system

Abstract

Provide a system. The system includes a means for users to input information such as family composition, allergies, preferences, number of times cooked, budget, and delivery frequency; means for transmitting the input information to a server; A means for storing the received information by the server and generating a menu that takes nutritional balance into consideration; A means for generating a recipe and a list of ingredients from the generated menu; means for displaying the generated menu, recipe, and ingredient list to a user; A means for users to review, change, and approve; The system includes a means for automatically placing orders with partner companies based on the confirmed ingredient list and delivering the orders to the user.

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] Currently, there are pre-cut and pre-measured food kits and delivery services, but many people hesitate to use them due to their high prices and limited options. Another issue is the lack of menus that take into account the specific needs and nutritional balance of individual households. Furthermore, preparing meals that accommodate allergies and preferences is complicated and time-consuming, making daily meal preparation a burden. The present invention aims to solve the above-mentioned problems and reduce the burden of meal preparation by providing healthy, easy meals that meet the user's specific needs. [Means for solving the problem]

[0005] The system of the present invention includes a means for users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and a means for transmitting the input information to a server. The server stores this information and generates a menu that takes nutritional balance into consideration. The system also includes a means for generating recipes and ingredient lists from the generated menu, and provides a means for displaying these menus, recipes, and ingredient lists to the user. The user has a means for confirming, changing, and approving the displayed information. By including a means for automatically ordering from affiliated suppliers based on the finalized ingredient list and delivering it to the user, the system realizes the provision of healthy, easy meals that meet individual preferences.

[0006] "User" refers to a person who uses the system to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency, and receives menu suggestions and food delivery.

[0007] "Family composition" refers to information such as the number of people in the household and the age and gender of each member that the user enters into the system.

[0008] "Allergies" refers to information about foods that the user or a member of the user's family is sensitive to and should avoid.

[0009] "Preferences" refers to specific cooking styles and ingredient preferences based on the preferences of the user and their family.

[0010] "Number of meals cooked" refers to the number of meals the user desires to eat per day.

[0011] A "budget" refers to the amount of money a user plans to spend on cooking on a weekly or monthly basis.

[0012] "Delivery frequency" refers to how often a user requests food delivery.

[0013] "Server" refers to a central processing unit that receives, stores, and analyzes data from users, and generates menus and manages ingredient lists.

[0014] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on input data.

[0015] "Menu" refers to a list of meals suggested by the system for a week, taking into account nutritional balance.

[0016] A "recipe" refers to instructions that explain how to prepare a specific dish based on a menu.

[0017] "Ingredient list" refers to a list that lists the types and quantities of ingredients required based on the specified menu and recipe.

[0018] "Ordering" refers to the process of ordering ingredients from partner suppliers based on the confirmed ingredient list.

[0019] "Delivery" refers to the act of delivering the ordered ingredients to the user's address on the specified date and time. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves the ingredients, automatically orders the ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[0042] System Operation

[0043] 1. User registration and input

[0044] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[0045] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[0046] 2. Data transmission and storage

[0047] The terminal (user's device) sends the entered data to the server.

[0048] The server stores the received data in a database.

[0049] 3. Menu generation

[0050] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0051] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[0052] 4. Generate recipes and ingredient lists

[0053] The server generates a recipe based on the generated menu and generates a list of ingredients required for the recipe, including type, amount, and cutting and measuring options.

[0054] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[0055] 5. User Verification and Authorization

[0056] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0057] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[0058] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[0059] 6. Customize your ingredients

[0060] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[0061] The terminal transmits the user's selection to the server.

[0062] The server updates the final ingredient list based on the user's selections.

[0063] 7. Final confirmation and automatic delivery

[0064] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[0065] The delivery company delivers the ingredients to the user's address on the specified date and time.

[0066] The server confirms delivery completion and notifies the user.

[0067] Specific examples

[0068] User A is a family of two adults and one child who has a dairy allergy. Their preferences are primarily Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[0069] 1. User A enters the required information and sends it to the server.

[0070] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken," "stir-fried vegetables," "grilled salted fish," etc.).

[0071] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A.

[0072] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[0073] 5. The delivery company delivers the ingredients to User A's address on the specified date and time and notifies the server that delivery is complete.

[0074] The present invention allows users to easily prepare healthy meals tailored to their individual needs, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals.

[0075] The processing flow will be explained below.

[0076] Step 1:

[0077] A user visits an app or website and is prompted to create a new account.

[0078] Step 2:

[0079] The user creates an account by entering the required information, such as name, email address, and password.

[0080] Step 3:

[0081] The terminal transmits the input information to the server.

[0082] Step 4:

[0083] The server stores the received user data in a database.

[0084] Step 5:

[0085] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0086] Step 6:

[0087] The user enters the required information.

[0088] Step 7:

[0089] The terminal transmits the input data to the server.

[0090] Step 8:

[0091] The server stores the received data in a database.

[0092] Step 9:

[0093] The server retrieves the user's information from a database and inputs it into a generative AI model.

[0094] Step 10:

[0095] The generative AI model generates a week's worth of menus taking into account the user's family composition, allergies, preferences, and nutritional balance.

[0096] Step 11:

[0097] The server stores the generated menus and recipes in a database.

[0098] Step 12:

[0099] The server generates a list of ingredients needed based on the saved menu and recipes.

[0100] Step 13:

[0101] The server stores the generated ingredient list in a database.

[0102] Step 14:

[0103] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0104] Step 15:

[0105] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[0106] Step 16:

[0107] The device sends user changes and authorization information to the server.

[0108] Step 17:

[0109] The server updates the final ingredient list based on the changes and approvals received.

[0110] Step 18:

[0111] The user selects cutting and measuring options from the ingredient list.

[0112] Step 19:

[0113] The terminal transmits the selected option information to the server.

[0114] Step 20:

[0115] The server updates the final ingredient list and stores it in the database.

[0116] Step 21:

[0117] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[0118] Step 22:

[0119] The server notifies the user of the order details and delivery schedule.

[0120] Step 23:

[0121] A delivery company delivers the ingredients to the user's address on the specified date and time.

[0122] Step 24:

[0123] The delivery person completes the delivery and sends a confirmation to the server.

[0124] Step 25:

[0125] The server sends a delivery completion notification to the user.

[0126] Example 1

[0127] 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."

[0128] In today's busy lifestyles, it is difficult for users to prepare nutritionally balanced meals every day. Purchasing optimal ingredients and planning meals according to each household's allergies, preferences, budget, etc. takes time and effort. Furthermore, selecting ingredients and adjusting recipes is time-consuming and requires efficient operation. However, conventional systems have not been able to solve these issues in a unified manner.

[0129] 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.

[0130] In this invention, the server includes: means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency; means for transmitting the input information to the server; means for the server to store the received information and generate a menu that takes nutritional balance into consideration using a generative AI model; means for generating recipes and a list of necessary ingredients from the generated menu; means for displaying the generated menu, recipes, and ingredient list to the user; means for the user to confirm, change, and approve; means for the user to select cutting and measuring options based on the ingredient list; and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This enables users to efficiently plan nutritionally balanced meals that meet their individual needs and easily procure the necessary ingredients.

[0131] "User" refers to an individual or household who uses the system to input information and receive menu and recipe suggestions.

[0132] "Family composition" refers to information such as the number of people in the user's household and their ages, and is a factor that influences the creation of menus.

[0133] "Allergies" refer to hypersensitivity reactions that a user or their family members have to certain foods or ingredients, and are important information that is taken into consideration when generating menus.

[0134] "Preferences" refers to personal preferences such as favorite dishes and disliked ingredients of the user and their family.

[0135] "Number of times cooked" refers to the number of meals a user eats per day, and is important data for menu planning.

[0136] "Budget" refers to the amount of money a user allocates for food on a weekly or monthly basis.

[0137] "Delivery frequency" refers to how often a user wants food delivered (e.g., once a week, twice a month, etc.).

[0138] "Server" refers to the central computing device that receives and stores information submitted by users and generates menus, recipes, and ingredient lists using generative AI models.

[0139] A "generative AI model" refers to an artificial intelligence model that automatically generates menus that take into account nutritional balance, allergies, and preferences based on information input by the user.

[0140] A "menu" refers to a combination of multiple meal menus suggested by a generative AI model.

[0141] "Recipe" refers to detailed instructions on how to prepare each dish on a menu.

[0142] "Ingredient List" refers to a list of ingredients required based on a recipe, including their type, quantity, and options for cutting and measuring.

[0143] "Partner" refers to a company or organization that provides and delivers ingredients specified by the user.

[0144] "Delivery method" refers to the method for automatically placing an order with partner suppliers based on the confirmed ingredient list and delivering the ingredients to the user.

[0145] "Cutting and measuring options" refers to a customization function that allows users to select the shape, size, and quantity of ingredients according to their preferences.

[0146] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and a server generates nutritionally balanced menus based on that information. The system automatically generates recipes and lists of ingredients and provides them to the user. The user can then confirm, change, and approve the displayed information, order ingredients from affiliated suppliers, and have them delivered.

[0147] First, a user creates an account on a website or application. At this time, the user enters basic information such as name, email address, and password. Then, the user enters family composition (number of people, age, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.).

[0148] The information entered by the user is sent from the device to the server. Specifically, the device's application or web browser passes the data to the server via an HTML form or API. This data is parsed in JSON format or similar, and the server stores it in a database.

[0149] The server retrieves the stored information and inputs it into a generative AI model. This generative AI model automatically generates a week's worth of menus, taking into account the user's allergies, preferences, and nutritional balance. The generative AI model is built using a machine learning algorithm written in Python, for example. An example of a specific prompt is, "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[0150] Based on the generated menu, the server generates a recipe for each dish and a list of ingredients. The recipe includes detailed instructions on cooking steps, timing, and necessary cooking equipment. The ingredient list includes the type, amount, and cutting and measuring options of the ingredients, allowing the user to clearly see which ingredients they need to purchase.

[0151] The generated menu, recipe, and ingredient list are displayed to the user via the terminal. The user can review them and make changes or adjustments as needed. For example, if a specific dish needs to be replaced with another, it can be easily replaced in the system. The user can also select cutting and measuring options based on the ingredient list. For example, detailed selections such as "thinly slice the carrots and finely chop the onions" are possible.

[0152] The final ingredient list and delivery date are automatically sent from the server to the partner supplier's system. Data is exchanged using protocols such as APIs. The partner supplier delivers the ingredients to the user's address on the specified date and time, and is notified once delivery is complete. The server then confirms delivery completion and notifies the user.

[0153] This series of processes allows users to easily plan nutritionally balanced meals tailored to their individual needs and efficiently source the necessary ingredients. Furthermore, by providing options for cutting and measuring ingredients, the system significantly reduces the time and effort required for daily meal preparation.

[0154] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0155] Step 1:

[0156] User enters information

[0157] Subject: User

[0158] How it works: The user enters information such as family size, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0159] Input: Various information provided by the user (family composition, allergy information, preferences, cooking frequency, budget, delivery frequency).

[0160] Output: The entered information is temporarily stored on the device.

[0161] What happens: The user fills out a web form or app screen with this information and clicks the "Submit" button.

[0162] Step 2:

[0163] Data transmission

[0164] Subject: Terminal

[0165] Operation: The device sends the entered information to the server.

[0166] Input: The information the user entered in step 1.

[0167] Output: JSON formatted data sent to the server.

[0168] What it does: Data is securely transmitted to the server using the HTTPS protocol.

[0169] Step 3:

[0170] Data storage

[0171] Subject: Server

[0172] What it does: The server stores the received information in a database.

[0173] Input: JSON format data sent from the terminal.

[0174] Output: User information stored in the database.

[0175] What happens: The server parses the received data and stores it in a database in the appropriate format. For example, it stores information by user ID and assigns an index to it.

[0176] Step 4:

[0177] Menu generation

[0178] Subject: Server

[0179] How it works: The server retrieves the user's information from a database and inputs it into a generative AI model.

[0180] Input: User information stored in the database.

[0181] Output: A week's worth of meal plans generated by the AI ​​model.

[0182] Specific operation: The server sends a specific prompt to the generation AI model, and the AI ​​generates a menu. Example prompt: "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[0183] Step 5:

[0184] Recipe and ingredient list generation

[0185] Subject: Server

[0186] How it works: The server generates a recipe and a list of ingredients based on the menu.

[0187] Input: Generated menu data.

[0188] Output: Detailed recipe and ingredient list for each dish.

[0189] What it does: The server retrieves details of each dish from the recipe database and generates a list containing the required ingredients, their quantities, and cutting and measuring options.

[0190] Step 6:

[0191] User confirmation and changes

[0192] Subject: Terminal, User

[0193] What it does: The device displays the generated menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[0194] Input: Menu, recipe, and ingredient list provided by the server.

[0195] Output: The final menu and ingredients list, as reviewed and modified by the user.

[0196] Specific operation: The user checks the menu on the device and presses the change button if they want to make changes. The changes are sent to the server in real time.

[0197] Step 7:

[0198] Cutting and weighing options

[0199] Subject: User, Device

[0200] Action: User selects cutting and measuring options based on an ingredient list.

[0201] Input: Ingredient list and its customization options.

[0202] Output: A final customized ingredient list.

[0203] Specific operation: The user selects an option such as "slice carrots" or "chop onions," and the device sends that information to the server.

[0204] Step 8:

[0205] Final confirmation and order

[0206] Subject: Server

[0207] How it works: The server checks the final ingredient list and delivery schedule, and automatically places an order with partner suppliers.

[0208] Input: Finalized ingredient list and delivery date information.

[0209] Output: Purchase order information sent to partner.

[0210] Specific operation: The server uses the API to send order data to the partner's system.

[0211] Step 9:

[0212] Delivery and completion notification

[0213] Subject: Delivery company, server

[0214] How it works: The delivery company delivers the groceries to the user's address at the specified date and time and notifies the server that delivery is complete.

[0215] Input: Order information received by the delivery company.

[0216] Output: Delivery of ingredients and notification of delivery completion.

[0217] Specific operation: The delivery person delivers the food and sends a completion notification to the server after the delivery is complete. The server receives the completion notification and notifies the user that the delivery is complete.

[0218] (Application example 1)

[0219] 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."

[0220] In today's busy society, it is difficult to plan a nutritionally balanced menu, procure the necessary ingredients based on that menu, and measure them in the appropriate amounts. Furthermore, there is a lack of automated methods for preparing meals that take into consideration allergies and preferences. Therefore, there is a need for a system that provides optimal ingredients and recipes for each individual user.

[0221] 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.

[0222] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking is done, budget, and delivery frequency, means for transmitting the input information to the server, means for the server to store the received information and generate a menu using a generative AI model taking nutritional balance into consideration, means for generating recipes and a list of necessary ingredients from the generated menu, means for displaying the generated menu, recipes, and ingredient list on a display terminal, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This makes it possible to easily prepare healthy meals that meet the individual needs of the user.

[0223] "User" refers to a person who uses a service or system.

[0224] "Family composition" refers to information such as the number of people in a household and their ages.

[0225] "Allergy" refers to an immune response to a specific food or substance.

[0226] "Preferences" refers to the ingredients and types of food that one likes or dislikes.

[0227] "Cooking frequency" refers to the frequency of cooking per day or per week.

[0228] A "budget" refers to the total amount of money you can spend on ingredients and dishes.

[0229] "Delivery frequency" refers to the number of times or frequency at which food ingredients are delivered.

[0230] "Means" refers to a method or device for achieving a particular purpose.

[0231] "Server" refers to a computer system for storing and processing data.

[0232] "Means for inputting information" refers to a device or interface that allows a user to input information.

[0233] "Means for sending to server" refers to a method for transferring input information to the server.

[0234] "Nutritional balance" refers to the appropriate distribution of various nutrients that people need.

[0235] A "generative AI model" is an algorithm that uses artificial intelligence to generate results based on specified conditions.

[0236] A "menu" refers to a plan or list of dishes for a certain period of time.

[0237] A "recipe" is a document that details how to make a dish, the steps involved, and the ingredients needed.

[0238] An "ingredient list" refers to a list of ingredients and equipment needed based on a recipe.

[0239] "Display terminal" refers to a device for displaying information (smartphone, tablet, PC, etc.).

[0240] "Means for review, modification, and approval" refers to the interface or process by which a user can review the displayed information, modify it if necessary, and ultimately approve it.

[0241] "Affiliate companies" refer to companies that work in conjunction with the system to supply and deliver ingredients.

[0242] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves it, automatically orders ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[0243] System Configuration

[0244] 1. Enter and submit user information

[0245] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0246] The app sends the information entered by the user to the server via an HTTP POST request.

[0247] 2. Data processing and storage

[0248] The server stores the received information in a database. For this purpose, a cloud server such as AWS (registered trademark) EC2 or Google (registered trademark) Cloud Platform is used.

[0249] A relational database such as MySQL (registered trademark) or PostgreSQL is used as the database.

[0250] 3. Menu generation

[0251] The server retrieves information from the database and inputs it into a generative AI model, such as OpenAI's GPT-4 model or Google AI's T5 model.

[0252] Using a generative AI model, we generate a weekly menu with prompts like the following:

[0253] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[0254] For example, on the first day, "teriyaki chicken, stir-fried vegetables, miso soup" will be generated.

[0255] 4. Generate recipes and ingredient lists

[0256] Based on the menu, the server automatically generates a detailed recipe and ingredients list, including ingredient types, quantities, and cutting and measuring options.

[0257] 5. User Interface

[0258] The smartphone app displays the generated menu, recipe, and ingredient list to the user.

[0259] The user can review these and make changes or adjustments as needed.

[0260] 6. Final confirmation and ordering of materials

[0261] Based on the materials list that the user has confirmed and approved, the server automatically places orders with partner suppliers.

[0262] The partner company delivers the materials to the user at the specified date and time and reports the completion of delivery to the server.

[0263] Specific examples

[0264] User A is a family of two adults and one child who is allergic to dairy products. Their preferences are mainly Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[0265] 1. User A enters the necessary information through a smartphone app and sends it to the server.

[0266] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken, stir-fried vegetables, miso soup, etc.").

[0267] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A through a smartphone app.

[0268] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[0269] 5. The partner company delivers the materials to User A's address on the specified date and time and notifies the server that delivery is complete.

[0270] The system allows users to easily prepare healthy meals tailored to their individual needs, and delivers the ingredients, including cutting and measuring, significantly reducing the burden of daily meals.

[0271] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0272] Step 1:

[0273] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0274] The entered information is saved in the smartphone app.

[0275] Step 2:

[0276] The terminal sends the information entered by the user to the server using an HTTP POST request.

[0277] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0278] Output: The user information sent to the server.

[0279] Step 3:

[0280] The server converts the received data into a data format and inserts it into the database in order to store the received information in the database.

[0281] Input: User information.

[0282] Output: User information stored in the database.

[0283] Step 4:

[0284] The server retrieves user information from the database and inputs it as a prompt sentence into the generative AI model.

[0285] For example, to generate the following prompt:

[0286] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[0287] Input: Information stored in the user's database.

[0288] Output: The prompt sentence to be fed into the generative AI model.

[0289] Step 5:

[0290] The generative AI model generates a weekly menu based on the prompt, generating specific dish names and contents in the process.

[0291] Input: prompt statement.

[0292] Output: A week's worth of meals.

[0293] Step 6:

[0294] Based on the generated menu, the server generates the recipes and ingredient lists required for each dish.

[0295] Input: The generated menu.

[0296] Output: Recipe and ingredients list.

[0297] Step 7:

[0298] The device displays the generated menu, recipe, and ingredient list to the user, who can review them and make changes or adjustments as needed.

[0299] Input: Recipe and ingredients list.

[0300] Output: Information that is displayed to the user.

[0301] Step 8:

[0302] The material list that the user has confirmed and approved is sent back to the server from the terminal.

[0303] Input: A list of materials reviewed and approved by the user.

[0304] Output: Final material list sent to the server.

[0305] Step 9:

[0306] The server automatically places orders with partner suppliers based on the confirmed material list, generating order information and sending it to the supplier via an API for receiving orders.

[0307] Input: Finalized materials list.

[0308] Output: Order information sent to partner.

[0309] Step 10:

[0310] The partner company delivers the materials to the user at the specified date and time based on the order details. After the delivery is completed, the partner company notifies the server of the delivery completion information.

[0311] Input: Order information.

[0312] Output: Materials delivered to the user and notification of delivery completion.

[0313] This allows users to receive meals and ingredients tailored to their needs, reducing the burden of daily meal preparation.

[0314] 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.

[0315] In this invention, the user inputs information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc., and the system generates a menu that takes nutritional balance into consideration based on this information. Furthermore, this system aims to increase user satisfaction by combining an emotion engine that recognizes the user's emotions and customizing the menu and ingredient suggestions based on emotions.

[0316] System Operation

[0317] 1. User registration and input

[0318] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[0319] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[0320] 2. Data transmission and storage

[0321] The terminal (user's device) sends the entered data to the server.

[0322] The server stores the received data in a database.

[0323] 3. Menu generation

[0324] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0325] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[0326] 4. Sentiment Analysis and Customization

[0327] The device will activate an emotion engine to recognize the user's emotions. For example, users can input emotion data within the app through facial recognition or voice analysis.

[0328] The server receives the emotion data from the emotion engine and stores it in a database.

[0329] The server analyzes the user's current emotional state based on the emotion data and customizes the menu accordingly. For example, if the user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0330] 5. Generating recipes and ingredient lists

[0331] The server generates a recipe based on the generated menu and emotional customization, and generates an ingredient list for the recipe, including the type, amount, and cutting and measuring options.

[0332] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[0333] 6. User Verification and Authorization

[0334] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0335] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[0336] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[0337] 7. Customize your ingredients

[0338] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[0339] The terminal transmits the user's selection to the server.

[0340] The server updates the final ingredient list based on the user's selections.

[0341] 8. Final confirmation and automatic delivery

[0342] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[0343] The delivery company delivers the ingredients to the user's address on the specified date and time.

[0344] The server confirms delivery completion and notifies the user.

[0345] Specific examples

[0346] User B is a family of one adult and two children who has a nut allergy. They primarily prefer Western food, have a weekly budget of 15,000 yen, would like three meals a day, and have selected delivery once a week. Furthermore, they have been busy and stressed recently, so they would like a relaxing meal.

[0347] 1. User B enters the required information and sends it to the server.

[0348] 2. The server uses a generative AI model to generate a week's worth of Western-style meals that avoid nuts (e.g., grilled chicken, minestrone soup, fish and chips, etc.).

[0349] 3. The server analyzes User B's emotional data and suggests a menu that includes ingredients that have a relaxing effect.

[0350] 4. The server generates recipes and ingredient lists for these dishes and displays them to User B.

[0351] 5. User B checks the displayed information and confirms that he / she wants delivery on the weekend.

[0352] 6. The delivery company delivers the ingredients to User B's address on the specified date and time and notifies the server that delivery is complete.

[0353] This invention allows users to easily prepare healthy meals tailored to their individual needs and emotional state, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals. Furthermore, by using an emotion engine, it can also address the user's psychological needs.

[0354] The processing flow will be explained below.

[0355] Step 1:

[0356] A user visits an app or website and is prompted to create a new account.

[0357] Step 2:

[0358] The user creates an account by entering the required information, such as name, email address, and password.

[0359] Step 3:

[0360] The terminal transmits the input information to the server.

[0361] Step 4:

[0362] The server stores the received user data in a database.

[0363] Step 5:

[0364] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0365] Step 6:

[0366] The user enters the required information.

[0367] Step 7:

[0368] The terminal transmits the input data to the server.

[0369] Step 8:

[0370] The server stores the received data in a database.

[0371] Step 9:

[0372] The user launches the emotion engine on the app or website and inputs emotional data through facial expression recognition and voice analysis.

[0373] Step 10:

[0374] The device transmits the emotion data to the server.

[0375] Step 11:

[0376] The server receives the emotion data from the emotion engine and stores it in a database.

[0377] Step 12:

[0378] The server retrieves user information and emotional data from the database and inputs it into the generative AI model.

[0379] Step 13:

[0380] A generative AI model generates a week's worth of menus, taking into account the user's family structure, allergies, preferences, nutritional balance, and emotional state.

[0381] Step 14:

[0382] The server stores the generated menus and recipes in a database.

[0383] Step 15:

[0384] The server generates a list of ingredients based on the generated menu and recipe.

[0385] Step 16:

[0386] The server stores the generated ingredient list in a database.

[0387] Step 17:

[0388] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0389] Step 18:

[0390] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[0391] Step 19:

[0392] The device sends user changes and authorization information to the server.

[0393] Step 20:

[0394] The server updates the final ingredient list based on the changes and approvals received.

[0395] Step 21:

[0396] The user selects cutting and measuring options from the ingredient list.

[0397] Step 22:

[0398] The terminal transmits the selected option information to the server.

[0399] Step 23:

[0400] The server updates the final ingredient list and stores it in the database.

[0401] Step 24:

[0402] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[0403] Step 25:

[0404] The server notifies the user of the order details and delivery schedule.

[0405] Step 26:

[0406] A delivery company delivers the ingredients to the user's address on the specified date and time.

[0407] Step 27:

[0408] The delivery person completes the delivery and sends a confirmation to the server.

[0409] Step 28:

[0410] The server sends a delivery completion notification to the user.

[0411] Example 2

[0412] 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."

[0413] Conventional menu generation systems generate menus based on information such as the user's family structure, allergies, preferences, and budget, but they cannot customize the menu taking into account the user's emotional state, which prevents them from fully increasing user satisfaction. Furthermore, while there is a demand for meal suggestions that are tailored to individual emotional states in addition to nutritional balance, there is a problem in that no system exists that can achieve this.

[0414] 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.

[0415] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency, means for transmitting the input information to the server, means for saving the received information and generating a menu that takes nutritional balance into consideration using a generative AI model, means for generating recipes and a list of necessary ingredients from the generated menu, means for the terminal to activate an emotion engine that recognizes the user's emotions and transmit the emotion data to the server, means for the server to analyze the user's emotional state based on the emotion data and customize the menu, means for displaying the generated menu, recipes, and ingredient list to the user, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering it to the user. This makes it possible to propose individual menus tailored to the user's emotional state.

[0416] "User" refers to an individual who uses the system to create a menu that takes into account their own nutritional balance and receives food delivery.

[0417] A "terminal" is a device through which a user inputs information into a system and views output from the system.

[0418] "Server" refers to the central processing unit that receives the information sent by the user, generates the menu using the generative AI model, and sends the final ingredient list to the supplier.

[0419] A "generative AI model" is an artificial intelligence technology that includes an algorithm that automatically generates menus that take nutritional balance into consideration based on user input information.

[0420] The "emotion engine" is a software component that analyzes the user's emotional state and customizes menus based on that.

[0421] "Menu" refers to a meal combination generated by the system that takes into account nutritional balance.

[0422] A "recipe" is a document that describes the specific cooking steps for creating a menu.

[0423] An "ingredient list" is a table listing the types and quantities of ingredients needed to create a menu or recipe.

[0424] "Delivery company" refers to a company that delivers ingredients to the user based on the final ingredient list generated by the system.

[0425] "Partner" refers to a supplier with which the System partners for the procurement and delivery of ingredients.

[0426] "Customization" refers to modifying or changing menus and recipes based on the user's preferences and emotional state.

[0427] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and the system generates a menu that takes nutritional balance into consideration based on this information, and further enables the system to customize the menu according to the user's emotional state using an emotion engine.

[0428] First, a user accesses an app or website and creates an account by entering information such as their name, email address, and password. Then, they enter detailed information such as family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). This entered information is sent from the terminal (user's device) to the server.

[0429] The server then stores the received user information in a database. This information is stored in the database linked to the user ID. The server retrieves the user information from the database and inputs it into a generative AI model. This generative AI model uses OpenAI's GPT-4 and other technologies to generate a week's worth of menus taking into account allergies, preferences, and nutritional balance. For example, if the user has a nut allergy, the generative AI model will select menus that do not contain nuts.

[0430] The server generates a detailed recipe and ingredient list for each meal. The recipe includes cooking instructions, necessary ingredients, and cooking tools, while the ingredient list includes specific details such as type, amount, and cutting and measuring options. For example, a recipe for "Teriyaki Chicken" might call for 200 grams of chicken, 3 tablespoons of soy sauce, and 2 tablespoons of sugar.

[0431] The device then activates an emotion engine to recognize the user's emotions. This emotion recognition uses the smartphone's camera and microphone to collect emotional data, for example, through facial expression recognition and voice analysis. The server receives this emotional data and stores it in a database. The server analyzes the emotional data and customizes menus taking into account the user's emotional state. For example, if the user is feeling highly stressed, it will suggest menus using ingredients that have stress-reducing effects (e.g., chamomile and avocado).

[0432] The generated menu, recipes, and ingredient list are displayed to the user on the terminal, who can review them and make changes or adjustments as necessary. The user can also give final approval to the delivery schedule and ingredient costs. After approval, the final ingredient list is automatically ordered from the partner supplier by the server. The delivery company delivers the ingredients to the user's address on the specified date and time and notifies the server that delivery is complete. The server confirms that delivery is complete and notifies the user.

[0433] As a specific example, User B is a family of one adult and two children who has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, they would like three meals a day, and they have selected one delivery per week. They have recently been feeling tired and stressed, and are looking for a relaxing meal. User B enters the necessary information and sends it to the server. The server uses a generative AI model to generate a menu that focuses on Western food but avoids nuts. Dishes such as "grilled chicken," "minestrone soup," and "fish and chips" are suggested. Furthermore, emotional data is analyzed to customize the menu, including ingredients with a relaxing effect.

[0434] Based on the generated recipe and ingredient list, User B checks the menu, makes any necessary adjustments, and then approves the weekend delivery. The ingredients are delivered at the specified date and time, and the user then confirms that the delivery has been completed. This system allows users to easily prepare meals that suit their own health and emotional state.

[0435] Example prompt sentence:

[0436] The user's family consists of one adult and two children, and the user has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, and they would like three meals a day. They are feeling a bit tired and stressed, and would like to eat meals that will help them relax. Please generate a week's worth of menus based on these conditions.

[0437] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0438] Step 1:

[0439] Users access the app or website and create an account by entering information such as their name, email address, and password. Next, they enter detailed information such as their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget, and delivery frequency.

[0440] Input: Name, email address, password, family composition, allergies, preferences, cooking frequency, budget, delivery frequency.

[0441] Output: Input information is sent from the device to the server.

[0442] Step 2:

[0443] The terminal transmits the input information to the server.

[0444] The server stores the received user information in a database, where the information is linked to the user ID.

[0445] Input: User information.

[0446] Output: The user information is saved in the database.

[0447] Step 3:

[0448] The server retrieves user information from the database and inputs it as prompts into the generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0449] Input: A prompt such as, "The user's family consists of one adult and two children, and they have a nut allergy. Their preferences are primarily Western food, their budget is 15,000 yen per week, and they would like three meals a day."

[0450] Output: Generated weekly menu.

[0451] Step 4:

[0452] The server generates a detailed recipe and ingredients list based on the generated menu. The recipe includes cooking steps, required ingredients, and cooking tools, while the ingredients list includes types, amounts, and options for cutting and measuring.

[0453] Input: The generated menu.

[0454] Output: Recipe and ingredients list.

[0455] Step 5:

[0456] The device activates an emotion engine to recognize the user's emotions, collects emotion data through facial recognition and voice analysis, and sends it to the server.

[0457] Input: User's emotional expression (facial expression and voice).

[0458] Output: Emotion data.

[0459] Step 6:

[0460] The server receives the emotion data from the emotion engine and stores it in a database. Then, it analyzes the emotion data and customizes the menu based on the user's emotional state, thereby proposing a final menu that reflects the user's emotional state.

[0461] Input: Emotion data.

[0462] Output: Final menu reflecting emotional state.

[0463] Step 7:

[0464] The device displays the final menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[0465] Input: Final menu, recipe, and ingredient list.

[0466] Output: Information that the user reviews, modifies, and approves.

[0467] Step 8:

[0468] The user reviews the final menu and ingredient list and approves the delivery schedule and ingredient costs.

[0469] Input: Review and approve final menus, recipes and ingredient lists.

[0470] Output: Approved ingredient list.

[0471] Step 9:

[0472] The server automatically places orders with partner suppliers based on the final approved ingredient list.

[0473] Input: Approved ingredient list.

[0474] Output: Ingredients are ordered from partner suppliers.

[0475] Step 10:

[0476] The delivery company will deliver the ingredients to the user's address on the specified date and time.

[0477] The server confirms delivery completion and notifies the user.

[0478] Input: Order information and delivery instructions.

[0479] Output: Notification of delivery of ingredients and completion of delivery.

[0480] In this way, the system can easily provide a customized menu based on the user's individual needs and emotional state, along with the ingredients needed to make that menu.

[0481] (Application example 2)

[0482] 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."

[0483] Current nutritionally balanced menu suggestion and food delivery systems can generate menus based on user information, but they have the problem of not being able to customize suggestions that take the user's emotional state into account. This results in a problem of not being able to sufficiently increase user satisfaction. Furthermore, while there is a demand for systems that users can operate intuitively, conventional systems lack such operability. Therefore, there is a need for a system that can recognize and analyze the user's emotional state and customize menus based on that information to make suggestions that more closely meet individual needs.

[0484] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model to generate a menu based on the user's information and emotional state, means for analyzing the user's emotional state and customizing the menu based on this, and means for displaying the generated menu, recipe, and ingredient list to the user. This makes it possible to propose a menu that is adapted to the user's individual needs and emotional state.

[0485] The "user information input means" is a means by which a user inputs information such as family composition, allergies, preferences, number of times cooked, budget, and delivery frequency.

[0486] The "information transmission means" is a means for transmitting input information to a server.

[0487] The "information storage means" is a means for storing information received by the server.

[0488] The "menu generation means" is a means for generating a menu based on input information and emotional state, taking into consideration nutritional balance.

[0489] "Means for using a generative AI model" refers to means for using a generative AI model to generate a menu based on the user's information and emotional state.

[0490] The "recipe generation means" is a means for generating a recipe and a list of necessary ingredients from the generated menu.

[0491] The "information display means" is a means for displaying the generated menu, recipes, and ingredient list to the user.

[0492] "Means for confirmation, change and approval" refers to the means by which users can confirm, change and approve.

[0493] The "automatic ordering means" is a means for automatically placing orders with partner suppliers based on the confirmed ingredient list.

[0494] The "emotional state analysis means" is a means for analyzing the user's emotional state and customizing a menu based on this.

[0495] This invention relates to a system that proposes nutritionally balanced meals for users and automates the delivery of ingredients. In particular, it customizes the meals taking into account the user's emotional state. This system operates by allowing users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency using a smartphone app.

[0496] Enter and submit user information

[0497] First, the user accesses the smartphone app and enters the necessary information. This information includes family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). The entered information is sent from the smartphone device to the server.

[0498] Save information and generate menus

[0499] The server stores the information sent by the user in a database. The information stored in the database is used to generate nutritionally balanced menus using a "generative AI model." This generative AI model receives information such as the user's family composition, allergies, and preferences as input and generates a weekly menu. The generated menu also includes recipes and a list of necessary ingredients.

[0500] Sentiment analysis and menu customization

[0501] The user's emotional state is recognized using the smartphone's camera and microphone. Specifically, the system uses technologies such as the emotion recognition library "DeepFace" to analyze facial expressions and voice to identify the user's emotional state. The server then customizes the menu based on this emotional data. For example, if the user is excited, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0502] Menu display and user confirmation

[0503] The server displays the generated menu, recipes, and ingredient list on the user's smartphone. The user can check the displayed information and make changes or approvals as necessary. After the ingredient list is confirmed, an order is automatically placed with a partner delivery company, and the ingredients are delivered to the user's address at the specified date and time.

[0504] Hardware and software used

[0505] Hardware: Smartphones, servers

[0506] Software: Emotion recognition library "DeepFace", generative AI model "TENSORFLOW (registered trademark)"

[0507] Specific examples

[0508] For example, assume that User A has a family of one adult and two children, a nut allergy, a preference for Western food, a weekly budget of 15,000 yen, desires three meals a day, and selects delivery once a week. Assume that User A has been feeling stressed recently and desires a relaxing meal.

[0509] An example of a prompt sentence could be, "An excited user has a family of one adult and two children, has a nut allergy, and has a weekly budget of 15,000 yen. He wants suggestions for a week's worth of menus, mainly Western food."

[0510] In this way, the system can offer customized meal suggestions based on individual needs and emotional state.

[0511] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0512] Step 1:

[0513] Entering user information

[0514] Using a smartphone app, users input necessary information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc. The input information is then saved on the smartphone device.

[0515] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc.

[0516] Output: The smartphone device is now ready to send this information to the server.

[0517] Step 2:

[0518] Sending and storing information

[0519] The smartphone device sends the entered information to a server, which stores the received information in a database, thereby building a user profile.

[0520] Input: User information from the smartphone device.

[0521] Output: User information stored in the database.

[0522] Step 3:

[0523] Menu generation

[0524] The server retrieves user information from the database and inputs it into a generative AI model, which then takes into account family composition, allergies, preferences, and other factors to generate a week's worth of nutritionally balanced menus.

[0525] Input: User profile data.

[0526] Output: Generated weekly menu.

[0527] Step 4:

[0528] Emotion analysis

[0529] The user inputs their emotional state using a smartphone app. The device uses a camera and microphone to analyze facial expressions and voice, and an emotion recognition library (e.g., "DeepFace") identifies the user's emotion. The results are sent to a server.

[0530] Input: User's facial and voice data.

[0531] Output: Emotion data stored by the server.

[0532] Step 5:

[0533] Emotion-based customization

[0534] The server customizes the generated menu based on the emotional data. For example, if a user is feeling stressed, it will suggest a menu that includes ingredients that have a relaxing effect.

[0535] Input: Emotion data, generated menu.

[0536] Output: A customized menu.

[0537] Step 6:

[0538] Menu and ingredient list generation

[0539] The server generates a detailed recipe and ingredient list based on the customized meal plan, including ingredient types, quantities, and cutting and measuring options.

[0540] Input: Your customized menu.

[0541] Output: Recipe and ingredients list.

[0542] Step 7:

[0543] User Verification and Authorization

[0544] The generated menu, recipes, and ingredient list are displayed on the user's smartphone. The user can review them and make changes or approvals as necessary. Finally, they can confirm the delivery date and ingredient costs.

[0545] Input: Customized menus, recipes, and ingredient lists.

[0546] Output: User approval.

[0547] Step 8:

[0548] Food ordering and delivery

[0549] The server automatically places an order with a partner supplier based on the ingredient list confirmed by the user, and the partner supplier delivers the ingredients to the user's address on the specified date and time.

[0550] Input: Finalized ingredient list.

[0551] Output: Order confirmation and delivery of ingredients.

[0552] The above is the flow of specific processing steps for implementing the invention.

[0553] 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.

[0554] 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.

[0555] 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.

[0556] [Second embodiment]

[0557] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0558] 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.

[0559] 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).

[0560] 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.

[0561] 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.

[0562] 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).

[0563] 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. 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.

[0564] 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.

[0565] 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.

[0566] 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.

[0567] 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.

[0568] 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."

[0569] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves the ingredients, automatically orders the ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[0570] System Operation

[0571] 1. User registration and input

[0572] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[0573] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[0574] 2. Data transmission and storage

[0575] The terminal (user's device) sends the entered data to the server.

[0576] The server stores the received data in a database.

[0577] 3. Menu generation

[0578] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0579] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[0580] 4. Generate recipes and ingredient lists

[0581] The server generates a recipe based on the generated menu and generates a list of ingredients required for the recipe, including type, amount, and cutting and measuring options.

[0582] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[0583] 5. User Verification and Authorization

[0584] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0585] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[0586] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[0587] 6. Customize your ingredients

[0588] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[0589] The terminal transmits the user's selection to the server.

[0590] The server updates the final ingredient list based on the user's selections.

[0591] 7. Final confirmation and automatic delivery

[0592] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[0593] The delivery company delivers the ingredients to the user's address on the specified date and time.

[0594] The server confirms delivery completion and notifies the user.

[0595] Specific examples

[0596] User A is a family of two adults and one child who has a dairy allergy. Their preferences are primarily Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[0597] 1. User A enters the required information and sends it to the server.

[0598] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken," "stir-fried vegetables," "grilled salted fish," etc.).

[0599] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A.

[0600] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[0601] 5. The delivery company delivers the ingredients to User A's address on the specified date and time and notifies the server that delivery is complete.

[0602] The present invention allows users to easily prepare healthy meals tailored to their individual needs, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals.

[0603] The processing flow will be explained below.

[0604] Step 1:

[0605] A user visits an app or website and is prompted to create a new account.

[0606] Step 2:

[0607] The user creates an account by entering the required information, such as name, email address, and password.

[0608] Step 3:

[0609] The terminal transmits the input information to the server.

[0610] Step 4:

[0611] The server stores the received user data in a database.

[0612] Step 5:

[0613] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0614] Step 6:

[0615] The user enters the required information.

[0616] Step 7:

[0617] The terminal transmits the input data to the server.

[0618] Step 8:

[0619] The server stores the received data in a database.

[0620] Step 9:

[0621] The server retrieves the user's information from a database and inputs it into a generative AI model.

[0622] Step 10:

[0623] The generative AI model generates a week's worth of menus taking into account the user's family composition, allergies, preferences, and nutritional balance.

[0624] Step 11:

[0625] The server stores the generated menus and recipes in a database.

[0626] Step 12:

[0627] The server generates a list of ingredients needed based on the saved menu and recipes.

[0628] Step 13:

[0629] The server stores the generated ingredient list in a database.

[0630] Step 14:

[0631] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0632] Step 15:

[0633] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[0634] Step 16:

[0635] The device sends user changes and authorization information to the server.

[0636] Step 17:

[0637] The server updates the final ingredient list based on the changes and approvals received.

[0638] Step 18:

[0639] The user selects cutting and measuring options from the ingredient list.

[0640] Step 19:

[0641] The terminal transmits the selected option information to the server.

[0642] Step 20:

[0643] The server updates the final ingredient list and stores it in the database.

[0644] Step 21:

[0645] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[0646] Step 22:

[0647] The server notifies the user of the order details and delivery schedule.

[0648] Step 23:

[0649] A delivery company delivers the ingredients to the user's address on the specified date and time.

[0650] Step 24:

[0651] The delivery person completes the delivery and sends a confirmation to the server.

[0652] Step 25:

[0653] The server sends a delivery completion notification to the user.

[0654] Example 1

[0655] 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."

[0656] In today's busy lifestyles, it is difficult for users to prepare nutritionally balanced meals every day. Purchasing optimal ingredients and planning meals according to each household's allergies, preferences, budget, etc. takes time and effort. Furthermore, selecting ingredients and adjusting recipes is time-consuming and requires efficient operation. However, conventional systems have not been able to solve these issues in a unified manner.

[0657] 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.

[0658] In this invention, the server includes: means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency; means for transmitting the input information to the server; means for the server to store the received information and generate a menu that takes nutritional balance into consideration using a generative AI model; means for generating recipes and a list of necessary ingredients from the generated menu; means for displaying the generated menu, recipes, and ingredient list to the user; means for the user to confirm, change, and approve; means for the user to select cutting and measuring options based on the ingredient list; and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This enables users to efficiently plan nutritionally balanced meals that meet their individual needs and easily procure the necessary ingredients.

[0659] "User" refers to an individual or household who uses the system to input information and receive menu and recipe suggestions.

[0660] "Family composition" refers to information such as the number of people in the user's household and their ages, and is a factor that influences the creation of menus.

[0661] "Allergies" refer to hypersensitivity reactions that a user or their family members have to certain foods or ingredients, and are important information that is taken into consideration when generating menus.

[0662] "Preferences" refers to personal preferences such as favorite dishes and disliked ingredients of the user and their family.

[0663] "Number of times cooked" refers to the number of meals a user eats per day, and is important data for menu planning.

[0664] "Budget" refers to the amount of money a user allocates for food on a weekly or monthly basis.

[0665] "Delivery frequency" refers to how often a user wants food delivered (e.g., once a week, twice a month, etc.).

[0666] "Server" refers to the central computing device that receives and stores information submitted by users and generates menus, recipes, and ingredient lists using generative AI models.

[0667] A "generative AI model" refers to an artificial intelligence model that automatically generates menus that take into account nutritional balance, allergies, and preferences based on information input by the user.

[0668] A "menu" refers to a combination of multiple meal menus suggested by a generative AI model.

[0669] "Recipe" refers to detailed instructions on how to prepare each dish on a menu.

[0670] "Ingredient List" refers to a list of ingredients required based on a recipe, including their type, quantity, and options for cutting and measuring.

[0671] "Partner" refers to a company or organization that provides and delivers ingredients specified by the user.

[0672] "Delivery method" refers to the method for automatically placing an order with partner suppliers based on the confirmed ingredient list and delivering the ingredients to the user.

[0673] "Cutting and measuring options" refers to a customization function that allows users to select the shape, size, and quantity of ingredients according to their preferences.

[0674] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and a server generates nutritionally balanced menus based on that information. The system automatically generates recipes and lists of ingredients and provides them to the user. The user can then confirm, change, and approve the displayed information, order ingredients from affiliated suppliers, and have them delivered.

[0675] First, a user creates an account on a website or application. At this time, the user enters basic information such as name, email address, and password. Then, the user enters family composition (number of people, age, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.).

[0676] The information entered by the user is sent from the device to the server. Specifically, the device's application or web browser passes the data to the server via an HTML form or API. This data is parsed in JSON format or similar, and the server stores it in a database.

[0677] The server retrieves the stored information and inputs it into a generative AI model. This generative AI model automatically generates a week's worth of menus, taking into account the user's allergies, preferences, and nutritional balance. The generative AI model is built using a machine learning algorithm written in Python, for example. An example of a specific prompt is, "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[0678] Based on the generated menu, the server generates a recipe for each dish and a list of ingredients. The recipe includes detailed instructions on cooking steps, timing, and necessary cooking equipment. The ingredient list includes the type, amount, and cutting and measuring options of the ingredients, allowing the user to clearly see which ingredients they need to purchase.

[0679] The generated menu, recipe, and ingredient list are displayed to the user via the terminal. The user can review them and make changes or adjustments as needed. For example, if a specific dish needs to be replaced with another, it can be easily replaced in the system. The user can also select cutting and measuring options based on the ingredient list. For example, detailed selections such as "thinly slice the carrots and finely chop the onions" are possible.

[0680] The final ingredient list and delivery date are automatically sent from the server to the partner supplier's system. Data is exchanged using protocols such as APIs. The partner supplier delivers the ingredients to the user's address on the specified date and time, and is notified once delivery is complete. The server then confirms delivery completion and notifies the user.

[0681] This series of processes allows users to easily plan nutritionally balanced meals tailored to their individual needs and efficiently source the necessary ingredients. Furthermore, by providing options for cutting and measuring ingredients, the system significantly reduces the time and effort required for daily meal preparation.

[0682] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0683] Step 1:

[0684] User enters information

[0685] Subject: User

[0686] How it works: The user enters information such as family size, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0687] Input: Various information provided by the user (family composition, allergy information, preferences, cooking frequency, budget, delivery frequency).

[0688] Output: The entered information is temporarily stored on the device.

[0689] What happens: The user fills out a web form or app screen with this information and clicks the "Submit" button.

[0690] Step 2:

[0691] Data transmission

[0692] Subject: Terminal

[0693] Operation: The device sends the entered information to the server.

[0694] Input: The information the user entered in step 1.

[0695] Output: JSON formatted data sent to the server.

[0696] What it does: Data is securely transmitted to the server using the HTTPS protocol.

[0697] Step 3:

[0698] Data storage

[0699] Subject: Server

[0700] What it does: The server stores the received information in a database.

[0701] Input: JSON format data sent from the terminal.

[0702] Output: User information stored in the database.

[0703] What happens: The server parses the received data and stores it in a database in the appropriate format. For example, it stores information by user ID and assigns an index to it.

[0704] Step 4:

[0705] Menu generation

[0706] Subject: Server

[0707] How it works: The server retrieves the user's information from a database and inputs it into a generative AI model.

[0708] Input: User information stored in the database.

[0709] Output: A week's worth of meal plans generated by the AI ​​model.

[0710] Specific operation: The server sends a specific prompt to the generation AI model, and the AI ​​generates a menu. Example prompt: "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[0711] Step 5:

[0712] Recipe and ingredient list generation

[0713] Subject: Server

[0714] How it works: The server generates a recipe and a list of ingredients based on the menu.

[0715] Input: Generated menu data.

[0716] Output: Detailed recipe and ingredient list for each dish.

[0717] What it does: The server retrieves details of each dish from the recipe database and generates a list containing the required ingredients, their quantities, and cutting and measuring options.

[0718] Step 6:

[0719] User confirmation and changes

[0720] Subject: Terminal, User

[0721] What it does: The device displays the generated menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[0722] Input: Menu, recipe, and ingredient list provided by the server.

[0723] Output: The final menu and ingredients list, as reviewed and modified by the user.

[0724] Specific operation: The user checks the menu on the device and presses the change button if they want to make changes. The changes are sent to the server in real time.

[0725] Step 7:

[0726] Cutting and weighing options

[0727] Subject: User, Device

[0728] Action: User selects cutting and measuring options based on an ingredient list.

[0729] Input: Ingredient list and its customization options.

[0730] Output: A final customized ingredient list.

[0731] Specific operation: The user selects an option such as "slice carrots" or "chop onions," and the device sends that information to the server.

[0732] Step 8:

[0733] Final confirmation and order

[0734] Subject: Server

[0735] How it works: The server checks the final ingredient list and delivery schedule, and automatically places an order with partner suppliers.

[0736] Input: Finalized ingredient list and delivery date information.

[0737] Output: Purchase order information sent to partner.

[0738] Specific operation: The server uses the API to send order data to the partner's system.

[0739] Step 9:

[0740] Delivery and completion notification

[0741] Subject: Delivery company, server

[0742] How it works: The delivery company delivers the groceries to the user's address at the specified date and time and notifies the server that delivery is complete.

[0743] Input: Order information received by the delivery company.

[0744] Output: Delivery of ingredients and notification of delivery completion.

[0745] Specific operation: The delivery person delivers the food and sends a completion notification to the server after the delivery is complete. The server receives the completion notification and notifies the user that the delivery is complete.

[0746] (Application example 1)

[0747] 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."

[0748] In today's busy society, it is difficult to plan a nutritionally balanced menu, procure the necessary ingredients based on that menu, and measure them in the appropriate amounts. Furthermore, there is a lack of automated methods for preparing meals that take into consideration allergies and preferences. Therefore, there is a need for a system that provides optimal ingredients and recipes for each individual user.

[0749] 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.

[0750] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking is done, budget, and delivery frequency, means for transmitting the input information to the server, means for the server to store the received information and generate a menu using a generative AI model taking nutritional balance into consideration, means for generating recipes and a list of necessary ingredients from the generated menu, means for displaying the generated menu, recipes, and ingredient list on a display terminal, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This makes it possible to easily prepare healthy meals that meet the individual needs of the user.

[0751] "User" refers to a person who uses a service or system.

[0752] "Family composition" refers to information such as the number of people in a household and their ages.

[0753] "Allergy" refers to an immune response to a specific food or substance.

[0754] "Preferences" refers to the ingredients and types of food that one likes or dislikes.

[0755] "Cooking frequency" refers to the frequency of cooking per day or per week.

[0756] A "budget" refers to the total amount of money you can spend on ingredients and dishes.

[0757] "Delivery frequency" refers to the number of times or frequency at which food ingredients are delivered.

[0758] "Means" refers to a method or device for achieving a particular purpose.

[0759] "Server" refers to a computer system for storing and processing data.

[0760] "Means for inputting information" refers to a device or interface that allows a user to input information.

[0761] "Means for sending to server" refers to a method for transferring input information to the server.

[0762] "Nutritional balance" refers to the appropriate distribution of various nutrients that people need.

[0763] A "generative AI model" is an algorithm that uses artificial intelligence to generate results based on specified conditions.

[0764] A "menu" refers to a plan or list of dishes for a certain period of time.

[0765] A "recipe" is a document that details how to make a dish, the steps involved, and the ingredients needed.

[0766] An "ingredient list" refers to a list of ingredients and equipment needed based on a recipe.

[0767] "Display terminal" refers to a device for displaying information (smartphone, tablet, PC, etc.).

[0768] "Means for review, modification, and approval" refers to the interface or process by which a user can review the displayed information, modify it if necessary, and ultimately approve it.

[0769] "Affiliate companies" refer to companies that work in conjunction with the system to supply and deliver ingredients.

[0770] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves it, automatically orders ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[0771] System Configuration

[0772] 1. Enter and submit user information

[0773] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0774] The app sends the information entered by the user to the server via an HTTP POST request.

[0775] 2. Data processing and storage

[0776] The server stores the received information in a database, using cloud servers such as AWS EC2 and Google Cloud Platform.

[0777] The database used is a relational database such as MySQL or PostgreSQL.

[0778] 3. Menu generation

[0779] The server retrieves information from the database and inputs it into a generative AI model, which can be OpenAI's GPT-4 or Google AI's T5 model.

[0780] Using a generative AI model, we generate a weekly menu with prompts like the following:

[0781] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[0782] For example, on the first day, "teriyaki chicken, stir-fried vegetables, miso soup" will be generated.

[0783] 4. Generate recipes and ingredient lists

[0784] Based on the menu, the server automatically generates a detailed recipe and ingredients list, including ingredient types, quantities, and cutting and measuring options.

[0785] 5. User Interface

[0786] The smartphone app displays the generated menu, recipe, and ingredient list to the user.

[0787] The user can review these and make changes or adjustments as needed.

[0788] 6. Final confirmation and ordering of materials

[0789] Based on the materials list that the user has confirmed and approved, the server automatically places orders with partner suppliers.

[0790] The partner company delivers the materials to the user at the specified date and time and reports the completion of delivery to the server.

[0791] Specific examples

[0792] User A is a family of two adults and one child who is allergic to dairy products. Their preferences are mainly Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[0793] 1. User A enters the necessary information through a smartphone app and sends it to the server.

[0794] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken, stir-fried vegetables, miso soup, etc.").

[0795] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A through a smartphone app.

[0796] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[0797] 5. The partner company delivers the materials to User A's address on the specified date and time and notifies the server that delivery is complete.

[0798] The system allows users to easily prepare healthy meals tailored to their individual needs, and delivers the ingredients, including cutting and measuring, significantly reducing the burden of daily meals.

[0799] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0800] Step 1:

[0801] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0802] The entered information is saved in the smartphone app.

[0803] Step 2:

[0804] The terminal sends the information entered by the user to the server using an HTTP POST request.

[0805] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0806] Output: The user information sent to the server.

[0807] Step 3:

[0808] The server converts the received data into a data format and inserts it into the database in order to store the received information in the database.

[0809] Input: User information.

[0810] Output: User information stored in the database.

[0811] Step 4:

[0812] The server retrieves user information from the database and inputs it as a prompt sentence into the generative AI model.

[0813] For example, to generate the following prompt:

[0814] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[0815] Input: Information stored in the user's database.

[0816] Output: The prompt sentence to be fed into the generative AI model.

[0817] Step 5:

[0818] The generative AI model generates a weekly menu based on the prompt, generating specific dish names and contents in the process.

[0819] Input: prompt statement.

[0820] Output: A week's worth of meals.

[0821] Step 6:

[0822] Based on the generated menu, the server generates the recipes and ingredient lists required for each dish.

[0823] Input: The generated menu.

[0824] Output: Recipe and ingredients list.

[0825] Step 7:

[0826] The device displays the generated menu, recipe, and ingredient list to the user, who can review them and make changes or adjustments as needed.

[0827] Input: Recipe and ingredients list.

[0828] Output: Information that is displayed to the user.

[0829] Step 8:

[0830] The material list that the user has confirmed and approved is sent back to the server from the terminal.

[0831] Input: A list of materials reviewed and approved by the user.

[0832] Output: Final material list sent to the server.

[0833] Step 9:

[0834] The server automatically places orders with partner suppliers based on the confirmed material list, generating order information and sending it to the supplier via an API for receiving orders.

[0835] Input: Finalized materials list.

[0836] Output: Order information sent to partner.

[0837] Step 10:

[0838] The partner company delivers the materials to the user at the specified date and time based on the order details. After the delivery is completed, the partner company notifies the server of the delivery completion information.

[0839] Input: Order information.

[0840] Output: Materials delivered to the user and notification of delivery completion.

[0841] This allows users to receive meals and ingredients tailored to their needs, reducing the burden of daily meal preparation.

[0842] 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.

[0843] In this invention, the user inputs information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc., and the system generates a menu that takes nutritional balance into consideration based on this information. Furthermore, this system aims to increase user satisfaction by combining an emotion engine that recognizes the user's emotions and customizing the menu and ingredient suggestions based on emotions.

[0844] System Operation

[0845] 1. User registration and input

[0846] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[0847] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[0848] 2. Data transmission and storage

[0849] The terminal (user's device) sends the entered data to the server.

[0850] The server stores the received data in a database.

[0851] 3. Menu generation

[0852] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0853] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[0854] 4. Sentiment Analysis and Customization

[0855] The device will activate an emotion engine to recognize the user's emotions. For example, users can input emotion data within the app through facial recognition or voice analysis.

[0856] The server receives the emotion data from the emotion engine and stores it in a database.

[0857] The server analyzes the user's current emotional state based on the emotion data and customizes the menu accordingly. For example, if the user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[0858] 5. Generating recipes and ingredient lists

[0859] The server generates a recipe based on the generated menu and emotional customization, and generates an ingredient list for the recipe, including the type, amount, and cutting and measuring options.

[0860] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[0861] 6. User Verification and Authorization

[0862] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0863] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[0864] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[0865] 7. Customize your ingredients

[0866] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[0867] The terminal transmits the user's selection to the server.

[0868] The server updates the final ingredient list based on the user's selections.

[0869] 8. Final confirmation and automatic delivery

[0870] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[0871] The delivery company delivers the ingredients to the user's address on the specified date and time.

[0872] The server confirms delivery completion and notifies the user.

[0873] Specific examples

[0874] User B is a family of one adult and two children who has a nut allergy. They primarily prefer Western food, have a weekly budget of 15,000 yen, would like three meals a day, and have selected delivery once a week. Furthermore, they have been busy and stressed recently, so they would like a relaxing meal.

[0875] 1. User B enters the required information and sends it to the server.

[0876] 2. The server uses a generative AI model to generate a week's worth of Western-style meals that avoid nuts (e.g., grilled chicken, minestrone soup, fish and chips, etc.).

[0877] 3. The server analyzes User B's emotional data and suggests a menu that includes ingredients that have a relaxing effect.

[0878] 4. The server generates recipes and ingredient lists for these dishes and displays them to User B.

[0879] 5. User B checks the displayed information and confirms that he / she wants delivery on the weekend.

[0880] 6. The delivery company delivers the ingredients to User B's address on the specified date and time and notifies the server that delivery is complete.

[0881] This invention allows users to easily prepare healthy meals tailored to their individual needs and emotional state, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals. Furthermore, by using an emotion engine, it can also address the user's psychological needs.

[0882] The processing flow will be explained below.

[0883] Step 1:

[0884] A user visits an app or website and is prompted to create a new account.

[0885] Step 2:

[0886] The user creates an account by entering the required information, such as name, email address, and password.

[0887] Step 3:

[0888] The terminal transmits the input information to the server.

[0889] Step 4:

[0890] The server stores the received user data in a database.

[0891] Step 5:

[0892] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[0893] Step 6:

[0894] The user enters the required information.

[0895] Step 7:

[0896] The terminal transmits the input data to the server.

[0897] Step 8:

[0898] The server stores the received data in a database.

[0899] Step 9:

[0900] The user launches the emotion engine on the app or website and inputs emotional data through facial expression recognition and voice analysis.

[0901] Step 10:

[0902] The device transmits the emotion data to the server.

[0903] Step 11:

[0904] The server receives the emotion data from the emotion engine and stores it in a database.

[0905] Step 12:

[0906] The server retrieves user information and emotional data from the database and inputs it into the generative AI model.

[0907] Step 13:

[0908] A generative AI model generates a week's worth of menus, taking into account the user's family structure, allergies, preferences, nutritional balance, and emotional state.

[0909] Step 14:

[0910] The server stores the generated menus and recipes in a database.

[0911] Step 15:

[0912] The server generates a list of ingredients based on the generated menu and recipe.

[0913] Step 16:

[0914] The server stores the generated ingredient list in a database.

[0915] Step 17:

[0916] The terminal displays the generated menu, recipes, and ingredient list to the user.

[0917] Step 18:

[0918] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[0919] Step 19:

[0920] The device sends user changes and authorization information to the server.

[0921] Step 20:

[0922] The server updates the final ingredient list based on the changes and approvals received.

[0923] Step 21:

[0924] The user selects cutting and measuring options from the ingredient list.

[0925] Step 22:

[0926] The terminal transmits the selected option information to the server.

[0927] Step 23:

[0928] The server updates the final ingredient list and stores it in the database.

[0929] Step 24:

[0930] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[0931] Step 25:

[0932] The server notifies the user of the order details and delivery schedule.

[0933] Step 26:

[0934] A delivery company delivers the ingredients to the user's address on the specified date and time.

[0935] Step 27:

[0936] The delivery person completes the delivery and sends a confirmation to the server.

[0937] Step 28:

[0938] The server sends a delivery completion notification to the user.

[0939] Example 2

[0940] 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."

[0941] Conventional menu generation systems generate menus based on information such as the user's family structure, allergies, preferences, and budget, but they cannot customize the menu taking into account the user's emotional state, which prevents them from fully increasing user satisfaction. Furthermore, while there is a demand for meal suggestions that are tailored to individual emotional states in addition to nutritional balance, there is a problem in that no system exists that can achieve this.

[0942] 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.

[0943] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency, means for transmitting the input information to the server, means for saving the received information and generating a menu that takes nutritional balance into consideration using a generative AI model, means for generating recipes and a list of necessary ingredients from the generated menu, means for the terminal to activate an emotion engine that recognizes the user's emotions and transmit the emotion data to the server, means for the server to analyze the user's emotional state based on the emotion data and customize the menu, means for displaying the generated menu, recipes, and ingredient list to the user, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering it to the user. This makes it possible to propose individual menus tailored to the user's emotional state.

[0944] "User" refers to an individual who uses the system to create a menu that takes into account their own nutritional balance and receives food delivery.

[0945] A "terminal" is a device through which a user inputs information into a system and views output from the system.

[0946] "Server" refers to the central processing unit that receives the information sent by the user, generates the menu using the generative AI model, and sends the final ingredient list to the supplier.

[0947] A "generative AI model" is an artificial intelligence technology that includes an algorithm that automatically generates menus that take nutritional balance into consideration based on user input information.

[0948] The "emotion engine" is a software component that analyzes the user's emotional state and customizes menus based on that.

[0949] "Menu" refers to a meal combination generated by the system that takes into account nutritional balance.

[0950] A "recipe" is a document that describes the specific cooking steps for creating a menu.

[0951] An "ingredient list" is a table listing the types and quantities of ingredients needed to create a menu or recipe.

[0952] "Delivery company" refers to a company that delivers ingredients to the user based on the final ingredient list generated by the system.

[0953] "Partner" refers to a supplier with which the System partners for the procurement and delivery of ingredients.

[0954] "Customization" refers to modifying or changing menus and recipes based on the user's preferences and emotional state.

[0955] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and the system generates a menu that takes nutritional balance into consideration based on this information, and further enables the system to customize the menu according to the user's emotional state using an emotion engine.

[0956] First, a user accesses an app or website and creates an account by entering information such as their name, email address, and password. Then, they enter detailed information such as family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). This entered information is sent from the terminal (user's device) to the server.

[0957] The server then stores the received user information in a database. This information is stored in the database linked to the user ID. The server retrieves the user information from the database and inputs it into a generative AI model. This generative AI model uses OpenAI's GPT-4 and other technologies to generate a week's worth of menus taking into account allergies, preferences, and nutritional balance. For example, if the user has a nut allergy, the generative AI model will select menus that do not contain nuts.

[0958] The server generates a detailed recipe and ingredient list for each meal. The recipe includes cooking instructions, necessary ingredients, and cooking tools, while the ingredient list includes specific details such as type, amount, and cutting and measuring options. For example, a recipe for "Teriyaki Chicken" might call for 200 grams of chicken, 3 tablespoons of soy sauce, and 2 tablespoons of sugar.

[0959] The device then activates an emotion engine to recognize the user's emotions. This emotion recognition uses the smartphone's camera and microphone to collect emotional data, for example, through facial expression recognition and voice analysis. The server receives this emotional data and stores it in a database. The server analyzes the emotional data and customizes menus taking into account the user's emotional state. For example, if the user is feeling highly stressed, it will suggest menus using ingredients that have stress-reducing effects (e.g., chamomile and avocado).

[0960] The generated menu, recipes, and ingredient list are displayed to the user on the terminal, who can review them and make changes or adjustments as necessary. The user can also give final approval to the delivery schedule and ingredient costs. After approval, the final ingredient list is automatically ordered from the partner supplier by the server. The delivery company delivers the ingredients to the user's address on the specified date and time and notifies the server that delivery is complete. The server confirms that delivery is complete and notifies the user.

[0961] As a specific example, User B is a family of one adult and two children who has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, they would like three meals a day, and they have selected one delivery per week. They have recently been feeling tired and stressed, and are looking for a relaxing meal. User B enters the necessary information and sends it to the server. The server uses a generative AI model to generate a menu that focuses on Western food but avoids nuts. Dishes such as "grilled chicken," "minestrone soup," and "fish and chips" are suggested. Furthermore, emotional data is analyzed to customize the menu, including ingredients with a relaxing effect.

[0962] Based on the generated recipe and ingredient list, User B checks the menu, makes any necessary adjustments, and then approves the weekend delivery. The ingredients are delivered at the specified date and time, and the user then confirms that the delivery has been completed. This system allows users to easily prepare meals that suit their own health and emotional state.

[0963] Example prompt sentence:

[0964] The user's family consists of one adult and two children, and the user has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, and they would like three meals a day. They are feeling a bit tired and stressed, and would like to eat meals that will help them relax. Please generate a week's worth of menus based on these conditions.

[0965] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0966] Step 1:

[0967] Users access the app or website and create an account by entering information such as their name, email address, and password. Next, they enter detailed information such as their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget, and delivery frequency.

[0968] Input: Name, email address, password, family composition, allergies, preferences, cooking frequency, budget, delivery frequency.

[0969] Output: Input information is sent from the device to the server.

[0970] Step 2:

[0971] The terminal transmits the input information to the server.

[0972] The server stores the received user information in a database, where the information is linked to the user ID.

[0973] Input: User information.

[0974] Output: The user information is saved in the database.

[0975] Step 3:

[0976] The server retrieves user information from the database and inputs it as prompts into the generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[0977] Input: A prompt such as, "The user's family consists of one adult and two children, and they have a nut allergy. Their preferences are primarily Western food, their budget is 15,000 yen per week, and they would like three meals a day."

[0978] Output: Generated weekly menu.

[0979] Step 4:

[0980] The server generates a detailed recipe and ingredients list based on the generated menu. The recipe includes cooking steps, required ingredients, and cooking tools, while the ingredients list includes types, amounts, and options for cutting and measuring.

[0981] Input: The generated menu.

[0982] Output: Recipe and ingredients list.

[0983] Step 5:

[0984] The device activates an emotion engine to recognize the user's emotions, collects emotion data through facial recognition and voice analysis, and sends it to the server.

[0985] Input: User's emotional expression (facial expression and voice).

[0986] Output: Emotion data.

[0987] Step 6:

[0988] The server receives the emotion data from the emotion engine and stores it in a database. Then, it analyzes the emotion data and customizes the menu based on the user's emotional state, thereby proposing a final menu that reflects the user's emotional state.

[0989] Input: Emotion data.

[0990] Output: Final menu reflecting emotional state.

[0991] Step 7:

[0992] The device displays the final menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[0993] Input: Final menu, recipe, and ingredient list.

[0994] Output: Information that the user reviews, modifies, and approves.

[0995] Step 8:

[0996] The user reviews the final menu and ingredient list and approves the delivery schedule and ingredient costs.

[0997] Input: Review and approve final menus, recipes and ingredient lists.

[0998] Output: Approved ingredient list.

[0999] Step 9:

[1000] The server automatically places orders with partner suppliers based on the final approved ingredient list.

[1001] Input: Approved ingredient list.

[1002] Output: Ingredients are ordered from partner suppliers.

[1003] Step 10:

[1004] The delivery company will deliver the ingredients to the user's address on the specified date and time.

[1005] The server confirms delivery completion and notifies the user.

[1006] Input: Order information and delivery instructions.

[1007] Output: Notification of delivery of ingredients and completion of delivery.

[1008] In this way, the system can easily provide a customized menu based on the user's individual needs and emotional state, along with the ingredients needed to make that menu.

[1009] (Application example 2)

[1010] 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."

[1011] Current nutritionally balanced menu suggestion and food delivery systems can generate menus based on user information, but they have the problem of not being able to customize suggestions that take the user's emotional state into account. This results in a problem of not being able to sufficiently increase user satisfaction. Furthermore, while there is a demand for systems that users can operate intuitively, conventional systems lack such operability. Therefore, there is a need for a system that can recognize and analyze the user's emotional state and customize menus based on that information to make suggestions that more closely meet individual needs.

[1012] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model to generate a menu based on the user's information and emotional state, means for analyzing the user's emotional state and customizing the menu based on this, and means for displaying the generated menu, recipe, and ingredient list to the user. This makes it possible to propose a menu that is adapted to the user's individual needs and emotional state.

[1013] The "user information input means" is a means by which a user inputs information such as family composition, allergies, preferences, number of times cooked, budget, and delivery frequency.

[1014] The "information transmission means" is a means for transmitting input information to a server.

[1015] The "information storage means" is a means for storing information received by the server.

[1016] The "menu generation means" is a means for generating a menu based on input information and emotional state, taking into consideration nutritional balance.

[1017] "Means for using a generative AI model" refers to means for using a generative AI model to generate a menu based on the user's information and emotional state.

[1018] The "recipe generation means" is a means for generating a recipe and a list of necessary ingredients from the generated menu.

[1019] The "information display means" is a means for displaying the generated menu, recipes, and ingredient list to the user.

[1020] "Means for confirmation, change and approval" refers to the means by which users can confirm, change and approve.

[1021] The "automatic ordering means" is a means for automatically placing orders with partner suppliers based on the confirmed ingredient list.

[1022] The "emotional state analysis means" is a means for analyzing the user's emotional state and customizing a menu based on this.

[1023] This invention relates to a system that proposes nutritionally balanced meals for users and automates the delivery of ingredients. In particular, it customizes the meals taking into account the user's emotional state. This system operates by allowing users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency using a smartphone app.

[1024] Enter and submit user information

[1025] First, the user accesses the smartphone app and enters the necessary information. This information includes family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). The entered information is sent from the smartphone device to the server.

[1026] Save information and generate menus

[1027] The server stores the information sent by the user in a database. The information stored in the database is used to generate nutritionally balanced menus using a "generative AI model." This generative AI model receives information such as the user's family composition, allergies, and preferences as input and generates a weekly menu. The generated menu also includes recipes and a list of necessary ingredients.

[1028] Sentiment analysis and menu customization

[1029] The user's emotional state is recognized using the smartphone's camera and microphone. Specifically, the system uses technologies such as the emotion recognition library "DeepFace" to analyze facial expressions and voice to identify the user's emotional state. The server then customizes the menu based on this emotional data. For example, if the user is excited, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1030] Menu display and user confirmation

[1031] The server displays the generated menu, recipes, and ingredient list on the user's smartphone. The user can check the displayed information and make changes or approvals as necessary. After the ingredient list is confirmed, an order is automatically placed with a partner delivery company, and the ingredients are delivered to the user's address at the specified date and time.

[1032] Hardware and software used

[1033] Hardware: Smartphones, servers

[1034] Software: Emotion recognition library "DeepFace", generative AI model "TensorFlow"

[1035] Specific examples

[1036] For example, assume that User A has a family of one adult and two children, a nut allergy, a preference for Western food, a weekly budget of 15,000 yen, desires three meals a day, and selects delivery once a week. Assume that User A has been feeling stressed recently and desires a relaxing meal.

[1037] An example of a prompt sentence could be, "An excited user has a family of one adult and two children, has a nut allergy, and has a weekly budget of 15,000 yen. He wants suggestions for a week's worth of menus, mainly Western food."

[1038] In this way, the system can offer customized meal suggestions based on individual needs and emotional state.

[1039] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1040] Step 1:

[1041] Entering user information

[1042] Using a smartphone app, users input necessary information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc. The input information is then saved on the smartphone device.

[1043] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc.

[1044] Output: The smartphone device is now ready to send this information to the server.

[1045] Step 2:

[1046] Sending and storing information

[1047] The smartphone device sends the entered information to a server, which stores the received information in a database, thereby building a user profile.

[1048] Input: User information from the smartphone device.

[1049] Output: User information stored in the database.

[1050] Step 3:

[1051] Menu generation

[1052] The server retrieves user information from the database and inputs it into a generative AI model, which then takes into account family composition, allergies, preferences, and other factors to generate a week's worth of nutritionally balanced menus.

[1053] Input: User profile data.

[1054] Output: Generated weekly menu.

[1055] Step 4:

[1056] Emotion analysis

[1057] The user inputs their emotional state using a smartphone app. The device uses a camera and microphone to analyze facial expressions and voice, and an emotion recognition library (e.g., "DeepFace") identifies the user's emotion. The results are sent to a server.

[1058] Input: User's facial and voice data.

[1059] Output: Emotion data stored by the server.

[1060] Step 5:

[1061] Emotion-based customization

[1062] The server customizes the generated menu based on the emotional data. For example, if a user is feeling stressed, it will suggest a menu that includes ingredients that have a relaxing effect.

[1063] Input: Emotion data, generated menu.

[1064] Output: A customized menu.

[1065] Step 6:

[1066] Menu and ingredient list generation

[1067] The server generates a detailed recipe and ingredient list based on the customized meal plan, including ingredient types, quantities, and cutting and measuring options.

[1068] Input: Your customized menu.

[1069] Output: Recipe and ingredients list.

[1070] Step 7:

[1071] User Verification and Authorization

[1072] The generated menu, recipes, and ingredient list are displayed on the user's smartphone. The user can review them and make changes or approvals as necessary. Finally, they can confirm the delivery date and ingredient costs.

[1073] Input: Customized menus, recipes, and ingredient lists.

[1074] Output: User approval.

[1075] Step 8:

[1076] Food ordering and delivery

[1077] The server automatically places an order with a partner supplier based on the ingredient list confirmed by the user, and the partner supplier delivers the ingredients to the user's address on the specified date and time.

[1078] Input: Finalized ingredient list.

[1079] Output: Order confirmation and delivery of ingredients.

[1080] The above is the flow of specific processing steps for implementing the invention.

[1081] 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.

[1082] 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.

[1083] 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.

[1084] [Third embodiment]

[1085] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1086] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1087] 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).

[1088] 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.

[1089] 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.

[1090] 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).

[1091] 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. 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.

[1092] 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.

[1093] 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.

[1094] 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.

[1095] 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.

[1096] 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."

[1097] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves the ingredients, automatically orders the ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[1098] System Operation

[1099] 1. User registration and input

[1100] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[1101] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[1102] 2. Data transmission and storage

[1103] The terminal (user's device) sends the entered data to the server.

[1104] The server stores the received data in a database.

[1105] 3. Menu generation

[1106] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[1107] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[1108] 4. Generate recipes and ingredient lists

[1109] The server generates a recipe based on the generated menu and generates a list of ingredients required for the recipe, including type, amount, and cutting and measuring options.

[1110] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[1111] 5. User Verification and Authorization

[1112] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1113] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[1114] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[1115] 6. Customize your ingredients

[1116] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[1117] The terminal transmits the user's selection to the server.

[1118] The server updates the final ingredient list based on the user's selections.

[1119] 7. Final confirmation and automatic delivery

[1120] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[1121] The delivery company delivers the ingredients to the user's address on the specified date and time.

[1122] The server confirms delivery completion and notifies the user.

[1123] Specific examples

[1124] User A is a family of two adults and one child who has a dairy allergy. Their preferences are primarily Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[1125] 1. User A enters the required information and sends it to the server.

[1126] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken," "stir-fried vegetables," "grilled salted fish," etc.).

[1127] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A.

[1128] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[1129] 5. The delivery company delivers the ingredients to User A's address on the specified date and time and notifies the server that delivery is complete.

[1130] The present invention allows users to easily prepare healthy meals tailored to their individual needs, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals.

[1131] The processing flow will be explained below.

[1132] Step 1:

[1133] A user visits an app or website and is prompted to create a new account.

[1134] Step 2:

[1135] The user creates an account by entering the required information, such as name, email address, and password.

[1136] Step 3:

[1137] The terminal transmits the input information to the server.

[1138] Step 4:

[1139] The server stores the received user data in a database.

[1140] Step 5:

[1141] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1142] Step 6:

[1143] The user enters the required information.

[1144] Step 7:

[1145] The terminal transmits the input data to the server.

[1146] Step 8:

[1147] The server stores the received data in a database.

[1148] Step 9:

[1149] The server retrieves the user's information from a database and inputs it into a generative AI model.

[1150] Step 10:

[1151] The generative AI model generates a week's worth of menus taking into account the user's family composition, allergies, preferences, and nutritional balance.

[1152] Step 11:

[1153] The server stores the generated menus and recipes in a database.

[1154] Step 12:

[1155] The server generates a list of ingredients needed based on the saved menu and recipes.

[1156] Step 13:

[1157] The server stores the generated ingredient list in a database.

[1158] Step 14:

[1159] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1160] Step 15:

[1161] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[1162] Step 16:

[1163] The device sends user changes and authorization information to the server.

[1164] Step 17:

[1165] The server updates the final ingredient list based on the changes and approvals received.

[1166] Step 18:

[1167] The user selects cutting and measuring options from the ingredient list.

[1168] Step 19:

[1169] The terminal transmits the selected option information to the server.

[1170] Step 20:

[1171] The server updates the final ingredient list and stores it in the database.

[1172] Step 21:

[1173] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[1174] Step 22:

[1175] The server notifies the user of the order details and delivery schedule.

[1176] Step 23:

[1177] A delivery company delivers the ingredients to the user's address on the specified date and time.

[1178] Step 24:

[1179] The delivery person completes the delivery and sends a confirmation to the server.

[1180] Step 25:

[1181] The server sends a delivery completion notification to the user.

[1182] Example 1

[1183] 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."

[1184] In today's busy lifestyles, it is difficult for users to prepare nutritionally balanced meals every day. Purchasing optimal ingredients and planning meals according to each household's allergies, preferences, budget, etc. takes time and effort. Furthermore, selecting ingredients and adjusting recipes is time-consuming and requires efficient operation. However, conventional systems have not been able to solve these issues in a unified manner.

[1185] 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.

[1186] In this invention, the server includes: means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency; means for transmitting the input information to the server; means for the server to store the received information and generate a menu that takes nutritional balance into consideration using a generative AI model; means for generating recipes and a list of necessary ingredients from the generated menu; means for displaying the generated menu, recipes, and ingredient list to the user; means for the user to confirm, change, and approve; means for the user to select cutting and measuring options based on the ingredient list; and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This enables users to efficiently plan nutritionally balanced meals that meet their individual needs and easily procure the necessary ingredients.

[1187] "User" refers to an individual or household who uses the system to input information and receive menu and recipe suggestions.

[1188] "Family composition" refers to information such as the number of people in the user's household and their ages, and is a factor that influences the creation of menus.

[1189] "Allergies" refer to hypersensitivity reactions that a user or their family members have to certain foods or ingredients, and are important information that is taken into consideration when generating menus.

[1190] "Preferences" refers to personal preferences such as favorite dishes and disliked ingredients of the user and their family.

[1191] "Number of times cooked" refers to the number of meals a user eats per day, and is important data for menu planning.

[1192] "Budget" refers to the amount of money a user allocates for food on a weekly or monthly basis.

[1193] "Delivery frequency" refers to how often a user wants food delivered (e.g., once a week, twice a month, etc.).

[1194] "Server" refers to the central computing device that receives and stores information submitted by users and generates menus, recipes, and ingredient lists using generative AI models.

[1195] A "generative AI model" refers to an artificial intelligence model that automatically generates menus that take into account nutritional balance, allergies, and preferences based on information input by the user.

[1196] A "menu" refers to a combination of multiple meal menus suggested by a generative AI model.

[1197] "Recipe" refers to detailed instructions on how to prepare each dish on a menu.

[1198] "Ingredient List" refers to a list of ingredients required based on a recipe, including their type, quantity, and options for cutting and measuring.

[1199] "Partner" refers to a company or organization that provides and delivers ingredients specified by the user.

[1200] "Delivery method" refers to the method for automatically placing an order with partner suppliers based on the confirmed ingredient list and delivering the ingredients to the user.

[1201] "Cutting and measuring options" refers to a customization function that allows users to select the shape, size, and quantity of ingredients according to their preferences.

[1202] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and a server generates nutritionally balanced menus based on that information. The system automatically generates recipes and lists of ingredients and provides them to the user. The user can then confirm, change, and approve the displayed information, order ingredients from affiliated suppliers, and have them delivered.

[1203] First, a user creates an account on a website or application. At this time, the user enters basic information such as name, email address, and password. Then, the user enters family composition (number of people, age, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.).

[1204] The information entered by the user is sent from the device to the server. Specifically, the device's application or web browser passes the data to the server via an HTML form or API. This data is parsed in JSON format or similar, and the server stores it in a database.

[1205] The server retrieves the stored information and inputs it into a generative AI model. This generative AI model automatically generates a week's worth of menus, taking into account the user's allergies, preferences, and nutritional balance. The generative AI model is built using a machine learning algorithm written in Python, for example. An example of a specific prompt is, "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[1206] Based on the generated menu, the server generates a recipe for each dish and a list of ingredients. The recipe includes detailed instructions on cooking steps, timing, and necessary cooking equipment. The ingredient list includes the type, amount, and cutting and measuring options of the ingredients, allowing the user to clearly see which ingredients they need to purchase.

[1207] The generated menu, recipe, and ingredient list are displayed to the user via the terminal. The user can review them and make changes or adjustments as needed. For example, if a specific dish needs to be replaced with another, it can be easily replaced in the system. The user can also select cutting and measuring options based on the ingredient list. For example, detailed selections such as "thinly slice the carrots and finely chop the onions" are possible.

[1208] The final ingredient list and delivery date are automatically sent from the server to the partner supplier's system. Data is exchanged using protocols such as APIs. The partner supplier delivers the ingredients to the user's address on the specified date and time, and is notified once delivery is complete. The server then confirms delivery completion and notifies the user.

[1209] This series of processes allows users to easily plan nutritionally balanced meals tailored to their individual needs and efficiently source the necessary ingredients. Furthermore, by providing options for cutting and measuring ingredients, the system significantly reduces the time and effort required for daily meal preparation.

[1210] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1211] Step 1:

[1212] User enters information

[1213] Subject: User

[1214] How it works: The user enters information such as family size, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1215] Input: Various information provided by the user (family composition, allergy information, preferences, cooking frequency, budget, delivery frequency).

[1216] Output: The entered information is temporarily stored on the device.

[1217] What happens: The user fills out a web form or app screen with this information and clicks the "Submit" button.

[1218] Step 2:

[1219] Data transmission

[1220] Subject: Terminal

[1221] Operation: The device sends the entered information to the server.

[1222] Input: The information the user entered in step 1.

[1223] Output: JSON formatted data sent to the server.

[1224] What it does: Data is securely transmitted to the server using the HTTPS protocol.

[1225] Step 3:

[1226] Data storage

[1227] Subject: Server

[1228] What it does: The server stores the received information in a database.

[1229] Input: JSON format data sent from the terminal.

[1230] Output: User information stored in the database.

[1231] What happens: The server parses the received data and stores it in a database in the appropriate format. For example, it stores information by user ID and assigns an index to it.

[1232] Step 4:

[1233] Menu generation

[1234] Subject: Server

[1235] How it works: The server retrieves the user's information from a database and inputs it into a generative AI model.

[1236] Input: User information stored in the database.

[1237] Output: A week's worth of meal plans generated by the AI ​​model.

[1238] Specific operation: The server sends a specific prompt to the generation AI model, and the AI ​​generates a menu. Example prompt: "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[1239] Step 5:

[1240] Recipe and ingredient list generation

[1241] Subject: Server

[1242] How it works: The server generates a recipe and a list of ingredients based on the menu.

[1243] Input: Generated menu data.

[1244] Output: Detailed recipe and ingredient list for each dish.

[1245] What it does: The server retrieves details of each dish from the recipe database and generates a list containing the required ingredients, their quantities, and cutting and measuring options.

[1246] Step 6:

[1247] User confirmation and changes

[1248] Subject: Terminal, User

[1249] What it does: The device displays the generated menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[1250] Input: Menu, recipe, and ingredient list provided by the server.

[1251] Output: The final menu and ingredients list, as reviewed and modified by the user.

[1252] Specific operation: The user checks the menu on the device and presses the change button if they want to make changes. The changes are sent to the server in real time.

[1253] Step 7:

[1254] Cutting and weighing options

[1255] Subject: User, Device

[1256] Action: User selects cutting and measuring options based on an ingredient list.

[1257] Input: Ingredient list and its customization options.

[1258] Output: A final customized ingredient list.

[1259] Specific operation: The user selects an option such as "slice carrots" or "chop onions," and the device sends that information to the server.

[1260] Step 8:

[1261] Final confirmation and order

[1262] Subject: Server

[1263] How it works: The server checks the final ingredient list and delivery schedule, and automatically places an order with partner suppliers.

[1264] Input: Finalized ingredient list and delivery date information.

[1265] Output: Purchase order information sent to partner.

[1266] Specific operation: The server uses the API to send order data to the partner's system.

[1267] Step 9:

[1268] Delivery and completion notification

[1269] Subject: Delivery company, server

[1270] How it works: The delivery company delivers the groceries to the user's address at the specified date and time and notifies the server that delivery is complete.

[1271] Input: Order information received by the delivery company.

[1272] Output: Delivery of ingredients and notification of delivery completion.

[1273] Specific operation: The delivery person delivers the food and sends a completion notification to the server after the delivery is complete. The server receives the completion notification and notifies the user that the delivery is complete.

[1274] (Application example 1)

[1275] 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."

[1276] In today's busy society, it is difficult to plan a nutritionally balanced menu, procure the necessary ingredients based on that menu, and measure them in the appropriate amounts. Furthermore, there is a lack of automated methods for preparing meals that take into consideration allergies and preferences. Therefore, there is a need for a system that provides optimal ingredients and recipes for each individual user.

[1277] 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.

[1278] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking is done, budget, and delivery frequency, means for transmitting the input information to the server, means for the server to store the received information and generate a menu using a generative AI model taking nutritional balance into consideration, means for generating recipes and a list of necessary ingredients from the generated menu, means for displaying the generated menu, recipes, and ingredient list on a display terminal, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This makes it possible to easily prepare healthy meals that meet the individual needs of the user.

[1279] "User" refers to a person who uses a service or system.

[1280] "Family composition" refers to information such as the number of people in a household and their ages.

[1281] "Allergy" refers to an immune response to a specific food or substance.

[1282] "Preferences" refers to the ingredients and types of food that one likes or dislikes.

[1283] "Cooking frequency" refers to the frequency of cooking per day or per week.

[1284] A "budget" refers to the total amount of money you can spend on ingredients and dishes.

[1285] "Delivery frequency" refers to the number of times or frequency at which food ingredients are delivered.

[1286] "Means" refers to a method or device for achieving a particular purpose.

[1287] "Server" refers to a computer system for storing and processing data.

[1288] "Means for inputting information" refers to a device or interface that allows a user to input information.

[1289] "Means for sending to server" refers to a method for transferring input information to the server.

[1290] "Nutritional balance" refers to the appropriate distribution of various nutrients that people need.

[1291] A "generative AI model" is an algorithm that uses artificial intelligence to generate results based on specified conditions.

[1292] A "menu" refers to a plan or list of dishes for a certain period of time.

[1293] A "recipe" is a document that details how to make a dish, the steps involved, and the ingredients needed.

[1294] An "ingredient list" refers to a list of ingredients and equipment needed based on a recipe.

[1295] "Display terminal" refers to a device for displaying information (smartphone, tablet, PC, etc.).

[1296] "Means for review, modification, and approval" refers to the interface or process by which a user can review the displayed information, modify it if necessary, and ultimately approve it.

[1297] "Affiliate companies" refer to companies that work in conjunction with the system to supply and deliver ingredients.

[1298] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves it, automatically orders ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[1299] System Configuration

[1300] 1. Enter and submit user information

[1301] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1302] The app sends the information entered by the user to the server via an HTTP POST request.

[1303] 2. Data processing and storage

[1304] The server stores the received information in a database, using cloud servers such as AWS EC2 and Google Cloud Platform.

[1305] The database used is a relational database such as MySQL or PostgreSQL.

[1306] 3. Menu generation

[1307] The server retrieves information from the database and inputs it into a generative AI model, which can be OpenAI's GPT-4 or Google AI's T5 model.

[1308] Using a generative AI model, we generate a weekly menu with prompts like the following:

[1309] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[1310] For example, on the first day, "teriyaki chicken, stir-fried vegetables, miso soup" will be generated.

[1311] 4. Generate recipes and ingredient lists

[1312] Based on the menu, the server automatically generates a detailed recipe and ingredients list, including ingredient types, quantities, and cutting and measuring options.

[1313] 5. User Interface

[1314] The smartphone app displays the generated menu, recipe, and ingredient list to the user.

[1315] The user can review these and make changes or adjustments as needed.

[1316] 6. Final confirmation and ordering of materials

[1317] Based on the materials list that the user has confirmed and approved, the server automatically places orders with partner suppliers.

[1318] The partner company delivers the materials to the user at the specified date and time and reports the completion of delivery to the server.

[1319] Specific examples

[1320] User A is a family of two adults and one child who is allergic to dairy products. Their preferences are mainly Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[1321] 1. User A enters the necessary information through a smartphone app and sends it to the server.

[1322] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken, stir-fried vegetables, miso soup, etc.").

[1323] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A through a smartphone app.

[1324] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[1325] 5. The partner company delivers the materials to User A's address on the specified date and time and notifies the server that delivery is complete.

[1326] The system allows users to easily prepare healthy meals tailored to their individual needs, and delivers the ingredients, including cutting and measuring, significantly reducing the burden of daily meals.

[1327] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1328] Step 1:

[1329] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1330] The entered information is saved in the smartphone app.

[1331] Step 2:

[1332] The terminal sends the information entered by the user to the server using an HTTP POST request.

[1333] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1334] Output: The user information sent to the server.

[1335] Step 3:

[1336] The server converts the received data into a data format and inserts it into the database in order to store the received information in the database.

[1337] Input: User information.

[1338] Output: User information stored in the database.

[1339] Step 4:

[1340] The server retrieves user information from the database and inputs it as a prompt sentence into the generative AI model.

[1341] For example, to generate the following prompt:

[1342] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[1343] Input: Information stored in the user's database.

[1344] Output: The prompt sentence to be fed into the generative AI model.

[1345] Step 5:

[1346] The generative AI model generates a weekly menu based on the prompt, generating specific dish names and contents in the process.

[1347] Input: prompt statement.

[1348] Output: A week's worth of meals.

[1349] Step 6:

[1350] Based on the generated menu, the server generates the recipes and ingredient lists required for each dish.

[1351] Input: The generated menu.

[1352] Output: Recipe and ingredients list.

[1353] Step 7:

[1354] The device displays the generated menu, recipe, and ingredient list to the user, who can review them and make changes or adjustments as needed.

[1355] Input: Recipe and ingredients list.

[1356] Output: Information that is displayed to the user.

[1357] Step 8:

[1358] The material list that the user has confirmed and approved is sent back to the server from the terminal.

[1359] Input: A list of materials reviewed and approved by the user.

[1360] Output: Final material list sent to the server.

[1361] Step 9:

[1362] The server automatically places orders with partner suppliers based on the confirmed material list, generating order information and sending it to the supplier via an API for receiving orders.

[1363] Input: Finalized materials list.

[1364] Output: Order information sent to partner.

[1365] Step 10:

[1366] The partner company delivers the materials to the user at the specified date and time based on the order details. After the delivery is completed, the partner company notifies the server of the delivery completion information.

[1367] Input: Order information.

[1368] Output: Materials delivered to the user and notification of delivery completion.

[1369] This allows users to receive meals and ingredients tailored to their needs, reducing the burden of daily meal preparation.

[1370] 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.

[1371] In this invention, the user inputs information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc., and the system generates a menu that takes nutritional balance into consideration based on this information. Furthermore, this system aims to increase user satisfaction by combining an emotion engine that recognizes the user's emotions and customizing the menu and ingredient suggestions based on emotions.

[1372] System Operation

[1373] 1. User registration and input

[1374] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[1375] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[1376] 2. Data transmission and storage

[1377] The terminal (user's device) sends the entered data to the server.

[1378] The server stores the received data in a database.

[1379] 3. Menu generation

[1380] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[1381] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[1382] 4. Sentiment Analysis and Customization

[1383] The device will activate an emotion engine to recognize the user's emotions. For example, users can input emotion data within the app through facial recognition or voice analysis.

[1384] The server receives the emotion data from the emotion engine and stores it in a database.

[1385] The server analyzes the user's current emotional state based on the emotion data and customizes the menu accordingly. For example, if the user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1386] 5. Generating recipes and ingredient lists

[1387] The server generates a recipe based on the generated menu and emotional customization, and generates an ingredient list for the recipe, including the type, amount, and cutting and measuring options.

[1388] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[1389] 6. User Verification and Authorization

[1390] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1391] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[1392] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[1393] 7. Customize your ingredients

[1394] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[1395] The terminal transmits the user's selection to the server.

[1396] The server updates the final ingredient list based on the user's selections.

[1397] 8. Final confirmation and automatic delivery

[1398] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[1399] The delivery company delivers the ingredients to the user's address on the specified date and time.

[1400] The server confirms delivery completion and notifies the user.

[1401] Specific examples

[1402] User B is a family of one adult and two children who has a nut allergy. They primarily prefer Western food, have a weekly budget of 15,000 yen, would like three meals a day, and have selected delivery once a week. Furthermore, they have been busy and stressed recently, so they would like a relaxing meal.

[1403] 1. User B enters the required information and sends it to the server.

[1404] 2. The server uses a generative AI model to generate a week's worth of Western-style meals that avoid nuts (e.g., grilled chicken, minestrone soup, fish and chips, etc.).

[1405] 3. The server analyzes User B's emotional data and suggests a menu that includes ingredients that have a relaxing effect.

[1406] 4. The server generates recipes and ingredient lists for these dishes and displays them to User B.

[1407] 5. User B checks the displayed information and confirms that he / she wants delivery on the weekend.

[1408] 6. The delivery company delivers the ingredients to User B's address on the specified date and time and notifies the server that delivery is complete.

[1409] This invention allows users to easily prepare healthy meals tailored to their individual needs and emotional state, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals. Furthermore, by using an emotion engine, it can also address the user's psychological needs.

[1410] The processing flow will be explained below.

[1411] Step 1:

[1412] A user visits an app or website and is prompted to create a new account.

[1413] Step 2:

[1414] The user creates an account by entering the required information, such as name, email address, and password.

[1415] Step 3:

[1416] The terminal transmits the input information to the server.

[1417] Step 4:

[1418] The server stores the received user data in a database.

[1419] Step 5:

[1420] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1421] Step 6:

[1422] The user enters the required information.

[1423] Step 7:

[1424] The terminal transmits the input data to the server.

[1425] Step 8:

[1426] The server stores the received data in a database.

[1427] Step 9:

[1428] The user launches the emotion engine on the app or website and inputs emotional data through facial expression recognition and voice analysis.

[1429] Step 10:

[1430] The device transmits the emotion data to the server.

[1431] Step 11:

[1432] The server receives the emotion data from the emotion engine and stores it in a database.

[1433] Step 12:

[1434] The server retrieves user information and emotional data from the database and inputs it into the generative AI model.

[1435] Step 13:

[1436] A generative AI model generates a week's worth of menus, taking into account the user's family structure, allergies, preferences, nutritional balance, and emotional state.

[1437] Step 14:

[1438] The server stores the generated menus and recipes in a database.

[1439] Step 15:

[1440] The server generates a list of ingredients based on the generated menu and recipe.

[1441] Step 16:

[1442] The server stores the generated ingredient list in a database.

[1443] Step 17:

[1444] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1445] Step 18:

[1446] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[1447] Step 19:

[1448] The device sends user changes and authorization information to the server.

[1449] Step 20:

[1450] The server updates the final ingredient list based on the changes and approvals received.

[1451] Step 21:

[1452] The user selects cutting and measuring options from the ingredient list.

[1453] Step 22:

[1454] The terminal transmits the selected option information to the server.

[1455] Step 23:

[1456] The server updates the final ingredient list and stores it in the database.

[1457] Step 24:

[1458] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[1459] Step 25:

[1460] The server notifies the user of the order details and delivery schedule.

[1461] Step 26:

[1462] A delivery company delivers the ingredients to the user's address on the specified date and time.

[1463] Step 27:

[1464] The delivery person completes the delivery and sends a confirmation to the server.

[1465] Step 28:

[1466] The server sends a delivery completion notification to the user.

[1467] Example 2

[1468] 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."

[1469] Conventional menu generation systems generate menus based on information such as the user's family structure, allergies, preferences, and budget, but they cannot customize the menu taking into account the user's emotional state, which prevents them from fully increasing user satisfaction. Furthermore, while there is a demand for meal suggestions that are tailored to individual emotional states in addition to nutritional balance, there is a problem in that no system exists that can achieve this.

[1470] 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.

[1471] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency, means for transmitting the input information to the server, means for saving the received information and generating a menu that takes nutritional balance into consideration using a generative AI model, means for generating recipes and a list of necessary ingredients from the generated menu, means for the terminal to activate an emotion engine that recognizes the user's emotions and transmit the emotion data to the server, means for the server to analyze the user's emotional state based on the emotion data and customize the menu, means for displaying the generated menu, recipes, and ingredient list to the user, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering it to the user. This makes it possible to propose individual menus tailored to the user's emotional state.

[1472] "User" refers to an individual who uses the system to create a menu that takes into account their own nutritional balance and receives food delivery.

[1473] A "terminal" is a device through which a user inputs information into a system and views output from the system.

[1474] "Server" refers to the central processing unit that receives the information sent by the user, generates the menu using the generative AI model, and sends the final ingredient list to the supplier.

[1475] A "generative AI model" is an artificial intelligence technology that includes an algorithm that automatically generates menus that take nutritional balance into consideration based on user input information.

[1476] The "emotion engine" is a software component that analyzes the user's emotional state and customizes menus based on that.

[1477] "Menu" refers to a meal combination generated by the system that takes into account nutritional balance.

[1478] A "recipe" is a document that describes the specific cooking steps for creating a menu.

[1479] An "ingredient list" is a table listing the types and quantities of ingredients needed to create a menu or recipe.

[1480] "Delivery company" refers to a company that delivers ingredients to the user based on the final ingredient list generated by the system.

[1481] "Partner" refers to a supplier with which the System partners for the procurement and delivery of ingredients.

[1482] "Customization" refers to modifying or changing menus and recipes based on the user's preferences and emotional state.

[1483] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and the system generates a menu that takes nutritional balance into consideration based on this information, and further enables the system to customize the menu according to the user's emotional state using an emotion engine.

[1484] First, a user accesses an app or website and creates an account by entering information such as their name, email address, and password. Then, they enter detailed information such as family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). This entered information is sent from the terminal (user's device) to the server.

[1485] The server then stores the received user information in a database. This information is stored in the database linked to the user ID. The server retrieves the user information from the database and inputs it into a generative AI model. This generative AI model uses OpenAI's GPT-4 and other technologies to generate a week's worth of menus taking into account allergies, preferences, and nutritional balance. For example, if the user has a nut allergy, the generative AI model will select menus that do not contain nuts.

[1486] The server generates a detailed recipe and ingredient list for each meal. The recipe includes cooking instructions, necessary ingredients, and cooking tools, while the ingredient list includes specific details such as type, amount, and cutting and measuring options. For example, a recipe for "Teriyaki Chicken" might call for 200 grams of chicken, 3 tablespoons of soy sauce, and 2 tablespoons of sugar.

[1487] The device then activates an emotion engine to recognize the user's emotions. This emotion recognition uses the smartphone's camera and microphone to collect emotional data, for example, through facial expression recognition and voice analysis. The server receives this emotional data and stores it in a database. The server analyzes the emotional data and customizes menus taking into account the user's emotional state. For example, if the user is feeling highly stressed, it will suggest menus using ingredients that have stress-reducing effects (e.g., chamomile and avocado).

[1488] The generated menu, recipes, and ingredient list are displayed to the user on the terminal, who can review them and make changes or adjustments as necessary. The user can also give final approval to the delivery schedule and ingredient costs. After approval, the final ingredient list is automatically ordered from the partner supplier by the server. The delivery company delivers the ingredients to the user's address on the specified date and time and notifies the server that delivery is complete. The server confirms that delivery is complete and notifies the user.

[1489] As a specific example, User B is a family of one adult and two children who has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, they would like three meals a day, and they have selected one delivery per week. They have recently been feeling tired and stressed, and are looking for a relaxing meal. User B enters the necessary information and sends it to the server. The server uses a generative AI model to generate a menu that focuses on Western food but avoids nuts. Dishes such as "grilled chicken," "minestrone soup," and "fish and chips" are suggested. Furthermore, emotional data is analyzed to customize the menu, including ingredients with a relaxing effect.

[1490] Based on the generated recipe and ingredient list, User B checks the menu, makes any necessary adjustments, and then approves the weekend delivery. The ingredients are delivered at the specified date and time, and the user then confirms that the delivery has been completed. This system allows users to easily prepare meals that suit their own health and emotional state.

[1491] Example prompt sentence:

[1492] The user's family consists of one adult and two children, and the user has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, and they would like three meals a day. They are feeling a bit tired and stressed, and would like to eat meals that will help them relax. Please generate a week's worth of menus based on these conditions.

[1493] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1494] Step 1:

[1495] Users access the app or website and create an account by entering information such as their name, email address, and password. Next, they enter detailed information such as their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget, and delivery frequency.

[1496] Input: Name, email address, password, family composition, allergies, preferences, cooking frequency, budget, delivery frequency.

[1497] Output: Input information is sent from the device to the server.

[1498] Step 2:

[1499] The terminal transmits the input information to the server.

[1500] The server stores the received user information in a database, where the information is linked to the user ID.

[1501] Input: User information.

[1502] Output: The user information is saved in the database.

[1503] Step 3:

[1504] The server retrieves user information from the database and inputs it as prompts into the generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[1505] Input: A prompt such as, "The user's family consists of one adult and two children, and they have a nut allergy. Their preferences are primarily Western food, their budget is 15,000 yen per week, and they would like three meals a day."

[1506] Output: Generated weekly menu.

[1507] Step 4:

[1508] The server generates a detailed recipe and ingredients list based on the generated menu. The recipe includes cooking steps, required ingredients, and cooking tools, while the ingredients list includes types, amounts, and options for cutting and measuring.

[1509] Input: The generated menu.

[1510] Output: Recipe and ingredients list.

[1511] Step 5:

[1512] The device activates an emotion engine to recognize the user's emotions, collects emotion data through facial recognition and voice analysis, and sends it to the server.

[1513] Input: User's emotional expression (facial expression and voice).

[1514] Output: Emotion data.

[1515] Step 6:

[1516] The server receives the emotion data from the emotion engine and stores it in a database. Then, it analyzes the emotion data and customizes the menu based on the user's emotional state, thereby proposing a final menu that reflects the user's emotional state.

[1517] Input: Emotion data.

[1518] Output: Final menu reflecting emotional state.

[1519] Step 7:

[1520] The device displays the final menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[1521] Input: Final menu, recipe, and ingredient list.

[1522] Output: Information that the user reviews, modifies, and approves.

[1523] Step 8:

[1524] The user reviews the final menu and ingredient list and approves the delivery schedule and ingredient costs.

[1525] Input: Review and approve final menus, recipes and ingredient lists.

[1526] Output: Approved ingredient list.

[1527] Step 9:

[1528] The server automatically places orders with partner suppliers based on the final approved ingredient list.

[1529] Input: Approved ingredient list.

[1530] Output: Ingredients are ordered from partner suppliers.

[1531] Step 10:

[1532] The delivery company will deliver the ingredients to the user's address on the specified date and time.

[1533] The server confirms delivery completion and notifies the user.

[1534] Input: Order information and delivery instructions.

[1535] Output: Notification of delivery of ingredients and completion of delivery.

[1536] In this way, the system can easily provide a customized menu based on the user's individual needs and emotional state, along with the ingredients needed to make that menu.

[1537] (Application example 2)

[1538] 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."

[1539] Current nutritionally balanced menu suggestion and food delivery systems can generate menus based on user information, but they have the problem of not being able to customize suggestions that take the user's emotional state into account. This results in a problem of not being able to sufficiently increase user satisfaction. Furthermore, while there is a demand for systems that users can operate intuitively, conventional systems lack such operability. Therefore, there is a need for a system that can recognize and analyze the user's emotional state and customize menus based on that information to make suggestions that more closely meet individual needs.

[1540] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model to generate a menu based on the user's information and emotional state, means for analyzing the user's emotional state and customizing the menu based on this, and means for displaying the generated menu, recipe, and ingredient list to the user. This makes it possible to propose a menu that is adapted to the user's individual needs and emotional state.

[1541] The "user information input means" is a means by which a user inputs information such as family composition, allergies, preferences, number of times cooked, budget, and delivery frequency.

[1542] The "information transmission means" is a means for transmitting input information to a server.

[1543] The "information storage means" is a means for storing information received by the server.

[1544] The "menu generation means" is a means for generating a menu based on input information and emotional state, taking into consideration nutritional balance.

[1545] "Means for using a generative AI model" refers to means for using a generative AI model to generate a menu based on the user's information and emotional state.

[1546] The "recipe generation means" is a means for generating a recipe and a list of necessary ingredients from the generated menu.

[1547] The "information display means" is a means for displaying the generated menu, recipes, and ingredient list to the user.

[1548] "Means for confirmation, change and approval" refers to the means by which users can confirm, change and approve.

[1549] The "automatic ordering means" is a means for automatically placing orders with partner suppliers based on the confirmed ingredient list.

[1550] The "emotional state analysis means" is a means for analyzing the user's emotional state and customizing a menu based on this.

[1551] This invention relates to a system that proposes nutritionally balanced meals for users and automates the delivery of ingredients. In particular, it customizes the meals taking into account the user's emotional state. This system operates by allowing users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency using a smartphone app.

[1552] Enter and submit user information

[1553] First, the user accesses the smartphone app and enters the necessary information. This information includes family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). The entered information is sent from the smartphone device to the server.

[1554] Save information and generate menus

[1555] The server stores the information sent by the user in a database. The information stored in the database is used to generate nutritionally balanced menus using a "generative AI model." This generative AI model receives information such as the user's family composition, allergies, and preferences as input and generates a weekly menu. The generated menu also includes recipes and a list of necessary ingredients.

[1556] Sentiment analysis and menu customization

[1557] The user's emotional state is recognized using the smartphone's camera and microphone. Specifically, the system uses technologies such as the emotion recognition library "DeepFace" to analyze facial expressions and voice to identify the user's emotional state. The server then customizes the menu based on this emotional data. For example, if the user is excited, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1558] Menu display and user confirmation

[1559] The server displays the generated menu, recipes, and ingredient list on the user's smartphone. The user can check the displayed information and make changes or approvals as necessary. After the ingredient list is confirmed, an order is automatically placed with a partner delivery company, and the ingredients are delivered to the user's address at the specified date and time.

[1560] Hardware and software used

[1561] Hardware: Smartphones, servers

[1562] Software: Emotion recognition library "DeepFace", generative AI model "TensorFlow"

[1563] Specific examples

[1564] For example, assume that User A has a family of one adult and two children, a nut allergy, a preference for Western food, a weekly budget of 15,000 yen, desires three meals a day, and selects delivery once a week. Assume that User A has been feeling stressed recently and desires a relaxing meal.

[1565] An example of a prompt sentence could be, "An excited user has a family of one adult and two children, has a nut allergy, and has a weekly budget of 15,000 yen. He wants suggestions for a week's worth of menus, mainly Western food."

[1566] In this way, the system can offer customized meal suggestions based on individual needs and emotional state.

[1567] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1568] Step 1:

[1569] Entering user information

[1570] Using a smartphone app, users input necessary information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc. The input information is then saved on the smartphone device.

[1571] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc.

[1572] Output: The smartphone device is now ready to send this information to the server.

[1573] Step 2:

[1574] Sending and storing information

[1575] The smartphone device sends the entered information to a server, which stores the received information in a database, thereby building a user profile.

[1576] Input: User information from the smartphone device.

[1577] Output: User information stored in the database.

[1578] Step 3:

[1579] Menu generation

[1580] The server retrieves user information from the database and inputs it into a generative AI model, which then takes into account family composition, allergies, preferences, and other factors to generate a week's worth of nutritionally balanced menus.

[1581] Input: User profile data.

[1582] Output: Generated weekly menu.

[1583] Step 4:

[1584] Emotion analysis

[1585] The user inputs their emotional state using a smartphone app. The device uses a camera and microphone to analyze facial expressions and voice, and an emotion recognition library (e.g., "DeepFace") identifies the user's emotion. The results are sent to a server.

[1586] Input: User's facial and voice data.

[1587] Output: Emotion data stored by the server.

[1588] Step 5:

[1589] Emotion-based customization

[1590] The server customizes the generated menu based on the emotional data. For example, if a user is feeling stressed, it will suggest a menu that includes ingredients that have a relaxing effect.

[1591] Input: Emotion data, generated menu.

[1592] Output: A customized menu.

[1593] Step 6:

[1594] Menu and ingredient list generation

[1595] The server generates a detailed recipe and ingredient list based on the customized meal plan, including ingredient types, quantities, and cutting and measuring options.

[1596] Input: Your customized menu.

[1597] Output: Recipe and ingredients list.

[1598] Step 7:

[1599] User Verification and Authorization

[1600] The generated menu, recipes, and ingredient list are displayed on the user's smartphone. The user can review them and make changes or approvals as necessary. Finally, they can confirm the delivery date and ingredient costs.

[1601] Input: Customized menus, recipes, and ingredient lists.

[1602] Output: User approval.

[1603] Step 8:

[1604] Food ordering and delivery

[1605] The server automatically places an order with a partner supplier based on the ingredient list confirmed by the user, and the partner supplier delivers the ingredients to the user's address on the specified date and time.

[1606] Input: Finalized ingredient list.

[1607] Output: Order confirmation and delivery of ingredients.

[1608] The above is the flow of specific processing steps for implementing the invention.

[1609] 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.

[1610] 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.

[1611] 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.

[1612] [Fourth embodiment]

[1613] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1614] 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.

[1615] 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).

[1616] 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.

[1617] 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.

[1618] 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).

[1619] 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. 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.

[1620] 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.

[1621] 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.

[1622] 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.

[1623] 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.

[1624] 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.

[1625] 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."

[1626] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves the ingredients, automatically orders the ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[1627] System Operation

[1628] 1. User registration and input

[1629] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[1630] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[1631] 2. Data transmission and storage

[1632] The terminal (user's device) sends the entered data to the server.

[1633] The server stores the received data in a database.

[1634] 3. Menu generation

[1635] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[1636] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[1637] 4. Generate recipes and ingredient lists

[1638] The server generates a recipe based on the generated menu and generates a list of ingredients required for the recipe, including type, amount, and cutting and measuring options.

[1639] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[1640] 5. User Verification and Authorization

[1641] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1642] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[1643] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[1644] 6. Customize your ingredients

[1645] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[1646] The terminal transmits the user's selection to the server.

[1647] The server updates the final ingredient list based on the user's selections.

[1648] 7. Final confirmation and automatic delivery

[1649] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[1650] The delivery company delivers the ingredients to the user's address on the specified date and time.

[1651] The server confirms delivery completion and notifies the user.

[1652] Specific examples

[1653] User A is a family of two adults and one child who has a dairy allergy. Their preferences are primarily Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[1654] 1. User A enters the required information and sends it to the server.

[1655] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken," "stir-fried vegetables," "grilled salted fish," etc.).

[1656] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A.

[1657] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[1658] 5. The delivery company delivers the ingredients to User A's address on the specified date and time and notifies the server that delivery is complete.

[1659] The present invention allows users to easily prepare healthy meals tailored to their individual needs, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals.

[1660] The processing flow will be explained below.

[1661] Step 1:

[1662] A user visits an app or website and is prompted to create a new account.

[1663] Step 2:

[1664] The user creates an account by entering the required information, such as name, email address, and password.

[1665] Step 3:

[1666] The terminal transmits the input information to the server.

[1667] Step 4:

[1668] The server stores the received user data in a database.

[1669] Step 5:

[1670] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1671] Step 6:

[1672] The user enters the required information.

[1673] Step 7:

[1674] The terminal transmits the input data to the server.

[1675] Step 8:

[1676] The server stores the received data in a database.

[1677] Step 9:

[1678] The server retrieves the user's information from a database and inputs it into a generative AI model.

[1679] Step 10:

[1680] The generative AI model generates a week's worth of menus taking into account the user's family composition, allergies, preferences, and nutritional balance.

[1681] Step 11:

[1682] The server stores the generated menus and recipes in a database.

[1683] Step 12:

[1684] The server generates a list of ingredients needed based on the saved menu and recipes.

[1685] Step 13:

[1686] The server stores the generated ingredient list in a database.

[1687] Step 14:

[1688] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1689] Step 15:

[1690] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[1691] Step 16:

[1692] The device sends user changes and authorization information to the server.

[1693] Step 17:

[1694] The server updates the final ingredient list based on the changes and approvals received.

[1695] Step 18:

[1696] The user selects cutting and measuring options from the ingredient list.

[1697] Step 19:

[1698] The terminal transmits the selected option information to the server.

[1699] Step 20:

[1700] The server updates the final ingredient list and stores it in the database.

[1701] Step 21:

[1702] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[1703] Step 22:

[1704] The server notifies the user of the order details and delivery schedule.

[1705] Step 23:

[1706] A delivery company delivers the ingredients to the user's address on the specified date and time.

[1707] Step 24:

[1708] The delivery person completes the delivery and sends a confirmation to the server.

[1709] Step 25:

[1710] The server sends a delivery completion notification to the user.

[1711] Example 1

[1712] 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."

[1713] In today's busy lifestyles, it is difficult for users to prepare nutritionally balanced meals every day. Purchasing optimal ingredients and planning meals according to each household's allergies, preferences, budget, etc. takes time and effort. Furthermore, selecting ingredients and adjusting recipes is time-consuming and requires efficient operation. However, conventional systems have not been able to solve these issues in a unified manner.

[1714] 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.

[1715] In this invention, the server includes: means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency; means for transmitting the input information to the server; means for the server to store the received information and generate a menu that takes nutritional balance into consideration using a generative AI model; means for generating recipes and a list of necessary ingredients from the generated menu; means for displaying the generated menu, recipes, and ingredient list to the user; means for the user to confirm, change, and approve; means for the user to select cutting and measuring options based on the ingredient list; and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This enables users to efficiently plan nutritionally balanced meals that meet their individual needs and easily procure the necessary ingredients.

[1716] "User" refers to an individual or household who uses the system to input information and receive menu and recipe suggestions.

[1717] "Family composition" refers to information such as the number of people in the user's household and their ages, and is a factor that influences the creation of menus.

[1718] "Allergies" refer to hypersensitivity reactions that a user or their family members have to certain foods or ingredients, and are important information that is taken into consideration when generating menus.

[1719] "Preferences" refers to personal preferences such as favorite dishes and disliked ingredients of the user and their family.

[1720] "Number of times cooked" refers to the number of meals a user eats per day, and is important data for menu planning.

[1721] "Budget" refers to the amount of money a user allocates for food on a weekly or monthly basis.

[1722] "Delivery frequency" refers to how often a user wants food delivered (e.g., once a week, twice a month, etc.).

[1723] "Server" refers to the central computing device that receives and stores information submitted by users and generates menus, recipes, and ingredient lists using generative AI models.

[1724] A "generative AI model" refers to an artificial intelligence model that automatically generates menus that take into account nutritional balance, allergies, and preferences based on information input by the user.

[1725] A "menu" refers to a combination of multiple meal menus suggested by a generative AI model.

[1726] "Recipe" refers to detailed instructions on how to prepare each dish on a menu.

[1727] "Ingredient List" refers to a list of ingredients required based on a recipe, including their type, quantity, and options for cutting and measuring.

[1728] "Partner" refers to a company or organization that provides and delivers ingredients specified by the user.

[1729] "Delivery method" refers to the method for automatically placing an order with partner suppliers based on the confirmed ingredient list and delivering the ingredients to the user.

[1730] "Cutting and measuring options" refers to a customization function that allows users to select the shape, size, and quantity of ingredients according to their preferences.

[1731] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and a server generates nutritionally balanced menus based on that information. The system automatically generates recipes and lists of ingredients and provides them to the user. The user can then confirm, change, and approve the displayed information, order ingredients from affiliated suppliers, and have them delivered.

[1732] First, a user creates an account on a website or application. At this time, the user enters basic information such as name, email address, and password. Then, the user enters family composition (number of people, age, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.).

[1733] The information entered by the user is sent from the device to the server. Specifically, the device's application or web browser passes the data to the server via an HTML form or API. This data is parsed in JSON format or similar, and the server stores it in a database.

[1734] The server retrieves the stored information and inputs it into a generative AI model. This generative AI model automatically generates a week's worth of menus, taking into account the user's allergies, preferences, and nutritional balance. The generative AI model is built using a machine learning algorithm written in Python, for example. An example of a specific prompt is, "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[1735] Based on the generated menu, the server generates a recipe for each dish and a list of ingredients. The recipe includes detailed instructions on cooking steps, timing, and necessary cooking equipment. The ingredient list includes the type, amount, and cutting and measuring options of the ingredients, allowing the user to clearly see which ingredients they need to purchase.

[1736] The generated menu, recipe, and ingredient list are displayed to the user via the terminal. The user can review them and make changes or adjustments as needed. For example, if a specific dish needs to be replaced with another, it can be easily replaced in the system. The user can also select cutting and measuring options based on the ingredient list. For example, detailed selections such as "thinly slice the carrots and finely chop the onions" are possible.

[1737] The final ingredient list and delivery date are automatically sent from the server to the partner supplier's system. Data is exchanged using protocols such as APIs. The partner supplier delivers the ingredients to the user's address on the specified date and time, and is notified once delivery is complete. The server then confirms delivery completion and notifies the user.

[1738] This series of processes allows users to easily plan nutritionally balanced meals tailored to their individual needs and efficiently source the necessary ingredients. Furthermore, by providing options for cutting and measuring ingredients, the system significantly reduces the time and effort required for daily meal preparation.

[1739] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1740] Step 1:

[1741] User enters information

[1742] Subject: User

[1743] How it works: The user enters information such as family size, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1744] Input: Various information provided by the user (family composition, allergy information, preferences, cooking frequency, budget, delivery frequency).

[1745] Output: The entered information is temporarily stored on the device.

[1746] What happens: The user fills out a web form or app screen with this information and clicks the "Submit" button.

[1747] Step 2:

[1748] Data transmission

[1749] Subject: Terminal

[1750] Operation: The device sends the entered information to the server.

[1751] Input: The information the user entered in step 1.

[1752] Output: JSON formatted data sent to the server.

[1753] What it does: Data is securely transmitted to the server using the HTTPS protocol.

[1754] Step 3:

[1755] Data storage

[1756] Subject: Server

[1757] What it does: The server stores the received information in a database.

[1758] Input: JSON format data sent from the terminal.

[1759] Output: User information stored in the database.

[1760] What happens: The server parses the received data and stores it in a database in the appropriate format. For example, it stores information by user ID and assigns an index to it.

[1761] Step 4:

[1762] Menu generation

[1763] Subject: Server

[1764] How it works: The server retrieves the user's information from a database and inputs it into a generative AI model.

[1765] Input: User information stored in the database.

[1766] Output: A week's worth of meal plans generated by the AI ​​model.

[1767] Specific operation: The server sends a specific prompt to the generation AI model, and the AI ​​generates a menu. Example prompt: "Please suggest a Japanese menu that takes nutritional balance into consideration for a user who has a dairy allergy."

[1768] Step 5:

[1769] Recipe and ingredient list generation

[1770] Subject: Server

[1771] How it works: The server generates a recipe and a list of ingredients based on the menu.

[1772] Input: Generated menu data.

[1773] Output: Detailed recipe and ingredient list for each dish.

[1774] What it does: The server retrieves details of each dish from the recipe database and generates a list containing the required ingredients, their quantities, and cutting and measuring options.

[1775] Step 6:

[1776] User confirmation and changes

[1777] Subject: Terminal, User

[1778] What it does: The device displays the generated menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[1779] Input: Menu, recipe, and ingredient list provided by the server.

[1780] Output: The final menu and ingredients list, as reviewed and modified by the user.

[1781] Specific operation: The user checks the menu on the device and presses the change button if they want to make changes. The changes are sent to the server in real time.

[1782] Step 7:

[1783] Cutting and weighing options

[1784] Subject: User, Device

[1785] Action: User selects cutting and measuring options based on an ingredient list.

[1786] Input: Ingredient list and its customization options.

[1787] Output: A final customized ingredient list.

[1788] Specific operation: The user selects an option such as "slice carrots" or "chop onions," and the device sends that information to the server.

[1789] Step 8:

[1790] Final confirmation and order

[1791] Subject: Server

[1792] How it works: The server checks the final ingredient list and delivery schedule, and automatically places an order with partner suppliers.

[1793] Input: Finalized ingredient list and delivery date information.

[1794] Output: Purchase order information sent to partner.

[1795] Specific operation: The server uses the API to send order data to the partner's system.

[1796] Step 9:

[1797] Delivery and completion notification

[1798] Subject: Delivery company, server

[1799] How it works: The delivery company delivers the groceries to the user's address at the specified date and time and notifies the server that delivery is complete.

[1800] Input: Order information received by the delivery company.

[1801] Output: Delivery of ingredients and notification of delivery completion.

[1802] Specific operation: The delivery person delivers the food and sends a completion notification to the server after the delivery is complete. The server receives the completion notification and notifies the user that the delivery is complete.

[1803] (Application example 1)

[1804] 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."

[1805] In today's busy society, it is difficult to plan a nutritionally balanced menu, procure the necessary ingredients based on that menu, and measure them in the appropriate amounts. Furthermore, there is a lack of automated methods for preparing meals that take into consideration allergies and preferences. Therefore, there is a need for a system that provides optimal ingredients and recipes for each individual user.

[1806] 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.

[1807] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking is done, budget, and delivery frequency, means for transmitting the input information to the server, means for the server to store the received information and generate a menu using a generative AI model taking nutritional balance into consideration, means for generating recipes and a list of necessary ingredients from the generated menu, means for displaying the generated menu, recipes, and ingredient list on a display terminal, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering to the user. This makes it possible to easily prepare healthy meals that meet the individual needs of the user.

[1808] "User" refers to a person who uses a service or system.

[1809] "Family composition" refers to information such as the number of people in a household and their ages.

[1810] "Allergy" refers to an immune response to a specific food or substance.

[1811] "Preferences" refers to the ingredients and types of food that one likes or dislikes.

[1812] "Cooking frequency" refers to the frequency of cooking per day or per week.

[1813] A "budget" refers to the total amount of money you can spend on ingredients and dishes.

[1814] "Delivery frequency" refers to the number of times or frequency at which food ingredients are delivered.

[1815] "Means" refers to a method or device for achieving a particular purpose.

[1816] "Server" refers to a computer system for storing and processing data.

[1817] "Means for inputting information" refers to a device or interface that allows a user to input information.

[1818] "Means for sending to server" refers to a method for transferring input information to the server.

[1819] "Nutritional balance" refers to the appropriate distribution of various nutrients that people need.

[1820] A "generative AI model" is an algorithm that uses artificial intelligence to generate results based on specified conditions.

[1821] A "menu" refers to a plan or list of dishes for a certain period of time.

[1822] A "recipe" is a document that details how to make a dish, the steps involved, and the ingredients needed.

[1823] An "ingredient list" refers to a list of ingredients and equipment needed based on a recipe.

[1824] "Display terminal" refers to a device for displaying information (smartphone, tablet, PC, etc.).

[1825] "Means for review, modification, and approval" refers to the interface or process by which a user can review the displayed information, modify it if necessary, and ultimately approve it.

[1826] "Affiliate companies" refer to companies that work in conjunction with the system to supply and deliver ingredients.

[1827] The present invention is a system that generates nutritionally balanced menus based on information entered by the user, such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and then the server analyzes this information. Based on the generated menu, the system automatically generates recipes and a list of ingredients needed, which are then displayed to the user. The system also finalizes the ingredient list through a process in which the user confirms, modifies, and approves it, automatically orders ingredients from partner suppliers, and delivers the ingredients at the specified date and time.

[1828] System Configuration

[1829] 1. Enter and submit user information

[1830] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1831] The app sends the information entered by the user to the server via an HTTP POST request.

[1832] 2. Data processing and storage

[1833] The server stores the received information in a database, using cloud servers such as AWS EC2 and Google Cloud Platform.

[1834] The database used is a relational database such as MySQL or PostgreSQL.

[1835] 3. Menu generation

[1836] The server retrieves information from the database and inputs it into a generative AI model, which can be OpenAI's GPT-4 or Google AI's T5 model.

[1837] Using a generative AI model, we generate a weekly menu with prompts like the following:

[1838] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[1839] For example, on the first day, "teriyaki chicken, stir-fried vegetables, miso soup" will be generated.

[1840] 4. Generate recipes and ingredient lists

[1841] Based on the menu, the server automatically generates a detailed recipe and ingredients list, including ingredient types, quantities, and cutting and measuring options.

[1842] 5. User Interface

[1843] The smartphone app displays the generated menu, recipe, and ingredient list to the user.

[1844] The user can review these and make changes or adjustments as needed.

[1845] 6. Final confirmation and ordering of materials

[1846] Based on the materials list that the user has confirmed and approved, the server automatically places orders with partner suppliers.

[1847] The partner company delivers the materials to the user at the specified date and time and reports the completion of delivery to the server.

[1848] Specific examples

[1849] User A is a family of two adults and one child who is allergic to dairy products. Their preferences are mainly Japanese food, their budget is 10,000 yen per week, they would like three meals a day, and they have selected delivery once a week.

[1850] 1. User A enters the necessary information through a smartphone app and sends it to the server.

[1851] 2. The server uses a generative AI model to generate a week's worth of Japanese-style menus that avoid dairy products (for example, "teriyaki chicken, stir-fried vegetables, miso soup, etc.").

[1852] 3. The server generates recipes and ingredient lists for these dishes and displays them to User A through a smartphone app.

[1853] 4. User A checks the displayed information and confirms that they would like delivery on the weekend.

[1854] 5. The partner company delivers the materials to User A's address on the specified date and time and notifies the server that delivery is complete.

[1855] The system allows users to easily prepare healthy meals tailored to their individual needs, and delivers the ingredients, including cutting and measuring, significantly reducing the burden of daily meals.

[1856] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1857] Step 1:

[1858] Users install the smartphone app and enter information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1859] The entered information is saved in the smartphone app.

[1860] Step 2:

[1861] The terminal sends the information entered by the user to the server using an HTTP POST request.

[1862] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1863] Output: The user information sent to the server.

[1864] Step 3:

[1865] The server converts the received data into a data format and inserts it into the database in order to store the received information in the database.

[1866] Input: User information.

[1867] Output: User information stored in the database.

[1868] Step 4:

[1869] The server retrieves user information from the database and inputs it as a prompt sentence into the generative AI model.

[1870] For example, to generate the following prompt:

[1871] "Family composition: 2 adults, 1 child. Dairy allergy. Preferences: Japanese food. Budget: 10,000 yen per week. 3 meals per day. Please generate Japanese menus for the next week."

[1872] Input: Information stored in the user's database.

[1873] Output: The prompt sentence to be fed into the generative AI model.

[1874] Step 5:

[1875] The generative AI model generates a weekly menu based on the prompt, generating specific dish names and contents in the process.

[1876] Input: prompt statement.

[1877] Output: A week's worth of meals.

[1878] Step 6:

[1879] Based on the generated menu, the server generates the recipes and ingredient lists required for each dish.

[1880] Input: The generated menu.

[1881] Output: Recipe and ingredients list.

[1882] Step 7:

[1883] The device displays the generated menu, recipe, and ingredient list to the user, who can review them and make changes or adjustments as needed.

[1884] Input: Recipe and ingredients list.

[1885] Output: Information that is displayed to the user.

[1886] Step 8:

[1887] The material list that the user has confirmed and approved is sent back to the server from the terminal.

[1888] Input: A list of materials reviewed and approved by the user.

[1889] Output: Final material list sent to the server.

[1890] Step 9:

[1891] The server automatically places orders with partner suppliers based on the confirmed material list, generating order information and sending it to the supplier via an API for receiving orders.

[1892] Input: Finalized materials list.

[1893] Output: Order information sent to partner.

[1894] Step 10:

[1895] The partner company delivers the materials to the user at the specified date and time based on the order details. After the delivery is completed, the partner company notifies the server of the delivery completion information.

[1896] Input: Order information.

[1897] Output: Materials delivered to the user and notification of delivery completion.

[1898] This allows users to receive meals and ingredients tailored to their needs, reducing the burden of daily meal preparation.

[1899] 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.

[1900] In this invention, the user inputs information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc., and the system generates a menu that takes nutritional balance into consideration based on this information. Furthermore, this system aims to increase user satisfaction by combining an emotion engine that recognizes the user's emotions and customizing the menu and ingredient suggestions based on emotions.

[1901] System Operation

[1902] 1. User registration and input

[1903] A user accesses an app or website and creates an account by entering the required information (name, email address, password, etc.).

[1904] Users input their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), number of meals cooked (number of meals per day), budget (food expenses on a weekly or monthly basis), and delivery frequency (once a week, twice a month, etc.).

[1905] 2. Data transmission and storage

[1906] The terminal (user's device) sends the entered data to the server.

[1907] The server stores the received data in a database.

[1908] 3. Menu generation

[1909] The server retrieves user information from the database and inputs it into a generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[1910] For example, if a user's family consists of two adults and one child and has a dairy allergy, the AI ​​model will select a menu from dishes that do not contain dairy products.

[1911] 4. Sentiment Analysis and Customization

[1912] The device will activate an emotion engine to recognize the user's emotions. For example, users can input emotion data within the app through facial recognition or voice analysis.

[1913] The server receives the emotion data from the emotion engine and stores it in a database.

[1914] The server analyzes the user's current emotional state based on the emotion data and customizes the menu accordingly. For example, if the user is feeling stressed, the server will suggest a menu that includes ingredients that have a relaxing effect.

[1915] 5. Generating recipes and ingredient lists

[1916] The server generates a recipe based on the generated menu and emotional customization, and generates an ingredient list for the recipe, including the type, amount, and cutting and measuring options.

[1917] For example, if a week's menu includes dishes such as "Teriyaki Chicken," "Vegetable Soup," and "Grilled Salt Fish," a detailed list of the chicken, vegetables, fish, etc. needed for these dishes is generated.

[1918] 6. User Verification and Authorization

[1919] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1920] Users can review the menu, recipes, and ingredient lists and make changes or adjustments as needed. For example, if a user wants to change a particular dish, the system can replace it with another dish.

[1921] The user confirms the displayed information and finally approves the delivery date and ingredient costs.

[1922] 7. Customize your ingredients

[1923] The user selects cutting and measuring options for the provided list of ingredients, such as "thinly slice the carrots and finely chop the onions."

[1924] The terminal transmits the user's selection to the server.

[1925] The server updates the final ingredient list based on the user's selections.

[1926] 8. Final confirmation and automatic delivery

[1927] The server checks the final ingredient list and delivery schedule and places an order with affiliated ingredient suppliers.

[1928] The delivery company delivers the ingredients to the user's address on the specified date and time.

[1929] The server confirms delivery completion and notifies the user.

[1930] Specific examples

[1931] User B is a family of one adult and two children who has a nut allergy. They primarily prefer Western food, have a weekly budget of 15,000 yen, would like three meals a day, and have selected delivery once a week. Furthermore, they have been busy and stressed recently, so they would like a relaxing meal.

[1932] 1. User B enters the required information and sends it to the server.

[1933] 2. The server uses a generative AI model to generate a week's worth of Western-style meals that avoid nuts (e.g., grilled chicken, minestrone soup, fish and chips, etc.).

[1934] 3. The server analyzes User B's emotional data and suggests a menu that includes ingredients that have a relaxing effect.

[1935] 4. The server generates recipes and ingredient lists for these dishes and displays them to User B.

[1936] 5. User B checks the displayed information and confirms that he / she wants delivery on the weekend.

[1937] 6. The delivery company delivers the ingredients to User B's address on the specified date and time and notifies the server that delivery is complete.

[1938] This invention allows users to easily prepare healthy meals tailored to their individual needs and emotional state, and delivers ingredients including cutting and measuring, significantly reducing the burden of daily meals. Furthermore, by using an emotion engine, it can also address the user's psychological needs.

[1939] The processing flow will be explained below.

[1940] Step 1:

[1941] A user visits an app or website and is prompted to create a new account.

[1942] Step 2:

[1943] The user creates an account by entering the required information, such as name, email address, and password.

[1944] Step 3:

[1945] The terminal transmits the input information to the server.

[1946] Step 4:

[1947] The server stores the received user data in a database.

[1948] Step 5:

[1949] A screen is displayed where the user can enter detailed information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency.

[1950] Step 6:

[1951] The user enters the required information.

[1952] Step 7:

[1953] The terminal transmits the input data to the server.

[1954] Step 8:

[1955] The server stores the received data in a database.

[1956] Step 9:

[1957] The user launches the emotion engine on the app or website and inputs emotional data through facial expression recognition and voice analysis.

[1958] Step 10:

[1959] The device transmits the emotion data to the server.

[1960] Step 11:

[1961] The server receives the emotion data from the emotion engine and stores it in a database.

[1962] Step 12:

[1963] The server retrieves user information and emotional data from the database and inputs it into the generative AI model.

[1964] Step 13:

[1965] A generative AI model generates a week's worth of menus, taking into account the user's family structure, allergies, preferences, nutritional balance, and emotional state.

[1966] Step 14:

[1967] The server stores the generated menus and recipes in a database.

[1968] Step 15:

[1969] The server generates a list of ingredients based on the generated menu and recipe.

[1970] Step 16:

[1971] The server stores the generated ingredient list in a database.

[1972] Step 17:

[1973] The terminal displays the generated menu, recipes, and ingredient list to the user.

[1974] Step 18:

[1975] The user reviews the displayed information, makes any necessary changes or adjustments, and approves.

[1976] Step 19:

[1977] The device sends user changes and authorization information to the server.

[1978] Step 20:

[1979] The server updates the final ingredient list based on the changes and approvals received.

[1980] Step 21:

[1981] The user selects cutting and measuring options from the ingredient list.

[1982] Step 22:

[1983] The terminal transmits the selected option information to the server.

[1984] Step 23:

[1985] The server updates the final ingredient list and stores it in the database.

[1986] Step 24:

[1987] The server confirms the final ingredient list and delivery schedule and places an order with the partner supplier.

[1988] Step 25:

[1989] The server notifies the user of the order details and delivery schedule.

[1990] Step 26:

[1991] A delivery company delivers the ingredients to the user's address on the specified date and time.

[1992] Step 27:

[1993] The delivery person completes the delivery and sends a confirmation to the server.

[1994] Step 28:

[1995] The server sends a delivery completion notification to the user.

[1996] Example 2

[1997] 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."

[1998] Conventional menu generation systems generate menus based on information such as the user's family structure, allergies, preferences, and budget, but they cannot customize the menu taking into account the user's emotional state, which prevents them from fully increasing user satisfaction. Furthermore, while there is a demand for meal suggestions that are tailored to individual emotional states in addition to nutritional balance, there is a problem in that no system exists that can achieve this.

[1999] 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.

[2000] In this invention, the server includes means for a user to input information such as family composition, allergies, preferences, number of times cooking, budget, and delivery frequency, means for transmitting the input information to the server, means for saving the received information and generating a menu that takes nutritional balance into consideration using a generative AI model, means for generating recipes and a list of necessary ingredients from the generated menu, means for the terminal to activate an emotion engine that recognizes the user's emotions and transmit the emotion data to the server, means for the server to analyze the user's emotional state based on the emotion data and customize the menu, means for displaying the generated menu, recipes, and ingredient list to the user, means for the user to confirm, change, and approve, and means for automatically ordering from affiliated suppliers based on the confirmed ingredient list and delivering it to the user. This makes it possible to propose individual menus tailored to the user's emotional state.

[2001] "User" refers to an individual who uses the system to create a menu that takes into account their own nutritional balance and receives food delivery.

[2002] A "terminal" is a device through which a user inputs information into a system and views output from the system.

[2003] "Server" refers to the central processing unit that receives the information sent by the user, generates the menu using the generative AI model, and sends the final ingredient list to the supplier.

[2004] A "generative AI model" is an artificial intelligence technology that includes an algorithm that automatically generates menus that take nutritional balance into consideration based on user input information.

[2005] The "emotion engine" is a software component that analyzes the user's emotional state and customizes menus based on that.

[2006] "Menu" refers to a meal combination generated by the system that takes into account nutritional balance.

[2007] A "recipe" is a document that describes the specific cooking steps for creating a menu.

[2008] An "ingredient list" is a table listing the types and quantities of ingredients needed to create a menu or recipe.

[2009] "Delivery company" refers to a company that delivers ingredients to the user based on the final ingredient list generated by the system.

[2010] "Partner" refers to a supplier with which the System partners for the procurement and delivery of ingredients.

[2011] "Customization" refers to modifying or changing menus and recipes based on the user's preferences and emotional state.

[2012] The present invention is a system in which a user inputs information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency, and the system generates a menu that takes nutritional balance into consideration based on this information, and further enables the system to customize the menu according to the user's emotional state using an emotion engine.

[2013] First, a user accesses an app or website and creates an account by entering information such as their name, email address, and password. Then, they enter detailed information such as family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). This entered information is sent from the terminal (user's device) to the server.

[2014] The server then stores the received user information in a database. This information is stored in the database linked to the user ID. The server retrieves the user information from the database and inputs it into a generative AI model. This generative AI model uses OpenAI's GPT-4 and other technologies to generate a week's worth of menus taking into account allergies, preferences, and nutritional balance. For example, if the user has a nut allergy, the generative AI model will select menus that do not contain nuts.

[2015] The server generates a detailed recipe and ingredient list for each meal. The recipe includes cooking instructions, necessary ingredients, and cooking tools, while the ingredient list includes specific details such as type, amount, and cutting and measuring options. For example, a recipe for "Teriyaki Chicken" might call for 200 grams of chicken, 3 tablespoons of soy sauce, and 2 tablespoons of sugar.

[2016] The device then activates an emotion engine to recognize the user's emotions. This emotion recognition uses the smartphone's camera and microphone to collect emotional data, for example, through facial expression recognition and voice analysis. The server receives this emotional data and stores it in a database. The server analyzes the emotional data and customizes menus taking into account the user's emotional state. For example, if the user is feeling highly stressed, it will suggest menus using ingredients that have stress-reducing effects (e.g., chamomile and avocado).

[2017] The generated menu, recipes, and ingredient list are displayed to the user on the terminal, who can review them and make changes or adjustments as necessary. The user can also give final approval to the delivery schedule and ingredient costs. After approval, the final ingredient list is automatically ordered from the partner supplier by the server. The delivery company delivers the ingredients to the user's address on the specified date and time and notifies the server that delivery is complete. The server confirms that delivery is complete and notifies the user.

[2018] As a specific example, User B is a family of one adult and two children who has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, they would like three meals a day, and they have selected one delivery per week. They have recently been feeling tired and stressed, and are looking for a relaxing meal. User B enters the necessary information and sends it to the server. The server uses a generative AI model to generate a menu that focuses on Western food but avoids nuts. Dishes such as "grilled chicken," "minestrone soup," and "fish and chips" are suggested. Furthermore, emotional data is analyzed to customize the menu, including ingredients with a relaxing effect.

[2019] Based on the generated recipe and ingredient list, User B checks the menu, makes any necessary adjustments, and then approves the weekend delivery. The ingredients are delivered at the specified date and time, and the user then confirms that the delivery has been completed. This system allows users to easily prepare meals that suit their own health and emotional state.

[2020] Example prompt sentence:

[2021] The user's family consists of one adult and two children, and the user has a nut allergy. Their preferences are primarily Western food, their weekly budget is 15,000 yen, and they would like three meals a day. They are feeling a bit tired and stressed, and would like to eat meals that will help them relax. Please generate a week's worth of menus based on these conditions.

[2022] The flow of the identification process in the second embodiment will be described with reference to FIG.

[2023] Step 1:

[2024] Users access the app or website and create an account by entering information such as their name, email address, and password. Next, they enter detailed information such as their family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, least favorite ingredients), cooking frequency (number of meals per day), budget, and delivery frequency.

[2025] Input: Name, email address, password, family composition, allergies, preferences, cooking frequency, budget, delivery frequency.

[2026] Output: Input information is sent from the device to the server.

[2027] Step 2:

[2028] The terminal transmits the input information to the server.

[2029] The server stores the received user information in a database, where the information is linked to the user ID.

[2030] Input: User information.

[2031] Output: The user information is saved in the database.

[2032] Step 3:

[2033] The server retrieves user information from the database and inputs it as prompts into the generative AI model, which then generates a week's worth of menus, taking into account allergies, preferences, and nutritional balance.

[2034] Input: A prompt such as, "The user's family consists of one adult and two children, and they have a nut allergy. Their preferences are primarily Western food, their budget is 15,000 yen per week, and they would like three meals a day."

[2035] Output: Generated weekly menu.

[2036] Step 4:

[2037] The server generates a detailed recipe and ingredients list based on the generated menu. The recipe includes cooking steps, required ingredients, and cooking tools, while the ingredients list includes types, amounts, and options for cutting and measuring.

[2038] Input: The generated menu.

[2039] Output: Recipe and ingredients list.

[2040] Step 5:

[2041] The device activates an emotion engine to recognize the user's emotions, collects emotion data through facial recognition and voice analysis, and sends it to the server.

[2042] Input: User's emotional expression (facial expression and voice).

[2043] Output: Emotion data.

[2044] Step 6:

[2045] The server receives the emotion data from the emotion engine and stores it in a database. Then, it analyzes the emotion data and customizes the menu based on the user's emotional state, thereby proposing a final menu that reflects the user's emotional state.

[2046] Input: Emotion data.

[2047] Output: Final menu reflecting emotional state.

[2048] Step 7:

[2049] The device displays the final menu, recipe, and ingredient list to the user, who can review it and make changes or adjustments as needed.

[2050] Input: Final menu, recipe, and ingredient list.

[2051] Output: Information that the user reviews, modifies, and approves.

[2052] Step 8:

[2053] The user reviews the final menu and ingredient list and approves the delivery schedule and ingredient costs.

[2054] Input: Review and approve final menus, recipes and ingredient lists.

[2055] Output: Approved ingredient list.

[2056] Step 9:

[2057] The server automatically places orders with partner suppliers based on the final approved ingredient list.

[2058] Input: Approved ingredient list.

[2059] Output: Ingredients are ordered from partner suppliers.

[2060] Step 10:

[2061] The delivery company will deliver the ingredients to the user's address on the specified date and time.

[2062] The server confirms delivery completion and notifies the user.

[2063] Input: Order information and delivery instructions.

[2064] Output: Notification of delivery of ingredients and completion of delivery.

[2065] In this way, the system can easily provide a customized menu based on the user's individual needs and emotional state, along with the ingredients needed to make that menu.

[2066] (Application example 2)

[2067] 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."

[2068] Current nutritionally balanced menu suggestion and food delivery systems can generate menus based on user information, but they have the problem of not being able to customize suggestions that take the user's emotional state into account. This results in a problem of not being able to sufficiently increase user satisfaction. Furthermore, while there is a demand for systems that users can operate intuitively, conventional systems lack such operability. Therefore, there is a need for a system that can recognize and analyze the user's emotional state and customize menus based on that information to make suggestions that more closely meet individual needs.

[2069] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for using a generative AI model to generate a menu based on the user's information and emotional state, means for analyzing the user's emotional state and customizing the menu based on this, and means for displaying the generated menu, recipe, and ingredient list to the user. This makes it possible to propose a menu that is adapted to the user's individual needs and emotional state.

[2070] The "user information input means" is a means by which a user inputs information such as family composition, allergies, preferences, number of times cooked, budget, and delivery frequency.

[2071] The "information transmission means" is a means for transmitting input information to a server.

[2072] The "information storage means" is a means for storing information received by the server.

[2073] The "menu generation means" is a means for generating a menu based on input information and emotional state, taking into consideration nutritional balance.

[2074] "Means for using a generative AI model" refers to means for using a generative AI model to generate a menu based on the user's information and emotional state.

[2075] The "recipe generation means" is a means for generating a recipe and a list of necessary ingredients from the generated menu.

[2076] The "information display means" is a means for displaying the generated menu, recipes, and ingredient list to the user.

[2077] "Means for confirmation, change and approval" refers to the means by which users can confirm, change and approve.

[2078] The "automatic ordering means" is a means for automatically placing orders with partner suppliers based on the confirmed ingredient list.

[2079] The "emotional state analysis means" is a means for analyzing the user's emotional state and customizing a menu based on this.

[2080] This invention relates to a system that proposes nutritionally balanced meals for users and automates the delivery of ingredients. In particular, it customizes the meals taking into account the user's emotional state. This system operates by allowing users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency using a smartphone app.

[2081] Enter and submit user information

[2082] First, the user accesses the smartphone app and enters the necessary information. This information includes family composition (number of people, ages, etc.), allergy information, preferences (favorite dishes, disliked ingredients, etc.), cooking frequency (number of meals per day), budget (weekly or monthly food expenses), and delivery frequency (once a week, twice a month, etc.). The entered information is sent from the smartphone device to the server.

[2083] Save information and generate menus

[2084] The server stores the information sent by the user in a database. The information stored in the database is used to generate nutritionally balanced menus using a "generative AI model." This generative AI model receives information such as the user's family composition, allergies, and preferences as input and generates a weekly menu. The generated menu also includes recipes and a list of necessary ingredients.

[2085] Sentiment analysis and menu customization

[2086] The user's emotional state is recognized using the smartphone's camera and microphone. Specifically, the system uses technologies such as the emotion recognition library "DeepFace" to analyze facial expressions and voice to identify the user's emotional state. The server then customizes the menu based on this emotional data. For example, if the user is excited, the server will suggest a menu that includes ingredients that have a relaxing effect.

[2087] Menu display and user confirmation

[2088] The server displays the generated menu, recipes, and ingredient list on the user's smartphone. The user can check the displayed information and make changes or approvals as necessary. After the ingredient list is confirmed, an order is automatically placed with a partner delivery company, and the ingredients are delivered to the user's address at the specified date and time.

[2089] Hardware and software used

[2090] Hardware: Smartphones, servers

[2091] Software: Emotion recognition library "DeepFace", generative AI model "TensorFlow"

[2092] Specific examples

[2093] For example, assume that User A has a family of one adult and two children, a nut allergy, a preference for Western food, a weekly budget of 15,000 yen, desires three meals a day, and selects delivery once a week. Assume that User A has been feeling stressed recently and desires a relaxing meal.

[2094] An example of a prompt sentence could be, "An excited user has a family of one adult and two children, has a nut allergy, and has a weekly budget of 15,000 yen. He wants suggestions for a week's worth of menus, mainly Western food."

[2095] In this way, the system can offer customized meal suggestions based on individual needs and emotional state.

[2096] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2097] Step 1:

[2098] Entering user information

[2099] Using a smartphone app, users input necessary information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc. The input information is then saved on the smartphone device.

[2100] Input: Information such as family composition, allergies, preferences, cooking frequency, budget, delivery frequency, etc.

[2101] Output: The smartphone device is now ready to send this information to the server.

[2102] Step 2:

[2103] Sending and storing information

[2104] The smartphone device sends the entered information to a server, which stores the received information in a database, thereby building a user profile.

[2105] Input: User information from the smartphone device.

[2106] Output: User information stored in the database.

[2107] Step 3:

[2108] Menu generation

[2109] The server retrieves user information from the database and inputs it into a generative AI model, which then takes into account family composition, allergies, preferences, and other factors to generate a week's worth of nutritionally balanced menus.

[2110] Input: User profile data.

[2111] Output: Generated weekly menu.

[2112] Step 4:

[2113] Emotion analysis

[2114] The user inputs their emotional state using a smartphone app. The device uses a camera and microphone to analyze facial expressions and voice, and an emotion recognition library (e.g., "DeepFace") identifies the user's emotion. The results are sent to a server.

[2115] Input: User's facial and voice data.

[2116] Output: Emotion data stored by the server.

[2117] Step 5:

[2118] Emotion-based customization

[2119] The server customizes the generated menu based on the emotional data. For example, if a user is feeling stressed, it will suggest a menu that includes ingredients that have a relaxing effect.

[2120] Input: Emotion data, generated menu.

[2121] Output: A customized menu.

[2122] Step 6:

[2123] Menu and ingredient list generation

[2124] The server generates a detailed recipe and ingredient list based on the customized meal plan, including ingredient types, quantities, and cutting and measuring options.

[2125] Input: Your customized menu.

[2126] Output: Recipe and ingredients list.

[2127] Step 7:

[2128] User Verification and Authorization

[2129] The generated menu, recipes, and ingredient list are displayed on the user's smartphone. The user can review them and make changes or approvals as necessary. Finally, they can confirm the delivery date and ingredient costs.

[2130] Input: Customized menus, recipes, and ingredient lists.

[2131] Output: User approval.

[2132] Step 8:

[2133] Food ordering and delivery

[2134] The server automatically places an order with a partner supplier based on the ingredient list confirmed by the user, and the partner supplier delivers the ingredients to the user's address on the specified date and time.

[2135] Input: Finalized ingredient list.

[2136] Output: Order confirmation and delivery of ingredients.

[2137] The above is the flow of specific processing steps for implementing the invention.

[2138] 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.

[2139] 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.

[2140] 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.

[2141] 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.

[2142] FIG. 9 illustrates 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 behaviors 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.

[2143] 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.

[2144] 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).

[2145] 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.

[2146] 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."

[2147] 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.

[2148] 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).

[2149] 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.

[2150] 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.

[2151] 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.

[2152] 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.

[2153] 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.

[2154] 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.

[2155] 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.

[2156] 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.

[2157] 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.

[2158] 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.

[2159] The following is further disclosed regarding the above embodiment.

[2160] (Claim 1)

[2161] A means for users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency;

[2162] means for transmitting the input information to a server;

[2163] A means for storing the received information by the server and generating a menu that takes nutritional balance into consideration;

[2164] A means for generating a recipe and a list of ingredients from the generated menu;

[2165] means for displaying the generated menu, recipe, and ingredient list to a user;

[2166] A means for users to review, change, and approve;

[2167] The system includes a means for automatically placing orders with partner companies based on the confirmed ingredient list and delivering the orders to the user.

[2168] (Claim 2)

[2169] 10. The system of claim 1, further comprising: means for customizing the generated recipe and ingredient list based on user preferences.

[2170] (Claim 3)

[2171] 10. The system of claim 1, further comprising means for saving the generated menu and recipes and a list of ingredients required, and for providing the user with information including nutritional reference intakes.

[2172] "Example 1"

[2173] (Claim 1)

[2174] A means for users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency;

[2175] means for transmitting the input information to a server;

[2176] A means for storing the received information by the server and generating a menu that takes nutritional balance into consideration using a generative AI model;

[2177] A means for generating a recipe and a list of ingredients from the generated menu;

[2178] means for displaying the generated menu, recipe, and ingredient list to a user;

[2179] A means for users to review, change, and approve;

[2180] a means for a user to select cutting and measuring options based on an ingredient list;

[2181] The system includes a means for automatically placing orders with partner companies based on the confirmed ingredient list and delivering ...

Claims

1. A means for users to input information such as family composition, allergies, preferences, cooking frequency, budget, and delivery frequency; means for transmitting the input information to a server; A means for storing the received information by the server and generating a menu that takes nutritional balance into consideration; A means for generating a recipe and a list of ingredients from the generated menu; means for displaying the generated menu, recipe, and ingredient list to a user; A means for users to review, change, and approve; The system includes a means for automatically placing orders with partner companies based on the confirmed ingredient list and delivering the orders to the user.

2. The system of claim 1 , further comprising: means for customizing the generated recipe and ingredient list based on user preferences.

3. The system of claim 1 further comprising means for storing the generated menus and recipes and required ingredient lists, and for providing information including nutritional reference intakes to the user.

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