System

Abstract

A system is provided.SOLUTION: This system includes a means for inputting the taste and allergy information of a user, a means for automatically generating a menu under the consideration of nutritional balance by using generation AI, a means for acquiring the information of an online shopping site by listing necessary food materials, a means for purchasing the food materials and arranging delivery, and a means for providing a recipe moving image to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Today's busy families raising children and single-parent households often lack the time to plan their daily meals or do the shopping. This leads to a tendency to rely on eating out or convenience store food, which can result in an unbalanced diet. Furthermore, it takes even more time to consider allergies and food preferences. There is a need for a system that can solve these problems and help people balance work and family life. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system that includes a means for inputting user preferences and allergy information, a means for automatically generating menus that take nutritional balance into consideration using generation AI, a means for listing necessary ingredients and obtaining information from online shopping sites, a means for purchasing ingredients and arranging for delivery, and a means for providing recipe videos to users.

[0006] First, the user enters necessary information into the system, such as family composition, allergy information, ingredient preferences, and weekly food budget. Next, the system uses generative AI to automatically generate a week's worth of nutritionally balanced meals based on this information. It then creates a list of ingredients based on the meals and retrieves ingredient availability and price information from online shopping sites, making it easy for the user to purchase. Finally, the system completes the purchase process and arranges delivery, and provides the user with recipe videos to help with cooking. This series of processes allows users to reduce the time they spend shopping and planning meals, enabling them to efficiently prepare nutritionally balanced meals.

[0007] A "user" is a person who uses the system to input information such as family composition, food preferences, allergy information, and meal budget.

[0008] "Generative AI" is an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on input information.

[0009] A "menu" is a list of dishes served for a specific period of time (e.g., a week).

[0010] "Ingredient list" refers to a list of ingredients required based on the generated menu.

[0011] An "online shopping site" is an e-commerce platform for purchasing food ingredients over the Internet.

[0012] "API" stands for Application Program Interface, a means by which different software systems communicate with each other.

[0013] "Recipe videos" are video content that visually shows cooking steps.

[0014] "Delivery arrangement" refers to the procedure for delivering the purchased ingredients to the location specified by the user. [Brief explanation of the drawings]

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

[0016] An example of an embodiment of a system according to the technology of the present disclosure will be described below with reference to the accompanying drawings.

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

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

[0019] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0020] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0021] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0022] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0023] [First embodiment]

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

[0025] 1, a data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0026] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0027] The smart device 14 includes a computer 36, a reception device 38, an output device 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The reception device 38, the output device 40, and the camera 42 are also connected to the bus 52.

[0028] The reception device 38 includes a touch panel 38A, a microphone 38B, and the like, and receives user input. The touch panel 38A detects contact with an indicator (for example, a pen or a finger) to receive user input by the touch of the indicator. The microphone 38B detects the user's voice to receive user input by voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0029] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form of expression that the user 20 can perceive (for example, audio and / or text). The display 40A displays visible information such as text and images in accordance with instructions from the processor 46. The speaker 40B outputs audio in accordance with instructions from the processor 46. The camera 42 is a compact digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0030] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

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

[0032] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0033] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0034] In the smart device 14, the processor 46 performs the reception output process. The storage 50 stores a reception output program 60. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

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

[0036] The purpose of this system is to automate the process of efficiently preparing nutritionally balanced meals for busy families with children or single parents. To achieve this, the system provides the following main functions:

[0037] Registering user information

[0038] The device collects information entered by the user, such as family composition, allergy information, food preferences, weekly food budget, etc. Once the user enters this information, the device sends the data to the server.

[0039] Examples:

[0040] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information.

[0041] Automatic menu generation

[0042] The server analyzes the received user information and passes it to the generation AI, which then automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can view it.

[0043] Examples:

[0044] Based on user information including "2 adults, 1 child," "peanut allergy," "Japanese food," and "Italian," the server uses generative AI to generate menus such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls."

[0045] Generate a list of ingredients needed

[0046] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[0047] Examples:

[0048] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[0049] Purchasing ingredients and arranging delivery

[0050] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0051] Examples:

[0052] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0053] Providing recipe videos

[0054] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can then play the provided recipe video on their device and proceed with cooking while watching the video.

[0055] Examples:

[0056] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking.

[0057] With each of the above functions, this system helps users prepare nutritionally balanced meals easily and efficiently. In particular, it can significantly reduce users' time and effort through a series of processes: automatic menu generation using generative AI, linking with online shopping sites for ingredient lists, arranging delivery, and providing recipe videos. This system makes it easier to balance work and home life and maintain a healthy diet.

[0058] The processing flow will be explained below.

[0059] Step 1:

[0060] A user logs in to the system using a terminal. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The terminal then sends this information to the server.

[0061] Step 2:

[0062] The server analyzes the received user information and provides the AI ​​with data such as family composition, allergies, and food preferences based on the analyzed information.

[0063] Step 3:

[0064] The AI ​​automatically generates a weekly menu that takes nutritional balance into consideration based on the provided data, and the generated menu is sent back to the server.

[0065] Step 4:

[0066] The server sends the generated menu to the user's device, where the user can view the weekly menu (e.g., "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll...").

[0067] Step 5:

[0068] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," it adds items such as "500g of chicken, 100ml of soy sauce, and 10g of ginger" to the list.

[0069] Step 6:

[0070] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates the final ingredients list based on the information obtained.

[0071] Step 7:

[0072] The server sends the ingredient list and a purchase link to the user's device. The user checks the provided shopping list on the device, selects the ingredients they need, and adds them to their cart.

[0073] Step 8:

[0074] When the user completes the purchase, the terminal sends the list of selected ingredients to the server, which then sends the ingredient order to the online shopping site and completes the purchase.

[0075] Step 9:

[0076] The server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for the ingredients to be delivered. Details of the delivery arrangements are sent to the user's terminal.

[0077] Step 10:

[0078] The server retrieves the URL of the recipe video corresponding to the menu from the database. For example, it retrieves the recipe video URL for "Teriyaki Chicken" ("https: / / example.com / recipe / teriyaki_chicken").

[0079] Step 11:

[0080] The server sends the URL of the recipe video to the user's device, where the user can play the recipe video and cook the dish while watching the video.

[0081] Through these steps, the system helps users efficiently prepare nutritionally balanced meals.

[0082] Example 1

[0083] 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."

[0084] In busy families with children or single parents, it is often difficult to efficiently prepare nutritionally balanced meals. In these households, time is limited, and the time and effort required for carefully selecting ingredients, planning menus, purchasing ingredients, and cooking can be a significant burden. A system that solves this problem and allows users to easily prepare nutritionally balanced meals is needed.

[0085] 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.

[0086] In this invention, the server includes means for inputting information such as the user's family composition, allergy information, ingredient preferences, budget, etc., means for automatically generating a menu that takes nutritional balance into consideration using a generative AI model, means for creating a list of necessary ingredients based on the generated menu, means for acquiring ingredient availability and price information using an online shopping API, means for purchasing ingredients and arranging for delivery, and means for providing the user with a URL for a recipe video, thereby enabling the user to prepare nutritionally balanced meals while reducing the burden on the user.

[0087] "User information" refers to information such as the user's family structure, allergy information, food preferences, budget, etc.

[0088] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on user information.

[0089] "Automatic menu generation" refers to the process of using a generative AI model to automatically create a weekly menu based on user information.

[0090] "Creating an ingredient list" refers to the process of compiling a list of ingredients needed based on the generated menu.

[0091] An "online shopping API" refers to an application programming interface for obtaining inventory and price information from shopping sites via the Internet.

[0092] "Ingredients purchasing procedure" refers to the process by which a user purchases selected ingredients through an online shopping site.

[0093] "Delivery Arrangement" refers to the process of coordinating the delivery service of purchased ingredients to a specified address.

[0094] "Providing recipe videos" refers to the process of providing users with URLs of videos showing cooking methods that can be used as reference when the user cooks.

[0095] The system of the present invention allows users to efficiently prepare nutritionally balanced meals, and is targeted particularly at busy families with children and single-parent households. The system includes a series of processes: registering user information, automatically generating menus, generating a list of ingredients, purchasing ingredients and arranging for delivery, and providing recipe videos.

[0096] First, the user uses the device to enter user information such as family composition, allergy information, food preferences, budget, etc. Once the user has entered the information, the device sends the data to the server, which then stores the received information in a database.

[0097] The server then retrieves the saved user information, incorporates that data into a prompt, and passes it to the generative AI model. The generative AI model then analyzes the user information and automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can review it.

[0098] For example, if a user enters "2 adults, 1 child" as their family composition, "peanut allergy" as their allergy information, and "Japanese food" and "Italian food" as their food preferences, the server will send a prompt based on this information to the generative AI model. The generative AI model will generate a menu such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls," and the server will provide this information to the user.

[0099] Examples of prompts are:

[0100] "The user information is: family size: 2 adults, 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0101] Based on the generated menu, the server creates a list of ingredients. The server uses an online shopping API to obtain information on ingredient availability and prices. Based on this information, the server generates the final ingredient list and sends it to the device. The user can then view the list and prices on their device.

[0102] The user uses their device to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site's API, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0103] Finally, the server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can play the provided recipe video on their device and cook while watching the video. As a specific example, the URL for the recipe video for "Teriyaki Chicken" "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[0104] Through this series of processes, the system enables users to efficiently prepare nutritionally balanced meals while reducing their burden. In particular, the combination of automatic menu generation using a generative AI model, obtaining ingredient inventory and price information using an online shopping API, and arranging delivery and providing recipe videos significantly reduces the user's workload.

[0105] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0106] Step 1: Enter your user information

[0107] The user uses the terminal to input user information such as family composition, allergy information, food preferences, budget, etc.

[0108] Specific behavior:

[0109] The user enters information such as "Family composition: 2 adults, 1 child," "Allergy information: peanuts," "Food preferences: Japanese, Italian," and "Budget: 10,000 yen" into the input form on the device.

[0110] Input: Individual pieces of information entered by the user

[0111] Output: User information data entered

[0112] Step 2: Submit user information

[0113] The terminal sends the input information to the server.

[0114] Specific behavior:

[0115] The device sends the collected information to the server using an HTTP POST request.

[0116] Input: User information data

[0117] Output: User information transferred to the server

[0118] Step 3: Save user information

[0119] The server stores the received information in a database.

[0120] Specific behavior:

[0121] The server parses the received data and stores information such as family composition, allergy information, food preferences, and budget in a database (e.g., MySQL).

[0122] Input: User information transferred to the server

[0123] Output: User information stored in the database

[0124] Step 4: Generate a prompt statement

[0125] The server retrieves the saved user information and generates a prompt.

[0126] Specific behavior:

[0127] The server reads the user information from the database and constructs a prompt message that reads, "User information: Family composition: 2 adults and 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0128] Input: User information stored in the database

[0129] Output: Generated prompt statement

[0130] Step 5: Automatic menu generation

[0131] The server passes the prompt text to a generative AI model, which automatically generates a menu that takes nutritional balance into consideration.

[0132] Specific behavior:

[0133] The server sends the prompt to the generative AI model, which then generates a weekly menu (e.g., "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Rolls").

[0134] Input: Generated prompt statement

[0135] Output: Generated weekly menu information

[0136] Step 6: Submit your menu

[0137] The server sends the generated menu to the terminal.

[0138] Specific behavior:

[0139] The server sends the generated menu information to the terminal as an HTTP response.

[0140] Input: Generated weekly menu information

[0141] Output: Menu information sent to the device

[0142] Step 7: Generate an ingredient list

[0143] The server analyzes the menu information and creates a list of necessary ingredients.

[0144] Specific behavior:

[0145] The server analyzes each dish on the menu and lists the ingredients needed (e.g., "500g chicken, 100ml soy sauce, 10g ginger").

[0146] Input: Generated weekly menu information

[0147] Output: List of ingredients needed

[0148] Step 8: Get ingredient availability and pricing information

[0149] The server uses an online shopping API to retrieve food availability and pricing information.

[0150] Specific behavior:

[0151] The server calls the API of the online shopping site (e.g., Amazon API) to obtain stock status and price information for each ingredient.

[0152] Input: List of ingredients needed

[0153] Output: A list of ingredients with availability and pricing information

[0154] Step 9: Submit your ingredient list

[0155] The server sends a list of ingredients with stock status and price information to the terminal.

[0156] Specific behavior:

[0157] The server sends the ingredient list to the terminal as an HTTP response.

[0158] Input: A list of ingredients with availability and pricing information

[0159] Output: The final ingredients list sent to the terminal

[0160] Step 10: Confirm and select ingredients

[0161] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase process.

[0162] Specific behavior:

[0163] The user can view the final ingredient list on the terminal, add the ingredients to be purchased to the cart, and complete the purchase procedure.

[0164] Input: Final ingredient list sent to the terminal

[0165] Output: Shopping list and shipping information

[0166] Step 11: Complete your purchase

[0167] The server sends the list of selected ingredients to the online shopping site's API to complete the purchase process.

[0168] Specific behavior:

[0169] The server sends the purchase information (e.g., ingredient list, shipping information) to the online shopping site's API to complete the purchase.

[0170] Input: Shopping list and shipping information

[0171] Output: Completed checkout

[0172] Step 12: Arrange for delivery

[0173] Based on the information regarding the completed purchase procedure, the server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for delivery.

[0174] Specific behavior:

[0175] The server sends purchase information (e.g., order ID, delivery address, specified date and time) to the delivery service API and arranges for delivery.

[0176] Input: Completed purchase

[0177] Output: Completed shipping process

[0178] Step 13: Submit a recipe video

[0179] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user.

[0180] Specific behavior:

[0181] The server retrieves the URL of the "Teriyaki Chicken" recipe video (e.g., "https: / / example.com / recipe / teriyaki_chicken") from the database and sends it to the terminal.

[0182] Input: Generated weekly menu information

[0183] Output: Recipe video URL sent to the device

[0184] (Application example 1)

[0185] 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."

[0186] For busy families with children or single parents, the complex and time-consuming process of efficiently preparing nutritionally balanced meals is a problem. There is a need to solve this problem and enable users to easily purchase ingredients and cook in physical stores. There is also a need to improve user convenience by providing effective suggestions in real time.

[0187] 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.

[0188] In this invention, the server includes a means for inputting user preferences and allergy information, a means for automatically generating a menu that takes nutritional balance into consideration using generation AI, and a means for making suggestions in real time in the physical store, thereby enabling users to easily purchase ingredients and cook in the physical store.

[0189] "User preference and allergy information" refers to information about preferences that a user takes into consideration when selecting food and allergic reactions to specific ingredients.

[0190] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate optimal results for specific purposes.

[0191] A "menu that takes into consideration nutritional balance" is a meal menu that includes an appropriate amount of nutrients necessary to maintain the user's health.

[0192] "Online database" means a repository of information accessible over the Internet, including food availability and pricing information.

[0193] A "cooking guide" is a document or video that describes the steps and methods that a user should follow when cooking.

[0194] "Real-time suggestions in physical stores" means providing users with information on appropriate ingredients and menus instantly via digital devices while they are in the actual store.

[0195] A "smartphone" is a mobile device that has the functions of a computer in addition to a mobile phone, and can be used by installing applications.

[0196] This invention is a system that automates a series of processes for efficiently preparing nutritionally balanced meals for busy families with children or single parents. This system includes a means for inputting user preferences and allergy information, a means for automatically generating menus that take nutritional balance into consideration using generation AI, a means for listing necessary ingredients and retrieving information from an online database, a means for making real-time suggestions in a physical store, a means for purchasing ingredients and arranging for delivery, and a means for providing users with cooking guides.

[0197] Overall flow

[0198] First, users use a device to input their own and their family's preferences and allergy information. This allows the system to select foods that meet individual needs and collect basic data for creating menus. This data is sent to a server, which uses AI to automatically create menus that take nutritional balance into consideration. The generated menus are then presented to the user in real time, after which a list of the necessary ingredients is generated. Furthermore, the system retrieves information on ingredient availability and prices from an online database, helping users to easily purchase ingredients in physical stores.

[0199] Hardware and software used

[0200] Device: Smartphone

[0201] Server: The server is the central system that holds the generative AI model and performs data analysis.

[0202] Online database: Get ingredient availability and pricing information from third-party APIs.

[0203] Generative AI model: An AI that automatically generates menus that take nutritional balance into consideration.

[0204] Processing flow

[0205] 1. Collecting user information: The device collects information from the user, such as family composition, allergy information, food preferences, budget, etc., and sends it to the server. For example, the user enters "2 adults, 1 child, peanut allergy, prefers Japanese and Italian food."

[0206] 2. Automatic menu generation: Based on the received user information, the server uses a generative AI model to generate a nutritionally balanced menu for one week. For example, a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese" may be generated.

[0207] 3. Generate a list of required ingredients: The server generates a list of required ingredients based on the generated menu information and obtains ingredient stock and price information from the online database API. For example, a list of "500g of chicken, 100ml of soy sauce, and 10g of ginger" might be generated.

[0208] 4. Real-time suggestions: Users can receive real-time suggestions using their smartphones in-store. Specifically, the location and stock status of ingredients needed for a meal are immediately displayed.

[0209] 5. Purchase and delivery: The user selects the ingredients they need and completes the purchase process. The server uses the online shopping API to complete the order and arrange for delivery.

[0210] 6. Providing cooking guides: The server provides users with cooking guides (such as recipe videos) corresponding to the menu. For example, users can watch a video showing the cooking steps for "Teriyaki Chicken."

[0211] Specific examples

[0212] If a user inputs "2 adults and 1 child, peanut allergy, likes Japanese and Italian food," the server will use generative AI to generate a menu, offering options such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." Based on this, an ingredient list is generated, and information on ingredients such as chicken, soy sauce, and ginger is retrieved from an online database. Furthermore, real-time suggestions are made to make in-store ingredient purchases easy, and after the user selects the necessary ingredients and completes the purchase process, a recipe video is provided as a cooking guide.

[0213] Prompt Sentence Examples

[0214] The user enters the following information into the terminal:

[0215] Family composition: 2 adults, 1 child

[0216] Allergy Information: Peanut Allergy

[0217] Food preferences: Japanese, Italian

[0218] Budget: 10,000 yen

[0219] This will support the invention's goal of preparing efficient and nutritionally balanced meals, and improve user convenience.

[0220] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0221] Step 1:

[0222] Users use a terminal to input their own and their family's preferences and allergy information. The terminal collects specific information from the user, such as "two adults, one child, peanut allergy, preference for Japanese and Italian food, budget of 10,000 yen." The input information is sent from the terminal to the server. The input data includes family composition, allergy information, food preferences, budget, etc.

[0223] Step 2:

[0224] The server analyzes the received user information and passes it to the generative AI model. The generative AI model automatically generates a menu that takes nutritional balance into consideration based on the input data. For example, it outputs a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." The server then sends this menu information to the device.

[0225] Step 3:

[0226] The terminal displays the received menu information. The user checks the weekly menu and a list of necessary ingredients is displayed. The server generates a list of necessary ingredients based on the generated menu. The input data is the menu information, and the output data is the list of ingredients.

[0227] Step 4:

[0228] The server uses the API of an online database to obtain stock status and price information for the required ingredients. To do this, the server accesses the API, sends specific ingredient information such as "500g of chicken, 100ml of soy sauce, 10g of ginger" as input, and receives stock status and price information as output. This information is sent to the terminal and provided to the user.

[0229] Step 5:

[0230] The user uses the device to check and select ingredients suggested in real time. In the physical store, the device suggests to the user the location and stock status of ingredients in real time. For example, it may indicate to the user that "chicken is in the refrigerated section, and soy sauce is in the condiment section." The user then adds the ingredients they need to their cart.

[0231] Step 6:

[0232] Based on the ingredients selected by the user, the terminal completes the purchase process. The server then uses the online shopping site's API to send the order information and complete the purchase process. Once the purchase process is complete, the server contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0233] Step 7:

[0234] The server retrieves the URL of the cooking guide (such as a recipe video) corresponding to the menu from the database and sends it to the device. The user cooks the meal while watching the recipe video on the device. For example, the URL "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[0235] Example prompt sentence:

[0236] The user enters the following information into the terminal:

[0237] Family composition: 2 adults, 1 child

[0238] Allergy Information: Peanut Allergy

[0239] Food preferences: Japanese, Italian

[0240] Budget: 10,000 yen

[0241] 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.

[0242] The present invention provides a system for efficiently preparing nutritionally balanced meals that takes into account the user's emotions as well as their preferences and allergies. This system is capable of recognizing the user's emotions and adjusting menus and optimizing cooking procedures based on the user's emotions.

[0243] Registering user information

[0244] The device uses an emotion engine to recognize the user's emotions, in addition to information entered by the user, such as family composition, allergy information, food preferences, and weekly food budget. Once the user enters this information, the device sends the data to the server.

[0245] Examples:

[0246] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information. Furthermore, the emotion engine detects that the user is "feeling stressed."

[0247] Automatic menu generation and emotion regulation

[0248] The server analyzes the received user information and passes it to the generation AI. The generation AI automatically generates a weekly menu that takes nutritional balance into consideration. It also adjusts the menu to recommend specific ingredients and dishes based on the user's emotions recognized by the emotion engine. This menu information is sent from the server to the device so that the user can review it.

[0249] Examples:

[0250] Based on the information such as "2 adults, 1 child," "peanut allergy," "Japanese food," "Italian food," and "feeling stressed," the server uses generative AI to generate tailored menus such as "Monday: Chicken teriyaki (high in ginger, which has a relaxing effect)" and "Tuesday: Spaghetti Bolognese (a menu high in nutrients to energize you on Wednesday)."

[0251] Generate a list of ingredients needed

[0252] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[0253] Examples:

[0254] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[0255] Purchasing ingredients and arranging delivery

[0256] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0257] Examples:

[0258] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0259] Providing recipe videos and emotional feedback

[0260] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user plays the provided recipe video on their device and proceeds with the cooking while watching the video. In addition, the emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on that feedback.

[0261] Examples:

[0262] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking. If the user becomes "confused" during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0263] With these functions, the system helps users prepare nutritionally balanced meals easily and efficiently. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing user stress. This system makes it easier to balance work and home life and maintain a healthy diet.

[0264] The processing flow will be explained below.

[0265] Step 1:

[0266] The user logs in to the application using a device. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The emotion engine recognizes the user's emotions through the device's camera and voice input. This information is sent from the device to the server.

[0267] Step 2:

[0268] The server analyzes the received user information and passes it on as the data needed for the generation AI, which then combines the user's input information with the emotional information obtained from the emotion engine to automatically generate a week's worth of menus.

[0269] Step 3:

[0270] The AI ​​creates a menu that takes nutritional balance into consideration. The emotion engine also takes into account emotional information, adjusting the menu to include specific ingredients and dishes that correspond to the user's emotions. For example, if the user is "feeling stressed," the system will recommend dishes that contain ingredients with a relaxing effect.

[0271] Step 4:

[0272] The server sends the generated menu to the user's device, where the user can check the menu for the week (e.g., "Monday: Teriyaki chicken (relaxing effect) / Tuesday: Spaghetti Bolognese").

[0273] Step 5:

[0274] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," the server generates an ingredient list of "500g of chicken, 100ml of soy sauce, and 10g of ginger."

[0275] Step 6:

[0276] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates a final ingredient list based on the information obtained and sends it to the user's device.

[0277] Step 7:

[0278] The user checks the shopping list provided on the terminal, selects the ingredients they need, and proceeds with the purchase. The terminal then sends the selected ingredients list to the server.

[0279] Step 8:

[0280] The server sends the order for ingredients to the online shopping site and completes the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery. A notification is sent to the user's device.

[0281] Step 9:

[0282] The server retrieves the URL of the recipe video corresponding to the menu from the database and sends it to the user's device. The user can then cook the dish while playing the recipe video on their device.

[0283] Step 10:

[0284] While cooking, the device's emotion engine recognizes the user's emotions in real time. If the user feels confused or stressed, the server will simplify the cooking steps and provide additional instructions based on the emotion engine's feedback.

[0285] Through these processing steps, the system enables users to efficiently prepare nutritionally balanced meals. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing stress for the user.

[0286] Example 2

[0287] 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."

[0288] Conventional meal recommendation systems can provide nutritionally balanced menus based on the user's preferences and allergy information, but they do not take into account the user's emotions or psychological state. This can cause users to feel stressed or confused, and they are unable to provide satisfactory service. Furthermore, there is a lack of a means to consistently and efficiently manage the process from purchasing ingredients to cooking. Therefore, improving user satisfaction and convenience is a challenge.

[0289] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting a user's preferences, allergy information, family composition, and weekly food budget; a means for recognizing emotions; a means for automatically generating and adjusting a menu that takes nutritional balance into consideration based on the user's preferences, allergy information, and emotional information using a generation AI; a means for listing necessary ingredients and acquiring information from online shopping sites; a means for purchasing ingredients and arranging for delivery; a means for providing the user with a recipe video; and a means for recognizing the user's emotions in real time during cooking and optimizing the cooking procedure based on the feedback. This enables individual adjustments based on the user's emotions, reducing stress and confusion and efficiently supporting the user from proposing menus to purchasing ingredients and cooking.

[0290] A "user" is an entity that uses the system to input preferences, allergy information, and emotional information, and receives menu suggestions, purchases ingredients, and recipes.

[0291] "Preferences" refers to information about ingredients and types of dishes that a user particularly likes, and are factors that are taken into consideration when the system generates a menu.

[0292] "Allergy information" is information about ingredients to which the user has an allergy, and is an element that is taken into consideration as ingredients to be avoided when the system generates a menu.

[0293] "Family composition" is information about the number of people and age groups in the user's household, and is a factor used by the system to determine the quantity and type of food when generating a menu.

[0294] The "weekly food budget" is information about the amount of money a user can spend on ingredients and meals per week, and is a factor that is taken into account as an economic constraint when the system generates menus.

[0295] "Emotion" refers to a psychological state that the system recognizes by analyzing the user's facial expressions and tone of voice, and is an element used to adjust menus and optimize cooking procedures.

[0296] An "emotion engine" is a combination of hardware and software for analyzing and recognizing a user's emotions, and is a means of understanding the user's psychological state.

[0297] "Generative AI" is an artificial intelligence program that automatically generates and adjusts menus that take nutritional balance into consideration based on input user information.

[0298] An "online shopping site" is a website where ingredients and other products can be purchased via the Internet, and is a source of information from which the system obtains information on ingredient availability and prices.

[0299] A "recipe video" is video content that visually shows specific steps for cooking, and allows users to cook while watching the video.

[0300] "Real-time" refers to the immediacy with which the system instantly recognizes and processes the user's input and emotions, which is an important element when providing feedback during cooking.

[0301] "Feedback" refers to the response and adjustments made by the system based on the user's emotional state, etc., and is a means used by the user to cook in optimal conditions.

[0302] "Optimizing cooking steps" means that the system adjusts the cooking process and instructions according to the user's emotions and situation, providing a more effective and satisfying cooking experience.

[0303] This system generates nutritionally balanced menus based on the user's preferences, allergy information, emotional information, family composition, and weekly food budget, lists the necessary ingredients, and provides support for purchasing, arranging delivery, and cooking. This system consists of a user terminal, a server, an emotion engine, a generation AI, and an online shopping site API.

[0304] Registering user information

[0305] Users input their preferences, allergies, family composition, and weekly food budget using a terminal, and this information is then sent from the terminal to the server.

[0306] Examples:

[0307] The user enters "2 adults, 1 child" into the terminal, sets "peanut allergy" as allergy information, "Japanese food" and "Italian food" as preferences, and sets the budget to "5,000 yen." This information is sent from the terminal to the server.

[0308] Emotion recognition

[0309] The emotion engine installed in the device recognizes the user's emotions in real time and sends that information to the server.

[0310] Examples:

[0311] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that the user is "feeling stressed," and sends this information to the server.

[0312] Automatic menu generation

[0313] The server analyzes the received user information and emotional information and creates prompts for the AI, which then generates a weekly menu that takes nutritional balance into consideration.

[0314] Examples:

[0315] The server inputs the following as a prompt to the generation AI:

[0316] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[0317] Based on this information, please suggest a nutritionally balanced menu for one week.

[0318] This allows the generation AI to generate a menu.

[0319] Emotion regulation and regeneration

[0320] The server re-evaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The adjusted menu is then passed back to the generation AI to finalize the menu.

[0321] Examples:

[0322] The generated menu becomes a weekly plan that includes "Teriyaki Chicken with Ginger, which has a relaxing effect." The emotion engine recommends ingredients and dishes that are suitable for the "stressed" state. The final menu is confirmed as "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese."

[0323] Generate an ingredient list

[0324] The server creates a list of ingredients based on the finalized menu, and uses the API of the online shopping site to obtain stock availability and price information, which is then provided to the user.

[0325] Examples:

[0326] The server creates a list of ingredients such as "500g chicken, 100ml soy sauce, 10g ginger" and uses the API to check stock and price information, providing this information to the user.

[0327] Purchasing ingredients and arranging delivery

[0328] The user checks the shopping list on the terminal, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completes the purchase, and notifies the delivery service of the order ID, delivery address, and specified date and time.

[0329] Examples:

[0330] The user adds "chicken, soy sauce, ginger" to the cart and completes the purchase. After completing the order, the server uses the online shopping API to contact the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0331] Providing recipe videos and emotional feedback while cooking

[0332] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. While the user is cooking, the device's emotion engine recognizes emotions in real time and optimizes the cooking procedure based on the feedback.

[0333] Examples:

[0334] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0335] As described above, the present system supports users in efficiently preparing nutritionally balanced meals, and can also improve psychological satisfaction, particularly by making adjustments based on the user's emotions.

[0336] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0337] Step 1: Register user information

[0338] Users use a device to input their family composition, allergy information, food preferences, and weekly food budget. The device stores this information in a database and sends it to the server. The input data includes family composition, allergy information, preferences, and budget. The output data is a dataset that compiles this user information.

[0339] Specific behavior:

[0340] The user enters into the terminal the family composition as "2 adults, 1 child," allergy information as "peanut allergy," preferences as "Japanese food" and "Italian food," and budget as "5,000 yen," and this information is sent to the server.

[0341] Step 2: Recognize emotions

[0342] The emotion engine installed in the device recognizes the user's emotions in real time. The input data includes the user's facial expressions and tone of voice, which are analyzed to extract emotional information. The output data is the recognized emotional information.

[0343] Specific behavior:

[0344] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that they are "feeling stressed," and sends this information to the server.

[0345] Step 3: Automatic menu generation

[0346] The server analyzes user information and emotional information, and creates and inputs prompts to the generation AI. The input data includes user information and emotional information, and the generation AI uses this to generate a week's worth of menus that take nutritional balance into consideration. The output data is the generated menu information.

[0347] Specific behavior:

[0348] The server inputs the following prompt to the generated AI:

[0349] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[0350] Based on this information, please suggest a nutritionally balanced menu for one week.

[0351] The generation AI generates a menu, which is sent to the server.

[0352] Step 4: Emotional regulation and regeneration

[0353] The server reevaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The input data are the generated menu and the user's emotion information, and the emotion engine makes adjustments based on this. The output data is the adjusted final menu.

[0354] Specific behavior:

[0355] The generated menu is adjusted into a weekly plan that includes "Chicken Teriyaki with Ginger, which has a relaxing effect." The final menu is finalized as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese."

[0356] Step 5: Generate an ingredient list

[0357] The server creates a list of ingredients based on the final menu. The input data is the final menu, and it uses the API of an online shopping site to obtain stock and price information. The output data is the list of ingredients.

[0358] Specific behavior:

[0359] The server creates a list of ingredients, such as "500g chicken, 100ml soy sauce, 10g ginger," and uses an online shopping API to check inventory and price information, which is then provided to the user.

[0360] Step 6: Purchase ingredients and arrange delivery

[0361] The user checks the provided shopping list on their device, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completing the purchase process. The delivery service is then notified of the order ID, delivery address, and specified date and time. The input data is the list of ingredients selected by the user, and the output data is confirmation that the order has been completed.

[0362] Specific behavior:

[0363] The user adds "chicken, soy sauce, and ginger" to the cart and completes the purchase. The server completes the order using the online shopping site API and contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0364] Step 7: Providing recipe videos and emotional feedback during cooking

[0365] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The device's emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on the feedback. The input data is the user's emotional state while cooking, and the output data is the optimized cooking steps.

[0366] Specific behavior:

[0367] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0368] The above is a detailed description of the specific processing flow of this system and the operation at each step.

[0369] (Application example 2)

[0370] 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."

[0371] While conventional meal preparation systems can take into account a user's preferences and allergy information, they have difficulty optimizing menu suggestions and cooking procedures that reflect the user's emotional state. As a result, they are unable to respond adequately to situations where the user is likely to feel stressed, which can result in meal preparation being time-consuming and inefficient. Furthermore, the lack of real-time emotional cooking support often leaves users confused.

[0372] 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 inputting the user's preferences, allergy information, and emotions, means for automatically generating a menu that takes nutritional balance into consideration using a generation AI and adjusting the menu based on emotional information, means for listing necessary ingredients and acquiring information from online shopping sites, means for purchasing ingredients and arranging for delivery, and means for providing the user with recipe videos, acquiring emotional feedback in real time during cooking, and optimizing cooking procedures. This makes it possible to adjust the menu and optimize cooking procedures according to the user's emotional state, resulting in efficient and stress-free meal preparation.

[0373] "User preference and allergy information" is information about preferences and allergies that are individually input by the user.

[0374] "Emotion information" is data that indicates the user's current psychological state, and is information obtained using the emotion engine.

[0375] "Generative AI" is an artificial intelligence model that automatically generates menus that take nutritional balance into consideration based on provided data.

[0376] The "means for adjusting the menu" refers to a method or function for adjusting the generated menu to an optimal one, taking into account the user's emotional information.

[0377] An "online shopping site" is an e-commerce platform for purchasing products over the Internet.

[0378] "Recipe videos" are video content that explains cooking steps and methods.

[0379] "Emotional feedback" is information that acquires the user's emotional information in real time and adjusts the system's behavior based on that information.

[0380] The "means for optimizing the cooking procedure" refers to a method or function for changing the cooking procedure to an optimal form based on the user's emotional information.

[0381] The "ingredient list" is a list of all ingredients required based on the generated menu.

[0382] "Delivery arrangement" refers to carrying out procedures to deliver the selected ingredients to a location designated by the user.

[0383] The present invention is a system that efficiently prepares nutritionally balanced meals by taking into account the user's preferences, allergy information, and emotional information. This system is composed of a user terminal and a server, and performs the following processes.

[0384] Registering user information

[0385] First, the user uses the device to input information such as family composition, allergies, favorite ingredients, and weekly food budget. The device is also equipped with an emotion engine that captures emotional information from the user's facial expressions in real time. This information is then sent to the server and stored in a database.

[0386] Automatic menu generation and emotion regulation

[0387] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. It also adjusts the generated menu based on emotional information obtained from the emotion engine. For example, if it detects that the user is "feeling stressed," it will suggest a menu that includes many ingredients with a relaxing effect.

[0388] Generate a list of ingredients needed

[0389] The server creates a list of ingredients based on the generated menu, and then uses the API of the online shopping site to obtain information on ingredient availability and prices, which it then provides to the user.

[0390] Purchasing ingredients and arranging delivery

[0391] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the order information to the online shopping site to complete the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0392] Providing recipe videos and emotional feedback

[0393] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user cooks while playing the provided recipe video on their device. The emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking procedure based on that feedback. Specifically, if the server detects that the user is "confused," it automatically provides simplifications or additional explanations.

[0394] Example of a system

[0395] If a user inputs their family composition (two adults, one child), their "peanut allergy," and their "preference for Japanese and Italian food," and the emotion engine detects that they are "feeling stressed," the generative AI model automatically generates and adjusts a menu suggestion, such as "Monday: Chicken Teriyaki (high in ginger, which has a relaxing effect) and Tuesday: Spaghetti Bolognese." The user confirms this, purchases the necessary ingredients from an online shopping site, and cooks while watching a recipe video. If confusion is detected during cooking, a prompt message will be displayed, such as, "If you find the steps difficult, we will explain in detail how to fry the chicken first and then add the ginger and soy sauce. We also provide a detailed explanation from 01:45 to 02:10 in the video."

[0396] In this way, the system adjusts menus and optimizes cooking procedures according to the user's emotional state, supporting efficient and stress-free meal preparation.

[0397] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0398] Step 1:

[0399] The user uses a device to input information such as family composition, allergy information, favorite ingredients, and weekly food budget. The emotion engine then captures the user's facial expressions and obtains emotional information. The input data includes text data such as family composition and allergy information, as well as image data, and the organized user information is sent to the server as output.

[0400] Step 2:

[0401] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. The user information is used as input data, and a weekly menu is generated as output. In addition, based on emotional information, the menu is adjusted to include more ingredients that have a relaxing effect. Specifically, the system refers to the nutrition database and emotional database to select an appropriate menu.

[0402] Step 3:

[0403] The server creates a list of ingredients based on the generated menu and uses the online shopping site's API to obtain the availability and price information of those ingredients. The generated menu and the online shopping site's API endpoint are used as input data, and the list of ingredients, their availability, and price information is generated as output. Specifically, the server sends an API request and analyzes the received data to create the list.

[0404] Step 4:

[0405] The user uses a terminal to check the provided shopping list, select the ingredients they need, and complete the purchase procedure. The created ingredient list and the user's selection information are used as input data, and the final shopping list is determined as output. Specific actions include pressing the purchase confirmation button on the user interface.

[0406] Step 5:

[0407] The server sends the order information for the selected ingredients to the online shopping site to complete the purchase process. It also contacts the delivery service with the order ID, delivery address, and specified date and time to arrange delivery. The input data is the final purchase list and delivery address information, and the output is a confirmation of the order and the completion of delivery arrangements. Specifically, it sends the order information using an API request and makes a request to the delivery service.

[0408] Step 6:

[0409] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The generated menu is used as input data, and the URL of the recipe video is generated as output. Specifically, the database is queried using the menu name as a key to retrieve the corresponding video URL.

[0410] Step 7:

[0411] The user cooks while playing a recipe video provided on the device. While cooking, the device uses an emotion engine to obtain the user's emotions in real time and optimizes the cooking steps based on that feedback. Real-time emotion information is used as input data, and optimized cooking steps are provided as output. Specifically, support is provided, such as displaying prompts if the user is confused.

[0412] 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.

[0413] 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.

[0414] 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.

[0415] [Second embodiment]

[0416] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0417] 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.

[0418] 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).

[0419] 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.

[0420] 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.

[0421] 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).

[0422] 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.

[0423] 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.

[0424] 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.

[0425] 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.

[0426] In the smart glasses 214, 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.

[0427] 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."

[0428] The purpose of this system is to automate the process of efficiently preparing nutritionally balanced meals for busy families with children or single parents. To achieve this, the system provides the following main functions:

[0429] Registering user information

[0430] The device collects information entered by the user, such as family composition, allergy information, food preferences, weekly food budget, etc. Once the user enters this information, the device sends the data to the server.

[0431] Examples:

[0432] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information.

[0433] Automatic menu generation

[0434] The server analyzes the received user information and passes it to the generation AI, which then automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can view it.

[0435] Examples:

[0436] Based on user information including "2 adults, 1 child," "peanut allergy," "Japanese food," and "Italian," the server uses generative AI to generate menus such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls."

[0437] Generate a list of ingredients needed

[0438] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[0439] Examples:

[0440] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[0441] Purchasing ingredients and arranging delivery

[0442] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0443] Examples:

[0444] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0445] Providing recipe videos

[0446] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can then play the provided recipe video on their device and proceed with cooking while watching the video.

[0447] Examples:

[0448] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking.

[0449] With each of the above functions, this system helps users prepare nutritionally balanced meals easily and efficiently. In particular, it can significantly reduce users' time and effort through a series of processes: automatic menu generation using generative AI, linking with online shopping sites for ingredient lists, arranging delivery, and providing recipe videos. This system makes it easier to balance work and home life and maintain a healthy diet.

[0450] The processing flow will be explained below.

[0451] Step 1:

[0452] A user logs in to the system using a terminal. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The terminal then sends this information to the server.

[0453] Step 2:

[0454] The server analyzes the received user information and provides the AI ​​with data such as family composition, allergies, and food preferences based on the analyzed information.

[0455] Step 3:

[0456] The AI ​​automatically generates a weekly menu that takes nutritional balance into consideration based on the provided data, and the generated menu is sent back to the server.

[0457] Step 4:

[0458] The server sends the generated menu to the user's device, where the user can view the weekly menu (e.g., "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll...").

[0459] Step 5:

[0460] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," it adds items such as "500g of chicken, 100ml of soy sauce, and 10g of ginger" to the list.

[0461] Step 6:

[0462] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates the final ingredients list based on the information obtained.

[0463] Step 7:

[0464] The server sends the ingredient list and a purchase link to the user's device. The user checks the provided shopping list on the device, selects the ingredients they need, and adds them to their cart.

[0465] Step 8:

[0466] When the user completes the purchase, the terminal sends the list of selected ingredients to the server, which then sends the ingredient order to the online shopping site and completes the purchase.

[0467] Step 9:

[0468] The server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for the ingredients to be delivered. Details of the delivery arrangements are sent to the user's terminal.

[0469] Step 10:

[0470] The server retrieves the URL of the recipe video corresponding to the menu from the database. For example, it retrieves the recipe video URL for "Teriyaki Chicken" ("https: / / example.com / recipe / teriyaki_chicken").

[0471] Step 11:

[0472] The server sends the URL of the recipe video to the user's device, where the user can play the recipe video and cook the dish while watching the video.

[0473] Through these steps, the system helps users efficiently prepare nutritionally balanced meals.

[0474] Example 1

[0475] 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."

[0476] In busy families with children or single parents, it is often difficult to efficiently prepare nutritionally balanced meals. In these households, time is limited, and the time and effort required for carefully selecting ingredients, planning menus, purchasing ingredients, and cooking can be a significant burden. A system that solves this problem and allows users to easily prepare nutritionally balanced meals is needed.

[0477] 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.

[0478] In this invention, the server includes means for inputting information such as the user's family composition, allergy information, ingredient preferences, budget, etc., means for automatically generating a menu that takes nutritional balance into consideration using a generative AI model, means for creating a list of necessary ingredients based on the generated menu, means for acquiring ingredient availability and price information using an online shopping API, means for purchasing ingredients and arranging for delivery, and means for providing the user with a URL for a recipe video, thereby enabling the user to prepare nutritionally balanced meals while reducing the burden on the user.

[0479] "User information" refers to information such as the user's family structure, allergy information, food preferences, budget, etc.

[0480] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on user information.

[0481] "Automatic menu generation" refers to the process of using a generative AI model to automatically create a weekly menu based on user information.

[0482] "Creating an ingredient list" refers to the process of compiling a list of ingredients needed based on the generated menu.

[0483] An "online shopping API" refers to an application programming interface for obtaining inventory and price information from shopping sites via the Internet.

[0484] "Ingredients purchasing procedure" refers to the process by which a user purchases selected ingredients through an online shopping site.

[0485] "Delivery Arrangement" refers to the process of coordinating the delivery service of purchased ingredients to a specified address.

[0486] "Providing recipe videos" refers to the process of providing users with URLs of videos showing cooking methods that can be used as reference when the user cooks.

[0487] The system of the present invention allows users to efficiently prepare nutritionally balanced meals, and is targeted particularly at busy families with children and single-parent households. The system includes a series of processes: registering user information, automatically generating menus, generating a list of ingredients, purchasing ingredients and arranging for delivery, and providing recipe videos.

[0488] First, the user uses the device to enter user information such as family composition, allergy information, food preferences, budget, etc. Once the user has entered the information, the device sends the data to the server, which then stores the received information in a database.

[0489] The server then retrieves the saved user information, incorporates that data into a prompt, and passes it to the generative AI model. The generative AI model then analyzes the user information and automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can review it.

[0490] For example, if a user enters "2 adults, 1 child" as their family composition, "peanut allergy" as their allergy information, and "Japanese food" and "Italian food" as their food preferences, the server will send a prompt based on this information to the generative AI model. The generative AI model will generate a menu such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls," and the server will provide this information to the user.

[0491] Examples of prompts are:

[0492] "The user information is: family composition: 2 adults, 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0493] Based on the generated menu, the server creates a list of ingredients. The server uses an online shopping API to obtain ingredient availability and price information. Based on this information, the server generates the final ingredient list and sends it to the device. The user can then view the list and prices on their device.

[0494] The user uses their device to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site's API, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0495] Finally, the server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can play the provided recipe video on their device and cook while watching the video. As a specific example, the URL for the recipe video for "Teriyaki Chicken" "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[0496] Through this series of processes, the system enables users to efficiently prepare nutritionally balanced meals while reducing their burden. In particular, the combination of automatic menu generation using a generative AI model, obtaining ingredient inventory and price information using an online shopping API, and arranging delivery and providing recipe videos significantly reduces the user's workload.

[0497] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0498] Step 1: Enter your user information

[0499] The user uses the terminal to input user information such as family composition, allergy information, food preferences, budget, etc.

[0500] Specific behavior:

[0501] The user enters information such as "Family composition: 2 adults, 1 child," "Allergy information: peanuts," "Food preferences: Japanese, Italian," and "Budget: 10,000 yen" into the input form on the device.

[0502] Input: Individual pieces of information entered by the user

[0503] Output: User information data entered

[0504] Step 2: Submit user information

[0505] The terminal sends the input information to the server.

[0506] Specific behavior:

[0507] The device sends the collected information to the server using an HTTP POST request.

[0508] Input: User information data

[0509] Output: User information transferred to the server

[0510] Step 3: Save user information

[0511] The server stores the received information in a database.

[0512] Specific behavior:

[0513] The server parses the received data and stores information such as family composition, allergy information, food preferences, and budget in a database (e.g., MySQL).

[0514] Input: User information transferred to the server

[0515] Output: User information stored in the database

[0516] Step 4: Generate a prompt statement

[0517] The server retrieves the saved user information and generates a prompt.

[0518] Specific behavior:

[0519] The server reads the user information from the database and constructs a prompt message that reads, "User information: Family composition: 2 adults and 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0520] Input: User information stored in the database

[0521] Output: Generated prompt statement

[0522] Step 5: Automatic menu generation

[0523] The server passes the prompt text to a generative AI model, which automatically generates a menu that takes nutritional balance into consideration.

[0524] Specific behavior:

[0525] The server sends the prompt to the generative AI model, which then generates a weekly menu (e.g., "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Rolls").

[0526] Input: Generated prompt statement

[0527] Output: Generated weekly menu information

[0528] Step 6: Submit your menu

[0529] The server sends the generated menu to the terminal.

[0530] Specific behavior:

[0531] The server sends the generated menu information to the terminal as an HTTP response.

[0532] Input: Generated weekly menu information

[0533] Output: Menu information sent to the device

[0534] Step 7: Generate an ingredient list

[0535] The server analyzes the menu information and creates a list of necessary ingredients.

[0536] Specific behavior:

[0537] The server analyzes each dish on the menu and lists the ingredients needed (e.g., "500g chicken, 100ml soy sauce, 10g ginger").

[0538] Input: Generated weekly menu information

[0539] Output: List of ingredients needed

[0540] Step 8: Get ingredient availability and pricing information

[0541] The server uses an online shopping API to retrieve food availability and pricing information.

[0542] Specific behavior:

[0543] The server calls the API of the online shopping site (e.g., Amazon API) to obtain stock status and price information for each ingredient.

[0544] Input: List of ingredients needed

[0545] Output: A list of ingredients with availability and pricing information

[0546] Step 9: Submit your ingredient list

[0547] The server sends a list of ingredients with stock status and price information to the terminal.

[0548] Specific behavior:

[0549] The server sends the ingredient list to the terminal as an HTTP response.

[0550] Input: A list of ingredients with availability and pricing information

[0551] Output: The final ingredients list sent to the terminal

[0552] Step 10: Confirm and select ingredients

[0553] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase process.

[0554] Specific behavior:

[0555] The user can view the final ingredient list on the terminal, add the ingredients to be purchased to the cart, and complete the purchase procedure.

[0556] Input: Final ingredient list sent to the terminal

[0557] Output: Shopping list and shipping information

[0558] Step 11: Complete your purchase

[0559] The server sends the list of selected ingredients to the online shopping site's API to complete the purchase process.

[0560] Specific behavior:

[0561] The server sends the purchase information (e.g., ingredient list, shipping information) to the online shopping site's API to complete the purchase.

[0562] Input: Shopping list and shipping information

[0563] Output: Completed checkout

[0564] Step 12: Arrange for delivery

[0565] Based on the information regarding the completed purchase procedure, the server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for delivery.

[0566] Specific behavior:

[0567] The server sends purchase information (e.g., order ID, delivery address, specified date and time) to the delivery service API and arranges for delivery.

[0568] Input: Completed purchase

[0569] Output: Completed shipping process

[0570] Step 13: Submit a recipe video

[0571] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user.

[0572] Specific behavior:

[0573] The server retrieves the URL of the "Teriyaki Chicken" recipe video (e.g., "https: / / example.com / recipe / teriyaki_chicken") from the database and sends it to the terminal.

[0574] Input: Generated weekly menu information

[0575] Output: Recipe video URL sent to the device

[0576] (Application example 1)

[0577] 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."

[0578] For busy families with children or single parents, the complex and time-consuming process of efficiently preparing nutritionally balanced meals is a problem. There is a need to solve this problem and enable users to easily purchase ingredients and cook in physical stores. There is also a need to improve user convenience by providing effective suggestions in real time.

[0579] 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.

[0580] In this invention, the server includes a means for inputting user preferences and allergy information, a means for automatically generating a menu that takes nutritional balance into consideration using generation AI, and a means for making suggestions in real time in the physical store, thereby enabling users to easily purchase ingredients and cook in the physical store.

[0581] "User preference and allergy information" refers to information about preferences that a user takes into consideration when selecting food and allergic reactions to specific ingredients.

[0582] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate optimal results for specific purposes.

[0583] A "menu that takes into consideration nutritional balance" is a meal menu that includes an appropriate amount of nutrients necessary to maintain the user's health.

[0584] "Online database" means a repository of information accessible over the Internet, including food availability and pricing information.

[0585] A "cooking guide" is a document or video that describes the steps and methods that a user should follow when cooking.

[0586] "Real-time suggestions in physical stores" means providing users with information on appropriate ingredients and menus instantly via digital devices while they are in the actual store.

[0587] A "smartphone" is a mobile device that has the functions of a computer in addition to a mobile phone and can be used by installing applications.

[0588] This invention is a system that automates a series of processes for efficiently preparing nutritionally balanced meals for busy families with children or single parents. This system includes a means for inputting user preferences and allergy information, a means for automatically generating menus that take nutritional balance into consideration using generation AI, a means for listing necessary ingredients and retrieving information from an online database, a means for making real-time suggestions in a physical store, a means for purchasing ingredients and arranging for delivery, and a means for providing users with cooking guides.

[0589] Overall flow

[0590] First, users use a device to input their own and their family's preferences and allergy information. This allows the system to select foods that meet individual needs and collect basic data for creating menus. This data is sent to a server, which uses AI to automatically create menus that take nutritional balance into consideration. The generated menus are then presented to the user in real time, after which a list of the necessary ingredients is generated. Furthermore, the system retrieves information on ingredient availability and prices from an online database, helping users to easily purchase ingredients in physical stores.

[0591] Hardware and software used

[0592] Device: Smartphone

[0593] Server: The server is the central system that holds the generative AI model and performs data analysis.

[0594] Online database: Get ingredient availability and pricing information from third-party APIs.

[0595] Generative AI model: An AI that automatically generates menus that take nutritional balance into consideration.

[0596] Processing flow

[0597] 1. Collecting user information: The device collects information from the user, such as family composition, allergy information, food preferences, budget, etc., and sends it to the server. For example, the user enters "2 adults, 1 child, peanut allergy, prefers Japanese and Italian food."

[0598] 2. Automatic menu generation: Based on the received user information, the server uses a generative AI model to generate a nutritionally balanced menu for one week. For example, a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese" may be generated.

[0599] 3. Generate a list of required ingredients: The server generates a list of required ingredients based on the generated menu information and obtains ingredient stock and price information from the online database API. For example, a list of "500g of chicken, 100ml of soy sauce, and 10g of ginger" might be generated.

[0600] 4. Real-time suggestions: Users can receive real-time suggestions using their smartphones in-store. Specifically, the location and stock status of ingredients needed for a meal are immediately displayed.

[0601] 5. Purchase and delivery: The user selects the ingredients they need and completes the purchase process. The server uses the online shopping API to complete the order and arrange for delivery.

[0602] 6. Providing cooking guides: The server provides users with cooking guides (such as recipe videos) corresponding to the menu. For example, users can watch a video showing the cooking steps for "Teriyaki Chicken."

[0603] Specific examples

[0604] If a user inputs "2 adults and 1 child, peanut allergy, likes Japanese and Italian food," the server will use generative AI to generate a menu, offering options such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." Based on this, an ingredient list is generated, and information on ingredients such as chicken, soy sauce, and ginger is retrieved from an online database. Furthermore, real-time suggestions are made to make in-store ingredient purchases easy, and after the user selects the necessary ingredients and completes the purchase process, a recipe video is provided as a cooking guide.

[0605] Prompt Sentence Examples

[0606] The user enters the following information into the terminal:

[0607] Family composition: 2 adults, 1 child

[0608] Allergy Information: Peanut Allergy

[0609] Food preferences: Japanese, Italian

[0610] Budget: 10,000 yen

[0611] This will support the invention's goal of preparing efficient and nutritionally balanced meals, and improve user convenience.

[0612] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0613] Step 1:

[0614] Users use a terminal to input their own and their family's preferences and allergy information. The terminal collects specific information from the user, such as "two adults, one child, peanut allergy, preference for Japanese and Italian food, budget of 10,000 yen." The input information is sent from the terminal to the server. The input data includes family composition, allergy information, food preferences, budget, etc.

[0615] Step 2:

[0616] The server analyzes the received user information and passes it to the generative AI model. The generative AI model automatically generates a menu that takes nutritional balance into consideration based on the input data. For example, it outputs a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." The server then sends this menu information to the device.

[0617] Step 3:

[0618] The terminal displays the received menu information. The user checks the weekly menu and a list of necessary ingredients is displayed. The server generates a list of necessary ingredients based on the generated menu. The input data is the menu information, and the output data is the list of ingredients.

[0619] Step 4:

[0620] The server uses the API of an online database to obtain stock status and price information for the required ingredients. To do this, the server accesses the API, sends specific ingredient information such as "500g of chicken, 100ml of soy sauce, 10g of ginger" as input, and receives stock status and price information as output. This information is sent to the terminal and provided to the user.

[0621] Step 5:

[0622] The user uses the device to check and select ingredients suggested in real time. In the physical store, the device suggests to the user the location and stock status of ingredients in real time. For example, it may indicate to the user that "chicken is in the refrigerated section, and soy sauce is in the condiment section." The user then adds the ingredients they need to their cart.

[0623] Step 6:

[0624] Based on the ingredients selected by the user, the terminal completes the purchase process. The server then uses the online shopping site's API to send the order information and complete the purchase process. Once the purchase process is complete, the server contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0625] Step 7:

[0626] The server retrieves the URL of the cooking guide (such as a recipe video) corresponding to the menu from the database and sends it to the device. The user cooks the meal while watching the recipe video on the device. For example, the URL "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[0627] Example prompt sentence:

[0628] The user enters the following information into the terminal:

[0629] Family composition: 2 adults, 1 child

[0630] Allergy Information: Peanut Allergy

[0631] Food preferences: Japanese, Italian

[0632] Budget: 10,000 yen

[0633] 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.

[0634] The present invention provides a system for efficiently preparing nutritionally balanced meals that takes into account the user's emotions as well as their preferences and allergies. This system is capable of recognizing the user's emotions and adjusting menus and optimizing cooking procedures based on the user's emotions.

[0635] Registering user information

[0636] The device uses an emotion engine to recognize the user's emotions, in addition to information entered by the user, such as family composition, allergy information, food preferences, and weekly food budget. Once the user enters this information, the device sends the data to the server.

[0637] Examples:

[0638] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information. Furthermore, the emotion engine detects that the user is "feeling stressed."

[0639] Automatic menu generation and emotion regulation

[0640] The server analyzes the received user information and passes it to the generation AI. The generation AI automatically generates a weekly menu that takes nutritional balance into consideration. It also adjusts the menu to recommend specific ingredients and dishes based on the user's emotions recognized by the emotion engine. This menu information is sent from the server to the device so that the user can review it.

[0641] Examples:

[0642] Based on the information such as "2 adults, 1 child," "peanut allergy," "Japanese food," "Italian food," and "feeling stressed," the server uses generative AI to generate tailored menus such as "Monday: Chicken teriyaki (high in ginger, which has a relaxing effect)" and "Tuesday: Spaghetti Bolognese (a menu high in nutrients to energize you on Wednesday)."

[0643] Generate a list of ingredients needed

[0644] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[0645] Examples:

[0646] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[0647] Purchasing ingredients and arranging delivery

[0648] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0649] Examples:

[0650] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0651] Providing recipe videos and emotional feedback

[0652] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user plays the provided recipe video on their device and proceeds with the cooking while watching the video. In addition, the emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on that feedback.

[0653] Examples:

[0654] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking. If the user becomes "confused" during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0655] With these functions, the system helps users prepare nutritionally balanced meals easily and efficiently. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing user stress. This system makes it easier to balance work and home life and maintain a healthy diet.

[0656] The processing flow will be explained below.

[0657] Step 1:

[0658] The user logs in to the application using a device. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The emotion engine recognizes the user's emotions through the device's camera and voice input. This information is sent from the device to the server.

[0659] Step 2:

[0660] The server analyzes the received user information and passes it on as the data needed for the generation AI, which then combines the user's input information with the emotional information obtained from the emotion engine to automatically generate a week's worth of menus.

[0661] Step 3:

[0662] The AI ​​creates a menu that takes nutritional balance into consideration. The emotion engine also takes into account emotional information, adjusting the menu to include specific ingredients and dishes that correspond to the user's emotions. For example, if the user is "feeling stressed," the system will recommend dishes that contain ingredients with a relaxing effect.

[0663] Step 4:

[0664] The server sends the generated menu to the user's device, where the user can check the menu for the week (e.g., "Monday: Teriyaki chicken (relaxing effect) / Tuesday: Spaghetti Bolognese").

[0665] Step 5:

[0666] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," the server generates an ingredient list of "500g of chicken, 100ml of soy sauce, and 10g of ginger."

[0667] Step 6:

[0668] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates a final ingredient list based on the information obtained and sends it to the user's device.

[0669] Step 7:

[0670] The user checks the shopping list provided on the terminal, selects the ingredients they need, and proceeds with the purchase. The terminal then sends the selected ingredients list to the server.

[0671] Step 8:

[0672] The server sends the order for ingredients to the online shopping site and completes the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery. A notification is sent to the user's device.

[0673] Step 9:

[0674] The server retrieves the URL of the recipe video corresponding to the menu from the database and sends it to the user's device. The user can then cook the dish while playing the recipe video on their device.

[0675] Step 10:

[0676] While cooking, the device's emotion engine recognizes the user's emotions in real time. If the user feels confused or stressed, the server will simplify the cooking steps and provide additional instructions based on the emotion engine's feedback.

[0677] Through these processing steps, the system enables users to efficiently prepare nutritionally balanced meals. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing stress for the user.

[0678] Example 2

[0679] 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."

[0680] Conventional meal recommendation systems can provide nutritionally balanced menus based on the user's preferences and allergy information, but they do not take into account the user's emotions or psychological state. This can cause users to feel stressed or confused, and they are unable to provide satisfactory service. Furthermore, there is a lack of a means to consistently and efficiently manage the process from purchasing ingredients to cooking. Therefore, improving user satisfaction and convenience is a challenge.

[0681] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting a user's preferences, allergy information, family composition, and weekly food budget; a means for recognizing emotions; a means for automatically generating and adjusting a menu that takes nutritional balance into consideration based on the user's preferences, allergy information, and emotional information using a generation AI; a means for listing necessary ingredients and acquiring information from online shopping sites; a means for purchasing ingredients and arranging for delivery; a means for providing the user with a recipe video; and a means for recognizing the user's emotions in real time during cooking and optimizing the cooking procedure based on the feedback. This enables individual adjustments based on the user's emotions, reducing stress and confusion and efficiently supporting the user from proposing menus to purchasing ingredients and cooking.

[0682] A "user" is an entity that uses the system to input preferences, allergy information, and emotional information, and receives menu suggestions, purchases ingredients, and recipes.

[0683] "Preferences" refers to information about ingredients and types of dishes that a user particularly likes, and are factors that are taken into consideration when the system generates a menu.

[0684] "Allergy information" is information about ingredients to which the user has an allergy, and is an element that is taken into consideration as ingredients to be avoided when the system generates a menu.

[0685] "Family composition" is information about the number of people and age groups in the user's household, and is a factor used by the system to determine the quantity and type of food when generating a menu.

[0686] The "weekly food budget" is information about the amount of money a user can spend on ingredients and meals per week, and is a factor that is taken into account as an economic constraint when the system generates menus.

[0687] "Emotion" refers to a psychological state that the system recognizes by analyzing the user's facial expressions and tone of voice, and is an element used to adjust menus and optimize cooking procedures.

[0688] An "emotion engine" is a combination of hardware and software for analyzing and recognizing a user's emotions, and is a means of understanding the user's psychological state.

[0689] "Generative AI" is an artificial intelligence program that automatically generates and adjusts menus that take nutritional balance into consideration based on input user information.

[0690] An "online shopping site" is a website where ingredients and other products can be purchased via the Internet, and is a source of information from which the system obtains information on ingredient availability and prices.

[0691] A "recipe video" is video content that visually shows specific steps for cooking, and allows users to cook while watching the video.

[0692] "Real-time" refers to the immediacy with which the system instantly recognizes and processes the user's input and emotions, which is an important element when providing feedback during cooking.

[0693] "Feedback" refers to the response and adjustments made by the system based on the user's emotional state, etc., and is a means used by the user to cook in optimal conditions.

[0694] "Optimizing cooking steps" means that the system adjusts the cooking process and instructions according to the user's emotions and situation, providing a more effective and satisfying cooking experience.

[0695] This system generates nutritionally balanced menus based on the user's preferences, allergy information, emotional information, family composition, and weekly food budget, lists the necessary ingredients, and provides support for purchasing, arranging delivery, and cooking. This system consists of a user terminal, a server, an emotion engine, a generation AI, and an online shopping site API.

[0696] Registering user information

[0697] Users input their preferences, allergies, family composition, and weekly food budget using a terminal, and this information is then sent from the terminal to the server.

[0698] Examples:

[0699] The user enters "2 adults, 1 child" into the terminal, sets "peanut allergy" as allergy information, "Japanese food" and "Italian food" as preferences, and sets the budget to "5,000 yen." This information is sent from the terminal to the server.

[0700] Emotion recognition

[0701] The emotion engine installed in the device recognizes the user's emotions in real time and sends that information to the server.

[0702] Examples:

[0703] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that the user is "feeling stressed," and sends this information to the server.

[0704] Automatic menu generation

[0705] The server analyzes the received user information and emotional information and creates prompts for the AI, which then generates a weekly menu that takes nutritional balance into consideration.

[0706] Examples:

[0707] The server inputs the following as a prompt to the generation AI:

[0708] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[0709] Based on this information, please suggest a nutritionally balanced menu for one week.

[0710] This allows the generation AI to generate a menu.

[0711] Emotion regulation and regeneration

[0712] The server re-evaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The adjusted menu is then passed back to the generation AI to finalize the menu.

[0713] Examples:

[0714] The generated menu becomes a weekly plan that includes "Teriyaki Chicken with Ginger, which has a relaxing effect." The emotion engine recommends ingredients and dishes that are suitable for the "stressed" state. The final menu is confirmed as "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese."

[0715] Generate an ingredient list

[0716] The server creates a list of ingredients based on the finalized menu, and uses the API of the online shopping site to obtain stock status and price information and provides it to the user.

[0717] Examples:

[0718] The server creates a list of ingredients such as "500g chicken, 100ml soy sauce, 10g ginger" and uses the API to check stock and price information, providing this information to the user.

[0719] Purchasing ingredients and arranging delivery

[0720] The user checks the shopping list on the terminal, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completes the purchase, and notifies the delivery service of the order ID, delivery address, and specified date and time.

[0721] Examples:

[0722] The user adds "chicken, soy sauce, ginger" to the cart and completes the purchase. After completing the order, the server uses the online shopping API to contact the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0723] Providing recipe videos and emotional feedback while cooking

[0724] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. While the user is cooking, the device's emotion engine recognizes emotions in real time and optimizes the cooking procedure based on the feedback.

[0725] Examples:

[0726] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0727] As described above, the present system supports users in efficiently preparing nutritionally balanced meals, and can also improve psychological satisfaction, particularly by making adjustments based on the user's emotions.

[0728] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0729] Step 1: Register user information

[0730] Users use a device to input their family composition, allergy information, food preferences, and weekly food budget. The device stores this information in a database and sends it to the server. The input data includes family composition, allergy information, preferences, and budget. The output data is a dataset that compiles this user information.

[0731] Specific behavior:

[0732] The user enters into the terminal the family composition as "2 adults, 1 child," allergy information as "peanut allergy," preferences as "Japanese food" and "Italian food," and budget as "5,000 yen," and this information is sent to the server.

[0733] Step 2: Recognize emotions

[0734] The emotion engine installed in the device recognizes the user's emotions in real time. The input data includes the user's facial expressions and tone of voice, which are analyzed to extract emotional information. The output data is the recognized emotional information.

[0735] Specific behavior:

[0736] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that they are "feeling stressed," and sends this information to the server.

[0737] Step 3: Automatic menu generation

[0738] The server analyzes user information and emotional information, and creates and inputs prompts to the generation AI. The input data includes user information and emotional information, and the generation AI uses this to generate a week's worth of menus that take nutritional balance into consideration. The output data is the generated menu information.

[0739] Specific behavior:

[0740] The server inputs the following prompt to the generated AI:

[0741] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[0742] Based on this information, please suggest a nutritionally balanced menu for one week.

[0743] The generation AI generates a menu, which is sent to the server.

[0744] Step 4: Emotional regulation and regeneration

[0745] The server reevaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The input data are the generated menu and the user's emotion information, and the emotion engine makes adjustments based on this. The output data is the adjusted final menu.

[0746] Specific behavior:

[0747] The generated menu is adjusted into a weekly plan that includes "Chicken Teriyaki with Ginger, which has a relaxing effect." The final menu is finalized as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese."

[0748] Step 5: Generate an ingredient list

[0749] The server creates a list of ingredients based on the final menu. The input data is the final menu, and it uses the API of an online shopping site to obtain stock availability and price information. The output data is the list of ingredients.

[0750] Specific behavior:

[0751] The server creates a list of ingredients, such as "500g chicken, 100ml soy sauce, 10g ginger," and uses an online shopping API to check stock and price information, which is then provided to the user.

[0752] Step 6: Purchase ingredients and arrange delivery

[0753] The user checks the provided shopping list on their device, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completing the purchase process. The delivery service is then notified of the order ID, delivery address, and specified date and time. The input data is the list of ingredients selected by the user, and the output data is confirmation that the order has been completed.

[0754] Specific behavior:

[0755] The user adds "chicken, soy sauce, and ginger" to the cart and completes the purchase. The server completes the order using the online shopping site API and contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0756] Step 7: Providing recipe videos and emotional feedback during cooking

[0757] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The device's emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on the feedback. The input data is the user's emotional state while cooking, and the output data is the optimized cooking steps.

[0758] Specific behavior:

[0759] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[0760] The above is a detailed description of the specific processing flow of this system and the operation at each step.

[0761] (Application example 2)

[0762] 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."

[0763] While conventional meal preparation systems can take into account a user's preferences and allergy information, they have difficulty optimizing menu suggestions and cooking procedures that reflect the user's emotional state. As a result, they are unable to respond adequately to situations where the user is likely to feel stressed, which can result in meal preparation being time-consuming and inefficient. Furthermore, the lack of real-time emotional cooking support often leaves users confused.

[0764] 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 inputting the user's preferences, allergy information, and emotions, means for automatically generating a menu that takes nutritional balance into consideration using a generation AI and adjusting the menu based on emotional information, means for listing necessary ingredients and acquiring information from online shopping sites, means for purchasing ingredients and arranging for delivery, and means for providing the user with recipe videos, acquiring emotional feedback in real time during cooking, and optimizing cooking procedures. This makes it possible to adjust the menu and optimize cooking procedures according to the user's emotional state, resulting in efficient and stress-free meal preparation.

[0765] "User preference and allergy information" is information about preferences and allergies that are individually input by the user.

[0766] "Emotion information" is data that indicates the user's current psychological state, and is information obtained using the emotion engine.

[0767] "Generative AI" is an artificial intelligence model that automatically generates menus that take nutritional balance into consideration based on provided data.

[0768] The "means for adjusting the menu" refers to a method or function for adjusting the generated menu to an optimal one, taking into account the user's emotional information.

[0769] An "online shopping site" is an e-commerce platform for purchasing products over the Internet.

[0770] "Recipe videos" are video content that explains cooking steps and methods.

[0771] "Emotional feedback" is information that acquires the user's emotional information in real time and adjusts the system's behavior based on that information.

[0772] The "means for optimizing the cooking procedure" refers to a method or function for changing the cooking procedure to an optimal form based on the user's emotional information.

[0773] The "ingredient list" is a list of all ingredients required based on the generated menu.

[0774] "Delivery arrangement" refers to carrying out procedures to deliver the selected ingredients to a location designated by the user.

[0775] The present invention is a system that efficiently prepares nutritionally balanced meals by taking into account the user's preferences, allergy information, and emotional information. This system is composed of a user terminal and a server, and performs the following processes.

[0776] Registering user information

[0777] First, the user uses the device to input information such as family composition, allergies, favorite ingredients, and weekly food budget. The device is also equipped with an emotion engine that captures emotional information from the user's facial expressions in real time. This information is then sent to the server and stored in a database.

[0778] Automatic menu generation and emotion regulation

[0779] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. It also adjusts the generated menu based on emotional information obtained from the emotion engine. For example, if it detects that the user is "feeling stressed," it will suggest a menu that includes many ingredients with a relaxing effect.

[0780] Generate a list of ingredients needed

[0781] The server creates a list of ingredients based on the generated menu, and then uses the API of the online shopping site to obtain information on ingredient availability and prices, which it then provides to the user.

[0782] Purchasing ingredients and arranging delivery

[0783] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the order information to the online shopping site to complete the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0784] Providing recipe videos and emotional feedback

[0785] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user cooks while playing the provided recipe video on their device. The emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking procedure based on that feedback. Specifically, if the server detects that the user is "confused," it automatically provides simplifications or additional explanations.

[0786] Example of a system

[0787] If a user inputs their family composition (two adults, one child), their "peanut allergy," and their "preference for Japanese and Italian food," and the emotion engine detects that they are "feeling stressed," the generative AI model automatically generates and adjusts a menu suggestion, such as "Monday: Chicken Teriyaki (high in ginger, which has a relaxing effect) and Tuesday: Spaghetti Bolognese." The user confirms this, purchases the necessary ingredients from an online shopping site, and cooks while watching a recipe video. If confusion is detected during cooking, a prompt message will be displayed, such as, "If you find the steps difficult, we will explain in detail how to fry the chicken first and then add the ginger and soy sauce. We also provide a detailed explanation from 01:45 to 02:10 in the video."

[0788] In this way, the system adjusts menus and optimizes cooking procedures according to the user's emotional state, supporting efficient and stress-free meal preparation.

[0789] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0790] Step 1:

[0791] The user uses a device to input information such as family composition, allergy information, favorite ingredients, and weekly food budget. The emotion engine then captures the user's facial expressions and obtains emotional information. The input data includes text data such as family composition and allergy information, as well as image data, and the organized user information is sent to the server as output.

[0792] Step 2:

[0793] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. The user information is used as input data, and a weekly menu is generated as output. In addition, based on emotional information, the menu is adjusted to include more ingredients that have a relaxing effect. Specifically, the system refers to the nutrition database and emotional database to select an appropriate menu.

[0794] Step 3:

[0795] The server creates a list of ingredients based on the generated menu and uses the online shopping site's API to obtain the availability and price information of those ingredients. The generated menu and the online shopping site's API endpoint are used as input data, and the list of ingredients, their availability, and price information is generated as output. Specifically, the server sends an API request and analyzes the received data to create the list.

[0796] Step 4:

[0797] The user uses a terminal to check the provided shopping list, select the ingredients they need, and complete the purchase procedure. The created ingredient list and the user's selection information are used as input data, and the final shopping list is determined as output. Specific actions include pressing the purchase confirmation button on the user interface.

[0798] Step 5:

[0799] The server sends the order information for the selected ingredients to the online shopping site to complete the purchase process. It also contacts the delivery service with the order ID, delivery address, and specified date and time to arrange delivery. The input data is the final purchase list and delivery address information, and the output is a confirmation of the order and the completion of delivery arrangements. Specifically, it sends the order information using an API request and makes a request to the delivery service.

[0800] Step 6:

[0801] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The generated menu is used as input data, and the URL of the recipe video is generated as output. Specifically, the database is queried using the menu name as a key to retrieve the corresponding video URL.

[0802] Step 7:

[0803] The user cooks while playing a recipe video provided on the device. While cooking, the device uses an emotion engine to obtain the user's emotions in real time and optimizes the cooking steps based on that feedback. Real-time emotion information is used as input data, and optimized cooking steps are provided as output. Specifically, support is provided, such as displaying prompts if the user is confused.

[0804] 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.

[0805] 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.

[0806] 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.

[0807] [Third embodiment]

[0808] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0809] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0810] 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).

[0811] 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.

[0812] 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.

[0813] 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).

[0814] 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.

[0815] 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.

[0816] 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.

[0817] 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.

[0818] 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.

[0819] 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."

[0820] The purpose of this system is to automate the process of efficiently preparing nutritionally balanced meals for busy families with children or single parents. To achieve this, the system provides the following main functions:

[0821] Registering user information

[0822] The device collects information entered by the user, such as family composition, allergy information, food preferences, weekly food budget, etc. Once the user enters this information, the device sends the data to the server.

[0823] Examples:

[0824] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information.

[0825] Automatic menu generation

[0826] The server analyzes the received user information and passes it to the generation AI, which then automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can view it.

[0827] Examples:

[0828] Based on user information including "2 adults, 1 child," "peanut allergy," "Japanese food," and "Italian," the server uses generative AI to generate menus such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls."

[0829] Generate a list of ingredients needed

[0830] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[0831] Examples:

[0832] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[0833] Purchasing ingredients and arranging delivery

[0834] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0835] Examples:

[0836] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[0837] Providing recipe videos

[0838] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can then play the provided recipe video on their device and proceed with cooking while watching the video.

[0839] Examples:

[0840] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking.

[0841] With each of the above functions, this system helps users prepare nutritionally balanced meals easily and efficiently. In particular, it can significantly reduce users' time and effort through a series of processes: automatic menu generation using generative AI, linking with online shopping sites for ingredient lists, arranging delivery, and providing recipe videos. This system makes it easier to balance work and home life and maintain a healthy diet.

[0842] The processing flow will be explained below.

[0843] Step 1:

[0844] A user logs in to the system using a terminal. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The terminal then sends this information to the server.

[0845] Step 2:

[0846] The server analyzes the received user information and provides the AI ​​with data such as family composition, allergies, and food preferences based on the analyzed information.

[0847] Step 3:

[0848] The AI ​​automatically generates a weekly menu that takes nutritional balance into consideration based on the provided data, and the generated menu is sent back to the server.

[0849] Step 4:

[0850] The server sends the generated menu to the user's device, where the user can view the weekly menu (e.g., "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll...").

[0851] Step 5:

[0852] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," it adds items such as "500g of chicken, 100ml of soy sauce, and 10g of ginger" to the list.

[0853] Step 6:

[0854] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates the final ingredients list based on the information obtained.

[0855] Step 7:

[0856] The server sends the ingredient list and a purchase link to the user's device. The user checks the provided shopping list on the device, selects the ingredients they need, and adds them to their cart.

[0857] Step 8:

[0858] When the user completes the purchase, the terminal sends the list of selected ingredients to the server, which then sends the ingredient order to the online shopping site and completes the purchase.

[0859] Step 9:

[0860] The server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for the ingredients to be delivered. Details of the delivery arrangements are sent to the user's terminal.

[0861] Step 10:

[0862] The server retrieves the URL of the recipe video corresponding to the menu from the database. For example, it retrieves the recipe video URL for "Teriyaki Chicken" ("https: / / example.com / recipe / teriyaki_chicken").

[0863] Step 11:

[0864] The server sends the URL of the recipe video to the user's device, where the user can play the recipe video and cook the dish while watching the video.

[0865] Through these steps, the system helps users efficiently prepare nutritionally balanced meals.

[0866] Example 1

[0867] 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."

[0868] In busy families with children or single parents, it is often difficult to efficiently prepare nutritionally balanced meals. In these households, time is limited, and the time and effort required for carefully selecting ingredients, planning menus, purchasing ingredients, and cooking can be a significant burden. A system that solves this problem and allows users to easily prepare nutritionally balanced meals is needed.

[0869] 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.

[0870] In this invention, the server includes means for inputting information such as the user's family composition, allergy information, ingredient preferences, budget, etc., means for automatically generating a menu that takes nutritional balance into consideration using a generative AI model, means for creating a list of necessary ingredients based on the generated menu, means for acquiring ingredient availability and price information using an online shopping API, means for purchasing ingredients and arranging for delivery, and means for providing the user with a URL for a recipe video, thereby enabling the user to prepare nutritionally balanced meals while reducing the burden on the user.

[0871] "User information" refers to information such as the user's family structure, allergy information, food preferences, budget, etc.

[0872] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on user information.

[0873] "Automatic menu generation" refers to the process of using a generative AI model to automatically create a weekly menu based on user information.

[0874] "Creating an ingredient list" refers to the process of compiling a list of ingredients needed based on the generated menu.

[0875] An "online shopping API" refers to an application programming interface for obtaining inventory and price information from shopping sites via the Internet.

[0876] "Ingredients purchasing procedure" refers to the process by which a user purchases selected ingredients through an online shopping site.

[0877] "Delivery Arrangement" refers to the process of coordinating the delivery service of purchased ingredients to a specified address.

[0878] "Providing recipe videos" refers to the process of providing users with URLs of videos showing cooking methods that can be used as reference when the user cooks.

[0879] The system of the present invention allows users to efficiently prepare nutritionally balanced meals, and is targeted particularly at busy families with children and single-parent households. The system includes a series of processes: registering user information, automatically generating menus, generating a list of ingredients, purchasing ingredients and arranging for delivery, and providing recipe videos.

[0880] First, the user uses the device to enter user information such as family composition, allergy information, food preferences, budget, etc. Once the user has entered the information, the device sends the data to the server, which then stores the received information in a database.

[0881] The server then retrieves the saved user information, incorporates that data into a prompt, and passes it to the generative AI model. The generative AI model then analyzes the user information and automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can review it.

[0882] For example, if a user enters "2 adults, 1 child" as their family composition, "peanut allergy" as their allergy information, and "Japanese food" and "Italian food" as their food preferences, the server will send a prompt based on this information to the generative AI model. The generative AI model will generate a menu such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls," and the server will provide this information to the user.

[0883] Examples of prompts are:

[0884] "The user information is: family composition: 2 adults, 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0885] Based on the generated menu, the server creates a list of ingredients. The server uses an online shopping API to obtain ingredient availability and price information. Based on this information, the server generates the final ingredient list and sends it to the device. The user can then view the list and prices on their device.

[0886] The user uses their device to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site's API, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[0887] Finally, the server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can play the provided recipe video on their device and cook while watching the video. As a specific example, the URL for the recipe video for "Teriyaki Chicken" "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[0888] Through this series of processes, the system enables users to efficiently prepare nutritionally balanced meals while reducing their burden. In particular, the combination of automatic menu generation using a generative AI model, obtaining ingredient inventory and price information using an online shopping API, and arranging delivery and providing recipe videos significantly reduces the user's workload.

[0889] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0890] Step 1: Enter your user information

[0891] The user uses the terminal to input user information such as family composition, allergy information, food preferences, budget, etc.

[0892] Specific behavior:

[0893] The user enters information such as "Family composition: 2 adults, 1 child," "Allergy information: peanuts," "Food preferences: Japanese, Italian," and "Budget: 10,000 yen" into the input form on the device.

[0894] Input: Individual pieces of information entered by the user

[0895] Output: User information data entered

[0896] Step 2: Submit user information

[0897] The terminal sends the input information to the server.

[0898] Specific behavior:

[0899] The device sends the collected information to the server using an HTTP POST request.

[0900] Input: User information data

[0901] Output: User information transferred to the server

[0902] Step 3: Save user information

[0903] The server stores the received information in a database.

[0904] Specific behavior:

[0905] The server parses the received data and stores information such as family composition, allergy information, food preferences, and budget in a database (e.g., MySQL).

[0906] Input: User information transferred to the server

[0907] Output: User information stored in the database

[0908] Step 4: Generate a prompt statement

[0909] The server retrieves the saved user information and generates a prompt.

[0910] Specific behavior:

[0911] The server reads the user information from the database and constructs a prompt message that reads, "User information: Family composition: 2 adults and 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[0912] Input: User information stored in the database

[0913] Output: Generated prompt statement

[0914] Step 5: Automatic menu generation

[0915] The server passes the prompt text to a generative AI model, which automatically generates a menu that takes nutritional balance into consideration.

[0916] Specific behavior:

[0917] The server sends the prompt to the generative AI model, which then generates a weekly menu (e.g., "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Rolls").

[0918] Input: Generated prompt statement

[0919] Output: Generated weekly menu information

[0920] Step 6: Submit your menu

[0921] The server sends the generated menu to the terminal.

[0922] Specific behavior:

[0923] The server sends the generated menu information to the terminal as an HTTP response.

[0924] Input: Generated weekly menu information

[0925] Output: Menu information sent to the device

[0926] Step 7: Generate an ingredient list

[0927] The server analyzes the menu information and creates a list of necessary ingredients.

[0928] Specific behavior:

[0929] The server analyzes each dish on the menu and lists the ingredients needed (e.g., "500g chicken, 100ml soy sauce, 10g ginger").

[0930] Input: Generated weekly menu information

[0931] Output: List of ingredients needed

[0932] Step 8: Get ingredient availability and pricing information

[0933] The server uses an online shopping API to retrieve food availability and pricing information.

[0934] Specific behavior:

[0935] The server calls the API of the online shopping site (e.g., Amazon API) to obtain stock status and price information for each ingredient.

[0936] Input: List of ingredients needed

[0937] Output: A list of ingredients with availability and pricing information

[0938] Step 9: Submit your ingredient list

[0939] The server sends a list of ingredients with stock status and price information to the terminal.

[0940] Specific behavior:

[0941] The server sends the ingredient list to the terminal as an HTTP response.

[0942] Input: A list of ingredients with availability and pricing information

[0943] Output: The final ingredients list sent to the terminal

[0944] Step 10: Confirm and select ingredients

[0945] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase process.

[0946] Specific behavior:

[0947] The user can view the final ingredient list on the terminal, add the ingredients to be purchased to the cart, and complete the purchase procedure.

[0948] Input: Final ingredient list sent to the terminal

[0949] Output: Shopping list and shipping information

[0950] Step 11: Complete your purchase

[0951] The server sends the list of selected ingredients to the online shopping site's API to complete the purchase process.

[0952] Specific behavior:

[0953] The server sends the purchase information (e.g., ingredient list, shipping information) to the online shopping site's API to complete the purchase.

[0954] Input: Shopping list and shipping information

[0955] Output: Completed checkout

[0956] Step 12: Arrange for delivery

[0957] Based on the information regarding the completed purchase procedure, the server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for delivery.

[0958] Specific behavior:

[0959] The server sends purchase information (e.g., order ID, delivery address, specified date and time) to the delivery service API and arranges for delivery.

[0960] Input: Completed purchase

[0961] Output: Completed shipping process

[0962] Step 13: Submit a recipe video

[0963] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user.

[0964] Specific behavior:

[0965] The server retrieves the URL of the "Teriyaki Chicken" recipe video (e.g., "https: / / example.com / recipe / teriyaki_chicken") from the database and sends it to the terminal.

[0966] Input: Generated weekly menu information

[0967] Output: Recipe video URL sent to the device

[0968] (Application example 1)

[0969] 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."

[0970] For busy families with children or single parents, the complex and time-consuming process of efficiently preparing nutritionally balanced meals is a problem. There is a need to solve this problem and enable users to easily purchase ingredients and cook in physical stores. There is also a need to improve user convenience by providing effective suggestions in real time.

[0971] 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.

[0972] In this invention, the server includes a means for inputting user preferences and allergy information, a means for automatically generating a menu that takes nutritional balance into consideration using generation AI, and a means for making suggestions in real time in the physical store, thereby enabling users to easily purchase ingredients and cook in the physical store.

[0973] "User preference and allergy information" refers to information about preferences that a user takes into consideration when selecting food and allergic reactions to specific ingredients.

[0974] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate optimal results for specific purposes.

[0975] A "menu that takes into consideration nutritional balance" is a meal menu that includes an appropriate amount of nutrients necessary to maintain the user's health.

[0976] "Online database" means a repository of information accessible over the Internet, including food availability and pricing information.

[0977] A "cooking guide" is a document or video that describes the steps and methods that a user should follow when cooking.

[0978] "Real-time suggestions in physical stores" means providing users with information on appropriate ingredients and menus instantly via digital devices while they are in the actual store.

[0979] A "smartphone" is a mobile device that has the functions of a computer in addition to a mobile phone and can be used by installing applications.

[0980] This invention is a system that automates a series of processes for efficiently preparing nutritionally balanced meals for busy families with children or single parents. This system includes a means for inputting user preferences and allergy information, a means for automatically generating menus that take nutritional balance into consideration using generation AI, a means for listing necessary ingredients and retrieving information from an online database, a means for making real-time suggestions in a physical store, a means for purchasing ingredients and arranging for delivery, and a means for providing users with cooking guides.

[0981] Overall flow

[0982] First, users use a device to input their own and their family's preferences and allergy information. This allows the system to select foods that meet individual needs and collect basic data for creating menus. This data is sent to a server, which uses AI to automatically create menus that take nutritional balance into consideration. The generated menus are then presented to the user in real time, after which a list of the necessary ingredients is generated. Furthermore, the system retrieves information on ingredient availability and prices from an online database, helping users to easily purchase ingredients in physical stores.

[0983] Hardware and software used

[0984] Device: Smartphone

[0985] Server: The server is the central system that holds the generative AI model and performs data analysis.

[0986] Online database: Get ingredient availability and pricing information from third-party APIs.

[0987] Generative AI model: An AI that automatically generates menus that take nutritional balance into consideration.

[0988] Processing flow

[0989] 1. Collecting user information: The device collects information from the user, such as family composition, allergy information, food preferences, budget, etc., and sends it to the server. For example, the user enters "2 adults, 1 child, peanut allergy, prefers Japanese and Italian food."

[0990] 2. Automatic menu generation: Based on the received user information, the server uses a generative AI model to generate a nutritionally balanced menu for one week. For example, a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese" may be generated.

[0991] 3. Generate a list of required ingredients: The server generates a list of required ingredients based on the generated menu information and obtains ingredient stock and price information from the online database API. For example, a list of "500g of chicken, 100ml of soy sauce, and 10g of ginger" might be generated.

[0992] 4. Real-time suggestions: Users can receive real-time suggestions using their smartphones in-store. Specifically, the location and stock status of ingredients needed for a meal are immediately displayed.

[0993] 5. Purchase and delivery: The user selects the ingredients they need and completes the purchase process. The server uses the online shopping API to complete the order and arrange for delivery.

[0994] 6. Providing cooking guides: The server provides users with cooking guides (such as recipe videos) corresponding to the menu. For example, users can watch a video showing the cooking steps for "Teriyaki Chicken."

[0995] Specific examples

[0996] If a user inputs "2 adults and 1 child, peanut allergy, likes Japanese and Italian food," the server will use generative AI to generate a menu, offering options such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." Based on this, an ingredient list is generated, and information on ingredients such as chicken, soy sauce, and ginger is retrieved from an online database. Furthermore, real-time suggestions are made to make in-store ingredient purchases easy, and after the user selects the necessary ingredients and completes the purchase process, a recipe video is provided as a cooking guide.

[0997] Prompt Sentence Examples

[0998] The user enters the following information into the terminal:

[0999] Family composition: 2 adults, 1 child

[1000] Allergy Information: Peanut Allergy

[1001] Food preferences: Japanese, Italian

[1002] Budget: 10,000 yen

[1003] This will support the invention's goal of preparing efficient and nutritionally balanced meals, and improve user convenience.

[1004] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1005] Step 1:

[1006] Users use a terminal to input their own and their family's preferences and allergy information. The terminal collects specific information from the user, such as "two adults, one child, peanut allergy, preference for Japanese and Italian food, budget of 10,000 yen." The input information is sent from the terminal to the server. The input data includes family composition, allergy information, food preferences, budget, etc.

[1007] Step 2:

[1008] The server analyzes the received user information and passes it to the generative AI model. The generative AI model automatically generates a menu that takes nutritional balance into consideration based on the input data. For example, it outputs a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." The server then sends this menu information to the device.

[1009] Step 3:

[1010] The terminal displays the received menu information. The user checks the weekly menu and a list of necessary ingredients is displayed. The server generates a list of necessary ingredients based on the generated menu. The input data is the menu information, and the output data is the list of ingredients.

[1011] Step 4:

[1012] The server uses the API of an online database to obtain stock status and price information for the required ingredients. To do this, the server accesses the API, sends specific ingredient information such as "500g of chicken, 100ml of soy sauce, 10g of ginger" as input, and receives stock status and price information as output. This information is sent to the terminal and provided to the user.

[1013] Step 5:

[1014] The user uses the device to check and select ingredients suggested in real time. In the physical store, the device suggests to the user the location and stock status of ingredients in real time. For example, it may indicate to the user that "chicken is in the refrigerated section, and soy sauce is in the condiment section." The user then adds the ingredients they need to their cart.

[1015] Step 6:

[1016] Based on the ingredients selected by the user, the terminal completes the purchase process. The server then uses the online shopping site's API to send the order information and complete the purchase process. Once the purchase process is complete, the server contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1017] Step 7:

[1018] The server retrieves the URL of the cooking guide (such as a recipe video) corresponding to the menu from the database and sends it to the device. The user cooks the meal while watching the recipe video on the device. For example, the URL "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[1019] Example prompt sentence:

[1020] The user enters the following information into the terminal:

[1021] Family composition: 2 adults, 1 child

[1022] Allergy Information: Peanut Allergy

[1023] Food preferences: Japanese, Italian

[1024] Budget: 10,000 yen

[1025] 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.

[1026] The present invention provides a system for efficiently preparing nutritionally balanced meals that takes into account the user's emotions as well as their preferences and allergies. This system is capable of recognizing the user's emotions and adjusting menus and optimizing cooking procedures based on the user's emotions.

[1027] Registering user information

[1028] The device uses an emotion engine to recognize the user's emotions, in addition to information entered by the user, such as family composition, allergy information, food preferences, and weekly food budget. Once the user enters this information, the device sends the data to the server.

[1029] Examples:

[1030] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information. Furthermore, the emotion engine detects that the user is "feeling stressed."

[1031] Automatic menu generation and emotion regulation

[1032] The server analyzes the received user information and passes it to the generation AI. The generation AI automatically generates a weekly menu that takes nutritional balance into consideration. It also adjusts the menu to recommend specific ingredients and dishes based on the user's emotions recognized by the emotion engine. This menu information is sent from the server to the device so that the user can review it.

[1033] Examples:

[1034] Based on the information such as "2 adults, 1 child," "peanut allergy," "Japanese food," "Italian food," and "feeling stressed," the server uses generative AI to generate tailored menus such as "Monday: Chicken teriyaki (high in ginger, which has a relaxing effect)" and "Tuesday: Spaghetti Bolognese (a menu high in nutrients to energize you on Wednesday)."

[1035] Generate a list of ingredients needed

[1036] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[1037] Examples:

[1038] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[1039] Purchasing ingredients and arranging delivery

[1040] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1041] Examples:

[1042] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1043] Providing recipe videos and emotional feedback

[1044] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user plays the provided recipe video on their device and proceeds with the cooking while watching the video. In addition, the emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on that feedback.

[1045] Examples:

[1046] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking. If the user becomes "confused" during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1047] With these functions, the system helps users prepare nutritionally balanced meals easily and efficiently. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing user stress. This system makes it easier to balance work and home life and maintain a healthy diet.

[1048] The processing flow will be explained below.

[1049] Step 1:

[1050] The user logs in to the application using a device. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The emotion engine recognizes the user's emotions through the device's camera and voice input. This information is sent from the device to the server.

[1051] Step 2:

[1052] The server analyzes the received user information and passes it on as the data needed for the generation AI, which then combines the user's input information with the emotional information obtained from the emotion engine to automatically generate a week's worth of menus.

[1053] Step 3:

[1054] The AI ​​creates a menu that takes nutritional balance into consideration. The emotion engine also takes into account emotional information, adjusting the menu to include specific ingredients and dishes that correspond to the user's emotions. For example, if the user is "feeling stressed," the system will recommend dishes that contain ingredients with a relaxing effect.

[1055] Step 4:

[1056] The server sends the generated menu to the user's device, where the user can check the menu for the week (e.g., "Monday: Teriyaki chicken (relaxing effect) / Tuesday: Spaghetti Bolognese").

[1057] Step 5:

[1058] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," the server generates an ingredient list of "500g of chicken, 100ml of soy sauce, and 10g of ginger."

[1059] Step 6:

[1060] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates a final ingredient list based on the information obtained and sends it to the user's device.

[1061] Step 7:

[1062] The user checks the shopping list provided on the terminal, selects the ingredients they need, and proceeds with the purchase. The terminal then sends the selected ingredients list to the server.

[1063] Step 8:

[1064] The server sends the order for ingredients to the online shopping site and completes the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery. A notification is sent to the user's device.

[1065] Step 9:

[1066] The server retrieves the URL of the recipe video corresponding to the menu from the database and sends it to the user's device. The user can then cook the dish while playing the recipe video on their device.

[1067] Step 10:

[1068] While cooking, the device's emotion engine recognizes the user's emotions in real time. If the user feels confused or stressed, the server will simplify the cooking steps and provide additional instructions based on the emotion engine's feedback.

[1069] Through these processing steps, the system enables users to efficiently prepare nutritionally balanced meals. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing stress for the user.

[1070] Example 2

[1071] 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."

[1072] Conventional meal recommendation systems can provide nutritionally balanced menus based on the user's preferences and allergy information, but they do not take into account the user's emotions or psychological state. This can cause users to feel stressed or confused, and they are unable to provide satisfactory service. Furthermore, there is a lack of a means to consistently and efficiently manage the process from purchasing ingredients to cooking. Therefore, improving user satisfaction and convenience is a challenge.

[1073] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting a user's preferences, allergy information, family composition, and weekly food budget; a means for recognizing emotions; a means for automatically generating and adjusting a menu that takes nutritional balance into consideration based on the user's preferences, allergy information, and emotional information using a generation AI; a means for listing necessary ingredients and acquiring information from online shopping sites; a means for purchasing ingredients and arranging for delivery; a means for providing the user with a recipe video; and a means for recognizing the user's emotions in real time during cooking and optimizing the cooking procedure based on the feedback. This enables individual adjustments based on the user's emotions, reducing stress and confusion and efficiently supporting the user from proposing menus to purchasing ingredients and cooking.

[1074] A "user" is an entity that uses the system to input preferences, allergy information, and emotional information, and receives menu suggestions, purchases ingredients, and recipes.

[1075] "Preferences" refers to information about ingredients and types of dishes that a user particularly likes, and are factors that are taken into consideration when the system generates a menu.

[1076] "Allergy information" is information about ingredients to which the user has an allergy, and is an element that is taken into consideration as ingredients to be avoided when the system generates a menu.

[1077] "Family composition" is information about the number of people and age groups in the user's household, and is a factor used by the system to determine the quantity and type of food when generating a menu.

[1078] The "weekly food budget" is information about the amount of money a user can spend on ingredients and meals per week, and is a factor that is taken into account as an economic constraint when the system generates menus.

[1079] "Emotion" refers to a psychological state that the system recognizes by analyzing the user's facial expressions and tone of voice, and is an element used to adjust menus and optimize cooking procedures.

[1080] An "emotion engine" is a combination of hardware and software for analyzing and recognizing a user's emotions, and is a means of understanding the user's psychological state.

[1081] "Generative AI" is an artificial intelligence program that automatically generates and adjusts menus that take nutritional balance into consideration based on input user information.

[1082] An "online shopping site" is a website where ingredients and other products can be purchased via the Internet, and is a source of information from which the system obtains information on ingredient availability and prices.

[1083] A "recipe video" is video content that visually shows specific steps for cooking, and allows users to cook while watching the video.

[1084] "Real-time" refers to the immediacy with which the system instantly recognizes and processes the user's input and emotions, which is an important element when providing feedback during cooking.

[1085] "Feedback" refers to the response and adjustments made by the system based on the user's emotional state, etc., and is a means used by the user to cook in optimal conditions.

[1086] "Optimizing cooking steps" means that the system adjusts the cooking process and instructions according to the user's emotions and situation, providing a more effective and satisfying cooking experience.

[1087] This system generates nutritionally balanced menus based on the user's preferences, allergy information, emotional information, family composition, and weekly food budget, lists the necessary ingredients, and provides support for purchasing, arranging delivery, and cooking. This system consists of a user terminal, a server, an emotion engine, a generation AI, and an online shopping site API.

[1088] Registering user information

[1089] Users input their preferences, allergies, family composition, and weekly food budget using a terminal, and this information is then sent from the terminal to the server.

[1090] Examples:

[1091] The user enters "2 adults, 1 child" into the terminal, sets "peanut allergy" as allergy information, "Japanese food" and "Italian food" as preferences, and sets the budget to "5,000 yen." This information is sent from the terminal to the server.

[1092] Emotion recognition

[1093] The emotion engine installed in the device recognizes the user's emotions in real time and sends that information to the server.

[1094] Examples:

[1095] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that the user is "feeling stressed," and sends this information to the server.

[1096] Automatic menu generation

[1097] The server analyzes the received user information and emotional information and creates prompts for the AI, which then generates a weekly menu that takes nutritional balance into consideration.

[1098] Examples:

[1099] The server inputs the following as a prompt to the generation AI:

[1100] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[1101] Based on this information, please suggest a nutritionally balanced menu for one week.

[1102] This allows the generation AI to generate a menu.

[1103] Emotion regulation and regeneration

[1104] The server re-evaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The adjusted menu is then passed back to the generation AI to finalize the menu.

[1105] Examples:

[1106] The generated menu becomes a weekly plan that includes "Teriyaki Chicken with Ginger, which has a relaxing effect." The emotion engine recommends ingredients and dishes that are suitable for the "stressed" state. The final menu is confirmed as "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese."

[1107] Generate an ingredient list

[1108] The server creates a list of ingredients based on the finalized menu, and uses the API of the online shopping site to obtain stock status and price information and provides it to the user.

[1109] Examples:

[1110] The server creates a list of ingredients such as "500g chicken, 100ml soy sauce, 10g ginger" and uses the API to check stock and price information, providing this information to the user.

[1111] Purchasing ingredients and arranging delivery

[1112] The user checks the shopping list on the terminal, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completes the purchase, and notifies the delivery service of the order ID, delivery address, and specified date and time.

[1113] Examples:

[1114] The user adds "chicken, soy sauce, ginger" to the cart and completes the purchase. After completing the order, the server uses the online shopping API to contact the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1115] Providing recipe videos and emotional feedback while cooking

[1116] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. While the user is cooking, the device's emotion engine recognizes emotions in real time and optimizes the cooking procedure based on the feedback.

[1117] Examples:

[1118] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1119] As described above, the present system supports users in efficiently preparing nutritionally balanced meals, and can also improve psychological satisfaction, particularly by making adjustments based on the user's emotions.

[1120] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1121] Step 1: Register user information

[1122] Users use a device to input their family composition, allergy information, food preferences, and weekly food budget. The device stores this information in a database and sends it to the server. The input data includes family composition, allergy information, preferences, and budget. The output data is a dataset that compiles this user information.

[1123] Specific behavior:

[1124] The user enters into the terminal the family composition as "2 adults, 1 child," allergy information as "peanut allergy," preferences as "Japanese food" and "Italian food," and budget as "5,000 yen," and this information is sent to the server.

[1125] Step 2: Recognize emotions

[1126] The emotion engine installed in the device recognizes the user's emotions in real time. The input data includes the user's facial expressions and tone of voice, which are analyzed to extract emotional information. The output data is the recognized emotional information.

[1127] Specific behavior:

[1128] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that they are "feeling stressed," and sends this information to the server.

[1129] Step 3: Automatic menu generation

[1130] The server analyzes user information and emotional information, and creates and inputs prompts to the generation AI. The input data includes user information and emotional information, and the generation AI uses this to generate a week's worth of menus that take nutritional balance into consideration. The output data is the generated menu information.

[1131] Specific behavior:

[1132] The server inputs the following prompt to the generated AI:

[1133] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[1134] Based on this information, please suggest a nutritionally balanced menu for one week.

[1135] The generation AI generates a menu, which is sent to the server.

[1136] Step 4: Emotional regulation and regeneration

[1137] The server reevaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The input data are the generated menu and the user's emotion information, and the emotion engine makes adjustments based on this. The output data is the adjusted final menu.

[1138] Specific behavior:

[1139] The generated menu is adjusted into a weekly plan that includes "Chicken Teriyaki with Ginger, which has a relaxing effect." The final menu is finalized as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese."

[1140] Step 5: Generate an ingredient list

[1141] The server creates a list of ingredients based on the final menu. The input data is the final menu, and it uses the API of an online shopping site to obtain stock availability and price information. The output data is the list of ingredients.

[1142] Specific behavior:

[1143] The server creates a list of ingredients, such as "500g chicken, 100ml soy sauce, 10g ginger," and uses an online shopping API to check stock and price information, which is then provided to the user.

[1144] Step 6: Purchase ingredients and arrange delivery

[1145] The user checks the provided shopping list on their device, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completing the purchase process. The delivery service is then notified of the order ID, delivery address, and specified date and time. The input data is the list of ingredients selected by the user, and the output data is confirmation that the order has been completed.

[1146] Specific behavior:

[1147] The user adds "chicken, soy sauce, and ginger" to the cart and completes the purchase. The server completes the order using the online shopping site API and contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1148] Step 7: Providing recipe videos and emotional feedback during cooking

[1149] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The device's emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on the feedback. The input data is the user's emotional state while cooking, and the output data is the optimized cooking steps.

[1150] Specific behavior:

[1151] The server provides a link to a video recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1152] The above is a detailed description of the specific processing flow of this system and the operation at each step.

[1153] (Application example 2)

[1154] 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."

[1155] While conventional meal preparation systems can take into account a user's preferences and allergy information, they have difficulty optimizing menu suggestions and cooking procedures that reflect the user's emotional state. As a result, they are unable to respond adequately to situations where the user is likely to feel stressed, which can result in meal preparation being time-consuming and inefficient. Furthermore, the lack of real-time emotional cooking support often leaves users confused.

[1156] 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 inputting the user's preferences, allergy information, and emotions, means for automatically generating a menu that takes nutritional balance into consideration using a generation AI and adjusting the menu based on emotional information, means for listing necessary ingredients and acquiring information from online shopping sites, means for purchasing ingredients and arranging for delivery, and means for providing the user with recipe videos, acquiring emotional feedback in real time during cooking, and optimizing cooking procedures. This makes it possible to adjust the menu and optimize cooking procedures according to the user's emotional state, resulting in efficient and stress-free meal preparation.

[1157] "User preference and allergy information" is information about preferences and allergies that are individually input by the user.

[1158] "Emotion information" is data that indicates the user's current psychological state, and is information obtained using the emotion engine.

[1159] "Generative AI" is an artificial intelligence model that automatically generates menus that take nutritional balance into consideration based on provided data.

[1160] The "means for adjusting the menu" refers to a method or function for adjusting the generated menu to an optimal one, taking into account the user's emotional information.

[1161] An "online shopping site" is an e-commerce platform for purchasing products over the Internet.

[1162] "Recipe videos" are video content that explains cooking steps and methods.

[1163] "Emotional feedback" is information that acquires the user's emotional information in real time and adjusts the system's behavior based on that information.

[1164] The "means for optimizing the cooking procedure" refers to a method or function for changing the cooking procedure to an optimal form based on the user's emotional information.

[1165] The "ingredient list" is a list of all ingredients required based on the generated menu.

[1166] "Delivery arrangement" refers to carrying out procedures to deliver the selected ingredients to a location designated by the user.

[1167] The present invention is a system that efficiently prepares nutritionally balanced meals by taking into consideration the user's preferences, allergy information, and emotional information. This system is composed of a user terminal and a server, and performs the following processes.

[1168] Registering user information

[1169] First, the user uses the device to input information such as family composition, allergies, favorite ingredients, and weekly food budget. The device is also equipped with an emotion engine that captures emotional information from the user's facial expressions in real time. This information is then sent to the server and stored in a database.

[1170] Automatic menu generation and emotion regulation

[1171] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. It also adjusts the generated menu based on emotional information obtained from the emotion engine. For example, if it detects that the user is "feeling stressed," it will suggest a menu that includes many ingredients with a relaxing effect.

[1172] Generate a list of ingredients needed

[1173] The server creates a list of ingredients based on the generated menu, and then uses the API of the online shopping site to obtain information on ingredient availability and prices, which it then provides to the user.

[1174] Purchasing ingredients and arranging delivery

[1175] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the order information to the online shopping site to complete the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1176] Providing recipe videos and emotional feedback

[1177] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user cooks while playing the provided recipe video on their device. The emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking procedure based on that feedback. Specifically, if the server detects that the user is "confused," it automatically provides simplifications or additional explanations.

[1178] Example of a system

[1179] If a user inputs their family composition (two adults, one child), their "peanut allergy," and their "preference for Japanese and Italian food," and the emotion engine detects that they are "feeling stressed," the generative AI model automatically generates and adjusts a menu suggestion, such as "Monday: Chicken Teriyaki (high in ginger, which has a relaxing effect) and Tuesday: Spaghetti Bolognese." The user confirms this, purchases the necessary ingredients from an online shopping site, and cooks while watching a recipe video. If confusion is detected during cooking, a prompt message will be displayed, such as, "If you find the steps difficult, we will explain in detail how to fry the chicken first and then add the ginger and soy sauce. We also provide a detailed explanation from 01:45 to 02:10 in the video."

[1180] In this way, the system adjusts menus and optimizes cooking procedures according to the user's emotional state, supporting efficient and stress-free meal preparation.

[1181] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1182] Step 1:

[1183] The user uses a device to input information such as family composition, allergy information, favorite ingredients, and weekly food budget. The emotion engine then captures the user's facial expressions and obtains emotional information. The input data includes text data such as family composition and allergy information, as well as image data, and the organized user information is sent to the server as output.

[1184] Step 2:

[1185] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. The user information is used as input data, and a weekly menu is generated as output. In addition, based on emotional information, the menu is adjusted to include more ingredients that have a relaxing effect. Specifically, the system refers to the nutrition database and emotional database to select an appropriate menu.

[1186] Step 3:

[1187] The server creates a list of ingredients based on the generated menu and uses the online shopping site's API to obtain the availability and price information of those ingredients. The generated menu and the online shopping site's API endpoint are used as input data, and the list of ingredients, their availability, and price information is generated as output. Specifically, the server sends an API request and analyzes the received data to create the list.

[1188] Step 4:

[1189] The user uses a terminal to check the provided shopping list, select the ingredients they need, and complete the purchase procedure. The created ingredient list and the user's selection information are used as input data, and the final shopping list is determined as output. Specific actions include pressing the purchase confirmation button on the user interface.

[1190] Step 5:

[1191] The server sends the order information for the selected ingredients to the online shopping site to complete the purchase process. It also contacts the delivery service with the order ID, delivery address, and specified date and time to arrange delivery. The input data is the final purchase list and delivery address information, and the output is a confirmation of the order and the completion of delivery arrangements. Specifically, it sends the order information using an API request and makes a request to the delivery service.

[1192] Step 6:

[1193] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The generated menu is used as input data, and the URL of the recipe video is generated as output. Specifically, the database is queried using the menu name as a key to retrieve the corresponding video URL.

[1194] Step 7:

[1195] The user cooks while playing a recipe video provided on the device. While cooking, the device uses an emotion engine to obtain the user's emotions in real time and optimizes the cooking steps based on that feedback. Real-time emotion information is used as input data, and optimized cooking steps are provided as output. Specifically, support is provided, such as displaying prompts if the user is confused.

[1196] 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.

[1197] 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.

[1198] 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.

[1199] [Fourth embodiment]

[1200] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1201] 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.

[1202] 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).

[1203] 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.

[1204] 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.

[1205] 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).

[1206] 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.

[1207] 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.

[1208] 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.

[1209] 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.

[1210] 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.

[1211] 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.

[1212] 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."

[1213] The purpose of this system is to automate the process of efficiently preparing nutritionally balanced meals for busy families with children or single parents. To achieve this, the system provides the following main functions:

[1214] Registering user information

[1215] The device collects information entered by the user, such as family composition, allergy information, food preferences, weekly food budget, etc. Once the user enters this information, the device sends the data to the server.

[1216] Examples:

[1217] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information.

[1218] Automatic menu generation

[1219] The server analyzes the received user information and passes it to the generation AI, which then automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can view it.

[1220] Examples:

[1221] Based on user information including "2 adults, 1 child," "peanut allergy," "Japanese food," and "Italian," the server uses generative AI to generate menus such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls."

[1222] Generate a list of ingredients needed

[1223] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[1224] Examples:

[1225] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[1226] Purchasing ingredients and arranging delivery

[1227] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1228] Examples:

[1229] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1230] Providing recipe videos

[1231] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can then play the provided recipe video on their device and proceed with cooking while watching the video.

[1232] Examples:

[1233] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking.

[1234] With each of the above functions, this system helps users prepare nutritionally balanced meals easily and efficiently. In particular, it can significantly reduce users' time and effort through a series of processes: automatic menu generation using generative AI, linking with online shopping sites for ingredient lists, arranging delivery, and providing recipe videos. This system makes it easier to balance work and home life and maintain a healthy diet.

[1235] The processing flow will be explained below.

[1236] Step 1:

[1237] A user logs in to the system using a terminal. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The terminal then sends this information to the server.

[1238] Step 2:

[1239] The server analyzes the received user information and provides the AI ​​with data such as family composition, allergies, and food preferences based on the analyzed information.

[1240] Step 3:

[1241] The AI ​​automatically generates a weekly menu that takes nutritional balance into consideration based on the provided data, and the generated menu is sent back to the server.

[1242] Step 4:

[1243] The server sends the generated menu to the user's device, where the user can view the weekly menu (e.g., "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll...").

[1244] Step 5:

[1245] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," it adds items such as "500g of chicken, 100ml of soy sauce, and 10g of ginger" to the list.

[1246] Step 6:

[1247] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates the final ingredients list based on the information obtained.

[1248] Step 7:

[1249] The server sends the ingredient list and a purchase link to the user's device. The user checks the provided shopping list on the device, selects the ingredients they need, and adds them to their cart.

[1250] Step 8:

[1251] When the user completes the purchase, the terminal sends the list of selected ingredients to the server, which then sends the ingredient order to the online shopping site and completes the purchase.

[1252] Step 9:

[1253] The server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for the ingredients to be delivered. Details of the delivery arrangements are sent to the user's terminal.

[1254] Step 10:

[1255] The server retrieves the URL of the recipe video corresponding to the menu from the database. For example, it retrieves the recipe video URL for "Teriyaki Chicken" ("https: / / example.com / recipe / teriyaki_chicken").

[1256] Step 11:

[1257] The server sends the URL of the recipe video to the user's device, where the user can play the recipe video and cook the dish while watching the video.

[1258] Through these steps, the system helps users efficiently prepare nutritionally balanced meals.

[1259] Example 1

[1260] 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."

[1261] In busy families with children or single parents, it is often difficult to efficiently prepare nutritionally balanced meals. In these households, time is limited, and the time and effort required for carefully selecting ingredients, planning menus, purchasing ingredients, and cooking can be a significant burden. A system that solves this problem and allows users to easily prepare nutritionally balanced meals is needed.

[1262] 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.

[1263] In this invention, the server includes means for inputting information such as the user's family composition, allergy information, ingredient preferences, budget, etc., means for automatically generating a menu that takes nutritional balance into consideration using a generative AI model, means for creating a list of necessary ingredients based on the generated menu, means for acquiring ingredient availability and price information using an online shopping API, means for purchasing ingredients and arranging for delivery, and means for providing the user with a URL for a recipe video, thereby enabling the user to prepare nutritionally balanced meals while reducing the burden on the user.

[1264] "User information" refers to information such as the user's family structure, allergy information, food preferences, budget, etc.

[1265] A "generative AI model" refers to an artificial intelligence algorithm that automatically generates a menu that takes nutritional balance into consideration based on user information.

[1266] "Automatic menu generation" refers to the process of using a generative AI model to automatically create a weekly menu based on user information.

[1267] "Creating an ingredient list" refers to the process of compiling a list of ingredients needed based on the generated menu.

[1268] An "online shopping API" refers to an application programming interface for obtaining inventory and price information from shopping sites via the Internet.

[1269] "Ingredients purchasing procedure" refers to the process by which a user purchases selected ingredients through an online shopping site.

[1270] "Delivery Arrangement" refers to the process of coordinating the delivery service of purchased ingredients to a specified address.

[1271] "Providing recipe videos" refers to the process of providing users with URLs of videos showing cooking methods that can be used as reference when the user cooks.

[1272] The system of the present invention allows users to efficiently prepare nutritionally balanced meals, and is targeted particularly at busy families with children and single-parent households. The system includes a series of processes: registering user information, automatically generating menus, generating a list of ingredients, purchasing ingredients and arranging for delivery, and providing recipe videos.

[1273] First, the user uses the device to enter user information such as family composition, allergy information, food preferences, budget, etc. Once the user has entered the information, the device sends the data to the server, which then stores the received information in a database.

[1274] The server then retrieves the saved user information, incorporates that data into a prompt, and passes it to the generative AI model. The generative AI model then analyzes the user information and automatically generates a weekly menu that takes nutritional balance into consideration. This menu information is then sent from the server to the device so that the user can review it.

[1275] For example, if a user enters "2 adults, 1 child" as their family composition, "peanut allergy" as their allergy information, and "Japanese food" and "Italian food" as their food preferences, the server will send a prompt based on this information to the generative AI model. The generative AI model will generate a menu such as "Monday: Chicken teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi rolls," and the server will provide this information to the user.

[1276] Examples of prompts are:

[1277] "The user information is: family composition: 2 adults, 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[1278] Based on the generated menu, the server creates a list of ingredients. The server uses an online shopping API to obtain ingredient availability and price information. Based on this information, the server generates the final ingredient list and sends it to the device. The user can then view the list and prices on their device.

[1279] The user uses their device to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site's API, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1280] Finally, the server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user can play the provided recipe video on their device and cook while watching the video. As a specific example, the URL for the recipe video for "Teriyaki Chicken" "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[1281] Through this series of processes, the system enables users to efficiently prepare nutritionally balanced meals while reducing their burden. In particular, the combination of automatic menu generation using a generative AI model, obtaining ingredient inventory and price information using an online shopping API, and arranging delivery and providing recipe videos significantly reduces the user's workload.

[1282] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1283] Step 1: Enter your user information

[1284] The user uses the terminal to input user information such as family composition, allergy information, food preferences, budget, etc.

[1285] Specific behavior:

[1286] The user enters information such as "Family composition: 2 adults, 1 child," "Allergy information: peanuts," "Food preferences: Japanese, Italian," and "Budget: 10,000 yen" into the input form on the device.

[1287] Input: Individual pieces of information entered by the user

[1288] Output: User information data entered

[1289] Step 2: Submit user information

[1290] The terminal sends the input information to the server.

[1291] Specific behavior:

[1292] The device sends the collected information to the server using an HTTP POST request.

[1293] Input: User information data

[1294] Output: User information transferred to the server

[1295] Step 3: Save user information

[1296] The server stores the received information in a database.

[1297] Specific behavior:

[1298] The server parses the received data and stores information such as family composition, allergy information, food preferences, and budget in a database (e.g., MySQL).

[1299] Input: User information transferred to the server

[1300] Output: User information stored in the database

[1301] Step 4: Generate a prompt statement

[1302] The server retrieves the saved user information and generates a prompt.

[1303] Specific behavior:

[1304] The server reads the user information from the database and constructs a prompt message that reads, "User information: Family composition: 2 adults and 1 child. Allergy information: peanuts. Food preferences: Japanese and Italian. Please generate a weekly menu based on this information."

[1305] Input: User information stored in the database

[1306] Output: Generated prompt statement

[1307] Step 5: Automatic menu generation

[1308] The server passes the prompt text to a generative AI model, which automatically generates a menu that takes nutritional balance into consideration.

[1309] Specific behavior:

[1310] The server sends the prompt to the generative AI model, which then generates a weekly menu (e.g., "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Rolls").

[1311] Input: Generated prompt statement

[1312] Output: Generated weekly menu information

[1313] Step 6: Submit your menu

[1314] The server sends the generated menu to the terminal.

[1315] Specific behavior:

[1316] The server sends the generated menu information to the terminal as an HTTP response.

[1317] Input: Generated weekly menu information

[1318] Output: Menu information sent to the device

[1319] Step 7: Generate an ingredient list

[1320] The server analyzes the menu information and creates a list of necessary ingredients.

[1321] Specific behavior:

[1322] The server analyzes each dish on the menu and lists the ingredients needed (e.g., "500g chicken, 100ml soy sauce, 10g ginger").

[1323] Input: Generated weekly menu information

[1324] Output: List of ingredients needed

[1325] Step 8: Get ingredient availability and pricing information

[1326] The server uses an online shopping API to retrieve food availability and pricing information.

[1327] Specific behavior:

[1328] The server calls the API of the online shopping site (e.g., Amazon API) to obtain stock status and price information for each ingredient.

[1329] Input: List of ingredients needed

[1330] Output: A list of ingredients with availability and pricing information

[1331] Step 9: Submit your ingredient list

[1332] The server sends a list of ingredients with stock status and price information to the terminal.

[1333] Specific behavior:

[1334] The server sends the ingredient list to the terminal as an HTTP response.

[1335] Input: A list of ingredients with availability and pricing information

[1336] Output: The final ingredients list sent to the terminal

[1337] Step 10: Confirm and select ingredients

[1338] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase process.

[1339] Specific behavior:

[1340] The user can view the final ingredient list on the terminal, add the ingredients to be purchased to the cart, and complete the purchase procedure.

[1341] Input: Final ingredient list sent to the terminal

[1342] Output: Shopping list and shipping information

[1343] Step 11: Complete your purchase

[1344] The server sends the list of selected ingredients to the online shopping site's API to complete the purchase process.

[1345] Specific behavior:

[1346] The server sends the purchase information (e.g., ingredient list, shipping information) to the online shopping site's API to complete the purchase.

[1347] Input: Shopping list and shipping information

[1348] Output: Completed checkout

[1349] Step 12: Arrange for delivery

[1350] Based on the information regarding the completed purchase procedure, the server contacts the delivery service with the order ID, delivery address, and specified date and time, and arranges for delivery.

[1351] Specific behavior:

[1352] The server sends purchase information (e.g., order ID, delivery address, specified date and time) to the delivery service API and arranges for delivery.

[1353] Input: Completed purchase

[1354] Output: Completed shipping process

[1355] Step 13: Submit a recipe video

[1356] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user.

[1357] Specific behavior:

[1358] The server retrieves the URL of the "Teriyaki Chicken" recipe video (e.g., "https: / / example.com / recipe / teriyaki_chicken") from the database and sends it to the terminal.

[1359] Input: Generated weekly menu information

[1360] Output: Recipe video URL sent to the device

[1361] (Application example 1)

[1362] 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."

[1363] For busy families with children or single parents, the complex and time-consuming process of efficiently preparing nutritionally balanced meals is a problem. There is a need to solve this problem and enable users to easily purchase ingredients and cook in physical stores. There is also a need to improve user convenience by providing effective suggestions in real time.

[1364] 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.

[1365] In this invention, the server includes a means for inputting user preferences and allergy information, a means for automatically generating a menu that takes nutritional balance into consideration using generation AI, and a means for making suggestions in real time in the physical store, thereby enabling users to easily purchase ingredients and cook in the physical store.

[1366] "User preference and allergy information" refers to information about preferences that a user takes into consideration when selecting food and allergic reactions to specific ingredients.

[1367] "Generative AI" is a system that uses artificial intelligence technology to analyze data and automatically generate optimal results for specific purposes.

[1368] A "menu that takes into consideration nutritional balance" is a meal menu that includes an appropriate amount of nutrients necessary to maintain the user's health.

[1369] "Online database" means a repository of information accessible over the Internet, including food availability and pricing information.

[1370] A "cooking guide" is a document or video that describes the steps and methods that a user should follow when cooking.

[1371] "Real-time suggestions in physical stores" means providing users with information on appropriate ingredients and menus instantly via digital devices while they are in the actual store.

[1372] A "smartphone" is a mobile device that has the functions of a computer in addition to a mobile phone and can be used by installing applications.

[1373] This invention is a system that automates a series of processes for efficiently preparing nutritionally balanced meals for busy families with children or single parents. This system includes a means for inputting user preferences and allergy information, a means for automatically generating menus that take nutritional balance into consideration using generation AI, a means for listing necessary ingredients and retrieving information from an online database, a means for making real-time suggestions in a physical store, a means for purchasing ingredients and arranging for delivery, and a means for providing users with cooking guides.

[1374] Overall flow

[1375] First, users use a device to input their own and their family's preferences and allergy information. This allows the system to select foods that meet individual needs and collect basic data for creating menus. This data is sent to a server, which uses AI to automatically create menus that take nutritional balance into consideration. The generated menus are then presented to the user in real time, after which a list of the necessary ingredients is generated. Furthermore, the system retrieves information on ingredient availability and prices from an online database, helping users to easily purchase ingredients in physical stores.

[1376] Hardware and software used

[1377] Device: Smartphone

[1378] Server: The server is the central system that holds the generative AI model and performs data analysis.

[1379] Online database: Get ingredient availability and pricing information from third-party APIs.

[1380] Generative AI model: An AI that automatically generates menus that take nutritional balance into consideration.

[1381] Processing flow

[1382] 1. Collecting user information: The device collects information from the user, such as family composition, allergy information, food preferences, budget, etc., and sends it to the server. For example, the user enters "2 adults, 1 child, peanut allergy, prefers Japanese and Italian food."

[1383] 2. Automatic menu generation: Based on the received user information, the server uses a generative AI model to generate a nutritionally balanced menu for one week. For example, a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese" may be generated.

[1384] 3. Generate a list of required ingredients: The server generates a list of required ingredients based on the generated menu information and obtains ingredient stock and price information from the online database API. For example, a list of "500g of chicken, 100ml of soy sauce, and 10g of ginger" might be generated.

[1385] 4. Real-time suggestions: Users can receive real-time suggestions using their smartphones in-store. Specifically, the location and stock status of ingredients needed for a meal are immediately displayed.

[1386] 5. Purchase and delivery: The user selects the ingredients they need and completes the purchase process. The server uses the online shopping API to complete the order and arrange for delivery.

[1387] 6. Providing cooking guides: The server provides users with cooking guides (such as recipe videos) corresponding to the menu. For example, users can watch a video showing the cooking steps for "Teriyaki Chicken."

[1388] Specific examples

[1389] If a user inputs "2 adults and 1 child, peanut allergy, likes Japanese and Italian food," the server will use generative AI to generate a menu, offering options such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." Based on this, an ingredient list is generated, and information on ingredients such as chicken, soy sauce, and ginger is retrieved from an online database. Furthermore, real-time suggestions are made to make in-store ingredient purchases easy, and after the user selects the necessary ingredients and completes the purchase process, a recipe video is provided as a cooking guide.

[1390] Prompt Sentence Examples

[1391] The user enters the following information into the terminal:

[1392] Family composition: 2 adults, 1 child

[1393] Allergy Information: Peanut Allergy

[1394] Food preferences: Japanese, Italian

[1395] Budget: 10,000 yen

[1396] This will support the invention's goal of preparing efficient and nutritionally balanced meals, and improve user convenience.

[1397] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1398] Step 1:

[1399] Users use a terminal to input their own and their family's preferences and allergy information. The terminal collects specific information from the user, such as "two adults, one child, peanut allergy, preference for Japanese and Italian food, budget of 10,000 yen." The input information is sent from the terminal to the server. The input data includes family composition, allergy information, food preferences, budget, etc.

[1400] Step 2:

[1401] The server analyzes the received user information and passes it to the generative AI model. The generative AI model automatically generates a menu that takes nutritional balance into consideration based on the input data. For example, it outputs a menu such as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese, Wednesday: Sushi Roll." The server then sends this menu information to the device.

[1402] Step 3:

[1403] The terminal displays the received menu information. The user checks the weekly menu and a list of necessary ingredients is displayed. The server generates a list of necessary ingredients based on the generated menu. The input data is the menu information, and the output data is the list of ingredients.

[1404] Step 4:

[1405] The server uses the API of an online database to obtain stock status and price information for the required ingredients. To do this, the server accesses the API, sends specific ingredient information such as "500g of chicken, 100ml of soy sauce, 10g of ginger" as input, and receives stock status and price information as output. This information is sent to the terminal and provided to the user.

[1406] Step 5:

[1407] The user uses the device to check and select ingredients suggested in real time. In the physical store, the device suggests to the user the location and stock status of ingredients in real time. For example, it may indicate to the user that "chicken is in the refrigerated section, and soy sauce is in the condiment section." The user then adds the ingredients they need to their cart.

[1408] Step 6:

[1409] Based on the ingredients selected by the user, the terminal completes the purchase process. The server then uses the online shopping site's API to send the order information and complete the purchase process. Once the purchase process is complete, the server contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1410] Step 7:

[1411] The server retrieves the URL of the cooking guide (such as a recipe video) corresponding to the menu from the database and sends it to the device. The user cooks the meal while watching the recipe video on the device. For example, the URL "https: / / example.com / recipe / teriyaki_chicken" is provided to the user.

[1412] Example prompt sentence:

[1413] The user enters the following information into the terminal:

[1414] Family composition: 2 adults, 1 child

[1415] Allergy Information: Peanut Allergy

[1416] Food preferences: Japanese, Italian

[1417] Budget: 10,000 yen

[1418] 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.

[1419] The present invention provides a system for efficiently preparing nutritionally balanced meals that takes into account the user's emotions as well as their preferences and allergies. This system is capable of recognizing the user's emotions and adjusting menus and optimizing cooking procedures based on the user's emotions.

[1420] Registering user information

[1421] The device uses an emotion engine to recognize the user's emotions, in addition to information entered by the user, such as family composition, allergy information, food preferences, and weekly food budget. Once the user enters this information, the device sends the data to the server.

[1422] Examples:

[1423] The user enters "2 adults, 1 child" as the family composition and registers "peanut allergy" as the allergy information. The user also selects "Japanese food" and "Italian food" as their favorites and submits the input information. Furthermore, the emotion engine detects that the user is "feeling stressed."

[1424] Automatic menu generation and emotion regulation

[1425] The server analyzes the received user information and passes it to the generation AI. The generation AI automatically generates a weekly menu that takes nutritional balance into consideration. It also adjusts the menu to recommend specific ingredients and dishes based on the user's emotions recognized by the emotion engine. This menu information is sent from the server to the device so that the user can review it.

[1426] Examples:

[1427] Based on the information such as "2 adults, 1 child," "peanut allergy," "Japanese food," "Italian food," and "feeling stressed," the server uses generative AI to generate tailored menus such as "Monday: Chicken teriyaki (high in ginger, which has a relaxing effect)" and "Tuesday: Spaghetti Bolognese (a menu high in nutrients to energize you on Wednesday)."

[1428] Generate a list of ingredients needed

[1429] The server creates a list of ingredients based on the generated menu. The server uses the API of the online shopping site to obtain information on the availability and price of ingredients and provides it to the user.

[1430] Examples:

[1431] If the menu includes "Teriyaki Chicken," the server will list "500g of chicken, 100ml of soy sauce, and 10g of ginger," and then use an online shopping API to check the availability and price of these ingredients. The server will send this information to the user and display the final ingredients list.

[1432] Purchasing ingredients and arranging delivery

[1433] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the selected ingredients list to the online shopping site, completing the purchase process. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1434] Examples:

[1435] The user confirms "chicken, soy sauce, and ginger," adds them all to the cart, and completes the purchase. The server completes the order using the online shopping site API, and then contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1436] Providing recipe videos and emotional feedback

[1437] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user plays the provided recipe video on their device and proceeds with the cooking while watching the video. In addition, the emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on that feedback.

[1438] Examples:

[1439] The server retrieves a recipe video for "Teriyaki Chicken" from the database and sends the URL "https: / / example.com / recipe / teriyaki_chicken" to the user. The user plays the recipe video on their device while cooking. If the user becomes "confused" during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1440] With these functions, the system helps users prepare nutritionally balanced meals easily and efficiently. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing user stress. This system makes it easier to balance work and home life and maintain a healthy diet.

[1441] The processing flow will be explained below.

[1442] Step 1:

[1443] The user logs in to the application using a device. The user enters their family composition (e.g., "2 adults, 1 child"), allergy information (e.g., "peanut allergy"), food preferences (e.g., "Japanese food" or "Italian food"), and weekly food budget. The emotion engine recognizes the user's emotions through the device's camera and voice input. This information is sent from the device to the server.

[1444] Step 2:

[1445] The server analyzes the received user information and passes it on as the data needed for the generation AI, which then combines the user's input information with the emotional information obtained from the emotion engine to automatically generate a week's worth of menus.

[1446] Step 3:

[1447] The AI ​​creates a menu that takes nutritional balance into consideration. The emotion engine also takes into account emotional information, adjusting the menu to include specific ingredients and dishes that correspond to the user's emotions. For example, if the user is "feeling stressed," the system will recommend dishes that contain ingredients with a relaxing effect.

[1448] Step 4:

[1449] The server sends the generated menu to the user's device, where the user can check the menu for the week (e.g., "Monday: Teriyaki chicken (relaxing effect) / Tuesday: Spaghetti Bolognese").

[1450] Step 5:

[1451] The server creates a list of ingredients based on the generated menu. For example, for "Teriyaki Chicken," the server generates an ingredient list of "500g of chicken, 100ml of soy sauce, and 10g of ginger."

[1452] Step 6:

[1453] The server uses the API of the online shopping site to obtain information on the availability and prices of ingredients, and then generates a final ingredient list based on the information obtained and sends it to the user's device.

[1454] Step 7:

[1455] The user checks the shopping list provided on the terminal, selects the ingredients they need, and proceeds with the purchase. The terminal then sends the selected ingredients list to the server.

[1456] Step 8:

[1457] The server sends the order for ingredients to the online shopping site and completes the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery. A notification is sent to the user's device.

[1458] Step 9:

[1459] The server retrieves the URL of the recipe video corresponding to the menu from the database and sends it to the user's device. The user can then cook the dish while playing the recipe video on their device.

[1460] Step 10:

[1461] While cooking, the device's emotion engine recognizes the user's emotions in real time. If the user feels confused or stressed, the server will simplify the cooking steps and provide additional instructions based on the emotion engine's feedback.

[1462] Through these processing steps, the system enables users to efficiently prepare nutritionally balanced meals. In particular, by using an emotion engine, the system adjusts menus and optimizes cooking procedures according to the user's psychological state, reducing stress for the user.

[1463] Example 2

[1464] 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."

[1465] Conventional meal recommendation systems can provide nutritionally balanced menus based on the user's preferences and allergy information, but they do not take into account the user's emotions or psychological state. This can cause users to feel stressed or confused, and they are unable to provide satisfactory service. Furthermore, there is a lack of a means to consistently and efficiently manage the process from purchasing ingredients to cooking. Therefore, improving user satisfaction and convenience is a challenge.

[1466] The specification process by the specification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes a means for inputting a user's preferences, allergy information, family composition, and weekly food budget; a means for recognizing emotions; a means for automatically generating and adjusting a menu that takes nutritional balance into consideration based on the user's preferences, allergy information, and emotional information using a generation AI; a means for listing necessary ingredients and acquiring information from online shopping sites; a means for purchasing ingredients and arranging for delivery; a means for providing the user with a recipe video; and a means for recognizing the user's emotions in real time during cooking and optimizing the cooking procedure based on the feedback. This enables individual adjustments based on the user's emotions, reducing stress and confusion and efficiently supporting the user from proposing menus to purchasing ingredients and cooking.

[1467] A "user" is an entity that uses the system to input preferences, allergy information, and emotional information, and receives menu suggestions, purchases ingredients, and recipes.

[1468] "Preferences" refers to information about ingredients and types of dishes that a user particularly likes, and are factors that are taken into consideration when the system generates a menu.

[1469] "Allergy information" is information about ingredients to which the user has an allergy, and is an element that is taken into consideration as ingredients to be avoided when the system generates a menu.

[1470] "Family composition" is information about the number of people and age groups in the user's household, and is a factor used by the system to determine the quantity and type of food when generating a menu.

[1471] The "weekly food budget" is information about the amount of money a user can spend on ingredients and meals per week, and is a factor that is taken into account as an economic constraint when the system generates menus.

[1472] "Emotion" refers to a psychological state that the system recognizes by analyzing the user's facial expressions and tone of voice, and is an element used to adjust menus and optimize cooking procedures.

[1473] An "emotion engine" is a combination of hardware and software for analyzing and recognizing a user's emotions, and is a means of understanding the user's psychological state.

[1474] "Generative AI" is an artificial intelligence program that automatically generates and adjusts menus that take nutritional balance into consideration based on input user information.

[1475] An "online shopping site" is a website where ingredients and other products can be purchased via the Internet, and is a source of information from which the system obtains information on ingredient availability and prices.

[1476] A "recipe video" is video content that visually shows specific steps for cooking, and allows users to cook while watching the video.

[1477] "Real-time" refers to the immediacy with which the system instantly recognizes and processes the user's input and emotions, which is an important element when providing feedback during cooking.

[1478] "Feedback" refers to the response and adjustments made by the system based on the user's emotional state, etc., and is a means used by the user to cook in optimal conditions.

[1479] "Optimizing cooking steps" means that the system adjusts the cooking process and instructions according to the user's emotions and situation, providing a more effective and satisfying cooking experience.

[1480] This system generates nutritionally balanced menus based on the user's preferences, allergy information, emotional information, family composition, and weekly food budget, lists the necessary ingredients, and provides support for purchasing, arranging delivery, and cooking. This system consists of a user terminal, a server, an emotion engine, a generation AI, and an online shopping site API.

[1481] Registering user information

[1482] Users input their preferences, allergies, family composition, and weekly food budget using a terminal, and this information is then sent from the terminal to the server.

[1483] Examples:

[1484] The user enters "2 adults, 1 child" into the terminal, sets "peanut allergy" as allergy information, "Japanese food" and "Italian food" as preferences, and sets the budget to "5,000 yen." This information is sent from the terminal to the server.

[1485] Emotion recognition

[1486] The emotion engine installed in the device recognizes the user's emotions in real time and sends that information to the server.

[1487] Examples:

[1488] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that the user is "feeling stressed," and sends this information to the server.

[1489] Automatic menu generation

[1490] The server analyzes the received user information and emotional information and creates prompts for the AI, which then generates a weekly menu that takes nutritional balance into consideration.

[1491] Examples:

[1492] The server inputs the following as a prompt to the generation AI:

[1493] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[1494] Based on this information, please suggest a nutritionally balanced menu for one week.

[1495] This allows the generation AI to generate a menu.

[1496] Emotion regulation and regeneration

[1497] The server re-evaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The adjusted menu is then passed back to the generation AI to finalize the menu.

[1498] Examples:

[1499] The generated menu becomes a weekly plan that includes "Teriyaki Chicken with Ginger, which has a relaxing effect." The emotion engine recommends ingredients and dishes that are suitable for the "stressed" state. The final menu is confirmed as "Monday: Teriyaki Chicken, Tuesday: Spaghetti Bolognese."

[1500] Generate an ingredient list

[1501] The server creates a list of ingredients based on the finalized menu, and uses the API of the online shopping site to obtain stock status and price information and provides it to the user.

[1502] Examples:

[1503] The server creates a list of ingredients such as "500g chicken, 100ml soy sauce, 10g ginger" and uses the API to check stock and price information, providing this information to the user.

[1504] Purchasing ingredients and arranging delivery

[1505] The user checks the shopping list on the terminal, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completes the purchase, and notifies the delivery service of the order ID, delivery address, and specified date and time.

[1506] Examples:

[1507] The user adds "chicken, soy sauce, ginger" to the cart and completes the purchase. After completing the order, the server uses the online shopping API to contact the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1508] Providing recipe videos and emotional feedback while cooking

[1509] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. While the user is cooking, the device's emotion engine recognizes emotions in real time and optimizes the cooking procedure based on the feedback.

[1510] Examples:

[1511] The server provides a video link to the recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1512] As described above, the present system supports users in efficiently preparing nutritionally balanced meals, and can also improve psychological satisfaction, particularly by making adjustments based on the user's emotions.

[1513] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1514] Step 1: Register user information

[1515] Users use a device to input their family composition, allergy information, food preferences, and weekly food budget. The device stores this information in a database and sends it to the server. The input data includes family composition, allergy information, preferences, and budget. The output data is a dataset that compiles this user information.

[1516] Specific behavior:

[1517] The user enters into the terminal the family composition as "2 adults, 1 child," allergy information as "peanut allergy," preferences as "Japanese food" and "Italian food," and budget as "5,000 yen," and this information is sent to the server.

[1518] Step 2: Recognize emotions

[1519] The emotion engine installed in the device recognizes the user's emotions in real time. The input data includes the user's facial expressions and tone of voice, which are analyzed to extract emotional information. The output data is the recognized emotional information.

[1520] Specific behavior:

[1521] Using the device's camera and microphone, the emotion engine analyzes the user's facial expressions and tone of voice, recognizes that they are "feeling stressed," and sends this information to the server.

[1522] Step 3: Automatic menu generation

[1523] The server analyzes user information and emotional information, and creates and inputs prompts to the generation AI. The input data includes user information and emotional information, and the generation AI uses this to generate a week's worth of menus that take nutritional balance into consideration. The output data is the generated menu information.

[1524] Specific behavior:

[1525] The server inputs the following prompt to the generated AI:

[1526] User information: 2 adults, 1 child, peanut allergy, loves Japanese and Italian food, feels stressed

[1527] Based on this information, please suggest a nutritionally balanced menu for one week.

[1528] The generation AI generates a menu, which is sent to the server.

[1529] Step 4: Emotional regulation and regeneration

[1530] The server reevaluates the generated menu with the emotion engine and adjusts the menu based on the user's emotions. The input data are the generated menu and the user's emotion information, and the emotion engine makes adjustments based on this. The output data is the adjusted final menu.

[1531] Specific behavior:

[1532] The generated menu is adjusted into a weekly plan that includes "Chicken Teriyaki with Ginger, which has a relaxing effect." The final menu is finalized as "Monday: Chicken Teriyaki, Tuesday: Spaghetti Bolognese."

[1533] Step 5: Generate an ingredient list

[1534] The server creates a list of ingredients based on the final menu. The input data is the final menu, and it uses the API of an online shopping site to obtain stock availability and price information. The output data is the list of ingredients.

[1535] Specific behavior:

[1536] The server creates a list of ingredients, such as "500g chicken, 100ml soy sauce, 10g ginger," and uses an online shopping API to check stock and price information, which is then provided to the user.

[1537] Step 6: Purchase ingredients and arrange delivery

[1538] The user checks the provided shopping list on their device, selects the ingredients they need, and completes the purchase. The server then sends the order information for the selected ingredients to the online shopping site, completing the purchase process. The delivery service is then notified of the order ID, delivery address, and specified date and time. The input data is the list of ingredients selected by the user, and the output data is confirmation that the order has been completed.

[1539] Specific behavior:

[1540] The user adds "chicken, soy sauce, and ginger" to the cart and completes the purchase. The server completes the order using the online shopping site API and contacts the delivery service with the "order ID, delivery address, and specified date and time" to arrange for delivery.

[1541] Step 7: Providing recipe videos and emotional feedback during cooking

[1542] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The device's emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking steps based on the feedback. The input data is the user's emotional state while cooking, and the output data is the optimized cooking steps.

[1543] Specific behavior:

[1544] The server provides a link to a video recipe for "Teriyaki Chicken," and the user cooks while watching the video on their device. If the user becomes confused during cooking, the system automatically simplifies the cooking steps and provides additional explanations.

[1545] The above is a detailed description of the specific processing flow of this system and the operation at each step.

[1546] (Application example 2)

[1547] 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."

[1548] While conventional meal preparation systems can take into account a user's preferences and allergy information, they have difficulty optimizing menu suggestions and cooking procedures that reflect the user's emotional state. As a result, they are unable to respond adequately to situations where the user is likely to feel stressed, which can result in meal preparation being time-consuming and inefficient. Furthermore, the lack of real-time emotional cooking support often leaves users confused.

[1549] 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 inputting the user's preferences, allergy information, and emotions, means for automatically generating a menu that takes nutritional balance into consideration using a generation AI and adjusting the menu based on emotional information, means for listing necessary ingredients and acquiring information from online shopping sites, means for purchasing ingredients and arranging for delivery, and means for providing the user with recipe videos, acquiring emotional feedback in real time during cooking, and optimizing cooking procedures. This makes it possible to adjust the menu and optimize cooking procedures according to the user's emotional state, resulting in efficient and stress-free meal preparation.

[1550] "User preference and allergy information" is information about preferences and allergies that are individually input by the user.

[1551] "Emotion information" is data that indicates the user's current psychological state, and is information obtained using the emotion engine.

[1552] "Generative AI" is an artificial intelligence model that automatically generates menus that take nutritional balance into consideration based on provided data.

[1553] The "means for adjusting the menu" refers to a method or function for adjusting the generated menu to an optimal one, taking into account the user's emotional information.

[1554] An "online shopping site" is an e-commerce platform for purchasing products over the Internet.

[1555] "Recipe videos" are video content that explains cooking steps and methods.

[1556] "Emotional feedback" is information that acquires the user's emotional information in real time and adjusts the system's behavior based on that information.

[1557] The "means for optimizing the cooking procedure" refers to a method or function for changing the cooking procedure to an optimal form based on the user's emotional information.

[1558] The "ingredient list" is a list of all ingredients required based on the generated menu.

[1559] "Delivery arrangement" refers to carrying out procedures to deliver the selected ingredients to a location designated by the user.

[1560] The present invention is a system that efficiently prepares nutritionally balanced meals by taking into consideration the user's preferences, allergy information, and emotional information. This system is composed of a user terminal and a server, and performs the following processes.

[1561] Registering user information

[1562] First, the user uses the device to input information such as family composition, allergies, favorite ingredients, and weekly food budget. The device is also equipped with an emotion engine that captures emotional information from the user's facial expressions in real time. This information is then sent to the server and stored in a database.

[1563] Automatic menu generation and emotion regulation

[1564] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. It also adjusts the generated menu based on emotional information obtained from the emotion engine. For example, if it detects that the user is "feeling stressed," it will suggest a menu that includes many ingredients with a relaxing effect.

[1565] Generate a list of ingredients needed

[1566] The server creates a list of ingredients based on the generated menu, and then uses the API of the online shopping site to obtain information on ingredient availability and prices, which it then provides to the user.

[1567] Purchasing ingredients and arranging delivery

[1568] The user uses the terminal to check the provided shopping list, select the ingredients they need, and complete the purchase. The server then sends the order information to the online shopping site to complete the purchase. The server then contacts the delivery service with the order ID, delivery address, and specified date and time to arrange for delivery.

[1569] Providing recipe videos and emotional feedback

[1570] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The user cooks while playing the provided recipe video on their device. The emotion engine recognizes the user's emotions in real time while cooking and optimizes the cooking procedure based on that feedback. Specifically, if the server detects that the user is "confused," it automatically provides simplifications or additional explanations.

[1571] Example of a system

[1572] If a user inputs their family composition (two adults, one child), their "peanut allergy," and their "preference for Japanese and Italian food," and the emotion engine detects that they are "feeling stressed," the generative AI model automatically generates and adjusts a menu suggestion, such as "Monday: Chicken Teriyaki (high in ginger, which has a relaxing effect) and Tuesday: Spaghetti Bolognese." The user confirms this, purchases the necessary ingredients from an online shopping site, and cooks while watching a recipe video. If confusion is detected during cooking, a prompt message will be displayed, such as, "If you find the steps difficult, we will explain in detail how to fry the chicken first and then add the ginger and soy sauce. We also provide a detailed explanation from 01:45 to 02:10 in the video."

[1573] In this way, the system adjusts menus and optimizes cooking procedures according to the user's emotional state, supporting efficient and stress-free meal preparation.

[1574] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1575] Step 1:

[1576] The user uses a device to input information such as family composition, allergy information, favorite ingredients, and weekly food budget. The emotion engine then captures the user's facial expressions and obtains emotional information. The input data includes text data such as family composition and allergy information, as well as image data, and the organized user information is sent to the server as output.

[1577] Step 2:

[1578] The server uses a generative AI model based on the received user information to automatically generate a menu that takes nutritional balance into consideration. The user information is used as input data, and a weekly menu is generated as output. In addition, based on emotional information, the menu is adjusted to include more ingredients that have a relaxing effect. Specifically, the system refers to the nutrition database and emotional database to select an appropriate menu.

[1579] Step 3:

[1580] The server creates a list of ingredients based on the generated menu and uses the online shopping site's API to obtain the availability and price information of those ingredients. The generated menu and the online shopping site's API endpoint are used as input data, and the list of ingredients, their availability, and price information is generated as output. Specifically, the server sends an API request and analyzes the received data to create the list.

[1581] Step 4:

[1582] The user uses a terminal to check the provided shopping list, select the ingredients they need, and complete the purchase procedure. The created ingredient list and the user's selection information are used as input data, and the final shopping list is determined as output. Specific actions include pressing the purchase confirmation button on the user interface.

[1583] Step 5:

[1584] The server sends the order information for the selected ingredients to the online shopping site to complete the purchase process. It also contacts the delivery service with the order ID, delivery address, and specified date and time to arrange delivery. The input data is the final purchase list and delivery address information, and the output is a confirmation of the order and the completion of delivery arrangements. Specifically, it sends the order information using an API request and makes a request to the delivery service.

[1585] Step 6:

[1586] The server retrieves the URL of the recipe video corresponding to the menu from the database and provides it to the user. The generated menu is used as input data, and the URL of the recipe video is generated as output. Specifically, the database is queried using the menu name as a key to retrieve the corresponding video URL.

[1587] Step 7:

[1588] The user cooks while playing a recipe video provided on the device. While cooking, the device uses an emotion engine to obtain the user's emotions in real time and optimizes the cooking steps based on that feedback. Real-time emotion information is used as input data, and optimized cooking steps are provided as output. Specifically, support is provided, such as displaying prompts if the user is confused.

[1589] 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.

[1590] 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.

[1591] 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 robot 414.

[1592] 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.

[1593] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1594] 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.

[1595] 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).

[1596] 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.

[1597] 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."

[1598] 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.

[1599] 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).

[1600] 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.

[1601] 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.

[1602] 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.

[1603] 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.

[1604] 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.

[1605] 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.

[1606] 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.

[1607] 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.

[1608] 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.

[1609] 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.

[1610] The following is further disclosed regarding the above embodiment.

[1611] (Claim 1)

[1612] a means for inputting user preference and allergy information;

[1613] A means to automatically generate menus that take nutritional balance into consideration using generation AI,

[1614] A way to make a list of ingredients needed and get information on online shopping sites,

[1615] A means of purchasing ingredients and arranging for delivery;

[1616] A means for providing recipe videos to users;

[1617] A system including:

[1618] (Claim 2)

[1619] 10. The system of claim 1, further comprising means for generating individually customized nutritionally balanced menus based on the user's preferences and allergy information.

[1620] (Claim 3)

[1621] The system according to claim 1, further comprising means for automatically listing necessary ingredients based on the generated menu and obtaining the information from an API of an online shopping site.

[1622] "Example 1"

[1623] (Claim 1)

[1624] A means for inputting information such as the user's family composition, allergy information, food preferences, budget, etc.

[1625] A means to automatically generate menus that take nutritional balance into consideration using a generative AI model;

[1626] A means for creating a list of ingredients required based on the generated menu;

[1627] A means of obtaining food availability and price information using an online shopping API;

[1628] A means of purchasing ingredients and arranging for delivery;

[1629] A means for providing a URL of a recipe video to a user;

[1630] A system including:

[1631] (Claim 2)

[1632] The system of claim 1, further comprising means for generating an individually customized nutritionally balanced menu by analyzing user information and inputting prompt sentences into a generative AI model.

[1633] (Claim 3)

[1634] The system of claim 1, further comprising means for automatically listing necessary ingredients based on the generated menu and obtaining the information from an online shopping API.

[1635] "Application Example 1"

[1636] (Claim 1)

[1637] a means for inputting user preference and allergy information;

[1638] A means to automatically generate menus that take nutritional balance into consideration using generation AI,

[1639] A way to list the ingredients needed and retrieve information from an online database.

[1640] A means of purchasing ingredients and arranging for delivery;

[1641] means for providing a cooking guide to a user;

[1642] A means to make real-time suggestions in physical stores,

[1643] A system including:

[1644] (Claim 2)

[1645] The system according to claim 1, further comprising a means for listing ingredients required in a physical store in real time based on the generated menu and obtaining the provision information thereof from an API of an online database.

[1646] (Claim 3)

[1647] The system according to claim 1, further comprising a means for a user to cook while watching a recipe video using a smartphone in a physical store.

[1648] "Example 2: Combining Emotion Engines"

[1649] (Claim 1)

[1650] A means to input user preferences, allergy information, family composition, and weekly food budget;

[1651] A means of recognizing emotions;

[1652] A means for automatically generating and adjusting nutritionally balanced menus based on user preferences, allergy information, and emotional information using generative AI;

[1653] A way to make a list of ingredients needed and get information on online shopping sites,

[1654] A means of purchasing ingredients and arranging for delivery;

[1655] A means for providing recipe videos to users;

[1656] A means for recognizing a user's emotions in real time while cooking and optimizing cooking procedures based on the feedback;

[1657] A system including:

[1658] (Claim 2)

[1659] 10. The system of claim 1, further comprising means for generating and adjusting individually customized nutritionally balanced menus based on user preferences, allergy information, and emotional information.

[1660] (Claim 3)

[1661] The system according to claim 1, further comprising means for automatically listing necessary ingredients based on the generated menu and obtaining the information from an API of an online shopping site.

[1662] "Application example 2 when combining emotion engines"

[1663] (Claim 1)

[1664] A means for inputting user preferences, allergy information, and emotions;

[1665] A method for automatically generating nutritionally balanced menus using generative AI and adjusting the menus based on emotional information;

[1666] A way to make a list of ingredients needed and get information on online shopping sites,

[1667] A means of purchasing ingredients and arranging for delivery;

[1668] A means for providing recipe videos to users, obtaining real-time emotional feedback during cooking, and optimizing cooking procedures;

[1669] A system including:

[1670] (Claim 2)

[1671] 10. The system of claim 1, further comprising means for generating individually customized nutritionally balanced menus based on the user's preferences, allergy information, and emotional information.

[1672] (Claim 3)

[1673] The system according to claim 1, further comprising means for automatically listing necessary ingredients based on the generated menu and obtaining the information from an API of an online shopping site. [Explanation of symbols]

[1674] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for inputting user preference and allergy information; A method for automatically generating menus that take nutritional balance into consideration using generation AI, A way to make a list of ingredients needed and get information on online shopping sites, A means of purchasing ingredients and arranging for delivery; A means for providing recipe videos to users; A system including:

2. 10. The system according to claim 1, further comprising means for generating individually customized nutritionally balanced menus based on the user's preferences and allergy information.

3. 2. The system according to claim 1, further comprising means for automatically listing necessary ingredients based on the generated menu and acquiring the information from an API of an online shopping site.

Images