System

Abstract

To provide a system.SOLUTION: Provided is a system, using a generative AI, comprising: means for generating a weekly menu and a shopping list taking into account a user's family structure, an amount of a meal, disliked / allergic food materials, a health state, a lifestyle, seasonal food materials, and food material prices; means for setting a combination of baby food, infant food and elderly food, not just depending on the user's adult and child family structure; means for delivering food materials on the basis of the generated shopping list; and means for informing the user of progress of the delivery.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] While there are an abundance of recipes and apps available today, only a limited number of apps offer personalized menus and shopping lists. It is particularly difficult to offer menu suggestions that take into account family composition, meal sizes, food allergies and dislikes, health status, lifestyle, seasonal ingredients, and ingredient prices. [Means for solving the problem]

[0005] To solve this problem, this invention uses generative AI to generate a week's worth of menus and shopping lists that take into account the user's family composition, meal amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices. It is also possible to set the user's family composition not only by adult and child, but also by combining baby food, toddler food, and elderly people aged 0 or over. Furthermore, based on the information input by the user, the generative AI suggests ingredient selection and cooking procedures, and adjusts meal amounts and nutritional balance according to the user's health condition and lifestyle. [Brief explanation of the drawings]

[0006] [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. 2 is a sequence diagram showing a flow of processing in the data processing system according to the first embodiment of the first form example. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Embodiment 1. [Figure 13] FIG. 10 is a sequence diagram showing a processing flow of a data processing system in a second embodiment of the second form example. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Embodiment Example 2. [Figure 15] FIG. 10 is a sequence diagram showing the flow of processing in a data processing system according to a third embodiment of the third embodiment. [Figure 16] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Embodiment 3. [Figure 17] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the first embodiment of the first form example when an emotion engine is combined. [Figure 18] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1 of Form Example 1 when an emotion engine is combined. [Figure 19] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the second embodiment of the second form example when an emotion engine is combined. [Figure 20] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 of Form Example 2 when an emotion engine is combined. [Figure 21] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in the third embodiment of the third form example when an emotion engine is combined. [Figure 22] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 3 of Form Example 3 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0007] 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.

[0008] First, the terms used in the following description will be explained.

[0009] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (TENSOR PROCESSING UNIT (registered trademark)).

[0010] 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.

[0011] 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.

[0012] 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.

[0013] 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."

[0014] [First embodiment]

[0015] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0016] 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.

[0017] 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).

[0018] 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.

[0019] 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.

[0020] 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.

[0021] 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.

[0022] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0027] "Example 1"

[0028] One embodiment of the present invention is a menu suggestion system that uses generative AI. This system generates a weekly menu and shopping list based on information input by the user, taking into consideration family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices. Specifically, when a user inputs "Family composition: 2 adults, 1 child (toddler food)," "Meal size: Regular," "Food dislikes: None," "Health condition: None in particular," "Lifestyle: Budget-oriented," and "Seasonal ingredients: Sweet potato," a weekly menu and shopping list are generated based on this information.

[0029] "Example 2"

[0030] Furthermore, in another embodiment of the present invention, the generative AI has the function of suggesting ingredient selection and cooking steps. Specifically, in addition to the menu suggestions mentioned above, if the user inputs requests such as "I want to use chicken breast" or "I want to make a stew," the system will suggest ingredient selection and cooking steps based on these requests. For example, it will suggest a recipe for "stewed chicken breast" and how to make it.

[0031] "Example 3"

[0032] In addition, as a further embodiment of the present invention, the generative AI has the function of adjusting the amount of food and nutritional balance according to the user's health condition and lifestyle. Specifically, when the user inputs their health condition, such as "currently doing strength training" or "currently managing salt intake," the system will suggest the amount of food and nutritional balance taking this information into consideration. For example, for a user who is "currently doing strength training," the system will suggest a meal that is high in protein.

[0033] The processing flow of each embodiment will be described below.

[0034] "Example 1"

[0035] Step 1: The user enters information into the system, such as family composition, food amount, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices.

[0036] Step 2: The generative AI generates a weekly menu and shopping list based on the input information. Step 3: The generated menu and shopping list are presented to the user.

[0037] "Example 2"

[0038] Step 1: The user inputs their request for ingredients and cooking instructions into the system.

[0039] Step 2: Based on the input information, the generative AI suggests ingredient selection and cooking steps.

[0040] Step 3: The user is presented with suggested ingredient choices and cooking instructions.

[0041] "Example 3"

[0042] Step 1: The user enters information about their health and lifestyle into the system.

[0043] Step 2: The generative AI adjusts the amount of food and nutritional balance based on the input information.

[0044] Step 3: The adjusted meal size and nutritional balance are presented to the user.

[0045] Example 1

[0046] Next, a description will be given of Example 1 of Form 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."

[0047] Conventional menu suggestion systems have difficulty generating menus that take into account various factors such as the user's family structure, lifestyle, and health condition. They also lack the means to efficiently process the user's input information and provide appropriate menus and shopping lists. Furthermore, the generated menus often do not match the user's specific needs, failing to increase user satisfaction.

[0048] 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.

[0049] In this invention, the server includes means for using generative artificial intelligence to generate a week's worth of menus and shopping lists that take into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly food, means for sending user input information from the terminal to the server, means for the server to generate prompt sentences based on the received information and input them into the generative artificial intelligence model, and means for sending the generated menus and shopping lists from the server to the terminal, which then displays them to the user. This makes it possible to generate menus and shopping lists that meet the diverse needs of users.

[0050] "Generative AI" is an AI technology that automatically executes specific tasks based on input information from the user.

[0051] "User's family composition" refers to the composition of members in the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people who need special diets.

[0052] "Food portion" refers to the amount of food a user consumes on a daily basis, and is expressed in categories such as normal, large, or small.

[0053] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes and cannot eat, or ingredients that may cause an allergic reaction.

[0054] "Health Status" means information about your current health, including any specific illnesses or health restrictions.

[0055] "Lifestyle" refers to a user's daily life patterns and habits, including, for example, a tendency to save money or a busy lifestyle.

[0056] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0057] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[0058] A "menu" refers to a meal plan for a specific period of time, including specific menus such as breakfast, lunch, and dinner.

[0059] A "shopping list" refers to a list of ingredients and other items needed to make a meal.

[0060] "Terminal" refers to the device used by a user to input information and receive results, including smartphones and personal computers.

[0061] "Server" refers to a computer system that receives input information from a user, processes it, generates a result, and sends it to a terminal.

[0062] A "prompt" refers to a textual instruction that is input into a generative artificial intelligence model and is generated based on information input by the user.

[0063] This invention relates to a menu suggestion system using generative artificial intelligence. This system generates a weekly menu and shopping list based on user input, taking into account family composition, meal size, food allergies / dislikes, health status, lifestyle, seasonal ingredients, and ingredient prices.

[0064] System configuration

[0065] This system includes a terminal used by the user, a server that processes data, and a generative artificial intelligence model. The terminal is a device such as a smartphone or PC that the user uses to input information and receive results. The server is a computer system that receives input information from the user, processes it, generates results, and sends them to the terminal. An example of a generative artificial intelligence model that is used is GPT-4 (registered trademark).

[0066] Processing the data

[0067] Using the device, users input information such as family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, etc. Specifically, they input information such as "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Food dislikes: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", and "Seasonal ingredients: Sweet potato" into a dedicated input form.

[0068] The device sends the information entered by the user to the server. The server generates a prompt based on the information received from the user. For example, it generates a prompt like this: "My family consists of two adults and one child (baby food). Average food portions. No food dislikes. No particular health condition. My lifestyle is frugal. My seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information."

[0069] The server inputs the generated prompts into a generative AI model to generate a weekly menu and shopping list. Based on the prompts, the generative AI model may decide, for example, that Monday's breakfast is sweet potato and spinach soup, lunch is stir-fried chicken and vegetables, and dinner is boiled fish and rice, with the shopping list including sweet potato, spinach, chicken, and fish.

[0070] The generated menu and shopping list are sent from the server to the device, which then displays them to the user. The user can then view the weekly menu and shopping list in list or calendar format on a dedicated application or web page.

[0071] Specific examples

[0072] Examples of user input include:

[0073] Family composition: 2 adults, 1 child (toddler meal)

[0074] Amount of food: Normal

[0075] Food dislikes: None

[0076] Health condition: None

[0077] Lifestyle: Frugal

[0078] Seasonal ingredients: Sweet potatoes

[0079] An example of the prompt that might be generated is:

[0080] "The family consists of two adults and one child (on toddler food). Average food portions. No food dislikes. No particular health condition. A budget-oriented lifestyle. A seasonal ingredient is sweet potatoes. Please generate a weekly menu and shopping list based on this information."

[0081] In this way, users can easily get a weekly menu and shopping list.

[0082] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0083] Step 1:

[0084] The user uses the terminal to input information such as family composition, food intake, food allergies / dislikes, health condition, lifestyle, and seasonal foods.

[0085] Input: Information entered by the user into the input form (e.g., "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked foods: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", "Seasonal ingredients: Sweet potatoes")

[0086] Output: The entered information is saved on the device.

[0087] Specific operation: The user enters the required information into a dedicated input form and presses the submit button.

[0088] Step 2:

[0089] The terminal transmits the information entered by the user to the server.

[0090] Input: Information entered by the user

[0091] Output: The input information is sent to the server.

[0092] Specific operation: When the submit button on the input form is pressed, the terminal sends the entered information to the server as an HTTP request.

[0093] Step 3:

[0094] The server generates a prompt sentence based on the received user input information.

[0095] Input: User input sent from the device

[0096] Output: Generated prompt (e.g., "The family consists of two adults and one child (toddler food). Average food portion sizes. No food dislikes. No particular health condition. Lifestyle is frugal. Seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information.")

[0097] Specific operation: The server analyzes the received data and generates a prompt.

[0098] Step 4:

[0099] The server inputs the generated prompts into a generative AI model to generate a week's worth of menus and shopping lists.

[0100] Input: Generated prompt statement

[0101] Output: A weekly meal plan and shopping list returned by the generative AI model (e.g., Monday's breakfast is sweet potato and spinach soup, lunch is chicken and vegetable stir-fry, and dinner is stewed fish with rice. The shopping list includes sweet potato, spinach, chicken, fish, etc.)

[0102] Specific operation: The server sends a prompt to the generative AI model and receives the results returned by the model.

[0103] Step 5:

[0104] The server sends the generated menu and shopping list to the terminal.

[0105] Input: A week's worth of meal plans and a shopping list returned by a generative AI model

[0106] Output: Menu and shopping list sent to device.

[0107] Specific operation: The server sends the generated data to the terminal as an HTTP response.

[0108] Step 6:

[0109] The terminal displays the received menu and shopping list to the user.

[0110] Input: Menu and shopping list sent from the server

[0111] Output: A weekly menu and shopping list displayed to the user

[0112] Specific operation: The device analyzes the received data and displays it in a format that is easy for the user to view. For example, a weekly meal plan and shopping list can be displayed in list or calendar format on a dedicated application or web page.

[0113] (Application example 1)

[0114] Next, a description will be given of Application Example 1 of Embodiment 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."

[0115] Conventional menu suggestion systems have difficulty proposing detailed menus that fit a user's family structure and lifestyle, and have also had the problem of having to purchase and deliver ingredients based on the suggested menu, which can be time-consuming. Furthermore, there is a lack of means for users to grasp the progress of actually implementing the suggested menu.

[0116] 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.

[0117] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over), means for delivering ingredients based on the generated shopping list, and means for notifying the user of the progress of delivery. This enables menu suggestions based on the user's detailed needs and efficient purchasing and delivery of ingredients based on those suggestions, improving user convenience.

[0118] "Generative AI" refers to artificial intelligence that generates data and information for specific purposes based on input from users.

[0119] "Family composition" refers to the composition of members in the user's household, and includes categories such as adults, children, infants who need baby food, young children who need toddler food, and elderly people.

[0120] "Amount of food" refers to the amount of food the user consumes on a daily basis, including categories such as regular, large, and small portions.

[0121] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes or that may cause an allergic reaction.

[0122] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[0123] "Lifestyle" refers to the behavioral patterns and values ​​of users in their daily lives, and includes categories such as being frugal or health-conscious.

[0124] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0125] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[0126] A "menu" refers to a meal menu for a specific period of time, including categories such as breakfast, lunch, and dinner.

[0127] A "shopping list" refers to a list of ingredients and other items needed based on a menu.

[0128] "Delivery" refers to the service of delivering ingredients or goods ordered by the user to a specified location.

[0129] "Notification" refers to a method of informing a user of specific information, whether via a smartphone or other device.

[0130] The system for implementing this invention uses generative AI to generate a weekly menu and shopping list that takes into consideration the user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, and delivers ingredients based on this. A specific embodiment of this system is described below.

[0131] Hardware and software used

[0132] Hardware: Smartphones, smart glasses, head-mounted displays

[0133] Software: Generative AI models (e.g., GPT-4®), databases (e.g., MySQL®), food delivery APIs (e.g., Uber Eats API)

[0134] Program processing

[0135] Getting User Input

[0136] Using a smartphone, smart glasses, or head-mounted display, users can input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. For example, users can input the following information:

[0137] Family composition: 2 adults, 1 child (toddler meal)

[0138] Amount of food: Normal

[0139] Disliked foods: None

[0140] Health condition: None in particular

[0141] Lifestyle: Frugal

[0142] Seasonal ingredients: sweet potatoes

[0143] Prompt generation for generative AI models

[0144] The server generates a prompt for the generative AI model based on the input information. An example of a prompt is as follows:

[0145] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0146] Generative AI model for generating menus and shopping lists

[0147] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a weekly menu and shopping list. The generated menu and shopping list are stored in a database (e.g., MySQL).

[0148] Integration with food delivery API

[0149] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Once the order is complete, the user is notified and the delivery progress is displayed in real time.

[0150] Specific examples

[0151] For example, if a user inputs "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked ingredients: None", "Health condition: None", "Lifestyle: Frugal", and "Seasonal ingredients: Sweet potato", the generative AI model will generate the following prompt:

[0152] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0153] Based on this prompt, the generative AI model generates a weekly menu and shopping list, stores it in a database, and then uses a food delivery API to order ingredients and notify the user.

[0154] In this way, it becomes possible to propose menus that meet the user's detailed needs, and to efficiently purchase and deliver ingredients based on those menus.

[0155] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0156] Step 1:

[0157] Users use a smartphone, smart glasses, or head-mounted display to input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. The input information is sent from the device to the server. Examples of input data include "Family composition: 2 adults, 1 child (toddler food)", "Food intake: normal", "Food allergies: none", "Health status: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[0158] Step 2:

[0159] The server generates a prompt for the generative AI model based on the received user input. Specifically, it converts the input into text and formats it in a format that the generative AI model can understand. An example of a generated prompt is as follows:

[0160] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0161] This prompt sentence becomes the input data for the generative AI model.

[0162] Step 3:

[0163] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a week's worth of menus and shopping lists. The generative AI model performs data calculations based on the prompts and outputs appropriate menus and shopping lists. The output data is stored in a database (e.g., MySQL) on the server.

[0164] Step 4:

[0165] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Specifically, it sends each item on the shopping list to the API and processes the order. The API responds with order confirmation information, estimated delivery time, and other information.

[0166] Step 5:

[0167] The server notifies the user that the order has been completed. The notification is sent via a smartphone, smart glasses, or head-mounted display. The notification includes order details and delivery progress. The user can check the delivery status in real time.

[0168] In this way, menu suggestions based on the user's detailed needs and the purchase and delivery of ingredients based on those suggestions can be carried out efficiently.

[0169] Example 2

[0170] Next, a description will be given of Example 2 of Form 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."

[0171] Conventional menu suggestion systems have difficulty in suggesting ingredient selection and cooking procedures based on the user's specific requests. Furthermore, they are unable to make detailed adjustments based on the user's family structure, health condition, or lifestyle, making it difficult to provide suggestions that meet individual needs. Furthermore, there was a lack of a way to properly display the suggested content on the user's device, resulting in low user convenience.

[0172] 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.

[0173] In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition by combining not only adults and children but also baby food, toddler food, and elderly people (ages 0 and over); means for receiving user requests as input and suggesting ingredient selection and cooking procedures based on those requests; and means for transmitting and displaying the generated suggestions to the user's device. This enables suggestions for ingredient selection and cooking procedures based on the user's specific requests, enabling menu suggestions that meet individual needs. Furthermore, by appropriately displaying the suggestions on the user's device, user convenience is improved.

[0174] "Generative AI" is an artificial intelligence technology that automatically generates appropriate ingredient selections and cooking procedures based on information input by the user.

[0175] "User's family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[0176] "Meal Quantity" refers to the amount of food required by each member of the User's household.

[0177] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that cause allergic reactions.

[0178] "Health Status" means information about the health of you and your family, including any specific illnesses or health restrictions.

[0179] "Lifestyle" refers to the daily patterns and habits of the user and their family, including meal times and frequency.

[0180] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0181] "Price of ingredients" refers to price information of ingredients in the market.

[0182] A "menu" refers to a meal plan for a specific period of time (e.g., one week), including the contents of each meal.

[0183] A "shopping list" is a list of ingredients and seasonings needed based on a menu.

[0184] "Request" refers to the specific wishes or requests that a user inputs into the system.

[0185] "Suggestion content" refers to information including ingredient selection and cooking steps generated by generative AI based on the user's requests.

[0186] "Terminal" refers to the device a user uses to interface with the system, including smartphones, tablets, and personal computers.

[0187] The present invention is a system that suggests ingredient selection and cooking procedures based on the specific needs of a user. Specific embodiments of this system will be described below.

[0188] System configuration

[0189] User operations

[0190] The user inputs their request into the system's input screen. For example, they input a prompt such as, "I want to use chicken breast. I want to make a stew." This communicates the user's specific request to the system.

[0191] Server Processing

[0192] The server receives input from the user and analyzes the content. Natural language processing technology is used for analysis. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to understand the content of the request and extract the keywords "chicken breast" and "simmered food."

[0193] Next, the server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[0194] An example of a generated recipe is:

[0195] "Chicken breast stew recipe:

[0196] 1. Cut the chicken breast into bite-sized pieces.

[0197] 2. Heat oil in a pot and fry the chicken breast.

[0198] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[0199] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[0200] 5. Simmer until all ingredients are soft.

[0201] 6. Finally, adjust the flavor and it's done.

[0202] Terminal display

[0203] The server sends the generated recipe and instructions to the terminal. The HTTP protocol is used for sending. The terminal displays the recipe and instructions sent from the server to the user. Specifically, the following content is displayed on the terminal screen:

[0204] "Chicken breast stew recipe:

[0205] 1. Cut the chicken breast into bite-sized pieces.

[0206] 2. Heat oil in a pot and fry the chicken breast.

[0207] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[0208] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[0209] 5. Simmer until all ingredients are soft.

[0210] 6. Finally, adjust the flavor and it's done.

[0211] Hardware and software used

[0212] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[0213] Software: Generative AI models (such as OpenAI's GPT-4®), natural language processing libraries (such as SpaCy and NLTK), and HTTP protocols

[0214] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[0215] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0216] Step 1:

[0217] The user inputs a request into the system's input screen. For example, the user inputs a prompt such as, "I want to use chicken breast meat. I want to make a stew." The input request is sent to the system.

[0218] Input: User request (prompt)

[0219] Output: Request sent to the system

[0220] Step 2:

[0221] The server receives requests from users. It analyzes the received requests using natural language processing technology and understands the content of the requests. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to extract the keywords "chicken breast" and "simmered food."

[0222] Input: User request (prompt)

[0223] Output: Analyzed request content (keywords)

[0224] Step 3:

[0225] The server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[0226] Input: Analyzed request content (keywords)

[0227] Output: Generated recipe and instructions

[0228] Step 4:

[0229] The server sends the generated recipe and instructions to the terminal using the HTTP protocol.

[0230] Input: Generated recipe and instructions

[0231] Output: Recipe and instructions sent to the terminal

[0232] Step 5:

[0233] The device displays the recipe and instructions sent from the server to the user. Specifically, the device displays the following on its screen:

[0234] "Chicken breast stew recipe:

[0235] 1. Cut the chicken breast into bite-sized pieces.

[0236] 2. Heat oil in a pot and fry the chicken breast.

[0237] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[0238] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[0239] 5. Simmer until all ingredients are soft.

[0240] 6. Finally, adjust the flavor and it's done.

[0241] Input: Recipe and instructions sent to the device

[0242] Output: The recipe and instructions displayed to the user

[0243] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[0244] (Application example 2)

[0245] Next, a description will be given of Application Example 2 of Form 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."

[0246] Conventional menu suggestion systems have problems with user convenience, as they are difficult to respond to individual user requests and ingredient selections, and lack the functionality to automatically arrange the necessary ingredients based on the suggested recipe. Furthermore, there is no way to centrally manage and display the suggested recipes and order status, making it difficult for users to procure ingredients and cook without hassle.

[0247] The specific processing by the specific 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 using generative AI to generate a weekly menu and shopping list taking into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only as adults and children but also as a combination of baby food, toddler food, and elderly people (ages 0 and over); means for suggesting appropriate recipes and their procedures based on the ingredients and types of dishes entered by the user; means for selecting the necessary ingredients based on the suggested recipe and automatically arranging for the delivery of the ingredients; and means for displaying the suggested recipe and order status to the user. This enables recipe suggestions and automatic ordering of ingredients according to the user's individual needs, significantly improving user convenience.

[0248] "Generative AI" is artificial intelligence that automatically generates appropriate recipes, ingredient selections, and cooking steps based on user input.

[0249] "Family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, children who need toddler food, and elderly people.

[0250] "Meal portion" refers to the amount of food determined based on the user's family size and individual dietary needs.

[0251] "Ingredients that you dislike / allergic to" are ingredients that you or your family dislike or that may cause an allergic reaction.

[0252] "Health Status" means information about the health of the User and their family, including specific nutrient restrictions and dietary recommendations.

[0253] "Lifestyle" refers to the daily patterns, meal timings, and food preferences of the user and their family.

[0254] "Seasonal ingredients" are those that are the freshest, most nutritious, and most readily available in the market during a particular season.

[0255] "Price of ingredients" refers to price information of ingredients in the market, and is used to select ingredients according to the user's budget.

[0256] A "menu" is a meal plan for a specific period of time (e.g., a week), including the menu for each meal.

[0257] A "shopping list" is a list of ingredients needed based on a menu, helping users to shop efficiently.

[0258] A "recipe" is a detailed description of the steps and ingredients for making a particular dish.

[0259] "Food delivery" is a service that delivers the food ingredients a user needs to a specified location.

[0260] "Order status" is information that indicates the delivery status and arrangement status of ingredients ordered by the user.

[0261] The system for implementing this invention uses generative AI to propose recipes and automatically arrange ingredients according to user requests. Specific embodiments are described below.

[0262] System Configuration

[0263] The system consists of a user terminal, a server, and a food delivery service API. The user terminal is a device such as a smartphone or tablet, and the server is a computer system for running generative AI. The food delivery service API is an external service for managing food ordering and delivery.

[0264] Hardware and software used

[0265] Hardware: smartphones, tablets, servers

[0266] Software: Python, OpenAI API, food delivery service API

[0267] Data processing and calculation

[0268] 1. Obtaining user input: Obtain the ingredients and type of dish entered by the user on the user device. For example, the user enters "I want to use chicken breast."

[0269] 2. Recipe generation using generative AI: The server uses the OpenAI API to generate a recipe and its steps based on the user's request. An example of a prompt is, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps."

[0270] 3. Selecting and ordering ingredients: The server selects the necessary ingredients based on the proposed recipe and places an order through the food delivery service API.

[0271] 4. Displaying the results: The suggested recipes and order status are displayed on the user's device, allowing the user to easily source the necessary ingredients and cook.

[0272] Specific examples

[0273] When a user uses a smartphone application to input "I want to use chicken breast," the server uses the OpenAI API to generate a recipe and instructions for "simmered chicken breast." The generated recipe includes the necessary ingredients, their quantities, and cooking instructions. The server then uses a food delivery service API to automatically order the necessary ingredients (e.g., chicken breast, soy sauce, sugar, mirin, and sake) and arranges for delivery to the address specified by the user. The user can check the suggested recipe and the order status through the application.

[0274] In this way, it becomes possible to propose recipes and automatically arrange ingredients according to the user's individual needs, greatly improving user convenience.

[0275] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0276] Step 1:

[0277] The user launches the smartphone application and inputs the ingredients they want to use and the type of dish they want to make. For example, they might input "I want to use chicken breast." This input information is sent to the server via the application.

[0278] Input: Ingredients and type of dish entered by the user

[0279] Output: User request data sent to the server

[0280] Step 2:

[0281] The server uses a generative AI model to generate an appropriate recipe and its steps based on the received user request data. Specifically, it uses the OpenAI API to generate prompts and have the AI ​​suggest recipes.

[0282] Input: User's desired data

[0283] Output: The generated recipe and its steps

[0284] Specific behavior:

[0285] The server generates a prompt saying, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps." and sends it to the OpenAI API. The server receives the recipe and steps returned by the API.

[0286] Step 3:

[0287] The server selects the necessary ingredients based on the generated recipe, extracts the ingredients and their amounts listed in the recipe, and creates an ingredient list.

[0288] Input: The generated recipe and its steps

[0289] Output: List of ingredients needed

[0290] Specific behavior:

[0291] The server extracts ingredients such as "chicken breast," "soy sauce," "sugar," "mirin," and "sake" from the recipe and creates a list of them.

[0292] Step 4:

[0293] The server uses the food delivery service API to order ingredients based on the created ingredient list. It sends the ingredient list to the API and starts the ordering process.

[0294] Input: List of ingredients needed

[0295] Output: Checkout result

[0296] Specific behavior:

[0297] The server sends the list of ingredients to the food delivery service API and checks whether the order has been successfully received.

[0298] Step 5:

[0299] The server sends the results of the order process and the generated recipe to the user's device, where the user can check the proposed recipe and order status through the application.

[0300] Input: Recipe generated as a result of ordering process

[0301] Output: Recipe and order status displayed on the user's device

[0302] Specific behavior:

[0303] The server sends the order processing results (e.g., order acceptance, estimated delivery date, etc.) and the generated recipe to the user's device and displays them in the application. This allows the user to check when the necessary ingredients will arrive and get ready to start cooking.

[0304] Example 3

[0305] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0306] Conventional meal recommendation systems have difficulty adjusting meal portions and nutritional balance appropriately based on the user's health condition and lifestyle. Furthermore, they have not adequately generated menus and shopping lists that take into account the user's family structure and individual dietary restrictions. This makes it difficult for users to select meals that suit their health condition and lifestyle, potentially resulting in inadequate health management.

[0307] The specification process by the specification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a means for the user to input health status and lifestyle, a means for the terminal to transmit the input information to the server, a means for the server to generate meal suggestions using the generation AI model, a means for the server to transmit the generated meal suggestions to the terminal, and a means for the terminal to display the meal suggestions to the user. This makes it possible to appropriately adjust the amount of food and nutritional balance according to the user's health status and lifestyle, and to provide meal suggestions that meet individual needs.

[0308] "Generative AI" is an artificial intelligence system that automatically generates meal suggestions, menus, shopping lists, etc. based on information input by the user.

[0309] "User's family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[0310] "Meal amount" refers to the amount of ingredients or food consumed by the user or their family in one meal.

[0311] "Ingredients that you dislike / are allergic to" refers to ingredients that the user or their family dislikes and cannot eat, or ingredients that may cause an allergic reaction.

[0312] "Health status" refers to information about the current health of the user or their family, such as "currently working out" or "currently managing salt intake."

[0313] "Lifestyle" refers to the daily patterns and habits of users and their families, such as "busy weekdays" and "relaxing time on weekends."

[0314] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[0315] "Price of ingredients" refers to the price at which a particular ingredient is sold in the market.

[0316] A "menu" refers to a meal plan for a specific period of time (e.g., a week), including specific dishes and ingredient combinations.

[0317] A "shopping list" is a list of ingredients and seasonings needed based on a menu, and serves as a reference for users when shopping.

[0318] "Terminal" means a device used by a user to input information or receive information from a server, including a smartphone, tablet, or PC.

[0319] "Server" refers to a computer system that receives input information from users, generates meal suggestions using generative AI, and transmits the results to a terminal.

[0320] "Meal suggestions" refer to the specific meal content and nutritional balance suggested by generative AI based on the user's health condition and lifestyle.

[0321] MODE FOR CARRYING OUT THE INVENTION

[0322] This invention is a system that makes meal suggestions based on the user's health condition and lifestyle. Based on the information entered by the user, the system uses a generative AI model to adjust the amount of food and nutritional balance, and makes appropriate meal suggestions.

[0323] Hardware and software used

[0324] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[0325] Software: Generative AI models (e.g., GPT-4®), database management systems (e.g., MySQL), communication protocols (e.g., HTTP / HTTPS)

[0326] Explanation of program processing

[0327] The server receives information about the user's health and lifestyle through the device. For example, the user may enter information such as "I'm doing strength training" or "I'm managing my salt intake." The device uses the HTTP / HTTPS protocol to send this information to the server.

[0328] The server analyzes the received information and generates a prompt for the generative AI model. For example, it generates a prompt such as, "Please generate meal suggestions suitable for a user currently working out." The generative AI model then generates meal suggestions based on this prompt. The generated meal suggestions include specific menu items, such as "chicken breast and broccoli salad."

[0329] The server converts the generated meal suggestions into JSON format and sends them to the device, which then analyzes the data and visually displays it to the user, allowing the user to select the actual meal.

[0330] Specific examples

[0331] Example 1: User working out

[0332] 1. The user types "working out" into the device.

[0333] 2. The device sends this information to the server.

[0334] 3. The server uses the generative AI model to generate protein-rich meal suggestions.

[0335] 4. The server sends the generated proposal to the device.

[0336] 5. The device displays meal suggestions to the user, such as "chicken breast and broccoli salad."

[0337] Example 2: User on salt management

[0338] 1. The user types "salt management" into the terminal.

[0339] 2. The device sends this information to the server.

[0340] 3. The server uses the generative AI model to generate low-salt meal suggestions.

[0341] 4. The server sends the generated proposal to the device.

[0342] 5. The device displays meal suggestions to the user, such as "steamed vegetables with salt-free dressing."

[0343] Prompt Sentence Examples

[0344] "Generate meal suggestions suitable for users who are working out."

[0345] "Generate suitable meal suggestions for users managing their salt intake."

[0346] In this way, the system allows the server, terminal, and user to work together to make meal suggestions that are suited to the user's health condition and lifestyle. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0347] Program processing flow

[0348] Step 1: User inputs health status and lifestyle

[0349] Users use devices such as smartphones or PCs to enter their health status and lifestyle information. For example, users might enter information such as "I'm currently doing strength training" or "I'm currently managing my salt intake." The input form includes text boxes and drop-down menus.

[0350] Input: User's health status and lifestyle (e.g., "Currently working out")

[0351] Output: Input information is saved to the device

[0352] Specific behavior:

[0353] The user launches an application.

[0354] The user responds to the prompt "Please enter your health status" and enters "Working out."

[0355] Step 2: The device sends the input information to the server

[0356] The device sends the health and lifestyle information entered by the user to a server, and this communication is carried out using the HTTP / HTTPS protocol.

[0357] Input: User-entered health and lifestyle information

[0358] Output: The input information is sent to the server

[0359] Specific behavior:

[0360] The terminal converts the input information into JSON format.

[0361] The device sends a POST request to the server's API endpoint.

[0362] Step 3: The server generates meal suggestions using the generative AI model

[0363] The server generates meal suggestions using a generative AI model (e.g., GPT-4 (registered trademark)) based on the received information on the user's health condition and lifestyle. The generative AI model uses pre-trained data to suggest meal amounts and nutritional balance that suit the user's needs.

[0364] Input: User's health and lifestyle information

[0365] Output: Generated meal suggestions

[0366] Specific behavior:

[0367] The server parses the received JSON data.

[0368] The server generates and inputs a prompt sentence to the generative AI model.

[0369] Example: "Generate meal suggestions suitable for a strength training user."

[0370] A generative AI model generates meal suggestions.

[0371] Example: "Chicken breast and broccoli salad"

[0372] Step 4: The server sends the meal suggestions to the device.

[0373] The server then sends the meal suggestions obtained from the generative AI model to the device, again using the HTTP / HTTPS protocol.

[0374] Input: Generated meal suggestions

[0375] Output: Meal suggestions sent to device

[0376] Specific behavior:

[0377] The server converts the generated meal suggestions into JSON format.

[0378] The server sends a POST request to the device's API endpoint.

[0379] Step 5: The device displays meal suggestions to the user.

[0380] The terminal displays the meal suggestions received from the server to the user, who can then use them as a reference to select an actual meal.

[0381] Input: Meal suggestions received from the server

[0382] Output: Meal suggestions are displayed to the user

[0383] Specific behavior:

[0384] The terminal parses the received JSON data.

[0385] The terminal visually displays meal suggestions to the user.

[0386] Example: "Today's meal recommendation: Chicken breast and broccoli salad."

[0387] In this way, the system works in cooperation with the user, the terminal, and the server to make meal suggestions that suit the user's health condition and lifestyle.

[0388] (Application example 3)

[0389] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0390] In modern society, there is a demand for systems that suggest appropriate meals based on the user's health condition and lifestyle, and allow them to easily order these meals in conjunction with delivery services. However, conventional systems have had the problem of making meal suggestions based on the user's detailed health condition and lifestyle, and also of not being able to order these suggestions in conjunction with delivery services.

[0391] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food portions, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for suggesting meals according to the user's health condition and lifestyle and for enabling the user to order those meals in cooperation with a delivery service; and means for displaying the nutritional balance of the suggested meals. This makes it possible to suggest meals based on the user's detailed health condition and lifestyle, and for the suggestion to be easily ordered in cooperation with a delivery service.

[0392] "Generative AI" is an artificial intelligence that makes appropriate meal suggestions and adjusts nutritional balance based on information input by the user.

[0393] "Family composition" is information that indicates the ages and dietary needs of members in the user's household.

[0394] "Meal portion" is information indicating the amount of food consumed by the user or their family in one meal.

[0395] "Ingredients that you dislike / are allergic to" is information that indicates ingredients that the user and their family should avoid.

[0396] "Health status" refers to information about the current health of the user and their family, and includes, for example, "currently doing strength training" or "currently managing salt intake."

[0397] "Lifestyle" is information that indicates the patterns and habits of daily life of the user and their family.

[0398] "Seasonal ingredients" refers to information that indicates the freshest and most nutritious ingredients in a particular season.

[0399] "Price of ingredients" is information indicating the market price of ingredients.

[0400] "Menu" is information indicating the meal menu for a specific period of time.

[0401] A "shopping list" is a list of ingredients needed based on a menu.

[0402] "Delivery service" refers to a service that delivers meals ordered by users to a specified location.

[0403] "Nutritional balance" is information that indicates the proportion and balance of nutrients contained in a meal.

[0404] The system for implementing this invention uses generative AI to suggest meals based on the user's health condition and lifestyle, and also has the function of enabling the user to order those meals in conjunction with a delivery service. Specific embodiments of this system are described below.

[0405] System configuration

[0406] 1. Hardware

[0407] Server: A server for running generative AI. In this case, we use a cloud-based server.

[0408] Device: A smartphone or tablet used by the user, which allows the user to input information about their health and lifestyle and receive dietary suggestions.

[0409] 2. Software

[0410] Generative AI: Uses OpenAI APIs to generate meal suggestions based on user input.

[0411] Delivery service integration module: A module for ordering suggested meals in collaboration with delivery services.

[0412] Nutritional balance display module: A module for displaying the nutritional balance of the proposed meal.

[0413] Data processing and calculation

[0414] 1. User Input

[0415] Users can enter information such as their health status (e.g., strength training, salt management), lifestyle, family composition, and food allergies / dislikes through a smartphone application.

[0416] 2. Generative AI Meal Suggestions

[0417] The server receives input from the user and uses generative AI to generate appropriate meal suggestions, using the following prompt:

[0418] Give users suitable meal suggestions while they are working out.

[0419] 3. Delivery service collaboration

[0420] The suggested meals can be easily ordered by users through a delivery service integration module.

[0421] 4. Nutritional Balance Display

[0422] The nutritional balance of the suggested meal is displayed to the user through a nutritional balance display module.

[0423] Specific examples

[0424] For example, if a user types "I'm working out," the generative AI will suggest a high-protein meal. Specifically, it will generate a menu such as "grilled chicken breast, broccoli, and brown rice." This suggestion can then be easily ordered by the user through a delivery service integration module. Additionally, the nutritional balance display module will show the user the nutritional balance of this meal (e.g., the percentage of protein, carbohydrates, and fat).

[0425] In this way, a system will be realized that can suggest meals based on the user's detailed health condition and lifestyle, and that these suggestions can be easily linked to delivery services for ordering.

[0426] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0427] Step 1:

[0428] The user starts the smartphone application and inputs information such as their health status (e.g., currently doing muscle training, currently managing salt intake), lifestyle, family composition, food allergies / dislikes, etc. This input information is sent to the server via the application.

[0429] Step 2:

[0430] The server receives the input information sent by the user. Based on the received information, it generates a prompt for the generative AI. For example, if the user inputs "Working out," the following prompt is generated:

[0431] Give users suitable meal suggestions while they are working out.

[0432] Step 3:

[0433] The server sends a prompt to the generative AI (OpenAI's API) to generate appropriate meal suggestions. The generative AI processes and calculates data based on the prompt to generate meal suggestions. For example, a menu such as "grilled chicken breast, broccoli, and brown rice" may be generated.

[0434] Step 4:

[0435] The server receives the generated meal suggestions and sends them to a delivery service integration module, which converts the suggested meals into a delivery service ordering format so that the user can easily place an order.

[0436] Step 5:

[0437] The server calculates the nutritional balance of the proposed meal and sends it to a nutritional balance display module, which calculates the proportions and balance of nutrients contained in the meal and displays them to the user.

[0438] Step 6:

[0439] Users can check the nutritional balance of the suggested meals through a smartphone application and order the meals through a delivery service, which then delivers the meals to the specified location.

[0440] In this way, a system is realized that makes it possible to suggest meals based on the user's detailed health condition and lifestyle, and that can also easily order these suggestions in conjunction with a delivery service.

[0441] 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.

[0442] "Example 1"

[0443] One embodiment of the present invention provides a system that uses an emotion engine to recognize a user's emotions. This system generates a weekly menu and shopping list taking into consideration the user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, as well as the user's emotional state. Specifically, when the user is feeling stressed, the system suggests ingredients and dishes that may alleviate that stress. When the user is feeling happy, the system suggests ingredients and dishes that may amplify that happiness.

[0444] "Example 2"

[0445] In another embodiment of the present invention, a system is provided that uses an emotion engine to suggest ingredient selection and cooking steps based on input information from a user and the user's emotional state. Specifically, when a user is feeling down, the system suggests ingredients and cooking steps that may lift the user's spirits. When a user is excited, the system suggests ingredients and cooking steps that may calm the user's excitement.

[0446] "Example 3"

[0447] As a further embodiment of the present invention, a system is provided that uses an emotion engine to adjust the amount of food and nutritional balance according to the user's emotional state and lifestyle. Specifically, when the user is feeling stressed, the system suggests a food amount and nutritional balance that may reduce the stress. Also, when the user is relaxed, the system suggests a food amount and nutritional balance that may maintain the relaxed state.

[0448] The processing flow of each embodiment will be described below.

[0449] "Example 1"

[0450] Step 1: Recognize the user's emotional state with the emotion engine.

[0451] Step 2: Obtain the user's family composition, food amount, disliked / allergic ingredients, health condition, lifestyle, seasonal ingredients, and ingredient prices from the database.

[0452] Step 3: Generate a weekly menu and shopping list taking into account the information obtained and the user's emotional state.

[0453] "Example 2"

[0454] Step 1: The emotion engine recognizes the user's input information and emotional state. Step 2: Based on the recognized information, it suggests ingredient selection and cooking steps.

[0455] "Example 3"

[0456] Step 1: Recognize the user's emotional state and lifestyle with the emotion engine.

[0457] Step 2: Adjust the amount of food you eat and the nutritional balance based on the information you have gained.

[0458] Example 1

[0459] Next, a description will be given of Example 1 of Form 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."

[0460] While conventional menu suggestion systems can take into account a user's family structure, food intake, food allergies / dislikes, health status, lifestyle, seasonal ingredients, and ingredient prices, they do not suggest menus that take into account the user's emotional state. As a result, they are unable to provide optimal menus based on the user's emotional state, making it difficult to increase user satisfaction. Furthermore, there was a lack of a way to display the generated menus and shopping lists on the user's device, creating a need for a system that was easy for users to use.

[0461] 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.

[0462] In this invention, the server includes means for using generative artificial intelligence to generate a week's worth of menus and shopping lists that take into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and the elderly, means for recognizing the user's emotional state and adjusting the menus and shopping lists based on that emotional state, and means for displaying the generated menus and shopping lists on the user's terminal. This makes it possible to provide the user with optimal menus and shopping lists that suit their emotional state, thereby increasing user satisfaction.

[0463] "Generative AI" is an AI technology that automatically executes specific tasks based on input information from the user.

[0464] "Family composition" refers to the composition of members in the user's household, and includes categories such as adults, children, infants who need baby food, young children who need toddler food, and elderly people.

[0465] "Meal size" refers to the amount of food a user consumes in one sitting, expressed in categories such as regular, small, medium, or large.

[0466] "Ingredients that you dislike / are allergic to" refers to ingredients that you dislike or that may cause an allergic reaction.

[0467] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[0468] "Lifestyle" refers to a user's daily life patterns and habits, and includes categories such as frugality, health consciousness, and busy lifestyles.

[0469] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most delicious during a particular season.

[0470] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[0471] "Emotional state" refers to the user's current psychological state, including emotions such as stress, joy, and sadness.

[0472] A "menu" refers to a meal plan for a specific period (e.g., a week), including menus for breakfast, lunch, dinner, etc.

[0473] A "shopping list" refers to a list of ingredients and other items needed to make a meal.

[0474] "Terminal" refers to a device used by a user to input information or receive generated information, including smartphones, tablets, and personal computers.

[0475] This invention is a menu suggestion system that uses generative artificial intelligence to generate a week's worth of menus and shopping lists, taking into consideration the user's family structure, food intake, food allergies and dislikes, health condition, lifestyle, seasonal ingredients, and prices of ingredients. It also has a function to recognize the user's emotional state and adjust the menu and shopping list based on that emotional state.

[0476] Hardware and software used

[0477] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[0478] Software: Generative AI models (e.g., GPT-4®), emotion engines, user interfaces

[0479] Explanation of program processing

[0480] 1. Collection of User-Entered Information

[0481] Users use the device to enter information such as family composition, food intake, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and prices of ingredients.

[0482] Example: A user opens a smartphone app and fills in the input form with the following information: "Family composition: 2 adults, 1 child (toddler food)", "Meal size: normal", "Food dislikes: none", "Health condition: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[0483] 2. Recognizing emotional states

[0484] The server uses an emotion engine to recognize the user's emotional state.

[0485] Example: The server analyzes the user's input, past usage history, and even facial and voice data (if available) to determine whether the user is stressed.

[0486] 3. Menu and shopping list generation

[0487] The server uses a generative AI model (e.g., GPT-4®) to generate a weekly menu and shopping list based on the user's input and emotional state.

[0488] Example: The server inputs the following prompt into the generative AI model: "Family composition: 2 adults, 1 child (toddler food), food amount: normal, disliked ingredients: none, health condition: nothing in particular, lifestyle: frugal, seasonal ingredients: sweet potato, emotional state: stressed." Based on this, the generative AI model generates menus for Monday through Sunday and a list of the ingredients needed to accompany them.

[0489] 4. Displaying the generated results

[0490] The server generates a menu and a shopping list, which are then sent to the terminal and displayed to the user.

[0491] Example: The server generates data and sends it to the device, and the user's smartphone app displays menu suggestions such as "Monday's dinner is a healthy sweet potato soup, and Tuesday's dinner is a budget-friendly chicken and vegetable stir-fry," along with the necessary shopping list.

[0492] Prompt Sentence Examples

[0493] "Family composition: 2 adults, 1 child (baby food), Meal size: Normal, Food dislikes: None, Health condition: None in particular, Lifestyle: Frugal, Seasonal food: Sweet potatoes, Emotional state: Stressed."

[0494] The system allows users to easily get the best meal plans and shopping lists tailored to their individual needs and emotional state.

[0495] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0496] Step 1:

[0497] Collecting user-entered information

[0498] Users use the device to enter information such as family composition, food intake, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and prices of ingredients.

[0499] Input: The user opens the app on their smartphone and fills in the input form with the following information: "Family composition: 2 adults, 1 child (toddler food)", "Meal size: normal", "Food dislikes: none", "Health condition: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[0500] Output: The entered information is sent to the server and stored in a database.

[0501] Specific behavior: When a user enters the required information into the application's input form and presses the submit button, the information is sent to the server.

[0502] Step 2:

[0503] Recognition of emotional states

[0504] The server uses an emotion engine to recognize the user's emotional state.

[0505] Input: The server receives the user's input, past usage history, and even the user's facial and voice data (if available).

[0506] Output: The user's emotional state (e.g., feeling stressed) is recognized and stored in a database.

[0507] Specific operation: The server launches the emotion engine, analyzes the user's input information and past data, and determines the user's emotional state.

[0508] Step 3:

[0509] Menu and shopping list generation

[0510] The server uses a generative AI model (e.g., GPT-4®) to generate a weekly menu and shopping list based on the user's input and emotional state.

[0511] Input: The server inputs the following prompt into the generative AI model: "Family composition: 2 adults, 1 child (toddler food), Meal size: Normal, Food dislikes: None, Health condition: None in particular, Lifestyle: Frugal, Seasonal food: Sweet potato, Emotional state: Stressed."

[0512] Output: The generative AI model generates menus and ingredient lists for each day from Monday to Sunday, which are stored in a database.

[0513] How it works: The server inputs prompts into the generative AI model, which then generates a menu and shopping list based on them.

[0514] Step 4:

[0515] Viewing the generated results

[0516] The server generates a menu and a shopping list, which are then sent to the terminal and displayed to the user.

[0517] Input: Receives server-generated menu and shopping list data.

[0518] Output: The user's smartphone app displays a menu such as "Monday's dinner is a healthy sweet potato soup, and Tuesday's dinner is a budget-friendly chicken and vegetable stir-fry," along with a shopping list.

[0519] Specific operation: The server sends the generated data to the terminal and it is displayed in the user's smartphone app.

[0520] (Application example 1)

[0521] Next, a description will be given of Application Example 1 of Embodiment 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."

[0522] While conventional menu suggestion systems can take into account a user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, they have the problem of not being able to make suggestions that take into account the user's emotional state. Furthermore, they lack the functionality to suggest optimal ingredients in real time while shopping in a physical store and update the shopping list. This resulted in insufficient suggestions for ingredients and dishes that would reduce the user's stress and increase their enjoyment, and reduced shopping efficiency.

[0523] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for recognizing the user's emotional state and suggesting ingredients and dishes that reduce stress and increase joy based on that emotional state; and means for suggesting optimal ingredients and updating the shopping list in real time while shopping in a physical store. This makes it possible to suggest optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in a physical store.

[0524] "Generative AI" is an artificial intelligence technology that automatically generates data and suggestions for specific purposes based on information input from users.

[0525] "Family composition" refers to the types and number of members in the user's household, including adults, children, infants who need baby food, children who need toddler food, and elderly people.

[0526] "Amount of food" refers to the amount of food the user consumes on a daily basis, and includes quantitative settings such as normal, large, or small.

[0527] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes or that may cause an allergic reaction.

[0528] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[0529] "Lifestyle" refers to the user's behavioral patterns and values ​​in their daily lives, including, for example, styles such as being frugal or health-conscious.

[0530] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[0531] "Prices of ingredients" refers to price information of ingredients in the market, allowing users to make choices according to their budget.

[0532] "Emotional state" refers to the user's current psychological state, including emotions such as stress or joy.

[0533] "Brick and mortar store" refers to a physical store where users actually visit and purchase products.

[0534] "Real-time" refers to immediate response to ongoing user activity.

[0535] "Optimal ingredients" refers to the most suitable ingredients based on the user's input information and emotional state.

[0536] A "shopping list" refers to a list of ingredients and products that a user plans to purchase.

[0537] The system for implementing this invention uses generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices. It also includes a function to recognize the user's emotional state and suggest ingredients and dishes that will reduce stress or increase joy based on that emotional state. It also has a function to suggest optimal ingredients and update the shopping list in real time while shopping in a physical store.

[0538] Hardware and software used

[0539] Hardware: Smartphone

[0540] Software: Python, OpenAI API

[0541] System configuration

[0542] 1. User input: Users enter information about their family composition, food intake, food allergies / dislikes, health status, lifestyle, seasonal ingredients, food prices, and emotional state through a smartphone app.

[0543] 2. Generative AI: Based on the information input by the user, the server uses generative AI (OpenAI's GPT-3 (registered trademark)) to generate a week's worth of menus and shopping lists.

[0544] 3. Emotion Recognition: The server recognizes the user's emotional state and suggests ingredients and dishes that will reduce stress or increase joy based on that emotional state.

[0545] 4. Real-time suggestions: While shopping in a physical store, the smartphone app will suggest the best ingredients in real time and update your shopping list.

[0546] Specific examples

[0547] The user enters the following information into the app:

[0548] Family composition: 2 adults, 1 child (toddler meal)

[0549] Amount of food: Normal

[0550] Disliked foods: None

[0551] Health condition: None in particular

[0552] Lifestyle: Frugal

[0553] Seasonal ingredients: sweet potatoes

[0554] Food prices: Moderate

[0555] Emotional state: Stress

[0556] Based on this information, the server sends the following prompt to the generative AI:

[0557] Family composition: 2 adults, 1 child (toddler meal)

[0558] Amount of food: Normal

[0559] Food dislikes: None

[0560] Health condition: None

[0561] Lifestyle: Frugal

[0562] Seasonal ingredients: Sweet potatoes

[0563] Food prices: Moderate

[0564] Emotional state: Stress

[0565] Use this information to generate a weekly menu and shopping list.

[0566] Based on this prompt, the generative AI generates a weekly menu and shopping list and returns it to the server. The server then sends this information to a smartphone app and displays it to the user. While shopping in a physical store, the smartphone app suggests optimal ingredients in real time and updates the shopping list.

[0567] In this way, it becomes possible to suggest optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in physical stores.

[0568] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0569] Step 1:

[0570] The user launches the smartphone app and inputs information such as family composition, meal size, food allergies and dislikes, health status, lifestyle, seasonal ingredients, food prices, and emotional state. The input information is then saved in the application's database.

[0571] Step 2:

[0572] The device sends the input information to the server. The server analyzes the received information and generates a prompt to send to the generative AI model. An example of a prompt is as follows:

[0573] Family composition: 2 adults, 1 child (toddler meal)

[0574] Amount of food: Normal

[0575] Food dislikes: None

[0576] Health condition: None

[0577] Lifestyle: Frugal

[0578] Seasonal ingredients: Sweet potatoes

[0579] Food prices: Moderate

[0580] Emotional state: Stress

[0581] Use this information to generate a weekly menu and shopping list.

[0582] Step 3:

[0583] The server sends the generated prompt to a generative AI model (OpenAI's GPT-3), which calculates the data based on the prompt and generates a weekly menu and shopping list. The generated data is returned to the server.

[0584] Step 4:

[0585] The server analyzes the weekly menu and shopping list received from the generative AI model and generates additional data to suggest ingredients and dishes that reduce stress or increase joy based on the user's emotional state. This enables optimal suggestions to be made according to the user's emotional state.

[0586] Step 5:

[0587] The server sends the final menu and shopping list to the device, which displays the received data to the user. The user can check the displayed menu and shopping list and modify them as necessary.

[0588] Step 6:

[0589] When a user goes shopping in a physical store, the device will suggest the best ingredients in real time and update the shopping list. The device will suggest the best ingredients to the user based on the store's location and inventory information.

[0590] Step 7:

[0591] After the user completes their shopping, the device sends the final shopping list to the server, which analyzes the data and updates the database to reflect the next recommendation.

[0592] The above steps make it possible to propose optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in physical stores.

[0593] Example 2

[0594] Next, a description will be given of Example 2 of Form 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."

[0595] Conventional menu suggestion systems make suggestions based on the user's family structure, health status, and lifestyle, but they lack the ability to select ingredients and suggest cooking steps that correspond to the user's specific requests and emotional state. This has led to problems such as an inability to respond to the diverse needs of users and a decrease in satisfaction. In addition, because it is not possible to suggest ingredients and dishes that correspond to the user's emotional state, it is difficult to increase the user's psychological satisfaction.

[0596] 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.

[0597] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by combining adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over), means for suggesting ingredient selection and cooking steps based on the user's requests, and means for suggesting ingredients and cooking steps based on the user's emotional state. This makes it possible to suggest ingredient selection and cooking steps according to the user's specific requests and emotional state.

[0598] "Generative AI" is artificial intelligence that uses natural language processing and machine learning techniques to generate appropriate suggestions and answers based on user input.

[0599] "User's family composition" is information that refers to the ages and roles of members in the user's household (adults, children, babies who need solid food, toddlers, elderly people, etc.).

[0600] "Meal portion" refers to the amount of ingredients or food consumed by the user or their family in one meal.

[0601] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that may cause allergic reactions.

[0602] "Health Status" refers to information about a user's or their family's current health status and specific health goals (e.g., diet, diabetes management, etc.).

[0603] "Lifestyle" refers to information about the daily patterns and habits of the user and their family (e.g., work hours, exercise habits, etc.).

[0604] "Seasonal ingredients" refers to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season or time of year.

[0605] "Prices of ingredients" refers to information about prices of ingredients in the market, and is useful information for users to select ingredients according to their budget.

[0606] A "menu" refers to a meal plan or menu for a specific period of time (e.g., a week), including ingredient selection and cooking instructions.

[0607] A "shopping list" is a list of ingredients and seasonings needed based on a menu, and is information that allows users to shop efficiently.

[0608] "Emotional state" is information that refers to the user's current psychological state (e.g., depressed, excited, etc.).

[0609] "Ingredient selection" refers to the process of selecting appropriate ingredients based on the user's requests and conditions.

[0610] "Cooking instructions" refers to the specific steps and methods for preparing a dish using selected ingredients.

[0611] This invention is a system that uses generative AI to suggest ingredient selection and cooking procedures based on the user's requests and emotional state. Specific embodiments of this system are described below.

[0612] Hardware and software used

[0613] Hardware: Servers, terminals (PCs, smartphones)

[0614] Software: Generative AI models (e.g., GPT-4®), emotion engines (e.g., Affectiva)

[0615] System Overview

[0616] The system generates a weekly menu and shopping list taking into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices. It also suggests ingredient selection and cooking steps based on the user's preferences, and even suggests ingredients and cooking steps based on the user's emotional state.

[0617] Program processing

[0618] 1. User request input

[0619] The user uses a terminal to input requests such as "I want to use chicken breast" or "I want to make a stew" into the system interface.

[0620] Example: A user opens an app on their smartphone, enters "I want to use chicken breast" in the text box, and presses the send button.

[0621] 2. Analysis of requests

[0622] The server receives the request sent by the user and analyzes it using a generative AI model (e.g., GPT-4 (registered trademark)).

[0623] Example: The server receives the text "I want to use chicken breast" and sends the prompt "Please tell me a simple recipe using chicken breast" to the generative AI model.

[0624] 3. Proposal Generation

[0625] The server receives the response from the generative AI model and suggests appropriate recipes and how to make them to the user.

[0626] Example: A generative AI model generates a recipe and instructions for "Boiled Chicken Breast," and the server sends that information to the user's device. The recipe for "Boiled Chicken Breast" is then displayed on the user's smartphone.

[0627] 4. Emotional state analysis

[0628] The user inputs their emotional state through the terminal, or an emotion engine (e.g., Affectiva) analyzes the user's emotional state from their facial expressions and voice.

[0629] Example: A user types "I feel depressed" in text, or a smartphone camera analyzes the user's facial expression, and the emotion engine determines that the user feels "depressed."

[0630] 5. Emotion-based suggestions

[0631] Based on the analysis results of the emotion engine, the server suggests ingredients and cooking procedures that correspond to the user's emotional state.

[0632] Example: The server receives the emotional state "feeling depressed" and sends a prompt to the generative AI model saying, "What food would you recommend when you're feeling depressed?" The generative AI model generates a recipe for "chocolate cake," and the server sends that information to the user's device. The recipe for "chocolate cake" is displayed on the user's smartphone.

[0633] In this way, the system can suggest appropriate ingredients and cooking instructions based on the user's desires and emotional state.

[0634] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0635] Step 1:

[0636] User request input

[0637] Input: The user uses a device (PC or smartphone) to input requests such as "I want to use chicken breast" or "I want to make a stew" into the system interface.

[0638] Specific actions: A user opens the app on their smartphone, enters "I want to use chicken breast" in the text box, and presses the send button.

[0639] Output: The user's request is sent to the server.

[0640] Step 2:

[0641] Request analysis

[0642] Input: The server receives a request sent by the user.

[0643] Specific operation: The server receives the text "I want to use chicken breast" and sends a prompt to the generative AI model (e.g., GPT-4 (registered trademark)) saying "Please tell me a simple recipe using chicken breast."

[0644] Data processing: A generative AI model analyzes the prompt and generates an appropriate recipe.

[0645] Output: The appropriate recipe is returned to the server as a response from the generative AI model.

[0646] Step 3:

[0647] Proposal Generation

[0648] Input: The server receives the response from the generative AI model.

[0649] Specific operation: The generative AI model generates a recipe and instructions for "braised chicken breast," and the server sends this information to the user's device.

[0650] Data processing: The server converts the recipe information received from the generative AI model into a format that can be displayed to the user.

[0651] Output: The recipe for "Simmered Chicken Breast" will be displayed on the user's smartphone.

[0652] Step 4:

[0653] Emotional state analysis

[0654] Input: The user inputs their emotional state through the device, or the emotion engine (e.g., Affectiva) analyzes their emotional state from their facial expressions and voice.

[0655] Specific operation: The user enters "I feel depressed" in text, or the smartphone camera analyzes the user's facial expression, and the emotion engine determines that the user feels "depressed."

[0656] Data processing: The emotion engine analyzes the user's emotional state and sends the results to the server.

[0657] Output: The user's emotional state is sent to the server.

[0658] Step 5:

[0659] Emotion-based suggestions

[0660] Input: The server receives the analysis results of the emotion engine.

[0661] Specific behavior: The server receives the emotional state "feeling depressed" and sends a prompt to the generative AI model: "What dishes would you recommend when feeling depressed?"

[0662] Data processing: A generative AI model analyzes the prompt and generates an appropriate recipe.

[0663] Output: The generative AI model responds by returning an appropriate recipe to the server, which then sends the information to the user's device. The user's smartphone displays the recipe for "Chocolate Cake."

[0664] (Application example 2)

[0665] Next, a description will be given of Application Example 2 of Form 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."

[0666] Conventional meal planning systems could suggest meals based on the user's family structure, health status, and lifestyle, but they could not suggest ingredients or cooking procedures that corresponded to the user's emotional state or specific requests. Furthermore, they lacked the ability to order the suggested dishes for delivery, which resulted in low user convenience.

[0667] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0668] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people aged 0 or older, means for suggesting ingredient selection and cooking procedures based on the user's requests and emotional state, and means for enabling delivery ordering of the suggested dishes. This makes it possible to suggest optimal dishes based on the user's specific requests and emotional state, and to order delivery as is.

[0669] "Generative AI" is artificial intelligence that generates data based on user input and makes optimal suggestions.

[0670] "Family composition" is information that indicates the ages and roles of members in the user's household.

[0671] "Meal portion" is information indicating the amount of food consumed by the user or their family in one meal.

[0672] "Ingredients that you dislike / are allergic to" is information that indicates ingredients that the user or their family dislikes or that may cause allergic reactions.

[0673] "Health status" is information that indicates the current health status of the user and their family members.

[0674] "Lifestyle" is information that indicates the patterns and habits of daily life of the user and their family.

[0675] "Seasonal ingredients" are ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0676] "Price of ingredients" is price information of ingredients in the market.

[0677] A "menu" is a plan showing the menu of meals for a specific period of time.

[0678] A "shopping list" is a list of ingredients and other items to purchase based on a menu.

[0679] A "request" is a user's wish or request for a particular ingredient or dish.

[0680] "Emotional state" is information that indicates the user's current mood or psychological state.

[0681] "Cooking instructions" is information that indicates the specific steps and methods for making a particular dish.

[0682] "Delivery Order" is a service that allows users to order suggested dishes online and have them delivered to their home.

[0683] The system for implementing this invention uses generative AI to suggest ingredient selection and cooking steps based on the user's requests and emotional state, and also has the function of allowing the suggested dishes to be delivered as is. Specific embodiments of this system are described below.

[0684] System Configuration

[0685] The system mainly uses the following hardware and software:

[0686] Hardware: Smartphones, servers

[0687] Software: Python, OpenAI API, Sentiment Analysis API

[0688] Program processing

[0689] The server receives input information from the user and uses generative AI to generate the optimal recipe. Specifically, the process is as follows:

[0690] 1. Getting user input:

[0691] Users input their ingredient and cooking preferences, as well as their current emotional state, through a smartphone application.

[0692] 2. Emotion analysis:

[0693] The server uses an emotion analysis API to analyze the user's input emotional state, thereby identifying the user's current mood.

[0694] 3. Prompt generation:

[0695] The server generates prompts to send to the generative AI based on the user's wishes and emotional state. Examples of prompts are as follows:

[0696] User request: I want to use chicken breast.

[0697] User sentiment: Tired

[0698] Please suggest the best recipe.

[0699] 4. Recipe generation:

[0700] The server sends prompts to the generative AI (OpenAI API) to generate the optimal recipe, which is then displayed to the user.

[0701] 5. Delivery Order:

[0702] Users can then order the suggested recipes for delivery, and the server will then work with the delivery service to process the order.

[0703] Specific examples

[0704] For example, if a user inputs "I want to use chicken breast" and "I'm tired" as their emotional state, the server will use the emotion analysis API to analyze the emotion "I'm tired" and send the following prompt to the generative AI:

[0705] User request: I want to use chicken breast.

[0706] User sentiment: Tired

[0707] Please suggest the best recipe.

[0708] The generative AI suggests a "simple chicken breast stew recipe," and after checking the recipe, users can place a delivery order.

[0709] In this way, a system can be realized that can suggest the most suitable dish based on the user's specific requests and emotional state, and also enable delivery orders to be placed directly.

[0710] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0711] Step 1:

[0712] The user launches the smartphone application and inputs their desired ingredients, cooking preferences, and current emotional state. The input information is then sent to the server. The input data includes specific requests, such as "I want chicken breast" or "I'm tired," as well as their emotional state.

[0713] Step 2:

[0714] The server analyzes the received user input information and sends it to the emotion analysis API. The emotion analysis API analyzes the user's emotional state and identifies emotions such as "tired." The analysis results are sent back to the server. The input data is the user's emotional state, and the output data is the analyzed emotional state.

[0715] Step 3:

[0716] The server generates a prompt to send to the generative AI based on the user's request and the analyzed emotional state. Examples of generated prompts include "User request: I would like to use chicken breast meat," "User emotion: I'm tired," and "Please suggest the best recipe." The input data are the user's request and emotional state, and the output data is the generated prompt.

[0717] Step 4:

[0718] The server sends the generated prompt to the generative AI (OpenAI API). The generative AI generates the optimal recipe based on the prompt and returns the result to the server. The input data is the prompt, and the output data is the generated recipe.

[0719] Step 5:

[0720] The server sends the generated recipe to the user's smartphone application. The user can review the proposed recipe and enter corrections or additions as needed. The input data is the generated recipe, and the output data is the recipe displayed to the user.

[0721] Step 6:

[0722] If the user checks the suggested recipe and places a delivery order, the server works with the delivery service to process the order. The user's order information is sent to the delivery service, and the order is confirmed. The input data is the user's order information, and the output data is the confirmed order information.

[0723] In this way, a system can be realized that can suggest the most suitable dish based on the user's specific requests and emotional state, and also enable delivery orders to be placed directly.

[0724] Example 3

[0725] Next, a description will be given of a third embodiment of the third embodiment. 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."

[0726] Conventional meal recommendation systems have difficulty in properly adjusting the amount of food and nutritional balance according to the user's health condition and lifestyle. They also do not adequately generate menus and shopping lists that take into account the user's family structure and individual dietary restrictions. Furthermore, they do not consider meal recommendations based on the user's emotional state, making it impossible to meet the diverse needs of users.

[0727] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes: means for using a generative AI to generate a one-week menu and shopping list taking into account the user's family composition, food portion sizes, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for receiving information on the user's health condition and lifestyle and inputting prompt sentences into the generative AI model based on that information; means for the generative AI model to generate meal suggestions based on the prompt sentences; and means for displaying the generated meal suggestions to the user. This makes it possible to adjust the amount of food and nutritional balance according to the user's health condition and lifestyle, thereby realizing meal suggestions that meet the diverse needs of users.

[0728] "Generative AI" is an artificial intelligence system that automatically generates meal suggestions, menus, shopping lists, etc. based on information input by the user.

[0729] A "prompt sentence" is an input sentence that provides specific instructions or information to a generative AI, allowing the AI ​​to generate appropriate output based on this.

[0730] "User's family composition" refers to the composition of members in the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[0731] "Meal portion" refers to the amount of food consumed by the user or their family in one meal, and is adjusted according to each individual's health condition and lifestyle.

[0732] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that may cause an allergic reaction.

[0733] "Health status" refers to information about the current health of the user and their family, including specific conditions such as "doing strength training" or "managing salt intake."

[0734] "Lifestyle" refers to the daily patterns and habits of the user and their family, including states such as "feeling stressed" and "relaxed."

[0735] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[0736] "Price of ingredients" refers to the price of ingredients in the market, which is taken into consideration according to the user's budget and economic situation.

[0737] A "menu" refers to a meal plan for a specific period of time (for example, a week), including the contents of each meal and the ingredients needed.

[0738] A "shopping list" is a list of ingredients and other items needed based on a menu, allowing users to shop efficiently.

[0739] This invention is a system that uses generative AI to suggest meals based on a user's health condition and lifestyle. Specific embodiments of this system are described below.

[0740] Hardware and software used

[0741] The system uses the following hardware and software:

[0742] Server: Processes data and runs generative AI models.

[0743] Terminal: A device (smartphone, PC, etc.) through which a user enters information and receives suggestions from the server.

[0744] Generative AI model: An artificial intelligence model that generates meal suggestions based on user input.

[0745] Data processing and calculation

[0746] Server Processing

[0747] The server receives information about the user's health and lifestyle entered on the device. For example, the user enters information such as "I'm working out" or "I'm feeling stressed." The server analyzes this information and inputs prompts into the generative AI model. Examples of prompts include:

[0748] "User inputs that they are working out. Generate protein-rich meal suggestions."

[0749] "User inputs that they are stressed. Generate food suggestions that may reduce stress."

[0750] The generative AI model generates meal suggestions based on a prompt, such as "grilled chicken breast, broccoli, and brown rice."

[0751] Terminal handling

[0752] The device sends the information entered by the user to the server, and displays the meal suggestions received from the server to the user, who then checks the displayed suggestions and selects a meal based on them.

[0753] Specific examples

[0754] 1. User input: The user opens the smartphone application, enters "working out," and presses the "Send" button.

[0755] 2. Sending data from the device to the server: The device converts the information entered by the user into JSON format and sends it to the server using an HTTP request.

[0756] 3. Data processing on the server: The server parses the received JSON data and generates prompt sentences to input into the generative AI model.

[0757] 4. Suggestion generation using generative AI model: The generative AI model generates meal suggestions based on the prompt sentence.

[0758] 5. Data transmission from server to device: The server converts the meal suggestions generated by the generative AI model into JSON format and sends them to the device using an HTTP response.

[0759] 6. Displaying suggestions on the device: The device parses the received JSON data and displays meal suggestions to the user. The user can then review the suggestions on the application screen and select a meal based on the suggestions.

[0760] In this way, meal suggestions are made according to the user's health condition and lifestyle. The flow of the specification process in the third embodiment will be described with reference to FIG.

[0761] Step 1:

[0762] The user opens the application on their smartphone or computer and inputs their health condition and lifestyle. For example, they input information such as "I'm working out" or "I'm feeling stressed," and then press the "Send" button. The input data is information about the user's health condition and lifestyle.

[0763] Step 2:

[0764] The device converts the information entered by the user into JSON format and sends it to the server using an HTTP request. The input data is the health and lifestyle information entered by the user, and the output data is JSON format data sent to the server. Specifically, the device generates the following JSON data:

[0765] json

[0766] {

[0767] "health_status": "Working out",

[0768] "lifestyle": "stressed"

[0769] }

[0770] Step 3:

[0771] The server analyzes the JSON data received from the device. The input data is the JSON format data sent from the device, and the output data is the analyzed information on the user's health condition and lifestyle. Specifically, the server analyzes the JSON data and extracts the following information:

[0772] Health status: Currently working out

[0773] Lifestyle: Feeling stressed

[0774] Step 4:

[0775] The server generates prompt sentences to be input into the generative AI model based on the analyzed information. The input data is the analyzed information on the user's health condition and lifestyle, and the output data is the generated prompt sentence. Specifically, the server generates prompt sentences like the following:

[0776] "User inputs that they are working out. Generate protein-rich meal suggestions."

[0777] "User inputs that they are stressed. Generate food suggestions that may reduce stress."

[0778] Step 5:

[0779] The generative AI model generates meal suggestions based on prompts received from the server. The input data is the prompt sent from the server, and the output data is the generated meal suggestions. Specifically, the generative AI model generates the following meal menu:

[0780] "Grilled chicken breast, broccoli, and brown rice"

[0781] Step 6:

[0782] The server converts the meal suggestions generated by the generative AI model into JSON format and sends it to the device using an HTTP response. The input data is the meal suggestions generated by the generative AI model, and the output data is JSON format data sent to the device. Specifically, the server generates the following JSON data:

[0783] json

[0784] {

[0785] "meal_suggestion": "Grilled chicken breast, broccoli, brown rice"

[0786] }

[0787] Step 7:

[0788] The device parses the JSON data received from the server and displays meal suggestions to the user. The input data is the JSON format data sent from the server, and the output data is the meal suggestions displayed to the user. Specifically, the device displays meal suggestions as follows:

[0789] "Grilled chicken breast, broccoli, and brown rice"

[0790] The user reviews the displayed suggestions and selects meals based on the suggestions.

[0791] (Application example 3)

[0792] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[0793] Conventional meal recommendation systems do not adequately suggest meals based on the user's health and emotional state, and lack a means to easily order the suggested meals. This makes it difficult for users to obtain the meals that best suit their health and emotional state.

[0794] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list taking into consideration the user's family composition, food amount, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people aged 0 or over; and means for suggesting optimal meals based on the user's health condition and emotional state and ordering those meals in cooperation with a food delivery service. This allows users to easily suggest and order meals that are optimal for their health condition and emotional state.

[0795] "Generative AI" refers to artificial intelligence that generates data and suggestions tailored to specific purposes based on input from users.

[0796] "Family composition" is information that refers to the age and role of each member in the user's household (adult, child, baby who needs solid food, infant, elderly, etc.).

[0797] "Meal amount" refers to the amount of food consumed by the user or their family in one meal.

[0798] "Ingredients that you dislike / have allergies to" refers to ingredients that you or your family dislike or that may cause allergic reactions.

[0799] "Health status" refers to information about the current health of the user or their family (e.g., currently doing strength training, currently managing salt intake, etc.).

[0800] "Lifestyle" refers to the daily patterns and habits of the user and their family (e.g., work hours, frequency of exercise, etc.).

[0801] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0802] "Price of ingredients" refers to the price information of each ingredient in the market.

[0803] A "menu" refers to a meal plan or menu for a specific period of time (e.g., one week).

[0804] A "shopping list" is a list of ingredients and products needed based on a menu.

[0805] "Emotional state" refers to the user's current psychological state (e.g., stressed, relaxed, etc.).

[0806] "Food delivery service" refers to a service that delivers meals ordered by users to a specified location.

[0807] The system for implementing this invention uses generative AI to suggest meals based on the user's health and emotional state, and then works with a food delivery service to order the meals. A specific embodiment of this system is described below.

[0808] First, the user accesses the application using a smartphone. The application provides an interface for inputting information such as the user's family composition, food intake, food allergies and dislikes, health condition, lifestyle, seasonal ingredients, and food prices. In addition to inputting this information, the user also inputs their current health condition (e.g., "currently working out") and emotional state (e.g., "stressed").

[0809] Next, the server uses a generative AI model to generate optimal meal recommendations based on the user's input. This generative AI model has the ability to adjust the amount of food and nutritional balance according to the user's health and emotional state. For example, if a user is "working out" and feeling "stressed," the generative AI model will suggest a meal that is high in protein and contains ingredients that have stress-reducing effects.

[0810] The generated meal suggestions are displayed to the user through the application. The user can review the suggested meals and order the meals through a food delivery service. The order is sent via the server to the food delivery service, which delivers the meal at the specified time.

[0811] The following hardware and software are used to implement this system:

[0812] Smartphone: A device where users enter information and view meal suggestions.

[0813] Server: A computer system for running the generative AI model and generating meal suggestions.

[0814] Generative AI model: An artificial intelligence model that generates meal suggestions based on user input.

[0815] Food delivery service: A service that delivers meals ordered by users.

[0816] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[0817] "The user's health status is training and their emotional state is stressed. Please suggest the optimal diet."

[0818] By sending this prompt to a generative AI model, meal suggestions such as "high-protein chicken breast salad with brown rice and orange juice containing vitamin C" can be obtained. By ordering this suggestion through a food delivery service, users can easily obtain the meal that best suits their health and emotional state.

[0819] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[0820] Step 1:

[0821] The user accesses the application using a smartphone. The user inputs information such as family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and food prices. The input information is sent to the server through the application interface. The input data also includes the user's current health condition (e.g., "currently working out") and emotional state (e.g., "stressed").

[0822] Step 2:

[0823] The server generates a prompt for the generative AI model based on the received user input information. The prompt is an instruction for generating meal suggestions based on the user's health and emotional state. For example, a generated prompt might read, "The user's health condition is currently working out, and their emotional state is stressed. Please suggest the optimal meal."

[0824] Step 3:

[0825] The server sends the generated prompt text to the generative AI model. The generative AI model analyzes the prompt text and generates meal suggestions that are optimal for the user's health and emotional state. The generative AI model processes and calculates data based on the user's input information and outputs meal suggestions. For example, a meal suggestion such as "high-protein chicken breast salad with brown rice and orange juice containing vitamin C" may be generated.

[0826] Step 4:

[0827] The server sends the meal suggestions received from the generative AI model to the application, which displays the meal suggestions on the user's smartphone. The user can review the suggested meals and make corrections or changes as needed.

[0828] Step 5:

[0829] The user reviews the meal suggestions and decides to order the meal through a food delivery service. The user confirms the order through the application and the order information is sent to the server.

[0830] Step 6:

[0831] The server sends the received order information to a food delivery service. The food delivery service prepares meals based on the order information and delivers them to the user's designated location at the specified time. The user receives the delivered meal and can enjoy a meal that is optimal for their health and emotional state.

[0832] 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.

[0833] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ) and other generative AIs. Data generation models 58

[0834] , 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 the data format of voice data, text data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0835] Another example of generative AI is Gemini (registered trademark) (Internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[0836] 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.

[0837] [Second embodiment]

[0838] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0839] 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.

[0840] 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).

[0841] 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.

[0842] 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.

[0843] 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).

[0844] 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.

[0845] 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.

[0846] 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.

[0847] 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.

[0848] 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.

[0849] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[0850] "Example 1"

[0851] One embodiment of the present invention is a menu suggestion system that uses generative AI. This system generates a weekly menu and shopping list based on information input by the user, taking into consideration family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices. Specifically, when a user inputs "Family composition: 2 adults, 1 child (toddler food)," "Meal size: Regular," "Food dislikes: None," "Health condition: None in particular," "Lifestyle: Budget-oriented," and "Seasonal ingredients: Sweet potato," a weekly menu and shopping list are generated based on this information.

[0852] "Example 2"

[0853] Furthermore, in another embodiment of the present invention, the generative AI has the function of suggesting ingredient selection and cooking steps. Specifically, in addition to the menu suggestions mentioned above, if the user inputs requests such as "I want to use chicken breast" or "I want to make a stew," the system will suggest ingredient selection and cooking steps based on these requests. For example, it will suggest a recipe for "stewed chicken breast" and how to make it.

[0854] "Example 3"

[0855] In addition, as a further embodiment of the present invention, the generative AI has the function of adjusting the amount of food and nutritional balance according to the user's health condition and lifestyle. Specifically, when the user inputs their health condition, such as "currently doing strength training" or "currently managing salt intake," the system will suggest the amount of food and nutritional balance taking this information into consideration. For example, for a user who is "currently doing strength training," the system will suggest a meal that is high in protein.

[0856] The processing flow of each embodiment will be described below.

[0857] "Example 1"

[0858] Step 1: The user enters information into the system, such as family composition, food amount, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices.

[0859] Step 2: The generative AI generates a weekly menu and shopping list based on the input information. Step 3: The generated menu and shopping list are presented to the user.

[0860] "Example 2"

[0861] Step 1: The user inputs their request for ingredients and cooking instructions into the system.

[0862] Step 2: Based on the input information, the generative AI suggests ingredient selection and cooking steps.

[0863] Step 3: The user is presented with suggested ingredient choices and cooking instructions.

[0864] "Example 3"

[0865] Step 1: The user enters information about their health and lifestyle into the system.

[0866] Step 2: The generative AI adjusts the amount of food and nutritional balance based on the input information.

[0867] Step 3: The adjusted meal size and nutritional balance are presented to the user.

[0868] Example 1

[0869] Next, a description will be given of Example 1 of Form 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."

[0870] Conventional menu suggestion systems have difficulty generating menus that take into account various factors such as the user's family structure, lifestyle, and health condition. They also lack the means to efficiently process the user's input information and provide appropriate menus and shopping lists. Furthermore, the generated menus often do not match the user's specific needs, failing to increase user satisfaction.

[0871] 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.

[0872] In this invention, the server includes means for using generative artificial intelligence to generate a week's worth of menus and shopping lists that take into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly food, means for sending user input information from the terminal to the server, means for the server to generate prompt sentences based on the received information and input them into the generative artificial intelligence model, and means for sending the generated menus and shopping lists from the server to the terminal, which then displays them to the user. This makes it possible to generate menus and shopping lists that meet the diverse needs of users.

[0873] "Generative AI" is an AI technology that automatically executes specific tasks based on input information from the user.

[0874] "User's family composition" refers to the composition of members in the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people who need special diets.

[0875] "Food portion" refers to the amount of food a user consumes on a daily basis, and is expressed in categories such as normal, large, or small.

[0876] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes and cannot eat, or ingredients that may cause an allergic reaction.

[0877] "Health Status" means information about your current health, including any specific illnesses or health restrictions.

[0878] "Lifestyle" refers to a user's daily life patterns and habits, including, for example, a tendency to save money or a busy lifestyle.

[0879] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0880] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[0881] A "menu" refers to a meal plan for a specific period of time, including specific menus such as breakfast, lunch, and dinner.

[0882] A "shopping list" refers to a list of ingredients and other items needed to make a meal.

[0883] "Terminal" refers to the device used by a user to input information and receive results, including smartphones and personal computers.

[0884] "Server" refers to a computer system that receives input information from a user, processes it, generates a result, and sends it to a terminal.

[0885] A "prompt" refers to a textual instruction that is input into a generative artificial intelligence model and is generated based on information input by the user.

[0886] This invention relates to a menu suggestion system using generative artificial intelligence. This system generates a weekly menu and shopping list based on user input, taking into account family composition, meal size, food allergies / dislikes, health status, lifestyle, seasonal ingredients, and ingredient prices.

[0887] System configuration

[0888] This system includes a terminal used by the user, a server that processes data, and a generative artificial intelligence model. The terminal is a device such as a smartphone or PC that the user uses to input information and receive results. The server is a computer system that receives input information from the user, processes it, generates results, and sends them to the terminal. An example of a generative artificial intelligence model that is used is GPT-4 (registered trademark).

[0889] Processing the data

[0890] Using the device, users input information such as family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, etc. Specifically, they input information such as "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Food dislikes: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", and "Seasonal ingredients: Sweet potato" into a dedicated input form.

[0891] The device sends the information entered by the user to the server. The server generates a prompt based on the information received from the user. For example, it generates a prompt like this: "My family consists of two adults and one child (baby food). Average food portions. No food dislikes. No particular health condition. My lifestyle is frugal. My seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information."

[0892] The server inputs the generated prompts into a generative AI model to generate a weekly menu and shopping list. Based on the prompts, the generative AI model may decide, for example, that Monday's breakfast is sweet potato and spinach soup, lunch is stir-fried chicken and vegetables, and dinner is boiled fish and rice, with the shopping list including sweet potato, spinach, chicken, and fish.

[0893] The generated menu and shopping list are sent from the server to the device, which then displays them to the user. The user can then view the weekly menu and shopping list in list or calendar format on a dedicated application or web page.

[0894] Specific examples

[0895] Examples of user input include:

[0896] Family composition: 2 adults, 1 child (toddler meal)

[0897] Amount of food: Normal

[0898] Food dislikes: None

[0899] Health condition: None

[0900] Lifestyle: Frugal

[0901] Seasonal ingredients: Sweet potatoes

[0902] An example of the prompt that might be generated is:

[0903] "The family consists of two adults and one child (on toddler food). Average food portions. No food dislikes. No particular health condition. A budget-oriented lifestyle. A seasonal ingredient is sweet potatoes. Please generate a weekly menu and shopping list based on this information."

[0904] In this way, users can easily get a weekly menu and shopping list.

[0905] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0906] Step 1:

[0907] The user uses the terminal to input information such as family composition, food intake, food allergies / dislikes, health condition, lifestyle, and seasonal foods.

[0908] Input: Information entered by the user into the input form (e.g., "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked foods: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", "Seasonal ingredients: Sweet potatoes")

[0909] Output: The entered information is saved on the device.

[0910] Specific operation: The user enters the required information into a dedicated input form and presses the submit button.

[0911] Step 2:

[0912] The terminal transmits the information entered by the user to the server.

[0913] Input: Information entered by the user

[0914] Output: The input information is sent to the server.

[0915] Specific operation: When the submit button on the input form is pressed, the terminal sends the entered information to the server as an HTTP request.

[0916] Step 3:

[0917] The server generates a prompt sentence based on the received user input information.

[0918] Input: User input sent from the device

[0919] Output: Generated prompt (e.g., "The family consists of two adults and one child (toddler food). Average food portion sizes. No food dislikes. No particular health condition. Lifestyle is frugal. Seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information.")

[0920] Specific operation: The server analyzes the received data and generates a prompt.

[0921] Step 4:

[0922] The server inputs the generated prompts into a generative AI model to generate a week's worth of menus and shopping lists.

[0923] Input: Generated prompt statement

[0924] Output: A weekly meal plan and shopping list returned by the generative AI model (e.g., Monday's breakfast is sweet potato and spinach soup, lunch is chicken and vegetable stir-fry, and dinner is stewed fish with rice. The shopping list includes sweet potato, spinach, chicken, fish, etc.)

[0925] Specific operation: The server sends a prompt to the generative AI model and receives the results returned by the model.

[0926] Step 5:

[0927] The server sends the generated menu and shopping list to the terminal.

[0928] Input: A week's worth of meal plans and a shopping list returned by a generative AI model

[0929] Output: Menu and shopping list sent to device.

[0930] Specific operation: The server sends the generated data to the terminal as an HTTP response.

[0931] Step 6:

[0932] The terminal displays the received menu and shopping list to the user.

[0933] Input: Menu and shopping list sent from the server

[0934] Output: A weekly menu and shopping list displayed to the user

[0935] Specific operation: The device analyzes the received data and displays it in a format that is easy for the user to view. For example, a weekly meal plan and shopping list can be displayed in list or calendar format on a dedicated application or web page.

[0936] (Application example 1)

[0937] Next, a description will be given of Application Example 1 of Form 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."

[0938] Conventional menu suggestion systems have difficulty proposing detailed menus that fit a user's family structure and lifestyle, and have also had the problem of having to purchase and deliver ingredients based on the suggested menu, which can be time-consuming. Furthermore, there is a lack of means for users to grasp the progress of actually implementing the suggested menu.

[0939] 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.

[0940] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over), means for delivering ingredients based on the generated shopping list, and means for notifying the user of the progress of delivery. This enables menu suggestions based on the user's detailed needs and efficient purchasing and delivery of ingredients based on those suggestions, improving user convenience.

[0941] "Generative AI" refers to artificial intelligence that generates data and information for specific purposes based on input from users.

[0942] "Family composition" refers to the composition of members in the user's household, and includes categories such as adults, children, infants who need baby food, young children who need toddler food, and elderly people.

[0943] "Amount of food" refers to the amount of food the user consumes on a daily basis, including categories such as regular, large, and small portions.

[0944] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes or that may cause an allergic reaction.

[0945] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[0946] "Lifestyle" refers to the behavioral patterns and values ​​of users in their daily lives, and includes categories such as being frugal or health-conscious.

[0947] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[0948] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[0949] A "menu" refers to a meal menu for a specific period of time, including categories such as breakfast, lunch, and dinner.

[0950] A "shopping list" refers to a list of ingredients and other items needed based on a menu.

[0951] "Delivery" refers to the service of delivering ingredients or goods ordered by the user to a specified location.

[0952] "Notification" refers to a method of informing a user of specific information, whether via a smartphone or other device.

[0953] The system for implementing this invention uses generative AI to generate a weekly menu and shopping list that takes into consideration the user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, and delivers ingredients based on this. A specific embodiment of this system is described below.

[0954] Hardware and software used

[0955] Hardware: Smartphones, smart glasses, head-mounted displays

[0956] Software: Generative AI models (e.g., GPT-4®), databases (e.g., MySQL), food delivery APIs (e.g., Uber Eats API)

[0957] Program processing

[0958] Getting User Input

[0959] Using a smartphone, smart glasses, or head-mounted display, users can input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. For example, users can input the following information:

[0960] Family composition: 2 adults, 1 child (toddler meal)

[0961] Amount of food: Normal

[0962] Disliked foods: None

[0963] Health condition: None in particular

[0964] Lifestyle: Frugal

[0965] Seasonal ingredients: sweet potatoes

[0966] Prompt generation for generative AI models

[0967] The server generates a prompt for the generative AI model based on the input information. An example of a prompt is as follows:

[0968] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0969] Generative AI model for generating menus and shopping lists

[0970] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a weekly menu and shopping list. The generated menu and shopping list are stored in a database (e.g., MySQL).

[0971] Integration with food delivery API

[0972] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Once the order is complete, the user is notified and the delivery progress is displayed in real time.

[0973] Specific examples

[0974] For example, if a user inputs "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked ingredients: None", "Health condition: None", "Lifestyle: Frugal", and "Seasonal ingredients: Sweet potato", the generative AI model will generate the following prompt:

[0975] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0976] Based on this prompt, the generative AI model generates a weekly menu and shopping list, stores it in a database, and then uses a food delivery API to order ingredients and notify the user.

[0977] In this way, it becomes possible to propose menus that meet the user's detailed needs, and to efficiently purchase and deliver ingredients based on those menus.

[0978] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0979] Step 1:

[0980] Users use a smartphone, smart glasses, or head-mounted display to input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. The input information is sent from the device to the server. Examples of input data include "Family composition: 2 adults, 1 child (toddler food)", "Food intake: normal", "Food allergies: none", "Health status: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[0981] Step 2:

[0982] The server generates a prompt for the generative AI model based on the received user input. Specifically, it converts the input into text and formats it in a format that the generative AI model can understand. An example of a generated prompt is as follows:

[0983] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[0984] This prompt sentence becomes the input data for the generative AI model.

[0985] Step 3:

[0986] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a week's worth of menus and shopping lists. The generative AI model performs data calculations based on the prompts and outputs appropriate menus and shopping lists. The output data is stored in a database (e.g., MySQL) on the server.

[0987] Step 4:

[0988] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Specifically, it sends each item on the shopping list to the API and processes the order. The API responds with order confirmation information, estimated delivery time, and other information.

[0989] Step 5:

[0990] The server notifies the user that the order has been completed. The notification is sent via a smartphone, smart glasses, or head-mounted display. The notification includes order details and delivery progress. The user can check the delivery status in real time.

[0991] In this way, menu suggestions based on the user's detailed needs and the purchase and delivery of ingredients based on those suggestions can be carried out efficiently.

[0992] Example 2

[0993] Next, a description will be given of Example 2 of Form 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."

[0994] Conventional menu suggestion systems have difficulty in suggesting ingredient selection and cooking procedures based on the user's specific requests. Furthermore, they are unable to make detailed adjustments based on the user's family structure, health condition, or lifestyle, making it difficult to provide suggestions that meet individual needs. Furthermore, there was a lack of a way to properly display the suggested content on the user's device, resulting in low user convenience.

[0995] 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.

[0996] In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition by combining not only adults and children but also baby food, toddler food, and elderly people (ages 0 and over); means for receiving user requests as input and suggesting ingredient selection and cooking procedures based on those requests; and means for transmitting and displaying the generated suggestions to the user's device. This enables suggestions for ingredient selection and cooking procedures based on the user's specific requests, enabling menu suggestions that meet individual needs. Furthermore, by appropriately displaying the suggestions on the user's device, user convenience is improved.

[0997] "Generative AI" is an artificial intelligence technology that automatically generates appropriate ingredient selections and cooking procedures based on information input by the user.

[0998] "User's family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[0999] "Meal Quantity" refers to the amount of food required by each member of the User's household.

[1000] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that cause allergic reactions.

[1001] "Health Status" means information about the health of you and your family, including any specific illnesses or health restrictions.

[1002] "Lifestyle" refers to the daily patterns and habits of the user and their family, including meal times and frequency.

[1003] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1004] "Price of ingredients" refers to price information of ingredients in the market.

[1005] A "menu" refers to a meal plan for a specific period of time (e.g., one week), including the contents of each meal.

[1006] A "shopping list" is a list of ingredients and seasonings needed based on a menu.

[1007] "Request" refers to the specific wishes or requests that a user inputs into the system.

[1008] "Suggestion content" refers to information including ingredient selection and cooking steps generated by generative AI based on the user's requests.

[1009] "Terminal" refers to the device a user uses to interface with the system, including smartphones, tablets, and personal computers.

[1010] The present invention is a system that suggests ingredient selection and cooking procedures based on the specific needs of a user. Specific embodiments of this system will be described below.

[1011] System configuration

[1012] User operations

[1013] The user inputs their request into the system's input screen. For example, they input a prompt such as, "I want to use chicken breast. I want to make a stew." This communicates the user's specific request to the system.

[1014] Server Processing

[1015] The server receives input from the user and analyzes the content. Natural language processing technology is used for analysis. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to understand the content of the request and extract the keywords "chicken breast" and "simmered food."

[1016] Next, the server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[1017] An example of a generated recipe is:

[1018] "Chicken breast stew recipe:

[1019] 1. Cut the chicken breast into bite-sized pieces.

[1020] 2. Heat oil in a pot and fry the chicken breast.

[1021] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1022] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1023] 5. Simmer until all ingredients are soft.

[1024] 6. Finally, adjust the flavor and it's done.

[1025] Terminal display

[1026] The server sends the generated recipe and instructions to the terminal. The HTTP protocol is used for sending. The terminal displays the recipe and instructions sent from the server to the user. Specifically, the following content is displayed on the terminal screen:

[1027] "Chicken breast stew recipe:

[1028] 1. Cut the chicken breast into bite-sized pieces.

[1029] 2. Heat oil in a pot and fry the chicken breast.

[1030] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1031] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1032] 5. Simmer until all ingredients are soft.

[1033] 6. Finally, adjust the flavor and it's done.

[1034] Hardware and software used

[1035] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[1036] Software: Generative AI models (such as OpenAI's GPT-4®), natural language processing libraries (such as SpaCy and NLTK), and HTTP protocols

[1037] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[1038] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1039] Step 1:

[1040] The user inputs a request into the system's input screen. For example, the user inputs a prompt such as, "I want to use chicken breast meat. I want to make a stew." The input request is sent to the system.

[1041] Input: User request (prompt)

[1042] Output: Request sent to the system

[1043] Step 2:

[1044] The server receives requests from users. It analyzes the received requests using natural language processing technology and understands the content of the requests. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to extract the keywords "chicken breast" and "simmered food."

[1045] Input: User request (prompt)

[1046] Output: Analyzed request content (keywords)

[1047] Step 3:

[1048] The server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[1049] Input: Analyzed request content (keywords)

[1050] Output: Generated recipe and instructions

[1051] Step 4:

[1052] The server sends the generated recipe and instructions to the terminal using the HTTP protocol.

[1053] Input: Generated recipe and instructions

[1054] Output: Recipe and instructions sent to the terminal

[1055] Step 5:

[1056] The device displays the recipe and instructions sent from the server to the user. Specifically, the device displays the following on its screen:

[1057] "Chicken breast stew recipe:

[1058] 1. Cut the chicken breast into bite-sized pieces.

[1059] 2. Heat oil in a pot and fry the chicken breast.

[1060] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1061] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1062] 5. Simmer until all ingredients are soft.

[1063] 6. Finally, adjust the flavor and it's done.

[1064] Input: Recipe and instructions sent to the device

[1065] Output: The recipe and instructions displayed to the user

[1066] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[1067] (Application example 2)

[1068] Next, a description will be given of Application Example 2 of Form 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."

[1069] Conventional menu suggestion systems have problems with user convenience, as they are difficult to respond to individual user requests and ingredient selections, and lack the functionality to automatically arrange the necessary ingredients based on the suggested recipe. Furthermore, there is no way to centrally manage and display the suggested recipes and order status, making it difficult for users to procure ingredients and cook without hassle.

[1070] The specific processing by the specific 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 using generative AI to generate a weekly menu and shopping list taking into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only as adults and children but also as a combination of baby food, toddler food, and elderly people (ages 0 and over); means for suggesting appropriate recipes and their procedures based on the ingredients and types of dishes entered by the user; means for selecting the necessary ingredients based on the suggested recipe and automatically arranging for the delivery of the ingredients; and means for displaying the suggested recipe and order status to the user. This enables recipe suggestions and automatic ordering of ingredients according to the user's individual needs, significantly improving user convenience.

[1071] "Generative AI" is artificial intelligence that automatically generates appropriate recipes, ingredient selections, and cooking steps based on user input.

[1072] "Family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, children who need toddler food, and elderly people.

[1073] "Meal portion" refers to the amount of food determined based on the user's family size and individual dietary needs.

[1074] "Ingredients that you dislike / allergic to" are ingredients that you or your family dislike or that may cause an allergic reaction.

[1075] "Health Status" means information about the health of the User and their family, including specific nutrient restrictions and dietary recommendations.

[1076] "Lifestyle" refers to the daily patterns, meal timings, and food preferences of the user and their family.

[1077] "Seasonal ingredients" are those that are the freshest, most nutritious, and most readily available in the market during a particular season.

[1078] "Price of ingredients" refers to price information of ingredients in the market, and is used to select ingredients according to the user's budget.

[1079] A "menu" is a meal plan for a specific period of time (e.g., a week), including the menu for each meal.

[1080] A "shopping list" is a list of ingredients needed based on a menu, helping users to shop efficiently.

[1081] A "recipe" is a detailed description of the steps and ingredients for making a particular dish.

[1082] "Food delivery" is a service that delivers the food ingredients a user needs to a specified location.

[1083] "Order status" is information that indicates the delivery status and arrangement status of ingredients ordered by the user.

[1084] The system for implementing this invention uses generative AI to propose recipes and automatically arrange ingredients according to user requests. Specific embodiments are described below.

[1085] System Configuration

[1086] The system consists of a user terminal, a server, and a food delivery service API. The user terminal is a device such as a smartphone or tablet, and the server is a computer system for running generative AI. The food delivery service API is an external service for managing food ordering and delivery.

[1087] Hardware and software used

[1088] Hardware: smartphones, tablets, servers

[1089] Software: Python, OpenAI API, food delivery service API

[1090] Data processing and calculation

[1091] 1. Obtaining user input: Obtain the ingredients and type of dish entered by the user on the user device. For example, the user enters "I want to use chicken breast."

[1092] 2. Recipe generation using generative AI: The server uses the OpenAI API to generate a recipe and its steps based on the user's request. An example of a prompt is, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps."

[1093] 3. Selecting and ordering ingredients: The server selects the necessary ingredients based on the proposed recipe and places an order through the food delivery service API.

[1094] 4. Displaying the results: The suggested recipes and order status are displayed on the user's device, allowing the user to easily source the necessary ingredients and cook.

[1095] Specific examples

[1096] When a user uses a smartphone application to input "I want to use chicken breast," the server uses the OpenAI API to generate a recipe and instructions for "simmered chicken breast." The generated recipe includes the necessary ingredients, their quantities, and cooking instructions. The server then uses a food delivery service API to automatically order the necessary ingredients (e.g., chicken breast, soy sauce, sugar, mirin, and sake) and arranges for delivery to the address specified by the user. The user can check the suggested recipe and the order status through the application.

[1097] In this way, it becomes possible to propose recipes and automatically arrange ingredients according to the user's individual needs, greatly improving user convenience.

[1098] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1099] Step 1:

[1100] The user launches the smartphone application and inputs the ingredients they want to use and the type of dish they want to make. For example, they might input "I want to use chicken breast." This input information is sent to the server via the application.

[1101] Input: Ingredients and type of dish entered by the user

[1102] Output: User request data sent to the server

[1103] Step 2:

[1104] The server uses a generative AI model to generate an appropriate recipe and its steps based on the received user request data. Specifically, it uses the OpenAI API to generate prompts and have the AI ​​suggest recipes.

[1105] Input: User's desired data

[1106] Output: The generated recipe and its steps

[1107] Specific behavior:

[1108] The server generates a prompt saying, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps." and sends it to the OpenAI API. The server receives the recipe and steps returned by the API.

[1109] Step 3:

[1110] The server selects the necessary ingredients based on the generated recipe, extracts the ingredients and their amounts listed in the recipe, and creates an ingredient list.

[1111] Input: The generated recipe and its steps

[1112] Output: List of ingredients needed

[1113] Specific behavior:

[1114] The server extracts ingredients such as "chicken breast," "soy sauce," "sugar," "mirin," and "sake" from the recipe and creates a list of them.

[1115] Step 4:

[1116] The server uses the food delivery service API to order ingredients based on the created ingredient list. It sends the ingredient list to the API and starts the ordering process.

[1117] Input: List of ingredients needed

[1118] Output: Checkout result

[1119] Specific behavior:

[1120] The server sends the list of ingredients to the food delivery service API and checks whether the order has been successfully received.

[1121] Step 5:

[1122] The server sends the results of the order process and the generated recipe to the user's device, where the user can check the proposed recipe and order status through the application.

[1123] Input: Recipe generated as a result of ordering process

[1124] Output: Recipe and order status displayed on the user's device

[1125] Specific behavior:

[1126] The server sends the order processing results (e.g., order acceptance, estimated delivery date, etc.) and the generated recipe to the user's device and displays them in the application. This allows the user to check when the necessary ingredients will arrive and get ready to start cooking.

[1127] Example 3

[1128] Next, a description will be given of Example 3 of Form Example 3. 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."

[1129] Conventional meal recommendation systems have difficulty adjusting meal portions and nutritional balance appropriately based on the user's health condition and lifestyle. Furthermore, they have not adequately generated menus and shopping lists that take into account the user's family structure and individual dietary restrictions. This makes it difficult for users to select meals that suit their health condition and lifestyle, potentially resulting in inadequate health management.

[1130] The specification process by the specification processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes a means for the user to input health status and lifestyle, a means for the terminal to transmit the input information to the server, a means for the server to generate meal suggestions using the generation AI model, a means for the server to transmit the generated meal suggestions to the terminal, and a means for the terminal to display the meal suggestions to the user. This makes it possible to appropriately adjust the amount of food and nutritional balance according to the user's health status and lifestyle, and to provide meal suggestions that meet individual needs.

[1131] "Generative AI" is an artificial intelligence system that automatically generates meal suggestions, menus, shopping lists, etc. based on information input by the user.

[1132] "User's family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[1133] "Meal amount" refers to the amount of ingredients or food consumed by the user or their family in one meal.

[1134] "Ingredients that you dislike / are allergic to" refers to ingredients that the user or their family dislikes and cannot eat, or ingredients that may cause an allergic reaction.

[1135] "Health status" refers to information about the current health of the user or their family, such as "currently working out" or "currently managing salt intake."

[1136] "Lifestyle" refers to the daily patterns and habits of users and their families, such as "busy weekdays" and "relaxing time on weekends."

[1137] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[1138] "Price of ingredients" refers to the price at which a particular ingredient is sold in the market.

[1139] A "menu" refers to a meal plan for a specific period of time (e.g., a week), including specific dishes and ingredient combinations.

[1140] A "shopping list" is a list of ingredients and seasonings needed based on a menu, and serves as a reference for users when shopping.

[1141] "Terminal" means a device used by a user to input information or receive information from a server, including a smartphone, tablet, or PC.

[1142] "Server" refers to a computer system that receives input information from users, generates meal suggestions using generative AI, and transmits the results to a terminal.

[1143] "Meal suggestions" refer to the specific meal content and nutritional balance suggested by generative AI based on the user's health condition and lifestyle.

[1144] MODE FOR CARRYING OUT THE INVENTION

[1145] This invention is a system that makes meal suggestions based on the user's health condition and lifestyle. Based on the information entered by the user, the system uses a generative AI model to adjust the amount of food and nutritional balance, and makes appropriate meal suggestions.

[1146] Hardware and software used

[1147] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[1148] Software: Generative AI models (e.g., GPT-4®), database management systems (e.g., MySQL), communication protocols (e.g., HTTP / HTTPS)

[1149] Explanation of program processing

[1150] The server receives information about the user's health and lifestyle through the device. For example, the user may enter information such as "I'm doing strength training" or "I'm managing my salt intake." The device uses the HTTP / HTTPS protocol to send this information to the server.

[1151] The server analyzes the received information and generates a prompt for the generative AI model. For example, it generates a prompt such as, "Please generate meal suggestions suitable for a user currently working out." The generative AI model then generates meal suggestions based on this prompt. The generated meal suggestions include specific menu items, such as "chicken breast and broccoli salad."

[1152] The server converts the generated meal suggestions into JSON format and sends them to the device, which then analyzes the data and visually displays it to the user, allowing the user to select the actual meal.

[1153] Specific examples

[1154] Example 1: User working out

[1155] 1. The user types "working out" into the device.

[1156] 2. The device sends this information to the server.

[1157] 3. The server uses the generative AI model to generate protein-rich meal suggestions.

[1158] 4. The server sends the generated proposal to the device.

[1159] 5. The device displays meal suggestions to the user, such as "chicken breast and broccoli salad."

[1160] Example 2: User on salt management

[1161] 1. The user types "salt management" into the terminal.

[1162] 2. The device sends this information to the server.

[1163] 3. The server uses the generative AI model to generate low-salt meal suggestions.

[1164] 4. The server sends the generated proposal to the device.

[1165] 5. The device displays meal suggestions to the user, such as "steamed vegetables with salt-free dressing."

[1166] Prompt Sentence Examples

[1167] "Generate meal suggestions suitable for users who are working out."

[1168] "Generate suitable meal suggestions for users managing their salt intake."

[1169] In this way, the system allows the server, terminal, and user to work together to make meal suggestions that are suited to the user's health condition and lifestyle. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1170] Program processing flow

[1171] Step 1: User inputs health status and lifestyle

[1172] Users use devices such as smartphones or PCs to enter their health status and lifestyle information. For example, users might enter information such as "I'm currently doing strength training" or "I'm currently managing my salt intake." The input form includes text boxes and drop-down menus.

[1173] Input: User's health status and lifestyle (e.g., "Currently working out")

[1174] Output: Input information is saved to the device

[1175] Specific behavior:

[1176] The user launches an application.

[1177] The user responds to the prompt "Please enter your health status" and enters "Working out."

[1178] Step 2: The device sends the input information to the server

[1179] The device sends the health and lifestyle information entered by the user to a server, and this communication is carried out using the HTTP / HTTPS protocol.

[1180] Input: User-entered health and lifestyle information

[1181] Output: The input information is sent to the server

[1182] Specific behavior:

[1183] The terminal converts the input information into JSON format.

[1184] The device sends a POST request to the server's API endpoint.

[1185] Step 3: The server generates meal suggestions using the generative AI model

[1186] The server generates meal suggestions using a generative AI model (e.g., GPT-4 (registered trademark)) based on the received information on the user's health condition and lifestyle. The generative AI model uses pre-trained data to suggest meal amounts and nutritional balance that suit the user's needs.

[1187] Input: User's health and lifestyle information

[1188] Output: Generated meal suggestions

[1189] Specific behavior:

[1190] The server parses the received JSON data.

[1191] The server generates and inputs a prompt sentence to the generative AI model.

[1192] Example: "Generate meal suggestions suitable for a strength training user."

[1193] A generative AI model generates meal suggestions.

[1194] Example: "Chicken breast and broccoli salad"

[1195] Step 4: The server sends the meal suggestions to the device.

[1196] The server then sends the meal suggestions obtained from the generative AI model to the device, again using the HTTP / HTTPS protocol.

[1197] Input: Generated meal suggestions

[1198] Output: Meal suggestions sent to device

[1199] Specific behavior:

[1200] The server converts the generated meal suggestions into JSON format.

[1201] The server sends a POST request to the device's API endpoint.

[1202] Step 5: The device displays meal suggestions to the user.

[1203] The terminal displays the meal suggestions received from the server to the user, who can then use them as a reference to select an actual meal.

[1204] Input: Meal suggestions received from the server

[1205] Output: Meal suggestions are displayed to the user

[1206] Specific behavior:

[1207] The terminal parses the received JSON data.

[1208] The terminal visually displays meal suggestions to the user.

[1209] Example: "Today's meal recommendation: Chicken breast and broccoli salad."

[1210] In this way, the system works in cooperation with the user, the terminal, and the server to make meal suggestions that suit the user's health condition and lifestyle.

[1211] (Application example 3)

[1212] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1213] In modern society, there is a demand for systems that suggest appropriate meals based on the user's health condition and lifestyle, and allow them to easily order these meals in conjunction with delivery services. However, conventional systems have had the problem of making meal suggestions based on the user's detailed health condition and lifestyle, and also of not being able to order these suggestions in conjunction with delivery services.

[1214] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food portions, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for suggesting meals according to the user's health condition and lifestyle and for enabling the user to order those meals in cooperation with a delivery service; and means for displaying the nutritional balance of the suggested meals. This makes it possible to suggest meals based on the user's detailed health condition and lifestyle, and for the suggestion to be easily ordered in cooperation with a delivery service.

[1215] "Generative AI" is an artificial intelligence that makes appropriate meal suggestions and adjusts nutritional balance based on information input by the user.

[1216] "Family composition" is information that indicates the ages and dietary needs of members in the user's household.

[1217] "Meal portion" is information indicating the amount of food consumed by the user or their family in one meal.

[1218] "Ingredients that you dislike / are allergic to" is information that indicates ingredients that the user and their family should avoid.

[1219] "Health status" refers to information about the current health of the user and their family, and includes, for example, "currently doing strength training" or "currently managing salt intake."

[1220] "Lifestyle" is information that indicates the patterns and habits of daily life of the user and their family.

[1221] "Seasonal ingredients" refers to information that indicates the freshest and most nutritious ingredients in a particular season.

[1222] "Price of ingredients" is information indicating the market price of ingredients.

[1223] "Menu" is information indicating the meal menu for a specific period of time.

[1224] A "shopping list" is a list of ingredients needed based on a menu.

[1225] "Delivery service" refers to a service that delivers meals ordered by users to a specified location.

[1226] "Nutritional balance" is information that indicates the proportion and balance of nutrients contained in a meal.

[1227] The system for implementing this invention uses generative AI to suggest meals based on the user's health condition and lifestyle, and also has the function of enabling the user to order those meals in conjunction with a delivery service. Specific embodiments of this system are described below.

[1228] System configuration

[1229] 1. Hardware

[1230] Server: A server for running generative AI. In this case, we use a cloud-based server.

[1231] Device: A smartphone or tablet used by the user, which allows the user to input information about their health and lifestyle and receive dietary suggestions.

[1232] 2. Software

[1233] Generative AI: Uses OpenAI APIs to generate meal suggestions based on user input.

[1234] Delivery service integration module: A module for ordering suggested meals in collaboration with delivery services.

[1235] Nutritional balance display module: A module for displaying the nutritional balance of the proposed meal.

[1236] Data processing and calculation

[1237] 1. User Input

[1238] Users can enter information such as their health status (e.g., strength training, salt management), lifestyle, family composition, and food allergies / dislikes through a smartphone application.

[1239] 2. Generative AI Meal Suggestions

[1240] The server receives input from the user and uses generative AI to generate appropriate meal suggestions, using the following prompt:

[1241] Give users suitable meal suggestions while they are working out.

[1242] 3. Delivery service collaboration

[1243] The suggested meals can be easily ordered by users through a delivery service integration module.

[1244] 4. Nutritional Balance Display

[1245] The nutritional balance of the suggested meal is displayed to the user through a nutritional balance display module.

[1246] Specific examples

[1247] For example, if a user types "I'm working out," the generative AI will suggest a high-protein meal. Specifically, it will generate a menu such as "grilled chicken breast, broccoli, and brown rice." This suggestion can then be easily ordered by the user through a delivery service integration module. Additionally, the nutritional balance display module will show the user the nutritional balance of this meal (e.g., the percentage of protein, carbohydrates, and fat).

[1248] In this way, a system will be realized that can suggest meals based on the user's detailed health condition and lifestyle, and that these suggestions can be easily linked to delivery services for ordering.

[1249] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1250] Step 1:

[1251] The user starts the smartphone application and inputs information such as their health status (e.g., currently doing muscle training, currently managing salt intake), lifestyle, family composition, food allergies / dislikes, etc. This input information is sent to the server via the application.

[1252] Step 2:

[1253] The server receives the input information sent by the user. Based on the received information, it generates a prompt for the generative AI. For example, if the user inputs "Working out," the following prompt is generated:

[1254] Give users suitable meal suggestions while they are working out.

[1255] Step 3:

[1256] The server sends a prompt to the generative AI (OpenAI's API) to generate appropriate meal suggestions. The generative AI processes and calculates data based on the prompt to generate meal suggestions. For example, a menu such as "grilled chicken breast, broccoli, and brown rice" may be generated.

[1257] Step 4:

[1258] The server receives the generated meal suggestions and sends them to a delivery service integration module, which converts the suggested meals into a delivery service ordering format so that the user can easily place an order.

[1259] Step 5:

[1260] The server calculates the nutritional balance of the proposed meal and sends it to a nutritional balance display module, which calculates the proportions and balance of nutrients contained in the meal and displays them to the user.

[1261] Step 6:

[1262] Users can check the nutritional balance of the suggested meals through a smartphone application and order the meals through a delivery service, which then delivers the meals to the specified location.

[1263] In this way, a system is realized that makes it possible to suggest meals based on the user's detailed health condition and lifestyle, and that can also easily order these suggestions in conjunction with a delivery service.

[1264] 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.

[1265] "Example 1"

[1266] One embodiment of the present invention provides a system that uses an emotion engine to recognize a user's emotions. This system generates a weekly menu and shopping list taking into account the user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, as well as the user's emotional state. Specifically, when the user is feeling stressed, the system suggests ingredients and dishes that may alleviate that stress.

[1267] Additionally, when users feel joy, the app suggests ingredients and dishes that may amplify that joy.

[1268] "Example 2"

[1269] In another embodiment of the present invention, a system is provided that uses an emotion engine to suggest ingredient selection and cooking steps based on input information from a user and the user's emotional state. Specifically, when a user is feeling down, the system suggests ingredients and cooking steps that may lift the user's spirits. When a user is excited, the system suggests ingredients and cooking steps that may calm the user's excitement.

[1270] "Example 3"

[1271] As a further embodiment of the present invention, a system is provided that uses an emotion engine to adjust the amount of food and nutritional balance according to the user's emotional state and lifestyle. Specifically, when the user is feeling stressed, the system suggests a food amount and nutritional balance that may reduce the stress. Also, when the user is relaxed, the system suggests a food amount and nutritional balance that may maintain the relaxed state.

[1272] The processing flow of each embodiment will be described below.

[1273] "Example 1"

[1274] Step 1: Recognize the user's emotional state with the emotion engine.

[1275] Step 2: Obtain the user's family composition, food amount, disliked / allergic ingredients, health condition, lifestyle, seasonal ingredients, and ingredient prices from the database.

[1276] Step 3: Generate a weekly menu and shopping list taking into account the information obtained and the user's emotional state.

[1277] "Example 2"

[1278] Step 1: The emotion engine recognizes the user's input information and emotional state. Step 2: Based on the recognized information, it suggests ingredient selection and cooking steps.

[1279] "Example 3"

[1280] Step 1: Recognize the user's emotional state and lifestyle with the emotion engine.

[1281] Step 2: Adjust the amount of food you eat and the nutritional balance based on the information you have gained.

[1282] Example 1

[1283] Next, a description will be given of Example 1 of Form 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."

[1284] Conventional menu suggestion systems can take into account the user's family structure, food intake, dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, but they do not suggest menus that take into account the user's emotional state. As a result, they are unable to provide optimal menus that match the user's emotional state, making it difficult to increase user satisfaction. In addition, there was a lack of a way to display the generated menus and shopping lists on the user's device, so a system that was easy for users to use was needed.

[1285] 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.

[1286] In this invention, the server includes means for using generative artificial intelligence to generate a week's worth of menus and shopping lists that take into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and the elderly, means for recognizing the user's emotional state and adjusting the menus and shopping lists based on that emotional state, and means for displaying the generated menus and shopping lists on the user's terminal. This makes it possible to provide the user with optimal menus and shopping lists that suit their emotional state, thereby increasing user satisfaction.

[1287] "Generative AI" is an AI technology that automatically executes specific tasks based on input information from the user.

[1288] "Family composition" refers to the composition of members in the user's household, and includes categories such as adults, children, infants who need baby food, young children who need toddler food, and elderly people.

[1289] "Meal size" refers to the amount of food a user consumes in one sitting, expressed in categories such as regular, small, medium, or large.

[1290] "Ingredients that you dislike / are allergic to" refers to ingredients that you dislike or that may cause an allergic reaction.

[1291] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[1292] "Lifestyle" refers to a user's daily life patterns and habits, and includes categories such as frugality, health consciousness, and busy lifestyles.

[1293] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most delicious during a particular season.

[1294] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[1295] "Emotional state" refers to the user's current psychological state, including emotions such as stress, joy, and sadness.

[1296] A "menu" refers to a meal plan for a specific period (e.g., a week), including menus for breakfast, lunch, dinner, etc.

[1297] A "shopping list" refers to a list of ingredients and other items needed to make a meal.

[1298] "Terminal" refers to a device used by a user to input information or receive generated information, including smartphones, tablets, and personal computers.

[1299] This invention is a menu suggestion system that uses generative artificial intelligence to generate a week's worth of menus and shopping lists, taking into consideration the user's family structure, food intake, food allergies and dislikes, health condition, lifestyle, seasonal ingredients, and prices of ingredients. It also has a function to recognize the user's emotional state and adjust the menu and shopping list based on that emotional state.

[1300] Hardware and software used

[1301] Hardware: Devices used by users (smartphones, tablets, PCs, etc.), servers

[1302] Software: Generative AI models (e.g., GPT-4®), emotion engines, user interfaces

[1303] Explanation of program processing

[1304] 1. Collection of User-Entered Information

[1305] Users use the device to enter information such as family composition, food intake, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and prices of ingredients.

[1306] Example: A user opens a smartphone app and fills in the input form with the following information: "Family composition: 2 adults, 1 child (toddler food)", "Meal size: normal", "Food dislikes: none", "Health condition: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[1307] 2. Recognizing emotional states

[1308] The server uses an emotion engine to recognize the user's emotional state.

[1309] Example: The server analyzes the user's input, past usage history, and even facial and voice data (if available) to determine whether the user is stressed.

[1310] 3. Menu and shopping list generation

[1311] The server uses a generative AI model (e.g., GPT-4®) to generate a weekly menu and shopping list based on the user's input and emotional state.

[1312] Example: The server inputs the following prompt into the generative AI model: "Family composition: 2 adults, 1 child (toddler food), food amount: normal, disliked ingredients: none, health condition: nothing in particular, lifestyle: frugal, seasonal ingredients: sweet potato, emotional state: stressed." Based on this, the generative AI model generates menus for Monday through Sunday and a list of the ingredients needed to accompany them.

[1313] 4. Displaying the generated results

[1314] The server generates a menu and a shopping list, which are then sent to the terminal and displayed to the user.

[1315] Example: The server generates data and sends it to the device, and the user's smartphone app displays menu suggestions such as "Monday's dinner is a healthy sweet potato soup, and Tuesday's dinner is a budget-friendly chicken and vegetable stir-fry," along with the necessary shopping list.

[1316] Prompt Sentence Examples

[1317] "Family composition: 2 adults, 1 child (baby food), Meal size: Normal, Food dislikes: None, Health condition: None in particular, Lifestyle: Frugal, Seasonal food: Sweet potatoes, Emotional state: Stressed."

[1318] The system allows users to easily get the best meal plans and shopping lists tailored to their individual needs and emotional state.

[1319] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1320] Step 1:

[1321] Collecting user-entered information

[1322] Users use the device to enter information such as family composition, food intake, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and prices of ingredients.

[1323] Input: The user opens the app on their smartphone and fills in the input form with the following information: "Family composition: 2 adults, 1 child (toddler food)", "Meal size: normal", "Food dislikes: none", "Health condition: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[1324] Output: The entered information is sent to the server and stored in a database.

[1325] Specific behavior: When a user enters the required information into the application's input form and presses the submit button, the information is sent to the server.

[1326] Step 2:

[1327] Recognition of emotional states

[1328] The server uses an emotion engine to recognize the user's emotional state.

[1329] Input: The server receives the user's input, past usage history, and even the user's facial and voice data (if available).

[1330] Output: The user's emotional state (e.g., feeling stressed) is recognized and stored in a database.

[1331] Specific operation: The server launches the emotion engine, analyzes the user's input information and past data, and determines the user's emotional state.

[1332] Step 3:

[1333] Menu and shopping list generation

[1334] The server uses a generative AI model (e.g., GPT-4®) to generate a weekly menu and shopping list based on the user's input and emotional state.

[1335] Input: The server inputs the following prompt into the generative AI model: "Family composition: 2 adults, 1 child (toddler food), Meal size: Normal, Food dislikes: None, Health condition: None in particular, Lifestyle: Frugal, Seasonal food: Sweet potato, Emotional state: Stressed."

[1336] Output: The generative AI model generates menus and ingredient lists for each day from Monday to Sunday, which are stored in a database.

[1337] How it works: The server inputs prompts into the generative AI model, which then generates a menu and shopping list based on them.

[1338] Step 4:

[1339] Viewing the generated results

[1340] The server generates a menu and a shopping list, which are then sent to the terminal and displayed to the user.

[1341] Input: Receives server-generated menu and shopping list data.

[1342] Output: The user's smartphone app displays a menu such as "Monday's dinner is a healthy sweet potato soup, and Tuesday's dinner is a budget-friendly chicken and vegetable stir-fry," along with a shopping list.

[1343] Specific operation: The server sends the generated data to the terminal and it is displayed in the user's smartphone app.

[1344] (Application example 1)

[1345] Next, a description will be given of Application Example 1 of Form 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."

[1346] While conventional menu suggestion systems can take into account a user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, they have the problem of not being able to make suggestions that take into account the user's emotional state. Furthermore, they lack the functionality to suggest optimal ingredients in real time while shopping in a physical store and update the shopping list. This resulted in insufficient suggestions for ingredients and dishes that would reduce the user's stress and increase their enjoyment, and reduced shopping efficiency.

[1347] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means. In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for recognizing the user's emotional state and suggesting ingredients and dishes that reduce stress and increase joy based on that emotional state; and means for suggesting optimal ingredients and updating the shopping list in real time while shopping in a physical store. This makes it possible to suggest optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in a physical store.

[1348] "Generative AI" is an artificial intelligence technology that automatically generates data and suggestions for specific purposes based on information input from users.

[1349] "Family composition" refers to the types and number of members in the user's household, including adults, children, infants who need baby food, children who need toddler food, and elderly people.

[1350] "Amount of food" refers to the amount of food the user consumes on a daily basis, and includes quantitative settings such as normal, large, or small.

[1351] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes or that may cause an allergic reaction.

[1352] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[1353] "Lifestyle" refers to the user's behavioral patterns and values ​​in their daily lives, including, for example, styles such as being frugal or health-conscious.

[1354] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[1355] "Prices of ingredients" refers to price information of ingredients in the market, allowing users to make choices according to their budget.

[1356] "Emotional state" refers to the user's current psychological state, including emotions such as stress or joy.

[1357] "Brick and mortar store" refers to a physical store where users actually visit and purchase products.

[1358] "Real-time" refers to immediate response to ongoing user activity.

[1359] "Optimal ingredients" refers to the most suitable ingredients based on the user's input information and emotional state.

[1360] A "shopping list" refers to a list of ingredients and products that a user plans to purchase.

[1361] The system for implementing this invention uses generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices. It also includes a function to recognize the user's emotional state and suggest ingredients and dishes that will reduce stress or increase joy based on that emotional state. It also has a function to suggest optimal ingredients and update the shopping list in real time while shopping in a physical store.

[1362] Hardware and software used

[1363] Hardware: Smartphone

[1364] Software: Python, OpenAI API

[1365] System configuration

[1366] 1. User input: Users enter information about their family composition, food intake, food allergies / dislikes, health status, lifestyle, seasonal ingredients, food prices, and emotional state through a smartphone app.

[1367] 2. Generative AI: Based on the information input by the user, the server uses generative AI (OpenAI's GPT-3) to generate a week's worth of menus and shopping lists.

[1368] 3. Emotion Recognition: The server recognizes the user's emotional state and suggests ingredients and dishes that will reduce stress or increase joy based on that emotional state.

[1369] 4. Real-time suggestions: While shopping in a physical store, the smartphone app will suggest the best ingredients in real time and update your shopping list.

[1370] Specific examples

[1371] The user enters the following information into the app:

[1372] Family composition: 2 adults, 1 child (toddler meal)

[1373] Amount of food: Normal

[1374] Disliked foods: None

[1375] Health condition: None in particular

[1376] Lifestyle: Frugal

[1377] Seasonal ingredients: sweet potatoes

[1378] Food prices: Moderate

[1379] Emotional state: Stress

[1380] Based on this information, the server sends the following prompt to the generative AI:

[1381] Family composition: 2 adults, 1 child (toddler meal)

[1382] Amount of food: Normal

[1383] Food dislikes: None

[1384] Health condition: None

[1385] Lifestyle: Frugal

[1386] Seasonal ingredients: Sweet potatoes

[1387] Food prices: Moderate

[1388] Emotional state: Stress

[1389] Use this information to generate a weekly menu and shopping list.

[1390] Based on this prompt, the generative AI generates a weekly menu and shopping list and returns it to the server. The server then sends this information to a smartphone app and displays it to the user. While shopping in a physical store, the smartphone app suggests optimal ingredients in real time and updates the shopping list.

[1391] In this way, it becomes possible to suggest optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in physical stores.

[1392] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1393] Step 1:

[1394] The user launches the smartphone app and inputs information such as family composition, meal size, food allergies and dislikes, health status, lifestyle, seasonal ingredients, food prices, and emotional state. The input information is then saved in the application's database.

[1395] Step 2:

[1396] The device sends the input information to the server. The server analyzes the received information and generates a prompt to send to the generative AI model. An example of a prompt is as follows:

[1397] Family composition: 2 adults, 1 child (toddler meal)

[1398] Amount of food: Normal

[1399] Food dislikes: None

[1400] Health condition: None

[1401] Lifestyle: Frugal

[1402] Seasonal ingredients: Sweet potatoes

[1403] Food prices: Moderate

[1404] Emotional state: Stress

[1405] Use this information to generate a weekly menu and shopping list.

[1406] Step 3:

[1407] The server sends the generated prompt to a generative AI model (OpenAI's GPT-3), which calculates the data based on the prompt and generates a weekly menu and shopping list. The generated data is returned to the server.

[1408] Step 4:

[1409] The server analyzes the weekly menu and shopping list received from the generative AI model and generates additional data to suggest ingredients and dishes that reduce stress or increase joy based on the user's emotional state. This enables optimal suggestions to be made according to the user's emotional state.

[1410] Step 5:

[1411] The server sends the final menu and shopping list to the device, which displays the received data to the user. The user can check the displayed menu and shopping list and modify them as necessary.

[1412] Step 6:

[1413] When a user goes shopping in a physical store, the device will suggest the best ingredients in real time and update the shopping list. The device will suggest the best ingredients to the user based on the store's location and inventory information.

[1414] Step 7:

[1415] After the user completes their shopping, the device sends the final shopping list to the server, which analyzes the data and updates the database to reflect the next recommendation.

[1416] The above steps make it possible to propose optimal menus and shopping lists based on the user's emotional state, improving the efficiency of shopping in physical stores.

[1417] Example 2

[1418] Next, a description will be given of Example 2 of Form 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."

[1419] Conventional menu suggestion systems make suggestions based on the user's family structure, health status, and lifestyle, but they lack the ability to select ingredients and suggest cooking steps that correspond to the user's specific requests and emotional state. This has led to problems such as an inability to respond to the diverse needs of users and a decrease in satisfaction. In addition, because it is not possible to suggest ingredients and dishes that correspond to the user's emotional state, it is difficult to increase the user's psychological satisfaction.

[1420] 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.

[1421] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by combining adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over), means for suggesting ingredient selection and cooking steps based on the user's requests, and means for suggesting ingredients and cooking steps based on the user's emotional state. This makes it possible to suggest ingredient selection and cooking steps according to the user's specific requests and emotional state.

[1422] "Generative AI" is artificial intelligence that uses natural language processing and machine learning techniques to generate appropriate suggestions and answers based on user input.

[1423] "User's family composition" is information that refers to the ages and roles of members in the user's household (adults, children, babies who need solid food, toddlers, elderly people, etc.).

[1424] "Meal portion" refers to the amount of ingredients or food consumed by the user or their family in one meal.

[1425] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that may cause allergic reactions.

[1426] "Health Status" refers to information about a user's or their family's current health status and specific health goals (e.g., diet, diabetes management, etc.).

[1427] "Lifestyle" refers to information about the daily patterns and habits of the user and their family (e.g., work hours, exercise habits, etc.).

[1428] "Seasonal ingredients" refers to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season or time of year.

[1429] "Prices of ingredients" refers to information about prices of ingredients in the market, and is useful information for users to select ingredients according to their budget.

[1430] A "menu" refers to a meal plan or menu for a specific period of time (e.g., a week), including ingredient selection and cooking instructions.

[1431] A "shopping list" is a list of ingredients and seasonings needed based on a menu, and is information that allows users to shop efficiently.

[1432] "Emotional state" is information that refers to the user's current psychological state (e.g., depressed, excited, etc.).

[1433] "Ingredient selection" refers to the process of selecting appropriate ingredients based on the user's requests and conditions.

[1434] "Cooking instructions" refers to the specific steps and methods for preparing a dish using selected ingredients.

[1435] This invention is a system that uses generative AI to suggest ingredient selection and cooking procedures based on the user's requests and emotional state. Specific embodiments of this system are described below.

[1436] Hardware and software used

[1437] Hardware: Servers, terminals (PCs, smartphones)

[1438] Software: Generative AI models (e.g., GPT-4®), emotion engines (e.g., Affectiva)

[1439] System Overview

[1440] The system generates a weekly menu and shopping list taking into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices. It also suggests ingredient selection and cooking steps based on the user's preferences, and even suggests ingredients and cooking steps based on the user's emotional state.

[1441] Program processing

[1442] 1. User request input

[1443] The user uses a terminal to input requests such as "I want to use chicken breast" or "I want to make a stew" into the system interface.

[1444] Example: A user opens an app on their smartphone, enters "I want to use chicken breast" in the text box, and presses the send button.

[1445] 2. Analysis of requests

[1446] The server receives the request sent by the user and analyzes it using a generative AI model (e.g., GPT-4 (registered trademark)).

[1447] Example: The server receives the text "I want to use chicken breast" and sends the prompt "Please tell me a simple recipe using chicken breast" to the generative AI model.

[1448] 3. Proposal Generation

[1449] The server receives the response from the generative AI model and suggests appropriate recipes and how to make them to the user.

[1450] Example: A generative AI model generates a recipe and instructions for "Boiled Chicken Breast," and the server sends that information to the user's device. The recipe for "Boiled Chicken Breast" is then displayed on the user's smartphone.

[1451] 4. Emotional state analysis

[1452] The user inputs their emotional state through the terminal, or an emotion engine (e.g., Affectiva) analyzes the user's emotional state from their facial expressions and voice.

[1453] Example: A user types "I feel depressed" in text, or a smartphone camera analyzes the user's facial expression, and the emotion engine determines that the user feels "depressed."

[1454] 5. Emotion-based suggestions

[1455] Based on the analysis results of the emotion engine, the server suggests ingredients and cooking procedures that correspond to the user's emotional state.

[1456] Example: The server receives the emotional state "feeling depressed" and sends a prompt to the generative AI model saying, "What food would you recommend when you're feeling depressed?" The generative AI model generates a recipe for "chocolate cake," and the server sends that information to the user's device. The recipe for "chocolate cake" is displayed on the user's smartphone.

[1457] In this way, the system can suggest appropriate ingredients and cooking instructions based on the user's desires and emotional state.

[1458] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1459] Step 1:

[1460] User request input

[1461] Input: The user uses a device (PC or smartphone) to input requests such as "I want to use chicken breast" or "I want to make a stew" into the system interface.

[1462] Specific actions: A user opens the app on their smartphone, enters "I want to use chicken breast" in the text box, and presses the send button.

[1463] Output: The user's request is sent to the server.

[1464] Step 2:

[1465] Request analysis

[1466] Input: The server receives a request sent by the user.

[1467] Specific operation: The server receives the text "I want to use chicken breast" and sends a prompt to the generative AI model (e.g., GPT-4 (registered trademark)) saying "Please tell me a simple recipe using chicken breast."

[1468] Data processing: A generative AI model analyzes the prompt and generates an appropriate recipe.

[1469] Output: The appropriate recipe is returned to the server as a response from the generative AI model.

[1470] Step 3:

[1471] Proposal Generation

[1472] Input: The server receives the response from the generative AI model.

[1473] Specific operation: The generative AI model generates a recipe and instructions for "braised chicken breast," and the server sends this information to the user's device.

[1474] Data processing: The server converts the recipe information received from the generative AI model into a format that can be displayed to the user.

[1475] Output: The recipe for "Simmered Chicken Breast" will be displayed on the user's smartphone.

[1476] Step 4:

[1477] Emotional state analysis

[1478] Input: The user inputs their emotional state through the device, or the emotion engine (e.g., Affectiva) analyzes their emotional state from their facial expressions and voice.

[1479] Specific operation: The user enters "I feel depressed" in text, or the smartphone camera analyzes the user's facial expression, and the emotion engine determines that the user feels "depressed."

[1480] Data processing: The emotion engine analyzes the user's emotional state and sends the results to the server.

[1481] Output: The user's emotional state is sent to the server.

[1482] Step 5:

[1483] Emotion-based suggestions

[1484] Input: The server receives the analysis results of the emotion engine.

[1485] Specific behavior: The server receives the emotional state "feeling depressed" and sends a prompt to the generative AI model: "What dishes would you recommend when feeling depressed?"

[1486] Data processing: A generative AI model analyzes the prompt and generates an appropriate recipe.

[1487] Output: The generative AI model responds by returning an appropriate recipe to the server, which then sends the information to the user's device. The user's smartphone displays the recipe for "Chocolate Cake."

[1488] (Application example 2)

[1489] Next, a description will be given of Application Example 2 of Form 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."

[1490] Conventional meal planning systems could suggest meals based on the user's family structure, health status, and lifestyle, but they could not suggest ingredients or cooking procedures that corresponded to the user's emotional state or specific requests. Furthermore, they lacked the ability to order the suggested dishes for delivery, which resulted in low user convenience.

[1491] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1492] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people aged 0 or older, means for suggesting ingredient selection and cooking procedures based on the user's requests and emotional state, and means for enabling delivery ordering of the suggested dishes. This makes it possible to suggest optimal dishes based on the user's specific requests and emotional state, and to order delivery as is.

[1493] "Generative AI" is artificial intelligence that generates data based on user input and makes optimal suggestions.

[1494] "Family composition" is information that indicates the ages and roles of members in the user's household.

[1495] "Meal portion" is information indicating the amount of food consumed by the user or their family in one meal.

[1496] "Ingredients that you dislike / are allergic to" is information that indicates ingredients that the user or their family dislikes or that may cause allergic reactions.

[1497] "Health status" is information that indicates the current health status of the user and their family members.

[1498] "Lifestyle" is information that indicates the patterns and habits of daily life of the user and their family.

[1499] "Seasonal ingredients" are ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1500] "Price of ingredients" is price information of ingredients in the market.

[1501] A "menu" is a plan showing the menu of meals for a specific period of time.

[1502] A "shopping list" is a list of ingredients and other items to purchase based on a menu.

[1503] A "request" is a user's wish or request for a particular ingredient or dish.

[1504] "Emotional state" is information that indicates the user's current mood or psychological state.

[1505] "Cooking instructions" is information that indicates the specific steps and methods for making a particular dish.

[1506] "Delivery Order" is a service that allows users to order suggested dishes online and have them delivered to their home.

[1507] The system for implementing this invention uses generative AI to suggest ingredient selection and cooking steps based on the user's requests and emotional state, and also has the function of allowing the suggested dishes to be delivered as is. Specific embodiments of this system are described below.

[1508] System Configuration

[1509] The system mainly uses the following hardware and software:

[1510] Hardware: Smartphones, servers

[1511] Software: Python, OpenAI API, Sentiment Analysis API

[1512] Program processing

[1513] The server receives input information from the user and uses generative AI to generate the optimal recipe. Specifically, the process is as follows:

[1514] 1. Getting user input:

[1515] Users input their ingredient and cooking preferences, as well as their current emotional state, through a smartphone application.

[1516] 2. Emotion analysis:

[1517] The server uses an emotion analysis API to analyze the user's input emotional state, thereby identifying the user's current mood.

[1518] 3. Prompt generation:

[1519] The server generates prompts to send to the generative AI based on the user's wishes and emotional state. Examples of prompts are as follows:

[1520] User request: I want to use chicken breast.

[1521] User sentiment: Tired

[1522] Please suggest the best recipe.

[1523] 4. Recipe generation:

[1524] The server sends prompts to the generative AI (OpenAI API) to generate the optimal recipe, which is then displayed to the user.

[1525] 5. Delivery Order:

[1526] Users can then order the suggested recipes for delivery, and the server will then work with the delivery service to process the order.

[1527] Specific examples

[1528] For example, if a user inputs "I want to use chicken breast" and "I'm tired" as their emotional state, the server will use the emotion analysis API to analyze the emotion "I'm tired" and send the following prompt to the generative AI:

[1529] User request: I want to use chicken breast.

[1530] User sentiment: Tired

[1531] Please suggest the best recipe.

[1532] The generative AI suggests a "simple chicken breast stew recipe," and after checking the recipe, users can place a delivery order.

[1533] In this way, a system can be realized that can suggest the most suitable dish based on the user's specific requests and emotional state, and also enable delivery orders to be placed directly.

[1534] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1535] Step 1:

[1536] The user launches the smartphone application and inputs their desired ingredients, cooking preferences, and current emotional state. The input information is then sent to the server. The input data includes specific requests, such as "I want chicken breast" or "I'm tired," as well as their emotional state.

[1537] Step 2:

[1538] The server analyzes the received user input information and sends it to the emotion analysis API. The emotion analysis API analyzes the user's emotional state and identifies emotions such as "tired." The analysis results are sent back to the server. The input data is the user's emotional state, and the output data is the analyzed emotional state.

[1539] Step 3:

[1540] The server generates a prompt to send to the generative AI based on the user's request and the analyzed emotional state. Examples of generated prompts include "User request: I would like to use chicken breast meat," "User emotion: I'm tired," and "Please suggest the best recipe." The input data are the user's request and emotional state, and the output data is the generated prompt.

[1541] Step 4:

[1542] The server sends the generated prompt to the generative AI (OpenAI API). The generative AI generates the optimal recipe based on the prompt and returns the result to the server. The input data is the prompt, and the output data is the generated recipe.

[1543] Step 5:

[1544] The server sends the generated recipe to the user's smartphone application. The user can review the proposed recipe and enter corrections or additions as needed. The input data is the generated recipe, and the output data is the recipe displayed to the user.

[1545] Step 6:

[1546] If the user checks the suggested recipe and places a delivery order, the server works with the delivery service to process the order. The user's order information is sent to the delivery service, and the order is confirmed. The input data is the user's order information, and the output data is the confirmed order information.

[1547] In this way, a system can be realized that can suggest the most suitable dish based on the user's specific requests and emotional state, and also enable delivery orders to be placed directly.

[1548] Example 3

[1549] Next, a description will be given of Example 3 of Form Example 3. 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."

[1550] Conventional meal recommendation systems have difficulty in properly adjusting the amount of food and nutritional balance according to the user's health condition and lifestyle. They also do not adequately generate menus and shopping lists that take into account the user's family structure and individual dietary restrictions. Furthermore, they do not consider meal recommendations based on the user's emotional state, making it impossible to meet the diverse needs of users.

[1551] The specific processing by the specific processing unit 290 of the data processing device 12 in Example 3 is realized by the following means. In this invention, the server includes: means for using a generative AI to generate a one-week menu and shopping list taking into account the user's family composition, food portion sizes, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over); means for receiving information on the user's health condition and lifestyle and inputting prompt sentences into the generative AI model based on that information; means for the generative AI model to generate meal suggestions based on the prompt sentences; and means for displaying the generated meal suggestions to the user. This makes it possible to adjust the amount of food and nutritional balance according to the user's health condition and lifestyle, thereby realizing meal suggestions that meet the diverse needs of users.

[1552] "Generative AI" is an artificial intelligence system that automatically generates meal suggestions, menus, shopping lists, etc. based on information input by the user.

[1553] A "prompt sentence" is an input sentence that provides specific instructions or information to a generative AI, allowing the AI ​​to generate appropriate output based on this.

[1554] "User's family composition" refers to the composition of members in the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[1555] "Meal portion" refers to the amount of food consumed by the user or their family in one meal, and is adjusted according to each individual's health condition and lifestyle.

[1556] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that may cause an allergic reaction.

[1557] "Health status" refers to information about the current health of the user and their family, including specific conditions such as "doing strength training" or "managing salt intake."

[1558] "Lifestyle" refers to the daily patterns and habits of the user and their family, including states such as "feeling stressed" and "relaxed."

[1559] "Seasonal ingredients" refer to ingredients that are the freshest, most nutritious, and most readily available in the market during a particular season.

[1560] "Price of ingredients" refers to the price of ingredients in the market, which is taken into consideration according to the user's budget and economic situation.

[1561] A "menu" refers to a meal plan for a specific period of time (for example, a week), including the contents of each meal and the ingredients needed.

[1562] A "shopping list" is a list of ingredients and other items needed based on a menu, allowing users to shop efficiently.

[1563] This invention is a system that uses generative AI to suggest meals based on a user's health condition and lifestyle. Specific embodiments of this system are described below.

[1564] Hardware and software used

[1565] The system uses the following hardware and software:

[1566] Server: Processes data and runs generative AI models.

[1567] Terminal: A device (smartphone, PC, etc.) through which a user enters information and receives suggestions from the server.

[1568] Generative AI model: An artificial intelligence model that generates meal suggestions based on user input.

[1569] Data processing and calculation

[1570] Server Processing

[1571] The server receives information about the user's health and lifestyle entered on the device. For example, the user enters information such as "I'm working out" or "I'm feeling stressed." The server analyzes this information and inputs prompts into the generative AI model. Examples of prompts include:

[1572] "User inputs that they are working out. Generate protein-rich meal suggestions."

[1573] "User inputs that they are stressed. Generate food suggestions that may reduce stress."

[1574] The generative AI model generates meal suggestions based on a prompt, such as "grilled chicken breast, broccoli, and brown rice."

[1575] Terminal handling

[1576] The device sends the information entered by the user to the server, and displays the meal suggestions received from the server to the user, who then checks the displayed suggestions and selects a meal based on them.

[1577] Specific examples

[1578] 1. User input: The user opens the smartphone application, enters "working out," and presses the "Send" button.

[1579] 2. Sending data from the device to the server: The device converts the information entered by the user into JSON format and sends it to the server using an HTTP request.

[1580] 3. Data processing on the server: The server parses the received JSON data and generates prompt sentences to input into the generative AI model.

[1581] 4. Suggestion generation using generative AI model: The generative AI model generates meal suggestions based on the prompt sentence.

[1582] 5. Data transmission from server to device: The server converts the meal suggestions generated by the generative AI model into JSON format and sends them to the device using an HTTP response.

[1583] 6. Displaying suggestions on the device: The device parses the received JSON data and displays meal suggestions to the user. The user can then review the suggestions on the application screen and select a meal based on the suggestions.

[1584] In this way, meal suggestions are made according to the user's health condition and lifestyle. The flow of the specification process in the third embodiment will be described with reference to FIG.

[1585] Step 1:

[1586] The user opens the application on their smartphone or computer and inputs their health condition and lifestyle. For example, they input information such as "I'm working out" or "I'm feeling stressed," and then press the "Send" button. The input data is information about the user's health condition and lifestyle.

[1587] Step 2:

[1588] The device converts the information entered by the user into JSON format and sends it to the server using an HTTP request. The input data is the health and lifestyle information entered by the user, and the output data is JSON format data sent to the server. Specifically, the device generates the following JSON data:

[1589] json

[1590] {

[1591] "health_status": "Working out",

[1592] "lifestyle": "stressed"

[1593] }

[1594] Step 3:

[1595] The server analyzes the JSON data received from the device. The input data is the JSON format data sent from the device, and the output data is the analyzed information on the user's health condition and lifestyle. Specifically, the server analyzes the JSON data and extracts the following information:

[1596] Health status: Currently working out

[1597] Lifestyle: Feeling stressed

[1598] Step 4:

[1599] The server generates prompt sentences to be input into the generative AI model based on the analyzed information. The input data is the analyzed information on the user's health condition and lifestyle, and the output data is the generated prompt sentence. Specifically, the server generates prompt sentences like the following:

[1600] "User inputs that they are working out. Generate protein-rich meal suggestions."

[1601] "User inputs that they are stressed. Generate food suggestions that may reduce stress."

[1602] Step 5:

[1603] The generative AI model generates meal suggestions based on prompts received from the server. The input data is the prompt sent from the server, and the output data is the generated meal suggestions. Specifically, the generative AI model generates the following meal menu:

[1604] "Grilled chicken breast, broccoli, and brown rice"

[1605] Step 6:

[1606] The server converts the meal suggestions generated by the generative AI model into JSON format and sends it to the device using an HTTP response. The input data is the meal suggestions generated by the generative AI model, and the output data is JSON format data sent to the device. Specifically, the server generates the following JSON data:

[1607] json

[1608] {

[1609] "meal_suggestion": "Grilled chicken breast, broccoli, brown rice"

[1610] }

[1611] Step 7:

[1612] The device parses the JSON data received from the server and displays meal suggestions to the user. The input data is the JSON format data sent from the server, and the output data is the meal suggestions displayed to the user. Specifically, the device displays meal suggestions as follows:

[1613] "Grilled chicken breast, broccoli, and brown rice"

[1614] The user reviews the displayed suggestions and selects meals based on the suggestions.

[1615] (Application example 3)

[1616] Next, a description will be given of Application Example 3 of Form Example 3. 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."

[1617] Conventional meal recommendation systems do not adequately suggest meals based on the user's health and emotional state, and lack a means to easily order the suggested meals. This makes it difficult for users to obtain the meals that best suit their health and emotional state.

[1618] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 3 is realized by the following means. In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list taking into consideration the user's family composition, food amount, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people aged 0 or over; and means for suggesting optimal meals based on the user's health condition and emotional state and ordering those meals in cooperation with a food delivery service. This allows users to easily suggest and order meals that are optimal for their health condition and emotional state.

[1619] "Generative AI" refers to artificial intelligence that generates data and suggestions tailored to specific purposes based on input from users.

[1620] "Family composition" is information that refers to the age and role of each member in the user's household (adult, child, baby who needs solid food, infant, elderly, etc.).

[1621] "Meal amount" refers to the amount of food consumed by the user or their family in one meal.

[1622] "Ingredients that you dislike / have allergies to" refers to ingredients that you or your family dislike or that may cause allergic reactions.

[1623] "Health status" refers to information about the current health of the user or their family (e.g., currently doing strength training, currently managing salt intake, etc.).

[1624] "Lifestyle" refers to the daily patterns and habits of the user and their family (e.g., work hours, frequency of exercise, etc.).

[1625] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1626] "Price of ingredients" refers to the price information of each ingredient in the market.

[1627] A "menu" refers to a meal plan or menu for a specific period of time (e.g., one week).

[1628] A "shopping list" is a list of ingredients and products needed based on a menu.

[1629] "Emotional state" refers to the user's current psychological state (e.g., stressed, relaxed, etc.).

[1630] "Food delivery service" refers to a service that delivers meals ordered by users to a specified location.

[1631] The system for implementing this invention uses generative AI to suggest meals based on the user's health and emotional state, and then works with a food delivery service to order the meals. A specific embodiment of this system is described below.

[1632] First, the user accesses the application using a smartphone. The application provides an interface for inputting information such as the user's family composition, food intake, food allergies and dislikes, health condition, lifestyle, seasonal ingredients, and food prices. In addition to inputting this information, the user also inputs their current health condition (e.g., "currently working out") and emotional state (e.g., "stressed").

[1633] Next, the server uses a generative AI model to generate optimal meal recommendations based on the user's input. This generative AI model has the ability to adjust the amount of food and nutritional balance according to the user's health and emotional state. For example, if a user is "working out" and feeling "stressed," the generative AI model will suggest a meal that is high in protein and contains ingredients that have stress-reducing effects.

[1634] The generated meal suggestions are displayed to the user through the application. The user can review the suggested meals and order the meals through a food delivery service. The order is sent via the server to the food delivery service, which delivers the meal at the specified time.

[1635] The following hardware and software are used to implement this system:

[1636] Smartphone: A device where users enter information and view meal suggestions.

[1637] Server: A computer system for running the generative AI model and generating meal suggestions.

[1638] Generative AI model: An artificial intelligence model that generates meal suggestions based on user input.

[1639] Food delivery service: A service that delivers meals ordered by users.

[1640] As a concrete example, the following is an example of a prompt sentence to be input to a generative AI model:

[1641] "The user's health status is training and their emotional state is stressed. Please suggest the optimal diet."

[1642] By sending this prompt to a generative AI model, meal suggestions such as "high-protein chicken breast salad with brown rice and orange juice containing vitamin C" can be obtained. By ordering this suggestion through a food delivery service, users can easily obtain the meal that best suits their health and emotional state.

[1643] The flow of the specific processing in Application Example 3 will be described with reference to FIG.

[1644] Step 1:

[1645] The user accesses the application using a smartphone. The user inputs information such as family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and food prices. The input information is sent to the server through the application interface. The input data also includes the user's current health condition (e.g., "currently working out") and emotional state (e.g., "stressed").

[1646] Step 2:

[1647] The server generates a prompt for the generative AI model based on the received user input information. The prompt is an instruction for generating meal suggestions based on the user's health and emotional state. For example, a generated prompt might read, "The user's health condition is currently working out, and their emotional state is stressed. Please suggest the optimal meal."

[1648] Step 3:

[1649] The server sends the generated prompt text to the generative AI model. The generative AI model analyzes the prompt text and generates meal suggestions that are optimal for the user's health and emotional state. The generative AI model processes and calculates data based on the user's input information and outputs meal suggestions. For example, a meal suggestion such as "high-protein chicken breast salad with brown rice and orange juice containing vitamin C" may be generated.

[1650] Step 4:

[1651] The server sends the meal suggestions received from the generative AI model to the application, which displays the meal suggestions on the user's smartphone. The user can review the suggested meals and make corrections or changes as needed.

[1652] Step 5:

[1653] The user reviews the meal suggestions and decides to order the meal through a food delivery service. The user confirms the order through the application and the order information is sent to the server.

[1654] Step 6:

[1655] The server sends the received order information to a food delivery service. The food delivery service prepares meals based on the order information and delivers them to the user's designated location at the specified time. The user receives the delivered meal and can enjoy a meal that is optimal for their health and emotional state.

[1656] 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.

[1657] 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> ) and other generative AIs. Data generation models 58

[1658] , 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 the data format of voice data, text data, etc. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1659] Another example of generative AI is Gemini (internet search engine). <url: https: gemini.google.com ?hl="ja">) are mentioned.

[1660] 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.

[1661] [Third embodiment]

[1662] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1663] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1664] 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).

[1665] 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.

[1666] 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.

[1667] 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).

[1668] 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.

[1669] 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.

[1670] 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.

[1671] 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.

[1672] 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.

[1673] Next, the specific processing by the specific processing unit 290 of the data processing device 12 will be described.

[1674] "Example 1"

[1675] One embodiment of the present invention is a menu suggestion system that uses generative AI. This system generates a weekly menu and shopping list based on information input by the user, taking into consideration family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices. Specifically, when a user inputs "Family composition: 2 adults, 1 child (toddler food)," "Meal size: Regular," "Food dislikes: None," "Health condition: None in particular," "Lifestyle: Budget-oriented," and "Seasonal ingredients: Sweet potato," a weekly menu and shopping list are generated based on this information.

[1676] "Example 2"

[1677] Furthermore, in another embodiment of the present invention, the generative AI has the function of suggesting ingredient selection and cooking steps. Specifically, in addition to the menu suggestions mentioned above, if the user inputs requests such as "I want to use chicken breast" or "I want to make a stew," the system will suggest ingredient selection and cooking steps based on these requests. For example, it will suggest a recipe for "stewed chicken breast" and how to make it.

[1678] "Example 3"

[1679] In addition, as a further embodiment of the present invention, the generative AI has the function of adjusting the amount of food and nutritional balance according to the user's health condition and lifestyle. Specifically, when the user inputs their health condition, such as "currently doing strength training" or "currently managing salt intake," the system will suggest the amount of food and nutritional balance taking this information into consideration. For example, for a user who is "currently doing strength training," the system will suggest a meal that is high in protein.

[1680] The processing flow of each embodiment will be described below.

[1681] "Example 1"

[1682] Step 1: The user enters information into the system, such as family composition, food amount, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices.

[1683] Step 2: The generative AI generates a weekly menu and shopping list based on the input information. Step 3: The generated menu and shopping list are presented to the user.

[1684] "Example 2"

[1685] Step 1: The user inputs their request for ingredients and cooking instructions into the system.

[1686] Step 2: Based on the input information, the generative AI suggests ingredient selection and cooking steps.

[1687] Step 3: The user is presented with suggested ingredient choices and cooking instructions.

[1688] "Example 3"

[1689] Step 1: The user enters information about their health and lifestyle into the system.

[1690] Step 2: The generative AI adjusts the amount of food and nutritional balance based on the input information.

[1691] Step 3: The adjusted meal size and nutritional balance are presented to the user.

[1692] Example 1

[1693] Next, a description will be given of Example 1 of Form 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."

[1694] Conventional menu suggestion systems have difficulty generating menus that take into account various factors such as the user's family structure, lifestyle, and health condition. They also lack the means to efficiently process the user's input information and provide appropriate menus and shopping lists. Furthermore, the generated menus often do not match the user's specific needs, failing to increase user satisfaction.

[1695] 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.

[1696] In this invention, the server includes means for using generative artificial intelligence to generate a week's worth of menus and shopping lists that take into consideration the user's family composition, food amounts, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly food, means for sending user input information from the terminal to the server, means for the server to generate prompt sentences based on the received information and input them into the generative artificial intelligence model, and means for sending the generated menus and shopping lists from the server to the terminal, which then displays them to the user. This makes it possible to generate menus and shopping lists that meet the diverse needs of users.

[1697] "Generative AI" is an AI technology that automatically executes specific tasks based on input information from the user.

[1698] "User's family composition" refers to the composition of members in the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people who need special diets.

[1699] "Food portion" refers to the amount of food a user consumes on a daily basis, and is expressed in categories such as normal, large, or small.

[1700] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes and cannot eat, or ingredients that may cause an allergic reaction.

[1701] "Health Status" means information about your current health, including any specific illnesses or health restrictions.

[1702] "Lifestyle" refers to a user's daily life patterns and habits, including, for example, a tendency to save money or a busy lifestyle.

[1703] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1704] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[1705] A "menu" refers to a meal plan for a specific period of time, including specific menus such as breakfast, lunch, and dinner.

[1706] A "shopping list" refers to a list of ingredients and other items needed to make a meal.

[1707] "Terminal" refers to the device used by a user to input information and receive results, including smartphones and personal computers.

[1708] "Server" refers to a computer system that receives input information from a user, processes it, generates a result, and sends it to a terminal.

[1709] A "prompt" refers to a textual instruction that is input into a generative artificial intelligence model and is generated based on information input by the user.

[1710] This invention relates to a menu suggestion system using generative artificial intelligence. This system generates a weekly menu and shopping list based on user input, taking into account family composition, meal size, food allergies / dislikes, health status, lifestyle, seasonal ingredients, and ingredient prices.

[1711] System configuration

[1712] This system includes a terminal used by the user, a server that processes data, and a generative artificial intelligence model. The terminal is a device such as a smartphone or PC that the user uses to input information and receive results. The server is a computer system that receives input information from the user, processes it, generates results, and sends them to the terminal. An example of a generative artificial intelligence model that is used is GPT-4 (registered trademark).

[1713] Processing the data

[1714] Using the device, users input information such as family composition, meal size, food dislikes / allergies, health condition, lifestyle, seasonal ingredients, etc. Specifically, they input information such as "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Food dislikes: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", and "Seasonal ingredients: Sweet potato" into a dedicated input form.

[1715] The device sends the information entered by the user to the server. The server generates a prompt based on the information received from the user. For example, it generates a prompt like this: "My family consists of two adults and one child (baby food). Average food portions. No food dislikes. No particular health condition. My lifestyle is frugal. My seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information."

[1716] The server inputs the generated prompts into a generative AI model to generate a weekly menu and shopping list. Based on the prompts, the generative AI model may decide, for example, that Monday's breakfast is sweet potato and spinach soup, lunch is stir-fried chicken and vegetables, and dinner is boiled fish and rice, with the shopping list including sweet potato, spinach, chicken, and fish.

[1717] The generated menu and shopping list are sent from the server to the device, which then displays them to the user. The user can then view the weekly menu and shopping list in list or calendar format on a dedicated application or web page.

[1718] Specific examples

[1719] Examples of user input include:

[1720] Family composition: 2 adults, 1 child (toddler meal)

[1721] Amount of food: Normal

[1722] Food dislikes: None

[1723] Health condition: None

[1724] Lifestyle: Frugal

[1725] Seasonal ingredients: Sweet potatoes

[1726] An example of the prompt that might be generated is:

[1727] "The family consists of two adults and one child (on toddler food). Average food portions. No food dislikes. No particular health condition. A budget-oriented lifestyle. A seasonal ingredient is sweet potatoes. Please generate a weekly menu and shopping list based on this information."

[1728] In this way, users can easily get a weekly menu and shopping list.

[1729] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1730] Step 1:

[1731] The user uses the terminal to input information such as family composition, food intake, food allergies / dislikes, health condition, lifestyle, and seasonal foods.

[1732] Input: Information entered by the user into the input form (e.g., "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked foods: None", "Health condition: None in particular", "Lifestyle: Budget-oriented", "Seasonal ingredients: Sweet potatoes")

[1733] Output: The entered information is saved on the device.

[1734] Specific operation: The user enters the required information into a dedicated input form and presses the submit button.

[1735] Step 2:

[1736] The terminal transmits the information entered by the user to the server.

[1737] Input: Information entered by the user

[1738] Output: The input information is sent to the server.

[1739] Specific operation: When the submit button on the input form is pressed, the terminal sends the entered information to the server as an HTTP request.

[1740] Step 3:

[1741] The server generates a prompt sentence based on the received user input information.

[1742] Input: User input sent from the device

[1743] Output: Generated prompt (e.g., "The family consists of two adults and one child (toddler food). Average food portion sizes. No food dislikes. No particular health condition. Lifestyle is frugal. Seasonal food is sweet potato. Please generate a weekly menu and shopping list based on this information.")

[1744] Specific operation: The server analyzes the received data and generates a prompt.

[1745] Step 4:

[1746] The server inputs the generated prompts into a generative AI model to generate a week's worth of menus and shopping lists.

[1747] Input: Generated prompt statement

[1748] Output: A weekly meal plan and shopping list returned by the generative AI model (e.g., Monday's breakfast is sweet potato and spinach soup, lunch is chicken and vegetable stir-fry, and dinner is stewed fish with rice. The shopping list includes sweet potato, spinach, chicken, fish, etc.)

[1749] Specific operation: The server sends a prompt to the generative AI model and receives the results returned by the model.

[1750] Step 5:

[1751] The server sends the generated menu and shopping list to the terminal.

[1752] Input: A week's worth of meal plans and a shopping list returned by a generative AI model

[1753] Output: Menu and shopping list sent to device.

[1754] Specific operation: The server sends the generated data to the terminal as an HTTP response.

[1755] Step 6:

[1756] The terminal displays the received menu and shopping list to the user.

[1757] Input: Menu and shopping list sent from the server

[1758] Output: A weekly menu and shopping list displayed to the user

[1759] Specific operation: The device analyzes the received data and displays it in a format that is easy for the user to view. For example, a weekly meal plan and shopping list can be displayed in list or calendar format on a dedicated application or web page.

[1760] (Application example 1)

[1761] Next, a description will be given of Application Example 1 of Form 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."

[1762] Conventional menu suggestion systems have difficulty proposing detailed menus that fit a user's family structure and lifestyle, and have also had the problem of having to purchase and deliver ingredients based on the suggested menu, which can be time-consuming. Furthermore, there is a lack of means for users to grasp the progress of actually implementing the suggested menu.

[1763] 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.

[1764] In this invention, the server includes means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, means for setting the user's family composition not only by adults and children but also by combining baby food, toddler food, and elderly people (ages 0 and over), means for delivering ingredients based on the generated shopping list, and means for notifying the user of the progress of delivery. This enables menu suggestions based on the user's detailed needs and efficient purchasing and delivery of ingredients based on those suggestions, improving user convenience.

[1765] "Generative AI" refers to artificial intelligence that generates data and information for specific purposes based on input from users.

[1766] "Family composition" refers to the composition of members in the user's household, and includes categories such as adults, children, infants who need baby food, young children who need toddler food, and elderly people.

[1767] "Amount of food" refers to the amount of food the user consumes on a daily basis, including categories such as regular, large, and small portions.

[1768] "Ingredients that you dislike / are allergic to" refers to ingredients that the user dislikes or that may cause an allergic reaction.

[1769] "Health Status" means information about your current health, including any specific illnesses or health limitations.

[1770] "Lifestyle" refers to the behavioral patterns and values ​​of users in their daily lives, and includes categories such as being frugal or health-conscious.

[1771] "Seasonal ingredients" refers to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1772] "Price of ingredients" refers to the market price of a particular ingredient, a factor that affects a user's budget.

[1773] A "menu" refers to a meal menu for a specific period of time, including categories such as breakfast, lunch, and dinner.

[1774] A "shopping list" refers to a list of ingredients and other items needed based on a menu.

[1775] "Delivery" refers to the service of delivering ingredients or goods ordered by the user to a specified location.

[1776] "Notification" refers to a method of informing a user of specific information, whether via a smartphone or other device.

[1777] The system for implementing this invention uses generative AI to generate a weekly menu and shopping list that takes into consideration the user's family structure, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices, and delivers ingredients based on this. A specific embodiment of this system is described below.

[1778] Hardware and software used

[1779] Hardware: Smartphones, smart glasses, head-mounted displays

[1780] Software: Generative AI models (e.g., GPT-4®), databases (e.g., MySQL), food delivery APIs (e.g., Uber Eats API)

[1781] Program processing

[1782] Getting User Input

[1783] Using a smartphone, smart glasses, or head-mounted display, users can input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. For example, users can input the following information:

[1784] Family composition: 2 adults, 1 child (toddler meal)

[1785] Amount of food: Normal

[1786] Disliked foods: None

[1787] Health condition: None in particular

[1788] Lifestyle: Frugal

[1789] Seasonal ingredients: sweet potatoes

[1790] Prompt generation for generative AI models

[1791] The server generates a prompt for the generative AI model based on the input information. An example of a prompt is as follows:

[1792] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[1793] Generative AI model for generating menus and shopping lists

[1794] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a weekly menu and shopping list. The generated menu and shopping list are stored in a database (e.g., MySQL).

[1795] Integration with food delivery API

[1796] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Once the order is complete, the user is notified and the delivery progress is displayed in real time.

[1797] Specific examples

[1798] For example, if a user inputs "Family composition: 2 adults, 1 child (toddler food)", "Meal size: Regular", "Disliked ingredients: None", "Health condition: None", "Lifestyle: Frugal", and "Seasonal ingredients: Sweet potato", the generative AI model will generate the following prompt:

[1799] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[1800] Based on this prompt, the generative AI model generates a weekly menu and shopping list, stores it in a database, and then uses a food delivery API to order ingredients and notify the user.

[1801] In this way, it becomes possible to propose menus that meet the user's detailed needs, and to efficiently purchase and deliver ingredients based on those menus.

[1802] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1803] Step 1:

[1804] Users use a smartphone, smart glasses, or head-mounted display to input information such as family composition, food intake, food allergies / dislikes, health status, lifestyle, and seasonal ingredients. The input information is sent from the device to the server. Examples of input data include "Family composition: 2 adults, 1 child (toddler food)", "Food intake: normal", "Food allergies: none", "Health status: none in particular", "Lifestyle: budget-conscious", and "Seasonal ingredients: sweet potato".

[1805] Step 2:

[1806] The server generates a prompt for the generative AI model based on the received user input. Specifically, it converts the input into text and formats it in a format that the generative AI model can understand. An example of a generated prompt is as follows:

[1807] The family consists of two adults and one child (on toddler food), normal food portions, no food dislikes, no particular health condition, a budget-conscious lifestyle, and a seasonal ingredient: sweet potato. Use this information to generate a weekly menu and shopping list.

[1808] This prompt sentence becomes the input data for the generative AI model.

[1809] Step 3:

[1810] The server inputs prompts into a generative AI model (e.g., GPT-4 (registered trademark)) to generate a week's worth of menus and shopping lists. The generative AI model performs data calculations based on the prompts and outputs appropriate menus and shopping lists. The output data is stored in a database (e.g., MySQL) on the server.

[1811] Step 4:

[1812] The server uses a food delivery API (e.g., Uber Eats API) to order the necessary ingredients based on the saved shopping list. Specifically, it sends each item on the shopping list to the API and processes the order. The API responds with order confirmation information, estimated delivery time, and other information.

[1813] Step 5:

[1814] The server notifies the user that the order has been completed. The notification is sent via a smartphone, smart glasses, or head-mounted display. The notification includes order details and delivery progress. The user can check the delivery status in real time.

[1815] In this way, menu suggestions based on the user's detailed needs and the purchase and delivery of ingredients based on those suggestions can be carried out efficiently.

[1816] Example 2

[1817] Next, a description will be given of Example 2 of Form 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."

[1818] Conventional menu suggestion systems have difficulty in suggesting ingredient selection and cooking procedures based on the user's specific requests. Furthermore, they are unable to make detailed adjustments based on the user's family structure, health condition, or lifestyle, making it difficult to provide suggestions that meet individual needs. Furthermore, there was a lack of a way to properly display the suggested content on the user's device, resulting in low user convenience.

[1819] 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.

[1820] In this invention, the server includes: means for using generative AI to generate a weekly menu and shopping list that takes into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition by combining not only adults and children but also baby food, toddler food, and elderly people (ages 0 and over); means for receiving user requests as input and suggesting ingredient selection and cooking procedures based on those requests; and means for transmitting and displaying the generated suggestions to the user's device. This enables suggestions for ingredient selection and cooking procedures based on the user's specific requests, enabling menu suggestions that meet individual needs. Furthermore, by appropriately displaying the suggestions on the user's device, user convenience is improved.

[1821] "Generative AI" is an artificial intelligence technology that automatically generates appropriate ingredient selections and cooking procedures based on information input by the user.

[1822] "User's family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, young children who need toddler food, and elderly people over a certain age.

[1823] "Meal Quantity" refers to the amount of food required by each member of the User's household.

[1824] "Ingredients that you dislike / are allergic to" refers to ingredients that you or your family dislike or that cause allergic reactions.

[1825] "Health Status" means information about the health of you and your family, including any specific illnesses or health restrictions.

[1826] "Lifestyle" refers to the daily patterns and habits of the user and their family, including meal times and frequency.

[1827] "Seasonal ingredients" refer to ingredients that are considered to be at their freshest and most nutritious during a particular season.

[1828] "Price of ingredients" refers to price information of ingredients in the market.

[1829] A "menu" refers to a meal plan for a specific period of time (e.g., one week), including the contents of each meal.

[1830] A "shopping list" is a list of ingredients and seasonings needed based on a menu.

[1831] "Request" refers to the specific wishes or requests that a user inputs into the system.

[1832] "Suggestion content" refers to information including ingredient selection and cooking steps generated by generative AI based on the user's requests.

[1833] "Terminal" refers to the device a user uses to interface with the system, including smartphones, tablets, and personal computers.

[1834] The present invention is a system that suggests ingredient selection and cooking procedures based on the specific needs of a user. Specific embodiments of this system will be described below.

[1835] System configuration

[1836] User operations

[1837] The user inputs their request into the system's input screen. For example, they input a prompt such as, "I want to use chicken breast. I want to make a stew." This communicates the user's specific request to the system.

[1838] Server Processing

[1839] The server receives input from the user and analyzes the content. Natural language processing technology is used for analysis. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to understand the content of the request and extract the keywords "chicken breast" and "simmered food."

[1840] Next, the server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[1841] An example of a generated recipe is:

[1842] "Chicken breast stew recipe:

[1843] 1. Cut the chicken breast into bite-sized pieces.

[1844] 2. Heat oil in a pot and fry the chicken breast.

[1845] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1846] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1847] 5. Simmer until all ingredients are soft.

[1848] 6. Finally, adjust the flavor and it's done.

[1849] Terminal display

[1850] The server sends the generated recipe and instructions to the terminal. The HTTP protocol is used for sending. The terminal displays the recipe and instructions sent from the server to the user. Specifically, the following content is displayed on the terminal screen:

[1851] "Chicken breast stew recipe:

[1852] 1. Cut the chicken breast into bite-sized pieces.

[1853] 2. Heat oil in a pot and fry the chicken breast.

[1854] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1855] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1856] 5. Simmer until all ingredients are soft.

[1857] 6. Finally, adjust the flavor and it's done.

[1858] Hardware and software used

[1859] Hardware: Servers, user devices (smartphones, tablets, PCs, etc.)

[1860] Software: Generative AI models (such as OpenAI's GPT-4®), natural language processing libraries (such as SpaCy and NLTK), and HTTP protocols

[1861] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[1862] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1863] Step 1:

[1864] The user inputs a request into the system's input screen. For example, the user inputs a prompt such as, "I want to use chicken breast meat. I want to make a stew." The input request is sent to the system.

[1865] Input: User request (prompt)

[1866] Output: Request sent to the system

[1867] Step 2:

[1868] The server receives requests from users. It analyzes the received requests using natural language processing technology and understands the content of the requests. Specifically, it uses natural language processing libraries such as SpaCy and NLTK to extract the keywords "chicken breast" and "simmered food."

[1869] Input: User request (prompt)

[1870] Output: Analyzed request content (keywords)

[1871] Step 3:

[1872] The server calls a generative AI model (for example, OpenAI's GPT-4 (registered trademark)) based on the analysis results. When calling, the analysis results are input to the generative AI model as a prompt. The generative AI model generates a recipe for "braised chicken breast" and how to make it based on the input prompt.

[1873] Input: Analyzed request content (keywords)

[1874] Output: Generated recipe and instructions

[1875] Step 4:

[1876] The server sends the generated recipe and instructions to the terminal using the HTTP protocol.

[1877] Input: Generated recipe and instructions

[1878] Output: Recipe and instructions sent to the terminal

[1879] Step 5:

[1880] The device displays the recipe and instructions sent from the server to the user. Specifically, the device displays the following on its screen:

[1881] "Chicken breast stew recipe:

[1882] 1. Cut the chicken breast into bite-sized pieces.

[1883] 2. Heat oil in a pot and fry the chicken breast.

[1884] 3. Add the dashi stock, soy sauce, mirin, and sugar and bring to a boil.

[1885] 4. Add vegetables (e.g. carrots, potatoes) and continue to simmer.

[1886] 5. Simmer until all ingredients are soft.

[1887] 6. Finally, adjust the flavor and it's done.

[1888] Input: Recipe and instructions sent to the device

[1889] Output: The recipe and instructions displayed to the user

[1890] In this way, users can receive cooking suggestions based on their specific requests. The system analyzes the user's requests, generates appropriate recipes using a generative AI model, and displays them on the device, improving user convenience.

[1891] (Application example 2)

[1892] Next, a description will be given of Application Example 2 of Form 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."

[1893] Conventional menu suggestion systems have problems with user convenience, as they are difficult to respond to individual user requests and ingredient selections, and lack the functionality to automatically arrange the necessary ingredients based on the suggested recipe. Furthermore, there is no way to centrally manage and display the suggested recipes and order status, making it difficult for users to procure ingredients and cook without hassle.

[1894] The specific processing by the specific 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 using generative AI to generate a weekly menu and shopping list taking into account the user's family composition, food intake, food allergies / dislikes, health condition, lifestyle, seasonal ingredients, and ingredient prices; means for setting the user's family composition not only as adults and children but also as a combination of baby food, toddler food, and elderly people (ages 0 and over); means for suggesting appropriate recipes and their procedures based on the ingredients and types of dishes entered by the user; means for selecting the necessary ingredients based on the suggested recipe and automatically arranging for the delivery of the ingredients; and means for displaying the suggested recipe and order status to the user. This enables recipe suggestions and automatic ordering of ingredients according to the user's individual needs, significantly improving user convenience.

[1895] "Generative AI" is artificial intelligence that automatically generates appropriate recipes, ingredient selections, and cooking steps based on user input.

[1896] "Family composition" refers to the composition of the user's household, including adults, children, infants who need baby food, children who need toddler food, and elderly people.

[1897] "Meal portion" refers to the amount of food determined based on the user's family size and individual dietary needs.

[1898] "Ingredients that you dislike / allergic to" are ingredients that you or your family dislike or that may cause an allergic reaction.

[1899] "Health Status" means information about the health of the User and their family, including specific nutrient restrictions and dietary recommendations.

[1900] "Lifestyle" refers to the daily patterns, meal timings, and food preferences of the user and their family.

[1901] "Seasonal ingredients" are those that are the freshest, most nutritious, and most readily available in the market during a particular season.

[1902] "Price of ingredients" refers to price information of ingredients in the market, and is used to select ingredients according to the user's budget.

[1903] A "menu" is a meal plan for a specific period of time (e.g., a week), including the menu for each meal.

[1904] A "shopping list" is a list of ingredients needed based on a menu, helping users to shop efficiently.

[1905] A "recipe" is a detailed description of the steps and ingredients for making a particular dish.

[1906] "Food delivery" is a service that delivers the food ingredients a user needs to a specified location.

[1907] "Order status" is information that indicates the delivery status and arrangement status of ingredients ordered by the user.

[1908] The system for implementing this invention uses generative AI to propose recipes and automatically arrange ingredients according to user requests. Specific embodiments are described below.

[1909] System Configuration

[1910] The system consists of a user terminal, a server, and a food delivery service API. The user terminal is a device such as a smartphone or tablet, and the server is a computer system for running generative AI. The food delivery service API is an external service for managing food ordering and delivery.

[1911] Hardware and software used

[1912] Hardware: smartphones, tablets, servers

[1913] Software: Python, OpenAI API, food delivery service API

[1914] Data processing and calculation

[1915] 1. Obtaining user input: Obtain the ingredients and type of dish entered by the user on the user device. For example, the user enters "I want to use chicken breast."

[1916] 2. Recipe generation using generative AI: The server uses the OpenAI API to generate a recipe and its steps based on the user's request. An example of a prompt is, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps."

[1917] 3. Selecting and ordering ingredients: The server selects the necessary ingredients based on the proposed recipe and places an order through the food delivery service API.

[1918] 4. Displaying the results: The suggested recipes and order status are displayed on the user's device, allowing the user to easily source the necessary ingredients and cook.

[1919] Specific examples

[1920] When a user uses a smartphone application to input "I want to use chicken breast," the server uses the OpenAI API to generate a recipe and instructions for "simmered chicken breast." The generated recipe includes the necessary ingredients, their quantities, and cooking instructions. The server then uses a food delivery service API to automatically order the necessary ingredients (e.g., chicken breast, soy sauce, sugar, mirin, and sake) and arranges for delivery to the address specified by the user. The user can check the suggested recipe and the order status through the application.

[1921] In this way, it becomes possible to propose recipes and automatically arrange ingredients according to the user's individual needs, greatly improving user convenience.

[1922] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1923] Step 1:

[1924] The user launches the smartphone application and inputs the ingredients they want to use and the type of dish they want to make. For example, they might input "I want to use chicken breast." This input information is sent to the server via the application.

[1925] Input: Ingredients and type of dish entered by the user

[1926] Output: User request data sent to the server

[1927] Step 2:

[1928] The server uses a generative AI model to generate an appropriate recipe and its steps based on the received user request data. Specifically, it uses the OpenAI API to generate prompts and have the AI ​​suggest recipes.

[1929] Input: User's desired data

[1930] Output: The generated recipe and its steps

[1931] Specific behavior:

[1932] The server generates a prompt saying, "The user says, 'I want to use chicken breast.' Please suggest an appropriate recipe and its steps." and sends it to the OpenAI API. The server receives the recipe and steps returned by the API.

[1933] Step 3:

[1934] The server selects the necessary ingredients based on the generated recipe, extracts the ingredients and their amounts listed in the recipe, and creates an ingredient list.

[1935] Input: The generated recipe and its steps

[1936] Output: List of ingredients needed

[1937] Specific behavior:

[1938] The server extracts ingredients such as "chicken breast," "soy sauce," "sugar," "mirin," and "sake" from the recipe and creates a list of them.

[1939] Step 4:

[1940] The server uses the food delivery service API to order ingredients based on the created ingredient list. It sends the ingredient list to the API and starts the ordering process.

[1941] Input: Li...

Claims

1. A means for generating a one-week menu and shopping list using generative AI, taking into consideration the user's family structure, meal size, food preferences / allergies, health condition, lifestyle, seasonal food, and food prices; A way to set the user's family composition by combining not only adults and children, but also baby food, toddler food, and elderly ages, A method for delivering ingredients based on the generated shopping list; A means of informing users of the progress of their delivery; A system including:

2. The generative AI further includes a means for suggesting ingredient selection and cooking procedures based on input information from a user. The system of claim 1 .

3. The generating AI further includes a means for adjusting the amount of food and nutritional balance according to the user's health condition or lifestyle. The system of claim 1 .

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