System

Abstract

A system is provided.SOLUTION: The system includes means for inputting physical condition data, means for analyzing the input physical condition data, means for generating a menu based on the analyzed physical condition data, means for displaying the generated menu information, means for creating a necessary food material list based on the generated menu, and means for notifying the created food material list.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] In today's modern lifestyles, it is difficult to plan meals that take into account each individual's physical condition and health status. It is also difficult for the whole family to share a consistent, healthy menu. Furthermore, there is a lack of means to properly manage and efficiently purchase the necessary ingredients. To solve these problems, there is a need for a system that can automatically generate menus based on the user's physical condition information and share them with the whole family. [Means for solving the problem]

[0005] The present invention provides a system that includes a means for inputting physical condition data, a means for analyzing the input physical condition data, a means for generating a menu based on the analyzed physical condition data, a means for displaying the generated menu information, a means for creating a necessary ingredient list based on the generated menu, and a means for notifying the user of the created ingredient list. Furthermore, the system also includes a means for sharing menu information among family members, a means for storing the user's home inventory information, and a means for comparing the created ingredient list with the home inventory information, thereby realizing the proposal of a menu suited to the user's physical condition and efficient ingredient management.

[0006] "Physical condition data" is information relating to the user's physical condition and health status, specifically data on fatigue, nutrient deficiencies, allergies, and the like.

[0007] The "analysis means" is a means for evaluating the user's health condition based on the input physical condition data and analyzing the nutrients needed and foods that should be avoided.

[0008] The "means for generating a menu" is a means for automatically creating a meal menu that is optimal for the user's health condition based on the analyzed physical condition data.

[0009] The "means for displaying menu information" refers to a display device or screen for visually presenting the generated menu to the user.

[0010] The "means for creating an ingredient list" is a means for automatically creating a list of necessary ingredients based on the created menu.

[0011] The "means for notifying the ingredient list" is a notification function for informing the user of the created ingredient list, and is provided in the form of email, in-app notification, or the like.

[0012] "Methods of sharing" refers to features for sharing menu information in a way that is accessible to the whole family, including cloud storage and in-app message boards.

[0013] The "means for storing home inventory information" is a means for storing information about ingredients that the user has in their home in a database.

[0014] The "means for checking against home inventory information" is a means for comparing the created ingredient list with the user's home inventory information to identify ingredients that are in short supply. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13]FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, a processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), and an APU (Accelerated Processing Unit).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0036] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0037] Input of user's physical condition data

[0038] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.) The device checks the input data, formats it, and then sends it to the server.

[0039] Analysis of physical condition data

[0040] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0041] Menu generation

[0042] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0043] Display and share menu information

[0044] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0045] Creating a list of ingredients needed

[0046] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0047] Ingredient list notification

[0048] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0049] Specific examples

[0050] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device will send this information to the server. The server will analyze this physical condition data and generate a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, fruit yogurt, etc.). This menu information will be sent to the device and shared so that the user and their family can check it. The server will then compare it with household inventory information, and if salmon or yogurt is low, it will add those ingredients to the list and send a notification to the device. Finally, the user will receive a notification and be able to purchase the necessary ingredients.

[0051] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0052] The processing flow will be explained below.

[0053] Step 1:

[0054] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.).

[0055] Step 2:

[0056] The terminal receives the input physical condition data, formats it, and generates data to be sent to the server.

[0057] Step 3:

[0058] The device sends the prepared data to a server and uploads the health data.

[0059] Step 4:

[0060] The server stores the received physical condition data in a database.

[0061] Step 5:

[0062] The server retrieves the latest health data from the database and begins analysis.

[0063] Step 6:

[0064] The server evaluates the user's health condition based on their physical condition data and analyzes the nutrients they need and foods they should avoid.

[0065] Step 7:

[0066] The server uses the analysis results to generate nutritionally balanced meals, for example, suggesting a meal that includes citrus salad and broccoli for a user who is deficient in vitamin C.

[0067] Step 8:

[0068] The server sends the generated menu to the terminal.

[0069] Step 9:

[0070] The menu information received by the device is displayed within the application so that the user can check it.

[0071] Step 10:

[0072] The user can review the displayed menu and, if desired, upload it to a shared folder or in-app bulletin board that the whole family can access.

[0073] Step 11:

[0074] The server lists all the ingredients needed based on the generated menu.

[0075] Step 12:

[0076] The server compares the user's home inventory information stored in a database with the listed ingredients needed.

[0077] Step 13:

[0078] The server generates a list of missing ingredients based on the matching results.

[0079] Step 14:

[0080] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0081] Step 15:

[0082] The terminal displays the received notification to the user, allowing the user to check the ingredients they need.

[0083] Step 16:

[0084] The user checks the notified list of ingredients and uses it as a shopping list.

[0085] This allows users to easily obtain menus that suit their physical condition and efficiently manage and purchase the ingredients they need.

[0086] Example 1

[0087] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0088] Conventional health management systems lack the support required for users to accurately understand their own health status and take appropriate nutritional supplements and manage their diet. Furthermore, they are unable to efficiently share menu and ingredient information with family members, which leads to duplicate ingredient purchases and makes it difficult to prepare nutritionally balanced meals. Furthermore, there is a demand for a function that creates a list of ingredients needed based on household inventory information and supports waste-free shopping.

[0089] 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.

[0090] In this invention, the server includes means for inputting a user's physical condition data, means for checking and formatting the input physical condition data, means for transmitting the formatted physical condition data to the server, means for storing the received physical condition data in a database, means for analyzing the user's physical condition data and identifying missing nutrients and foods to avoid, means for generating an optimal menu based on the analyzed physical condition data, means for displaying the menu information sent from the server on a terminal, means for sharing the generated menu information with family members via a shared folder or bulletin board function, means for creating a necessary ingredient list based on the generated menu, means for comparing the ingredient list with home inventory information and adding missing ingredients to the final list, means for generating a notification message of the created ingredient list and transmitting it to the terminal, and means for receiving and displaying the notification. This enables the creation of nutritionally balanced menus based on the user's health status, thereby enabling efficient meal preparation and ingredient management at home.

[0091] "Means for inputting user's physical condition data" refers to an interface for the user to input their own health condition, such as an input form, check box, or text box within the application.

[0092] "Means for checking and formatting entered health data" refers to the function by which the system checks data entered by users and converts it into a standard format, such as standardizing date formats and correcting input errors.

[0093] "Means for sending formatted health data to a server" refers to the function of sending formatted data to a server via a network. Generally, communication methods such as the HTTP protocol or WebSocket are used.

[0094] "Means for storing received health data in a database" refers to the function of storing the received data on the server side in an appropriate database, such as an SQL database or NoSQL database.

[0095] "A means of analyzing the user's physical condition data and identifying nutrients that are lacking and foods that should be avoided" refers to a function that uses algorithms and AI models to analyze stored data and identify the nutrients that the user needs and foods that should be avoided.

[0096] "Means for generating optimal menus based on analyzed health data" refers to a function that searches for recipes and nutritional information in a database based on the analysis results and generates menus that are appropriate for the user's health condition.

[0097] "Means for displaying menu information sent from the server on the terminal" refers to the function of displaying menu information generated by the server on the user's terminal (such as a smartphone or tablet).

[0098] "Means for sharing the generated menu information with family members using a shared folder or bulletin board function" refers to the function for sharing the generated menu information through a shared folder or bulletin board function that can be accessed by all family members.

[0099] "Means for creating a list of ingredients required based on the generated menu" refers to a function that compiles a list of ingredients required for cooking based on the generated menu.

[0100] "Means for checking the ingredient list against home inventory information and adding missing ingredients to the final list" refers to a function that compares the generated ingredient list with home inventory information registered in advance by the user and adds only missing ingredients to the final list.

[0101] "Means for generating a notification message for the created ingredient list and sending it to the terminal" refers to a function for generating a notification message based on the required ingredient list and sending it to the user's terminal.

[0102] "Means for receiving and displaying notifications" refers to a function that displays the notification message received by the user's terminal so that the user can check the content.

[0103] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0104] Hardware and Software Configuration

[0105] This system consists of a terminal that receives user input, a server that analyzes data and generates menus, and a database that stores and shares data. Specifically, the system uses the following hardware and software:

[0106] Device: A mobile device such as a smartphone or tablet. The application runs on the iOS or ANDROID (registered trademark) platform.

[0107] Server: A high-performance computing device used to run AI models and analyze data. Specifically, it uses machine learning libraries such as TENSORFLOW (registered trademark) and PyTorch.

[0108] Database: An SQL database (MySQL (registered trademark), PostgreSQL, etc.) or a NoSQL database (MongoDB, etc.). Stores user health data and home inventory information.

[0109] Program processing

[0110] 1. Enter user's physical condition data:

[0111] Users use a dedicated application to input their own physical condition data (fatigue, vitamin deficiencies, allergy information, etc.). The input form has text boxes and check boxes, and is designed to make data entry easy. For example, you might enter, "I feel very tired today."

[0112] 2. Sending health data:

[0113] The device checks the entered data and formats it as needed, for example to standardize date formats or correct typos. The data is then converted to JSON format and sent to the server.

[0114] 3. Analysis of physical condition data:

[0115] The server stores the received health data in a database. A table is created for each user in the database, allowing comparison with past data. The data is then analyzed using an AI model (for example, a model using TensorFlow or PyTorch) to identify nutrient deficiencies and foods that should be avoided.

[0116] 4. Menu generation:

[0117] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects recipes that use ingredients that are high in vitamin C.

[0118] 5. View and share menu information:

[0119] The device receives the menu information sent from the server and displays it on the user interface. The generated menu can also be shared by the whole family using a shared folder or the app's bulletin board function.

[0120] 6. Make a list of ingredients needed:

[0121] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0122] 7. Ingredient List Notification:

[0123] The server generates a notification message based on the final ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can then check the displayed ingredient list and use it as a shopping list.

[0124] Specific examples

[0125] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device converts this information into JSON format and sends it to the server. The server stores the physical condition data in a database and analyzes it. If the analysis results show that the user is lacking in vitamin C, the server will create a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, and fruit yogurt). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or yogurt are low, it adds those ingredients to the list and sends a notification to the device. The user can receive the notification and purchase the necessary ingredients to prepare a nutritionally balanced meal.

[0126] Prompt Sentence Examples

[0127] "For a user who has recently been feeling tired, please suggest a meal plan that contains the appropriate vitamins. Please also note that this user is deficient in vitamin C. Please generate the meal plan and a list of the ingredients required for it."

[0128] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0129] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0130] Step 1:

[0131] The user uses a dedicated application to input data about their physical condition. Information such as fatigue, vitamin deficiencies, and allergies is entered into a form in the application using text boxes and check boxes. The input data (e.g., "I've been feeling tired recently") is sent to the application.

[0132] Step 2:

[0133] The terminal receives the data entered by the user, checks the input data, and formats it. For example, it standardizes the date format and cleans the text data. The formatted data (e.g., {"fatigue": "high", "vitamin deficiency": "vitamin C"}) is generated.

[0134] Step 3:

[0135] The terminal converts the formatted data into JSON format and sends it to the server. This conversion process prepares the data in a format suitable for network communication. After transmission, the server receives the JSON data.

[0136] Step 4:

[0137] The server stores the received health data in a database. Specifically, it creates a table for each user in an SQL or NoSQL database and stores the data. In this step, the health data is persistently stored and can be analyzed.

[0138] Step 5:

[0139] The server analyzes the received health data using an AI model. Specifically, it uses TensorFlow and PyTorch to run a model that evaluates the user's health condition. The model analyzes the input data (e.g., "Vitamin C deficiency") and identifies nutrients that are lacking and foods that should be avoided. An analysis result (e.g., "Vitamin C deficiency") is generated.

[0140] Step 6:

[0141] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects a recipe that uses ingredients that are high in vitamin C. The generated menu (e.g., "Citrus salad, grilled broccoli and salmon") is then generated.

[0142] Step 7:

[0143] The server sends the generated menu information to the terminal. The sent data is displayed on the user interface. For example, "Citrus salad, broccoli and grilled salmon" is displayed on the application screen.

[0144] Step 8:

[0145] The device displays the generated menu information, and the user can review it. The information can also be shared using a shared folder accessible to the whole family or the app's message board function. Clicking the share button uploads the information to the shared folder.

[0146] Step 9:

[0147] The server creates a list of ingredients based on the generated menu. This list is compared with the home inventory information registered in advance by the user. Ingredients already in the home are removed from the list, and only ingredients that are missing are added to the final list. A final ingredient list (e.g., "salmon, yogurt") is generated.

[0148] Step 10:

[0149] The server generates a notification message for the created ingredient list and sends it to the device. The notification message includes a list of the ingredients needed. For example, "You are running low on salmon and yogurt. They have been added to your shopping list."

[0150] Step 11:

[0151] The device receives the notification sent from the server and displays it on the user interface. The user can check the notification and use the required ingredients as a shopping list, which is displayed in the shopping list section of the application.

[0152] (Application example 1)

[0153] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0154] While conventional menu generation systems provide healthy menus based on the user's physical condition, the process of purchasing ingredients is time-consuming, resulting in a lack of user convenience. Furthermore, it is difficult to manage food inventory at home, leading to a high likelihood of unnecessary purchases. To solve these problems, a system is needed that integrates menu generation based on physical condition data with efficient food purchasing and management.

[0155] 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.

[0156] In this invention, the server includes means for inputting physical condition data, means for analyzing the input physical condition data, means for generating a menu based on the analyzed physical condition data, means for displaying the generated menu information, means for creating a required ingredient list based on the generated menu, means for notifying the user of the created ingredient list, and means for transmitting the required ingredient list to the online store via a communications network and performing a bulk purchase procedure. This allows the user to quickly obtain an optimal menu based on their physical condition and efficiently purchase the required ingredients.

[0157] "Physical condition data" is information indicating the user's health condition, such as fatigue, vitamin deficiency, and allergy information.

[0158] The "analyzing means" is a process or device that stores the user's physical condition data in a database and analyzes the data for the purpose of assessing the user's health condition.

[0159] The "means for generating a menu" is a process or system that creates an optimal meal menu based on analyzed physical condition data, taking into consideration the user's nutritional status.

[0160] The "displaying means" refers to a display device or software for visually presenting the generated menu information to the user.

[0161] The "means for creating an ingredient list" is a process or system that identifies the ingredients needed based on the generated menu and compiles them in list form.

[0162] The "notification means" is a message sending device or software for notifying the user of the created ingredient list.

[0163] "Means for sending to the online store via a communications network and completing the bulk purchase procedure" refers to a process or system that sends the created ingredient list to the online store via a network such as the Internet, allowing the user to purchase the ingredients they need in bulk.

[0164] The "means for sharing menu information among family members" is a software function or a shared folder that allows all family members to access the generated menu information.

[0165] "Home inventory information" is information about ingredients currently held in the user's home, and is used to calculate the ingredients that are in short supply.

[0166] The "means for checking against inventory information" is a process or system that compares the home inventory information with the generated ingredient list and excludes ingredients that are already present.

[0167] The present invention is a system that automatically creates healthy menus based on the user's physical condition data, shares that information with family members, notifies them of a list of necessary ingredients, and then transmits the list to an online store via a communication network for bulk purchasing. A specific embodiment of this system will be described below.

[0168] Input of user's physical condition data

[0169] Users use a dedicated smartphone application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). The device checks the input data, formats it, and then sends it to the server.

[0170] Analysis of physical condition data

[0171] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0172] Menu generation

[0173] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0174] Display and share menu information

[0175] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0176] Creating and notifying a list of ingredients needed

[0177] The server creates a list of ingredients needed based on the generated menu. This list is compared with the home inventory information registered in advance by the user, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list. The server then creates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the required ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0178] Send your ingredient list to online stores and buy in bulk

[0179] The server transmits the final ingredient list to the online store via a communication network, allowing the user to order the ingredients they need from the online store in a single purchase.

[0180] Specific examples

[0181] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device sends this information to the server. The server analyzes this physical condition data and generates a menu rich in vitamin C (e.g., orange juice, granola, grilled broccoli and salmon, kiwi fruit salad, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or broccoli are low, it adds those ingredients to the list and sends a notification to the device. Finally, the server sends the ingredient list to an online store, allowing the user to purchase the necessary ingredients in bulk.

[0182] Example prompt sentence:

[0183] The user's health data has been entered. They are deficient in Vitamin C. Based on this data, generate a nutritionally balanced meal plan and create a list of ingredients needed for that plan.

[0184] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0185] Step 1:

[0186] The user inputs their physical condition data using a dedicated smartphone application.

[0187] Input: Physical condition data such as fatigue, vitamin deficiency, and allergy information.

[0188] Specific operation: The user enters their status into each item in the app and presses the send button. The device collects this data, converts it into an appropriate format, and sends it to the server.

[0189] Step 2:

[0190] The server stores the received physical condition data in a database and performs data analysis.

[0191] Input: The user's health data.

[0192] Output: User's health assessment results and a list of nutrients they are lacking and foods they should avoid.

[0193] Specific operation: The server stores the received data in a database and uses the AI ​​model to analyze the data, sending a prompt to the generating AI model such as, "The user's physical condition data has been entered. Please evaluate the user's health condition based on this data."

[0194] Step 3:

[0195] The server automatically generates a menu based on the analysis results.

[0196] Input: Health assessment results, list of nutrients you're lacking and foods to avoid.

[0197] Output: A nutritionally balanced menu.

[0198] Specific operation: Based on the analysis results, the server uses the generative AI model to generate a menu by sending a prompt such as, "Please generate a nutritionally balanced menu that suits the user's health condition." The generated menu is then stored in a database.

[0199] Step 4:

[0200] The server sends the generated menu information to the terminal, which displays it to the user.

[0201] Enter: Menu.

[0202] Output: Menu information displayed to the user.

[0203] Specific operation: The server sends the generated menu information to the device, and the application visually displays it to the user, who can then review it and share it with their family within the app.

[0204] Step 5:

[0205] The server creates a list of ingredients needed based on the generated menu.

[0206] Input: Menu, household inventory information.

[0207] Output: A list of ingredients needed.

[0208] Specific operation: The server compares the information with a pre-registered household inventory database, excludes ingredients already in the home, and adds only ingredients that are in short supply to the list.

[0209] Step 6:

[0210] The server sends the created ingredient list to the terminal, which then displays it to the user.

[0211] Input: List of ingredients needed.

[0212] Output: A list of ingredients that are in short supply and notified to the user.

[0213] Specific operation: The server generates a final ingredient list and sends it to the device as a notification message. The device visually displays the missing ingredients to the user.

[0214] Step 7:

[0215] The server transmits the list of ingredients to the online store via a communication network, and a bulk purchase procedure is carried out.

[0216] Input: Final ingredient list.

[0217] Output: Purchase completion information in the online store.

[0218] Specific operation: The server sends the list of ingredients to the online store's purchasing API, allowing the user to complete the purchase all at once. The user confirms the purchase within the app.

[0219] The above are the specific processing steps.

[0220] 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.

[0221] The present invention is a system that automatically generates healthy menus using not only a user's physical condition data but also their emotional data, shares the menus with family members, and notifies them of necessary ingredients. Specific embodiments of this system will be described below.

[0222] Input of user's physical condition data and emotional data

[0223] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes their current emotional state (e.g., stress, elation, relief, etc.). The device checks the physical condition data and emotional data, formats it, and generates data to be sent to the server.

[0224] Analysis of physical condition data and emotional data

[0225] The server stores the received physical condition and emotional data in a database and analyzes the user's health and emotional state. Specifically, it comprehensively analyzes the user's current physical condition, nutritional status, and emotional state to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[0226] Menu generation

[0227] The server generates an optimal menu based on the analyzed physical condition data and emotional data. The generated menu is not only nutritionally balanced but also takes into consideration the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0228] Display and share menu information

[0229] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0230] Creating a list of ingredients needed

[0231] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0232] Ingredient list notification

[0233] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0234] Specific examples

[0235] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the device sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or almonds are low, it adds those ingredients to the list and sends a notification to the device. Finally, the user receives a notification and can purchase the necessary ingredients.

[0236] In this way, the present invention provides a menu that matches the user's physical condition and emotions, streamlines meal preparation at home, and realizes a system that supports comprehensive health management.

[0237] The processing flow will be explained below.

[0238] Step 1:

[0239] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes the user's current emotional state (e.g., stress, elation, relief, etc.).

[0240] Step 2:

[0241] The terminal receives the input physical condition data and emotion data and formats the data.

[0242] Step 3:

[0243] The terminal sends the formatted data to the server.

[0244] Step 4:

[0245] The server stores the received physical condition data and emotion data in a database.

[0246] Step 5:

[0247] The server retrieves the latest physical condition and emotional data from the database and begins analysis.

[0248] Step 6:

[0249] The server evaluates the user's health and emotional state based on physical condition data and emotional data, and analyzes the nutrients needed, foods to avoid, and ingredients that will boost your mood.

[0250] Step 7:

[0251] The server uses the analysis results to generate a menu that is nutritionally balanced and takes into account the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0252] Step 8:

[0253] The server sends the generated menu to the terminal.

[0254] Step 9:

[0255] The menu information received by the device is displayed within the application so that the user can check it.

[0256] Step 10:

[0257] The user can review the displayed menu and then use the sharing function to upload it to a shared folder or in-app bulletin board that can be accessed by the whole family.

[0258] Step 11:

[0259] The server generates a list of ingredients based on the generated menu. The list contains all the ingredients needed for the dish.

[0260] Step 12:

[0261] The server retrieves the user's home inventory information from a database and compares it with the generated ingredient list.

[0262] Step 13:

[0263] The server generates a list of ingredients that are missing based on the matching results, excluding ingredients that are already in the home.

[0264] Step 14:

[0265] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0266] Step 15:

[0267] The terminal displays the received notification to the user, allowing the user to check the ingredients that are missing.

[0268] Step 16:

[0269] The user can check the list of ingredients they are short of and use it as a shopping list. For example, the user can create a list in the app or on paper and use it to purchase ingredients.

[0270] Through this series of steps, users can easily obtain a menu that best suits their physical condition and emotions, and can also efficiently manage and purchase the necessary ingredients.

[0271] Example 2

[0272] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0273] Conventional menu generation systems only suggest menus based on the user's physical condition data, so they can only suggest uniform menus without considering the user's emotional state. Also, because they create ingredient lists without considering household inventory information, ingredients are likely to be wasted. This has led to issues such as low user satisfaction and a high likelihood of food waste.

[0274] 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.

[0275] In this invention, the server includes means for inputting a user's physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for generating a menu using a generative AI model, means for displaying the generated menu information, means for sharing the displayed menu information, means for creating a necessary ingredient list based on the generated menu, means for comparing the created ingredient list with home inventory information, and means for notifying the user of the created ingredient list. This enables personalized menu suggestions that take the user's physical condition and emotions into consideration, and realizes efficient ingredient management that takes home inventory information into account.

[0276] "User's physical condition data" is information that indicates the user's health condition, such as the user's sense of fatigue, vitamin deficiency, allergy information, and the like.

[0277] "Emotion data" is information that indicates the user's emotional state, such as stress, elation, or relief.

[0278] "Analysis" refers to a process of comprehensively analyzing the user's health condition and emotional state based on the input physical condition data and emotional data.

[0279] "Menu generation" is a process that suggests optimal food and dish combinations to the user based on analyzed physical condition data and emotional data.

[0280] A "generative AI model" is an artificial intelligence model that automatically generates text and information to create menus based on specific prompts.

[0281] "Menu information" is information about the combination of food and dishes that has been generated.

[0282] "Display" refers to visualizing and presenting data or information on a user interface.

[0283] "Sharing" means allowing multiple users to access, view, and use information.

[0284] The "ingredient list" is a list of foods needed to create a menu.

[0285] "Home inventory information" is information about food already in the home.

[0286] A "notification" is a message or other means sent to inform a user of information.

[0287] The present invention is a system that collects data on a user's physical condition and emotions, automatically generates an optimal menu based on that data, shares the menu with family members, and notifies them of a list of necessary ingredients.

[0288] First, the user inputs their own physical condition data using a dedicated application. This data includes information on health conditions such as fatigue, vitamin deficiencies, and allergies. The user then uses the camera to activate an emotion engine that automatically recognizes their own emotional state. The emotion engine can be general facial expression recognition software (e.g., an emotion recognition API) that analyzes facial expressions.

[0289] The device formats and transmits the physical and emotional data obtained from the user to the server using an HTTP POST request, ensuring security using the HTTPS protocol.

[0290] The server stores the received data in a database (for example, a MySQL database) and performs the necessary analysis. This analysis uses data analysis libraries such as Python and Pandas. Specifically, it compares trends in the user's physical condition data and emotional data with past data to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[0291] The server then uses a generative AI model (e.g., a generative AI) to generate a menu based on the prompt, which includes information about the user's current physical condition and emotions, and the generative AI model uses this information to suggest the optimal menu.

[0292] For example, you can generate a plan like this:

[0293] If a user inputs "I've been feeling tired and stressed lately," the server will generate a menu rich in vitamin C and effective in reducing stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This information is sent to the device and can be viewed by the user and their family.

[0294] The server then creates a list of ingredients based on the user's home inventory and the generated menu. The home inventory information is compared with the information stored in the database. The list is adjusted to include only the ingredients that are missing.

[0295] Finally, the server generates this ingredient list as a notification message and sends it to the terminal. The terminal receives the notification and displays it on its user interface. The user can check the displayed ingredient list and use it as a shopping list.

[0296] By integrating this series of processes, it is possible to realize a system that proposes personalized menus tailored to the user's physical condition and emotions, streamlines meal preparation at home, and supports comprehensive health management.

[0297] Example prompt sentence:

[0298] If a user inputs that they have recently been feeling tired and stressed, the system will suggest a menu rich in vitamin C and effective in relieving stress based on the analysis results.

[0299] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0300] Step 1:

[0301] Users use a dedicated application to input their physical condition data. Specifically, they manually enter information such as fatigue, vitamin deficiencies, and allergies into a form on the application screen. In addition, to input or automatically recognize their current emotional state, the camera is used to activate the emotion engine, and emotion data is obtained through facial expression recognition software. The input at this time is information about the user's health and emotional state.

[0302] Step 2:

[0303] The device formats the physical condition and emotion data received from the user and sends it to the server. Specifically, it formats the physical condition and emotion data into a format such as JSON and sends it to the server using an HTTP POST request. This formatted data also includes additional information such as the user ID and timestamp. The input is the formatted physical condition and emotion data obtained from the user, and the output is the data to be sent to the server.

[0304] Step 3:

[0305] The server receives the data sent from the device and stores it in a database. Specifically, it saves the data in a MySQL database. The input at this stage is the physical condition data and emotion data sent from the device, and the output is the data stored in the database. Transactions are used when storing data to ensure data integrity.

[0306] Step 4:

[0307] The server analyzes the stored data. Using Python data analysis libraries (e.g., Pandas, Scikit-learn), it compares trends in the stored physical condition and emotional data with past data to comprehensively analyze the user's current health and emotional state. This analysis identifies nutrients that are lacking, foods to avoid, and ingredients that boost mood. The input is the physical condition and emotional data stored in the database, and the output is the analysis results.

[0308] Step 5:

[0309] The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-4 (registered trademark)). This prompt includes information about the user's physical condition and emotions. Specifically, if the user inputs that they have recently been feeling tired and stressed, the following prompt will be sent to the generative AI model: "Please suggest a menu based on the analysis results that is rich in vitamin C and has a stress-relieving effect." The input is the analysis results, and the output is the prompt.

[0310] Step 6:

[0311] The server generates a menu using a generative AI model. When a prompt is sent to the generative AI model, the model returns an optimal menu that is nutritionally balanced and takes into account the user's emotional state. The input is the prompt, and the output is the generated menu.

[0312] Step 7:

[0313] The terminal receives the menu information sent from the server and displays it on the user interface. Specifically, it displays the menu details, ingredient list, cooking instructions, etc. in a format that is easy for the user to understand. The input is the menu information sent from the server, and the output is the information displayed on the user interface.

[0314] Step 8:

[0315] Users can check the displayed menu information and share it through a shared folder that can be accessed by the whole family or through the message board function within the app. This sharing makes it easier for the whole family to plan meals together. The input is the displayed menu information, and the output is the information to be shared.

[0316] Step 9:

[0317] The server creates a list of ingredients based on the generated menu. First, it checks the home inventory information to remove ingredients already in the home from the list, and then lists only ingredients that are in short supply. The input is the menu and home inventory information, and the output is the final ingredient list.

[0318] Step 10:

[0319] The server generates a notification message based on the created ingredient list and sends it to the terminal. The notification message is sent to the user using the application's notification function. The input is the ingredient list, and the output is the notification message that is displayed to the user.

[0320] Step 11:

[0321] The terminal displays the notification message received from the server on the user interface, and the user can check the displayed ingredient list and use it as a shopping list. The input is the notification message, and the output is the display information on the user interface.

[0322] Through the above processing steps, this system provides personalized menus tailored to the user's physical condition and emotions, streamlines meal planning at home, and realizes a system that supports comprehensive health management.

[0323] (Application example 2)

[0324] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0325] Conventional menu generation systems based on physical condition do not take into account the user's emotional state and do not adequately integrate with household inventory information, making it difficult to streamline the user's overall health management and meal preparation. Furthermore, the system lacks the functionality to instantly order delivery meals based on the generated menu. This means that users have to spend a lot of time planning their own menus, purchasing ingredients, and cooking them.

[0326] 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.

[0327] In this invention, the server includes means for inputting physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for displaying the generated menu information, means for generating an orderable menu based on the generated menu, means for notifying the user of the generated menu, means for confirming a delivery order for the menu selected by the user, and means for sending a delivery notification. This makes it possible to easily generate and display an optimal menu based on the user's physical condition and emotional state, and to directly order delivery, thereby significantly improving the efficiency of the user's health management and meal preparation.

[0328] "Physical condition data" is information relating to the user's health condition, including fatigue, vitamin deficiency, allergy information, and the like.

[0329] "Emotion data" is information about the user's psychological state, including stress, elation, relief, and the like.

[0330] A "menu" is a meal suggestion generated based on the user's physical condition data and emotional data, and takes into consideration nutritional balance and emotional care.

[0331] A "menu" is a list of foods that are provided to the user based on the generated recipe, from which the user can select and order.

[0332] An "orderable menu" is a list of foods that a user can order through a delivery service based on the generated menu.

[0333] "Delivery notification" is information that notifies the user of the delivery status of food after a delivery order has been confirmed.

[0334] "Home inventory information" is information about ingredients currently held in the user's home, and is used to create and compare ingredient lists.

[0335] This invention is a system that generates an optimal menu based on a user's physical condition data and emotional data, generates an orderable menu based on the optimal menu, and places a delivery order. A specific embodiment of this system will be described.

[0336] Entering User Data

[0337] Using a dedicated smartphone app, users input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). An emotion engine is also used to automatically recognize the user's current emotional state (stress, elation, relief, etc.). The physical condition data and emotional data are formatted and sent to the server.

[0338] Data analysis

[0339] The server stores the received physical condition and emotional data in a database and analyzes it. Specifically, the server uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's current health and emotional state. This allows the server to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[0340] Plan and menu generation

[0341] The server generates an optimal menu based on the analysis results, and then generates a menu that the user can order for delivery based on that menu. The menu is generated to balance nutritional balance with emotional care. For example, it may include a salad rich in vitamin C if you are feeling tired, or a relaxing herbal tea if you are stressed.

[0342] Menu Notification and Ordering

[0343] The generated menu is displayed on the smartphone app, allowing the user to review and select an item. Once the user selects a menu item, the order is confirmed and the server generates a delivery notification and sends it to the user. The user can then check the delivery status in real time based on this notification.

[0344] Specific examples

[0345] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the smartphone app will send this information to the server. The server will analyze the physical condition data and emotional data and generate a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, herbal tea, etc.). Based on this menu, it will generate a menu that the user can order and notify the smartphone app. Once the user selects a menu and confirms the order, the server will send a delivery notification, allowing them to check the delivery status.

[0346] Prompt Sentence Examples

[0347] "User ID: 1, physical condition data: fatigue, emotional data: stress"

[0348] Generate appropriate menus based on the user's physical condition and emotions.

[0349] This system will significantly improve the efficiency of users' health management and meal preparation, and enable quick responses through delivery services.

[0350] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0351] Step 1:

[0352] Using a dedicated smartphone app, users input their physical condition data (fatigue, vitamin deficiency, allergy information, etc.), and the emotion engine automatically recognizes their current emotional state (stress, elation, relief, etc.) and inputs the data into the app. The input data is formatted in JSON and sent to the server.

[0353] Input: physical condition data, emotional data

[0354] Output: Pretty-printed JSON data

[0355] Step 2:

[0356] The server stores the received physical condition and emotional data in a database. It uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's health and emotional state. This allows it to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[0357] Input: Formatted JSON data

[0358] Output: Analysis results (nutrients you are lacking, foods to avoid, ingredients that boost your mood)

[0359] Step 3:

[0360] The server then generates an optimal menu based on the analysis results. This menu includes nutritionally balanced foods and foods that take emotional care into consideration. The generated menu is designed to be specific and actionable for the user.

[0361] Input: Analysis results

[0362] Output: Optimal menu

[0363] Step 4:

[0364] The server generates a menu that the user can order from based on the generated menu. The generated menu is displayed on the smartphone app. The user can select from the displayed menu.

[0365] Input: Optimal menu

[0366] Output: Orderable menu

[0367] Step 5:

[0368] The user selects from the displayed menu through the smartphone app and confirms the delivery order. The selected menu is sent to the server and recorded in the order database.

[0369] Input: User's selection from an orderable menu

[0370] Output: Confirmed delivery order

[0371] Step 6:

[0372] The server generates a delivery notification based on the confirmed order details and sends it to the user's smartphone app. The user can receive this delivery notification and check the delivery status in real time.

[0373] Input: Confirmed delivery order

[0374] Output: Delivery notification

[0375] Specific examples

[0376] For example, if a user enters into the app that they have been feeling tired and stressed recently, the smartphone app sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is displayed on the user's smartphone as an optimal menu. The user selects from the displayed menu and confirms the delivery order. If salmon or almonds are in short supply, those ingredients will be delivered based on the delivery notification.

[0377] 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.

[0378] 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> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0379] 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.

[0380] [Second embodiment]

[0381] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0382] 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.

[0383] 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).

[0384] 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.

[0385] 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.

[0386] 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).

[0387] 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.

[0388] 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.

[0389] 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.

[0390] 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.

[0391] 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.

[0392] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0393] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0394] Input of user's physical condition data

[0395] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.) The device checks the input data, formats it, and then sends it to the server.

[0396] Analysis of physical condition data

[0397] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0398] Menu generation

[0399] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0400] Display and share menu information

[0401] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0402] Creating a list of ingredients needed

[0403] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0404] Ingredient list notification

[0405] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0406] Specific examples

[0407] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device will send this information to the server. The server will analyze this physical condition data and generate a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, fruit yogurt, etc.). This menu information will be sent to the device and shared so that the user and their family can check it. The server will then compare it with household inventory information, and if salmon or yogurt is low, it will add those ingredients to the list and send a notification to the device. Finally, the user will receive a notification and be able to purchase the necessary ingredients.

[0408] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0409] The processing flow will be explained below.

[0410] Step 1:

[0411] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.).

[0412] Step 2:

[0413] The terminal receives the input physical condition data, formats it, and generates data to be sent to the server.

[0414] Step 3:

[0415] The device sends the prepared data to a server and uploads the health data.

[0416] Step 4:

[0417] The server stores the received physical condition data in a database.

[0418] Step 5:

[0419] The server retrieves the latest health data from the database and begins analysis.

[0420] Step 6:

[0421] The server evaluates the user's health condition based on their physical condition data and analyzes the nutrients they need and foods they should avoid.

[0422] Step 7:

[0423] The server uses the analysis results to generate nutritionally balanced meals, for example, suggesting a meal that includes citrus salad and broccoli for a user who is deficient in vitamin C.

[0424] Step 8:

[0425] The server sends the generated menu to the terminal.

[0426] Step 9:

[0427] The menu information received by the device is displayed within the application so that the user can check it.

[0428] Step 10:

[0429] The user can review the displayed menu and, if desired, upload it to a shared folder or in-app bulletin board that the whole family can access.

[0430] Step 11:

[0431] The server lists all the ingredients needed based on the generated menu.

[0432] Step 12:

[0433] The server compares the user's home inventory information stored in a database with the listed ingredients needed.

[0434] Step 13:

[0435] The server generates a list of missing ingredients based on the matching results.

[0436] Step 14:

[0437] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0438] Step 15:

[0439] The terminal displays the received notification to the user, allowing the user to check the ingredients they need.

[0440] Step 16:

[0441] The user checks the notified list of ingredients and uses it as a shopping list.

[0442] This allows users to easily obtain menus that suit their physical condition and efficiently manage and purchase the ingredients they need.

[0443] Example 1

[0444] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0445] Conventional health management systems lack the support required for users to accurately understand their own health status and take appropriate nutritional supplements and manage their diet. Furthermore, they are unable to efficiently share menu and ingredient information with family members, which leads to duplicate ingredient purchases and makes it difficult to prepare nutritionally balanced meals. Furthermore, there is a demand for a function that creates a list of ingredients needed based on household inventory information and supports waste-free shopping.

[0446] 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.

[0447] In this invention, the server includes means for inputting a user's physical condition data, means for checking and formatting the input physical condition data, means for transmitting the formatted physical condition data to the server, means for storing the received physical condition data in a database, means for analyzing the user's physical condition data and identifying missing nutrients and foods to avoid, means for generating an optimal menu based on the analyzed physical condition data, means for displaying the menu information sent from the server on a terminal, means for sharing the generated menu information with family members via a shared folder or bulletin board function, means for creating a necessary ingredient list based on the generated menu, means for comparing the ingredient list with home inventory information and adding missing ingredients to the final list, means for generating a notification message of the created ingredient list and transmitting it to the terminal, and means for receiving and displaying the notification. This enables the creation of nutritionally balanced menus based on the user's health status, thereby enabling efficient meal preparation and ingredient management at home.

[0448] "Means for inputting user's physical condition data" refers to an interface for the user to input their own health condition, such as an input form, check box, or text box within the application.

[0449] "Means for checking and formatting entered health data" refers to the function by which the system checks data entered by users and converts it into a standard format, such as standardizing date formats and correcting input errors.

[0450] "Means for sending formatted health data to a server" refers to the function of sending formatted data to a server via a network. Generally, communication methods such as the HTTP protocol or WebSocket are used.

[0451] "Means for storing received health data in a database" refers to the function of storing the received data on the server side in an appropriate database, such as an SQL database or NoSQL database.

[0452] "A means of analyzing the user's physical condition data and identifying nutrients that are lacking and foods that should be avoided" refers to a function that uses algorithms and AI models to analyze stored data and identify the nutrients that the user needs and foods that should be avoided.

[0453] "Means for generating optimal menus based on analyzed health data" refers to a function that searches for recipes and nutritional information in a database based on the analysis results and generates menus that are appropriate for the user's health condition.

[0454] "Means for displaying menu information sent from the server on the terminal" refers to the function of displaying menu information generated by the server on the user's terminal (such as a smartphone or tablet).

[0455] "Means for sharing the generated menu information with family members using a shared folder or bulletin board function" refers to the function for sharing the generated menu information through a shared folder or bulletin board function that can be accessed by all family members.

[0456] "Means for creating a list of ingredients required based on the generated menu" refers to a function that compiles a list of ingredients required for cooking based on the generated menu.

[0457] "Means for checking the ingredient list against home inventory information and adding missing ingredients to the final list" refers to a function that compares the generated ingredient list with home inventory information registered in advance by the user and adds only missing ingredients to the final list.

[0458] "Means for generating a notification message for the created ingredient list and sending it to the terminal" refers to a function for generating a notification message based on the required ingredient list and sending it to the user's terminal.

[0459] "Means for receiving and displaying notifications" refers to a function that displays the notification message received by the user's terminal so that the user can check the content.

[0460] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0461] Hardware and Software Configuration

[0462] This system consists of a terminal that receives user input, a server that analyzes data and generates menus, and a database that stores and shares data. Specifically, the system uses the following hardware and software:

[0463] Device: A mobile device such as a smartphone or tablet. The application runs on the iOS or Android platform.

[0464] Server: A high-performance computing device used to run AI models and analyze data. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch.

[0465] Database: An SQL database (MySQL, PostgreSQL, etc.) or a NoSQL database (MongoDB, etc.) that stores user health data and home inventory information.

[0466] Program processing

[0467] 1. Enter user's physical condition data:

[0468] Users use a dedicated application to input their own physical condition data (fatigue, vitamin deficiencies, allergy information, etc.). The input form has text boxes and check boxes, and is designed to make data entry easy. For example, you might enter, "I feel very tired today."

[0469] 2. Sending health data:

[0470] The device checks the entered data and formats it as needed, for example to standardize date formats or correct typos. The data is then converted to JSON format and sent to the server.

[0471] 3. Analysis of physical condition data:

[0472] The server stores the received health data in a database. A table is created for each user in the database, allowing comparison with past data. The data is then analyzed using an AI model (for example, a model using TensorFlow or PyTorch) to identify nutrient deficiencies and foods that should be avoided.

[0473] 4. Menu generation:

[0474] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects recipes that use ingredients that are high in vitamin C.

[0475] 5. View and share menu information:

[0476] The device receives the menu information sent from the server and displays it on the user interface. The generated menu can also be shared by the whole family using a shared folder or the app's bulletin board function.

[0477] 6. Make a list of ingredients needed:

[0478] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0479] 7. Ingredient List Notification:

[0480] The server generates a notification message based on the final ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can then check the displayed ingredient list and use it as a shopping list.

[0481] Specific examples

[0482] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device converts this information into JSON format and sends it to the server. The server stores the physical condition data in a database and analyzes it. If the analysis results show that the user is lacking in vitamin C, the server will create a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, and fruit yogurt). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or yogurt are low, it adds those ingredients to the list and sends a notification to the device. The user can receive the notification and purchase the necessary ingredients to prepare a nutritionally balanced meal.

[0483] Prompt Sentence Examples

[0484] "For a user who has recently been feeling tired, please suggest a meal plan that contains the appropriate vitamins. Please also note that this user is deficient in vitamin C. Please generate the meal plan and a list of the ingredients required for it."

[0485] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0486] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0487] Step 1:

[0488] The user uses a dedicated application to input data about their physical condition. Information such as fatigue, vitamin deficiencies, and allergies is entered into a form in the application using text boxes and check boxes. The input data (e.g., "I've been feeling tired recently") is sent to the application.

[0489] Step 2:

[0490] The terminal receives the data entered by the user, checks the input data, and formats it. For example, it standardizes the date format and cleans the text data. The formatted data (e.g., {"fatigue": "high", "vitamin deficiency": "vitamin C"}) is generated.

[0491] Step 3:

[0492] The terminal converts the formatted data into JSON format and sends it to the server. This conversion process prepares the data in a format suitable for network communication. After transmission, the server receives the JSON data.

[0493] Step 4:

[0494] The server stores the received health data in a database. Specifically, it creates a table for each user in an SQL or NoSQL database and stores the data. In this step, the health data is persistently stored and can be analyzed.

[0495] Step 5:

[0496] The server analyzes the received health data using an AI model. Specifically, it uses TensorFlow and PyTorch to run a model that evaluates the user's health condition. The model analyzes the input data (e.g., "Vitamin C deficiency") and identifies nutrients that are lacking and foods that should be avoided. An analysis result (e.g., "Vitamin C deficiency") is generated.

[0497] Step 6:

[0498] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects a recipe that uses ingredients that are high in vitamin C. The generated menu (e.g., "Citrus salad, grilled broccoli and salmon") is then generated.

[0499] Step 7:

[0500] The server sends the generated menu information to the terminal. The sent data is displayed on the user interface. For example, "Citrus salad, broccoli and grilled salmon" is displayed on the application screen.

[0501] Step 8:

[0502] The device displays the generated menu information, and the user can review it. The information can also be shared using a shared folder accessible to the whole family or the app's message board function. Clicking the share button uploads the information to the shared folder.

[0503] Step 9:

[0504] The server creates a list of ingredients based on the generated menu. This list is compared with the home inventory information registered in advance by the user. Ingredients already in the home are removed from the list, and only ingredients that are missing are added to the final list. A final ingredient list (e.g., "salmon, yogurt") is generated.

[0505] Step 10:

[0506] The server generates a notification message for the created ingredient list and sends it to the device. The notification message includes a list of the ingredients needed. For example, "You are running low on salmon and yogurt. They have been added to your shopping list."

[0507] Step 11:

[0508] The device receives the notification sent from the server and displays it on the user interface. The user can check the notification and use the required ingredients as a shopping list, which is displayed in the shopping list section of the application.

[0509] (Application example 1)

[0510] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0511] While conventional menu generation systems provide healthy menus based on the user's physical condition, the process of purchasing ingredients is time-consuming, resulting in a lack of user convenience. Furthermore, it is difficult to manage food inventory at home, leading to a high likelihood of unnecessary purchases. To solve these problems, a system is needed that integrates menu generation based on physical condition data with efficient food purchasing and management.

[0512] 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.

[0513] In this invention, the server includes means for inputting physical condition data, means for analyzing the input physical condition data, means for generating a menu based on the analyzed physical condition data, means for displaying the generated menu information, means for creating a required ingredient list based on the generated menu, means for notifying the user of the created ingredient list, and means for transmitting the required ingredient list to the online store via a communications network and performing a bulk purchase procedure. This allows the user to quickly obtain an optimal menu based on their physical condition and efficiently purchase the required ingredients.

[0514] "Physical condition data" is information indicating the user's health condition, such as fatigue, vitamin deficiency, and allergy information.

[0515] The "analyzing means" is a process or device that stores the user's physical condition data in a database and analyzes the data for the purpose of assessing the user's health condition.

[0516] The "means for generating a menu" is a process or system that creates an optimal meal menu based on analyzed physical condition data, taking into consideration the user's nutritional status.

[0517] The "displaying means" refers to a display device or software for visually presenting the generated menu information to the user.

[0518] The "means for creating an ingredient list" is a process or system that identifies the ingredients needed based on the generated menu and compiles them in list form.

[0519] The "notification means" is a message sending device or software for notifying the user of the created ingredient list.

[0520] "Means for sending to the online store via a communications network and completing the bulk purchase procedure" refers to a process or system that sends the created ingredient list to the online store via a network such as the Internet, allowing the user to purchase the ingredients they need in bulk.

[0521] The "means for sharing menu information among family members" is a software function or a shared folder that allows all family members to access the generated menu information.

[0522] "Home inventory information" is information about ingredients currently held in the user's home, and is used to calculate the ingredients that are in short supply.

[0523] The "means for checking against inventory information" is a process or system that compares the home inventory information with the generated ingredient list and excludes ingredients that are already present.

[0524] The present invention is a system that automatically creates healthy menus based on the user's physical condition data, shares that information with family members, notifies them of a list of necessary ingredients, and then transmits the list to an online store via a communication network for bulk purchasing. A specific embodiment of this system will be described below.

[0525] Input of user's physical condition data

[0526] Users use a dedicated smartphone application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). The device checks the input data, formats it, and then sends it to the server.

[0527] Analysis of physical condition data

[0528] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0529] Menu generation

[0530] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0531] Display and share menu information

[0532] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0533] Creating and notifying a list of ingredients needed

[0534] The server creates a list of ingredients needed based on the generated menu. This list is compared with the home inventory information registered in advance by the user, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list. The server then creates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the required ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0535] Send your ingredient list to online stores and buy in bulk

[0536] The server transmits the final ingredient list to the online store via a communication network, allowing the user to order the ingredients they need from the online store in a single purchase.

[0537] Specific examples

[0538] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device sends this information to the server. The server analyzes this physical condition data and generates a menu rich in vitamin C (e.g., orange juice, granola, grilled broccoli and salmon, kiwi fruit salad, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or broccoli are low, it adds those ingredients to the list and sends a notification to the device. Finally, the server sends the ingredient list to an online store, allowing the user to purchase the necessary ingredients in bulk.

[0539] Example prompt sentence:

[0540] The user's health data has been entered. They are deficient in Vitamin C. Based on this data, generate a nutritionally balanced meal plan and create a list of ingredients needed for that plan.

[0541] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0542] Step 1:

[0543] The user inputs their physical condition data using a dedicated smartphone application.

[0544] Input: Physical condition data such as fatigue, vitamin deficiency, and allergy information.

[0545] Specific operation: The user enters their status into each item in the app and presses the send button. The device collects this data, converts it into an appropriate format, and sends it to the server.

[0546] Step 2:

[0547] The server stores the received physical condition data in a database and performs data analysis.

[0548] Input: The user's health data.

[0549] Output: User's health assessment results and a list of nutrients they are lacking and foods they should avoid.

[0550] Specific operation: The server stores the received data in a database and uses the AI ​​model to analyze the data, sending a prompt to the generating AI model such as, "The user's physical condition data has been entered. Please evaluate the user's health condition based on this data."

[0551] Step 3:

[0552] The server automatically generates a menu based on the analysis results.

[0553] Input: Health assessment results, list of nutrients you're lacking and foods to avoid.

[0554] Output: A nutritionally balanced menu.

[0555] Specific operation: Based on the analysis results, the server uses the generative AI model to generate a menu by sending a prompt such as, "Please generate a nutritionally balanced menu that suits the user's health condition." The generated menu is then stored in a database.

[0556] Step 4:

[0557] The server sends the generated menu information to the terminal, which displays it to the user.

[0558] Enter: Menu.

[0559] Output: Menu information displayed to the user.

[0560] Specific operation: The server sends the generated menu information to the device, and the application visually displays it to the user, who can then review it and share it with their family within the app.

[0561] Step 5:

[0562] The server creates a list of ingredients needed based on the generated menu.

[0563] Input: Menu, household inventory information.

[0564] Output: A list of ingredients needed.

[0565] Specific operation: The server compares the information with a pre-registered household inventory database, excludes ingredients already in the home, and adds only ingredients that are in short supply to the list.

[0566] Step 6:

[0567] The server sends the created ingredient list to the terminal, which then displays it to the user.

[0568] Input: List of ingredients needed.

[0569] Output: A list of ingredients that are in short supply and notified to the user.

[0570] Specific operation: The server generates a final ingredient list and sends it to the device as a notification message. The device visually displays the missing ingredients to the user.

[0571] Step 7:

[0572] The server transmits the list of ingredients to the online store via a communication network, and a bulk purchase procedure is carried out.

[0573] Input: Final ingredient list.

[0574] Output: Purchase completion information in the online store.

[0575] Specific operation: The server sends the list of ingredients to the online store's purchasing API, allowing the user to complete the purchase all at once. The user confirms the purchase within the app.

[0576] The above are the specific processing steps.

[0577] 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.

[0578] The present invention is a system that automatically generates healthy menus using not only a user's physical condition data but also their emotional data, shares the menus with family members, and notifies them of necessary ingredients. Specific embodiments of this system will be described below.

[0579] Input of user's physical condition data and emotional data

[0580] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes their current emotional state (e.g., stress, elation, relief, etc.). The device checks the physical condition data and emotional data, formats it, and generates data to be sent to the server.

[0581] Analysis of physical condition data and emotional data

[0582] The server stores the received physical condition and emotional data in a database and analyzes the user's health and emotional state. Specifically, it comprehensively analyzes the user's current physical condition, nutritional status, and emotional state to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[0583] Menu generation

[0584] The server generates an optimal menu based on the analyzed physical condition data and emotional data. The generated menu is not only nutritionally balanced but also takes into consideration the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0585] Display and share menu information

[0586] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0587] Creating a list of ingredients needed

[0588] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0589] Ingredient list notification

[0590] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0591] Specific examples

[0592] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the device sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or almonds are low, it adds those ingredients to the list and sends a notification to the device. Finally, the user receives a notification and can purchase the necessary ingredients.

[0593] In this way, the present invention provides a menu that matches the user's physical condition and emotions, streamlines meal preparation at home, and realizes a system that supports comprehensive health management.

[0594] The processing flow will be explained below.

[0595] Step 1:

[0596] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes the user's current emotional state (e.g., stress, elation, relief, etc.).

[0597] Step 2:

[0598] The terminal receives the input physical condition data and emotion data and formats the data.

[0599] Step 3:

[0600] The terminal sends the formatted data to the server.

[0601] Step 4:

[0602] The server stores the received physical condition data and emotion data in a database.

[0603] Step 5:

[0604] The server retrieves the latest physical condition and emotional data from the database and begins analysis.

[0605] Step 6:

[0606] The server evaluates the user's health and emotional state based on physical condition data and emotional data, and analyzes the nutrients needed, foods to avoid, and ingredients that will boost your mood.

[0607] Step 7:

[0608] The server uses the analysis results to generate a menu that is nutritionally balanced and takes into account the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0609] Step 8:

[0610] The server sends the generated menu to the terminal.

[0611] Step 9:

[0612] The menu information received by the device is displayed within the application so that the user can check it.

[0613] Step 10:

[0614] The user can review the displayed menu and then use the sharing function to upload it to a shared folder or in-app bulletin board that can be accessed by the whole family.

[0615] Step 11:

[0616] The server generates a list of ingredients based on the generated menu. The list contains all the ingredients needed for the dish.

[0617] Step 12:

[0618] The server retrieves the user's home inventory information from a database and compares it with the generated ingredient list.

[0619] Step 13:

[0620] The server generates a list of ingredients that are missing based on the matching results, excluding ingredients that are already in the home.

[0621] Step 14:

[0622] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0623] Step 15:

[0624] The terminal displays the received notification to the user, allowing the user to check the ingredients that are missing.

[0625] Step 16:

[0626] The user can check the list of ingredients they are short of and use it as a shopping list. For example, the user can create a list in the app or on paper and use it to purchase ingredients.

[0627] Through this series of steps, users can easily obtain a menu that best suits their physical condition and emotions, and can also efficiently manage and purchase the necessary ingredients.

[0628] Example 2

[0629] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0630] Conventional menu generation systems only suggest menus based on the user's physical condition data, so they can only suggest uniform menus without considering the user's emotional state. Also, because they create ingredient lists without considering household inventory information, ingredients are likely to be wasted. This has led to issues such as low user satisfaction and a high likelihood of food waste.

[0631] 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.

[0632] In this invention, the server includes means for inputting a user's physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for generating a menu using a generative AI model, means for displaying the generated menu information, means for sharing the displayed menu information, means for creating a necessary ingredient list based on the generated menu, means for comparing the created ingredient list with home inventory information, and means for notifying the user of the created ingredient list. This enables personalized menu suggestions that take the user's physical condition and emotions into consideration, and realizes efficient ingredient management that takes home inventory information into account.

[0633] "User's physical condition data" is information that indicates the user's health condition, such as the user's sense of fatigue, vitamin deficiency, allergy information, and the like.

[0634] "Emotion data" is information that indicates the user's emotional state, such as stress, elation, or relief.

[0635] "Analysis" refers to a process of comprehensively analyzing the user's health condition and emotional state based on the input physical condition data and emotional data.

[0636] "Menu generation" is a process that suggests optimal food and dish combinations to the user based on analyzed physical condition data and emotional data.

[0637] A "generative AI model" is an artificial intelligence model that automatically generates text and information to create menus based on specific prompts.

[0638] "Menu information" is information about the combination of food and dishes that has been generated.

[0639] "Display" refers to visualizing and presenting data or information on a user interface.

[0640] "Sharing" means allowing multiple users to access, view, and use information.

[0641] The "ingredient list" is a list of foods needed to create a menu.

[0642] "Home inventory information" is information about food already in the home.

[0643] A "notification" is a message or other means sent to inform a user of information.

[0644] The present invention is a system that collects data on a user's physical condition and emotions, automatically generates an optimal menu based on that data, shares the menu with family members, and notifies them of a list of necessary ingredients.

[0645] First, the user inputs their own physical condition data using a dedicated application. This data includes information on health conditions such as fatigue, vitamin deficiencies, and allergies. The user then uses the camera to activate an emotion engine that automatically recognizes their own emotional state. The emotion engine can be general facial expression recognition software (e.g., an emotion recognition API) that analyzes facial expressions.

[0646] The device formats and transmits the physical and emotional data obtained from the user to the server using an HTTP POST request, ensuring security using the HTTPS protocol.

[0647] The server stores the received data in a database (for example, a MySQL database) and performs the necessary analysis. This analysis uses data analysis libraries such as Python and Pandas. Specifically, it compares trends in the user's physical condition data and emotional data with past data to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[0648] The server then uses a generative AI model (e.g., a generative AI) to generate a menu based on the prompt, which includes information about the user's current physical condition and emotions, and the generative AI model uses this information to suggest the optimal menu.

[0649] For example, you can generate a plan like this:

[0650] If a user inputs "I've been feeling tired and stressed lately," the server will generate a menu rich in vitamin C and effective in reducing stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This information is sent to the device and can be viewed by the user and their family.

[0651] The server then creates a list of ingredients based on the user's home inventory and the generated menu. The home inventory information is compared with the information stored in the database. The list is adjusted to include only the ingredients that are missing.

[0652] Finally, the server generates this ingredient list as a notification message and sends it to the terminal. The terminal receives the notification and displays it on its user interface. The user can check the displayed ingredient list and use it as a shopping list.

[0653] By integrating this series of processes, it is possible to realize a system that proposes personalized menus tailored to the user's physical condition and emotions, streamlines meal preparation at home, and supports comprehensive health management.

[0654] Example prompt sentence:

[0655] If a user inputs that they have recently been feeling tired and stressed, the system will suggest a menu rich in vitamin C and effective in relieving stress based on the analysis results.

[0656] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0657] Step 1:

[0658] Users use a dedicated application to input their physical condition data. Specifically, they manually enter information such as fatigue, vitamin deficiencies, and allergies into a form on the application screen. In addition, to input or automatically recognize their current emotional state, the camera is used to activate the emotion engine, and emotion data is obtained through facial expression recognition software. The input at this time is information about the user's health and emotional state.

[0659] Step 2:

[0660] The device formats the physical condition and emotion data received from the user and sends it to the server. Specifically, it formats the physical condition and emotion data into a format such as JSON and sends it to the server using an HTTP POST request. This formatted data also includes additional information such as the user ID and timestamp. The input is the formatted physical condition and emotion data obtained from the user, and the output is the data to be sent to the server.

[0661] Step 3:

[0662] The server receives the data sent from the device and stores it in a database. Specifically, it saves the data in a MySQL database. The input at this stage is the physical condition data and emotion data sent from the device, and the output is the data stored in the database. Transactions are used when storing data to ensure data integrity.

[0663] Step 4:

[0664] The server analyzes the stored data. Using Python data analysis libraries (e.g., Pandas, Scikit-learn), it compares trends in the stored physical condition and emotional data with past data to comprehensively analyze the user's current health and emotional state. This analysis identifies nutrients that are lacking, foods to avoid, and ingredients that boost mood. The input is the physical condition and emotional data stored in the database, and the output is the analysis results.

[0665] Step 5:

[0666] The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-4). This prompt includes information about the user's physical condition and emotions. Specifically, if the user inputs that they have recently been feeling tired and stressed, the following prompt will be sent to the generative AI model: "Please suggest a menu based on the analysis results that is rich in vitamin C and has a stress-relieving effect." The input is the analysis results, and the output is the prompt.

[0667] Step 6:

[0668] The server generates a menu using a generative AI model. When a prompt is sent to the generative AI model, the model returns an optimal menu that is nutritionally balanced and takes into account the user's emotional state. The input is the prompt, and the output is the generated menu.

[0669] Step 7:

[0670] The terminal receives the menu information sent from the server and displays it on the user interface. Specifically, it displays the menu details, ingredient list, cooking instructions, etc. in a format that is easy for the user to understand. The input is the menu information sent from the server, and the output is the information displayed on the user interface.

[0671] Step 8:

[0672] Users can check the displayed menu information and share it through a shared folder that can be accessed by the whole family or through the message board function within the app. This sharing makes it easier for the whole family to plan meals together. The input is the displayed menu information, and the output is the information to be shared.

[0673] Step 9:

[0674] The server creates a list of ingredients based on the generated menu. First, it checks the home inventory information to remove ingredients already in the home from the list, and then lists only ingredients that are in short supply. The input is the menu and home inventory information, and the output is the final ingredient list.

[0675] Step 10:

[0676] The server generates a notification message based on the created ingredient list and sends it to the terminal. The notification message is sent to the user using the application's notification function. The input is the ingredient list, and the output is the notification message that is displayed to the user.

[0677] Step 11:

[0678] The terminal displays the notification message received from the server on the user interface, and the user can check the displayed ingredient list and use it as a shopping list. The input is the notification message, and the output is the display information on the user interface.

[0679] Through the above processing steps, this system provides personalized menus tailored to the user's physical condition and emotions, streamlines meal planning at home, and realizes a system that supports comprehensive health management.

[0680] (Application example 2)

[0681] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0682] Conventional menu generation systems based on physical condition do not take into account the user's emotional state and do not adequately integrate with household inventory information, making it difficult to streamline the user's overall health management and meal preparation. Furthermore, the system lacks the functionality to instantly order delivery meals based on the generated menu. This means that users have to spend a lot of time planning their own menus, purchasing ingredients, and cooking them.

[0683] 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.

[0684] In this invention, the server includes means for inputting physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for displaying the generated menu information, means for generating an orderable menu based on the generated menu, means for notifying the user of the generated menu, means for confirming a delivery order for the menu selected by the user, and means for sending a delivery notification. This makes it possible to easily generate and display an optimal menu based on the user's physical condition and emotional state, and to directly order delivery, thereby significantly improving the efficiency of the user's health management and meal preparation.

[0685] "Physical condition data" is information relating to the user's health condition, including fatigue, vitamin deficiency, allergy information, and the like.

[0686] "Emotion data" is information about the user's psychological state, including stress, elation, relief, and the like.

[0687] A "menu" is a meal suggestion generated based on the user's physical condition data and emotional data, and takes into consideration nutritional balance and emotional care.

[0688] A "menu" is a list of foods that are provided to the user based on the generated recipe, from which the user can select and order.

[0689] An "orderable menu" is a list of foods that a user can order through a delivery service based on the generated menu.

[0690] "Delivery notification" is information that notifies the user of the delivery status of food after a delivery order has been confirmed.

[0691] "Home inventory information" is information about ingredients currently held in the user's home, and is used to create and compare ingredient lists.

[0692] This invention is a system that generates an optimal menu based on a user's physical condition data and emotional data, generates an orderable menu based on the optimal menu, and places a delivery order. A specific embodiment of this system will be described.

[0693] Entering User Data

[0694] Using a dedicated smartphone app, users input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). An emotion engine is also used to automatically recognize the user's current emotional state (stress, elation, relief, etc.). The physical condition data and emotional data are formatted and sent to the server.

[0695] Data analysis

[0696] The server stores the received physical condition and emotional data in a database and analyzes it. Specifically, the server uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's current health and emotional state. This allows the server to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[0697] Plan and menu generation

[0698] The server generates an optimal menu based on the analysis results, and then generates a menu that the user can order for delivery based on that menu. The menu is generated to balance nutritional balance with emotional care. For example, it may include a salad rich in vitamin C if you are feeling tired, or a relaxing herbal tea if you are stressed.

[0699] Menu Notification and Ordering

[0700] The generated menu is displayed on the smartphone app, allowing the user to review and select an item. Once the user selects a menu item, the order is confirmed and the server generates a delivery notification and sends it to the user. The user can then check the delivery status in real time based on this notification.

[0701] Specific examples

[0702] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the smartphone app will send this information to the server. The server will analyze the physical condition data and emotional data and generate a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, herbal tea, etc.). Based on this menu, it will generate a menu that the user can order and notify the smartphone app. Once the user selects a menu and confirms the order, the server will send a delivery notification, allowing them to check the delivery status.

[0703] Prompt Sentence Examples

[0704] "User ID: 1, physical condition data: fatigue, emotional data: stress"

[0705] Generate appropriate menus based on the user's physical condition and emotions.

[0706] This system will significantly improve the efficiency of users' health management and meal preparation, and enable quick responses through delivery services.

[0707] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0708] Step 1:

[0709] Using a dedicated smartphone app, users input their physical condition data (fatigue, vitamin deficiency, allergy information, etc.), and the emotion engine automatically recognizes their current emotional state (stress, elation, relief, etc.) and inputs the data into the app. The input data is formatted in JSON and sent to the server.

[0710] Input: physical condition data, emotional data

[0711] Output: Pretty-printed JSON data

[0712] Step 2:

[0713] The server stores the received physical condition and emotional data in a database. It uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's health and emotional state. This allows it to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[0714] Input: Formatted JSON data

[0715] Output: Analysis results (nutrients you are lacking, foods to avoid, ingredients that boost your mood)

[0716] Step 3:

[0717] The server then generates an optimal menu based on the analysis results. This menu includes nutritionally balanced foods and foods that take emotional care into consideration. The generated menu is designed to be specific and actionable for the user.

[0718] Input: Analysis results

[0719] Output: Optimal menu

[0720] Step 4:

[0721] The server generates a menu that the user can order from based on the generated menu. The generated menu is displayed on the smartphone app. The user can select from the displayed menu.

[0722] Input: Optimal menu

[0723] Output: Orderable menu

[0724] Step 5:

[0725] The user selects from the displayed menu through the smartphone app and confirms the delivery order. The selected menu is sent to the server and recorded in the order database.

[0726] Input: User's selection from an orderable menu

[0727] Output: Confirmed delivery order

[0728] Step 6:

[0729] The server generates a delivery notification based on the confirmed order details and sends it to the user's smartphone app. The user can receive this delivery notification and check the delivery status in real time.

[0730] Input: Confirmed delivery order

[0731] Output: Delivery notification

[0732] Specific examples

[0733] For example, if a user enters into the app that they have been feeling tired and stressed recently, the smartphone app sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is displayed on the user's smartphone as an optimal menu. The user selects from the displayed menu and confirms the delivery order. If salmon or almonds are in short supply, those ingredients will be delivered based on the delivery notification.

[0734] 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.

[0735] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0736] 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.

[0737] [Third embodiment]

[0738] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0739] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0740] 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).

[0741] 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.

[0742] 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.

[0743] 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).

[0744] 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.

[0745] 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.

[0746] 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.

[0747] 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.

[0748] 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.

[0749] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0750] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0751] Input of user's physical condition data

[0752] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.) The device checks the input data, formats it, and then sends it to the server.

[0753] Analysis of physical condition data

[0754] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0755] Menu generation

[0756] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0757] Display and share menu information

[0758] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0759] Creating a list of ingredients needed

[0760] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0761] Ingredient list notification

[0762] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0763] Specific examples

[0764] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device will send this information to the server. The server will analyze this physical condition data and generate a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, fruit yogurt, etc.). This menu information will be sent to the device and shared so that the user and their family can check it. The server will then compare it with household inventory information, and if salmon or yogurt is low, it will add those ingredients to the list and send a notification to the device. Finally, the user will receive a notification and be able to purchase the necessary ingredients.

[0765] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0766] The processing flow will be explained below.

[0767] Step 1:

[0768] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.).

[0769] Step 2:

[0770] The terminal receives the input physical condition data, formats it, and generates data to be sent to the server.

[0771] Step 3:

[0772] The device sends the prepared data to a server and uploads the health data.

[0773] Step 4:

[0774] The server stores the received physical condition data in a database.

[0775] Step 5:

[0776] The server retrieves the latest health data from the database and begins analysis.

[0777] Step 6:

[0778] The server evaluates the user's health condition based on their physical condition data and analyzes the nutrients they need and foods they should avoid.

[0779] Step 7:

[0780] The server uses the analysis results to generate nutritionally balanced meals, for example, suggesting a meal that includes citrus salad and broccoli for a user who is deficient in vitamin C.

[0781] Step 8:

[0782] The server sends the generated menu to the terminal.

[0783] Step 9:

[0784] The menu information received by the device is displayed within the application so that the user can check it.

[0785] Step 10:

[0786] The user can review the displayed menu and, if desired, upload it to a shared folder or in-app bulletin board that the whole family can access.

[0787] Step 11:

[0788] The server lists all the ingredients needed based on the generated menu.

[0789] Step 12:

[0790] The server compares the user's home inventory information stored in a database with the listed ingredients needed.

[0791] Step 13:

[0792] The server generates a list of missing ingredients based on the matching results.

[0793] Step 14:

[0794] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0795] Step 15:

[0796] The terminal displays the received notification to the user, allowing the user to check the ingredients they need.

[0797] Step 16:

[0798] The user checks the notified list of ingredients and uses it as a shopping list.

[0799] This allows users to easily obtain menus that suit their physical condition and efficiently manage and purchase the ingredients they need.

[0800] Example 1

[0801] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0802] Conventional health management systems lack the support required for users to accurately understand their own health status and take appropriate nutritional supplements and manage their diet. Furthermore, they are unable to efficiently share menu and ingredient information with family members, which leads to duplicate ingredient purchases and makes it difficult to prepare nutritionally balanced meals. Furthermore, there is a demand for a function that creates a list of ingredients needed based on household inventory information and supports waste-free shopping.

[0803] 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.

[0804] In this invention, the server includes means for inputting a user's physical condition data, means for checking and formatting the input physical condition data, means for transmitting the formatted physical condition data to the server, means for storing the received physical condition data in a database, means for analyzing the user's physical condition data and identifying missing nutrients and foods to avoid, means for generating an optimal menu based on the analyzed physical condition data, means for displaying the menu information sent from the server on a terminal, means for sharing the generated menu information with family members via a shared folder or bulletin board function, means for creating a necessary ingredient list based on the generated menu, means for comparing the ingredient list with home inventory information and adding missing ingredients to the final list, means for generating a notification message of the created ingredient list and transmitting it to the terminal, and means for receiving and displaying the notification. This enables the creation of nutritionally balanced menus based on the user's health status, thereby enabling efficient meal preparation and ingredient management at home.

[0805] "Means for inputting user's physical condition data" refers to an interface for the user to input their own health condition, such as an input form, check box, or text box within the application.

[0806] "Means for checking and formatting entered health data" refers to the function by which the system checks data entered by users and converts it into a standard format, such as standardizing date formats and correcting input errors.

[0807] "Means for sending formatted health data to a server" refers to the function of sending formatted data to a server via a network. Generally, communication methods such as the HTTP protocol or WebSocket are used.

[0808] "Means for storing received health data in a database" refers to the function of storing the received data on the server side in an appropriate database, such as an SQL database or NoSQL database.

[0809] "A means of analyzing the user's physical condition data and identifying nutrients that are lacking and foods that should be avoided" refers to a function that uses algorithms and AI models to analyze stored data and identify the nutrients that the user needs and foods that should be avoided.

[0810] "Means for generating optimal menus based on analyzed health data" refers to a function that searches for recipes and nutritional information in a database based on the analysis results and generates menus that are appropriate for the user's health condition.

[0811] "Means for displaying menu information sent from the server on the terminal" refers to the function of displaying menu information generated by the server on the user's terminal (such as a smartphone or tablet).

[0812] "Means for sharing the generated menu information with family members using a shared folder or bulletin board function" refers to the function for sharing the generated menu information through a shared folder or bulletin board function that can be accessed by all family members.

[0813] "Means for creating a list of ingredients required based on the generated menu" refers to a function that compiles a list of ingredients required for cooking based on the generated menu.

[0814] "Means for checking the ingredient list against home inventory information and adding missing ingredients to the final list" refers to a function that compares the generated ingredient list with home inventory information registered in advance by the user and adds only missing ingredients to the final list.

[0815] "Means for generating a notification message for the created ingredient list and sending it to the terminal" refers to a function for generating a notification message based on the required ingredient list and sending it to the user's terminal.

[0816] "Means for receiving and displaying notifications" refers to a function that displays the notification message received by the user's terminal so that the user can check the content.

[0817] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[0818] Hardware and Software Configuration

[0819] This system consists of a terminal that receives user input, a server that analyzes data and generates menus, and a database that stores and shares data. Specifically, the system uses the following hardware and software:

[0820] Device: A mobile device such as a smartphone or tablet. The application runs on the iOS or Android platform.

[0821] Server: A high-performance computing device used to run AI models and analyze data. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch.

[0822] Database: An SQL database (MySQL, PostgreSQL, etc.) or a NoSQL database (MongoDB, etc.) that stores user health data and home inventory information.

[0823] Program processing

[0824] 1. Enter user's physical condition data:

[0825] Users use a dedicated application to input their own physical condition data (fatigue, vitamin deficiencies, allergy information, etc.). The input form has text boxes and check boxes, and is designed to make data entry easy. For example, you might enter, "I feel very tired today."

[0826] 2. Sending health data:

[0827] The device checks the entered data and formats it as needed, for example to standardize date formats or correct typos. The data is then converted to JSON format and sent to the server.

[0828] 3. Analysis of physical condition data:

[0829] The server stores the received health data in a database. A table is created for each user in the database, allowing comparison with past data. The data is then analyzed using an AI model (for example, a model using TensorFlow or PyTorch) to identify nutrient deficiencies and foods that should be avoided.

[0830] 4. Menu generation:

[0831] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects recipes that use ingredients that are high in vitamin C.

[0832] 5. View and share menu information:

[0833] The device receives the menu information sent from the server and displays it on the user interface. The generated menu can also be shared by the whole family using a shared folder or the app's bulletin board function.

[0834] 6. Make a list of ingredients needed:

[0835] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0836] 7. Ingredient List Notification:

[0837] The server generates a notification message based on the final ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can then check the displayed ingredient list and use it as a shopping list.

[0838] Specific examples

[0839] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device converts this information into JSON format and sends it to the server. The server stores the physical condition data in a database and analyzes it. If the analysis results show that the user is lacking in vitamin C, the server will create a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, and fruit yogurt). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or yogurt are low, it adds those ingredients to the list and sends a notification to the device. The user can receive the notification and purchase the necessary ingredients to prepare a nutritionally balanced meal.

[0840] Prompt Sentence Examples

[0841] "For a user who has recently been feeling tired, please suggest a meal plan that contains the appropriate vitamins. Please also note that this user is deficient in vitamin C. Please generate the meal plan and a list of the ingredients required for it."

[0842] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[0843] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0844] Step 1:

[0845] The user uses a dedicated application to input data about their physical condition. Information such as fatigue, vitamin deficiencies, and allergies is entered into a form in the application using text boxes and check boxes. The input data (e.g., "I've been feeling tired recently") is sent to the application.

[0846] Step 2:

[0847] The terminal receives the data entered by the user, checks the input data, and formats it. For example, it standardizes the date format and cleans the text data. The formatted data (e.g., {"fatigue": "high", "vitamin deficiency": "vitamin C"}) is generated.

[0848] Step 3:

[0849] The terminal converts the formatted data into JSON format and sends it to the server. This conversion process prepares the data in a format suitable for network communication. After transmission, the server receives the JSON data.

[0850] Step 4:

[0851] The server stores the received health data in a database. Specifically, it creates a table for each user in an SQL or NoSQL database and stores the data. In this step, the health data is persistently stored and can be analyzed.

[0852] Step 5:

[0853] The server analyzes the received health data using an AI model. Specifically, it uses TensorFlow and PyTorch to run a model that evaluates the user's health condition. The model analyzes the input data (e.g., "Vitamin C deficiency") and identifies nutrients that are lacking and foods that should be avoided. An analysis result (e.g., "Vitamin C deficiency") is generated.

[0854] Step 6:

[0855] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects a recipe that uses ingredients that are high in vitamin C. The generated menu (e.g., "Citrus salad, grilled broccoli and salmon") is then generated.

[0856] Step 7:

[0857] The server sends the generated menu information to the terminal. The sent data is displayed on the user interface. For example, "Citrus salad, broccoli and grilled salmon" is displayed on the application screen.

[0858] Step 8:

[0859] The device displays the generated menu information, and the user can review it. The information can also be shared using a shared folder accessible to the whole family or the app's message board function. Clicking the share button uploads the information to the shared folder.

[0860] Step 9:

[0861] The server creates a list of ingredients based on the generated menu. This list is compared with the home inventory information registered in advance by the user. Ingredients already in the home are removed from the list, and only ingredients that are missing are added to the final list. A final ingredient list (e.g., "salmon, yogurt") is generated.

[0862] Step 10:

[0863] The server generates a notification message for the created ingredient list and sends it to the device. The notification message includes a list of the ingredients needed. For example, "You are running low on salmon and yogurt. They have been added to your shopping list."

[0864] Step 11:

[0865] The device receives the notification sent from the server and displays it on the user interface. The user can check the notification and use the required ingredients as a shopping list, which is displayed in the shopping list section of the application.

[0866] (Application example 1)

[0867] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0868] While conventional menu generation systems provide healthy menus based on the user's physical condition, the process of purchasing ingredients is time-consuming, resulting in a lack of user convenience. Furthermore, it is difficult to manage food inventory at home, leading to a high likelihood of unnecessary purchases. To solve these problems, a system is needed that integrates menu generation based on physical condition data with efficient food purchasing and management.

[0869] 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.

[0870] In this invention, the server includes means for inputting physical condition data, means for analyzing the input physical condition data, means for generating a menu based on the analyzed physical condition data, means for displaying the generated menu information, means for creating a required ingredient list based on the generated menu, means for notifying the user of the created ingredient list, and means for transmitting the required ingredient list to the online store via a communications network and performing a bulk purchase procedure. This allows the user to quickly obtain an optimal menu based on their physical condition and efficiently purchase the required ingredients.

[0871] "Physical condition data" is information indicating the user's health condition, such as fatigue, vitamin deficiency, and allergy information.

[0872] The "analyzing means" is a process or device that stores the user's physical condition data in a database and analyzes the data for the purpose of assessing the user's health condition.

[0873] The "means for generating a menu" is a process or system that creates an optimal meal menu based on analyzed physical condition data, taking into consideration the user's nutritional status.

[0874] The "displaying means" refers to a display device or software for visually presenting the generated menu information to the user.

[0875] The "means for creating an ingredient list" is a process or system that identifies the ingredients needed based on the generated menu and compiles them in list form.

[0876] The "notification means" is a message sending device or software for notifying the user of the created ingredient list.

[0877] "Means for sending to the online store via a communications network and completing the bulk purchase procedure" refers to a process or system that sends the created ingredient list to the online store via a network such as the Internet, allowing the user to purchase the ingredients they need in bulk.

[0878] The "means for sharing menu information among family members" is a software function or a shared folder that allows all family members to access the generated menu information.

[0879] "Home inventory information" is information about ingredients currently held in the user's home, and is used to calculate the ingredients that are in short supply.

[0880] The "means for checking against inventory information" is a process or system that compares the home inventory information with the generated ingredient list and excludes ingredients that are already present.

[0881] The present invention is a system that automatically creates healthy menus based on the user's physical condition data, shares that information with family members, notifies them of a list of necessary ingredients, and then transmits the list to an online store via a communication network for bulk purchasing. A specific embodiment of this system will be described below.

[0882] Input of user's physical condition data

[0883] Users use a dedicated smartphone application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). The device checks the input data, formats it, and then sends it to the server.

[0884] Analysis of physical condition data

[0885] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[0886] Menu generation

[0887] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[0888] Display and share menu information

[0889] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0890] Creating and notifying a list of ingredients needed

[0891] The server creates a list of ingredients needed based on the generated menu. This list is compared with the home inventory information registered in advance by the user, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list. The server then creates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the required ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0892] Send your ingredient list to online stores and buy in bulk

[0893] The server transmits the final ingredient list to the online store via a communication network, allowing the user to order the ingredients they need from the online store in a single purchase.

[0894] Specific examples

[0895] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device sends this information to the server. The server analyzes this physical condition data and generates a menu rich in vitamin C (e.g., orange juice, granola, grilled broccoli and salmon, kiwi fruit salad, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or broccoli are low, it adds those ingredients to the list and sends a notification to the device. Finally, the server sends the ingredient list to an online store, allowing the user to purchase the necessary ingredients in bulk.

[0896] Example prompt sentence:

[0897] The user's health data has been entered. They are deficient in Vitamin C. Based on this data, generate a nutritionally balanced meal plan and create a list of ingredients needed for that plan.

[0898] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0899] Step 1:

[0900] The user inputs their physical condition data using a dedicated smartphone application.

[0901] Input: Physical condition data such as fatigue, vitamin deficiency, and allergy information.

[0902] Specific operation: The user enters their status into each item in the app and presses the send button. The device collects this data, converts it into an appropriate format, and sends it to the server.

[0903] Step 2:

[0904] The server stores the received physical condition data in a database and performs data analysis.

[0905] Input: The user's health data.

[0906] Output: User's health assessment results and a list of nutrients they are lacking and foods they should avoid.

[0907] Specific operation: The server stores the received data in a database and uses the AI ​​model to analyze the data, sending a prompt to the generating AI model such as, "The user's physical condition data has been entered. Please evaluate the user's health condition based on this data."

[0908] Step 3:

[0909] The server automatically generates a menu based on the analysis results.

[0910] Input: Health assessment results, list of nutrients you're lacking and foods to avoid.

[0911] Output: A nutritionally balanced menu.

[0912] Specific operation: Based on the analysis results, the server uses the generative AI model to generate a menu by sending a prompt such as, "Please generate a nutritionally balanced menu that suits the user's health condition." The generated menu is then stored in a database.

[0913] Step 4:

[0914] The server sends the generated menu information to the terminal, which displays it to the user.

[0915] Enter: Menu.

[0916] Output: Menu information displayed to the user.

[0917] Specific operation: The server sends the generated menu information to the device, and the application visually displays it to the user, who can then review it and share it with their family within the app.

[0918] Step 5:

[0919] The server creates a list of ingredients needed based on the generated menu.

[0920] Input: Menu, household inventory information.

[0921] Output: A list of ingredients needed.

[0922] Specific operation: The server compares the information with a pre-registered household inventory database, excludes ingredients already in the home, and adds only ingredients that are in short supply to the list.

[0923] Step 6:

[0924] The server sends the created ingredient list to the terminal, which then displays it to the user.

[0925] Input: List of ingredients needed.

[0926] Output: A list of ingredients that are in short supply and notified to the user.

[0927] Specific operation: The server generates a final ingredient list and sends it to the device as a notification message. The device visually displays the missing ingredients to the user.

[0928] Step 7:

[0929] The server transmits the list of ingredients to the online store via a communication network, and a bulk purchase procedure is carried out.

[0930] Input: Final ingredient list.

[0931] Output: Purchase completion information in the online store.

[0932] Specific operation: The server sends the list of ingredients to the online store's purchasing API, allowing the user to complete the purchase all at once. The user confirms the purchase within the app.

[0933] The above are the specific processing steps.

[0934] 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.

[0935] The present invention is a system that automatically generates healthy menus using not only a user's physical condition data but also their emotional data, shares the menus with family members, and notifies them of necessary ingredients. Specific embodiments of this system will be described below.

[0936] Input of user's physical condition data and emotional data

[0937] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes their current emotional state (e.g., stress, elation, relief, etc.). The device checks the physical condition data and emotional data, formats it, and generates data to be sent to the server.

[0938] Analysis of physical condition data and emotional data

[0939] The server stores the received physical condition and emotional data in a database and analyzes the user's health and emotional state. Specifically, it comprehensively analyzes the user's current physical condition, nutritional status, and emotional state to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[0940] Menu generation

[0941] The server generates an optimal menu based on the analyzed physical condition data and emotional data. The generated menu is not only nutritionally balanced but also takes into consideration the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0942] Display and share menu information

[0943] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[0944] Creating a list of ingredients needed

[0945] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[0946] Ingredient list notification

[0947] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[0948] Specific examples

[0949] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the device sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or almonds are low, it adds those ingredients to the list and sends a notification to the device. Finally, the user receives a notification and can purchase the necessary ingredients.

[0950] In this way, the present invention provides a menu that matches the user's physical condition and emotions, streamlines meal preparation at home, and realizes a system that supports comprehensive health management.

[0951] The processing flow will be explained below.

[0952] Step 1:

[0953] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes the user's current emotional state (e.g., stress, elation, relief, etc.).

[0954] Step 2:

[0955] The terminal receives the input physical condition data and emotion data and formats the data.

[0956] Step 3:

[0957] The terminal sends the formatted data to the server.

[0958] Step 4:

[0959] The server stores the received physical condition data and emotion data in a database.

[0960] Step 5:

[0961] The server retrieves the latest physical condition and emotional data from the database and begins analysis.

[0962] Step 6:

[0963] The server evaluates the user's health and emotional state based on physical condition data and emotional data, and analyzes the nutrients needed, foods to avoid, and ingredients that will boost your mood.

[0964] Step 7:

[0965] The server uses the analysis results to generate a menu that is nutritionally balanced and takes into account the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0966] Step 8:

[0967] The server sends the generated menu to the terminal.

[0968] Step 9:

[0969] The menu information received by the device is displayed within the application so that the user can check it.

[0970] Step 10:

[0971] The user can review the displayed menu and then use the sharing function to upload it to a shared folder or in-app bulletin board that can be accessed by the whole family.

[0972] Step 11:

[0973] The server generates a list of ingredients based on the generated menu. The list contains all the ingredients needed for the dish.

[0974] Step 12:

[0975] The server retrieves the user's home inventory information from a database and compares it with the generated ingredient list.

[0976] Step 13:

[0977] The server generates a list of ingredients that are missing based on the matching results, excluding ingredients that are already in the home.

[0978] Step 14:

[0979] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[0980] Step 15:

[0981] The terminal displays the received notification to the user, allowing the user to check the ingredients that are missing.

[0982] Step 16:

[0983] The user can check the list of ingredients they are short of and use it as a shopping list. For example, the user can create a list in the app or on paper and use it to purchase ingredients.

[0984] Through this series of steps, users can easily obtain a menu that best suits their physical condition and emotions, and can also efficiently manage and purchase the necessary ingredients.

[0985] Example 2

[0986] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0987] Conventional menu generation systems only suggest menus based on the user's physical condition data, so they can only suggest uniform menus without considering the user's emotional state. Also, because they create ingredient lists without considering household inventory information, ingredients are likely to be wasted. This has led to issues such as low user satisfaction and a high likelihood of food waste.

[0988] 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.

[0989] In this invention, the server includes means for inputting a user's physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for generating a menu using a generative AI model, means for displaying the generated menu information, means for sharing the displayed menu information, means for creating a necessary ingredient list based on the generated menu, means for comparing the created ingredient list with home inventory information, and means for notifying the user of the created ingredient list. This enables personalized menu suggestions that take the user's physical condition and emotions into consideration, and realizes efficient ingredient management that takes home inventory information into account.

[0990] "User's physical condition data" is information that indicates the user's health condition, such as the user's sense of fatigue, vitamin deficiency, allergy information, and the like.

[0991] "Emotion data" is information that indicates the user's emotional state, such as stress, elation, or relief.

[0992] "Analysis" refers to a process of comprehensively analyzing the user's health condition and emotional state based on the input physical condition data and emotional data.

[0993] "Menu generation" is a process that suggests optimal food and dish combinations to the user based on analyzed physical condition data and emotional data.

[0994] A "generative AI model" is an artificial intelligence model that automatically generates text and information to create menus based on specific prompts.

[0995] "Menu information" is information about the combination of food and dishes that has been generated.

[0996] "Display" refers to visualizing and presenting data or information on a user interface.

[0997] "Sharing" means allowing multiple users to access, view, and use information.

[0998] The "ingredient list" is a list of foods needed to create a menu.

[0999] "Home inventory information" is information about food already in the home.

[1000] A "notification" is a message or other means sent to inform a user of information.

[1001] The present invention is a system that collects data on a user's physical condition and emotions, automatically generates an optimal menu based on that data, shares the menu with family members, and notifies them of a list of necessary ingredients.

[1002] First, the user inputs their own physical condition data using a dedicated application. This data includes information on health conditions such as fatigue, vitamin deficiencies, and allergies. The user then uses the camera to activate an emotion engine that automatically recognizes their own emotional state. The emotion engine can be general facial expression recognition software (e.g., an emotion recognition API) that analyzes facial expressions.

[1003] The device formats and transmits the physical and emotional data obtained from the user to the server using an HTTP POST request, ensuring security using the HTTPS protocol.

[1004] The server stores the received data in a database (for example, a MySQL database) and performs the necessary analysis. This analysis uses data analysis libraries such as Python and Pandas. Specifically, it compares trends in the user's physical condition data and emotional data with past data to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[1005] The server then uses a generative AI model (e.g., a generative AI) to generate a menu based on the prompt, which includes information about the user's current physical condition and emotions, and the generative AI model uses this information to suggest the optimal menu.

[1006] For example, you can generate a plan like this:

[1007] If a user inputs "I've been feeling tired and stressed lately," the server will generate a menu rich in vitamin C and effective in reducing stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This information is sent to the device and can be viewed by the user and their family.

[1008] The server then creates a list of ingredients based on the user's home inventory and the generated menu. The home inventory information is compared with the information stored in the database. The list is adjusted to include only the ingredients that are missing.

[1009] Finally, the server generates this ingredient list as a notification message and sends it to the terminal. The terminal receives the notification and displays it on its user interface. The user can check the displayed ingredient list and use it as a shopping list.

[1010] By integrating this series of processes, it is possible to realize a system that proposes personalized menus tailored to the user's physical condition and emotions, streamlines meal preparation at home, and supports comprehensive health management.

[1011] Example prompt sentence:

[1012] If a user inputs that they have recently been feeling tired and stressed, the system will suggest a menu rich in vitamin C and effective in relieving stress based on the analysis results.

[1013] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1014] Step 1:

[1015] Users use a dedicated application to input their physical condition data. Specifically, they manually enter information such as fatigue, vitamin deficiencies, and allergies into a form on the application screen. In addition, to input or automatically recognize their current emotional state, the camera is used to activate the emotion engine, and emotion data is obtained through facial expression recognition software. The input at this time is information about the user's health and emotional state.

[1016] Step 2:

[1017] The device formats the physical condition and emotion data received from the user and sends it to the server. Specifically, it formats the physical condition and emotion data into a format such as JSON and sends it to the server using an HTTP POST request. This formatted data also includes additional information such as the user ID and timestamp. The input is the formatted physical condition and emotion data obtained from the user, and the output is the data to be sent to the server.

[1018] Step 3:

[1019] The server receives the data sent from the device and stores it in a database. Specifically, it saves the data in a MySQL database. The input at this stage is the physical condition data and emotion data sent from the device, and the output is the data stored in the database. Transactions are used when storing data to ensure data integrity.

[1020] Step 4:

[1021] The server analyzes the stored data. Using Python data analysis libraries (e.g., Pandas, Scikit-learn), it compares trends in the stored physical condition and emotional data with past data to comprehensively analyze the user's current health and emotional state. This analysis identifies nutrients that are lacking, foods to avoid, and ingredients that boost mood. The input is the physical condition and emotional data stored in the database, and the output is the analysis results.

[1022] Step 5:

[1023] The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-4). This prompt includes information about the user's physical condition and emotions. Specifically, if the user inputs that they have recently been feeling tired and stressed, the following prompt will be sent to the generative AI model: "Please suggest a menu based on the analysis results that is rich in vitamin C and has a stress-relieving effect." The input is the analysis results, and the output is the prompt.

[1024] Step 6:

[1025] The server generates a menu using a generative AI model. When a prompt is sent to the generative AI model, the model returns an optimal menu that is nutritionally balanced and takes into account the user's emotional state. The input is the prompt, and the output is the generated menu.

[1026] Step 7:

[1027] The terminal receives the menu information sent from the server and displays it on the user interface. Specifically, it displays the menu details, ingredient list, cooking instructions, etc. in a format that is easy for the user to understand. The input is the menu information sent from the server, and the output is the information displayed on the user interface.

[1028] Step 8:

[1029] Users can check the displayed menu information and share it through a shared folder that can be accessed by the whole family or through the message board function within the app. This sharing makes it easier for the whole family to plan meals together. The input is the displayed menu information, and the output is the information to be shared.

[1030] Step 9:

[1031] The server creates a list of ingredients based on the generated menu. First, it checks the home inventory information to remove ingredients already in the home from the list, and then lists only ingredients that are in short supply. The input is the menu and home inventory information, and the output is the final ingredient list.

[1032] Step 10:

[1033] The server generates a notification message based on the created ingredient list and sends it to the terminal. The notification message is sent to the user using the application's notification function. The input is the ingredient list, and the output is the notification message that is displayed to the user.

[1034] Step 11:

[1035] The terminal displays the notification message received from the server on the user interface, and the user can check the displayed ingredient list and use it as a shopping list. The input is the notification message, and the output is the display information on the user interface.

[1036] Through the above processing steps, this system provides personalized menus tailored to the user's physical condition and emotions, streamlines meal planning at home, and realizes a system that supports comprehensive health management.

[1037] (Application example 2)

[1038] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1039] Conventional menu generation systems based on physical condition do not take into account the user's emotional state and do not adequately integrate with household inventory information, making it difficult to streamline the user's overall health management and meal preparation. Furthermore, the system lacks the functionality to instantly order delivery meals based on the generated menu. This means that users have to spend a lot of time planning their own menus, purchasing ingredients, and cooking them.

[1040] 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.

[1041] In this invention, the server includes means for inputting physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for displaying the generated menu information, means for generating an orderable menu based on the generated menu, means for notifying the user of the generated menu, means for confirming a delivery order for the menu selected by the user, and means for sending a delivery notification. This makes it possible to easily generate and display an optimal menu based on the user's physical condition and emotional state, and to directly order delivery, thereby significantly improving the efficiency of the user's health management and meal preparation.

[1042] "Physical condition data" is information relating to the user's health condition, including fatigue, vitamin deficiency, allergy information, and the like.

[1043] "Emotion data" is information about the user's psychological state, including stress, elation, relief, and the like.

[1044] A "menu" is a meal suggestion generated based on the user's physical condition data and emotional data, and takes into consideration nutritional balance and emotional care.

[1045] A "menu" is a list of foods that are provided to the user based on the generated recipe, from which the user can select and order.

[1046] An "orderable menu" is a list of foods that a user can order through a delivery service based on the generated menu.

[1047] "Delivery notification" is information that notifies the user of the delivery status of food after a delivery order has been confirmed.

[1048] "Home inventory information" is information about ingredients currently held in the user's home, and is used to create and compare ingredient lists.

[1049] This invention is a system that generates an optimal menu based on a user's physical condition data and emotional data, generates an orderable menu based on the optimal menu, and places a delivery order. A specific embodiment of this system will be described.

[1050] Entering User Data

[1051] Using a dedicated smartphone app, users input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). An emotion engine is also used to automatically recognize the user's current emotional state (stress, elation, relief, etc.). The physical condition data and emotional data are formatted and sent to the server.

[1052] Data analysis

[1053] The server stores the received physical condition and emotional data in a database and analyzes it. Specifically, the server uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's current health and emotional state. This allows the server to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[1054] Plan and menu generation

[1055] The server generates an optimal menu based on the analysis results, and then generates a menu that the user can order for delivery based on that menu. The menu is generated to balance nutritional balance with emotional care. For example, it may include a salad rich in vitamin C if you are feeling tired, or a relaxing herbal tea if you are stressed.

[1056] Menu Notification and Ordering

[1057] The generated menu is displayed on the smartphone app, allowing the user to review and select an item. Once the user selects a menu item, the order is confirmed and the server generates a delivery notification and sends it to the user. The user can then check the delivery status in real time based on this notification.

[1058] Specific examples

[1059] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the smartphone app will send this information to the server. The server will analyze the physical condition data and emotional data and generate a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, herbal tea, etc.). Based on this menu, it will generate a menu that the user can order and notify the smartphone app. Once the user selects a menu and confirms the order, the server will send a delivery notification, allowing them to check the delivery status.

[1060] Prompt Sentence Examples

[1061] "User ID: 1, physical condition data: fatigue, emotional data: stress"

[1062] Generate appropriate menus based on the user's physical condition and emotions.

[1063] This system will significantly improve the efficiency of users' health management and meal preparation, and enable quick responses through delivery services.

[1064] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1065] Step 1:

[1066] Using a dedicated smartphone app, users input their physical condition data (fatigue, vitamin deficiency, allergy information, etc.), and the emotion engine automatically recognizes their current emotional state (stress, elation, relief, etc.) and inputs the data into the app. The input data is formatted in JSON and sent to the server.

[1067] Input: physical condition data, emotional data

[1068] Output: Pretty-printed JSON data

[1069] Step 2:

[1070] The server stores the received physical condition and emotional data in a database. It uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's health and emotional state. This allows it to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[1071] Input: Formatted JSON data

[1072] Output: Analysis results (nutrients you are lacking, foods to avoid, ingredients that boost your mood)

[1073] Step 3:

[1074] The server then generates an optimal menu based on the analysis results. This menu includes nutritionally balanced foods and foods that take emotional care into consideration. The generated menu is designed to be specific and actionable for the user.

[1075] Input: Analysis results

[1076] Output: Optimal menu

[1077] Step 4:

[1078] The server generates a menu that the user can order from based on the generated menu. The generated menu is displayed on the smartphone app. The user can select from the displayed menu.

[1079] Input: Optimal menu

[1080] Output: Orderable menu

[1081] Step 5:

[1082] The user selects from the displayed menu through the smartphone app and confirms the delivery order. The selected menu is sent to the server and recorded in the order database.

[1083] Input: User's selection from an orderable menu

[1084] Output: Confirmed delivery order

[1085] Step 6:

[1086] The server generates a delivery notification based on the confirmed order details and sends it to the user's smartphone app. The user can receive this delivery notification and check the delivery status in real time.

[1087] Input: Confirmed delivery order

[1088] Output: Delivery notification

[1089] Specific examples

[1090] For example, if a user enters into the app that they have been feeling tired and stressed recently, the smartphone app sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is displayed on the user's smartphone as an optimal menu. The user selects from the displayed menu and confirms the delivery order. If salmon or almonds are in short supply, those ingredients will be delivered based on the delivery notification.

[1091] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1092] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1093] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1094] [Fourth embodiment]

[1095] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1096] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1097] 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).

[1098] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1099] 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.

[1100] 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).

[1101] 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.

[1102] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1103] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1104] 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.

[1105] 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.

[1106] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1107] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1108] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[1109] Input of user's physical condition data

[1110] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.) The device checks the input data, formats it, and then sends it to the server.

[1111] Analysis of physical condition data

[1112] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[1113] Menu generation

[1114] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[1115] Display and share menu information

[1116] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[1117] Creating a list of ingredients needed

[1118] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[1119] Ingredient list notification

[1120] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[1121] Specific examples

[1122] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device will send this information to the server. The server will analyze this physical condition data and generate a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, fruit yogurt, etc.). This menu information will be sent to the device and shared so that the user and their family can check it. The server will then compare it with household inventory information, and if salmon or yogurt is low, it will add those ingredients to the list and send a notification to the device. Finally, the user will receive a notification and be able to purchase the necessary ingredients.

[1123] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[1124] The processing flow will be explained below.

[1125] Step 1:

[1126] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.).

[1127] Step 2:

[1128] The terminal receives the input physical condition data, formats it, and generates data to be sent to the server.

[1129] Step 3:

[1130] The device sends the prepared data to a server and uploads the health data.

[1131] Step 4:

[1132] The server stores the received physical condition data in a database.

[1133] Step 5:

[1134] The server retrieves the latest health data from the database and begins analysis.

[1135] Step 6:

[1136] The server evaluates the user's health condition based on their physical condition data and analyzes the nutrients they need and foods they should avoid.

[1137] Step 7:

[1138] The server uses the analysis results to generate nutritionally balanced meals, for example, suggesting a meal that includes citrus salad and broccoli for a user who is deficient in vitamin C.

[1139] Step 8:

[1140] The server sends the generated menu to the terminal.

[1141] Step 9:

[1142] The menu information received by the device is displayed within the application so that the user can check it.

[1143] Step 10:

[1144] The user can review the displayed menu and, if desired, upload it to a shared folder or in-app bulletin board that the whole family can access.

[1145] Step 11:

[1146] The server lists all the ingredients needed based on the generated menu.

[1147] Step 12:

[1148] The server compares the user's home inventory information stored in a database with the listed ingredients needed.

[1149] Step 13:

[1150] The server generates a list of missing ingredients based on the matching results.

[1151] Step 14:

[1152] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[1153] Step 15:

[1154] The terminal displays the received notification to the user, allowing the user to check the ingredients they need.

[1155] Step 16:

[1156] The user checks the notified list of ingredients and uses it as a shopping list.

[1157] This allows users to easily obtain menus that suit their physical condition and efficiently manage and purchase the ingredients they need.

[1158] Example 1

[1159] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1160] Conventional health management systems lack the support required for users to accurately understand their own health status and take appropriate nutritional supplements and manage their diet. Furthermore, they are unable to efficiently share menu and ingredient information with family members, which leads to duplicate ingredient purchases and makes it difficult to prepare nutritionally balanced meals. Furthermore, there is a demand for a function that creates a list of ingredients needed based on household inventory information and supports waste-free shopping.

[1161] 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.

[1162] In this invention, the server includes means for inputting a user's physical condition data, means for checking and formatting the input physical condition data, means for transmitting the formatted physical condition data to the server, means for storing the received physical condition data in a database, means for analyzing the user's physical condition data and identifying missing nutrients and foods to avoid, means for generating an optimal menu based on the analyzed physical condition data, means for displaying the menu information sent from the server on a terminal, means for sharing the generated menu information with family members via a shared folder or bulletin board function, means for creating a necessary ingredient list based on the generated menu, means for comparing the ingredient list with home inventory information and adding missing ingredients to the final list, means for generating a notification message of the created ingredient list and transmitting it to the terminal, and means for receiving and displaying the notification. This enables the creation of nutritionally balanced menus based on the user's health status, thereby enabling efficient meal preparation and ingredient management at home.

[1163] "Means for inputting user's physical condition data" refers to an interface for the user to input their own health condition, such as an input form, check box, or text box within the application.

[1164] "Means for checking and formatting entered health data" refers to the function by which the system checks data entered by users and converts it into a standard format, such as standardizing date formats and correcting input errors.

[1165] "Means for sending formatted health data to a server" refers to the function of sending formatted data to a server via a network. Generally, communication methods such as the HTTP protocol or WebSocket are used.

[1166] "Means for storing received health data in a database" refers to the function of storing the received data on the server side in an appropriate database, such as an SQL database or NoSQL database.

[1167] "A means of analyzing the user's physical condition data and identifying nutrients that are lacking and foods that should be avoided" refers to a function that uses algorithms and AI models to analyze stored data and identify the nutrients that the user needs and foods that should be avoided.

[1168] "Means for generating optimal menus based on analyzed health data" refers to a function that searches for recipes and nutritional information in a database based on the analysis results and generates menus that are appropriate for the user's health condition.

[1169] "Means for displaying menu information sent from the server on the terminal" refers to the function of displaying menu information generated by the server on the user's terminal (such as a smartphone or tablet).

[1170] "Means for sharing the generated menu information with family members using a shared folder or bulletin board function" refers to the function for sharing the generated menu information through a shared folder or bulletin board function that can be accessed by all family members.

[1171] "Means for creating a list of ingredients required based on the generated menu" refers to a function that compiles a list of ingredients required for cooking based on the generated menu.

[1172] "Means for checking the ingredient list against home inventory information and adding missing ingredients to the final list" refers to a function that compares the generated ingredient list with home inventory information registered in advance by the user and adds only missing ingredients to the final list.

[1173] "Means for generating a notification message for the created ingredient list and sending it to the terminal" refers to a function for generating a notification message based on the required ingredient list and sending it to the user's terminal.

[1174] "Means for receiving and displaying notifications" refers to a function that displays the notification message received by the user's terminal so that the user can check the content.

[1175] The present invention provides a system for automatically generating healthy menus based on a user's physical condition data, sharing the menus with family members, and notifying them of necessary ingredients. A specific embodiment of the system will be described below.

[1176] Hardware and Software Configuration

[1177] This system consists of a terminal that receives user input, a server that analyzes data and generates menus, and a database that stores and shares data. Specifically, the system uses the following hardware and software:

[1178] Device: A mobile device such as a smartphone or tablet. The application runs on the iOS or Android platform.

[1179] Server: A high-performance computing device used to run AI models and analyze data. Specifically, it uses machine learning libraries such as TensorFlow and PyTorch.

[1180] Database: An SQL database (MySQL, PostgreSQL, etc.) or a NoSQL database (MongoDB, etc.) that stores user health data and home inventory information.

[1181] Program processing

[1182] 1. Enter user's physical condition data:

[1183] Users use a dedicated application to input their own physical condition data (fatigue, vitamin deficiencies, allergy information, etc.). The input form has text boxes and check boxes, and is designed to make data entry easy. For example, you might enter, "I feel very tired today."

[1184] 2. Sending health data:

[1185] The device checks the entered data and formats it as needed, for example to standardize date formats or correct typos. The data is then converted to JSON format and sent to the server.

[1186] 3. Analysis of physical condition data:

[1187] The server stores the received health data in a database. A table is created for each user in the database, allowing comparison with past data. The data is then analyzed using an AI model (for example, a model using TensorFlow or PyTorch) to identify nutrient deficiencies and foods that should be avoided.

[1188] 4. Menu generation:

[1189] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects recipes that use ingredients that are high in vitamin C.

[1190] 5. View and share menu information:

[1191] The device receives the menu information sent from the server and displays it on the user interface. The generated menu can also be shared by the whole family using a shared folder or the app's bulletin board function.

[1192] 6. Make a list of ingredients needed:

[1193] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[1194] 7. Ingredient List Notification:

[1195] The server generates a notification message based on the final ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can then check the displayed ingredient list and use it as a shopping list.

[1196] Specific examples

[1197] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device converts this information into JSON format and sends it to the server. The server stores the physical condition data in a database and analyzes it. If the analysis results show that the user is lacking in vitamin C, the server will create a menu rich in vitamin C (e.g., citrus salad, grilled broccoli and salmon, and fruit yogurt). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or yogurt are low, it adds those ingredients to the list and sends a notification to the device. The user can receive the notification and purchase the necessary ingredients to prepare a nutritionally balanced meal.

[1198] Prompt Sentence Examples

[1199] "For a user who has recently been feeling tired, please suggest a meal plan that contains the appropriate vitamins. Please also note that this user is deficient in vitamin C. Please generate the meal plan and a list of the ingredients required for it."

[1200] In this way, the present invention realizes a system that provides menus that suit the user's physical condition and makes meal preparation at home more efficient.

[1201] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1202] Step 1:

[1203] The user uses a dedicated application to input data about their physical condition. Information such as fatigue, vitamin deficiencies, and allergies is entered into a form in the application using text boxes and check boxes. The input data (e.g., "I've been feeling tired recently") is sent to the application.

[1204] Step 2:

[1205] The terminal receives the data entered by the user, checks the input data, and formats it. For example, it standardizes the date format and cleans the text data. The formatted data (e.g., {"fatigue": "high", "vitamin deficiency": "vitamin C"}) is generated.

[1206] Step 3:

[1207] The terminal converts the formatted data into JSON format and sends it to the server. This conversion process prepares the data in a format suitable for network communication. After transmission, the server receives the JSON data.

[1208] Step 4:

[1209] The server stores the received health data in a database. Specifically, it creates a table for each user in an SQL or NoSQL database and stores the data. In this step, the health data is persistently stored and can be analyzed.

[1210] Step 5:

[1211] The server analyzes the received health data using an AI model. Specifically, it uses TensorFlow and PyTorch to run a model that evaluates the user's health condition. The model analyzes the input data (e.g., "Vitamin C deficiency") and identifies nutrients that are lacking and foods that should be avoided. An analysis result (e.g., "Vitamin C deficiency") is generated.

[1212] Step 6:

[1213] The server generates an optimal menu based on the analysis results. It searches for appropriate recipes from a recipe database and combines them to create a menu. For example, if a person is deficient in vitamin C, it selects a recipe that uses ingredients that are high in vitamin C. The generated menu (e.g., "Citrus salad, grilled broccoli and salmon") is then generated.

[1214] Step 7:

[1215] The server sends the generated menu information to the terminal. The sent data is displayed on the user interface. For example, "Citrus salad, broccoli and grilled salmon" is displayed on the application screen.

[1216] Step 8:

[1217] The device displays the generated menu information, and the user can review it. The information can also be shared using a shared folder accessible to the whole family or the app's message board function. Clicking the share button uploads the information to the shared folder.

[1218] Step 9:

[1219] The server creates a list of ingredients based on the generated menu. This list is compared with the home inventory information registered in advance by the user. Ingredients already in the home are removed from the list, and only ingredients that are missing are added to the final list. A final ingredient list (e.g., "salmon, yogurt") is generated.

[1220] Step 10:

[1221] The server generates a notification message for the created ingredient list and sends it to the device. The notification message includes a list of the ingredients needed. For example, "You are running low on salmon and yogurt. They have been added to your shopping list."

[1222] Step 11:

[1223] The device receives the notification sent from the server and displays it on the user interface. The user can check the notification and use the required ingredients as a shopping list, which is displayed in the shopping list section of the application.

[1224] (Application example 1)

[1225] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1226] While conventional menu generation systems provide healthy menus based on the user's physical condition, the process of purchasing ingredients is time-consuming, resulting in a lack of user convenience. Furthermore, it is difficult to manage food inventory at home, leading to a high likelihood of unnecessary purchases. To solve these problems, a system is needed that integrates menu generation based on physical condition data with efficient food purchasing and management.

[1227] 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.

[1228] In this invention, the server includes means for inputting physical condition data, means for analyzing the input physical condition data, means for generating a menu based on the analyzed physical condition data, means for displaying the generated menu information, means for creating a required ingredient list based on the generated menu, means for notifying the user of the created ingredient list, and means for transmitting the required ingredient list to the online store via a communications network and performing a bulk purchase procedure. This allows the user to quickly obtain an optimal menu based on their physical condition and efficiently purchase the required ingredients.

[1229] "Physical condition data" is information indicating the user's health condition, such as fatigue, vitamin deficiency, and allergy information.

[1230] The "analyzing means" is a process or device that stores the user's physical condition data in a database and analyzes the data for the purpose of assessing the user's health condition.

[1231] The "means for generating a menu" is a process or system that creates an optimal meal menu based on analyzed physical condition data, taking into consideration the user's nutritional status.

[1232] The "displaying means" refers to a display device or software for visually presenting the generated menu information to the user.

[1233] The "means for creating an ingredient list" is a process or system that identifies the ingredients needed based on the generated menu and compiles them in list form.

[1234] The "notification means" is a message sending device or software for notifying the user of the created ingredient list.

[1235] "Means for sending to the online store via a communications network and completing the bulk purchase procedure" refers to a process or system that sends the created ingredient list to the online store via a network such as the Internet, allowing the user to purchase the ingredients they need in bulk.

[1236] The "means for sharing menu information among family members" is a software function or a shared folder that allows all family members to access the generated menu information.

[1237] "Home inventory information" is information about ingredients currently held in the user's home, and is used to calculate the ingredients that are in short supply.

[1238] The "means for checking against inventory information" is a process or system that compares the home inventory information with the generated ingredient list and excludes ingredients that are already present.

[1239] The present invention is a system that automatically creates healthy menus based on the user's physical condition data, shares that information with family members, notifies them of a list of necessary ingredients, and then transmits the list to an online store via a communication network for bulk purchasing. A specific embodiment of this system will be described below.

[1240] Input of user's physical condition data

[1241] Users use a dedicated smartphone application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). The device checks the input data, formats it, and then sends it to the server.

[1242] Analysis of physical condition data

[1243] The server stores the received health data in a database and performs analysis to evaluate the user's health condition. Specifically, it analyzes the user's current physical condition and nutritional status and identifies nutrients that are lacking and foods that should be avoided.

[1244] Menu generation

[1245] The server generates an optimal menu based on the analyzed physical condition data. The generated menu is a nutritionally balanced meal menu and is adjusted according to the user's health condition. For example, if a user is deficient in vitamin C, it will suggest a menu rich in fruits and vegetables.

[1246] Display and share menu information

[1247] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[1248] Creating and notifying a list of ingredients needed

[1249] The server creates a list of ingredients needed based on the generated menu. This list is compared with the home inventory information registered in advance by the user, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list. The server then creates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the required ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[1250] Send your ingredient list to online stores and buy in bulk

[1251] The server transmits the final ingredient list to the online store via a communication network, allowing the user to order the ingredients they need from the online store in a single purchase.

[1252] Specific examples

[1253] For example, if a user enters into the app, "I've been feeling tired lately and I feel like I'm lacking in vitamins," the device sends this information to the server. The server analyzes this physical condition data and generates a menu rich in vitamin C (e.g., orange juice, granola, grilled broccoli and salmon, kiwi fruit salad, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or broccoli are low, it adds those ingredients to the list and sends a notification to the device. Finally, the server sends the ingredient list to an online store, allowing the user to purchase the necessary ingredients in bulk.

[1254] Example prompt sentence:

[1255] The user's health data has been entered. They are deficient in Vitamin C. Based on this data, generate a nutritionally balanced meal plan and create a list of ingredients needed for that plan.

[1256] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1257] Step 1:

[1258] The user inputs their physical condition data using a dedicated smartphone application.

[1259] Input: Physical condition data such as fatigue, vitamin deficiency, and allergy information.

[1260] Specific operation: The user enters their status into each item in the app and presses the send button. The device collects this data, converts it into an appropriate format, and sends it to the server.

[1261] Step 2:

[1262] The server stores the received physical condition data in a database and performs data analysis.

[1263] Input: The user's health data.

[1264] Output: User's health assessment results and a list of nutrients they are lacking and foods they should avoid.

[1265] Specific operation: The server stores the received data in a database and uses the AI ​​model to analyze the data, sending a prompt to the generating AI model such as, "The user's physical condition data has been entered. Please evaluate the user's health condition based on this data."

[1266] Step 3:

[1267] The server automatically generates a menu based on the analysis results.

[1268] Input: Health assessment results, list of nutrients you're lacking and foods to avoid.

[1269] Output: A nutritionally balanced menu.

[1270] Specific operation: Based on the analysis results, the server uses the generative AI model to generate a menu by sending a prompt such as, "Please generate a nutritionally balanced menu that suits the user's health condition." The generated menu is then stored in a database.

[1271] Step 4:

[1272] The server sends the generated menu information to the terminal, which displays it to the user.

[1273] Enter: Menu.

[1274] Output: Menu information displayed to the user.

[1275] Specific operation: The server sends the generated menu information to the device, and the application visually displays it to the user, who can then review it and share it with their family within the app.

[1276] Step 5:

[1277] The server creates a list of ingredients needed based on the generated menu.

[1278] Input: Menu, household inventory information.

[1279] Output: A list of ingredients needed.

[1280] Specific operation: The server compares the information with a pre-registered household inventory database, excludes ingredients already in the home, and adds only ingredients that are in short supply to the list.

[1281] Step 6:

[1282] The server sends the created ingredient list to the terminal, which then displays it to the user.

[1283] Input: List of ingredients needed.

[1284] Output: A list of ingredients that are in short supply and notified to the user.

[1285] Specific operation: The server generates a final ingredient list and sends it to the device as a notification message. The device visually displays the missing ingredients to the user.

[1286] Step 7:

[1287] The server transmits the list of ingredients to the online store via a communication network, and a bulk purchase procedure is carried out.

[1288] Input: Final ingredient list.

[1289] Output: Purchase completion information in the online store.

[1290] Specific operation: The server sends the list of ingredients to the online store's purchasing API, allowing the user to complete the purchase all at once. The user confirms the purchase within the app.

[1291] The above are the specific processing steps.

[1292] 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.

[1293] The present invention is a system that automatically generates healthy menus using not only a user's physical condition data but also their emotional data, shares the menus with family members, and notifies them of necessary ingredients. Specific embodiments of this system will be described below.

[1294] Input of user's physical condition data and emotional data

[1295] The user uses a dedicated application to input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes their current emotional state (e.g., stress, elation, relief, etc.). The device checks the physical condition data and emotional data, formats it, and generates data to be sent to the server.

[1296] Analysis of physical condition data and emotional data

[1297] The server stores the received physical condition and emotional data in a database and analyzes the user's health and emotional state. Specifically, it comprehensively analyzes the user's current physical condition, nutritional status, and emotional state to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[1298] Menu generation

[1299] The server generates an optimal menu based on the analyzed physical condition data and emotional data. The generated menu is not only nutritionally balanced but also takes into consideration the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1300] Display and share menu information

[1301] The device displays the menu information sent from the server, and the user can check the generated menu and share the information using a shared folder that can be accessed by the whole family or the message board function within the app.

[1302] Creating a list of ingredients needed

[1303] The server creates a list of ingredients based on the generated menu. This list is compared with the user's home inventory information, and ingredients already in the home are removed from the list. Only ingredients that are missing are added to the final list.

[1304] Ingredient list notification

[1305] The server generates a notification message based on the created ingredient list and sends it to the device. The device receives the notification and displays the necessary ingredients to the user. The user can check the displayed ingredient list and use it as a shopping list.

[1306] Specific examples

[1307] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the device sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is sent to the device and shared so that the user and their family can check it. The server then compares it with household inventory information, and if salmon or almonds are low, it adds those ingredients to the list and sends a notification to the device. Finally, the user receives a notification and can purchase the necessary ingredients.

[1308] In this way, the present invention provides a menu that matches the user's physical condition and emotions, streamlines meal preparation at home, and realizes a system that supports comprehensive health management.

[1309] The processing flow will be explained below.

[1310] Step 1:

[1311] The user launches a dedicated application and inputs their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). In addition, the emotion engine inputs or automatically recognizes the user's current emotional state (e.g., stress, elation, relief, etc.).

[1312] Step 2:

[1313] The terminal receives the input physical condition data and emotion data and formats the data.

[1314] Step 3:

[1315] The terminal sends the formatted data to the server.

[1316] Step 4:

[1317] The server stores the received physical condition data and emotion data in a database.

[1318] Step 5:

[1319] The server retrieves the latest physical condition and emotional data from the database and begins analysis.

[1320] Step 6:

[1321] The server evaluates the user's health and emotional state based on physical condition data and emotional data, and analyzes the nutrients needed, foods to avoid, and ingredients that will boost your mood.

[1322] Step 7:

[1323] The server uses the analysis results to generate a menu that is nutritionally balanced and takes into account the user's emotional state. For example, if a user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1324] Step 8:

[1325] The server sends the generated menu to the terminal.

[1326] Step 9:

[1327] The menu information received by the device is displayed within the application so that the user can check it.

[1328] Step 10:

[1329] The user can review the displayed menu and then use the sharing function to upload it to a shared folder or in-app bulletin board that can be accessed by the whole family.

[1330] Step 11:

[1331] The server generates a list of ingredients based on the generated menu. The list contains all the ingredients needed for the dish.

[1332] Step 12:

[1333] The server retrieves the user's home inventory information from a database and compares it with the generated ingredient list.

[1334] Step 13:

[1335] The server generates a list of ingredients that are missing based on the matching results, excluding ingredients that are already in the home.

[1336] Step 14:

[1337] The server generates a notification message based on the list of ingredients that are in short supply and sends it to the terminal.

[1338] Step 15:

[1339] The terminal displays the received notification to the user, allowing the user to check the ingredients that are missing.

[1340] Step 16:

[1341] The user can check the list of ingredients they are short of and use it as a shopping list. For example, the user can create a list in the app or on paper and use it to purchase ingredients.

[1342] Through this series of steps, users can easily obtain a menu that best suits their physical condition and emotions, and can also efficiently manage and purchase the necessary ingredients.

[1343] Example 2

[1344] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1345] Conventional menu generation systems only suggest menus based on the user's physical condition data, so they can only suggest uniform menus without considering the user's emotional state. Also, because they create ingredient lists without considering household inventory information, ingredients are likely to be wasted. This has led to issues such as low user satisfaction and a high likelihood of food waste.

[1346] 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.

[1347] In this invention, the server includes means for inputting a user's physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for generating a menu using a generative AI model, means for displaying the generated menu information, means for sharing the displayed menu information, means for creating a necessary ingredient list based on the generated menu, means for comparing the created ingredient list with home inventory information, and means for notifying the user of the created ingredient list. This enables personalized menu suggestions that take the user's physical condition and emotions into consideration, and realizes efficient ingredient management that takes home inventory information into account.

[1348] "User's physical condition data" is information that indicates the user's health condition, such as the user's sense of fatigue, vitamin deficiency, allergy information, and the like.

[1349] "Emotion data" is information that indicates the user's emotional state, such as stress, elation, or relief.

[1350] "Analysis" refers to a process of comprehensively analyzing the user's health condition and emotional state based on the input physical condition data and emotional data.

[1351] "Menu generation" is a process that suggests optimal food and dish combinations to the user based on analyzed physical condition data and emotional data.

[1352] A "generative AI model" is an artificial intelligence model that automatically generates text and information to create menus based on specific prompts.

[1353] "Menu information" is information about the combination of food and dishes that has been generated.

[1354] "Display" refers to visualizing and presenting data or information on a user interface.

[1355] "Sharing" means allowing multiple users to access, view, and use information.

[1356] The "ingredient list" is a list of foods needed to create a menu.

[1357] "Home inventory information" is information about food already in the home.

[1358] A "notification" is a message or other means sent to inform a user of information.

[1359] The present invention is a system that collects data on a user's physical condition and emotions, automatically generates an optimal menu based on that data, shares the menu with family members, and notifies them of a list of necessary ingredients.

[1360] First, the user inputs their own physical condition data using a dedicated application. This data includes information on health conditions such as fatigue, vitamin deficiencies, and allergies. The user then uses the camera to activate an emotion engine that automatically recognizes their own emotional state. The emotion engine can be general facial expression recognition software (e.g., an emotion recognition API) that analyzes facial expressions.

[1361] The device formats and transmits the physical and emotional data obtained from the user to the server using an HTTP POST request, ensuring security using the HTTPS protocol.

[1362] The server stores the received data in a database (for example, a MySQL database) and performs the necessary analysis. This analysis uses data analysis libraries such as Python and Pandas. Specifically, it compares trends in the user's physical condition data and emotional data with past data to identify nutrients that are lacking, foods to avoid, and ingredients that will boost your mood.

[1363] The server then uses a generative AI model (e.g., a generative AI) to generate a menu based on the prompt, which includes information about the user's current physical condition and emotions, and the generative AI model uses this information to suggest the optimal menu.

[1364] For example, you can generate a plan like this:

[1365] If a user inputs "I've been feeling tired and stressed lately," the server will generate a menu rich in vitamin C and effective in reducing stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This information is sent to the device and can be viewed by the user and their family.

[1366] The server then creates a list of ingredients based on the user's home inventory and the generated menu. The home inventory information is compared with the information stored in the database. The list is adjusted to include only the ingredients that are missing.

[1367] Finally, the server generates this ingredient list as a notification message and sends it to the terminal. The terminal receives the notification and displays it on its user interface. The user can check the displayed ingredient list and use it as a shopping list.

[1368] By integrating this series of processes, it is possible to realize a system that proposes personalized menus tailored to the user's physical condition and emotions, streamlines meal preparation at home, and supports comprehensive health management.

[1369] Example prompt sentence:

[1370] If a user inputs that they have recently been feeling tired and stressed, the system will suggest a menu rich in vitamin C and effective in relieving stress based on the analysis results.

[1371] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1372] Step 1:

[1373] Users use a dedicated application to input their physical condition data. Specifically, they manually enter information such as fatigue, vitamin deficiencies, and allergies into a form on the application screen. In addition, to input or automatically recognize their current emotional state, the camera is used to activate the emotion engine, and emotion data is obtained through facial expression recognition software. The input at this time is information about the user's health and emotional state.

[1374] Step 2:

[1375] The device formats the physical condition and emotion data received from the user and sends it to the server. Specifically, it formats the physical condition and emotion data into a format such as JSON and sends it to the server using an HTTP POST request. This formatted data also includes additional information such as the user ID and timestamp. The input is the formatted physical condition and emotion data obtained from the user, and the output is the data to be sent to the server.

[1376] Step 3:

[1377] The server receives the data sent from the device and stores it in a database. Specifically, it saves the data in a MySQL database. The input at this stage is the physical condition data and emotion data sent from the device, and the output is the data stored in the database. Transactions are used when storing data to ensure data integrity.

[1378] Step 4:

[1379] The server analyzes the stored data. Using Python data analysis libraries (e.g., Pandas, Scikit-learn), it compares trends in the stored physical condition and emotional data with past data to comprehensively analyze the user's current health and emotional state. This analysis identifies nutrients that are lacking, foods to avoid, and ingredients that boost mood. The input is the physical condition and emotional data stored in the database, and the output is the analysis results.

[1380] Step 5:

[1381] The server generates a prompt based on the analysis results and inputs it into a generative AI model (e.g., GPT-4). This prompt includes information about the user's physical condition and emotions. Specifically, if the user inputs that they have recently been feeling tired and stressed, the following prompt will be sent to the generative AI model: "Please suggest a menu based on the analysis results that is rich in vitamin C and has a stress-relieving effect." The input is the analysis results, and the output is the prompt.

[1382] Step 6:

[1383] The server generates a menu using a generative AI model. When a prompt is sent to the generative AI model, the model returns an optimal menu that is nutritionally balanced and takes into account the user's emotional state. The input is the prompt, and the output is the generated menu.

[1384] Step 7:

[1385] The terminal receives the menu information sent from the server and displays it on the user interface. Specifically, it displays the menu details, ingredient list, cooking instructions, etc. in a format that is easy for the user to understand. The input is the menu information sent from the server, and the output is the information displayed on the user interface.

[1386] Step 8:

[1387] Users can check the displayed menu information and share it through a shared folder that can be accessed by the whole family or through the message board function within the app. This sharing makes it easier for the whole family to plan meals together. The input is the displayed menu information, and the output is the information to be shared.

[1388] Step 9:

[1389] The server creates a list of ingredients based on the generated menu. First, it checks the home inventory information to remove ingredients already in the home from the list, and then lists only ingredients that are in short supply. The input is the menu and home inventory information, and the output is the final ingredient list.

[1390] Step 10:

[1391] The server generates a notification message based on the created ingredient list and sends it to the terminal. The notification message is sent to the user using the application's notification function. The input is the ingredient list, and the output is the notification message that is displayed to the user.

[1392] Step 11:

[1393] The terminal displays the notification message received from the server on the user interface, and the user can check the displayed ingredient list and use it as a shopping list. The input is the notification message, and the output is the display information on the user interface.

[1394] Through the above processing steps, this system provides personalized menus tailored to the user's physical condition and emotions, streamlines meal planning at home, and realizes a system that supports comprehensive health management.

[1395] (Application example 2)

[1396] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1397] Conventional menu generation systems based on physical condition do not take into account the user's emotional state and do not adequately integrate with household inventory information, making it difficult to streamline the user's overall health management and meal preparation. Furthermore, the system lacks the functionality to instantly order delivery meals based on the generated menu. This means that users have to spend a lot of time planning their own menus, purchasing ingredients, and cooking them.

[1398] 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.

[1399] In this invention, the server includes means for inputting physical condition data and emotional data, means for analyzing the input physical condition data and emotional data, means for generating a menu based on the analyzed physical condition data and emotional data, means for displaying the generated menu information, means for generating an orderable menu based on the generated menu, means for notifying the user of the generated menu, means for confirming a delivery order for the menu selected by the user, and means for sending a delivery notification. This makes it possible to easily generate and display an optimal menu based on the user's physical condition and emotional state, and to directly order delivery, thereby significantly improving the efficiency of the user's health management and meal preparation.

[1400] "Physical condition data" is information relating to the user's health condition, including fatigue, vitamin deficiency, allergy information, and the like.

[1401] "Emotion data" is information about the user's psychological state, including stress, elation, relief, and the like.

[1402] A "menu" is a meal suggestion generated based on the user's physical condition data and emotional data, and takes into consideration nutritional balance and emotional care.

[1403] A "menu" is a list of foods that are provided to the user based on the generated recipe, from which the user can select and order.

[1404] An "orderable menu" is a list of foods that a user can order through a delivery service based on the generated menu.

[1405] "Delivery notification" is information that notifies the user of the delivery status of food after a delivery order has been confirmed.

[1406] "Home inventory information" is information about ingredients currently held in the user's home, and is used to create and compare ingredient lists.

[1407] This invention is a system that generates an optimal menu based on a user's physical condition data and emotional data, generates an orderable menu based on the optimal menu, and places a delivery order. A specific embodiment of this system will be described.

[1408] Entering User Data

[1409] Using a dedicated smartphone app, users input their own physical condition data (fatigue, vitamin deficiency, allergy information, etc.). An emotion engine is also used to automatically recognize the user's current emotional state (stress, elation, relief, etc.). The physical condition data and emotional data are formatted and sent to the server.

[1410] Data analysis

[1411] The server stores the received physical condition and emotional data in a database and analyzes it. Specifically, the server uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's current health and emotional state. This allows the server to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[1412] Plan and menu generation

[1413] The server generates an optimal menu based on the analysis results, and then generates a menu that the user can order for delivery based on that menu. The menu is generated to balance nutritional balance with emotional care. For example, it may include a salad rich in vitamin C if you are feeling tired, or a relaxing herbal tea if you are stressed.

[1414] Menu Notification and Ordering

[1415] The generated menu is displayed on the smartphone app, allowing the user to review and select an item. Once the user selects a menu item, the order is confirmed and the server generates a delivery notification and sends it to the user. The user can then check the delivery status in real time based on this notification.

[1416] Specific examples

[1417] For example, if a user enters into the app, "I've been feeling tired and stressed lately," the smartphone app will send this information to the server. The server will analyze the physical condition data and emotional data and generate a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, herbal tea, etc.). Based on this menu, it will generate a menu that the user can order and notify the smartphone app. Once the user selects a menu and confirms the order, the server will send a delivery notification, allowing them to check the delivery status.

[1418] Prompt Sentence Examples

[1419] "User ID: 1, physical condition data: fatigue, emotional data: stress"

[1420] Generate appropriate menus based on the user's physical condition and emotions.

[1421] This system will significantly improve the efficiency of users' health management and meal preparation, and enable quick responses through delivery services.

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] Using a dedicated smartphone app, users input their physical condition data (fatigue, vitamin deficiency, allergy information, etc.), and the emotion engine automatically recognizes their current emotional state (stress, elation, relief, etc.) and inputs the data into the app. The input data is formatted in JSON and sent to the server.

[1425] Input: physical condition data, emotional data

[1426] Output: Pretty-printed JSON data

[1427] Step 2:

[1428] The server stores the received physical condition and emotional data in a database. It uses Pandas to analyze the data in a data frame format and comprehensively evaluates the user's health and emotional state. This allows it to identify nutrients that are lacking, foods to avoid, and ingredients that boost mood.

[1429] Input: Formatted JSON data

[1430] Output: Analysis results (nutrients you are lacking, foods to avoid, ingredients that boost your mood)

[1431] Step 3:

[1432] The server then generates an optimal menu based on the analysis results. This menu includes nutritionally balanced foods and foods that take emotional care into consideration. The generated menu is designed to be specific and actionable for the user.

[1433] Input: Analysis results

[1434] Output: Optimal menu

[1435] Step 4:

[1436] The server generates a menu that the user can order from based on the generated menu. The generated menu is displayed on the smartphone app. The user can select from the displayed menu.

[1437] Input: Optimal menu

[1438] Output: Orderable menu

[1439] Step 5:

[1440] The user selects from the displayed menu through the smartphone app and confirms the delivery order. The selected menu is sent to the server and recorded in the order database.

[1441] Input: User's selection from an orderable menu

[1442] Output: Confirmed delivery order

[1443] Step 6:

[1444] The server generates a delivery notification based on the confirmed order details and sends it to the user's smartphone app. The user can receive this delivery notification and check the delivery status in real time.

[1445] Input: Confirmed delivery order

[1446] Output: Delivery notification

[1447] Specific examples

[1448] For example, if a user enters into the app that they have been feeling tired and stressed recently, the smartphone app sends this information to the server. The server analyzes this physical condition and emotional data and generates a menu rich in vitamin C and effective in relieving stress (e.g., citrus salad, grilled salmon and broccoli with almonds, herbal tea, etc.). This menu information is displayed on the user's smartphone as an optimal menu. The user selects from the displayed menu and confirms the delivery order. If salmon or almonds are in short supply, those ingredients will be delivered based on the delivery notification.

[1449] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1450] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1451] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1452] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1453] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1454] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1455] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1456] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1457] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1458] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1459] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1460] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1461] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1462] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1463] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1464] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1465] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1466] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1467] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1468] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1469] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1470] The following is further disclosed regarding the above embodiment.

[1471] (Claim 1)

[1472] A means for inputting physical condition data;

[1473] A means for analyzing the input physical condition data;

[1474] A means for generating a menu based on the analyzed physical condition data;

[1475] A means for displaying the generated menu information;

[1476] A means for creating a list of ingredients required based on the generated menu;

[1477] a means for notifying the user of the created ingredient list;

[1478] A system including:

[1479] (Claim 2)

[1480] 10. The system according to claim 1, further comprising means for sharing menu information among family members.

[1481] (Claim 3)

[1482] 2. The system according to claim 1, further comprising means for storing home inventory information of a user, and means for checking the created ingredient list against the home inventory information.

[1483] "Example 1"

[1484] (Claim 1)

[1485] A means for inputting user's physical condition data;

[1486] A means to check and format the entered health data,

[1487] means for transmitting the formatted physical condition data to a server;

[1488] A means for storing the received physical condition data in a database;

[1489] A means of analyzing the user's physical condition data and identifying nutrients that are lacking and foods that should be avoided;

[1490] A means for generating an optimal menu based on the analyzed physical condition data;

[1491] A means for displaying the menu information sent from the server on the terminal;

[1492] The generated menu information can be shared with family members using shared folders and bulletin board functions.

[1493] A means for creating a list of ingredients required based on the generated menu;

[1494] a means of checking the ingredient list against home inventory information and adding missing ingredients to the final list;

[1495] means for generating a notification message of the created ingredient list and transmitting it to the terminal;

[1496] a means for receiving and displaying notifications;

[1497] A system including:

[1498] (Claim 2)

[1499] 10. The system according to claim 1, further comprising means for sharing menu information among family members.

[1500] (Claim 3)

[1501] 2. The system according to claim 1, further comprising means for storing home inventory information of a user, and means for checking the created ingredient list against the home inventory information.

[1502] "Application Example 1"

[1503] (Claim 1)

[1504] A means for inputting physical condition data;

[1505] A means for analyzing the input physical condition data;

[1506] A means for generating a menu based on the analyzed physical condition data;

[1507] A means for displaying the generated menu information;

[1508] A means for creating a list of ingredients required based on the generated menu;

[1509] a means for notifying the user of the created ingredient list;

[1510] a means for transmitting a list of ingredients required to an online store via a communication network and carrying out a bulk purchase procedure;

[1511] A system including:

[1512] (Claim 2)

[1513] 10. The system according to claim 1, further comprising means for sharing menu information among family members.

[1514] (Claim 3)

[1515] 2. The system according to claim 1, further comprising means for storing home inventory information of a user, and means for checking the created ingredient list against the home inventory information.

[1516] "Example 2: Combining Emotion Engines"

[1517] (Claim 1)

[1518] A means for inputting user's physical condition data and emotion data;

[1519] means for analyzing input physical condition data and emotion data;

[1520] A means for generating a menu based on the analyzed physical condition data and emotion data;

[1521] A means for generating a menu using a generative AI model;

[1522] A means for displaying the generated menu information;

[1523] A means for sharing the displayed menu information;

[1524] A means for creating a list of ingredients required based on the generated menu;

[1525] a means for matching the prepared ingredient list with home inventory information;

[1526] a means for notifying the user of the created ingredient list;

[1527] A system including:

[1528] (Claim 2)

[1529] 10. The system according to claim 1, further comprising means for sharing menu information among family members.

[1530] (Claim 3)

[1531] 2. The system according to claim 1, further comprising means for storing home inventory information of a user, and means for checking the created ingredient list against the home inventory information.

[1532] "Application example 2 when combining emotion engines"

[1533] (Claim 1)

[1534] A means for inputting physical condition data and emotional data;

[1535] means for analyzing input physical condition data and emotion data;

[1536] A means for generating a menu based on the analyzed physical condition data and emotion data;

[1537] A means for displaying the generated menu information;

[1538] A means for generating an orderable menu based on the generated menu;

[1539] a means for notifying the generated menu;

[1540] A means for confirming a delivery order for the menu selected by the user;

[1541] a means for sending a delivery notification;

[1542] A system including:

[1543] (Claim 2)

[1544] 10. The system according to claim 1, further comprising means for sharing menu information and recipe information among family members.

[1545] (Claim 3)

[1546] The system according to claim 1, further comprising means for storing a user's home inventory information, means for checking the created ingredient list against the home inventory information, and means for checking against delivered ingredients. [Explanation of symbols]

[1547] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for inputting physical condition data; A means for analyzing the input physical condition data; A means for generating a menu based on the analyzed physical condition data; A means for displaying the generated menu information; A means for creating a list of ingredients required based on the generated menu; a means for notifying the user of the created ingredient list; A system including:

2. The system according to claim 1 , further comprising means for sharing menu information among family members.

3. 2. The system according to claim 1, further comprising means for storing information on a user's home inventory, and means for checking the created ingredient list against the home inventory information.

Images