 2 As shown, the method comprises the following steps:

[0063] Step S201: obtaining geographical location information of a cooking device and main ingredient information and first nutrient component information of a main ingredient to be cooked.

[0064] In the embodiment of the present application, the kitchen appliance is specifically a cooking appliance, which may be a steam oven, etc. When the user operates the power button of the cooking appliance to enter the power-on interface, the cooking appliance is connected to the server through the network, and the server uses GPS, network positioning and other technical means to obtain the geographical location information of the cooking appliance. In addition, the user can also manually set the region in the key operation area and synchronize it to the mobile phone APP and the server through WiFi and other means. The region can also be selected on the mobile phone APP through mobile phone positioning, and synchronized to the cooking device and the server.

[0065] The main ingredient information includes the ingredient name, ingredient category, etc. The user can manually enter the ingredient information in the case operation area of ​​the cooking equipment and synchronize it to the server and mobile phone APP. The main ingredient information can also be collected through the camera device built into the kitchen appliance. The specific method of image recognition of the main ingredient information will be described in detail in the following embodiments and will not be repeated here.

[0066] Step S202: Generate a list of recommended side dishes based on the geographical location information, the main ingredient information and the first nutritional component information.

[0067] In one example, a grilled steak might be served with broccoli as a side dish, which would provide a more balanced nutritional combination.

[0068] Step S203: Generate a cooking method recommendation list based on the geographical location information and obtain a target cooking method from the cooking method recommendation list.

[0069] The cooking method generated by geographic location information is more in line with the taste of the user's area. Most users are locals, so the cooking method is basically in line with the user's eating habits, avoiding users from choosing one by one from a large number of cooking methods, greatly saving time.

[0070] The server sends the recommended cooking method list to the cooking device for display, and the user can further select the target cooking method in the recommended cooking method list according to his or her taste and other requirements. The recommended cooking method list can also be synchronized to the mobile phone APP for display, and the user can select it on the mobile phone APP. In one example, the recommended cooking method list includes "nutritional steaming, steaming, baking, air baking, air frying" and so on.

[0071] Each time the user selects a target cooking method, the cooking device will automatically classify the target cooking method. The user can search directly in the classification type next time. For example, "Nutritional Steaming" and "Pang Pai Steaming" are automatically classified into the [Steaming] category. The user can search directly for historical target cooking methods in the [Steaming] category next time, which is more convenient.

[0072] Step S204: Obtain the second nutritional component information of the target side dish in the side dish recommendation list.

[0073] The server side sends the generated side dish recommendation list to the cooking device side, which is displayed in the display area of ​​the cooking device side. The user can select one or more target side dishes from the side dish recommendation list according to his or her taste. For example, the side dish recommendation list includes green onions and ginger. However, some users do not like ginger, so they can only select green onions as the target side dish. The cooking device side sends the side dish name of the target side dish to the server side, and the server side can search for the corresponding second nutritional component information in the preset food nutrition database according to the side dish name. The second nutritional component information includes at least the nutritional component type and the nutritional component content. In an example, for example, the nutritional component types of steak include fat, protein, etc.

[0074] Step S205: Generate target cooking parameters based on the first nutrient component information, the second nutrient component information and the target cooking method.

[0075] The target cooking method is a cooking method that combines regional characteristics and personal needs. Therefore, the target cooking parameters generated by the first nutrient information, the second nutrient information and the target cooking method integrate geographical, nutritional and other personal needs, such as taste, sensory, etc., and are more in line with the user's cooking needs.

[0076] For example, in Hangzhou, the taste is mainly light, and the target cooking method is generally "nutritional steaming". The temperature of nutritional steaming is lower and the time is shorter, which can reduce the loss of nutrients in the food. However, due to the lower temperature, the color of the steamed and baked food is a little worse, that is, the sensory perception is worse. Due to the short time, the taste may also be worse. If it is Chengdu, the taste is heavier, the target cooking method is generally "surging steaming". The temperature of surging steaming is higher than that of nutritional steaming, so the nutritional value is lower, the sensory perception is better, and the time is longer, the taste may also be better. For the target cooking method with low nutritional value or low taste, further refer to the nutritional components of the main ingredients and side dishes to generate the target cooking parameters, adjust the cooking time and cooking temperature, so that the nutritional value, taste, etc. will be improved accordingly, and the nutritional value, sensory perception and taste will be neutralized.

[0077] Generating cooking parameters based on the first nutrient component information, the second nutrient component information and the target cooking method comprises the following steps:

[0078] Step S2051: Obtaining default cooking parameters of the target cooking method.

[0079] After the user selects the target cooking method in the display area of ​​the cooking device, the cooking device will upload the default cooking parameters to the server.

[0080] Step S2052: adjusting the default cooking parameters based on the first nutrient component information and the second nutrient component information to obtain target cooking parameters.

[0081] The server can input the default cooking parameters, the first nutritional component information, and the second nutritional component information into the big model, and the big model will output the adjusted target cooking parameters. The big model will calculate the impact data of the default cooking parameters on the first nutritional component information and the second nutritional component information, such as the nutritional loss. If the nutritional loss is too large, the big model will automatically adjust the default cooking parameters, such as reducing the cooking temperature, etc., to generate the adjusted target cooking parameters. The adjusted target cooking parameters neutralize the nutritional value, taste, and sensory perception.

[0082] Step S206: Generate a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameters.

[0083] The nutritional evaluation result can be generated by determining the retention of the nutritional information of the main ingredients and side dishes of the target cooking parameters.

[0084] Step S207: Determine whether to cook with target cooking parameters based on the nutritional evaluation result.

[0085] The server side sends the generated nutritional evaluation results and target cooking parameters to the cooking device side, and displays them in the display area of ​​the cooking device side. The user can perform relevant operations based on the nutritional evaluation results to confirm whether to cook with the target cooking parameters, and synchronize the relevant operation results to the server side, which will perform corresponding processing.

[0086] The embodiment of the present application generates target cooking parameters by integrating geographic location information and nutritional information, thereby achieving a balance between taste, sensory and nutritional value. The generated target cooking parameters are closer to user needs, reducing the time for users to repeatedly select and modify cooking parameters, and improving the efficiency of determining cooking parameters. Compared with the method of selecting cooking parameters in a fixed manner in the prior art, the present application combines nutritional information and geographic location information to determine cooking parameters, which is more flexible.

[0087] Based on the above embodiment, obtaining the main ingredient information and the first nutrient component information of the main ingredient to be cooked includes the following steps:

[0088] Step S2011: Capturing images of the main food to be cooked by an image acquisition device.

[0089] The image acquisition device may be integrated into the cooking device or installed independently of the cooking device, and images with cooking ingredients are acquired through the image acquisition device.

[0090] Step S2012: input the image of the main ingredient to be cooked into the pre-built large model for image recognition to obtain the main ingredient information, where the main ingredient at least includes the main ingredient name.

[0091] Large Model (also called Foundation Model) refers to a machine learning model with a large number of parameters and complex structure, which can process massive data and complete various complex tasks. Large models contain billions of parameters, and the model size can reach hundreds of GB or even larger. The huge model size gives large models powerful expression and learning capabilities. Large models usually have stronger learning and generalization capabilities, and can perform well on various tasks, including natural language processing, image recognition, speech recognition, etc.

[0092] In an embodiment of the present application, a visual large model may be used, such as Google's VIT series. In one example, based on Google's VIT series general large model, by collecting a large amount of food training image data for pre-training, target detection and image classification of food images can be achieved, thereby identifying the food category and food name in the image.

[0093] Step S2013: searching for first nutrient component information of the main ingredient to be cooked in a preset ingredient nutrition database based on the name of the main ingredient.

[0094] The first nutritional component information at least includes nutritional component types and nutritional component contents. The food nutrition database stores more than 30 common nutritional component types and contents of common food materials, such as nutritional component types and contents of leafy vegetables, white meat and other food materials.

[0095] Based on the above embodiment, generating a side dish recommendation list based on the geographical location information, the main ingredient information and the first nutritional component information includes the following steps:

[0096] Step S2021: Generate a local recommended recipe list containing main ingredients according to the main ingredient information and the geographical location information.

[0097] In this step, a local recommended recipe list can also be generated through the big model. Specifically, the special dishes and local recipes of each region can be input into the language big model for pre-training. After the training is completed, the local recommended recipe list can be obtained by entering the geographic location information and the name of the ingredient. For example, by entering the keywords fish and Hangzhou, a recipe for West Lake Vinegar Fish can be generated.

[0098] In another embodiment, if it is a major festival, such as the Spring Festival, the Mid-Autumn Festival, etc., the server can also generate some festival recommended recipes and send them to the cooking device to enrich the user's cooking experience. Specifically, the server obtains the current date information and determines whether it is a preset festival date according to the current date information. If so, it combines the main ingredient information and the geographical location information to generate a local recommended recipe list containing the main ingredients.

[0099] Step S2022: Obtain the target recipe from the local recommended recipe list.

[0100] The local recommended recipe list generated in the above steps may include multiple local recommended recipes. The server sends the local recommended recipe list to the cooking device and displays it in the display area of ​​the cooking device. It can also be sent to the mobile phone APP. The user can select a target recipe from the local recommended recipe list on the cooking device or mobile phone APP, and send the selection result to the server.

[0101] After the user selects the target recipe, the cooking device will automatically classify the target recipe. For example, "West Lake Vinegar Fish" and "Chopped Pepper Fish Head" are automatically classified into the [Fish] category. Next time, the user can search in the [Fish] category to directly find the target recipe, making it more convenient and quick to find the required recipe.

[0102] Step S2023: Determine the ingredients other than the main ingredient in the target recipe as side dishes, and generate a list of recommended side dishes.

[0103] For example, if the target recipe is West Lake Vinegar Fish, and its ingredients include grass carp, ginger, and green onion, then ginger and green onion can generate a list of recommended side dishes.

[0104] Based on the above embodiment, generating a cooking method recommendation list based on geographic location information includes:

[0105] Based on the geographic location information, the climate and food culture data of the user's area are searched in the preset regional feature database.

[0106] The preset regional characteristic database stores the climate and food culture data of each region, and the corresponding climate and food culture data can be searched through the geographical location information.

[0107] Based on the climate and food culture data of the region, a preset number of cooking method recommendation lists are generated through a pre-built large model.

[0108] A large model suitable for this step can be obtained by the same method based on the above embodiment, which will not be elaborated here. For example, by inputting the climate and food culture data of Hangzhou into the pre-built large model, a recommended cooking method list can be obtained. Since the display area of ​​the cooking equipment is limited, a preset number of recommended cooking method lists are generated according to the area of ​​the display area. The recommended cooking method list is, for example, "nutritional steaming, steaming, baking, wind baking, air frying".

[0109] Based on the above embodiment, the first nutrient component information and the second nutrient component information both include nutrient component type and nutrient component content, and a nutritional evaluation result is generated based on the first nutrient component information, the second nutrient component information and the target cooking parameters.

[0110] Step S2061: Obtain the reserved amount of the nutrient content corresponding to each nutrient type under the target cooking method.

[0111] In this step, a nutritional loss rate database of each nutrient under each cooking parameter is first constructed. In this nutritional loss rate database, the nutritional loss rate corresponding to each nutrient type under the target cooking parameters can be searched. Through the nutritional loss rate and the original nutrient content, the retained amount of the nutrient content after loss can be obtained.

[0112] Step S2062: Generate nutritional evaluation results based on the inventory.

[0113] In this step, the nutrition results can be graded, such as excellent, good, and poor. The more the retention amount, the higher the level of the nutrition evaluation result. Specifically, a nutrition retention amount threshold can be set for each nutrient type. If the nutrition retention amount threshold is exceeded, the nutrition evaluation result is excellent, otherwise it is good or poor.

[0114] Based on the above embodiment, determining whether to cook with target cooking parameters based on the nutritional evaluation result includes:

[0115] Step S207A1: Obtaining operation information for the nutrition evaluation result, where the operation information includes satisfactory operations and unsatisfactory operations.

[0116] The server sends the nutritional evaluation result to the cooking device and the mobile phone APP, which is displayed in the display area of ​​the cooking device or on the mobile phone APP. The user can click on the nutritional evaluation result, and a selection button will pop up on the interface. The selection buttons may be satisfied or dissatisfied. If satisfied is clicked, it indicates that the nutritional evaluation result is acceptable. If dissatisfied is clicked, the nutritional evaluation result is unacceptable.

[0117] Step S207A2: If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device so that the cooking device performs cooking according to the target cooking parameters.

[0118] Step S207A3: If the operation information is an unsatisfactory operation, adjust the target cooking parameters.

[0119] If the user is not satisfied with the current nutritional evaluation result, for example, the nutritional evaluation result is poor, the user can adjust the target cooking parameters in the key operation area of ​​the cooking device or the mobile phone APP, such as adjusting the cooking time through the time knob.

[0120] Step S207A4: Send the adjusted target cooking parameters to the cooking device, so that the cooking device performs cooking according to the adjusted target cooking parameters.

[0121] In another embodiment, determining whether to cook with target cooking parameters based on the nutritional evaluation result includes:

[0122] Step S207B1: Obtaining operation information for the nutrition evaluation result, the operation information includes satisfactory operations and unsatisfactory operations.

[0123] Step S207B2: If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device so that the cooking device performs cooking according to the target cooking parameters.

[0124] Step S207B3: If the operation information is an unsatisfactory operation, the target side dish in the side dish recommendation list is adjusted.

[0125] Step S207B4: reacquire the second nutritional component information of the adjusted target side dish.

[0126] Step S207B5: Regenerate the nutrition evaluation result and target cooking parameters based on the re-acquired second nutrition component information.

[0127] In this embodiment, the user can adjust the target side dishes on the cooking equipment or the mobile phone APP, and send the adjusted side dishes to the server. The server will regenerate the target cooking parameters and new nutritional evaluation results in the same way as the above embodiment, and let the user confirm again. If still not satisfied, he can adjust it again until satisfactory cooking parameters are selected.

[0128] Based on the same inventive concept, a cooking parameter determination device is provided, such as Figure 3 As shown, the device comprises:

[0129] The first acquisition unit 301 is used to acquire geographical location information of the cooking device and main ingredient information and first nutrient component information of the main ingredient to be cooked.

[0130] The first generating unit 302 is used to generate a side dish recommendation list based on the geographical location information, the main ingredient information and the first nutritional component information.

[0131] The second generating unit 303 is used to generate a cooking method recommendation list based on the geographical location information.

[0132] The second acquiring unit 304 is configured to acquire a target cooking method from the cooking method recommendation list.

[0133] The third obtaining unit 305 is used to obtain the second nutritional component information of the target side dish in the side dish recommendation list.

[0134] The third generating unit 306 is used to generate target cooking parameters based on the first nutrient component information, the second nutrient component information and the target cooking method.

[0135] The fourth generating unit 307 is used to generate a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameters.

[0136] The determination unit 308 is used to determine whether to cook with target cooking parameters based on the nutritional evaluation result.

[0137] Optionally, the acquisition unit is specifically used for:

[0138] Capturing images of the main food to be cooked by an image acquisition device;

[0139] Inputting the image of the main ingredient to be cooked into the pre-built large model for image recognition to obtain the main ingredient information, where the main ingredient at least includes the name of the main ingredient;

[0140] Based on the name of the main ingredient, first nutritional component information of the main ingredient to be cooked is searched in a preset ingredient nutrition database, where the first nutritional component information at least includes a nutritional component type and a nutritional component content.

[0141] Optionally, the first generating unit is specifically used for:

[0142] Generate a local recommended recipe list containing the main ingredients according to the main ingredient information and the geographical location information;

[0143] Obtain target recipes from the local recommended recipe list;

[0144] The other ingredients in the target recipe except the main ingredients are determined as side dishes, and a side dish recommendation list is generated.

[0145] Optionally, the second generating unit is specifically used for:

[0146] Based on the geographic location information, search for climate and food culture data of the user's region in a preset regional feature database;

[0147] Based on the climate and food culture data of the region, a preset number of cooking method recommendation lists are generated through a pre-built large model.

[0148] The first nutrient component information and the second nutrient component information both include nutrient component types and nutrient component contents. The fourth generating unit is specifically used for:

[0149] Obtaining the reserved amount of the nutrient content corresponding to each nutrient type under the target cooking parameters;

[0150] Generate nutritional evaluation results based on the inventory.

[0151] Optionally, the determining unit is specifically configured to:

[0152] Obtaining operation information for the nutrition evaluation results, including satisfactory operations and unsatisfactory operations;

[0153] If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters;

[0154] If the operation information is an unsatisfactory operation, the target cooking parameters are adjusted;

[0155] The adjusted target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the adjusted target cooking parameters.

[0156] Optionally, the determining unit is further configured to:

[0157] Obtaining operation information for the nutrition evaluation results, including satisfactory operations and unsatisfactory operations;

[0158] If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters;

[0159] If the operation information is an unsatisfactory operation, the target side dish in the side dish recommendation list is adjusted;

[0160] re-obtaining the adjusted second nutritional component information of the target side dish;

[0161] The nutrition evaluation result and the target cooking parameter are regenerated based on the reacquired second nutrition component information.

[0162] Based on the same technical concept, an embodiment of the present invention further provides an electronic device, such as Figure 4 As shown, it includes a processor 401 , a communication interface 402 , a memory 403 and a communication bus 404 , wherein the processor 401 , the communication interface 402 , and the memory 403 communicate with each other via the communication bus 404 .

[0163] Memory 403, used for storing computer programs;

[0164] The processor 401 is used to implement the steps of the cooking parameter determination method when executing the program stored in the memory 403.

[0165] The communication bus mentioned in the above electronic device can be a Peripheral Component Interconnect (PCI) bus or an Extended Industry Standard Architecture (EISA) bus, etc. The communication bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one thick line is used in the figure, but it does not mean that there is only one bus or one type of bus.

[0166] The communication interface is used for communication between the above electronic device and other devices.

[0167] The memory may include a random access memory (RAM) or a non-volatile memory (NVM), such as at least one disk memory. Optionally, the memory may also be at least one storage device located away from the aforementioned processor.

[0168] The above-mentioned processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components.

[0169] The computer program product for determining cooking parameters provided in the embodiment of the present invention includes a computer-readable storage medium storing program code. The instructions included in the program code can be used to execute the method described in the previous method embodiment. The specific implementation can be found in the method embodiment and will not be repeated here.

[0170] The cooking parameter determination device provided in the embodiment of the present invention may be specific hardware on the device or software or firmware installed on the device. The implementation principle and technical effects of the device provided in the embodiment of the present invention are the same as those of the aforementioned method embodiment. For the sake of brief description, for matters not mentioned in the device embodiment, reference may be made to the corresponding contents in the aforementioned method embodiment. Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working processes of the systems, devices and units described above can all refer to the corresponding processes in the aforementioned method embodiment, and will not be repeated here.

[0171] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0172] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple 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.

[0173] In addition, each functional unit in the embodiment provided by the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0174] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc., which can store program codes.

[0175] It should be noted that similar numbers and letters represent similar items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. In addition, the terms "first", "second", "third", etc. are only used to distinguish the description and are not to be understood as indicating or implying relative importance.

[0176] Finally, it should be noted that the above-described embodiments are only specific implementations of the present invention, which are used to illustrate the technical solutions of the present invention, rather than to limit them. The protection scope of the present invention is not limited thereto. Although the present invention is described in detail with reference to the above-described embodiments, those skilled in the art should understand that any person skilled in the art can still modify the technical solutions described in the above-described embodiments within the technical scope disclosed by the present invention, or can easily think of changes, or perform equivalent replacements on some of the technical features thereof; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention. They should all be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. A method for determining cooking parameters, characterized in that: The method comprises: Acquire geographic location information of the cooking device and main ingredient information and first nutrient component information of the main ingredient to be cooked; Generate a recommended list of side dishes based on the geographical location information, the main ingredient information and the first nutritional component information; generating a cooking method recommendation list based on the geographical location information, and acquiring a target cooking method from the cooking method recommendation list; Acquire second nutritional component information of a target side dish in the side dish recommendation list; generating target cooking parameters based on the first nutrient component information, the second nutrient component information and the target cooking method; generating a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameter; Based on the nutritional evaluation result, it is determined whether to cook with the target cooking parameters.

2. The method according to claim 1, characterized in that Obtaining the main ingredient information and the first nutritional component information of the main ingredient to be cooked includes: Capturing images of the main food to be cooked by an image acquisition device; Inputting the image of the main ingredient to be cooked into a pre-built large model for image recognition to obtain main ingredient information, wherein the main ingredient at least includes the name of the main ingredient; Based on the main ingredient name, first nutritional component information of the main ingredient to be cooked is searched in a preset ingredient nutrition database.

3. The method according to claim 1, characterized in that The generating of the side dish recommendation list based on the geographical location information, the main ingredient information and the first nutritional component information comprises: generating a local recommended recipe list containing the main ingredients according to the main ingredient information and the geographical location information; Acquire a target recipe from the local recommended recipe list; Ingredients other than the main ingredient in the target recipe are determined as side dishes, and a side dish recommendation list is generated.

4. The method according to claim 1, characterized in that: The generating of a cooking method recommendation list based on the geographical location information includes: Based on the geographical location information, searching for climate and food culture data of the user's region in a preset regional feature database; Based on the climate and food culture data of the region, a preset number of cooking method recommendation lists are generated through a pre-built large model.

5. The method according to claim 1, characterized in that The first nutrient component information and the second nutrient component information both include nutrient component types and nutrient component contents, and the nutrient evaluation result generated based on the first nutrient component information, the second nutrient component information and the target cooking method includes: Obtaining the reserved amount of the nutrient content corresponding to each nutrient type under the target cooking parameters; A nutritional evaluation result is generated based on the retained amount of the nutritional content corresponding to each nutritional type.

6. The method according to claim 1, characterized in that The determining whether to cook with the target cooking parameters based on the nutrition evaluation result includes: Acquiring operation information for the nutrition evaluation result, wherein the operation information includes satisfactory operations and unsatisfactory operations; If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters; If the operation information is an unsatisfactory operation, adjusting the target cooking parameter; The adjusted target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the adjusted target cooking parameters.

7. The method according to claim 1, characterized in that The determining whether to cook with the target cooking parameters based on the nutrition evaluation result includes: Acquiring operation information for the nutrition evaluation result, wherein the operation information includes satisfactory operations and unsatisfactory operations; If the operation information is a satisfactory operation, the target cooking parameters are sent to the cooking device, so that the cooking device performs cooking according to the target cooking parameters; If the operation information is an unsatisfactory operation, adjusting the target side dish in the side dish recommendation list; re-obtaining the adjusted second nutritional component information of the target side dish; The nutrition evaluation result and the target cooking parameter are regenerated based on the reacquired second nutrition component information.

8. A cooking parameter determination device, characterized in that: The device comprises: A first acquisition unit, used to acquire geographical location information of the cooking device and main ingredient information and first nutrient component information of the main ingredient to be cooked; A first generating unit, configured to generate a side dish recommendation list based on the geographical location information, the main ingredient information and the first nutritional component information; A second generating unit, configured to generate a cooking method recommendation list based on the geographical location information; a second acquiring unit, configured to acquire a target cooking method from the cooking method recommendation list; A third obtaining unit, configured to obtain second nutritional component information of a target side dish in the side dish recommendation list; a third generating unit, configured to generate a target cooking parameter based on the first nutrient component information, the second nutrient component information and the target cooking method; a fourth generating unit, configured to generate a nutrition evaluation result based on the first nutrition component information, the second nutrition component information and the target cooking parameter; A determination unit is used to determine whether to cook with the target cooking parameters based on the nutritional evaluation result.

9. An electronic device, characterized in that: It includes a processor, a communication interface, a memory and a communication bus, wherein the processor, the communication interface and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, for implementing the method steps described in any one of claims 1 to 7 when executing a program stored in a memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method steps described in any one of claims 1 to 7 are implemented.

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