System

Abstract

A system is provided.SOLUTION: A system comprising: means for inputting allergy information and like and dislike information by a user; means for inputting food materials that the user wants to use; means for inputting health limitation items by the user; means for acquiring corresponding information from a database including nutritional information based on the input information; means for using a AI engine for generating a cooking recipe based on the acquired information and the health limitation items; and means for presenting the generated cooking recipe and cooking procedure to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a system. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Preparing healthy meals is a huge burden for many people. In particular, people who lack culinary knowledge and skills have difficulty understanding what ingredients to choose and how to cook them to create healthy meals. This becomes even more complicated for people with allergies or specific nutritional restrictions. In addition, the time required to select ingredients and prepare them every day can be a major burden, often resulting in unhealthy eating habits. [Means for solving the problem]

[0005] The present invention provides a means for users to input allergy information, likes and dislikes, desired ingredients, and health restrictions. Based on this information, the system retrieves relevant information from a database containing nutritional information, and uses an AI engine to generate cooking recipes based on the retrieved information and health restrictions. It also provides a means for presenting the generated recipes and cooking instructions to the user. Furthermore, the system includes a means for evaluating nutritional balance based on the input information and health restrictions, and a means for checking whether the generated recipes meet calorie, fat, salt, and sugar restrictions, allowing users to easily prepare healthy meals.

[0006] "Allergy information" is information that indicates whether a user has an allergic reaction to a particular food or ingredient.

[0007] "Likes and dislikes information" is information that indicates the user's preferences for specific dishes or ingredients.

[0008] "Ingredients to Use" is a list of specific ingredients that the user wants to use in the dish.

[0009] "Health restriction items" are restrictions set by a user on specific nutrients (calories, fat, salt, sugar, etc.) in order to maintain their health.

[0010] A "database" is a system for storing and managing various data, including nutritional information.

[0011] "Nutrition information" refers to information about nutrients such as calories, fat, salt, and sugar contained in food ingredients.

[0012] A "cooking recipe" is a list of instructions and ingredients for a dish to be made using specific ingredients.

[0013] An "AI engine" refers to an artificial intelligence algorithm that analyzes input information and achieves a specific purpose (in this case, generating cooking recipes).

[0014] "Cooking instructions" describe the specific steps and methods for preparing a dish.

[0015] "Evaluation of nutritional balance" refers to determining whether the nutritional content of the dish to be created is healthy based on the input ingredients and restrictions. [Brief explanation of the drawings]

[0016] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0017] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

[0018] First, the terms used in the following description will be explained.

[0019] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0020] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0021] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0022] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0023] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0024] [First embodiment]

[0025] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0026] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0027] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0028] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0029] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0030] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0031] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0032] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0033] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0034] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0035] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0036] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0037] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user on a terminal on a server, and generates recipes using an AI engine.

[0038] System configuration

[0039] 1. User Interface (UI)

[0040] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0041] Basic information: User's allergies, likes and dislikes.

[0042] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0043] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0044] 2. Database

[0045] The server manages an ingredient database and a recipe database.

[0046] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0047] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0048] 3. AI Engine

[0049] The server uses the input information to generate recipes that meet the specified health restrictions using an AI engine that pulls nutritional information from a database to find the optimal combination.

[0050] Program processing

[0051] 1. Enter basic user information

[0052] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[0053] Server: Receives the basic information sent and stores it in a database as a user profile.

[0054] 2. Enter ingredients used

[0055] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[0056] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[0057] 3. Enter health restrictions

[0058] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[0059] Server: Receives the entered health restrictions and stores them in association with the user profile.

[0060] 4. Recipe Generation

[0061] Server: Calls the recipe generation algorithm based on the acquired ingredient information, user profile, and health restrictions. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[0062] AI engine: Evaluates the nutritional balance of the generated recipes and ensures that the calorie and salt content does not exceed the specified limits. It repeats the process of generating and evaluating recipes until it finds a recipe that meets the specified limits.

[0063] 5. Display results

[0064] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[0065] User: Check the recipe and cooking instructions sent from the server through the device UI.

[0066] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[0067] 1. Cut the lettuce into bite-sized pieces.

[0068] 2. Thinly slice the tomatoes and cucumbers.

[0069] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0070] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0071] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[0072] The processing flow will be explained below.

[0073] Step 1:

[0074] The user enters basic information (allergies, likes and dislikes).

[0075] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[0076] Step 2:

[0077] The device sends basic information to the server.

[0078] The terminal transmits the input basic information to the server.

[0079] Step 3:

[0080] The server stores the user profile.

[0081] The server stores the received basic information in a database and manages it as a user profile.

[0082] Step 4:

[0083] The user inputs the ingredients to be used.

[0084] The user enters the ingredients they want to use this time into an input form on the terminal.

[0085] Step 5:

[0086] The terminal transmits information about ingredients used to the server.

[0087] The terminal transmits the input ingredient information to the server.

[0088] Step 6:

[0089] The server acquires the ingredient data.

[0090] The server retrieves the nutritional information of the specified foodstuff from the database.

[0091] Step 7:

[0092] The user inputs health restrictions.

[0093] Users input the health items they want to consider or restrict (calorie limits, salt, sugar, fat restrictions, etc.) into the device.

[0094] Step 8:

[0095] The device sends the health restriction items to the server.

[0096] The terminal transmits the entered health items to the server.

[0097] Step 9:

[0098] The server stores the health restriction conditions.

[0099] The server stores the received health restriction conditions in association with the user profile.

[0100] Step 10:

[0101] The server invokes the recipe generation algorithm.

[0102] The server starts the AI ​​engine by inputting information on ingredients, health restrictions, and user profile.

[0103] Step 11:

[0104] The AI ​​engine generates the appropriate recipe.

[0105] The AI ​​engine analyzes the input data and generates a recipe that meets the conditions.

[0106] Step 12:

[0107] The server checks the recipe for suitability.

[0108] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[0109] Step 13:

[0110] The server sends the generated recipe to the device.

[0111] The server sends the matching recipe and cooking instructions to the user terminal.

[0112] Step 14:

[0113] The user checks the results.

[0114] The user checks the recipe and cooking instructions presented on the terminal.

[0115] Step 15:

[0116] The user starts cooking.

[0117] The user follows the instructions to start cooking.

[0118] Example 1

[0119] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0120] In modern society, there is a demand for easy and fast provision of cooking recipes that suit individual health conditions and preferences. In particular, it has been difficult for conventional systems to automatically generate recipes that accommodate allergies and health restrictions (e.g., restrictions on calories, salt, sugar, and fat) and evaluate the nutritional balance of those recipes. Therefore, there is a need for a system that allows users to easily select dishes that suit their preferences while taking their health conditions into consideration.

[0121] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0122] In this invention, the server includes: means for a user to input allergy information and likes and dislikes; means for a user to input ingredients that the user wants to use; means for a user to input health restrictions; means for retrieving relevant information from a database containing nutritional information based on the input information; means for using an AI engine to generate cooking recipes based on the retrieved information and health restrictions; means for evaluating the nutritional balance of the generated cooking recipes and repeating the generation and evaluation of recipes until a recipe that meets the specified restrictions is found; and means for presenting the generated cooking recipes and cooking procedures to the user. This allows users to quickly and easily obtain recipes that meet their allergies and health restrictions.

[0123] A "user" is an individual who uses the system to obtain cooking recipes.

[0124] "Allergy information" refers to information about whether a user has an allergic reaction to a particular food.

[0125] "Likes and dislikes information" refers to information about the dishes that the user likes and dislikes.

[0126] An "ingredient" is a specific food that a user wishes to use.

[0127] "Health restriction items" refer to conditions related to upper limits on calories, salt, sugar, fat, and other nutritional restrictions that are set with the user's health in mind.

[0128] "Nutrition information" refers to information about the nutritional components of food ingredients, such as calories, fat, salt, and sugar.

[0129] A "database" is an information system for storing ingredients, recipes, and their nutritional information.

[0130] An "AI engine" is an artificial intelligence that generates cooking recipes that meet the conditions based on input information and evaluates nutritional balance.

[0131] A "recipe generation algorithm" is a computational method used by an AI engine to find the optimal recipe based on input information.

[0132] "Cooking steps" refer to the specific cooking steps required to complete the generated cooking recipe.

[0133] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user using a terminal on a server, and generates recipes using an AI engine. Specific embodiments for implementing this system are described below.

[0134] System Configuration

[0135] 1. User Interface (UI)

[0136] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0137] Allergy information: For example, peanut allergy.

[0138] Likes and dislikes: For example, your favorite food is salad, and you don't have any disliked food.

[0139] Ingredients: A list of ingredients you would like to use, for example, lettuce, tomato, cucumber, chicken breast, etc.

[0140] Health restrictions: For example, calorie limit of 300 kcal, salt limit of 1g, etc.

[0141] 2. Database

[0142] The server manages an ingredient database and a recipe database.

[0143] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0144] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0145] 3. AI Engine

[0146] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine retrieves nutritional information from a database and finds the optimal combination. It also evaluates the nutritional balance of the generated recipes to ensure that the calorie and salt content does not exceed the specified upper limit. Recipe generation and evaluation are repeated until a recipe that meets the specified restrictions is found.

[0147] Specific examples

[0148] For example, you can enter:

[0149] Allergy Information: Peanut Allergy

[0150] Likes and dislikes: Favorite food is salad, dislikes nothing

[0151] Ingredients: lettuce, tomato, cucumber, chicken breast

[0152] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[0153] Based on that, the following recipe is generated:

[0154] Recipe Name: Healthy Grilled Chicken Salad

[0155] Cooking Instructions:

[0156] 1. Cut the lettuce into bite-sized pieces.

[0157] 2. Thinly slice the tomatoes and cucumbers.

[0158] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0159] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0160] This process allows users to quickly and easily find recipes that accommodate their allergies and health restrictions, allowing them to enjoy food that suits their tastes while maintaining their health.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Step 1:

[0163] The user enters allergy information and likes and dislikes.

[0164] Specific operation: The user enters their allergy information (e.g., peanut allergy) and favorite food information (e.g., favorite food is salad, no disliked food) into the device's UI. The entered information is sent from the device to the server.

[0165] Input: Allergy information and food preferences

[0166] Output: User information sent to the server

[0167] Step 2:

[0168] The user inputs the ingredients they want to use.

[0169] Specific operation: The user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast) into the device's UI. The input information is sent from the device to the server.

[0170] Input: List of ingredients you want to use

[0171] Output: Ingredient information sent to the server

[0172] Step 3:

[0173] The user inputs health restrictions.

[0174] Specific operation: The user inputs health restrictions (e.g., calorie limit 300 kcal, salt intake 1g or less) into the device's UI. The input information is sent from the device to the server.

[0175] Input: Health Restrictions

[0176] Output: Health restrictions sent to the server

[0177] Step 4:

[0178] The server retrieves nutritional information from a database based on the transmitted information.

[0179] Specific operation: The server receives the user's allergy information, preference information, ingredient list, and health restrictions, and retrieves the nutritional information for each ingredient from the ingredient database.

[0180] Input: User information, food ingredients, and health restrictions sent to the server

[0181] Output: Nutritional information of the ingredients obtained

[0182] Step 5:

[0183] The server uses an AI engine to generate cooking recipes based on the acquired information and health restrictions.

[0184] Specific operation: The server launches an AI engine to generate suitable recipes based on the acquired nutritional information and health restrictions. The AI ​​engine uses a recipe generation algorithm to find the optimal combination. It repeats the process of generating and evaluating recipes until it finds one that meets the specified restrictions.

[0185] Input: Obtained nutritional information, health restrictions

[0186] Output: The generated recipe

[0187] Step 6:

[0188] The server presents the generated recipe and cooking instructions to the user.

[0189] Specific operation: The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device. The user can view the recipe and instructions through the device's UI.

[0190] Input: Generated recipe

[0191] Output: Recipe and cooking instructions displayed on the user's device

[0192] This series of steps allows users to easily obtain recipes that take into consideration their allergies and health restrictions.

[0193] (Application example 1)

[0194] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0195] In modern society, many people want to enjoy healthy meals, but at the same time, maintaining a balanced diet in a busy lifestyle can be difficult. Finding appropriate recipes can be especially challenging for people with allergies or health restrictions. Furthermore, many users want simple, healthy meals using specific ingredients, but there is a lack of systems that can meet these needs.

[0196] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0197] In this invention, the server includes a means for the user to input allergy information and likes and dislikes, a means for the user to input ingredients the user wants to use, and a means for the user to input health restriction items. This makes it possible to suggest healthy, nutritionally balanced dishes through an application installed on a smartphone that uses the information input by the user to suggest health-conscious recipes.

[0198] The "means for the user to input information about allergies and likes and dislikes" is an interface that allows the user to input information about his or her own allergies, preferences, and disliked foods.

[0199] The "means for inputting ingredients that the user wants to use" is an interface that allows the user to input the specific ingredients that the user wants to use in the current dish.

[0200] The "means for the user to input health restrictions" is an interface that allows the user to input health-related restrictions such as calorie limits, salt, sugar, and fat.

[0201] The "means for obtaining corresponding information from a database containing nutritional information based on the input information" is a program for analyzing the information input by the user and obtaining corresponding information from a database containing nutritional information.

[0202] "Means for using an AI engine to generate cooking recipes based on the acquired information and health restrictions" refers to a program that uses an artificial intelligence engine to generate optimal cooking recipes based on nutritional information and health restrictions acquired from a database.

[0203] The "means for presenting the generated recipe and cooking steps to the user" is an interface for displaying the recipe and cooking steps generated by the AI ​​engine to the user.

[0204] "Means that operate as an application installed on a smartphone and use information entered by the user to suggest healthy recipes" refers to an application that operates on a smartphone to suggest healthy recipes using information entered by the user.

[0205] This invention provides a system that generates healthy recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. The system includes a user interface, a database, an AI engine, and a means for displaying the results.

[0206] 1. User Interface (UI)

[0207] Users can enter the following information through a smartphone application:

[0208] Basic information: User's allergies, likes and dislikes.

[0209] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0210] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0211] 2. Database

[0212] The server manages a database containing nutritional information:

[0213] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0214] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0215] 3. AI Engine

[0216] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine is configured using the following software and tools:

[0217] AI engine: TensorFlow or PyTorch

[0218] API server: Django (server-side API management)

[0219] 4. Results display

[0220] The generated recipes and cooking instructions are displayed to the user through a smartphone application. The user can easily create dishes that meet health restrictions based on the provided recipes. The results are displayed by the following means:

[0221] Specific examples

[0222] For example, if a user enters the following information:

[0223] Allergy Information: Peanut Allergy

[0224] Likes and dislikes: Favorite food is salad, dislikes nothing

[0225] Ingredients: lettuce, tomato, cucumber, chicken breast

[0226] Health restrictions: Calorie limit 300 kcal, salt limit 1g or less

[0227] Using this information, the AI ​​engine generates a recipe for a "Healthy Grilled Chicken Salad" and displays it on the user's smartphone along with cooking instructions. Specifically, the following steps are presented:

[0228] 1. Cut the lettuce into bite-sized pieces.

[0229] 2. Thinly slice the tomatoes and cucumbers.

[0230] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0231] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0232] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[0233] Example prompts to input to the generative AI model

[0234] User Allergy Information: Peanut Allergy

[0235] Likes and dislikes: Favorite food is salad, dislikes nothing

[0236] Ingredients: lettuce, tomato, cucumber, chicken breast

[0237] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[0238] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0239] Step 1:

[0240] Users use a smartphone application to input their allergy information and likes and dislikes. The input basic information is sent by the device to a server and stored in a database on the server. The basic information includes peanut allergies, favorite dishes (e.g., salad), and disliked dishes (e.g., none). This information is stored in the database as a user profile.

[0241] Step 2:

[0242] Users input the ingredients they want to use through a smartphone application. The input ingredients are sent to the server via the device, and nutritional information about the ingredients is retrieved from the ingredient database. For example, if lettuce, tomato, cucumber, and chicken breast are input as ingredients, detailed nutritional information about these ingredients, such as calories, fat, salt, and sugar, is retrieved. This information becomes the basic data for recipe generation by the AI ​​engine.

[0243] Step 3:

[0244] Users input their health restrictions via a smartphone application. The entered health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less) are sent to the server via the device, associated with the user profile, and stored in a database. This data is used as a restriction that the AI ​​engine takes into account when generating recipes.

[0245] Step 4:

[0246] The AI ​​engine generates optimal cooking recipes based on basic information stored on the server, nutritional information for ingredients used, and health restrictions. The server passes input data to the AI ​​engine, which analyzes this information and generates recipes that fit the conditions. For example, a recipe for "Healthy Grilled Chicken Salad" using lettuce, tomato, cucumber, and chicken breast is generated. Machine learning engines such as TensorFlow or PyTorch are used in this process.

[0247] Step 5:

[0248] The server sends the generated recipe and cooking instructions to the device. The user can then view the recipe and cooking instructions sent from the server through a smartphone application. For example, for "Healthy Grilled Chicken Salad," the following steps are displayed:

[0249] 1. Cut the lettuce into bite-sized pieces.

[0250] 2. Thinly slice the tomatoes and cucumbers.

[0251] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0252] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0253] In this way, users can easily prepare healthy meals.

[0254] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0255] This invention is a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments of this system are described below.

[0256] System configuration

[0257] 1. User Interface (UI)

[0258] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0259] Basic information: User's allergies, likes and dislikes.

[0260] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0261] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0262] Emotion information: Recognizes user emotions using an emotion engine.

[0263] 2. Database

[0264] The server manages an ingredient database and a recipe database.

[0265] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0266] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0267] 3. AI Engine and Emotion Engine

[0268] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[0269] Program processing

[0270] 1. Enter basic user information

[0271] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[0272] Server: Receives the basic information sent and stores it in a database as a user profile.

[0273] 2. Enter ingredients used

[0274] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[0275] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[0276] 3. Enter health restrictions

[0277] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[0278] Server: Receives the entered health restrictions and stores them in association with the user profile.

[0279] 4. Acquiring emotional information

[0280] Emotion engine: Recognizes user emotions in real time based on facial recognition, voice, gestures, etc.

[0281] Server: Receives the recognized emotion information and passes it to the AI ​​engine.

[0282] 5. Recipe Generation

[0283] Server: Calls the recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[0284] AI Engine: Adjusts recipe variations and suggestions based on emotional information from the Emotion Engine. It also evaluates the nutritional balance of generated recipes to ensure that calorie and salt content do not exceed specified limits. It repeats recipe generation and evaluation until it finds a recipe that meets the specified constraints.

[0285] 6. Results display

[0286] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[0287] User: Check the recipe and cooking instructions sent from the server through the device UI.

[0288] Specific examples

[0289] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[0290] 1. Cut the lettuce into bite-sized pieces.

[0291] 2. Thinly slice the tomatoes and cucumbers.

[0292] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0293] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0294] In this way, users can easily prepare healthy meals that take emotional information into account. Furthermore, recipes that take into account restrictions on calories and salt content are provided, helping users maintain their health. Taking emotional information into account allows recipes that suit the user's preferences to be suggested, improving cooking satisfaction.

[0295] The processing flow will be explained below.

[0296] Step 1:

[0297] The user enters basic information (allergies, likes and dislikes).

[0298] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[0299] Step 2:

[0300] The device sends basic information to the server.

[0301] The terminal transmits the input basic information to the server.

[0302] Step 3:

[0303] The server stores the user profile.

[0304] The server stores the received basic information in a database and manages it as a user profile.

[0305] Step 4:

[0306] The user inputs the ingredients to be used.

[0307] The user enters the ingredients they want to use this time into an input form on the terminal.

[0308] Step 5:

[0309] The terminal transmits information about ingredients used to the server.

[0310] The terminal transmits the input ingredient information to the server.

[0311] Step 6:

[0312] The server acquires the ingredient data.

[0313] The server retrieves the nutritional information of the specified foodstuff from the database.

[0314] Step 7:

[0315] The user inputs health restrictions.

[0316] Users input the health items they want to consider or limit (e.g., calorie limit 300 kcal, salt less than 1g) on ​​their device.

[0317] Step 8:

[0318] The device sends the health restriction items to the server.

[0319] The terminal transmits the entered health items to the server.

[0320] Step 9:

[0321] The server stores the health restriction conditions.

[0322] The server stores the received health restriction conditions in association with the user profile.

[0323] Step 10:

[0324] The emotion engine acquires emotion information.

[0325] The emotion engine uses facial recognition, voice, and gestures to recognize the user's emotions.

[0326] Step 11:

[0327] The device transmits the emotion information to the server.

[0328] The terminal transmits the acquired emotion information to the server.

[0329] Step 12:

[0330] The server invokes the recipe generation algorithm.

[0331] The server inputs ingredients, health restrictions, user profile, and emotional information into the AI ​​engine.

[0332] Step 13:

[0333] The AI ​​engine generates the appropriate recipe.

[0334] The AI ​​engine analyzes the input information and generates a recipe that meets the conditions and emotional information.

[0335] Step 14:

[0336] The server checks the recipe for suitability.

[0337] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[0338] Step 15:

[0339] The server sends the generated recipe to the device.

[0340] The server sends the matching recipe and cooking instructions to the user terminal.

[0341] Step 16:

[0342] The user checks the results.

[0343] The user checks the recipe and cooking instructions presented on the terminal.

[0344] Step 17:

[0345] The user starts cooking.

[0346] The user follows the instructions to start cooking.

[0347] Example 2

[0348] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0349] Conventional recipe generation systems only generate recipes by taking into account the user's allergies, likes and dislikes, and health restrictions. However, because they do not take into account the user's emotional information, there is a problem in that the satisfaction of the food is not sufficiently improved. Furthermore, even when generating recipes that take into account individual health, it is not possible to reflect emotional information.

[0350] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0351] In this invention, the server includes means for the user to input allergy information and likes and dislikes, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for acquiring the user's emotional information using an emotion engine, means for acquiring relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the acquired information, health restriction items, and emotional information, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate healthy cooking recipes that are individually tailored to the user's emotional information and provide a high level of satisfaction.

[0352] "Allergy information" is information indicating that a user has an allergic reaction to a specific food ingredient or component.

[0353] "Likes and dislikes information" is information about ingredients and dishes that the user likes and dislikes.

[0354] "Ingredients" is a list of ingredients used to make a dish.

[0355] "Health restriction items" are restriction conditions such as calories, salt, fat, sugar, etc., set according to the user's health condition.

[0356] An "emotion engine" is a system that recognizes emotions from a user's facial expressions, voice, gestures, etc.

[0357] "Nutrition information" refers to information about the calorie, fat, salt, sugar, and other contents of a particular food ingredient.

[0358] A "database" is a digital system for systematically organizing and storing information.

[0359] A "recipe generation algorithm" is a program that refers to the steps to create an optimal cooking recipe based on input information.

[0360] An "AI engine" is an artificial intelligence system used to analyze input information and achieve a specific purpose (in this case, generating cooking recipes).

[0361] A "cooking recipe" is a list of specific steps to follow when preparing a dish.

[0362] A "recipe" is information that includes a set of ingredients and instructions for combining them to make a dish.

[0363] "User interface (UI)" refers to the screens and input devices that allow a user to interact with a system.

[0364] A "server" is a computer system that processes information and provides services to other computers and devices over a network.

[0365] "Terminal" refers to a device such as a computer, smartphone, or tablet that is directly operated by a user.

[0366] The present invention provides a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments for carrying out the present invention will be described below.

[0367] User Interface

[0368] Users enter the following information using a device such as a smartphone, tablet, or PC:

[0369] Basic information: Allergy information, likes and dislikes

[0370] Ingredients: A list of the specific ingredients you would like to use.

[0371] Health restrictions: Calorie limits, salt, sugar, and fat restrictions

[0372] Emotion information: Emotion information recognized by the emotion engine

[0373] Database

[0374] The server manages the following databases:

[0375] Ingredient database: detailed nutritional information for each ingredient

[0376] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[0377] AI engine and emotion engine

[0378] The server generates recipes based on the information provided by the user using the following engines:

[0379] AI engine: Extracts nutritional information from a database and finds optimal combinations

[0380] Emotion engine: Recognizes user emotions through facial recognition, voice, gestures, etc., and reflects them in recipe generation

[0381] Example of a system

[0382] Specific processing flow

[0383] The user uses the device's UI to input that they are allergic to peanuts and that they like salads. The device sends this information to the server, which stores the received information in a database and creates a user profile.

[0384] Next, the user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast). The terminal sends this information to the server, which then retrieves the nutritional information for each ingredient from the ingredient database.

[0385] Furthermore, the user inputs health restrictions (calorie limit 300 kcal, salt limit 1 g or less). When the device sends this information to the server, the server associates the received restrictions with the user profile and saves them.

[0386] The emotion engine recognizes the user's emotions in real time from facial recognition, voice, and gestures, and sends the information to the server, which then passes it on to the AI ​​engine.

[0387] The server calls a recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates optimal recipes while taking emotional information into account. It evaluates nutritional balance and adjusts calorie and salt content so that they do not exceed specified limits.

[0388] The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device, where the user can view the cooking instructions through the device's UI.

[0389] Examples and prompts

[0390] For example, the generated recipe for "Healthy Grilled Chicken Salad" includes the following steps:

[0391] 1. Cut the lettuce into bite-sized pieces

[0392] 2. Thinly slice the tomatoes and cucumbers

[0393] 3. Grill the chicken breasts and cut them into bite-sized pieces.

[0394] 4. Mix lemon juice with a little olive oil to make a dressing and pour it over the salad.

[0395] Examples of prompts include:

[0396] "I'd like a healthy recipe. I would like to use lettuce, tomato, cucumber, and chicken breast. Calories should be under 300 kcal and salt should be under 1g."

[0397] This system allows users to easily prepare healthy meals that take emotional information into account, thus providing recipes tailored to individual health and emotional states, improving user satisfaction.

[0398] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0399] Step 1:

[0400] The user inputs allergy information and likes and dislikes using the device's UI. Specifically, the user inputs that they have a peanut allergy and that their favorite dish is salad. The device then sends the input information to the server.

[0401] Input: Allergy information (peanuts) and likes and dislikes (likes: salad)

[0402] Data processing: Formatting information and sending it to the server

[0403] Output: User profile stored on the server

[0404] Step 2:

[0405] The server stores the received basic information in a database. After receiving the information, it stores it in the database as a user profile.

[0406] Input: Basic information sent from the device

[0407] Data processing: Convert the information into a storage format and save it in a database

[0408] Output: Saved user profile (peanut allergy, favorite food is salad)

[0409] Step 3:

[0410] The user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast) through the device's UI. The device then sends this ingredient information to the server.

[0411] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[0412] Data processing: Formatting information and sending it to the server

[0413] Output: Ingredient information is sent to the server

[0414] Step 4:

[0415] The server acquires corresponding nutrition information from the ingredient database based on the input ingredient information.

[0416] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[0417] Data processing: Search and obtain corresponding nutritional information from food ingredient database

[0418] Output: Retrieved nutrition information (lettuce: 5 kcal, tomato: 18 kcal, cucumber: 16 kcal, chicken breast: 165 kcal)

[0419] Step 5:

[0420] The user inputs health restriction items (e.g., calorie limit 300 kcal, salt intake 1 g or less) through the device's UI. The device then sends this information to the server.

[0421] Input: Health restriction items (calorie limit 300 kcal, salt less than 1g)

[0422] Data processing: Formatting information and sending it to the server

[0423] Output: Health restrictions are sent to the server

[0424] Step 6:

[0425] The server receives the entered health restriction items and stores them in association with the user profile.

[0426] Input: Health restriction items (calories 300 kcal or less, salt 1g or less)

[0427] Data processing: Information is associated with user profiles and stored in a database

[0428] Output: Health restrictions saved in association with the user profile

[0429] Step 7:

[0430] The emotion engine recognizes emotions in real time from the user's facial recognition, voice, and gestures, and sends that information to the server.

[0431] Input: User's facial expressions, voice, and gestures

[0432] Data processing: Acquire emotional information through facial recognition, voice analysis, and gesture analysis

[0433] Output: Emotional information obtained (e.g., joy)

[0434] Step 8:

[0435] The server receives the emotional information and passes it to the AI ​​engine, which then generates recipes taking the emotional information into account.

[0436] Input: Emotional information, food information, health restrictions, user profile

[0437] Data processing: Execute recipe generation algorithm taking into account emotional information

[0438] Output: Generated recipe and cooking instructions

[0439] Step 9:

[0440] The server transmits the generated recipe and its cooking steps to the terminal.

[0441] Input: Generated recipe and cooking instructions

[0442] Data processing: Converting information into a format that can be sent to the user's device

[0443] Output: Recipe and cooking instructions sent to device

[0444] Step 10:

[0445] The user can view the recipe and cooking instructions sent to them through the device's UI, including instructions to cut the lettuce into bite-sized pieces, thinly slice the tomatoes and cucumbers, and grill and cut the chicken breasts into bite-sized pieces.

[0446] Input: Recipe and cooking instructions sent from the server

[0447] Output: Check the recipe and cooking instructions displayed on your device

[0448] (Application example 2)

[0449] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0450] Conventional recipe generation systems generate recipes based on the user's health restrictions and desired ingredient information, but they are unable to take into account the user's current emotional state. This makes it difficult to provide recipes that perfectly match the user's preferences, resulting in low satisfaction.

[0451] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input allergy information and likes and dislikes information, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for retrieving relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the retrieved information and health restriction items, means for recognizing user emotional information in real time, means for reflecting the recognized emotional information in recipe generation, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate health-conscious cooking recipes that reflect the user's emotional state, thereby improving user satisfaction.

[0452] The "means for the user to input information about allergies and likes and dislikes" is an interface through which the user inputs information about his or her own allergies and preferences.

[0453] The "means for inputting ingredients that the user wants to use" is an interface through which the user inputs information about ingredients that the user plans to use in the dish.

[0454] The "means for the user to input health restriction items" is an interface through which the user inputs information about health restrictions such as calories and salt content.

[0455] The "means for retrieving relevant information from a database containing nutritional information" is a function for retrieving information that matches the conditions entered by the user from a database that stores nutritional information.

[0456] "Means for using an AI engine to generate cooking recipes" refers to an algorithm that generates optimal cooking recipes based on information entered by the user.

[0457] "Means for recognizing the user's emotional information in real time" is a function that determines the user's emotional state from their facial expressions and tone of voice.

[0458] The "means for reflecting recognized emotional information in recipe generation" is a function that adjusts recipe suggestions taking into account the user's emotional state.

[0459] The "means for presenting the generated recipe and cooking steps to the user" is an interface that displays the finally generated recipe and cooking steps to the user.

[0460] The present invention provides a system for generating healthy cooking recipes that take into account the emotional information of a user. Specific embodiments of this system will be described below.

[0461] System configuration

[0462] 1. User Interface (UI)

[0463] The user enters the following information through the UI of the device (smartphone, tablet, PC, etc.):

[0464] Allergy information (e.g., peanut allergy)

[0465] Likes and dislikes (e.g., favorite food is salad, no dislikes)

[0466] A list of ingredients you would like to use (e.g. lettuce, tomato, cucumber, chicken breast)

[0467] Health restrictions (e.g., calorie limit 300 kcal, salt limit 1g or less)

[0468] 2. Database

[0469] The server manages a database that stores the following information:

[0470] Food database: Detailed nutritional information for each food ingredient (calories, fat, salt, sugar, etc.)

[0471] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[0472] 3. AI Engine and Emotion Engine

[0473] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[0474] Specific examples of hardware and software used

[0475] Smart glasses: Used by field staff to scan customers' faces and obtain emotional information in real time.

[0476] Flask: A lightweight Python-based web application framework that acts as a server and receives user data and facial information.

[0477] OpenCV: A computer vision library, used for face recognition.

[0478] Keras: A deep learning library used to build emotion recognition models.

[0479] Data Processing and Computation

[0480] 1. Face Recognition: The smart glasses capture the customer's face, and then use OpenCV to detect the face and Keras models to recognize emotions.

[0481] 2. Emotion Recognition: Captured facial images are fed into a deep learning model to determine the emotional state.

[0482] 3. Recipe generation: The AI ​​engine generates optimal recipes based on the user's health restrictions and perceived emotions.

[0483] Examples and prompts

[0484] To illustrate, consider the following scenario in a cafe:

[0485] A cafe staff member wears smart glasses and says to the customer, "Hello, are you looking for today's specials?" The smart glasses capture the customer's facial expressions, which are then analyzed by an emotion engine. For example, if the customer expresses the emotion "happy," the Smart Healthy Cafe Assistant will suggest "marinated salmon." This recipe also takes into account the customer's health restrictions (e.g., a calorie limit of 300 kcal).

[0486] Example prompt sentence:

[0487] "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts"

[0488] In this way, a recipe suggestion system that takes emotional information into account improves customer satisfaction.

[0489] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0490] Step 1:

[0491] The user uses the device's user interface (UI) to input their allergy information, likes and dislikes, ingredients they want to use, and health restrictions. This input information is sent from the device to the server, which then packages the information in JSON or other appropriate format and sends it to the server.

[0492] Step 2:

[0493] The server receives user input information sent from the device. The received information is analyzed and information such as allergies, likes and dislikes, ingredients desired to use, and health restrictions is sorted into appropriate fields. This information is then saved in a database as a user profile.

[0494] Step 3:

[0495] The server retrieves the corresponding nutritional information from the ingredient database based on the information about the ingredients the user wants to use. Specifically, nutritional information such as calories, fat, salt, and sugar for lettuce, tomato, cucumber, and chicken breast is retrieved from the database. This completes the available information.

[0496] Step 4:

[0497] The server receives the user's health restriction information and associates it with the user profile. For example, if restrictions are set such as "calorie limit 300 kcal, salt intake 1g or less," this information is added to the user profile. Subsequent data processing is based on this information.

[0498] Step 5:

[0499] The server uses an emotion engine to recognize real-time user emotion information obtained from smart glasses, etc. The emotion engine analyzes the user's facial expressions, voice, gestures, etc., and recognizes whether the user is in an emotional state such as "happy," "sad," or "neutral." This emotion information is then sent to the server.

[0500] Step 6:

[0501] The server uses an AI engine to generate optimal cooking recipes based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions. It also incorporates emotional information from the emotional engine to suggest recipes that suit the user's emotional state. The generated recipes are also evaluated to see if they meet calorie and salt restrictions.

[0502] Step 7:

[0503] The server sends the successfully generated recipe and its cooking instructions to the device. For example, if a recipe for a healthy grilled chicken salad is generated, the server presents the user with information including the specific cooking instructions (e.g., cut the lettuce into bite-sized pieces, thinly slice the tomato and cucumber, etc.). The user can confirm this information through the device's UI.

[0504] Specific examples of operation

[0505] As an example of a prompt, if "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts" is entered, the server will pass the image file to the emotion engine, determine the user's emotional state as "happy," and then generate an appropriate recipe such as "marinated salmon," taking into account sugar and salt restrictions and presenting the final recipe.

[0506] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0507] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0508] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0509] [Second embodiment]

[0510] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0511] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0512] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0513] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0514] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0515] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0516] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0517] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0518] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0519] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0520] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0521] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0522] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user on a terminal on a server, and generates recipes using an AI engine.

[0523] System configuration

[0524] 1. User Interface (UI)

[0525] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0526] Basic information: User's allergies, likes and dislikes.

[0527] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0528] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0529] 2. Database

[0530] The server manages an ingredient database and a recipe database.

[0531] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0532] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0533] 3. AI Engine

[0534] The server uses the input information to generate recipes that meet the specified health restrictions using an AI engine that pulls nutritional information from a database to find the optimal combination.

[0535] Program processing

[0536] 1. Enter basic user information

[0537] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[0538] Server: Receives the basic information sent and stores it in a database as a user profile.

[0539] 2. Enter ingredients used

[0540] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[0541] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[0542] 3. Enter health restrictions

[0543] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[0544] Server: Receives the entered health restrictions and stores them in association with the user profile.

[0545] 4. Recipe Generation

[0546] Server: Calls the recipe generation algorithm based on the acquired ingredient information, user profile, and health restrictions. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[0547] AI engine: Evaluates the nutritional balance of the generated recipes and ensures that the calorie and salt content does not exceed the specified limits. It repeats the process of generating and evaluating recipes until it finds a recipe that meets the specified limits.

[0548] 5. Display results

[0549] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[0550] User: Check the recipe and cooking instructions sent from the server through the device UI.

[0551] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[0552] 1. Cut the lettuce into bite-sized pieces.

[0553] 2. Thinly slice the tomatoes and cucumbers.

[0554] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0555] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0556] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[0557] The processing flow will be explained below.

[0558] Step 1:

[0559] The user enters basic information (allergies, likes and dislikes).

[0560] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[0561] Step 2:

[0562] The device sends basic information to the server.

[0563] The terminal transmits the input basic information to the server.

[0564] Step 3:

[0565] The server stores the user profile.

[0566] The server stores the received basic information in a database and manages it as a user profile.

[0567] Step 4:

[0568] The user inputs the ingredients to be used.

[0569] The user enters the ingredients they want to use this time into an input form on the terminal.

[0570] Step 5:

[0571] The terminal transmits information about ingredients used to the server.

[0572] The terminal transmits the input ingredient information to the server.

[0573] Step 6:

[0574] The server acquires the ingredient data.

[0575] The server retrieves the nutritional information of the specified foodstuff from the database.

[0576] Step 7:

[0577] The user inputs health restrictions.

[0578] Users input the health items they want to consider or restrict (calorie limits, salt, sugar, fat restrictions, etc.) into the device.

[0579] Step 8:

[0580] The device sends the health restriction items to the server.

[0581] The terminal transmits the entered health items to the server.

[0582] Step 9:

[0583] The server stores the health restriction conditions.

[0584] The server stores the received health restriction conditions in association with the user profile.

[0585] Step 10:

[0586] The server invokes the recipe generation algorithm.

[0587] The server starts the AI ​​engine by inputting information on ingredients, health restrictions, and user profile.

[0588] Step 11:

[0589] The AI ​​engine generates the appropriate recipe.

[0590] The AI ​​engine analyzes the input data and generates a recipe that meets the conditions.

[0591] Step 12:

[0592] The server checks the recipe for suitability.

[0593] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[0594] Step 13:

[0595] The server sends the generated recipe to the device.

[0596] The server sends the matching recipe and cooking instructions to the user terminal.

[0597] Step 14:

[0598] The user checks the results.

[0599] The user checks the recipe and cooking instructions presented on the terminal.

[0600] Step 15:

[0601] The user starts cooking.

[0602] The user follows the instructions to start cooking.

[0603] Example 1

[0604] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0605] In modern society, there is a demand for easy and fast provision of cooking recipes that suit individual health conditions and preferences. In particular, it has been difficult for conventional systems to automatically generate recipes that accommodate allergies and health restrictions (e.g., restrictions on calories, salt, sugar, and fat) and evaluate the nutritional balance of those recipes. Therefore, there is a need for a system that allows users to easily select dishes that suit their preferences while taking their health conditions into consideration.

[0606] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0607] In this invention, the server includes: means for a user to input allergy information and likes and dislikes; means for a user to input ingredients that the user wants to use; means for a user to input health restrictions; means for retrieving relevant information from a database containing nutritional information based on the input information; means for using an AI engine to generate cooking recipes based on the retrieved information and health restrictions; means for evaluating the nutritional balance of the generated cooking recipes and repeating the generation and evaluation of recipes until a recipe that meets the specified restrictions is found; and means for presenting the generated cooking recipes and cooking procedures to the user. This allows users to quickly and easily obtain recipes that meet their allergies and health restrictions.

[0608] A "user" is an individual who uses the system to obtain cooking recipes.

[0609] "Allergy information" refers to information about whether a user has an allergic reaction to a particular food.

[0610] "Likes and dislikes information" refers to information about the dishes that the user likes and dislikes.

[0611] An "ingredient" is a specific food that a user wishes to use.

[0612] "Health restriction items" refer to conditions related to upper limits on calories, salt, sugar, fat, and other nutritional restrictions that are set with the user's health in mind.

[0613] "Nutrition information" refers to information about the nutritional components of food ingredients, such as calories, fat, salt, and sugar.

[0614] A "database" is an information system for storing ingredients, recipes, and their nutritional information.

[0615] An "AI engine" is an artificial intelligence that generates cooking recipes that meet the conditions based on input information and evaluates nutritional balance.

[0616] A "recipe generation algorithm" is a computational method used by an AI engine to find the optimal recipe based on input information.

[0617] "Cooking steps" refer to the specific cooking steps required to complete the generated cooking recipe.

[0618] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user using a terminal on a server, and generates recipes using an AI engine. Specific embodiments for implementing this system are described below.

[0619] System Configuration

[0620] 1. User Interface (UI)

[0621] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0622] Allergy information: For example, peanut allergy.

[0623] Likes and dislikes: For example, your favorite food is salad, and you don't have any disliked food.

[0624] Ingredients: A list of ingredients you would like to use, for example, lettuce, tomato, cucumber, chicken breast, etc.

[0625] Health restrictions: For example, calorie limit of 300 kcal, salt limit of 1g, etc.

[0626] 2. Database

[0627] The server manages an ingredient database and a recipe database.

[0628] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0629] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0630] 3. AI Engine

[0631] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine retrieves nutritional information from a database and finds the optimal combination. It also evaluates the nutritional balance of the generated recipes to ensure that the calorie and salt content does not exceed the specified upper limit. Recipe generation and evaluation are repeated until a recipe that meets the specified restrictions is found.

[0632] Specific examples

[0633] For example, you can enter:

[0634] Allergy Information: Peanut Allergy

[0635] Likes and dislikes: Favorite food is salad, dislikes nothing

[0636] Ingredients: lettuce, tomato, cucumber, chicken breast

[0637] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[0638] Based on that, the following recipe is generated:

[0639] Recipe Name: Healthy Grilled Chicken Salad

[0640] Cooking Instructions:

[0641] 1. Cut the lettuce into bite-sized pieces.

[0642] 2. Thinly slice the tomatoes and cucumbers.

[0643] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0644] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0645] This process allows users to quickly and easily find recipes that accommodate their allergies and health restrictions, allowing them to enjoy food that suits their tastes while maintaining their health.

[0646] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0647] Step 1:

[0648] The user enters allergy information and likes and dislikes.

[0649] Specific operation: The user enters their allergy information (e.g., peanut allergy) and favorite food information (e.g., favorite food is salad, no disliked food) into the device's UI. The entered information is sent from the device to the server.

[0650] Input: Allergy information and food preferences

[0651] Output: User information sent to the server

[0652] Step 2:

[0653] The user inputs the ingredients they want to use.

[0654] Specific operation: The user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast) into the device's UI. The input information is sent from the device to the server.

[0655] Input: List of ingredients you want to use

[0656] Output: Ingredient information sent to the server

[0657] Step 3:

[0658] The user inputs health restrictions.

[0659] Specific operation: The user inputs health restrictions (e.g., calorie limit 300 kcal, salt intake 1g or less) into the device's UI. The input information is sent from the device to the server.

[0660] Input: Health Restrictions

[0661] Output: Health restrictions sent to the server

[0662] Step 4:

[0663] The server retrieves nutritional information from a database based on the transmitted information.

[0664] Specific operation: The server receives the user's allergy information, preference information, ingredient list, and health restrictions, and retrieves the nutritional information for each ingredient from the ingredient database.

[0665] Input: User information, food ingredients, and health restrictions sent to the server

[0666] Output: Nutritional information of the ingredients obtained

[0667] Step 5:

[0668] The server uses an AI engine to generate cooking recipes based on the acquired information and health restrictions.

[0669] Specific operation: The server launches an AI engine to generate suitable recipes based on the acquired nutritional information and health restrictions. The AI ​​engine uses a recipe generation algorithm to find the optimal combination. It repeats the process of generating and evaluating recipes until it finds one that meets the specified restrictions.

[0670] Input: Obtained nutritional information, health restrictions

[0671] Output: The generated recipe

[0672] Step 6:

[0673] The server presents the generated recipe and cooking instructions to the user.

[0674] Specific operation: The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device. The user can view the recipe and instructions through the device's UI.

[0675] Input: Generated recipe

[0676] Output: Recipe and cooking instructions displayed on the user's device

[0677] This series of steps allows users to easily obtain recipes that take into consideration their allergies and health restrictions.

[0678] (Application example 1)

[0679] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0680] In modern society, many people want to enjoy healthy meals, but at the same time, maintaining a balanced diet in a busy lifestyle can be difficult. Finding appropriate recipes can be especially challenging for people with allergies or health restrictions. Furthermore, many users want simple, healthy meals using specific ingredients, but there is a lack of systems that can meet these needs.

[0681] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0682] In this invention, the server includes a means for the user to input allergy information and likes and dislikes, a means for the user to input ingredients the user wants to use, and a means for the user to input health restriction items. This makes it possible to suggest healthy, nutritionally balanced dishes through an application installed on a smartphone that uses the information input by the user to suggest health-conscious recipes.

[0683] The "means for the user to input information about allergies and likes and dislikes" is an interface that allows the user to input information about his or her own allergies, preferences, and disliked foods.

[0684] The "means for inputting ingredients that the user wants to use" is an interface that allows the user to input the specific ingredients that the user wants to use in the current dish.

[0685] The "means for the user to input health restrictions" is an interface that allows the user to input health-related restrictions such as calorie limits, salt, sugar, and fat.

[0686] The "means for obtaining corresponding information from a database containing nutritional information based on the input information" is a program for analyzing the information input by the user and obtaining corresponding information from a database containing nutritional information.

[0687] "Means for using an AI engine to generate cooking recipes based on the acquired information and health restrictions" refers to a program that uses an artificial intelligence engine to generate optimal cooking recipes based on nutritional information and health restrictions acquired from a database.

[0688] The "means for presenting the generated recipe and cooking steps to the user" is an interface for displaying the recipe and cooking steps generated by the AI ​​engine to the user.

[0689] "Means that operate as an application installed on a smartphone and use information entered by the user to suggest healthy recipes" refers to an application that operates on a smartphone to suggest healthy recipes using information entered by the user.

[0690] This invention provides a system that generates healthy recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. The system includes a user interface, a database, an AI engine, and a means for displaying the results.

[0691] 1. User Interface (UI)

[0692] Users can enter the following information through a smartphone application:

[0693] Basic information: User's allergies, likes and dislikes.

[0694] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0695] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0696] 2. Database

[0697] The server manages a database containing nutritional information:

[0698] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0699] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0700] 3. AI Engine

[0701] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine is configured using the following software and tools:

[0702] AI engine: TensorFlow or PyTorch

[0703] API server: Django (server-side API management)

[0704] 4. Results display

[0705] The generated recipes and cooking instructions are displayed to the user through a smartphone application. The user can easily create dishes that meet health restrictions based on the provided recipes. The results are displayed by the following means:

[0706] Specific examples

[0707] For example, if a user enters the following information:

[0708] Allergy Information: Peanut Allergy

[0709] Likes and dislikes: Favorite food is salad, dislikes nothing

[0710] Ingredients: lettuce, tomato, cucumber, chicken breast

[0711] Health restrictions: Calorie limit 300 kcal, salt limit 1g or less

[0712] Using this information, the AI ​​engine generates a recipe for a "Healthy Grilled Chicken Salad" and displays it on the user's smartphone along with cooking instructions. Specifically, the following steps are presented:

[0713] 1. Cut the lettuce into bite-sized pieces.

[0714] 2. Thinly slice the tomatoes and cucumbers.

[0715] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0716] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0717] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[0718] Example prompts to input to the generative AI model

[0719] User Allergy Information: Peanut Allergy

[0720] Likes and dislikes: Favorite food is salad, dislikes nothing

[0721] Ingredients: lettuce, tomato, cucumber, chicken breast

[0722] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[0723] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0724] Step 1:

[0725] Users use a smartphone application to input their allergy information and likes and dislikes. The input basic information is sent by the device to a server and stored in a database on the server. The basic information includes peanut allergies, favorite dishes (e.g., salad), and disliked dishes (e.g., none). This information is stored in the database as a user profile.

[0726] Step 2:

[0727] Users input the ingredients they want to use through a smartphone application. The input ingredients are sent to the server via the device, and nutritional information about the ingredients is retrieved from the ingredient database. For example, if lettuce, tomato, cucumber, and chicken breast are input as ingredients, detailed nutritional information about these ingredients, such as calories, fat, salt, and sugar, is retrieved. This information becomes the basic data for recipe generation by the AI ​​engine.

[0728] Step 3:

[0729] Users input their health restrictions via a smartphone application. The entered health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less) are sent to the server via the device, associated with the user profile, and stored in a database. This data is used as a restriction that the AI ​​engine takes into account when generating recipes.

[0730] Step 4:

[0731] The AI ​​engine generates optimal cooking recipes based on basic information stored on the server, nutritional information for ingredients used, and health restrictions. The server passes input data to the AI ​​engine, which analyzes this information and generates recipes that fit the conditions. For example, a recipe for "Healthy Grilled Chicken Salad" using lettuce, tomato, cucumber, and chicken breast is generated. Machine learning engines such as TensorFlow or PyTorch are used in this process.

[0732] Step 5:

[0733] The server sends the generated recipe and cooking instructions to the device. The user can then view the recipe and cooking instructions sent from the server through a smartphone application. For example, for "Healthy Grilled Chicken Salad," the following steps are displayed:

[0734] 1. Cut the lettuce into bite-sized pieces.

[0735] 2. Thinly slice the tomatoes and cucumbers.

[0736] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0737] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0738] In this way, users can easily prepare healthy meals.

[0739] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0740] This invention is a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments of this system are described below.

[0741] System configuration

[0742] 1. User Interface (UI)

[0743] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[0744] Basic information: User's allergies, likes and dislikes.

[0745] Ingredients Used: A list of the specific ingredients you would like to use this time.

[0746] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[0747] Emotion information: Recognizes user emotions using an emotion engine.

[0748] 2. Database

[0749] The server manages an ingredient database and a recipe database.

[0750] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[0751] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[0752] 3. AI Engine and Emotion Engine

[0753] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[0754] Program processing

[0755] 1. Enter basic user information

[0756] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[0757] Server: Receives the basic information sent and stores it in a database as a user profile.

[0758] 2. Enter ingredients used

[0759] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[0760] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[0761] 3. Enter health restrictions

[0762] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[0763] Server: Receives the entered health restrictions and stores them in association with the user profile.

[0764] 4. Acquiring emotional information

[0765] Emotion engine: Recognizes user emotions in real time based on facial recognition, voice, gestures, etc.

[0766] Server: Receives the recognized emotion information and passes it to the AI ​​engine.

[0767] 5. Recipe Generation

[0768] Server: Calls the recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[0769] AI Engine: Adjusts recipe variations and suggestions based on emotional information from the Emotion Engine. It also evaluates the nutritional balance of generated recipes to ensure that calorie and salt content do not exceed specified limits. It repeats recipe generation and evaluation until it finds a recipe that meets the specified constraints.

[0770] 6. Results display

[0771] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[0772] User: Check the recipe and cooking instructions sent from the server through the device UI.

[0773] Specific examples

[0774] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[0775] 1. Cut the lettuce into bite-sized pieces.

[0776] 2. Thinly slice the tomatoes and cucumbers.

[0777] 3. Grill the chicken breasts and cut into bite-sized pieces.

[0778] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[0779] In this way, users can easily prepare healthy meals that take emotional information into account. Furthermore, recipes that take into account restrictions on calories and salt content are provided, helping users maintain their health. Taking emotional information into account allows recipes that suit the user's preferences to be suggested, improving cooking satisfaction.

[0780] The processing flow will be explained below.

[0781] Step 1:

[0782] The user enters basic information (allergies, likes and dislikes).

[0783] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[0784] Step 2:

[0785] The device sends basic information to the server.

[0786] The terminal transmits the input basic information to the server.

[0787] Step 3:

[0788] The server stores the user profile.

[0789] The server stores the received basic information in a database and manages it as a user profile.

[0790] Step 4:

[0791] The user inputs the ingredients to be used.

[0792] The user enters the ingredients they want to use this time into an input form on the terminal.

[0793] Step 5:

[0794] The terminal transmits information about ingredients used to the server.

[0795] The terminal transmits the input ingredient information to the server.

[0796] Step 6:

[0797] The server acquires the ingredient data.

[0798] The server retrieves the nutritional information of the specified foodstuff from the database.

[0799] Step 7:

[0800] The user inputs health restrictions.

[0801] Users input the health items they want to consider or limit (e.g., calorie limit 300 kcal, salt less than 1g) on ​​their device.

[0802] Step 8:

[0803] The device sends the health restriction items to the server.

[0804] The terminal transmits the entered health items to the server.

[0805] Step 9:

[0806] The server stores the health restriction conditions.

[0807] The server stores the received health restriction conditions in association with the user profile.

[0808] Step 10:

[0809] The emotion engine acquires emotion information.

[0810] The emotion engine uses facial recognition, voice, and gestures to recognize the user's emotions.

[0811] Step 11:

[0812] The device transmits the emotion information to the server.

[0813] The terminal transmits the acquired emotion information to the server.

[0814] Step 12:

[0815] The server invokes the recipe generation algorithm.

[0816] The server inputs ingredients, health restrictions, user profile, and emotional information into the AI ​​engine.

[0817] Step 13:

[0818] The AI ​​engine generates the appropriate recipe.

[0819] The AI ​​engine analyzes the input information and generates a recipe that meets the conditions and emotional information.

[0820] Step 14:

[0821] The server checks the recipe for suitability.

[0822] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[0823] Step 15:

[0824] The server sends the generated recipe to the device.

[0825] The server sends the matching recipe and cooking instructions to the user terminal.

[0826] Step 16:

[0827] The user checks the results.

[0828] The user checks the recipe and cooking instructions presented on the terminal.

[0829] Step 17:

[0830] The user starts cooking.

[0831] The user follows the instructions to start cooking.

[0832] Example 2

[0833] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0834] Conventional recipe generation systems only generate recipes by taking into account the user's allergies, likes and dislikes, and health restrictions. However, because they do not take into account the user's emotional information, there is a problem in that the satisfaction of the food is not sufficiently improved. Furthermore, even when generating recipes that take into account individual health, it is not possible to reflect emotional information.

[0835] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0836] In this invention, the server includes means for the user to input allergy information and likes and dislikes, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for acquiring the user's emotional information using an emotion engine, means for acquiring relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the acquired information, health restriction items, and emotional information, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate healthy cooking recipes that are individually tailored to the user's emotional information and provide a high level of satisfaction.

[0837] "Allergy information" is information indicating that a user has an allergic reaction to a specific food ingredient or component.

[0838] "Likes and dislikes information" is information about ingredients and dishes that the user likes and dislikes.

[0839] "Ingredients" is a list of ingredients used to make a dish.

[0840] "Health restriction items" are restriction conditions such as calories, salt, fat, sugar, etc., set according to the user's health condition.

[0841] An "emotion engine" is a system that recognizes emotions from a user's facial expressions, voice, gestures, etc.

[0842] "Nutrition information" refers to information about the calorie, fat, salt, sugar, and other contents of a particular food ingredient.

[0843] A "database" is a digital system for systematically organizing and storing information.

[0844] A "recipe generation algorithm" is a program that refers to the steps to create an optimal cooking recipe based on input information.

[0845] An "AI engine" is an artificial intelligence system used to analyze input information and achieve a specific purpose (in this case, generating cooking recipes).

[0846] A "cooking recipe" is a list of specific steps to follow when preparing a dish.

[0847] A "recipe" is information that includes a set of ingredients and instructions for combining them to make a dish.

[0848] "User interface (UI)" refers to the screens and input devices that allow a user to interact with a system.

[0849] A "server" is a computer system that processes information and provides services to other computers and devices over a network.

[0850] "Terminal" refers to a device such as a computer, smartphone, or tablet that is directly operated by a user.

[0851] The present invention provides a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments for carrying out the present invention will be described below.

[0852] User Interface

[0853] Users enter the following information using a device such as a smartphone, tablet, or PC:

[0854] Basic information: Allergy information, likes and dislikes

[0855] Ingredients: A list of the specific ingredients you would like to use.

[0856] Health restrictions: Calorie limits, salt, sugar, and fat restrictions

[0857] Emotion information: Emotion information recognized by the emotion engine

[0858] Database

[0859] The server manages the following databases:

[0860] Ingredient database: detailed nutritional information for each ingredient

[0861] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[0862] AI engine and emotion engine

[0863] The server generates recipes based on the information provided by the user using the following engines:

[0864] AI engine: Extracts nutritional information from a database and finds optimal combinations

[0865] Emotion engine: Recognizes user emotions through facial recognition, voice, gestures, etc., and reflects them in recipe generation

[0866] Example of a system

[0867] Specific processing flow

[0868] The user uses the device's UI to input that they are allergic to peanuts and that they like salads. The device sends this information to the server, which stores the received information in a database and creates a user profile.

[0869] Next, the user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast). The terminal sends this information to the server, which then retrieves the nutritional information for each ingredient from the ingredient database.

[0870] Furthermore, the user inputs health restrictions (calorie limit 300 kcal, salt limit 1 g or less). When the device sends this information to the server, the server associates the received restrictions with the user profile and saves them.

[0871] The emotion engine recognizes the user's emotions in real time from facial recognition, voice, and gestures, and sends the information to the server, which then passes it on to the AI ​​engine.

[0872] The server calls a recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates optimal recipes while taking emotional information into account. It evaluates nutritional balance and adjusts calorie and salt content so that they do not exceed specified limits.

[0873] The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device, where the user can view the cooking instructions through the device's UI.

[0874] Examples and prompts

[0875] For example, the generated recipe for "Healthy Grilled Chicken Salad" includes the following steps:

[0876] 1. Cut the lettuce into bite-sized pieces

[0877] 2. Thinly slice the tomatoes and cucumbers

[0878] 3. Grill the chicken breasts and cut them into bite-sized pieces.

[0879] 4. Mix lemon juice with a little olive oil to make a dressing and pour it over the salad.

[0880] Examples of prompts include:

[0881] "I'd like a healthy recipe. I would like to use lettuce, tomato, cucumber, and chicken breast. Calories should be under 300 kcal and salt should be under 1g."

[0882] This system allows users to easily prepare healthy meals that take emotional information into account, thus providing recipes tailored to individual health and emotional states, improving user satisfaction.

[0883] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0884] Step 1:

[0885] The user inputs allergy information and likes and dislikes using the device's UI. Specifically, the user inputs that they have a peanut allergy and that their favorite dish is salad. The device then sends the input information to the server.

[0886] Input: Allergy information (peanuts) and likes and dislikes (likes: salad)

[0887] Data processing: Formatting information and sending it to the server

[0888] Output: User profile stored on the server

[0889] Step 2:

[0890] The server stores the received basic information in a database. After receiving the information, it stores it in the database as a user profile.

[0891] Input: Basic information sent from the device

[0892] Data processing: Convert the information into a storage format and save it in a database

[0893] Output: Saved user profile (peanut allergy, favorite food is salad)

[0894] Step 3:

[0895] The user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast) through the device's UI. The device then sends this ingredient information to the server.

[0896] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[0897] Data processing: Formatting information and sending it to the server

[0898] Output: Ingredient information is sent to the server

[0899] Step 4:

[0900] The server acquires corresponding nutrition information from the ingredient database based on the input ingredient information.

[0901] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[0902] Data processing: Search and obtain corresponding nutritional information from food ingredient database

[0903] Output: Retrieved nutrition information (lettuce: 5 kcal, tomato: 18 kcal, cucumber: 16 kcal, chicken breast: 165 kcal)

[0904] Step 5:

[0905] The user inputs health restriction items (e.g., calorie limit 300 kcal, salt intake 1 g or less) through the device's UI. The device then sends this information to the server.

[0906] Input: Health restriction items (calorie limit 300 kcal, salt less than 1g)

[0907] Data processing: Formatting information and sending it to the server

[0908] Output: Health restrictions are sent to the server

[0909] Step 6:

[0910] The server receives the entered health restriction items and stores them in association with the user profile.

[0911] Input: Health restriction items (calories 300 kcal or less, salt 1g or less)

[0912] Data processing: Information is associated with user profiles and stored in a database

[0913] Output: Health restrictions saved in association with the user profile

[0914] Step 7:

[0915] The emotion engine recognizes emotions in real time from the user's facial recognition, voice, and gestures, and sends that information to the server.

[0916] Input: User's facial expressions, voice, and gestures

[0917] Data processing: Acquire emotional information through facial recognition, voice analysis, and gesture analysis

[0918] Output: Emotional information obtained (e.g., joy)

[0919] Step 8:

[0920] The server receives the emotional information and passes it to the AI ​​engine, which then generates recipes taking the emotional information into account.

[0921] Input: Emotional information, food information, health restrictions, user profile

[0922] Data processing: Execute recipe generation algorithm taking into account emotional information

[0923] Output: Generated recipe and cooking instructions

[0924] Step 9:

[0925] The server transmits the generated recipe and its cooking steps to the terminal.

[0926] Input: Generated recipe and cooking instructions

[0927] Data processing: Converting information into a format that can be sent to the user's device

[0928] Output: Recipe and cooking instructions sent to device

[0929] Step 10:

[0930] The user can view the recipe and cooking instructions sent to them through the device's UI, including instructions to cut the lettuce into bite-sized pieces, thinly slice the tomatoes and cucumbers, and grill and cut the chicken breasts into bite-sized pieces.

[0931] Input: Recipe and cooking instructions sent from the server

[0932] Output: Check the recipe and cooking instructions displayed on your device

[0933] (Application example 2)

[0934] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0935] Conventional recipe generation systems generate recipes based on the user's health restrictions and desired ingredient information, but they are unable to take into account the user's current emotional state. This makes it difficult to provide recipes that perfectly match the user's preferences, resulting in low satisfaction.

[0936] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input allergy information and likes and dislikes information, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for retrieving relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the retrieved information and health restriction items, means for recognizing user emotional information in real time, means for reflecting the recognized emotional information in recipe generation, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate health-conscious cooking recipes that reflect the user's emotional state, thereby improving user satisfaction.

[0937] The "means for the user to input information about allergies and likes and dislikes" is an interface through which the user inputs information about his or her own allergies and preferences.

[0938] The "means for inputting ingredients that the user wants to use" is an interface through which the user inputs information about ingredients that the user plans to use in the dish.

[0939] The "means for the user to input health restriction items" is an interface through which the user inputs information about health restrictions such as calories and salt content.

[0940] The "means for retrieving relevant information from a database containing nutritional information" is a function for retrieving information that matches the conditions entered by the user from a database that stores nutritional information.

[0941] "Means for using an AI engine to generate cooking recipes" refers to an algorithm that generates optimal cooking recipes based on information entered by the user.

[0942] "Means for recognizing the user's emotional information in real time" is a function that determines the user's emotional state from their facial expressions and tone of voice.

[0943] The "means for reflecting recognized emotional information in recipe generation" is a function that adjusts recipe suggestions taking into account the user's emotional state.

[0944] The "means for presenting the generated recipe and cooking steps to the user" is an interface that displays the finally generated recipe and cooking steps to the user.

[0945] The present invention provides a system for generating healthy cooking recipes that take into account the emotional information of a user. Specific embodiments of this system will be described below.

[0946] System configuration

[0947] 1. User Interface (UI)

[0948] The user enters the following information through the UI of the device (smartphone, tablet, PC, etc.):

[0949] Allergy information (e.g., peanut allergy)

[0950] Likes and dislikes (e.g., favorite food is salad, no dislikes)

[0951] A list of ingredients you would like to use (e.g. lettuce, tomato, cucumber, chicken breast)

[0952] Health restrictions (e.g., calorie limit 300 kcal, salt limit 1g or less)

[0953] 2. Database

[0954] The server manages a database that stores the following information:

[0955] Food database: Detailed nutritional information for each food ingredient (calories, fat, salt, sugar, etc.)

[0956] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[0957] 3. AI Engine and Emotion Engine

[0958] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[0959] Specific examples of hardware and software used

[0960] Smart glasses: Used by field staff to scan customers' faces and obtain emotional information in real time.

[0961] Flask: A lightweight Python-based web application framework that acts as a server and receives user data and facial information.

[0962] OpenCV: A computer vision library, used for face recognition.

[0963] Keras: A deep learning library used to build emotion recognition models.

[0964] Data Processing and Computation

[0965] 1. Face Recognition: The smart glasses capture the customer's face, and then use OpenCV to detect the face and Keras models to recognize emotions.

[0966] 2. Emotion Recognition: Captured facial images are fed into a deep learning model to determine the emotional state.

[0967] 3. Recipe generation: The AI ​​engine generates optimal recipes based on the user's health restrictions and perceived emotions.

[0968] Examples and prompts

[0969] To illustrate, consider the following scenario in a cafe:

[0970] A cafe staff member wears smart glasses and says to the customer, "Hello, are you looking for today's specials?" The smart glasses capture the customer's facial expressions, which are then analyzed by an emotion engine. For example, if the customer expresses the emotion "happy," the Smart Healthy Cafe Assistant will suggest "marinated salmon." This recipe also takes into account the customer's health restrictions (e.g., a calorie limit of 300 kcal).

[0971] Example prompt sentence:

[0972] "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts"

[0973] In this way, a recipe suggestion system that takes emotional information into account improves customer satisfaction.

[0974] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0975] Step 1:

[0976] The user uses the device's user interface (UI) to input their allergy information, likes and dislikes, ingredients they want to use, and health restrictions. This input information is sent from the device to the server, which then packages the information in JSON or other appropriate format and sends it to the server.

[0977] Step 2:

[0978] The server receives user input information sent from the device. The received information is analyzed and information such as allergies, likes and dislikes, ingredients desired to use, and health restrictions is sorted into appropriate fields. This information is then saved in a database as a user profile.

[0979] Step 3:

[0980] The server retrieves the corresponding nutritional information from the ingredient database based on the information about the ingredients the user wants to use. Specifically, nutritional information such as calories, fat, salt, and sugar for lettuce, tomato, cucumber, and chicken breast is retrieved from the database. This completes the available information.

[0981] Step 4:

[0982] The server receives the user's health restriction information and associates it with the user profile. For example, if restrictions are set such as "calorie limit 300 kcal, salt intake 1g or less," this information is added to the user profile. Subsequent data processing is based on this information.

[0983] Step 5:

[0984] The server uses an emotion engine to recognize real-time user emotion information obtained from smart glasses, etc. The emotion engine analyzes the user's facial expressions, voice, gestures, etc., and recognizes whether the user is in an emotional state such as "happy," "sad," or "neutral." This emotion information is then sent to the server.

[0985] Step 6:

[0986] The server uses an AI engine to generate optimal cooking recipes based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions. It also incorporates emotional information from the emotional engine to suggest recipes that suit the user's emotional state. The generated recipes are also evaluated to see if they meet calorie and salt restrictions.

[0987] Step 7:

[0988] The server sends the successfully generated recipe and its cooking instructions to the device. For example, if a recipe for a healthy grilled chicken salad is generated, the server presents the user with information including the specific cooking instructions (e.g., cut the lettuce into bite-sized pieces, thinly slice the tomato and cucumber, etc.). The user can confirm this information through the device's UI.

[0989] Specific examples of operation

[0990] As an example of a prompt, if "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts" is entered, the server will pass the image file to the emotion engine, determine the user's emotional state as "happy," and then generate an appropriate recipe such as "marinated salmon," taking into account sugar and salt restrictions and presenting the final recipe.

[0991] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0992] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0993] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0994] [Third embodiment]

[0995] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0996] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0997] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0998] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0999] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1000] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1001] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1002] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1003] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1004] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1005] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1006] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[1007] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user on a terminal on a server, and generates recipes using an AI engine.

[1008] System configuration

[1009] 1. User Interface (UI)

[1010] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1011] Basic information: User's allergies, likes and dislikes.

[1012] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1013] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1014] 2. Database

[1015] The server manages an ingredient database and a recipe database.

[1016] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1017] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1018] 3. AI Engine

[1019] The server uses the input information to generate recipes that meet the specified health restrictions using an AI engine that pulls nutritional information from a database to find the optimal combination.

[1020] Program processing

[1021] 1. Enter basic user information

[1022] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[1023] Server: Receives the basic information sent and stores it in a database as a user profile.

[1024] 2. Enter ingredients used

[1025] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[1026] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[1027] 3. Enter health restrictions

[1028] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[1029] Server: Receives the entered health restrictions and stores them in association with the user profile.

[1030] 4. Recipe Generation

[1031] Server: Calls the recipe generation algorithm based on the acquired ingredient information, user profile, and health restrictions. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[1032] AI engine: Evaluates the nutritional balance of the generated recipes and ensures that the calorie and salt content does not exceed the specified limits. It repeats the process of generating and evaluating recipes until it finds a recipe that meets the specified limits.

[1033] 5. Display results

[1034] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[1035] User: Check the recipe and cooking instructions sent from the server through the device UI.

[1036] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[1037] 1. Cut the lettuce into bite-sized pieces.

[1038] 2. Thinly slice the tomatoes and cucumbers.

[1039] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1040] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1041] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[1042] The processing flow will be explained below.

[1043] Step 1:

[1044] The user enters basic information (allergies, likes and dislikes).

[1045] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[1046] Step 2:

[1047] The device sends basic information to the server.

[1048] The terminal transmits the input basic information to the server.

[1049] Step 3:

[1050] The server stores the user profile.

[1051] The server stores the received basic information in a database and manages it as a user profile.

[1052] Step 4:

[1053] The user inputs the ingredients to be used.

[1054] The user enters the ingredients they want to use this time into an input form on the terminal.

[1055] Step 5:

[1056] The terminal transmits information about ingredients used to the server.

[1057] The terminal transmits the input ingredient information to the server.

[1058] Step 6:

[1059] The server acquires the ingredient data.

[1060] The server retrieves the nutritional information of the specified foodstuff from the database.

[1061] Step 7:

[1062] The user inputs health restrictions.

[1063] Users input the health items they want to consider or restrict (calorie limits, salt, sugar, fat restrictions, etc.) into the device.

[1064] Step 8:

[1065] The device sends the health restriction items to the server.

[1066] The terminal transmits the entered health items to the server.

[1067] Step 9:

[1068] The server stores the health restriction conditions.

[1069] The server stores the received health restriction conditions in association with the user profile.

[1070] Step 10:

[1071] The server invokes the recipe generation algorithm.

[1072] The server starts the AI ​​engine by inputting information on ingredients, health restrictions, and user profile.

[1073] Step 11:

[1074] The AI ​​engine generates the appropriate recipe.

[1075] The AI ​​engine analyzes the input data and generates a recipe that meets the conditions.

[1076] Step 12:

[1077] The server checks the recipe for suitability.

[1078] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[1079] Step 13:

[1080] The server sends the generated recipe to the device.

[1081] The server sends the matching recipe and cooking instructions to the user terminal.

[1082] Step 14:

[1083] The user checks the results.

[1084] The user checks the recipe and cooking instructions presented on the terminal.

[1085] Step 15:

[1086] The user starts cooking.

[1087] The user follows the instructions to start cooking.

[1088] Example 1

[1089] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1090] In modern society, there is a demand for easy and fast provision of cooking recipes that suit individual health conditions and preferences. In particular, it has been difficult for conventional systems to automatically generate recipes that accommodate allergies and health restrictions (e.g., restrictions on calories, salt, sugar, and fat) and evaluate the nutritional balance of those recipes. Therefore, there is a need for a system that allows users to easily select dishes that suit their preferences while taking their health conditions into consideration.

[1091] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1092] In this invention, the server includes: means for a user to input allergy information and likes and dislikes; means for a user to input ingredients that the user wants to use; means for a user to input health restrictions; means for retrieving relevant information from a database containing nutritional information based on the input information; means for using an AI engine to generate cooking recipes based on the retrieved information and health restrictions; means for evaluating the nutritional balance of the generated cooking recipes and repeating the generation and evaluation of recipes until a recipe that meets the specified restrictions is found; and means for presenting the generated cooking recipes and cooking procedures to the user. This allows users to quickly and easily obtain recipes that meet their allergies and health restrictions.

[1093] A "user" is an individual who uses the system to obtain cooking recipes.

[1094] "Allergy information" refers to information about whether a user has an allergic reaction to a particular food.

[1095] "Likes and dislikes information" refers to information about the dishes that the user likes and dislikes.

[1096] An "ingredient" is a specific food that a user wishes to use.

[1097] "Health restriction items" refer to conditions related to upper limits on calories, salt, sugar, fat, and other nutritional restrictions that are set with the user's health in mind.

[1098] "Nutrition information" refers to information about the nutritional components of food ingredients, such as calories, fat, salt, and sugar.

[1099] A "database" is an information system for storing ingredients, recipes, and their nutritional information.

[1100] An "AI engine" is an artificial intelligence that generates cooking recipes that meet the conditions based on input information and evaluates nutritional balance.

[1101] A "recipe generation algorithm" is a computational method used by an AI engine to find the optimal recipe based on input information.

[1102] "Cooking steps" refer to the specific cooking steps required to complete the generated cooking recipe.

[1103] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user using a terminal on a server, and generates recipes using an AI engine. Specific embodiments for implementing this system are described below.

[1104] System Configuration

[1105] 1. User Interface (UI)

[1106] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1107] Allergy information: For example, peanut allergy.

[1108] Likes and dislikes: For example, your favorite food is salad, and you don't have any disliked food.

[1109] Ingredients: A list of ingredients you would like to use, for example, lettuce, tomato, cucumber, chicken breast, etc.

[1110] Health restrictions: For example, calorie limit of 300 kcal, salt limit of 1g, etc.

[1111] 2. Database

[1112] The server manages an ingredient database and a recipe database.

[1113] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1114] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1115] 3. AI Engine

[1116] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine retrieves nutritional information from a database and finds the optimal combination. It also evaluates the nutritional balance of the generated recipes to ensure that the calorie and salt content does not exceed the specified upper limit. Recipe generation and evaluation are repeated until a recipe that meets the specified restrictions is found.

[1117] Specific examples

[1118] For example, you can enter:

[1119] Allergy Information: Peanut Allergy

[1120] Likes and dislikes: Favorite food is salad, dislikes nothing

[1121] Ingredients: lettuce, tomato, cucumber, chicken breast

[1122] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[1123] Based on that, the following recipe is generated:

[1124] Recipe Name: Healthy Grilled Chicken Salad

[1125] Cooking Instructions:

[1126] 1. Cut the lettuce into bite-sized pieces.

[1127] 2. Thinly slice the tomatoes and cucumbers.

[1128] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1129] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1130] This process allows users to quickly and easily find recipes that accommodate their allergies and health restrictions, allowing them to enjoy food that suits their tastes while maintaining their health.

[1131] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1132] Step 1:

[1133] The user enters allergy information and likes and dislikes.

[1134] Specific operation: The user enters their allergy information (e.g., peanut allergy) and favorite food information (e.g., favorite food is salad, no disliked food) into the device's UI. The entered information is sent from the device to the server.

[1135] Input: Allergy information and food preferences

[1136] Output: User information sent to the server

[1137] Step 2:

[1138] The user inputs the ingredients they want to use.

[1139] Specific operation: The user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast) into the device's UI. The input information is sent from the device to the server.

[1140] Input: List of ingredients you want to use

[1141] Output: Ingredient information sent to the server

[1142] Step 3:

[1143] The user inputs health restrictions.

[1144] Specific operation: The user inputs health restrictions (e.g., calorie limit 300 kcal, salt intake 1g or less) into the device's UI. The input information is sent from the device to the server.

[1145] Input: Health Restrictions

[1146] Output: Health restrictions sent to the server

[1147] Step 4:

[1148] The server retrieves nutritional information from a database based on the transmitted information.

[1149] Specific operation: The server receives the user's allergy information, preference information, ingredient list, and health restrictions, and retrieves the nutritional information for each ingredient from the ingredient database.

[1150] Input: User information, food ingredients, and health restrictions sent to the server

[1151] Output: Nutritional information of the ingredients obtained

[1152] Step 5:

[1153] The server uses an AI engine to generate cooking recipes based on the acquired information and health restrictions.

[1154] Specific operation: The server launches an AI engine to generate suitable recipes based on the acquired nutritional information and health restrictions. The AI ​​engine uses a recipe generation algorithm to find the optimal combination. It repeats the process of generating and evaluating recipes until it finds one that meets the specified restrictions.

[1155] Input: Obtained nutritional information, health restrictions

[1156] Output: The generated recipe

[1157] Step 6:

[1158] The server presents the generated recipe and cooking instructions to the user.

[1159] Specific operation: The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device. The user can view the recipe and instructions through the device's UI.

[1160] Input: Generated recipe

[1161] Output: Recipe and cooking instructions displayed on the user's device

[1162] This series of steps allows users to easily obtain recipes that take into consideration their allergies and health restrictions.

[1163] (Application example 1)

[1164] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1165] In modern society, many people want to enjoy healthy meals, but at the same time, maintaining a balanced diet in a busy lifestyle can be difficult. Finding appropriate recipes can be especially challenging for people with allergies or health restrictions. Furthermore, many users want simple, healthy meals using specific ingredients, but there is a lack of systems that can meet these needs.

[1166] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1167] In this invention, the server includes a means for the user to input allergy information and likes and dislikes, a means for the user to input ingredients the user wants to use, and a means for the user to input health restriction items. This makes it possible to suggest healthy, nutritionally balanced dishes through an application installed on a smartphone that uses the information input by the user to suggest health-conscious recipes.

[1168] The "means for the user to input information about allergies and likes and dislikes" is an interface that allows the user to input information about his or her own allergies, preferences, and disliked foods.

[1169] The "means for inputting ingredients that the user wants to use" is an interface that allows the user to input the specific ingredients that the user wants to use in the current dish.

[1170] The "means for the user to input health restrictions" is an interface that allows the user to input health-related restrictions such as calorie limits, salt, sugar, and fat.

[1171] The "means for obtaining corresponding information from a database containing nutritional information based on the input information" is a program for analyzing the information input by the user and obtaining corresponding information from a database containing nutritional information.

[1172] "Means for using an AI engine to generate cooking recipes based on the acquired information and health restrictions" refers to a program that uses an artificial intelligence engine to generate optimal cooking recipes based on nutritional information and health restrictions acquired from a database.

[1173] The "means for presenting the generated recipe and cooking steps to the user" is an interface for displaying the recipe and cooking steps generated by the AI ​​engine to the user.

[1174] "Means that operate as an application installed on a smartphone and use information entered by the user to suggest healthy recipes" refers to an application that operates on a smartphone to suggest healthy recipes using information entered by the user.

[1175] This invention provides a system that generates healthy recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. The system includes a user interface, a database, an AI engine, and a means for displaying the results.

[1176] 1. User Interface (UI)

[1177] Users can enter the following information through a smartphone application:

[1178] Basic information: User's allergies, likes and dislikes.

[1179] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1180] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1181] 2. Database

[1182] The server manages a database containing nutritional information:

[1183] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1184] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1185] 3. AI Engine

[1186] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine is configured using the following software and tools:

[1187] AI engine: TensorFlow or PyTorch

[1188] API server: Django (server-side API management)

[1189] 4. Results display

[1190] The generated recipes and cooking instructions are displayed to the user through a smartphone application. The user can easily create dishes that meet health restrictions based on the provided recipes. The results are displayed by the following means:

[1191] Specific examples

[1192] For example, if a user enters the following information:

[1193] Allergy Information: Peanut Allergy

[1194] Likes and dislikes: Favorite food is salad, dislikes nothing

[1195] Ingredients: lettuce, tomato, cucumber, chicken breast

[1196] Health restrictions: Calorie limit 300 kcal, salt limit 1g or less

[1197] Using this information, the AI ​​engine generates a recipe for a "Healthy Grilled Chicken Salad" and displays it on the user's smartphone along with cooking instructions. Specifically, the following steps are presented:

[1198] 1. Cut the lettuce into bite-sized pieces.

[1199] 2. Thinly slice the tomatoes and cucumbers.

[1200] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1201] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1202] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[1203] Example prompts to input to the generative AI model

[1204] User Allergy Information: Peanut Allergy

[1205] Likes and dislikes: Favorite food is salad, dislikes nothing

[1206] Ingredients: lettuce, tomato, cucumber, chicken breast

[1207] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[1208] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1209] Step 1:

[1210] Users use a smartphone application to input their allergy information and likes and dislikes. The input basic information is sent by the device to a server and stored in a database on the server. The basic information includes peanut allergies, favorite dishes (e.g., salad), and disliked dishes (e.g., none). This information is stored in the database as a user profile.

[1211] Step 2:

[1212] Users input the ingredients they want to use through a smartphone application. The input ingredients are sent to the server via the device, and nutritional information about the ingredients is retrieved from the ingredient database. For example, if lettuce, tomato, cucumber, and chicken breast are input as ingredients, detailed nutritional information about these ingredients, such as calories, fat, salt, and sugar, is retrieved. This information becomes the basic data for recipe generation by the AI ​​engine.

[1213] Step 3:

[1214] Users input their health restrictions via a smartphone application. The entered health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less) are sent to the server via the device, associated with the user profile, and stored in a database. This data is used as a restriction that the AI ​​engine takes into account when generating recipes.

[1215] Step 4:

[1216] The AI ​​engine generates optimal cooking recipes based on basic information stored on the server, nutritional information for ingredients used, and health restrictions. The server passes input data to the AI ​​engine, which analyzes this information and generates recipes that fit the conditions. For example, a recipe for "Healthy Grilled Chicken Salad" using lettuce, tomato, cucumber, and chicken breast is generated. Machine learning engines such as TensorFlow or PyTorch are used in this process.

[1217] Step 5:

[1218] The server sends the generated recipe and cooking instructions to the device. The user can then view the recipe and cooking instructions sent from the server through a smartphone application. For example, for "Healthy Grilled Chicken Salad," the following steps are displayed:

[1219] 1. Cut the lettuce into bite-sized pieces.

[1220] 2. Thinly slice the tomatoes and cucumbers.

[1221] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1222] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1223] In this way, users can easily prepare healthy meals.

[1224] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1225] This invention is a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments of this system are described below.

[1226] System configuration

[1227] 1. User Interface (UI)

[1228] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1229] Basic information: User's allergies, likes and dislikes.

[1230] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1231] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1232] Emotion information: Recognizes user emotions using an emotion engine.

[1233] 2. Database

[1234] The server manages an ingredient database and a recipe database.

[1235] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1236] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1237] 3. AI Engine and Emotion Engine

[1238] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[1239] Program processing

[1240] 1. Enter basic user information

[1241] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[1242] Server: Receives the basic information sent and stores it in a database as a user profile.

[1243] 2. Enter ingredients used

[1244] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[1245] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[1246] 3. Enter health restrictions

[1247] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[1248] Server: Receives the entered health restrictions and stores them in association with the user profile.

[1249] 4. Acquiring emotional information

[1250] Emotion engine: Recognizes user emotions in real time based on facial recognition, voice, gestures, etc.

[1251] Server: Receives the recognized emotion information and passes it to the AI ​​engine.

[1252] 5. Recipe Generation

[1253] Server: Calls the recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[1254] AI Engine: Adjusts recipe variations and suggestions based on emotional information from the Emotion Engine. It also evaluates the nutritional balance of generated recipes to ensure that calorie and salt content do not exceed specified limits. It repeats recipe generation and evaluation until it finds a recipe that meets the specified constraints.

[1255] 6. Results display

[1256] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[1257] User: Check the recipe and cooking instructions sent from the server through the device UI.

[1258] Specific examples

[1259] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[1260] 1. Cut the lettuce into bite-sized pieces.

[1261] 2. Thinly slice the tomatoes and cucumbers.

[1262] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1263] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1264] In this way, users can easily prepare healthy meals that take emotional information into account. Furthermore, recipes that take into account restrictions on calories and salt content are provided, helping users maintain their health. Taking emotional information into account allows recipes that suit the user's preferences to be suggested, improving cooking satisfaction.

[1265] The processing flow will be explained below.

[1266] Step 1:

[1267] The user enters basic information (allergies, likes and dislikes).

[1268] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[1269] Step 2:

[1270] The device sends basic information to the server.

[1271] The terminal transmits the input basic information to the server.

[1272] Step 3:

[1273] The server stores the user profile.

[1274] The server stores the received basic information in a database and manages it as a user profile.

[1275] Step 4:

[1276] The user inputs the ingredients to be used.

[1277] The user enters the ingredients they want to use this time into an input form on the terminal.

[1278] Step 5:

[1279] The terminal transmits information about ingredients used to the server.

[1280] The terminal transmits the input ingredient information to the server.

[1281] Step 6:

[1282] The server acquires the ingredient data.

[1283] The server retrieves the nutritional information of the specified foodstuff from the database.

[1284] Step 7:

[1285] The user inputs health restrictions.

[1286] Users input the health items they want to consider or limit (e.g., calorie limit 300 kcal, salt less than 1g) on ​​their device.

[1287] Step 8:

[1288] The device sends the health restriction items to the server.

[1289] The terminal transmits the entered health items to the server.

[1290] Step 9:

[1291] The server stores the health restriction conditions.

[1292] The server stores the received health restriction conditions in association with the user profile.

[1293] Step 10:

[1294] The emotion engine acquires emotion information.

[1295] The emotion engine uses facial recognition, voice, and gestures to recognize the user's emotions.

[1296] Step 11:

[1297] The device transmits the emotion information to the server.

[1298] The terminal transmits the acquired emotion information to the server.

[1299] Step 12:

[1300] The server invokes the recipe generation algorithm.

[1301] The server inputs ingredients, health restrictions, user profile, and emotional information into the AI ​​engine.

[1302] Step 13:

[1303] The AI ​​engine generates the appropriate recipe.

[1304] The AI ​​engine analyzes the input information and generates a recipe that meets the conditions and emotional information.

[1305] Step 14:

[1306] The server checks the recipe for suitability.

[1307] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[1308] Step 15:

[1309] The server sends the generated recipe to the device.

[1310] The server sends the matching recipe and cooking instructions to the user terminal.

[1311] Step 16:

[1312] The user checks the results.

[1313] The user checks the recipe and cooking instructions presented on the terminal.

[1314] Step 17:

[1315] The user starts cooking.

[1316] The user follows the instructions to start cooking.

[1317] Example 2

[1318] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1319] Conventional recipe generation systems only generate recipes by taking into account the user's allergies, likes and dislikes, and health restrictions. However, because they do not take into account the user's emotional information, there is a problem in that the satisfaction of the food is not sufficiently improved. Furthermore, even when generating recipes that take into account individual health, it is not possible to reflect emotional information.

[1320] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1321] In this invention, the server includes means for the user to input allergy information and likes and dislikes, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for acquiring the user's emotional information using an emotion engine, means for acquiring relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the acquired information, health restriction items, and emotional information, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate healthy cooking recipes that are individually tailored to the user's emotional information and provide a high level of satisfaction.

[1322] "Allergy information" is information indicating that a user has an allergic reaction to a specific food ingredient or component.

[1323] "Likes and dislikes information" is information about ingredients and dishes that the user likes and dislikes.

[1324] "Ingredients" is a list of ingredients used to make a dish.

[1325] "Health restriction items" are restriction conditions such as calories, salt, fat, sugar, etc., set according to the user's health condition.

[1326] An "emotion engine" is a system that recognizes emotions from a user's facial expressions, voice, gestures, etc.

[1327] "Nutrition information" refers to information about the calorie, fat, salt, sugar, and other contents of a particular food ingredient.

[1328] A "database" is a digital system for systematically organizing and storing information.

[1329] A "recipe generation algorithm" is a program that refers to the steps to create an optimal cooking recipe based on input information.

[1330] An "AI engine" is an artificial intelligence system used to analyze input information and achieve a specific purpose (in this case, generating cooking recipes).

[1331] A "cooking recipe" is a list of specific steps to follow when preparing a dish.

[1332] A "recipe" is information that includes a set of ingredients and instructions for combining them to make a dish.

[1333] "User interface (UI)" refers to the screens and input devices that allow a user to interact with a system.

[1334] A "server" is a computer system that processes information and provides services to other computers and devices over a network.

[1335] "Terminal" refers to a device such as a computer, smartphone, or tablet that is directly operated by a user.

[1336] The present invention provides a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments for carrying out the present invention will be described below.

[1337] User Interface

[1338] Users enter the following information using a device such as a smartphone, tablet, or PC:

[1339] Basic information: Allergy information, likes and dislikes

[1340] Ingredients: A list of the specific ingredients you would like to use.

[1341] Health restrictions: Calorie limits, salt, sugar, and fat restrictions

[1342] Emotion information: Emotion information recognized by the emotion engine

[1343] Database

[1344] The server manages the following databases:

[1345] Ingredient database: detailed nutritional information for each ingredient

[1346] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[1347] AI engine and emotion engine

[1348] The server generates recipes based on the information provided by the user using the following engines:

[1349] AI engine: Extracts nutritional information from a database and finds optimal combinations

[1350] Emotion engine: Recognizes user emotions through facial recognition, voice, gestures, etc., and reflects them in recipe generation

[1351] Example of a system

[1352] Specific processing flow

[1353] The user uses the device's UI to input that they are allergic to peanuts and that they like salads. The device sends this information to the server, which stores the received information in a database and creates a user profile.

[1354] Next, the user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast). The terminal sends this information to the server, which then retrieves the nutritional information for each ingredient from the ingredient database.

[1355] Furthermore, the user inputs health restrictions (calorie limit 300 kcal, salt limit 1 g or less). When the device sends this information to the server, the server associates the received restrictions with the user profile and saves them.

[1356] The emotion engine recognizes the user's emotions in real time from facial recognition, voice, and gestures, and sends the information to the server, which then passes it on to the AI ​​engine.

[1357] The server calls a recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates optimal recipes while taking emotional information into account. It evaluates nutritional balance and adjusts calorie and salt content so that they do not exceed specified limits.

[1358] The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device, where the user can view the cooking instructions through the device's UI.

[1359] Examples and prompts

[1360] For example, the generated recipe for "Healthy Grilled Chicken Salad" includes the following steps:

[1361] 1. Cut the lettuce into bite-sized pieces

[1362] 2. Thinly slice the tomatoes and cucumbers

[1363] 3. Grill the chicken breasts and cut them into bite-sized pieces.

[1364] 4. Mix lemon juice with a little olive oil to make a dressing and pour it over the salad.

[1365] Examples of prompts include:

[1366] "I'd like a healthy recipe. I would like to use lettuce, tomato, cucumber, and chicken breast. Calories should be under 300 kcal and salt should be under 1g."

[1367] This system allows users to easily prepare healthy meals that take emotional information into account, thus providing recipes tailored to individual health and emotional states, improving user satisfaction.

[1368] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1369] Step 1:

[1370] The user inputs allergy information and likes and dislikes using the device's UI. Specifically, the user inputs that they have a peanut allergy and that their favorite dish is salad. The device then sends the input information to the server.

[1371] Input: Allergy information (peanuts) and likes and dislikes (likes: salad)

[1372] Data processing: Formatting information and sending it to the server

[1373] Output: User profile stored on the server

[1374] Step 2:

[1375] The server stores the received basic information in a database. After receiving the information, it stores it in the database as a user profile.

[1376] Input: Basic information sent from the device

[1377] Data processing: Convert the information into a storage format and save it in a database

[1378] Output: Saved user profile (peanut allergy, favorite food is salad)

[1379] Step 3:

[1380] The user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast) through the device's UI. The device then sends this ingredient information to the server.

[1381] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[1382] Data processing: Formatting information and sending it to the server

[1383] Output: Ingredient information is sent to the server

[1384] Step 4:

[1385] The server acquires corresponding nutrition information from the ingredient database based on the input ingredient information.

[1386] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[1387] Data processing: Search and obtain corresponding nutritional information from food ingredient database

[1388] Output: Retrieved nutrition information (lettuce: 5 kcal, tomato: 18 kcal, cucumber: 16 kcal, chicken breast: 165 kcal)

[1389] Step 5:

[1390] The user inputs health restriction items (e.g., calorie limit 300 kcal, salt intake 1 g or less) through the device's UI. The device then sends this information to the server.

[1391] Input: Health restriction items (calorie limit 300 kcal, salt less than 1g)

[1392] Data processing: Formatting information and sending it to the server

[1393] Output: Health restrictions are sent to the server

[1394] Step 6:

[1395] The server receives the entered health restriction items and stores them in association with the user profile.

[1396] Input: Health restriction items (calories 300 kcal or less, salt 1g or less)

[1397] Data processing: Information is associated with user profiles and stored in a database

[1398] Output: Health restrictions saved in association with the user profile

[1399] Step 7:

[1400] The emotion engine recognizes emotions in real time from the user's facial recognition, voice, and gestures, and sends that information to the server.

[1401] Input: User's facial expressions, voice, and gestures

[1402] Data processing: Acquire emotional information through facial recognition, voice analysis, and gesture analysis

[1403] Output: Emotional information obtained (e.g., joy)

[1404] Step 8:

[1405] The server receives the emotional information and passes it to the AI ​​engine, which then generates recipes taking the emotional information into account.

[1406] Input: Emotional information, food information, health restrictions, user profile

[1407] Data processing: Execute recipe generation algorithm taking into account emotional information

[1408] Output: Generated recipe and cooking instructions

[1409] Step 9:

[1410] The server transmits the generated recipe and its cooking steps to the terminal.

[1411] Input: Generated recipe and cooking instructions

[1412] Data processing: Converting information into a format that can be sent to the user's device

[1413] Output: Recipe and cooking instructions sent to device

[1414] Step 10:

[1415] The user can view the recipe and cooking instructions sent to them through the device's UI, including instructions to cut the lettuce into bite-sized pieces, thinly slice the tomatoes and cucumbers, and grill and cut the chicken breasts into bite-sized pieces.

[1416] Input: Recipe and cooking instructions sent from the server

[1417] Output: Check the recipe and cooking instructions displayed on your device

[1418] (Application example 2)

[1419] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1420] Conventional recipe generation systems generate recipes based on the user's health restrictions and desired ingredient information, but they are unable to take into account the user's current emotional state. This makes it difficult to provide recipes that perfectly match the user's preferences, resulting in low satisfaction.

[1421] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input allergy information and likes and dislikes information, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for retrieving relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the retrieved information and health restriction items, means for recognizing user emotional information in real time, means for reflecting the recognized emotional information in recipe generation, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate health-conscious cooking recipes that reflect the user's emotional state, thereby improving user satisfaction.

[1422] The "means for the user to input information about allergies and likes and dislikes" is an interface through which the user inputs information about his or her own allergies and preferences.

[1423] The "means for inputting ingredients that the user wants to use" is an interface through which the user inputs information about ingredients that the user plans to use in the dish.

[1424] The "means for the user to input health restriction items" is an interface through which the user inputs information about health restrictions such as calories and salt content.

[1425] The "means for retrieving relevant information from a database containing nutritional information" is a function for retrieving information that matches the conditions entered by the user from a database that stores nutritional information.

[1426] "Means for using an AI engine to generate cooking recipes" refers to an algorithm that generates optimal cooking recipes based on information entered by the user.

[1427] "Means for recognizing the user's emotional information in real time" is a function that determines the user's emotional state from their facial expressions and tone of voice.

[1428] The "means for reflecting recognized emotional information in recipe generation" is a function that adjusts recipe suggestions taking into account the user's emotional state.

[1429] The "means for presenting the generated recipe and cooking steps to the user" is an interface that displays the finally generated recipe and cooking steps to the user.

[1430] The present invention provides a system for generating healthy cooking recipes that take into account the emotional information of a user. Specific embodiments of this system will be described below.

[1431] System configuration

[1432] 1. User Interface (UI)

[1433] The user enters the following information through the UI of the device (smartphone, tablet, PC, etc.):

[1434] Allergy information (e.g., peanut allergy)

[1435] Likes and dislikes (e.g., favorite food is salad, no dislikes)

[1436] A list of ingredients you would like to use (e.g. lettuce, tomato, cucumber, chicken breast)

[1437] Health restrictions (e.g., calorie limit 300 kcal, salt limit 1g or less)

[1438] 2. Database

[1439] The server manages a database that stores the following information:

[1440] Food database: Detailed nutritional information for each food ingredient (calories, fat, salt, sugar, etc.)

[1441] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[1442] 3. AI Engine and Emotion Engine

[1443] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[1444] Specific examples of hardware and software used

[1445] Smart glasses: Used by field staff to scan customers' faces and obtain emotional information in real time.

[1446] Flask: A lightweight Python-based web application framework that acts as a server and receives user data and facial information.

[1447] OpenCV: A computer vision library, used for face recognition.

[1448] Keras: A deep learning library used to build emotion recognition models.

[1449] Data Processing and Computation

[1450] 1. Face Recognition: The smart glasses capture the customer's face, and then use OpenCV to detect the face and Keras models to recognize emotions.

[1451] 2. Emotion Recognition: Captured facial images are fed into a deep learning model to determine the emotional state.

[1452] 3. Recipe generation: The AI ​​engine generates optimal recipes based on the user's health restrictions and perceived emotions.

[1453] Examples and prompts

[1454] To illustrate, consider the following scenario in a cafe:

[1455] A cafe staff member wears smart glasses and says to the customer, "Hello, are you looking for today's specials?" The smart glasses capture the customer's facial expressions, which are then analyzed by an emotion engine. For example, if the customer expresses the emotion "happy," the Smart Healthy Cafe Assistant will suggest "marinated salmon." This recipe also takes into account the customer's health restrictions (e.g., a calorie limit of 300 kcal).

[1456] Example prompt sentence:

[1457] "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts"

[1458] In this way, a recipe suggestion system that takes emotional information into account improves customer satisfaction.

[1459] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1460] Step 1:

[1461] The user uses the device's user interface (UI) to input their allergy information, likes and dislikes, ingredients they want to use, and health restrictions. This input information is sent from the device to the server, which then packages the information in JSON or other appropriate format and sends it to the server.

[1462] Step 2:

[1463] The server receives user input information sent from the device. The received information is analyzed and information such as allergies, likes and dislikes, ingredients desired to use, and health restrictions is sorted into appropriate fields. This information is then saved in a database as a user profile.

[1464] Step 3:

[1465] The server retrieves the corresponding nutritional information from the ingredient database based on the information about the ingredients the user wants to use. Specifically, nutritional information such as calories, fat, salt, and sugar for lettuce, tomato, cucumber, and chicken breast is retrieved from the database. This completes the available information.

[1466] Step 4:

[1467] The server receives the user's health restriction information and associates it with the user profile. For example, if restrictions are set such as "calorie limit 300 kcal, salt intake 1g or less," this information is added to the user profile. Subsequent data processing is based on this information.

[1468] Step 5:

[1469] The server uses an emotion engine to recognize real-time user emotion information obtained from smart glasses, etc. The emotion engine analyzes the user's facial expressions, voice, gestures, etc., and recognizes whether the user is in an emotional state such as "happy," "sad," or "neutral." This emotion information is then sent to the server.

[1470] Step 6:

[1471] The server uses an AI engine to generate optimal cooking recipes based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions. It also incorporates emotional information from the emotional engine to suggest recipes that suit the user's emotional state. The generated recipes are also evaluated to see if they meet calorie and salt restrictions.

[1472] Step 7:

[1473] The server sends the successfully generated recipe and its cooking instructions to the device. For example, if a recipe for a healthy grilled chicken salad is generated, the server presents the user with information including the specific cooking instructions (e.g., cut the lettuce into bite-sized pieces, thinly slice the tomato and cucumber, etc.). The user can confirm this information through the device's UI.

[1474] Specific examples of operation

[1475] As an example of a prompt, if "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts" is entered, the server will pass the image file to the emotion engine, determine the user's emotional state as "happy," and then generate an appropriate recipe such as "marinated salmon," taking into account sugar and salt restrictions and presenting the final recipe.

[1476] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1477] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1478] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1479] [Fourth embodiment]

[1480] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1481] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1482] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1483] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1484] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1485] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1486] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1487] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1488] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1489] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1490] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1491] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1492] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1493] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user on a terminal on a server, and generates recipes using an AI engine.

[1494] System configuration

[1495] 1. User Interface (UI)

[1496] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1497] Basic information: User's allergies, likes and dislikes.

[1498] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1499] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1500] 2. Database

[1501] The server manages an ingredient database and a recipe database.

[1502] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1503] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1504] 3. AI Engine

[1505] The server uses the input information to generate recipes that meet the specified health restrictions using an AI engine that pulls nutritional information from a database to find the optimal combination.

[1506] Program processing

[1507] 1. Enter basic user information

[1508] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[1509] Server: Receives the basic information sent and stores it in a database as a user profile.

[1510] 2. Enter ingredients used

[1511] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[1512] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[1513] 3. Enter health restrictions

[1514] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[1515] Server: Receives the entered health restrictions and stores them in association with the user profile.

[1516] 4. Recipe Generation

[1517] Server: Calls the recipe generation algorithm based on the acquired ingredient information, user profile, and health restrictions. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[1518] AI engine: Evaluates the nutritional balance of the generated recipes and ensures that the calorie and salt content does not exceed the specified limits. It repeats the process of generating and evaluating recipes until it finds a recipe that meets the specified limits.

[1519] 5. Display results

[1520] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[1521] User: Check the recipe and cooking instructions sent from the server through the device UI.

[1522] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[1523] 1. Cut the lettuce into bite-sized pieces.

[1524] 2. Thinly slice the tomatoes and cucumbers.

[1525] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1526] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1527] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[1528] The processing flow will be explained below.

[1529] Step 1:

[1530] The user enters basic information (allergies, likes and dislikes).

[1531] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[1532] Step 2:

[1533] The device sends basic information to the server.

[1534] The terminal transmits the input basic information to the server.

[1535] Step 3:

[1536] The server stores the user profile.

[1537] The server stores the received basic information in a database and manages it as a user profile.

[1538] Step 4:

[1539] The user inputs the ingredients to be used.

[1540] The user enters the ingredients they want to use this time into an input form on the terminal.

[1541] Step 5:

[1542] The terminal transmits information about ingredients used to the server.

[1543] The terminal transmits the input ingredient information to the server.

[1544] Step 6:

[1545] The server acquires the ingredient data.

[1546] The server retrieves the nutritional information of the specified foodstuff from the database.

[1547] Step 7:

[1548] The user inputs health restrictions.

[1549] Users input the health items they want to consider or restrict (calorie limits, salt, sugar, fat restrictions, etc.) into the device.

[1550] Step 8:

[1551] The device sends the health restriction items to the server.

[1552] The terminal transmits the entered health items to the server.

[1553] Step 9:

[1554] The server stores the health restriction conditions.

[1555] The server stores the received health restriction conditions in association with the user profile.

[1556] Step 10:

[1557] The server invokes the recipe generation algorithm.

[1558] The server starts the AI ​​engine by inputting information on ingredients, health restrictions, and user profile.

[1559] Step 11:

[1560] The AI ​​engine generates the appropriate recipe.

[1561] The AI ​​engine analyzes the input data and generates a recipe that meets the conditions.

[1562] Step 12:

[1563] The server checks the recipe for suitability.

[1564] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[1565] Step 13:

[1566] The server sends the generated recipe to the device.

[1567] The server sends the matching recipe and cooking instructions to the user terminal.

[1568] Step 14:

[1569] The user checks the results.

[1570] The user checks the recipe and cooking instructions presented on the terminal.

[1571] Step 15:

[1572] The user starts cooking.

[1573] The user follows the instructions to start cooking.

[1574] Example 1

[1575] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1576] In modern society, there is a demand for easy and fast provision of cooking recipes that suit individual health conditions and preferences. In particular, it has been difficult for conventional systems to automatically generate recipes that accommodate allergies and health restrictions (e.g., restrictions on calories, salt, sugar, and fat) and evaluate the nutritional balance of those recipes. Therefore, there is a need for a system that allows users to easily select dishes that suit their preferences while taking their health conditions into consideration.

[1577] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1578] In this invention, the server includes: means for a user to input allergy information and likes and dislikes; means for a user to input ingredients that the user wants to use; means for a user to input health restrictions; means for retrieving relevant information from a database containing nutritional information based on the input information; means for using an AI engine to generate cooking recipes based on the retrieved information and health restrictions; means for evaluating the nutritional balance of the generated cooking recipes and repeating the generation and evaluation of recipes until a recipe that meets the specified restrictions is found; and means for presenting the generated cooking recipes and cooking procedures to the user. This allows users to quickly and easily obtain recipes that meet their allergies and health restrictions.

[1579] A "user" is an individual who uses the system to obtain cooking recipes.

[1580] "Allergy information" refers to information about whether a user has an allergic reaction to a particular food.

[1581] "Likes and dislikes information" refers to information about the dishes that the user likes and dislikes.

[1582] An "ingredient" is a specific food that a user wishes to use.

[1583] "Health restriction items" refer to conditions related to upper limits on calories, salt, sugar, fat, and other nutritional restrictions that are set with the user's health in mind.

[1584] "Nutrition information" refers to information about the nutritional components of food ingredients, such as calories, fat, salt, and sugar.

[1585] A "database" is an information system for storing ingredients, recipes, and their nutritional information.

[1586] An "AI engine" is an artificial intelligence that generates cooking recipes that meet the conditions based on input information and evaluates nutritional balance.

[1587] A "recipe generation algorithm" is a computational method used by an AI engine to find the optimal recipe based on input information.

[1588] "Cooking steps" refer to the specific cooking steps required to complete the generated cooking recipe.

[1589] This invention provides a system that generates healthy cooking recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. This system analyzes information entered by the user using a terminal on a server, and generates recipes using an AI engine. Specific embodiments for implementing this system are described below.

[1590] System Configuration

[1591] 1. User Interface (UI)

[1592] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1593] Allergy information: For example, peanut allergy.

[1594] Likes and dislikes: For example, your favorite food is salad, and you don't have any disliked food.

[1595] Ingredients: A list of ingredients you would like to use, for example, lettuce, tomato, cucumber, chicken breast, etc.

[1596] Health restrictions: For example, calorie limit of 300 kcal, salt limit of 1g, etc.

[1597] 2. Database

[1598] The server manages an ingredient database and a recipe database.

[1599] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1600] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1601] 3. AI Engine

[1602] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine retrieves nutritional information from a database and finds the optimal combination. It also evaluates the nutritional balance of the generated recipes to ensure that the calorie and salt content does not exceed the specified upper limit. Recipe generation and evaluation are repeated until a recipe that meets the specified restrictions is found.

[1603] Specific examples

[1604] For example, you can enter:

[1605] Allergy Information: Peanut Allergy

[1606] Likes and dislikes: Favorite food is salad, dislikes nothing

[1607] Ingredients: lettuce, tomato, cucumber, chicken breast

[1608] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[1609] Based on that, the following recipe is generated:

[1610] Recipe Name: Healthy Grilled Chicken Salad

[1611] Cooking Instructions:

[1612] 1. Cut the lettuce into bite-sized pieces.

[1613] 2. Thinly slice the tomatoes and cucumbers.

[1614] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1615] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1616] This process allows users to quickly and easily find recipes that accommodate their allergies and health restrictions, allowing them to enjoy food that suits their tastes while maintaining their health.

[1617] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1618] Step 1:

[1619] The user enters allergy information and likes and dislikes.

[1620] Specific operation: The user enters their allergy information (e.g., peanut allergy) and favorite food information (e.g., favorite food is salad, no disliked food) into the device's UI. The entered information is sent from the device to the server.

[1621] Input: Allergy information and food preferences

[1622] Output: User information sent to the server

[1623] Step 2:

[1624] The user inputs the ingredients they want to use.

[1625] Specific operation: The user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast) into the device's UI. The input information is sent from the device to the server.

[1626] Input: List of ingredients you want to use

[1627] Output: Ingredient information sent to the server

[1628] Step 3:

[1629] The user inputs health restrictions.

[1630] Specific operation: The user inputs health restrictions (e.g., calorie limit 300 kcal, salt intake 1g or less) into the device's UI. The input information is sent from the device to the server.

[1631] Input: Health Restrictions

[1632] Output: Health restrictions sent to the server

[1633] Step 4:

[1634] The server retrieves nutritional information from a database based on the transmitted information.

[1635] Specific operation: The server receives the user's allergy information, preference information, ingredient list, and health restrictions, and retrieves the nutritional information for each ingredient from the ingredient database.

[1636] Input: User information, food ingredients, and health restrictions sent to the server

[1637] Output: Nutritional information of the ingredients obtained

[1638] Step 5:

[1639] The server uses an AI engine to generate cooking recipes based on the acquired information and health restrictions.

[1640] Specific operation: The server launches an AI engine to generate suitable recipes based on the acquired nutritional information and health restrictions. The AI ​​engine uses a recipe generation algorithm to find the optimal combination. It repeats the process of generating and evaluating recipes until it finds one that meets the specified restrictions.

[1641] Input: Obtained nutritional information, health restrictions

[1642] Output: The generated recipe

[1643] Step 6:

[1644] The server presents the generated recipe and cooking instructions to the user.

[1645] Specific operation: The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device. The user can view the recipe and instructions through the device's UI.

[1646] Input: Generated recipe

[1647] Output: Recipe and cooking instructions displayed on the user's device

[1648] This series of steps allows users to easily obtain recipes that take into consideration their allergies and health restrictions.

[1649] (Application example 1)

[1650] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1651] In modern society, many people want to enjoy healthy meals, but at the same time, maintaining a balanced diet in a busy lifestyle can be difficult. Finding appropriate recipes can be especially challenging for people with allergies or health restrictions. Furthermore, many users want simple, healthy meals using specific ingredients, but there is a lack of systems that can meet these needs.

[1652] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1653] In this invention, the server includes a means for the user to input allergy information and likes and dislikes, a means for the user to input ingredients the user wants to use, and a means for the user to input health restriction items. This makes it possible to suggest healthy, nutritionally balanced dishes through an application installed on a smartphone that uses the information input by the user to suggest health-conscious recipes.

[1654] The "means for the user to input information about allergies and likes and dislikes" is an interface that allows the user to input information about his or her own allergies, preferences, and disliked foods.

[1655] The "means for inputting ingredients that the user wants to use" is an interface that allows the user to input the specific ingredients that the user wants to use in the current dish.

[1656] The "means for the user to input health restrictions" is an interface that allows the user to input health-related restrictions such as calorie limits, salt, sugar, and fat.

[1657] The "means for obtaining corresponding information from a database containing nutritional information based on the input information" is a program for analyzing the information input by the user and obtaining corresponding information from a database containing nutritional information.

[1658] "Means for using an AI engine to generate cooking recipes based on the acquired information and health restrictions" refers to a program that uses an artificial intelligence engine to generate optimal cooking recipes based on nutritional information and health restrictions acquired from a database.

[1659] The "means for presenting the generated recipe and cooking steps to the user" is an interface for displaying the recipe and cooking steps generated by the AI ​​engine to the user.

[1660] "Means that operate as an application installed on a smartphone and use information entered by the user to suggest healthy recipes" refers to an application that operates on a smartphone to suggest healthy recipes using information entered by the user.

[1661] This invention provides a system that generates healthy recipes based on specific ingredients and health restrictions, and presents the cooking steps to the user. The system includes a user interface, a database, an AI engine, and a means for displaying the results.

[1662] 1. User Interface (UI)

[1663] Users can enter the following information through a smartphone application:

[1664] Basic information: User's allergies, likes and dislikes.

[1665] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1666] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1667] 2. Database

[1668] The server manages a database containing nutritional information:

[1669] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1670] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1671] 3. AI Engine

[1672] The server uses an AI engine based on the input information to generate recipes that meet the specified health restrictions. The AI ​​engine is configured using the following software and tools:

[1673] AI engine: TensorFlow or PyTorch

[1674] API server: Django (server-side API management)

[1675] 4. Results display

[1676] The generated recipes and cooking instructions are displayed to the user through a smartphone application. The user can easily create dishes that meet health restrictions based on the provided recipes. The results are displayed by the following means:

[1677] Specific examples

[1678] For example, if a user enters the following information:

[1679] Allergy Information: Peanut Allergy

[1680] Likes and dislikes: Favorite food is salad, dislikes nothing

[1681] Ingredients: lettuce, tomato, cucumber, chicken breast

[1682] Health restrictions: Calorie limit 300 kcal, salt limit 1g or less

[1683] Using this information, the AI ​​engine generates a recipe for a "Healthy Grilled Chicken Salad" and displays it on the user's smartphone along with cooking instructions. Specifically, the following steps are presented:

[1684] 1. Cut the lettuce into bite-sized pieces.

[1685] 2. Thinly slice the tomatoes and cucumbers.

[1686] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1687] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1688] In this way, users can easily prepare healthy meals, and the recipes provided take into account restrictions on calories, salt, etc., helping them to maintain their health.

[1689] Example prompts to input to the generative AI model

[1690] User Allergy Information: Peanut Allergy

[1691] Likes and dislikes: Favorite food is salad, dislikes nothing

[1692] Ingredients: lettuce, tomato, cucumber, chicken breast

[1693] Healthy Restrictions: Calorie limit 300 kcal, salt less than 1g

[1694] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1695] Step 1:

[1696] Users use a smartphone application to input their allergy information and likes and dislikes. The input basic information is sent by the device to a server and stored in a database on the server. The basic information includes peanut allergies, favorite dishes (e.g., salad), and disliked dishes (e.g., none). This information is stored in the database as a user profile.

[1697] Step 2:

[1698] Users input the ingredients they want to use through a smartphone application. The input ingredients are sent to the server via the device, and nutritional information about the ingredients is retrieved from the ingredient database. For example, if lettuce, tomato, cucumber, and chicken breast are input as ingredients, detailed nutritional information about these ingredients, such as calories, fat, salt, and sugar, is retrieved. This information becomes the basic data for recipe generation by the AI ​​engine.

[1699] Step 3:

[1700] Users input their health restrictions via a smartphone application. The entered health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less) are sent to the server via the device, associated with the user profile, and stored in a database. This data is used as a restriction that the AI ​​engine takes into account when generating recipes.

[1701] Step 4:

[1702] The AI ​​engine generates optimal cooking recipes based on basic information stored on the server, nutritional information for ingredients used, and health restrictions. The server passes input data to the AI ​​engine, which analyzes this information and generates recipes that fit the conditions. For example, a recipe for "Healthy Grilled Chicken Salad" using lettuce, tomato, cucumber, and chicken breast is generated. Machine learning engines such as TensorFlow or PyTorch are used in this process.

[1703] Step 5:

[1704] The server sends the generated recipe and cooking instructions to the device. The user can then view the recipe and cooking instructions sent from the server through a smartphone application. For example, for "Healthy Grilled Chicken Salad," the following steps are displayed:

[1705] 1. Cut the lettuce into bite-sized pieces.

[1706] 2. Thinly slice the tomatoes and cucumbers.

[1707] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1708] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1709] In this way, users can easily prepare healthy meals.

[1710] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1711] This invention is a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments of this system are described below.

[1712] System configuration

[1713] 1. User Interface (UI)

[1714] The user enters the following information through the user interface of the device (smartphone, tablet, PC, etc.):

[1715] Basic information: User's allergies, likes and dislikes.

[1716] Ingredients Used: A list of the specific ingredients you would like to use this time.

[1717] Health restrictions: Calorie limits, salt, sugar and fat restrictions.

[1718] Emotion information: Recognizes user emotions using an emotion engine.

[1719] 2. Database

[1720] The server manages an ingredient database and a recipe database.

[1721] Ingredient database: Stores detailed nutritional information for each ingredient (calories, fat, salt, sugar, etc.).

[1722] Recipe database: Stores existing recipe information, cooking steps, and ingredients used.

[1723] 3. AI Engine and Emotion Engine

[1724] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[1725] Program processing

[1726] 1. Enter basic user information

[1727] User: Using the device's UI, the user enters their allergy information (e.g., peanut allergy) and likes and dislikes (e.g., favorite food is salad, no dislikes). The device then sends this information to the server.

[1728] Server: Receives the basic information sent and stores it in a database as a user profile.

[1729] 2. Enter ingredients used

[1730] User: Using the device's UI, the user inputs the ingredients they want to use this time (e.g., lettuce, tomato, cucumber, chicken breast). The device then sends this information to the server.

[1731] Server: Receives the input ingredient information and retrieves the corresponding nutritional information from the ingredient database.

[1732] 3. Enter health restrictions

[1733] User: Using the device's UI, the user enters health restrictions (e.g., calorie limit 300 kcal, salt limit 1 g or less). The device then sends this information to the server.

[1734] Server: Receives the entered health restrictions and stores them in association with the user profile.

[1735] 4. Acquiring emotional information

[1736] Emotion engine: Recognizes user emotions in real time based on facial recognition, voice, gestures, etc.

[1737] Server: Receives the recognized emotion information and passes it to the AI ​​engine.

[1738] 5. Recipe Generation

[1739] Server: Calls the recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions.

[1740] AI Engine: Adjusts recipe variations and suggestions based on emotional information from the Emotion Engine. It also evaluates the nutritional balance of generated recipes to ensure that calorie and salt content do not exceed specified limits. It repeats recipe generation and evaluation until it finds a recipe that meets the specified constraints.

[1741] 6. Results display

[1742] Server: Sends the successfully generated recipe (e.g., Healthy Grilled Chicken Salad) and cooking instructions to the device.

[1743] User: Check the recipe and cooking instructions sent from the server through the device UI.

[1744] Specific examples

[1745] For example, if a recipe for a healthy grilled chicken salad is generated, the following steps are presented:

[1746] 1. Cut the lettuce into bite-sized pieces.

[1747] 2. Thinly slice the tomatoes and cucumbers.

[1748] 3. Grill the chicken breasts and cut into bite-sized pieces.

[1749] 4. For the dressing, mix lemon juice with a little olive oil and drizzle over the salad.

[1750] In this way, users can easily prepare healthy meals that take emotional information into account. Furthermore, recipes that take into account restrictions on calories and salt content are provided, helping users maintain their health. Taking emotional information into account allows recipes that suit the user's preferences to be suggested, improving cooking satisfaction.

[1751] The processing flow will be explained below.

[1752] Step 1:

[1753] The user enters basic information (allergies, likes and dislikes).

[1754] Users enter information about allergies, favorite dishes, and disliked dishes into an input form on their device (smartphone, PC, etc.).

[1755] Step 2:

[1756] The device sends basic information to the server.

[1757] The terminal transmits the input basic information to the server.

[1758] Step 3:

[1759] The server stores the user profile.

[1760] The server stores the received basic information in a database and manages it as a user profile.

[1761] Step 4:

[1762] The user inputs the ingredients to be used.

[1763] The user enters the ingredients they want to use this time into an input form on the terminal.

[1764] Step 5:

[1765] The terminal transmits information about ingredients used to the server.

[1766] The terminal transmits the input ingredient information to the server.

[1767] Step 6:

[1768] The server acquires the ingredient data.

[1769] The server retrieves the nutritional information of the specified foodstuff from the database.

[1770] Step 7:

[1771] The user inputs health restrictions.

[1772] Users input the health items they want to consider or limit (e.g., calorie limit 300 kcal, salt less than 1g) on ​​their device.

[1773] Step 8:

[1774] The device sends the health restriction items to the server.

[1775] The terminal transmits the entered health items to the server.

[1776] Step 9:

[1777] The server stores the health restriction conditions.

[1778] The server stores the received health restriction conditions in association with the user profile.

[1779] Step 10:

[1780] The emotion engine acquires emotion information.

[1781] The emotion engine uses facial recognition, voice, and gestures to recognize the user's emotions.

[1782] Step 11:

[1783] The device transmits the emotion information to the server.

[1784] The terminal transmits the acquired emotion information to the server.

[1785] Step 12:

[1786] The server invokes the recipe generation algorithm.

[1787] The server inputs ingredients, health restrictions, user profile, and emotional information into the AI ​​engine.

[1788] Step 13:

[1789] The AI ​​engine generates the appropriate recipe.

[1790] The AI ​​engine analyzes the input information and generates a recipe that meets the conditions and emotional information.

[1791] Step 14:

[1792] The server checks the recipe for suitability.

[1793] The server checks whether the generated recipe meets the specified health constraints, and if not, regenerates a new recipe.

[1794] Step 15:

[1795] The server sends the generated recipe to the device.

[1796] The server sends the matching recipe and cooking instructions to the user terminal.

[1797] Step 16:

[1798] The user checks the results.

[1799] The user checks the recipe and cooking instructions presented on the terminal.

[1800] Step 17:

[1801] The user starts cooking.

[1802] The user follows the instructions to start cooking.

[1803] Example 2

[1804] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1805] Conventional recipe generation systems only generate recipes by taking into account the user's allergies, likes and dislikes, and health restrictions. However, because they do not take into account the user's emotional information, there is a problem in that the satisfaction of the food is not sufficiently improved. Furthermore, even when generating recipes that take into account individual health, it is not possible to reflect emotional information.

[1806] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1807] In this invention, the server includes means for the user to input allergy information and likes and dislikes, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for acquiring the user's emotional information using an emotion engine, means for acquiring relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the acquired information, health restriction items, and emotional information, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate healthy cooking recipes that are individually tailored to the user's emotional information and provide a high level of satisfaction.

[1808] "Allergy information" is information indicating that a user has an allergic reaction to a specific food ingredient or component.

[1809] "Likes and dislikes information" is information about ingredients and dishes that the user likes and dislikes.

[1810] "Ingredients" is a list of ingredients used to make a dish.

[1811] "Health restriction items" are restriction conditions such as calories, salt, fat, sugar, etc., set according to the user's health condition.

[1812] An "emotion engine" is a system that recognizes emotions from a user's facial expressions, voice, gestures, etc.

[1813] "Nutrition information" refers to information about the calorie, fat, salt, sugar, and other contents of a particular food ingredient.

[1814] A "database" is a digital system for systematically organizing and storing information.

[1815] A "recipe generation algorithm" is a program that refers to the steps to create an optimal cooking recipe based on input information.

[1816] An "AI engine" is an artificial intelligence system used to analyze input information and achieve a specific purpose (in this case, generating cooking recipes).

[1817] A "cooking recipe" is a list of specific steps to follow when preparing a dish.

[1818] A "recipe" is information that includes a set of ingredients and instructions for combining them to make a dish.

[1819] "User interface (UI)" refers to the screens and input devices that allow a user to interact with a system.

[1820] A "server" is a computer system that processes information and provides services to other computers and devices over a network.

[1821] "Terminal" refers to a device such as a computer, smartphone, or tablet that is directly operated by a user.

[1822] The present invention provides a system that generates health-conscious cooking recipes based on specific ingredients and health restrictions, presents the cooking steps to the user, and also recognizes the user's emotional information using an emotion engine and reflects this in the recipe generation. Specific embodiments for carrying out the present invention will be described below.

[1823] User Interface

[1824] Users enter the following information using a device such as a smartphone, tablet, or PC:

[1825] Basic information: Allergy information, likes and dislikes

[1826] Ingredients: A list of the specific ingredients you would like to use.

[1827] Health restrictions: Calorie limits, salt, sugar, and fat restrictions

[1828] Emotion information: Emotion information recognized by the emotion engine

[1829] Database

[1830] The server manages the following databases:

[1831] Ingredient database: detailed nutritional information for each ingredient

[1832] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[1833] AI engine and emotion engine

[1834] The server generates recipes based on the information provided by the user using the following engines:

[1835] AI engine: Extracts nutritional information from a database and finds optimal combinations

[1836] Emotion engine: Recognizes user emotions through facial recognition, voice, gestures, etc., and reflects them in recipe generation

[1837] Example of a system

[1838] Specific processing flow

[1839] The user uses the device's UI to input that they are allergic to peanuts and that they like salads. The device sends this information to the server, which stores the received information in a database and creates a user profile.

[1840] Next, the user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast). The terminal sends this information to the server, which then retrieves the nutritional information for each ingredient from the ingredient database.

[1841] Furthermore, the user inputs health restrictions (calorie limit 300 kcal, salt limit 1 g or less). When the device sends this information to the server, the server associates the received restrictions with the user profile and saves them.

[1842] The emotion engine recognizes the user's emotions in real time from facial recognition, voice, and gestures, and sends the information to the server, which then passes it on to the AI ​​engine.

[1843] The server calls a recipe generation algorithm based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates optimal recipes while taking emotional information into account. It evaluates nutritional balance and adjusts calorie and salt content so that they do not exceed specified limits.

[1844] The server sends the generated recipe (e.g., Healthy Grilled Chicken Salad) and its cooking instructions to the device, where the user can view the cooking instructions through the device's UI.

[1845] Examples and prompts

[1846] For example, the generated recipe for "Healthy Grilled Chicken Salad" includes the following steps:

[1847] 1. Cut the lettuce into bite-sized pieces

[1848] 2. Thinly slice the tomatoes and cucumbers

[1849] 3. Grill the chicken breasts and cut them into bite-sized pieces.

[1850] 4. Mix lemon juice with a little olive oil to make a dressing and pour it over the salad.

[1851] Examples of prompts include:

[1852] "I'd like a healthy recipe. I would like to use lettuce, tomato, cucumber, and chicken breast. Calories should be under 300 kcal and salt should be under 1g."

[1853] This system allows users to easily prepare healthy meals that take emotional information into account, thus providing recipes tailored to individual health and emotional states, improving user satisfaction.

[1854] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1855] Step 1:

[1856] The user inputs allergy information and likes and dislikes using the device's UI. Specifically, the user inputs that they have a peanut allergy and that their favorite dish is salad. The device then sends the input information to the server.

[1857] Input: Allergy information (peanuts) and likes and dislikes (likes: salad)

[1858] Data processing: Formatting information and sending it to the server

[1859] Output: User profile stored on the server

[1860] Step 2:

[1861] The server stores the received basic information in a database. After receiving the information, it stores it in the database as a user profile.

[1862] Input: Basic information sent from the device

[1863] Data processing: Convert the information into a storage format and save it in a database

[1864] Output: Saved user profile (peanut allergy, favorite food is salad)

[1865] Step 3:

[1866] The user inputs the ingredients they want to use this time (lettuce, tomato, cucumber, chicken breast) through the device's UI. The device then sends this ingredient information to the server.

[1867] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[1868] Data processing: Formatting information and sending it to the server

[1869] Output: Ingredient information is sent to the server

[1870] Step 4:

[1871] The server acquires corresponding nutrition information from the ingredient database based on the input ingredient information.

[1872] Input: Ingredient information (lettuce, tomato, cucumber, chicken breast)

[1873] Data processing: Search and obtain corresponding nutritional information from food ingredient database

[1874] Output: Retrieved nutrition information (lettuce: 5 kcal, tomato: 18 kcal, cucumber: 16 kcal, chicken breast: 165 kcal)

[1875] Step 5:

[1876] The user inputs health restriction items (e.g., calorie limit 300 kcal, salt intake 1 g or less) through the device's UI. The device then sends this information to the server.

[1877] Input: Health restriction items (calorie limit 300 kcal, salt less than 1g)

[1878] Data processing: Formatting information and sending it to the server

[1879] Output: Health restrictions are sent to the server

[1880] Step 6:

[1881] The server receives the entered health restriction items and stores them in association with the user profile.

[1882] Input: Health restriction items (calories 300 kcal or less, salt 1g or less)

[1883] Data processing: Information is associated with user profiles and stored in a database

[1884] Output: Health restrictions saved in association with the user profile

[1885] Step 7:

[1886] The emotion engine recognizes emotions in real time from the user's facial recognition, voice, and gestures, and sends that information to the server.

[1887] Input: User's facial expressions, voice, and gestures

[1888] Data processing: Acquire emotional information through facial recognition, voice analysis, and gesture analysis

[1889] Output: Emotional information obtained (e.g., joy)

[1890] Step 8:

[1891] The server receives the emotional information and passes it to the AI ​​engine, which then generates recipes taking the emotional information into account.

[1892] Input: Emotional information, food information, health restrictions, user profile

[1893] Data processing: Execute recipe generation algorithm taking into account emotional information

[1894] Output: Generated recipe and cooking instructions

[1895] Step 9:

[1896] The server transmits the generated recipe and its cooking steps to the terminal.

[1897] Input: Generated recipe and cooking instructions

[1898] Data processing: Converting information into a format that can be sent to the user's device

[1899] Output: Recipe and cooking instructions sent to device

[1900] Step 10:

[1901] The user can view the recipe and cooking instructions sent to them through the device's UI, including instructions to cut the lettuce into bite-sized pieces, thinly slice the tomatoes and cucumbers, and grill and cut the chicken breasts into bite-sized pieces.

[1902] Input: Recipe and cooking instructions sent from the server

[1903] Output: Check the recipe and cooking instructions displayed on your device

[1904] (Application example 2)

[1905] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1906] Conventional recipe generation systems generate recipes based on the user's health restrictions and desired ingredient information, but they are unable to take into account the user's current emotional state. This makes it difficult to provide recipes that perfectly match the user's preferences, resulting in low satisfaction.

[1907] The specification process by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for the user to input allergy information and likes and dislikes information, means for the user to input ingredients that the user wants to use, means for the user to input health restriction items, means for retrieving relevant information from a database containing nutritional information based on the input information, means for using an AI engine to generate cooking recipes based on the retrieved information and health restriction items, means for recognizing user emotional information in real time, means for reflecting the recognized emotional information in recipe generation, and means for presenting the generated cooking recipes and cooking procedures to the user. This makes it possible to generate health-conscious cooking recipes that reflect the user's emotional state, thereby improving user satisfaction.

[1908] The "means for the user to input information about allergies and likes and dislikes" is an interface through which the user inputs information about his or her own allergies and preferences.

[1909] The "means for inputting ingredients that the user wants to use" is an interface through which the user inputs information about ingredients that the user plans to use in the dish.

[1910] The "means for the user to input health restriction items" is an interface through which the user inputs information about health restrictions such as calories and salt content.

[1911] The "means for retrieving relevant information from a database containing nutritional information" is a function for retrieving information that matches the conditions entered by the user from a database that stores nutritional information.

[1912] "Means for using an AI engine to generate cooking recipes" refers to an algorithm that generates optimal cooking recipes based on information entered by the user.

[1913] "Means for recognizing the user's emotional information in real time" is a function that determines the user's emotional state from their facial expressions and tone of voice.

[1914] The "means for reflecting recognized emotional information in recipe generation" is a function that adjusts recipe suggestions taking into account the user's emotional state.

[1915] The "means for presenting the generated recipe and cooking steps to the user" is an interface that displays the finally generated recipe and cooking steps to the user.

[1916] The present invention provides a system for generating healthy cooking recipes that take into account the emotional information of a user. Specific embodiments of this system will be described below.

[1917] System configuration

[1918] 1. User Interface (UI)

[1919] The user enters the following information through the UI of the device (smartphone, tablet, PC, etc.):

[1920] Allergy information (e.g., peanut allergy)

[1921] Likes and dislikes (e.g., favorite food is salad, no dislikes)

[1922] A list of ingredients you would like to use (e.g. lettuce, tomato, cucumber, chicken breast)

[1923] Health restrictions (e.g., calorie limit 300 kcal, salt limit 1g or less)

[1924] 2. Database

[1925] The server manages a database that stores the following information:

[1926] Food database: Detailed nutritional information for each food ingredient (calories, fat, salt, sugar, etc.)

[1927] Recipe database: Existing recipe information, cooking procedures, and ingredients used

[1928] 3. AI Engine and Emotion Engine

[1929] The server uses an AI engine and an emotion engine based on the input information to generate healthy recipes that take emotional information into account. The AI ​​engine extracts nutritional information from a database and finds the optimal combination. The emotion engine recognizes the user's emotions through facial recognition, voice, gestures, etc. and reflects them in the recipe suggestions.

[1930] Specific examples of hardware and software used

[1931] Smart glasses: Used by field staff to scan customers' faces and obtain emotional information in real time.

[1932] Flask: A lightweight Python-based web application framework that acts as a server and receives user data and facial information.

[1933] OpenCV: A computer vision library, used for face recognition.

[1934] Keras: A deep learning library used to build emotion recognition models.

[1935] Data Processing and Computation

[1936] 1. Face Recognition: The smart glasses capture the customer's face, and then use OpenCV to detect the face and Keras models to recognize emotions.

[1937] 2. Emotion Recognition: Captured facial images are fed into a deep learning model to determine the emotional state.

[1938] 3. Recipe generation: The AI ​​engine generates optimal recipes based on the user's health restrictions and perceived emotions.

[1939] Examples and prompts

[1940] To illustrate, consider the following scenario in a cafe:

[1941] A cafe staff member wears smart glasses and says to the customer, "Hello, are you looking for today's specials?" The smart glasses capture the customer's facial expressions, which are then analyzed by an emotion engine. For example, if the customer expresses the emotion "happy," the Smart Healthy Cafe Assistant will suggest "marinated salmon." This recipe also takes into account the customer's health restrictions (e.g., a calorie limit of 300 kcal).

[1942] Example prompt sentence:

[1943] "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts"

[1944] In this way, a recipe suggestion system that takes emotional information into account improves customer satisfaction.

[1945] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1946] Step 1:

[1947] The user uses the device's user interface (UI) to input their allergy information, likes and dislikes, ingredients they want to use, and health restrictions. This input information is sent from the device to the server, which then packages the information in JSON or other appropriate format and sends it to the server.

[1948] Step 2:

[1949] The server receives user input information sent from the device. The received information is analyzed and information such as allergies, likes and dislikes, ingredients desired to use, and health restrictions is sorted into appropriate fields. This information is then saved in a database as a user profile.

[1950] Step 3:

[1951] The server retrieves the corresponding nutritional information from the ingredient database based on the information about the ingredients the user wants to use. Specifically, nutritional information such as calories, fat, salt, and sugar for lettuce, tomato, cucumber, and chicken breast is retrieved from the database. This completes the available information.

[1952] Step 4:

[1953] The server receives the user's health restriction information and associates it with the user profile. For example, if restrictions are set such as "calorie limit 300 kcal, salt intake 1g or less," this information is added to the user profile. Subsequent data processing is based on this information.

[1954] Step 5:

[1955] The server uses an emotion engine to recognize real-time user emotion information obtained from smart glasses, etc. The emotion engine analyzes the user's facial expressions, voice, gestures, etc., and recognizes whether the user is in an emotional state such as "happy," "sad," or "neutral." This emotion information is then sent to the server.

[1956] Step 6:

[1957] The server uses an AI engine to generate optimal cooking recipes based on the acquired ingredient information, health restrictions, user profile, and emotional information. The AI ​​engine analyzes this information and generates recipes that meet the conditions. It also incorporates emotional information from the emotional engine to suggest recipes that suit the user's emotional state. The generated recipes are also evaluated to see if they meet calorie and salt restrictions.

[1958] Step 7:

[1959] The server sends the successfully generated recipe and its cooking instructions to the device. For example, if a recipe for a healthy grilled chicken salad is generated, the server presents the user with information including the specific cooking instructions (e.g., cut the lettuce into bite-sized pieces, thinly slice the tomato and cucumber, etc.). The user can confirm this information through the device's UI.

[1960] Specific examples of operation

[1961] As an example of a prompt, if "file: captured_image.jpg, user_data: calorie_limit: 300, allergies: peanuts" is entered, the server will pass the image file to the emotion engine, determine the user's emotional state as "happy," and then generate an appropriate recipe such as "marinated salmon," taking into account sugar and salt restrictions and presenting the final recipe.

[1962] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1963] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1964] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1965] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1966] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1967] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1968] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1969] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1970] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1971] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1972] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1973] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1974] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1975] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1976] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1977] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1978] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1979] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1980] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1981] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1982] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1983] The following is further disclosed regarding the above embodiment.

[1984] (Claim 1)

[1985] a means for the user to input allergy information and likes and dislikes;

[1986] a means for the user to input ingredients they wish to use;

[1987] a means for a user to input health restrictions;

[1988] A means for retrieving relevant information from a database containing nutritional information based on the input information;

[1989] Using an AI engine to generate cooking recipes based on the acquired information and health restrictions;

[1990] means for presenting the generated cooking recipe and cooking steps to a user;

[1991] A system including:

[1992] (Claim 2)

[1993] The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

[1994] (Claim 3)

[1995] 2. The system according to claim 1, further comprising means for checking whether the generated cooking recipe satisfies each of the restrictions on calories, fat, salt, and sugar.

[1996] "Example 1"

[1997] (Claim 1)

[1998] a means for the user to input allergy information and likes and dislikes;

[1999] a means for the user to input ingredients they wish to use;

[2000] a means for a user to input health restrictions;

[2001] A means for retrieving relevant information from a database containing nutritional information based on the input information;

[2002] Using an AI engine to generate cooking recipes based on the acquired information and health restrictions;

[2003] A means for evaluating the nutritional balance of the generated cooking recipes and repeating the generation and evaluation of recipes until a recipe that satisfies the specified constraints is found;

[2004] means for presenting the generated cooking recipe and cooking steps to a user;

[2005] A system including:

[2006] (Claim 2)

[2007] The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

[2008] (Claim 3)

[2009] 2. The system according to claim 1, further comprising means for checking whether the generated cooking recipe satisfies each of the restrictions on calories, fat, salt, and sugar.

[2010] "Application Example 1"

[2011] (Claim 1)

[2012] a means for the user to input allergy information and likes and dislikes;

[2013] a means for the user to input ingredients they wish to use;

[2014] a means for a user to input health restrictions;

[2015] A means for retrieving relevant information from a database containing nutritional information based on the input information;

[2016] Using an AI engine to generate cooking recipes based on the acquired information and health restrictions;

[2017] means for presenting the generated cooking recipe and cooking steps to a user;

[2018] The system operates as an application installed on a smartphone and includes a means for suggesting healthy recipes using information entered by the user.

[2019] (Claim 2)

[2020] The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

[2021] (Claim 3)

[2022] 2. The system according to claim 1, further comprising means for checking whether the generated cooking recipe satisfies each of the restrictions on calories, fat, salt, and sugar.

[2023] "Example 2: Combining Emotion Engines"

[2024] (Claim 1)

[2025] a means for the user to input allergy information and likes and dislikes;

[2026] a means for the user to input ingredients they wish to use;

[2027] a means for a user to input health restrictions;

[2028] A means for acquiring user emotion information by an emotion engine;

[2029] A means for retrieving relevant information from a database containing nutritional information based on the input information;

[2030] Using an AI engine to generate cooking recipes based on the acquired information, health restrictions, and emotional information;

[2031] means for presenting the generated cooking recipe and cooking steps to a user;

[2032] A system including:

[2033] (Claim 2)

[2034] The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

[2035] (Claim 3)

[2036] The system of claim 1 further comprising means for checking whether the generated cooking recipe satisfies each of the calorie, fat, salt, and sugar restrictions, and means for adjusting the recipe taking into account emotional information.

[2037] "Application example 2 when combining emotion engines"

[2038] (Claim 1)

[2039] a means for the user to input allergy information and likes and dislikes;

[2040] a means for the user to input ingredients they wish to use;

[2041] a means for a user to input health restrictions;

[2042] A means for retrieving relevant information from a database containing nutritional information based on the input information;

[2043] Using an AI engine to generate cooking recipes based on the acquired information and health restrictions;

[2044] A means for recognizing user emotional information in real time;

[2045] A means for reflecting the recognized emotion information in recipe generation;

[2046] means for presenting the generated cooking recipe and cooking steps to a user;

[2047] A system including:

[2048] (Claim 2)

[2049] The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

[2050] (Claim 3)

[2051] 2. The system according to claim 1, further comprising means for checking whether the generated cooking recipe satisfies each of the restrictions on calories, fat, salt, and sugar. [Explanation of symbols]

[2052] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for the user to input allergy information and likes and dislikes; a means for the user to input ingredients they wish to use; a means for a user to input health restrictions; A means for retrieving relevant information from a database containing nutritional information based on the input information; Using an AI engine to generate cooking recipes based on the acquired information and health restrictions; means for presenting the generated cooking recipe and cooking steps to a user; A system including:

2. The system according to claim 1, further comprising a means for evaluating nutritional balance based on the input information and health restriction items.

3. The system according to claim 1 , further comprising means for checking whether the generated cooking recipe satisfies each of the restrictions on calories, fat, salt, and sugar.

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