System

Abstract

A system is provided.SOLUTION: A system comprising: an interface means for receiving a consultation about a meal from a user; an interactive artificial intelligence means for analyzing the received consultation contents; a recipe proposing means for proposing meal contents in consideration of the user's preference and nutrition balance based on the analyzed consultation contents; an ordering means for ordering the proposed meal contents to a corresponding restaurant industry; and a delivering means for delivering the ordered meal contents to the user's residence.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] The purpose of this invention is to solve the problem of procuring daily meals for people who have difficulty shopping, such as the elderly and people living in depopulated areas whose homes are far from the nearest grocery store or supermarket. Specifically, the objective is to provide a system that enables these people to easily obtain nutritionally balanced meals without having to go through the trouble of purchasing and cooking the appropriate ingredients. [Means for solving the problem]

[0005] To solve the above-mentioned problems, the present invention provides a system including an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for ordering the suggested meal plans from a corresponding restaurant, and a delivery means for delivering the ordered meal plans to the user's residence. Furthermore, the interactive artificial intelligence means includes a user profile management means for referencing the user's past interaction history and profile information, enabling more individually tailored suggestions. The ordering means also includes a means for monitoring the order acceptance status of the corresponding restaurant and notifying the user of the order status, allowing the user to order and receive their meal with peace of mind.

[0006] "User" refers to a person who uses the system to suggest and order meals.

[0007] "Dietary consultation" refers to inquiries and requests made by users through this system regarding food choices, nutritional balance, preferences, etc.

[0008] "Interface means" refers to input and display means for users to interact with the system, and includes, for example, a smartphone app or a dedicated terminal.

[0009] "Interactive artificial intelligence means" refers to a system that analyzes the consultation content entered by the user and uses natural language processing to provide appropriate responses and suggestions.

[0010] "User profile management means" refers to a system for storing and managing personal information such as a user's past interaction history, preferences, and allergy information.

[0011] "Recipe suggestion means" refers to a system that suggests meal plans that take nutritional balance into consideration based on the user's consultation details and profile information.

[0012] "Ordering means" refers to a system for placing an order for the proposed meal contents with the food service industry.

[0013] "Delivery means" refers to a system for delivering ordered meals to the user's designated residence.

[0014] The "food service industry" refers to restaurants and catering services that provide meals.

[0015] "Means for notifying the order status" refers to a system for notifying the user of the acceptance status and delivery status of the order placed by the user. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from the restaurant industry to the user's residence. This system includes the following main components:

[0038] 1. User Interface (UI)

[0039] 2. Conversational AI Engine

[0040] 3. User Profile Management System

[0041] 4. Recipe suggestion engine

[0042] 5. Ordering System

[0043] 6. Delivery System

[0044] User Interface (UI)

[0045] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0046] Conversational Artificial Intelligence Engine

[0047] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0048] User Profile Management System

[0049] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0050] Recipe suggestion engine

[0051] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and the user profile to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[0052] Ordering System

[0053] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0054] Delivery System

[0055] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0056] Specific examples

[0057] 1. User accesses the system:

[0058] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0059] 2. Start a conversation:

[0060] Server: A conversational AI engine responds, "What would you like to eat today?"

[0061] 3. User Answer:

[0062] Terminal: The user types, "I'd like a vegetable-based menu."

[0063] 4. User Profile Reference:

[0064] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0065] 5. Recipe suggestions:

[0066] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[0067] 6. User Choice:

[0068] Terminal: User selects "Yes, please."

[0069] 7. Submitting an order:

[0070] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0071] 8. Delivery Arrangements:

[0072] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0073] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[0074] The processing flow will be explained below.

[0075] Step 1:

[0076] Terminal: The user launches the smartphone app and accesses the system. The terminal requests user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[0077] Step 2:

[0078] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[0079] Step 3:

[0080] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[0081] Step 4:

[0082] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[0083] Step 5:

[0084] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[0085] Step 6:

[0086] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[0087] Step 7:

[0088] Server: The recipe suggestion engine generates a recipe based on the user's request and profile information. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[0089] Step 8:

[0090] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[0091] Step 9:

[0092] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[0093] Step 10:

[0094] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[0095] Step 11:

[0096] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[0097] Example 1

[0098] 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."

[0099] For elderly people and people living in depopulated areas who have difficulty shopping, there is a lack of nutritionally balanced meal suggestions and easy ways to order and deliver them. There is also a need for technology that can efficiently suggest meals that take into account the user's individual preferences and allergy information. Our goal is to provide a system that supports healthy eating habits by solving these issues.

[0100] 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.

[0101] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the content of the consultations accepted, and a recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed content of the consultations. This enables users to easily receive nutritionally balanced meal suggestions, order meals based on the suggestions, and have them delivered to their homes.

[0102] The "interface means" is a means for accepting dietary consultations from users, and has the function of accepting requests entered by users via a dedicated terminal or smartphone app.

[0103] An "interactive artificial intelligence means" is a means for analyzing the content of inquiries received from users, and has the function of understanding the user's request using natural language processing and generating appropriate responses and questions.

[0104] The "recipe suggestion means" is a means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content, and has the function of generating optimal recipes based on user profile information and requests.

[0105] The "ordering means" is a means for placing an order with the restaurant that corresponds to the proposed meal contents, and has the function of sending an order to the restaurant based on the recipe selected by the user.

[0106] The "delivery means" is a means for delivering the ordered meal contents to the user's residence, and has the function of delivering the meal to the user's home in cooperation with a food delivery company.

[0107] The "user profile management means" is a means for managing a user's past interaction history and profile information for reference by the interactive artificial intelligence means, and has the function of enabling responses according to the individual requests of each user.

[0108] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from a restaurant to the user's residence. The system includes a user interface (UI), an interactive AI engine, a user profile management system, a recipe suggestion engine, an ordering system, and a delivery system.

[0109] User Interface (UI)

[0110] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user can start a conversation with the system by inputting a request such as, "I'd like some advice on what to eat today."

[0111] Conversational Artificial Intelligence Engine

[0112] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0113] User Profile Management System

[0114] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to individual user requests.

[0115] Recipe suggestion engine

[0116] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and user profiles to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0117] Ordering System

[0118] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0119] Delivery System

[0120] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0121] Specific examples

[0122] Below are some specific examples of how the system can be used.

[0123] 1. A user accesses the system

[0124] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0125] 2. Start a dialogue

[0126] Server: A conversational AI engine responds, "What would you like to eat today?"

[0127] 3. User Responses

[0128] Terminal: The user types, "I'd like a vegetable-based menu."

[0129] 4. User profile reference

[0130] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0131] 5. Recipe suggestions

[0132] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[0133] 6. User Choice

[0134] Terminal: User selects "Yes, please."

[0135] 7. Submitting an Order

[0136] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0137] 8. Delivery Arrangements

[0138] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0139] Examples of prompts for generative AI models

[0140] 1. "Could you please suggest a nutritionally balanced dinner menu for the elderly? Please give examples of menus that are particularly suitable for those who do not like seafood."

[0141] 2. "A user in a sparsely populated area wants a plant-based dinner. Explain the recipe suggestions and ordering process."

[0142] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[0143] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0144] Step 1:

[0145] A user connects to the system

[0146] Terminal: The user accesses the system by starting a dedicated terminal or smartphone app. Specifically, the user opens the app and enters "What should I have for dinner tonight?" into the interactive input form. This action sends the user's request to the system.

[0147] Input: User's meal-related enquiry (e.g., "What should we have for dinner tonight?")

[0148] Output: User request sent to server

[0149] Step 2:

[0150] A conversational artificial intelligence engine analyzes the request

[0151] Server: The conversational AI engine receives requests sent by users and analyzes the content using natural language processing. Specifically, it understands specific conditions and requests, such as "I don't like seafood," and generates appropriate questions and responses.

[0152] Input: User request data (e.g., "I'd like a menu that's mainly vegetables.")

[0153] Data processing: Natural language processing algorithms analyze the text and extract the required information.

[0154] Output: Generates a response or follow-up question based on the user's request (e.g., "What would you like to eat today?").

[0155] Step 3:

[0156] Retrieving information from a user profile management system

[0157] Server: The conversational AI engine retrieves user preferences and allergies from the user profile management system database, enabling personalized responses.

[0158] Input: Request data, including the user's ID and past interaction history

[0159] Data processing: A database query is performed to retrieve profile information for the relevant users.

[0160] Output: Profile data including user preferences and allergy information

[0161] Step 4:

[0162] Recipe suggestion engine generates recipes

[0163] Server: The recipe suggestion engine generates appropriate recipes that take nutritional balance into consideration based on information obtained from the conversational AI engine and the user profile. For example, if you request a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[0164] Input: User preferences and profile data

[0165] Data processing: Recipe suggestion algorithms generate recipes based on user profiles and preferences.

[0166] Output: Suggested recipe (e.g. "Grilled chicken breast with vegetable salad")

[0167] Step 5:

[0168] The user selects a recipe

[0169] On your device: The user selects one of the suggested recipes and selects "I'd like this recipe." Specifically, they tap "Grilled chicken breast and vegetable salad" from the list of recipes displayed.

[0170] Input: List of suggested recipes

[0171] Output: The recipe selected by the user (e.g., "Grilled chicken breast and vegetable salad")

[0172] Step 6:

[0173] The ordering system processes the order.

[0174] Server: Receives the recipe selected by the user and sends the order to the corresponding restaurant business through the ordering system. For example, it transfers the order information for the specified recipe to the restaurant's ordering system.

[0175] Input: User-selected recipe information

[0176] Data processing: The data is sent to the restaurant industry's API as order data.

[0177] Output: Order information sent to the restaurant

[0178] Step 7:

[0179] The delivery system arranges the delivery

[0180] Server: After the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location, for example, by adding the user's address to a delivery list at the specified time.

[0181] Input: Food preparation notification from the restaurant industry

[0182] Data processing: A delivery request is sent to the delivery company's system.

[0183] Output: Instructions for the meal to be delivered to the user's location.

[0184] Through this series of processes, users can easily obtain nutritionally balanced meals and maintain healthy eating habits.

[0185] (Application example 1)

[0186] 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."

[0187] Elderly people and people living in depopulated areas have difficulty eating a nutritionally balanced diet because they find it difficult to shop. They also have difficulty determining what kind of food is best for them, making it difficult for them to choose the right meal. For these users, there is a need for a system that can easily suggest meals and deliver them to their homes.

[0188] 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.

[0189] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, and a user interface means and smartphone application for suggesting appropriate recipes based on the user's consultation content and processing voice or text input. This allows users to easily select a nutritionally balanced meal that suits them and receive that meal at home.

[0190] The "interface means for receiving dietary consultations from users" is an input interface that allows users to input questions or requests about their own diet.

[0191] The "interactive artificial intelligence means for analyzing the received consultation content" is an interactive artificial intelligence (AI) system that analyzes the input content from the user and generates appropriate responses and suggestions.

[0192] The "recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content" is a system that suggests appropriate recipes based on the user's input, preferences, and nutritional balance.

[0193] The "ordering means for placing an order for the proposed meal contents with the corresponding restaurant industry" is a system for placing an order for the proposed recipe with the restaurant industry.

[0194] "Delivery means for delivering the ordered meal contents to the user's residence" is a system that delivers the ordered meal to the address specified by the user.

[0195] A "user interface means for processing voice or text input" is an interface for receiving information input by a user in voice or text form.

[0196] A "smartphone application" is application software that runs on a smartphone.

[0197] A "server" is a central computer system that performs various processes and mediates data exchange between users, the restaurant industry, and delivery companies.

[0198] A specific system for realizing the present invention is composed of multiple components, each of which will be described in detail below, along with its operation.

[0199] User Interface Means

[0200] The server provides a simple user interface that allows users to input meal-related inquiries and requests. This interface is implemented as a smartphone application. Users can make requests via text or voice input, for example, by entering questions such as "What should I have for dinner tonight?"

[0201] Interactive Artificial Intelligence Tools

[0202] The server uses conversational artificial intelligence (AI) to analyze the inquiries received from users. The AI ​​uses natural language processing to understand the user's request and generate appropriate questions and responses. For example, if a user requests, "I'd like a menu that's mainly vegetables," the server analyzes this and moves on to the next step.

[0203] User profile management methods

[0204] The conversational AI means utilizes a user profile management system to reference the user's past interaction history and profile information. This system stores the user's preferences, allergy information, past order history, etc. For example, if the user has registered that they are allergic to seafood, suggestions will be made based on that information.

[0205] Recipe suggestion method

[0206] The server proposes nutritionally balanced recipes based on the information obtained from the conversational AI means and the user profile. For example, in response to a request for a vegetable-based menu, the server proposes "Summer vegetable ratatouille" and asks, "Is this recipe okay?"

[0207] Ordering Method

[0208] When the user selects a suggested recipe, the server places a meal order with the corresponding restaurant. For example, if the user selects "Yes, please," an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[0209] Delivery method

[0210] After the ordered meal is ready, the server coordinates with a food delivery company to deliver the meal to the user's residence. For example, once the meal is ready, the server may issue instructions to a delivery company to arrange for the meal to be delivered to the user's home.

[0211] Hardware and software used

[0212] This system utilizes the following hardware and software:

[0213] Hardware: Smartphone

[0214] Software: Flask (web framework), requests (HTTP request library)

[0215] Database: In actual implementation, SQL or NoSQL databases are used.

[0216] API integration: API integration with the restaurant industry and food delivery companies

[0217] Specific examples

[0218] For example, if a user opens a smartphone app and types, "What should I have for dinner tonight?", the conversational AI engine will respond with, "What would you like to eat today?" If the user types, "I'd like a vegetable-based menu," the recipe suggestion engine will suggest "Summer vegetable ratatouille" and place the order according to the user's selection. Allergy information and past history are also referenced to suggest the most suitable and safe meal for the user.

[0219] Prompt Sentence Examples

[0220] If the user types "Suggest a vegetable-based, meatless dinner," the prompt text might look like this:

[0221] "I'd like some suggestions for a vegetable-based, meatless dinner."

[0222] Based on this, a system will be built that suggests appropriate recipes and delivers the meals to the user's home.

[0223] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0224] Step 1:

[0225] A user opens a smartphone app on their device and inputs a dietary inquiry. This input is sent to the server as a text question or request. For example, the input might be, "What should I have for dinner tonight?" The server accepts this input and prepares the data for the next processing step.

[0226] Step 2:

[0227] The server sends the received consultation details to the interactive AI means. The interactive AI uses natural language processing to analyze the user's input and understand the content of the question or request. Through this analysis, the AI ​​extracts specific information from the user's needs and converts them into a specific request, such as "I'd like a menu that is mainly vegetables."

[0228] Step 3:

[0229] Based on the analyzed request, the server accesses the user profile management means to obtain profile information such as the user's past interaction history, allergy information, and preferences. This provides data to determine whether the suggested recipe meets the user's individual requirements. For example, this information may include information such as "the user does not like seafood."

[0230] Step 4:

[0231] The server generates appropriate recipes using the recipe suggestion means based on information obtained from the interactive artificial intelligence and the user profile management means. The recipes take into consideration the nutritional balance and the user's preferences. For example, specific menus such as "Summer vegetable ratatouille" and "Grilled chicken breast and vegetable salad" are suggested.

[0232] Step 5:

[0233] The server sends the proposed recipe to the terminal for confirmation by the user. The user confirms the proposed recipe and enters a confirmation such as "Yes, please." This input is sent to the server and used as data to proceed to the next processing step.

[0234] Step 6:

[0235] The server receives confirmation from the user and uses the ordering means to place a meal order with the corresponding restaurant. The order is processed automatically online, so the user does not need to manually place the order. For example, an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[0236] Step 7:

[0237] After the order is confirmed by the restaurant and the meal is prepared, the server uses a delivery method to instruct the food delivery company to deliver the meal to the user's residence. Based on this instruction, the food delivery company delivers the meal to the user's home. The user's address information is used to arrange the delivery.

[0238] These processing steps allow users to easily select a nutritionally balanced meal that is right for them and have it delivered to their home.

[0239] 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.

[0240] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers those meals to the user's residence from a restaurant. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[0241] System Configuration

[0242] The system includes the following major components:

[0243] 1. User Interface (UI)

[0244] 2. Conversational AI Engine

[0245] 3. User Profile Management System

[0246] 4. Recipe suggestion engine

[0247] 5. Ordering System

[0248] 6. Delivery System

[0249] 7. Emotion Engine

[0250] User Interface (UI)

[0251] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0252] Conversational Artificial Intelligence Engine

[0253] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0254] User Profile Management System

[0255] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0256] Recipe suggestion engine

[0257] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0258] Ordering System

[0259] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0260] Delivery System

[0261] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0262] Emotion Engine

[0263] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[0264] Specific examples

[0265] 1. User accesses the system:

[0266] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0267] 2. Start a conversation:

[0268] Server: A conversational AI engine responds, "What would you like to eat today?"

[0269] 3. User Answer:

[0270] Terminal: The user types, "I'd like a vegetable-based menu."

[0271] 4. User Profile Reference:

[0272] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0273] 5. Emotion Analysis:

[0274] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[0275] 6. Recipe suggestions

[0276] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[0277] 7. User Choice:

[0278] Terminal: User selects "Yes, please."

[0279] 8. Submitting an Order:

[0280] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0281] 9. Delivery Arrangements:

[0282] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0283] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[0284] The processing flow will be explained below.

[0285] Step 1:

[0286] Terminal: The user launches the smartphone app and accesses the system. The terminal prompts for user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[0287] Step 2:

[0288] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[0289] Step 3:

[0290] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[0291] Step 4:

[0292] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[0293] Step 5:

[0294] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[0295] Step 6:

[0296] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[0297] Step 7:

[0298] Server: The emotion engine analyzes the user's dialogue and voice data to recognize the user's emotional state. For example, if the user is feeling stressed, it passes that information to the conversational AI engine.

[0299] Step 8:

[0300] Server: The recipe suggestion engine generates recipes based on the user's requests, profile information, and emotional state. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[0301] Step 9:

[0302] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[0303] Step 10:

[0304] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[0305] Step 11:

[0306] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[0307] Step 12:

[0308] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[0309] Example 2

[0310] 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."

[0311] Currently, many elderly people and those living in depopulated areas face difficulties with daily shopping and meal preparation. Furthermore, food choices are often made without considering individual preferences or health conditions, leading to nutritional imbalances. In particular, the lack of meal suggestions tailored to the user's emotional state may also affect their mental health.

[0312] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for ordering the suggested meal plans from a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's dialogue content and voice data and recognizing the user's emotional state, and a suggestion adjustment means for adjusting the suggestion content based on the emotion analysis results and making personalized suggestions. As a result, meal options are suggested in a form that is appropriate not only to the user's individual preferences and health condition but also to the user's emotional state, allowing the user to maintain a healthier and more satisfying dietary lifestyle.

[0313] The "interface means" refers to an input means by which a user accesses the system and makes dietary consultations.

[0314] "Interactive artificial intelligence means" refers to artificial intelligence technology that uses natural language processing to analyze the content of the consultation received and generate an appropriate response.

[0315] The "recipe suggestion means" is a means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content.

[0316] The "ordering means" is a means for placing an order with the restaurant industry based on the proposed meal contents.

[0317] "Delivery means" refers to a means for delivering the ordered meal to the user's residence after it has been prepared.

[0318] The "emotion analysis means" is a means for analyzing the content of the user's dialogue and voice data to recognize the user's emotional state.

[0319] The "proposal adjustment means" is a means for adjusting the content of meal proposals based on the emotion analysis results and making personalized proposals.

[0320] The "user profile management means" is a means for storing and referencing a user's past interaction history and profile information.

[0321] The "means for notifying the order status" is a means for monitoring the order acceptance status of the restaurant industry and contacting the user.

[0322] MODE FOR CARRYING OUT THE INVENTION

[0323] This system, which targets elderly people and those living in depopulated areas, uses conversational AI to suggest meal plans and delivers those meals to the user's residence from the restaurant industry. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[0324] The system includes the following major components:

[0325] User Interface (UI)

[0326] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0327] Conversational Artificial Intelligence Engine

[0328] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0329] User Profile Management System

[0330] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0331] Recipe suggestion engine

[0332] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0333] Ordering System

[0334] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0335] Delivery System

[0336] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0337] Emotion Engine

[0338] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[0339] Specific examples

[0340] 1. User accesses the system:

[0341] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0342] 2. Start a conversation:

[0343] Server: A conversational AI engine responds, "What would you like to eat today?"

[0344] 3. User Answer:

[0345] Terminal: The user types, "I'd like a vegetable-based menu."

[0346] 4. User Profile Reference:

[0347] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0348] 5. Emotion Analysis:

[0349] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[0350] 6. Recipe suggestions

[0351] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[0352] 7. User Choice:

[0353] Terminal: User selects "Yes, please."

[0354] 8. Submitting an Order:

[0355] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0356] 9. Delivery Arrangements:

[0357] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0358] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[0359] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0360] Step 1:

[0361] A user accesses the system

[0362] Input: A user launches a smartphone app and enters a prompt such as "What should we have for dinner tonight?"

[0363] Processing: The terminal receives the user's input and sends it to the server.

[0364] Output: The user request is sent to the server.

[0365] Step 2:

[0366] Receive and analyze user interaction requests

[0367] Input: The server receives a request sent by the user.

[0368] Processing: The conversational AI engine analyzes the received request using natural language processing technology. It understands that the request is for dietary advice and extracts keywords related to the user's preferences and dietary restrictions.

[0369] Output: Parsed request content and extracted keywords.

[0370] Specific operation: For example, if a user inputs "I'd like a menu that mainly consists of vegetables," the system will extract the keywords "vegetables" and "menu."

[0371] Step 3:

[0372] Viewing a user profile

[0373] Input: Parsed request content and extracted keywords.

[0374] Processing: The server accesses the user profile management system and references the user's profile information (past interaction history, preferences, allergy information, etc.).

[0375] Output: User profile information.

[0376] Specific behavior: For example, if the user previously set "nut allergy," obtain that information.

[0377] Step 4:

[0378] Analyzing user emotions with an emotion engine

[0379] Input: User request details and user profile information.

[0380] Processing: The emotion engine analyzes the emotion from the user's input. If there is voice data, it performs voice analysis, and if there is text data, it performs text analysis.

[0381] Output: User's emotional state information.

[0382] Specific behavior: For example, if a user inputs "I feel kind of tired today," the emotional state "tired" is recognized.

[0383] Step 5:

[0384] Suggest a recipe

[0385] Input: Extracted keywords, user profile information, and emotional state information.

[0386] Processing: The recipe suggestion engine selects recipes suitable for the user based on the input information above. It also adjusts the suggestions taking into account nutritional balance and emotional state.

[0387] Output: A suggested recipe.

[0388] Specific behavior: For example, if a user types "I want to relax," the app will suggest "relaxing vegetable soup with herbs."

[0389] Step 6:

[0390] The user selects a recipe

[0391] Input: A suggested recipe.

[0392] Process: The suggested recipes are displayed on the device, and the user selects one.

[0393] Output: The recipe selected by the user.

[0394] Specific operation: For example, the user selects "Summer vegetable ratatouille."

[0395] Step 7:

[0396] The ordering system sends the order

[0397] Input: The recipe selected by the user.

[0398] Processing: The server's ordering system sends the order to the corresponding restaurant based on the selected recipe. The order is accepted in real time.

[0399] Output: Order notification to the food service industry.

[0400] Specific operation: For example, a server sends an order for "Summer vegetable ratatouille" to a restaurant.

[0401] Step 8:

[0402] The delivery system arranges the delivery

[0403] Input: Meals prepared in the food service industry.

[0404] Processing: Once the meal is ready, the server's delivery system sends instructions to a food delivery company to arrange delivery to the user's location. Delivery status can be tracked in real time.

[0405] Output: Delivery status notification to user.

[0406] Specific operation: For example, after the meal is ready, the server instructs the delivery company to "deliver to the user's home," and the user can check the delivery status in the app.

[0407] (Application example 2)

[0408] 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."

[0409] Elderly people and those living in depopulated areas often face difficulties in preparing and selecting meals. This creates a need for an easy way to obtain nutritionally balanced meals. Furthermore, the lack of a system that can provide meal suggestions based on the user's emotional state prevents the provision of more personalized services. Additionally, there is a need for a smartphone application with advanced interactive capabilities.

[0410] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0411] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's emotional state and adjusting the suggested meal plans based on the emotion, and a user interface means in the form of a smartphone application, thereby enabling personalized meal suggestions and delivery according to the user's emotional state.

[0412] The "interface means" refers to an input and display device that allows the user to input dietary advice and receive suggestions from the system.

[0413] The "interactive artificial intelligence means" is a component that uses an artificial intelligence algorithm and natural language processing technology to analyze the content of the consultation received from the user and generate a response.

[0414] The "recipe suggestion means" is a function for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on information analyzed by the interactive artificial intelligence means.

[0415] The "ordering means" is a communication function for placing an order for the proposed meal contents with the corresponding restaurant.

[0416] "Delivery method" refers to a logistics system and a function linked to a delivery company for delivering the ordered meal contents to the user's residence.

[0417] "Emotion analysis means" refers to algorithms and computational techniques that analyze a user's emotional state and tailor suggestions based on that data.

[0418] A "smartphone application" is a software application that runs on a smartphone device and functions in conjunction with user interface means and other system components.

[0419] The "user profile management means" refers to a database and management system for storing and referencing a user's past interaction history and profile information.

[0420] The embodiment of the present invention mainly comprises the following components:

[0421] 1. User interface means (smartphone application)

[0422] 2. Interactive AI methods

[0423] 3. User profile management methods

[0424] 4. Recipe suggestion method

[0425] 5. Order Methods

[0426] 6. Delivery method

[0427] 7. Emotion analysis method

[0428] Overall Architecture

[0429] Accepting requests from users

[0430] Users use a smartphone application to input dietary inquiries, such as a request like, "What should I have for dinner tonight?" The application has an intuitive, easy-to-use interface and is designed to be easy to operate even for elderly people.

[0431] Analysis of Conversational Artificial Intelligence

[0432] The server analyzes the received request using an interactive AI means, which uses natural language processing technology to understand the user's input and generate an appropriate response, taking into account the user's preferences, allergy information, etc.

[0433] Viewing User Profiles

[0434] The server uses user profile management means to refer to past interaction history and profile information, which allows for more personalized responses. For example, if the user previously input information such as "I don't like seafood," this information will be taken into consideration.

[0435] Tailoring recommendations through sentiment analysis

[0436] The server uses emotion analysis to analyze the user's emotional state. This analysis is based on voice data and dialogue content, and the suggestions are adjusted to reflect the user's emotional state. For example, if the user is feeling stressed, a menu using ingredients with a relaxing effect will be suggested.

[0437] Recipe Suggestions

[0438] The server uses the recipe suggestion tool to suggest recipes that take nutritional balance into consideration based on the results of sentiment analysis and user profile information, such as "relaxing vegetable soup with herbs" or "grilled chicken breast and vegetable salad."

[0439] Ordering and Shipping

[0440] When the user selects a suggested recipe, the server uses the ordering means to place an order with the corresponding restaurant, and then uses the delivery means to deliver the order to the user's address, allowing the user to easily complete the entire process from request to final meal delivery.

[0441] Hardware and software used

[0442] The implementation of this system uses the following hardware and software:

[0443] Server: Flask (a Python micro web framework), Database (RDBMS or NoSQL)

[0444] User Interface: Smartphone application

[0445] Conversational AI: Natural language processing technology (GPT-3, etc.)

[0446] Sentiment analysis engine: IBM Watson, Azure AI, etc.

[0447] Specific examples

[0448] For example, an elderly user might use a smartphone application to input a request such as, "What should we have for dinner tonight?"

[0449] Assume that the interactive artificial intelligence means responds with "What would you like to eat today?" and the user replies, "I'd like a menu that is mainly vegetables."

[0450] Next, the emotion analysis means analyzes the user's emotion as "stress," and the recipe suggestion means suggests "relaxing vegetable soup using herbs."

[0451] Prompt Sentence Examples

[0452] "Based on the analysis results of the emotion engine, suggest meals that will have a relaxing effect on the elderly. Consider the user's data profile and emotional state and suggest recipes using appropriate ingredients."

[0453] In this way, users can easily obtain the optimal diet according to their emotional state and maintain their health.

[0454] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0455] Step 1:

[0456] The user starts the smartphone application and inputs a request about food, for example, "What should I have for dinner tonight?"

[0457] Input: User's meal request

[0458] Output: Request sent by smartphone application to server

[0459] Step 2:

[0460] The server passes the received request to an interactive AI means for analysis, which uses natural language processing techniques to analyze the user's input and generate a response.

[0461] Input: User request

[0462] Output: Parsed request and appropriate response

[0463] Step 3:

[0464] Based on the analysis results, the server uses the user profile management means to refer to the user's past interaction history and profile information. For example, if the user has previously registered food allergies or dislikes, that information is obtained.

[0465] Input: Parsed request content

[0466] Output: User's past interaction history and profile information

[0467] Step 4:

[0468] The emotion analysis means analyzes the user's emotional state based on the dialogue content and voice data, and is then ready to adjust the suggestions according to the user's emotional state.

[0469] Input: Dialogue content and voice data

[0470] Output: Parsed user's emotional state

[0471] Step 5:

[0472] The server uses the recipe suggestion means to suggest a nutritionally balanced meal, taking into account the results of the sentiment analysis and the user profile information. For example, it suggests a "relaxing vegetable soup using herbs."

[0473] Input: User's emotional state and profile information

[0474] Output: Suggested recipe content

[0475] Step 6:

[0476] The user reviews the suggested recipe via a smartphone application and enters a response such as "I'd like this recipe, please."

[0477] Input: User response to suggested recipe

[0478] Output: Sending user selections to the server

[0479] Step 7:

[0480] The server uses the ordering means to place an order for the selected recipe with the corresponding restaurant business, and the ordering means transmits the order data using a communication function.

[0481] Input: Recipe content selected by the user

[0482] Output: Order data for the restaurant industry

[0483] Step 8:

[0484] After the order is completed, the delivery method will coordinate with the food delivery company to arrange delivery to the user's residence. The server will monitor the delivery status and notify the user as necessary.

[0485] Input: Order data and shipping information

[0486] Output: Delivery instructions and delivery status notification to the user

[0487] Through these steps, users are easily recommended nutritionally balanced meals and have meals delivered to their home that correspond to their emotional state.

[0488] 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.

[0489] 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.

[0490] 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.

[0491] [Second embodiment]

[0492] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0493] 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.

[0494] 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).

[0495] 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.

[0496] 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.

[0497] 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).

[0498] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0499] 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.

[0500] 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.

[0501] 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.

[0502] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0503] 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."

[0504] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from the restaurant industry to the user's residence. This system includes the following main components:

[0505] 1. User Interface (UI)

[0506] 2. Conversational AI Engine

[0507] 3. User Profile Management System

[0508] 4. Recipe suggestion engine

[0509] 5. Ordering System

[0510] 6. Delivery System

[0511] User Interface (UI)

[0512] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0513] Conversational Artificial Intelligence Engine

[0514] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0515] User Profile Management System

[0516] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0517] Recipe suggestion engine

[0518] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and the user profile to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[0519] Ordering System

[0520] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0521] Delivery System

[0522] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0523] Specific examples

[0524] 1. User accesses the system:

[0525] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0526] 2. Start a conversation:

[0527] Server: A conversational AI engine responds, "What would you like to eat today?"

[0528] 3. User Answer:

[0529] Terminal: The user types, "I'd like a vegetable-based menu."

[0530] 4. User Profile Reference:

[0531] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0532] 5. Recipe suggestions:

[0533] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[0534] 6. User Choice:

[0535] Terminal: User selects "Yes, please."

[0536] 7. Submitting an order:

[0537] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0538] 8. Delivery Arrangements:

[0539] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0540] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[0541] The processing flow will be explained below.

[0542] Step 1:

[0543] Terminal: The user launches the smartphone app and accesses the system. The terminal requests user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[0544] Step 2:

[0545] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[0546] Step 3:

[0547] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[0548] Step 4:

[0549] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[0550] Step 5:

[0551] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[0552] Step 6:

[0553] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[0554] Step 7:

[0555] Server: The recipe suggestion engine generates a recipe based on the user's request and profile information. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[0556] Step 8:

[0557] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[0558] Step 9:

[0559] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[0560] Step 10:

[0561] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[0562] Step 11:

[0563] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[0564] Example 1

[0565] 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."

[0566] For elderly people and people living in depopulated areas who have difficulty shopping, there is a lack of nutritionally balanced meal suggestions and easy ways to order and deliver them. There is also a need for technology that can efficiently suggest meals that take into account the user's individual preferences and allergy information. Our goal is to provide a system that supports healthy eating habits by solving these issues.

[0567] 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.

[0568] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the content of the consultations accepted, and a recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed content of the consultations. This enables users to easily receive nutritionally balanced meal suggestions, order meals based on the suggestions, and have them delivered to their homes.

[0569] The "interface means" is a means for accepting dietary consultations from users, and has the function of accepting requests entered by users via a dedicated terminal or smartphone app.

[0570] An "interactive artificial intelligence means" is a means for analyzing the content of inquiries received from users, and has the function of understanding the user's request using natural language processing and generating appropriate responses and questions.

[0571] The "recipe suggestion means" is a means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content, and has the function of generating optimal recipes based on user profile information and requests.

[0572] The "ordering means" is a means for placing an order with the restaurant that corresponds to the proposed meal contents, and has the function of sending an order to the restaurant based on the recipe selected by the user.

[0573] The "delivery means" is a means for delivering the ordered meal contents to the user's residence, and has the function of delivering the meal to the user's home in cooperation with a food delivery company.

[0574] The "user profile management means" is a means for managing a user's past interaction history and profile information for reference by the interactive artificial intelligence means, and has the function of enabling responses according to the individual requests of each user.

[0575] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from a restaurant to the user's residence. The system includes a user interface (UI), an interactive AI engine, a user profile management system, a recipe suggestion engine, an ordering system, and a delivery system.

[0576] User Interface (UI)

[0577] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user can start a conversation with the system by inputting a request such as, "I'd like some advice on what to eat today."

[0578] Conversational Artificial Intelligence Engine

[0579] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0580] User Profile Management System

[0581] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to individual user requests.

[0582] Recipe suggestion engine

[0583] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and user profiles to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0584] Ordering System

[0585] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0586] Delivery System

[0587] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0588] Specific examples

[0589] Below are some specific examples of how the system can be used.

[0590] 1. A user accesses the system

[0591] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0592] 2. Start a dialogue

[0593] Server: A conversational AI engine responds, "What would you like to eat today?"

[0594] 3. User Responses

[0595] Terminal: The user types, "I'd like a vegetable-based menu."

[0596] 4. User profile reference

[0597] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0598] 5. Recipe suggestions

[0599] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[0600] 6. User Choice

[0601] Terminal: User selects "Yes, please."

[0602] 7. Submitting an Order

[0603] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0604] 8. Delivery Arrangements

[0605] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0606] Examples of prompts for generative AI models

[0607] 1. "Could you please suggest a nutritionally balanced dinner menu for the elderly? Please give examples of menus that are particularly suitable for those who do not like seafood."

[0608] 2. "A user in a sparsely populated area wants a plant-based dinner. Explain the recipe suggestions and ordering process."

[0609] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[0610] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0611] Step 1:

[0612] A user connects to the system

[0613] Terminal: The user accesses the system by starting a dedicated terminal or smartphone app. Specifically, the user opens the app and enters "What should I have for dinner tonight?" into the interactive input form. This action sends the user's request to the system.

[0614] Input: User's meal-related enquiry (e.g., "What should we have for dinner tonight?")

[0615] Output: User request sent to server

[0616] Step 2:

[0617] A conversational artificial intelligence engine analyzes the request

[0618] Server: The conversational AI engine receives requests sent by users and analyzes the content using natural language processing. Specifically, it understands specific conditions and requests, such as "I don't like seafood," and generates appropriate questions and responses.

[0619] Input: User request data (e.g., "I'd like a menu that's mainly vegetables.")

[0620] Data processing: Natural language processing algorithms analyze the text and extract the required information.

[0621] Output: Generates a response or follow-up question based on the user's request (e.g., "What would you like to eat today?").

[0622] Step 3:

[0623] Retrieving information from a user profile management system

[0624] Server: The conversational AI engine retrieves user preferences and allergies from the user profile management system database, enabling personalized responses.

[0625] Input: Request data, including the user's ID and past interaction history

[0626] Data processing: A database query is performed to retrieve profile information for the relevant users.

[0627] Output: Profile data including user preferences and allergy information

[0628] Step 4:

[0629] Recipe suggestion engine generates recipes

[0630] Server: The recipe suggestion engine generates appropriate recipes that take nutritional balance into consideration based on information obtained from the conversational AI engine and the user profile. For example, if you request a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[0631] Input: User preferences and profile data

[0632] Data processing: Recipe suggestion algorithms generate recipes based on user profiles and preferences.

[0633] Output: Suggested recipe (e.g. "Grilled chicken breast with vegetable salad")

[0634] Step 5:

[0635] The user selects a recipe

[0636] On your device: The user selects one of the suggested recipes and selects "I'd like this recipe." Specifically, they tap "Grilled chicken breast and vegetable salad" from the list of recipes displayed.

[0637] Input: List of suggested recipes

[0638] Output: The recipe selected by the user (e.g., "Grilled chicken breast and vegetable salad")

[0639] Step 6:

[0640] The ordering system processes the order.

[0641] Server: Receives the recipe selected by the user and sends the order to the corresponding restaurant business through the ordering system. For example, it transfers the order information for the specified recipe to the restaurant's ordering system.

[0642] Input: User-selected recipe information

[0643] Data processing: The data is sent to the restaurant industry's API as order data.

[0644] Output: Order information sent to the restaurant

[0645] Step 7:

[0646] The delivery system arranges the delivery

[0647] Server: After the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location, for example, by adding the user's address to a delivery list at the specified time.

[0648] Input: Food preparation notification from the restaurant industry

[0649] Data processing: A delivery request is sent to the delivery company's system.

[0650] Output: Instructions for the meal to be delivered to the user's location.

[0651] Through this series of processes, users can easily obtain nutritionally balanced meals and maintain healthy eating habits.

[0652] (Application example 1)

[0653] 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."

[0654] Elderly people and people living in depopulated areas have difficulty eating a nutritionally balanced diet because they find it difficult to shop. They also have difficulty determining what kind of food is best for them, making it difficult for them to choose the right meal. For these users, there is a need for a system that can easily suggest meals and deliver them to their homes.

[0655] 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.

[0656] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, and a user interface means and smartphone application for suggesting appropriate recipes based on the user's consultation content and processing voice or text input. This allows users to easily select a nutritionally balanced meal that suits them and receive that meal at home.

[0657] The "interface means for receiving dietary consultations from users" is an input interface that allows users to input questions or requests about their own diet.

[0658] The "interactive artificial intelligence means for analyzing the received consultation content" is an interactive artificial intelligence (AI) system that analyzes the input content from the user and generates appropriate responses and suggestions.

[0659] The "recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content" is a system that suggests appropriate recipes based on the user's input, preferences, and nutritional balance.

[0660] The "ordering means for placing an order for the proposed meal contents with the corresponding restaurant industry" is a system for placing an order for the proposed recipe with the restaurant industry.

[0661] "Delivery means for delivering the ordered meal contents to the user's residence" is a system that delivers the ordered meal to the address specified by the user.

[0662] A "user interface means for processing voice or text input" is an interface for receiving information input by a user in voice or text form.

[0663] A "smartphone application" is application software that runs on a smartphone.

[0664] A "server" is a central computer system that performs various processes and mediates data exchange between users, the restaurant industry, and delivery companies.

[0665] A specific system for realizing the present invention is composed of multiple components, each of which will be described in detail below, along with its operation.

[0666] User Interface Means

[0667] The server provides a simple user interface that allows users to input meal-related inquiries and requests. This interface is implemented as a smartphone application. Users can make requests via text or voice input, for example, by entering questions such as "What should I have for dinner tonight?"

[0668] Interactive Artificial Intelligence Tools

[0669] The server uses conversational artificial intelligence (AI) to analyze the inquiries received from users. The AI ​​uses natural language processing to understand the user's request and generate appropriate questions and responses. For example, if a user requests, "I'd like a menu that's mainly vegetables," the server analyzes this and moves on to the next step.

[0670] User profile management methods

[0671] The conversational AI means utilizes a user profile management system to reference the user's past interaction history and profile information. This system stores the user's preferences, allergy information, past order history, etc. For example, if the user has registered that they are allergic to seafood, suggestions will be made based on that information.

[0672] Recipe suggestion method

[0673] The server proposes nutritionally balanced recipes based on the information obtained from the conversational AI means and the user profile. For example, in response to a request for a vegetable-based menu, the server proposes "Summer vegetable ratatouille" and asks, "Is this recipe okay?"

[0674] Ordering Method

[0675] When the user selects a suggested recipe, the server places a meal order with the corresponding restaurant. For example, if the user selects "Yes, please," an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[0676] Delivery method

[0677] After the ordered meal is ready, the server coordinates with a food delivery company to deliver the meal to the user's residence. For example, once the meal is ready, the server may issue instructions to a delivery company to arrange for the meal to be delivered to the user's home.

[0678] Hardware and software used

[0679] This system utilizes the following hardware and software:

[0680] Hardware: Smartphone

[0681] Software: Flask (web framework), requests (HTTP request library)

[0682] Database: In actual implementation, SQL or NoSQL databases are used.

[0683] API integration: API integration with the restaurant industry and food delivery companies

[0684] Specific examples

[0685] For example, if a user opens a smartphone app and types, "What should I have for dinner tonight?", the conversational AI engine will respond with, "What would you like to eat today?" If the user types, "I'd like a vegetable-based menu," the recipe suggestion engine will suggest "Summer vegetable ratatouille" and place the order according to the user's selection. Allergy information and past history are also referenced to suggest the most suitable and safe meal for the user.

[0686] Prompt Sentence Examples

[0687] If the user types "Suggest a vegetable-based, meatless dinner," the prompt text might look like this:

[0688] "I'd like some suggestions for a vegetable-based, meatless dinner."

[0689] Based on this, a system will be built that suggests appropriate recipes and delivers the meals to the user's home.

[0690] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0691] Step 1:

[0692] A user opens a smartphone app on their device and inputs a dietary inquiry. This input is sent to the server as a text question or request. For example, the input might be, "What should I have for dinner tonight?" The server accepts this input and prepares the data for the next processing step.

[0693] Step 2:

[0694] The server sends the received consultation details to the interactive AI means. The interactive AI uses natural language processing to analyze the user's input and understand the content of the question or request. Through this analysis, the AI ​​extracts specific information from the user's needs and converts them into a specific request, such as "I'd like a menu that is mainly vegetables."

[0695] Step 3:

[0696] Based on the analyzed request, the server accesses the user profile management means to obtain profile information such as the user's past interaction history, allergy information, and preferences. This provides data to determine whether the suggested recipe meets the user's individual requirements. For example, this information may include information such as "the user does not like seafood."

[0697] Step 4:

[0698] The server generates appropriate recipes using the recipe suggestion means based on information obtained from the interactive artificial intelligence and the user profile management means. The recipes take into consideration the nutritional balance and the user's preferences. For example, specific menus such as "Summer vegetable ratatouille" and "Grilled chicken breast and vegetable salad" are suggested.

[0699] Step 5:

[0700] The server sends the proposed recipe to the terminal for confirmation by the user. The user confirms the proposed recipe and enters a confirmation such as "Yes, please." This input is sent to the server and used as data to proceed to the next processing step.

[0701] Step 6:

[0702] The server receives confirmation from the user and uses the ordering means to place a meal order with the corresponding restaurant. The order is processed automatically online, so the user does not need to manually place the order. For example, an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[0703] Step 7:

[0704] After the order is confirmed by the restaurant and the meal is prepared, the server uses a delivery method to instruct the food delivery company to deliver the meal to the user's residence. Based on this instruction, the food delivery company delivers the meal to the user's home. The user's address information is used to arrange the delivery.

[0705] These processing steps allow users to easily select a nutritionally balanced meal that is right for them and have it delivered to their home.

[0706] 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.

[0707] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers those meals to the user's residence from a restaurant. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[0708] System Configuration

[0709] The system includes the following major components:

[0710] 1. User Interface (UI)

[0711] 2. Conversational AI Engine

[0712] 3. User Profile Management System

[0713] 4. Recipe suggestion engine

[0714] 5. Ordering System

[0715] 6. Delivery System

[0716] 7. Emotion Engine

[0717] User Interface (UI)

[0718] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0719] Conversational Artificial Intelligence Engine

[0720] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0721] User Profile Management System

[0722] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0723] Recipe suggestion engine

[0724] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0725] Ordering System

[0726] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0727] Delivery System

[0728] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0729] Emotion Engine

[0730] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[0731] Specific examples

[0732] 1. User accesses the system:

[0733] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0734] 2. Start a conversation:

[0735] Server: A conversational AI engine responds, "What would you like to eat today?"

[0736] 3. User Answer:

[0737] Terminal: The user types, "I'd like a vegetable-based menu."

[0738] 4. User Profile Reference:

[0739] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0740] 5. Emotion Analysis:

[0741] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[0742] 6. Recipe suggestions

[0743] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[0744] 7. User Choice:

[0745] Terminal: User selects "Yes, please."

[0746] 8. Submitting an Order:

[0747] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0748] 9. Delivery Arrangements:

[0749] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0750] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[0751] The processing flow will be explained below.

[0752] Step 1:

[0753] Terminal: The user launches the smartphone app and accesses the system. The terminal prompts for user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[0754] Step 2:

[0755] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[0756] Step 3:

[0757] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[0758] Step 4:

[0759] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[0760] Step 5:

[0761] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[0762] Step 6:

[0763] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[0764] Step 7:

[0765] Server: The emotion engine analyzes the user's dialogue and voice data to recognize the user's emotional state. For example, if the user is feeling stressed, it passes that information to the conversational AI engine.

[0766] Step 8:

[0767] Server: The recipe suggestion engine generates recipes based on the user's requests, profile information, and emotional state. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[0768] Step 9:

[0769] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[0770] Step 10:

[0771] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[0772] Step 11:

[0773] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[0774] Step 12:

[0775] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[0776] Example 2

[0777] 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."

[0778] Currently, many elderly people and those living in depopulated areas face difficulties with daily shopping and meal preparation. Furthermore, food choices are often made without considering individual preferences or health conditions, leading to nutritional imbalances. In particular, the lack of meal suggestions tailored to the user's emotional state may also affect their mental health.

[0779] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for ordering the suggested meal plans from a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's dialogue content and voice data and recognizing the user's emotional state, and a suggestion adjustment means for adjusting the suggestion content based on the emotion analysis results and making personalized suggestions. As a result, meal options are suggested in a form that is appropriate not only to the user's individual preferences and health condition but also to the user's emotional state, allowing the user to maintain a healthier and more satisfying dietary lifestyle.

[0780] The "interface means" refers to an input means by which a user accesses the system and makes dietary consultations.

[0781] "Interactive artificial intelligence means" refers to artificial intelligence technology that uses natural language processing to analyze the content of the consultation received and generate an appropriate response.

[0782] The "recipe suggestion means" is a means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content.

[0783] The "ordering means" is a means for placing an order with the restaurant industry based on the proposed meal contents.

[0784] "Delivery means" refers to a means for delivering the ordered meal to the user's residence after it has been prepared.

[0785] The "emotion analysis means" is a means for analyzing the content of the user's dialogue and voice data to recognize the user's emotional state.

[0786] The "proposal adjustment means" is a means for adjusting the content of meal proposals based on the emotion analysis results and making personalized proposals.

[0787] The "user profile management means" is a means for storing and referencing a user's past interaction history and profile information.

[0788] The "means for notifying the order status" is a means for monitoring the order acceptance status of the restaurant industry and contacting the user.

[0789] MODE FOR CARRYING OUT THE INVENTION

[0790] This system, which targets elderly people and those living in depopulated areas, uses conversational AI to suggest meal plans and delivers those meals to the user's residence from the restaurant industry. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[0791] The system includes the following major components:

[0792] User Interface (UI)

[0793] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0794] Conversational Artificial Intelligence Engine

[0795] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0796] User Profile Management System

[0797] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0798] Recipe suggestion engine

[0799] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[0800] Ordering System

[0801] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0802] Delivery System

[0803] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0804] Emotion Engine

[0805] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[0806] Specific examples

[0807] 1. User accesses the system:

[0808] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0809] 2. Start a conversation:

[0810] Server: A conversational AI engine responds, "What would you like to eat today?"

[0811] 3. User Answer:

[0812] Terminal: The user types, "I'd like a vegetable-based menu."

[0813] 4. User Profile Reference:

[0814] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0815] 5. Emotion Analysis:

[0816] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[0817] 6. Recipe suggestions

[0818] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[0819] 7. User Choice:

[0820] Terminal: User selects "Yes, please."

[0821] 8. Submitting an Order:

[0822] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[0823] 9. Delivery Arrangements:

[0824] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[0825] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[0826] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0827] Step 1:

[0828] A user accesses the system

[0829] Input: A user launches a smartphone app and enters a prompt such as "What should we have for dinner tonight?"

[0830] Processing: The terminal receives the user's input and sends it to the server.

[0831] Output: The user request is sent to the server.

[0832] Step 2:

[0833] Receive and analyze user interaction requests

[0834] Input: The server receives a request sent by the user.

[0835] Processing: The conversational AI engine analyzes the received request using natural language processing technology. It understands that the request is for dietary advice and extracts keywords related to the user's preferences and dietary restrictions.

[0836] Output: Parsed request content and extracted keywords.

[0837] Specific operation: For example, if a user inputs "I'd like a menu that mainly consists of vegetables," the system will extract the keywords "vegetables" and "menu."

[0838] Step 3:

[0839] Viewing a user profile

[0840] Input: Parsed request content and extracted keywords.

[0841] Processing: The server accesses the user profile management system and references the user's profile information (past interaction history, preferences, allergy information, etc.).

[0842] Output: User profile information.

[0843] Specific behavior: For example, if the user previously set "nut allergy," obtain that information.

[0844] Step 4:

[0845] Analyzing user emotions with an emotion engine

[0846] Input: User request details and user profile information.

[0847] Processing: The emotion engine analyzes the emotion from the user's input. If there is voice data, it performs voice analysis, and if there is text data, it performs text analysis.

[0848] Output: User's emotional state information.

[0849] Specific behavior: For example, if a user inputs "I feel kind of tired today," the emotional state "tired" is recognized.

[0850] Step 5:

[0851] Suggest a recipe

[0852] Input: Extracted keywords, user profile information, and emotional state information.

[0853] Processing: The recipe suggestion engine selects recipes suitable for the user based on the input information above. It also adjusts the suggestions taking into account nutritional balance and emotional state.

[0854] Output: A suggested recipe.

[0855] Specific behavior: For example, if a user types "I want to relax," the app will suggest "relaxing vegetable soup with herbs."

[0856] Step 6:

[0857] The user selects a recipe

[0858] Input: A suggested recipe.

[0859] Process: The suggested recipes are displayed on the device, and the user selects one.

[0860] Output: The recipe selected by the user.

[0861] Specific operation: For example, the user selects "Summer vegetable ratatouille."

[0862] Step 7:

[0863] The ordering system sends the order

[0864] Input: The recipe selected by the user.

[0865] Processing: The server's ordering system sends the order to the corresponding restaurant based on the selected recipe. The order is accepted in real time.

[0866] Output: Order notification to the food service industry.

[0867] Specific operation: For example, a server sends an order for "Summer vegetable ratatouille" to a restaurant.

[0868] Step 8:

[0869] The delivery system arranges the delivery

[0870] Input: Meals prepared in the food service industry.

[0871] Processing: Once the meal is ready, the server's delivery system sends instructions to a food delivery company to arrange delivery to the user's location. Delivery status can be tracked in real time.

[0872] Output: Delivery status notification to user.

[0873] Specific operation: For example, after the meal is ready, the server instructs the delivery company to "deliver to the user's home," and the user can check the delivery status in the app.

[0874] (Application example 2)

[0875] 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."

[0876] Elderly people and those living in depopulated areas often face difficulties in preparing and selecting meals. This creates a need for an easy way to obtain nutritionally balanced meals. Furthermore, the lack of a system that can provide meal suggestions based on the user's emotional state prevents the provision of more personalized services. Additionally, there is a need for a smartphone application with advanced interactive capabilities.

[0877] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0878] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's emotional state and adjusting the suggested meal plans based on the emotion, and a user interface means in the form of a smartphone application, thereby enabling personalized meal suggestions and delivery according to the user's emotional state.

[0879] The "interface means" refers to an input and display device that allows the user to input dietary advice and receive suggestions from the system.

[0880] The "interactive artificial intelligence means" is a component that uses an artificial intelligence algorithm and natural language processing technology to analyze the content of the consultation received from the user and generate a response.

[0881] The "recipe suggestion means" is a function for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on information analyzed by the interactive artificial intelligence means.

[0882] The "ordering means" is a communication function for placing an order for the proposed meal contents with the corresponding restaurant.

[0883] "Delivery method" refers to a logistics system and a function linked to a delivery company for delivering the ordered meal contents to the user's residence.

[0884] "Emotion analysis means" refers to algorithms and computational techniques that analyze a user's emotional state and tailor suggestions based on that data.

[0885] A "smartphone application" is a software application that runs on a smartphone device and functions in conjunction with user interface means and other system components.

[0886] The "user profile management means" refers to a database and management system for storing and referencing a user's past interaction history and profile information.

[0887] The embodiment of the present invention mainly comprises the following components:

[0888] 1. User interface means (smartphone application)

[0889] 2. Interactive AI methods

[0890] 3. User profile management methods

[0891] 4. Recipe suggestion method

[0892] 5. Order Methods

[0893] 6. Delivery method

[0894] 7. Emotion analysis method

[0895] Overall Architecture

[0896] Accepting requests from users

[0897] Users use a smartphone application to input dietary inquiries, such as a request like, "What should I have for dinner tonight?" The application has an intuitive, easy-to-use interface and is designed to be easy to operate even for elderly people.

[0898] Analysis of Conversational Artificial Intelligence

[0899] The server analyzes the received request using an interactive AI means, which uses natural language processing technology to understand the user's input and generate an appropriate response, taking into account the user's preferences, allergy information, etc.

[0900] Viewing User Profiles

[0901] The server uses user profile management means to refer to past interaction history and profile information, which allows for more personalized responses. For example, if the user previously input information such as "I don't like seafood," this information will be taken into consideration.

[0902] Tailoring recommendations through sentiment analysis

[0903] The server uses emotion analysis to analyze the user's emotional state. This analysis is based on voice data and dialogue content, and the suggestions are adjusted to reflect the user's emotional state. For example, if the user is feeling stressed, a menu using ingredients with a relaxing effect will be suggested.

[0904] Recipe Suggestions

[0905] The server uses the recipe suggestion tool to suggest recipes that take nutritional balance into consideration based on the results of sentiment analysis and user profile information, such as "relaxing vegetable soup with herbs" or "grilled chicken breast and vegetable salad."

[0906] Ordering and Shipping

[0907] When the user selects a suggested recipe, the server uses the ordering means to place an order with the corresponding restaurant, and then uses the delivery means to deliver the order to the user's address, allowing the user to easily complete the entire process from request to final meal delivery.

[0908] Hardware and software used

[0909] The implementation of this system uses the following hardware and software:

[0910] Server: Flask (a Python micro web framework), Database (RDBMS or NoSQL)

[0911] User Interface: Smartphone application

[0912] Conversational AI: Natural language processing technology (GPT-3, etc.)

[0913] Sentiment analysis engine: IBM Watson, Azure AI, etc.

[0914] Specific examples

[0915] For example, an elderly user might use a smartphone application to input a request such as, "What should we have for dinner tonight?"

[0916] Assume that the interactive artificial intelligence means responds with "What would you like to eat today?" and the user replies, "I'd like a menu that is mainly vegetables."

[0917] Next, the emotion analysis means analyzes the user's emotion as "stress," and the recipe suggestion means suggests "relaxing vegetable soup using herbs."

[0918] Prompt Sentence Examples

[0919] "Based on the analysis results of the emotion engine, suggest meals that will have a relaxing effect on the elderly. Consider the user's data profile and emotional state and suggest recipes using appropriate ingredients."

[0920] In this way, users can easily obtain the optimal diet according to their emotional state and maintain their health.

[0921] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0922] Step 1:

[0923] The user starts the smartphone application and inputs a request about food, for example, "What should I have for dinner tonight?"

[0924] Input: User's meal request

[0925] Output: Request sent by smartphone application to server

[0926] Step 2:

[0927] The server passes the received request to an interactive AI means for analysis, which uses natural language processing techniques to analyze the user's input and generate a response.

[0928] Input: User request

[0929] Output: Parsed request and appropriate response

[0930] Step 3:

[0931] Based on the analysis results, the server uses the user profile management means to refer to the user's past interaction history and profile information. For example, if the user has previously registered food allergies or dislikes, that information is obtained.

[0932] Input: Parsed request content

[0933] Output: User's past interaction history and profile information

[0934] Step 4:

[0935] The emotion analysis means analyzes the user's emotional state based on the dialogue content and voice data, and is then ready to adjust the suggestions according to the user's emotional state.

[0936] Input: Dialogue content and voice data

[0937] Output: Parsed user's emotional state

[0938] Step 5:

[0939] The server uses the recipe suggestion means to suggest a nutritionally balanced meal, taking into account the results of the sentiment analysis and the user profile information. For example, it suggests a "relaxing vegetable soup using herbs."

[0940] Input: User's emotional state and profile information

[0941] Output: Suggested recipe content

[0942] Step 6:

[0943] The user reviews the suggested recipe via a smartphone application and enters a response such as "I'd like this recipe, please."

[0944] Input: User response to suggested recipe

[0945] Output: Sending user selections to the server

[0946] Step 7:

[0947] The server uses the ordering means to place an order for the selected recipe with the corresponding restaurant business, and the ordering means transmits the order data using a communication function.

[0948] Input: Recipe content selected by the user

[0949] Output: Order data for the restaurant industry

[0950] Step 8:

[0951] After the order is completed, the delivery method will coordinate with the food delivery company to arrange delivery to the user's residence. The server will monitor the delivery status and notify the user as necessary.

[0952] Input: Order data and shipping information

[0953] Output: Delivery instructions and delivery status notification to the user

[0954] Through these steps, users are easily recommended nutritionally balanced meals and have meals delivered to their home that correspond to their emotional state.

[0955] 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.

[0956] 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.

[0957] 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.

[0958] [Third embodiment]

[0959] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0960] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0961] 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).

[0962] 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.

[0963] 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.

[0964] 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).

[0965] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0966] 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.

[0967] 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.

[0968] 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.

[0969] 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.

[0970] 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."

[0971] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from the restaurant industry to the user's residence. This system includes the following main components:

[0972] 1. User Interface (UI)

[0973] 2. Conversational AI Engine

[0974] 3. User Profile Management System

[0975] 4. Recipe suggestion engine

[0976] 5. Ordering System

[0977] 6. Delivery System

[0978] User Interface (UI)

[0979] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[0980] Conversational Artificial Intelligence Engine

[0981] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[0982] User Profile Management System

[0983] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[0984] Recipe suggestion engine

[0985] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and the user profile to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[0986] Ordering System

[0987] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[0988] Delivery System

[0989] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[0990] Specific examples

[0991] 1. User accesses the system:

[0992] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[0993] 2. Start a conversation:

[0994] Server: A conversational AI engine responds, "What would you like to eat today?"

[0995] 3. User Answer:

[0996] Terminal: The user types, "I'd like a vegetable-based menu."

[0997] 4. User Profile Reference:

[0998] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[0999] 5. Recipe suggestions:

[1000] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[1001] 6. User Choice:

[1002] Terminal: User selects "Yes, please."

[1003] 7. Submitting an order:

[1004] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1005] 8. Delivery Arrangements:

[1006] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1007] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[1008] The processing flow will be explained below.

[1009] Step 1:

[1010] Terminal: The user launches the smartphone app and accesses the system. The terminal requests user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[1011] Step 2:

[1012] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[1013] Step 3:

[1014] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[1015] Step 4:

[1016] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[1017] Step 5:

[1018] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[1019] Step 6:

[1020] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[1021] Step 7:

[1022] Server: The recipe suggestion engine generates a recipe based on the user's request and profile information. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[1023] Step 8:

[1024] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[1025] Step 9:

[1026] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[1027] Step 10:

[1028] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[1029] Step 11:

[1030] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[1031] Example 1

[1032] 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."

[1033] For elderly people and people living in depopulated areas who have difficulty shopping, there is a lack of nutritionally balanced meal suggestions and easy ways to order and deliver them. There is also a need for technology that can efficiently suggest meals that take into account the user's individual preferences and allergy information. Our goal is to provide a system that supports healthy eating habits by solving these issues.

[1034] 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.

[1035] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the content of the consultations accepted, and a recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed content of the consultations. This enables users to easily receive nutritionally balanced meal suggestions, order meals based on the suggestions, and have them delivered to their homes.

[1036] The "interface means" is a means for accepting dietary consultations from users, and has the function of accepting requests entered by users via a dedicated terminal or smartphone app.

[1037] An "interactive artificial intelligence means" is a means for analyzing the content of inquiries received from users, and has the function of understanding the user's request using natural language processing and generating appropriate responses and questions.

[1038] The "recipe suggestion means" is a means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content, and has the function of generating optimal recipes based on user profile information and requests.

[1039] The "ordering means" is a means for placing an order with the restaurant that corresponds to the proposed meal contents, and has the function of sending an order to the restaurant based on the recipe selected by the user.

[1040] The "delivery means" is a means for delivering the ordered meal contents to the user's residence, and has the function of delivering the meal to the user's home in cooperation with a food delivery company.

[1041] The "user profile management means" is a means for managing a user's past interaction history and profile information for reference by the interactive artificial intelligence means, and has the function of enabling responses according to the individual requests of each user.

[1042] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from a restaurant to the user's residence. The system includes a user interface (UI), an interactive AI engine, a user profile management system, a recipe suggestion engine, an ordering system, and a delivery system.

[1043] User Interface (UI)

[1044] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user can start a conversation with the system by inputting a request such as, "I'd like some advice on what to eat today."

[1045] Conversational Artificial Intelligence Engine

[1046] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1047] User Profile Management System

[1048] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to individual user requests.

[1049] Recipe suggestion engine

[1050] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and user profiles to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1051] Ordering System

[1052] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1053] Delivery System

[1054] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1055] Specific examples

[1056] Below are some specific examples of how the system can be used.

[1057] 1. A user accesses the system

[1058] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1059] 2. Start a dialogue

[1060] Server: A conversational AI engine responds, "What would you like to eat today?"

[1061] 3. User Responses

[1062] Terminal: The user types, "I'd like a vegetable-based menu."

[1063] 4. User profile reference

[1064] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1065] 5. Recipe suggestions

[1066] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[1067] 6. User Choice

[1068] Terminal: User selects "Yes, please."

[1069] 7. Submitting an Order

[1070] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1071] 8. Delivery Arrangements

[1072] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1073] Examples of prompts for generative AI models

[1074] 1. "Could you please suggest a nutritionally balanced dinner menu for the elderly? Please give examples of menus that are particularly suitable for those who do not like seafood."

[1075] 2. "A user in a sparsely populated area wants a plant-based dinner. Explain the recipe suggestions and ordering process."

[1076] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[1077] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1078] Step 1:

[1079] A user connects to the system

[1080] Terminal: The user accesses the system by starting a dedicated terminal or smartphone app. Specifically, the user opens the app and enters "What should I have for dinner tonight?" into the interactive input form. This action sends the user's request to the system.

[1081] Input: User's meal-related enquiry (e.g., "What should we have for dinner tonight?")

[1082] Output: User request sent to server

[1083] Step 2:

[1084] A conversational artificial intelligence engine analyzes the request

[1085] Server: The conversational AI engine receives requests sent by users and analyzes the content using natural language processing. Specifically, it understands specific conditions and requests, such as "I don't like seafood," and generates appropriate questions and responses.

[1086] Input: User request data (e.g., "I'd like a menu that's mainly vegetables.")

[1087] Data processing: Natural language processing algorithms analyze the text and extract the required information.

[1088] Output: Generates a response or follow-up question based on the user's request (e.g., "What would you like to eat today?").

[1089] Step 3:

[1090] Retrieving information from a user profile management system

[1091] Server: The conversational AI engine retrieves user preferences and allergies from the user profile management system database, enabling personalized responses.

[1092] Input: Request data, including the user's ID and past interaction history

[1093] Data processing: A database query is performed to retrieve profile information for the relevant users.

[1094] Output: Profile data including user preferences and allergy information

[1095] Step 4:

[1096] Recipe suggestion engine generates recipes

[1097] Server: The recipe suggestion engine generates appropriate recipes that take nutritional balance into consideration based on information obtained from the conversational AI engine and the user profile. For example, if you request a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[1098] Input: User preferences and profile data

[1099] Data processing: Recipe suggestion algorithms generate recipes based on user profiles and preferences.

[1100] Output: Suggested recipe (e.g. "Grilled chicken breast with vegetable salad")

[1101] Step 5:

[1102] The user selects a recipe

[1103] On your device: The user selects one of the suggested recipes and selects "I'd like this recipe." Specifically, they tap "Grilled chicken breast and vegetable salad" from the list of recipes displayed.

[1104] Input: List of suggested recipes

[1105] Output: The recipe selected by the user (e.g., "Grilled chicken breast and vegetable salad")

[1106] Step 6:

[1107] The ordering system processes the order.

[1108] Server: Receives the recipe selected by the user and sends the order to the corresponding restaurant business through the ordering system. For example, it transfers the order information for the specified recipe to the restaurant's ordering system.

[1109] Input: User-selected recipe information

[1110] Data processing: The data is sent to the restaurant industry's API as order data.

[1111] Output: Order information sent to the restaurant

[1112] Step 7:

[1113] The delivery system arranges the delivery

[1114] Server: After the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location, for example, by adding the user's address to a delivery list at the specified time.

[1115] Input: Food preparation notification from the restaurant industry

[1116] Data processing: A delivery request is sent to the delivery company's system.

[1117] Output: Instructions for the meal to be delivered to the user's location.

[1118] Through this series of processes, users can easily obtain nutritionally balanced meals and maintain healthy eating habits.

[1119] (Application example 1)

[1120] 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."

[1121] Elderly people and people living in depopulated areas have difficulty eating a nutritionally balanced diet because they find it difficult to shop. They also have difficulty determining what kind of food is best for them, making it difficult for them to choose the right meal. For these users, there is a need for a system that can easily suggest meals and deliver them to their homes.

[1122] 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.

[1123] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, and a user interface means and smartphone application for suggesting appropriate recipes based on the user's consultation content and processing voice or text input. This allows users to easily select a nutritionally balanced meal that suits them and receive that meal at home.

[1124] The "interface means for receiving dietary consultations from users" is an input interface that allows users to input questions or requests about their own diet.

[1125] The "interactive artificial intelligence means for analyzing the received consultation content" is an interactive artificial intelligence (AI) system that analyzes the input content from the user and generates appropriate responses and suggestions.

[1126] The "recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content" is a system that suggests appropriate recipes based on the user's input, preferences, and nutritional balance.

[1127] The "ordering means for placing an order for the proposed meal contents with the corresponding restaurant industry" is a system for placing an order for the proposed recipe with the restaurant industry.

[1128] "Delivery means for delivering the ordered meal contents to the user's residence" is a system that delivers the ordered meal to the address specified by the user.

[1129] A "user interface means for processing voice or text input" is an interface for receiving information input by a user in voice or text form.

[1130] A "smartphone application" is application software that runs on a smartphone.

[1131] A "server" is a central computer system that performs various processes and mediates data exchange between users, the restaurant industry, and delivery companies.

[1132] A specific system for realizing the present invention is composed of multiple components, each of which will be described in detail below, along with its operation.

[1133] User Interface Means

[1134] The server provides a simple user interface that allows users to input meal-related inquiries and requests. This interface is implemented as a smartphone application. Users can make requests via text or voice input, for example, by entering questions such as "What should I have for dinner tonight?"

[1135] Interactive Artificial Intelligence Tools

[1136] The server uses conversational artificial intelligence (AI) to analyze the inquiries received from users. The AI ​​uses natural language processing to understand the user's request and generate appropriate questions and responses. For example, if a user requests, "I'd like a menu that's mainly vegetables," the server analyzes this and moves on to the next step.

[1137] User profile management methods

[1138] The conversational AI means utilizes a user profile management system to reference the user's past interaction history and profile information. This system stores the user's preferences, allergy information, past order history, etc. For example, if the user has registered that they are allergic to seafood, suggestions will be made based on that information.

[1139] Recipe suggestion method

[1140] The server proposes nutritionally balanced recipes based on the information obtained from the conversational AI means and the user profile. For example, in response to a request for a vegetable-based menu, the server proposes "Summer vegetable ratatouille" and asks, "Is this recipe okay?"

[1141] Ordering Method

[1142] When the user selects a suggested recipe, the server places a meal order with the corresponding restaurant. For example, if the user selects "Yes, please," an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[1143] Delivery method

[1144] After the ordered meal is ready, the server coordinates with a food delivery company to deliver the meal to the user's residence. For example, once the meal is ready, the server may issue instructions to a delivery company to arrange for the meal to be delivered to the user's home.

[1145] Hardware and software used

[1146] This system utilizes the following hardware and software:

[1147] Hardware: Smartphone

[1148] Software: Flask (web framework), requests (HTTP request library)

[1149] Database: In actual implementation, SQL or NoSQL databases are used.

[1150] API integration: API integration with the restaurant industry and food delivery companies

[1151] Specific examples

[1152] For example, if a user opens a smartphone app and types, "What should I have for dinner tonight?", the conversational AI engine will respond with, "What would you like to eat today?" If the user types, "I'd like a vegetable-based menu," the recipe suggestion engine will suggest "Summer vegetable ratatouille" and place the order according to the user's selection. Allergy information and past history are also referenced to suggest the most suitable and safe meal for the user.

[1153] Prompt Sentence Examples

[1154] If the user types "Suggest a vegetable-based, meatless dinner," the prompt text might look like this:

[1155] "I'd like some suggestions for a vegetable-based, meatless dinner."

[1156] Based on this, a system will be built that suggests appropriate recipes and delivers the meals to the user's home.

[1157] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1158] Step 1:

[1159] A user opens a smartphone app on their device and inputs a dietary inquiry. This input is sent to the server as a text question or request. For example, the input might be, "What should I have for dinner tonight?" The server accepts this input and prepares the data for the next processing step.

[1160] Step 2:

[1161] The server sends the received consultation details to the interactive AI means. The interactive AI uses natural language processing to analyze the user's input and understand the content of the question or request. Through this analysis, the AI ​​extracts specific information from the user's needs and converts them into a specific request, such as "I'd like a menu that is mainly vegetables."

[1162] Step 3:

[1163] Based on the analyzed request, the server accesses the user profile management means to obtain profile information such as the user's past interaction history, allergy information, and preferences. This provides data to determine whether the suggested recipe meets the user's individual requirements. For example, this information may include information such as "the user does not like seafood."

[1164] Step 4:

[1165] The server generates appropriate recipes using the recipe suggestion means based on information obtained from the interactive artificial intelligence and the user profile management means. The recipes take into consideration the nutritional balance and the user's preferences. For example, specific menus such as "Summer vegetable ratatouille" and "Grilled chicken breast and vegetable salad" are suggested.

[1166] Step 5:

[1167] The server sends the proposed recipe to the terminal for confirmation by the user. The user confirms the proposed recipe and enters a confirmation such as "Yes, please." This input is sent to the server and used as data to proceed to the next processing step.

[1168] Step 6:

[1169] The server receives confirmation from the user and uses the ordering means to place a meal order with the corresponding restaurant. The order is processed automatically online, so the user does not need to manually place the order. For example, an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[1170] Step 7:

[1171] After the order is confirmed by the restaurant and the meal is prepared, the server uses a delivery method to instruct the food delivery company to deliver the meal to the user's residence. Based on this instruction, the food delivery company delivers the meal to the user's home. The user's address information is used to arrange the delivery.

[1172] These processing steps allow users to easily select a nutritionally balanced meal that is right for them and have it delivered to their home.

[1173] 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.

[1174] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers those meals to the user's residence from a restaurant. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[1175] System Configuration

[1176] The system includes the following major components:

[1177] 1. User Interface (UI)

[1178] 2. Conversational AI Engine

[1179] 3. User Profile Management System

[1180] 4. Recipe suggestion engine

[1181] 5. Ordering System

[1182] 6. Delivery System

[1183] 7. Emotion Engine

[1184] User Interface (UI)

[1185] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[1186] Conversational Artificial Intelligence Engine

[1187] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1188] User Profile Management System

[1189] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[1190] Recipe suggestion engine

[1191] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1192] Ordering System

[1193] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1194] Delivery System

[1195] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1196] Emotion Engine

[1197] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[1198] Specific examples

[1199] 1. User accesses the system:

[1200] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1201] 2. Start a conversation:

[1202] Server: A conversational AI engine responds, "What would you like to eat today?"

[1203] 3. User Answer:

[1204] Terminal: The user types, "I'd like a vegetable-based menu."

[1205] 4. User Profile Reference:

[1206] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1207] 5. Emotion Analysis:

[1208] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[1209] 6. Recipe suggestions

[1210] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[1211] 7. User Choice:

[1212] Terminal: User selects "Yes, please."

[1213] 8. Submitting an Order:

[1214] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1215] 9. Delivery Arrangements:

[1216] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1217] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[1218] The processing flow will be explained below.

[1219] Step 1:

[1220] Terminal: The user launches the smartphone app and accesses the system. The terminal prompts for user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[1221] Step 2:

[1222] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[1223] Step 3:

[1224] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[1225] Step 4:

[1226] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[1227] Step 5:

[1228] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[1229] Step 6:

[1230] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[1231] Step 7:

[1232] Server: The emotion engine analyzes the user's dialogue and voice data to recognize the user's emotional state. For example, if the user is feeling stressed, it passes that information to the conversational AI engine.

[1233] Step 8:

[1234] Server: The recipe suggestion engine generates recipes based on the user's requests, profile information, and emotional state. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[1235] Step 9:

[1236] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[1237] Step 10:

[1238] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[1239] Step 11:

[1240] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[1241] Step 12:

[1242] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[1243] Example 2

[1244] 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."

[1245] Currently, many elderly people and those living in depopulated areas face difficulties with daily shopping and meal preparation. Furthermore, food choices are often made without considering individual preferences or health conditions, leading to nutritional imbalances. In particular, the lack of meal suggestions tailored to the user's emotional state may also affect their mental health.

[1246] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for ordering the suggested meal plans from a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's dialogue content and voice data and recognizing the user's emotional state, and a suggestion adjustment means for adjusting the suggestion content based on the emotion analysis results and making personalized suggestions. As a result, meal options are suggested in a form that is appropriate not only to the user's individual preferences and health condition but also to the user's emotional state, allowing the user to maintain a healthier and more satisfying dietary lifestyle.

[1247] The "interface means" refers to an input means by which a user accesses the system and makes dietary consultations.

[1248] "Interactive artificial intelligence means" refers to artificial intelligence technology that uses natural language processing to analyze the content of the consultation received and generate an appropriate response.

[1249] The "recipe suggestion means" is a means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content.

[1250] The "ordering means" is a means for placing an order with the restaurant industry based on the proposed meal contents.

[1251] "Delivery means" refers to a means for delivering the ordered meal to the user's residence after it has been prepared.

[1252] The "emotion analysis means" is a means for analyzing the content of the user's dialogue and voice data to recognize the user's emotional state.

[1253] The "proposal adjustment means" is a means for adjusting the content of meal proposals based on the emotion analysis results and making personalized proposals.

[1254] The "user profile management means" is a means for storing and referencing a user's past interaction history and profile information.

[1255] The "means for notifying the order status" is a means for monitoring the order acceptance status of the restaurant industry and contacting the user.

[1256] MODE FOR CARRYING OUT THE INVENTION

[1257] This system, which targets elderly people and those living in depopulated areas, uses conversational AI to suggest meal plans and delivers those meals to the user's residence from the restaurant industry. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[1258] The system includes the following major components:

[1259] User Interface (UI)

[1260] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[1261] Conversational Artificial Intelligence Engine

[1262] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1263] User Profile Management System

[1264] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[1265] Recipe suggestion engine

[1266] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1267] Ordering System

[1268] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1269] Delivery System

[1270] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1271] Emotion Engine

[1272] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[1273] Specific examples

[1274] 1. User accesses the system:

[1275] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1276] 2. Start a conversation:

[1277] Server: A conversational AI engine responds, "What would you like to eat today?"

[1278] 3. User Answer:

[1279] Terminal: The user types, "I'd like a vegetable-based menu."

[1280] 4. User Profile Reference:

[1281] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1282] 5. Emotion Analysis:

[1283] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[1284] 6. Recipe suggestions

[1285] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[1286] 7. User Choice:

[1287] Terminal: User selects "Yes, please."

[1288] 8. Submitting an Order:

[1289] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1290] 9. Delivery Arrangements:

[1291] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1292] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[1293] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1294] Step 1:

[1295] A user accesses the system

[1296] Input: A user launches a smartphone app and enters a prompt such as "What should we have for dinner tonight?"

[1297] Processing: The terminal receives the user's input and sends it to the server.

[1298] Output: The user request is sent to the server.

[1299] Step 2:

[1300] Receive and analyze user interaction requests

[1301] Input: The server receives a request sent by the user.

[1302] Processing: The conversational AI engine analyzes the received request using natural language processing technology. It understands that the request is for dietary advice and extracts keywords related to the user's preferences and dietary restrictions.

[1303] Output: Parsed request content and extracted keywords.

[1304] Specific operation: For example, if a user inputs "I'd like a menu that mainly consists of vegetables," the system will extract the keywords "vegetables" and "menu."

[1305] Step 3:

[1306] Viewing a user profile

[1307] Input: Parsed request content and extracted keywords.

[1308] Processing: The server accesses the user profile management system and references the user's profile information (past interaction history, preferences, allergy information, etc.).

[1309] Output: User profile information.

[1310] Specific behavior: For example, if the user previously set "nut allergy," obtain that information.

[1311] Step 4:

[1312] Analyzing user emotions with an emotion engine

[1313] Input: User request details and user profile information.

[1314] Processing: The emotion engine analyzes the emotion from the user's input. If there is voice data, it performs voice analysis, and if there is text data, it performs text analysis.

[1315] Output: User's emotional state information.

[1316] Specific behavior: For example, if a user inputs "I feel kind of tired today," the emotional state "tired" is recognized.

[1317] Step 5:

[1318] Suggest a recipe

[1319] Input: Extracted keywords, user profile information, and emotional state information.

[1320] Processing: The recipe suggestion engine selects recipes suitable for the user based on the input information above. It also adjusts the suggestions taking into account nutritional balance and emotional state.

[1321] Output: A suggested recipe.

[1322] Specific behavior: For example, if a user types "I want to relax," the app will suggest "relaxing vegetable soup with herbs."

[1323] Step 6:

[1324] The user selects a recipe

[1325] Input: A suggested recipe.

[1326] Process: The suggested recipes are displayed on the device, and the user selects one.

[1327] Output: The recipe selected by the user.

[1328] Specific operation: For example, the user selects "Summer vegetable ratatouille."

[1329] Step 7:

[1330] The ordering system sends the order

[1331] Input: The recipe selected by the user.

[1332] Processing: The server's ordering system sends the order to the corresponding restaurant based on the selected recipe. The order is accepted in real time.

[1333] Output: Order notification to the food service industry.

[1334] Specific operation: For example, a server sends an order for "Summer vegetable ratatouille" to a restaurant.

[1335] Step 8:

[1336] The delivery system arranges the delivery

[1337] Input: Meals prepared in the food service industry.

[1338] Processing: Once the meal is ready, the server's delivery system sends instructions to a food delivery company to arrange delivery to the user's location. Delivery status can be tracked in real time.

[1339] Output: Delivery status notification to user.

[1340] Specific operation: For example, after the meal is ready, the server instructs the delivery company to "deliver to the user's home," and the user can check the delivery status in the app.

[1341] (Application example 2)

[1342] 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."

[1343] Elderly people and those living in depopulated areas often face difficulties in preparing and selecting meals. This creates a need for an easy way to obtain nutritionally balanced meals. Furthermore, the lack of a system that can provide meal suggestions based on the user's emotional state prevents the provision of more personalized services. Additionally, there is a need for a smartphone application with advanced interactive capabilities.

[1344] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1345] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's emotional state and adjusting the suggested meal plans based on the emotion, and a user interface means in the form of a smartphone application, thereby enabling personalized meal suggestions and delivery according to the user's emotional state.

[1346] The "interface means" refers to an input and display device that allows the user to input dietary advice and receive suggestions from the system.

[1347] The "interactive artificial intelligence means" is a component that uses an artificial intelligence algorithm and natural language processing technology to analyze the content of the consultation received from the user and generate a response.

[1348] The "recipe suggestion means" is a function for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on information analyzed by the interactive artificial intelligence means.

[1349] The "ordering means" is a communication function for placing an order for the proposed meal contents with the corresponding restaurant.

[1350] "Delivery method" refers to a logistics system and a function linked to a delivery company for delivering the ordered meal contents to the user's residence.

[1351] "Emotion analysis means" refers to algorithms and computational techniques that analyze a user's emotional state and tailor suggestions based on that data.

[1352] A "smartphone application" is a software application that runs on a smartphone device and functions in conjunction with user interface means and other system components.

[1353] The "user profile management means" refers to a database and management system for storing and referencing a user's past interaction history and profile information.

[1354] The embodiment of the present invention mainly comprises the following components:

[1355] 1. User interface means (smartphone application)

[1356] 2. Interactive AI methods

[1357] 3. User profile management methods

[1358] 4. Recipe suggestion method

[1359] 5. Order Methods

[1360] 6. Delivery method

[1361] 7. Emotion analysis method

[1362] Overall Architecture

[1363] Accepting requests from users

[1364] Users use a smartphone application to input dietary inquiries, such as a request like, "What should I have for dinner tonight?" The application has an intuitive, easy-to-use interface and is designed to be easy to operate even for elderly people.

[1365] Analysis of Conversational Artificial Intelligence

[1366] The server analyzes the received request using an interactive AI means, which uses natural language processing technology to understand the user's input and generate an appropriate response, taking into account the user's preferences, allergy information, etc.

[1367] Viewing User Profiles

[1368] The server uses user profile management means to refer to past interaction history and profile information, which allows for more personalized responses. For example, if the user previously input information such as "I don't like seafood," this information will be taken into consideration.

[1369] Tailoring recommendations through sentiment analysis

[1370] The server uses emotion analysis to analyze the user's emotional state. This analysis is based on voice data and dialogue content, and the suggestions are adjusted to reflect the user's emotional state. For example, if the user is feeling stressed, a menu using ingredients with a relaxing effect will be suggested.

[1371] Recipe Suggestions

[1372] The server uses the recipe suggestion tool to suggest recipes that take nutritional balance into consideration based on the results of sentiment analysis and user profile information, such as "relaxing vegetable soup with herbs" or "grilled chicken breast and vegetable salad."

[1373] Ordering and Shipping

[1374] When the user selects a suggested recipe, the server uses the ordering means to place an order with the corresponding restaurant, and then uses the delivery means to deliver the order to the user's address, allowing the user to easily complete the entire process from request to final meal delivery.

[1375] Hardware and software used

[1376] The implementation of this system uses the following hardware and software:

[1377] Server: Flask (a Python micro web framework), Database (RDBMS or NoSQL)

[1378] User Interface: Smartphone application

[1379] Conversational AI: Natural language processing technology (GPT-3, etc.)

[1380] Sentiment analysis engine: IBM Watson, Azure AI, etc.

[1381] Specific examples

[1382] For example, an elderly user might use a smartphone application to input a request such as, "What should we have for dinner tonight?"

[1383] Assume that the interactive artificial intelligence means responds with "What would you like to eat today?" and the user replies, "I'd like a menu that is mainly vegetables."

[1384] Next, the emotion analysis means analyzes the user's emotion as "stress," and the recipe suggestion means suggests "relaxing vegetable soup using herbs."

[1385] Prompt Sentence Examples

[1386] "Based on the analysis results of the emotion engine, suggest meals that will have a relaxing effect on the elderly. Consider the user's data profile and emotional state and suggest recipes using appropriate ingredients."

[1387] In this way, users can easily obtain the optimal diet according to their emotional state and maintain their health.

[1388] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1389] Step 1:

[1390] The user starts the smartphone application and inputs a request about food, for example, "What should I have for dinner tonight?"

[1391] Input: User's meal request

[1392] Output: Request sent by smartphone application to server

[1393] Step 2:

[1394] The server passes the received request to an interactive AI means for analysis, which uses natural language processing techniques to analyze the user's input and generate a response.

[1395] Input: User request

[1396] Output: Parsed request and appropriate response

[1397] Step 3:

[1398] Based on the analysis results, the server uses the user profile management means to refer to the user's past interaction history and profile information. For example, if the user has previously registered food allergies or dislikes, that information is obtained.

[1399] Input: Parsed request content

[1400] Output: User's past interaction history and profile information

[1401] Step 4:

[1402] The emotion analysis means analyzes the user's emotional state based on the dialogue content and voice data, and is then ready to adjust the suggestions according to the user's emotional state.

[1403] Input: Dialogue content and voice data

[1404] Output: Parsed user's emotional state

[1405] Step 5:

[1406] The server uses the recipe suggestion means to suggest a nutritionally balanced meal, taking into account the results of the sentiment analysis and the user profile information. For example, it suggests a "relaxing vegetable soup using herbs."

[1407] Input: User's emotional state and profile information

[1408] Output: Suggested recipe content

[1409] Step 6:

[1410] The user reviews the suggested recipe via a smartphone application and enters a response such as "I'd like this recipe, please."

[1411] Input: User response to suggested recipe

[1412] Output: Sending user selections to the server

[1413] Step 7:

[1414] The server uses the ordering means to place an order for the selected recipe with the corresponding restaurant business, and the ordering means transmits the order data using a communication function.

[1415] Input: Recipe content selected by the user

[1416] Output: Order data for the restaurant industry

[1417] Step 8:

[1418] After the order is completed, the delivery method will coordinate with the food delivery company to arrange delivery to the user's residence. The server will monitor the delivery status and notify the user as necessary.

[1419] Input: Order data and shipping information

[1420] Output: Delivery instructions and delivery status notification to the user

[1421] Through these steps, users are easily recommended nutritionally balanced meals and have meals delivered to their home that correspond to their emotional state.

[1422] 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.

[1423] 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.

[1424] 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.

[1425] [Fourth embodiment]

[1426] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1427] 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.

[1428] 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).

[1429] 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.

[1430] 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.

[1431] 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).

[1432] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1433] 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.

[1434] 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.

[1435] 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.

[1436] 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.

[1437] 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.

[1438] 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."

[1439] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from the restaurant industry to the user's residence. This system includes the following main components:

[1440] 1. User Interface (UI)

[1441] 2. Conversational AI Engine

[1442] 3. User Profile Management System

[1443] 4. Recipe suggestion engine

[1444] 5. Ordering System

[1445] 6. Delivery System

[1446] User Interface (UI)

[1447] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[1448] Conversational Artificial Intelligence Engine

[1449] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1450] User Profile Management System

[1451] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[1452] Recipe suggestion engine

[1453] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and the user profile to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[1454] Ordering System

[1455] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1456] Delivery System

[1457] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1458] Specific examples

[1459] 1. User accesses the system:

[1460] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1461] 2. Start a conversation:

[1462] Server: A conversational AI engine responds, "What would you like to eat today?"

[1463] 3. User Answer:

[1464] Terminal: The user types, "I'd like a vegetable-based menu."

[1465] 4. User Profile Reference:

[1466] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1467] 5. Recipe suggestions:

[1468] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[1469] 6. User Choice:

[1470] Terminal: User selects "Yes, please."

[1471] 7. Submitting an order:

[1472] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1473] 8. Delivery Arrangements:

[1474] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1475] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[1476] The processing flow will be explained below.

[1477] Step 1:

[1478] Terminal: The user launches the smartphone app and accesses the system. The terminal requests user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[1479] Step 2:

[1480] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[1481] Step 3:

[1482] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[1483] Step 4:

[1484] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[1485] Step 5:

[1486] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[1487] Step 6:

[1488] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[1489] Step 7:

[1490] Server: The recipe suggestion engine generates a recipe based on the user's request and profile information. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[1491] Step 8:

[1492] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[1493] Step 9:

[1494] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[1495] Step 10:

[1496] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[1497] Step 11:

[1498] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[1499] Example 1

[1500] 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."

[1501] For elderly people and people living in depopulated areas who have difficulty shopping, there is a lack of nutritionally balanced meal suggestions and easy ways to order and deliver them. There is also a need for technology that can efficiently suggest meals that take into account the user's individual preferences and allergy information. Our goal is to provide a system that supports healthy eating habits by solving these issues.

[1502] 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.

[1503] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the content of the consultations accepted, and a recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed content of the consultations. This enables users to easily receive nutritionally balanced meal suggestions, order meals based on the suggestions, and have them delivered to their homes.

[1504] The "interface means" is a means for accepting dietary consultations from users, and has the function of accepting requests entered by users via a dedicated terminal or smartphone app.

[1505] An "interactive artificial intelligence means" is a means for analyzing the content of inquiries received from users, and has the function of understanding the user's request using natural language processing and generating appropriate responses and questions.

[1506] The "recipe suggestion means" is a means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content, and has the function of generating optimal recipes based on user profile information and requests.

[1507] The "ordering means" is a means for placing an order with the restaurant that corresponds to the proposed meal contents, and has the function of sending an order to the restaurant based on the recipe selected by the user.

[1508] The "delivery means" is a means for delivering the ordered meal contents to the user's residence, and has the function of delivering the meal to the user's home in cooperation with a food delivery company.

[1509] The "user profile management means" is a means for managing a user's past interaction history and profile information for reference by the interactive artificial intelligence means, and has the function of enabling responses according to the individual requests of each user.

[1510] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers the meals from a restaurant to the user's residence. The system includes a user interface (UI), an interactive AI engine, a user profile management system, a recipe suggestion engine, an ordering system, and a delivery system.

[1511] User Interface (UI)

[1512] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user can start a conversation with the system by inputting a request such as, "I'd like some advice on what to eat today."

[1513] Conversational Artificial Intelligence Engine

[1514] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1515] User Profile Management System

[1516] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to individual user requests.

[1517] Recipe suggestion engine

[1518] Server: The recipe suggestion engine uses information obtained from the conversational AI engine and user profiles to suggest recipes that take nutritional balance into consideration. For example, if a user requests a dinner that includes meat, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1519] Ordering System

[1520] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1521] Delivery System

[1522] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1523] Specific examples

[1524] Below are some specific examples of how the system can be used.

[1525] 1. A user accesses the system

[1526] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1527] 2. Start a dialogue

[1528] Server: A conversational AI engine responds, "What would you like to eat today?"

[1529] 3. User Responses

[1530] Terminal: The user types, "I'd like a vegetable-based menu."

[1531] 4. User profile reference

[1532] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1533] 5. Recipe suggestions

[1534] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this the correct recipe?"

[1535] 6. User Choice

[1536] Terminal: User selects "Yes, please."

[1537] 7. Submitting an Order

[1538] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1539] 8. Delivery Arrangements

[1540] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1541] Examples of prompts for generative AI models

[1542] 1. "Could you please suggest a nutritionally balanced dinner menu for the elderly? Please give examples of menus that are particularly suitable for those who do not like seafood."

[1543] 2. "A user in a sparsely populated area wants a plant-based dinner. Explain the recipe suggestions and ordering process."

[1544] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet, and is extremely convenient, especially for users who have difficulty shopping.

[1545] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1546] Step 1:

[1547] A user connects to the system

[1548] Terminal: The user accesses the system by starting a dedicated terminal or smartphone app. Specifically, the user opens the app and enters "What should I have for dinner tonight?" into the interactive input form. This action sends the user's request to the system.

[1549] Input: User's meal-related enquiry (e.g., "What should we have for dinner tonight?")

[1550] Output: User request sent to server

[1551] Step 2:

[1552] A conversational artificial intelligence engine analyzes the request

[1553] Server: The conversational AI engine receives requests sent by users and analyzes the content using natural language processing. Specifically, it understands specific conditions and requests, such as "I don't like seafood," and generates appropriate questions and responses.

[1554] Input: User request data (e.g., "I'd like a menu that's mainly vegetables.")

[1555] Data processing: Natural language processing algorithms analyze the text and extract the required information.

[1556] Output: Generates a response or follow-up question based on the user's request (e.g., "What would you like to eat today?").

[1557] Step 3:

[1558] Retrieving information from a user profile management system

[1559] Server: The conversational AI engine retrieves user preferences and allergies from the user profile management system database, enabling personalized responses.

[1560] Input: Request data, including the user's ID and past interaction history

[1561] Data processing: A database query is performed to retrieve profile information for the relevant users.

[1562] Output: Profile data including user preferences and allergy information

[1563] Step 4:

[1564] Recipe suggestion engine generates recipes

[1565] Server: The recipe suggestion engine generates appropriate recipes that take nutritional balance into consideration based on information obtained from the conversational AI engine and the user profile. For example, if you request a dinner that includes meat, it will suggest a menu such as grilled chicken breast and vegetable salad.

[1566] Input: User preferences and profile data

[1567] Data processing: Recipe suggestion algorithms generate recipes based on user profiles and preferences.

[1568] Output: Suggested recipe (e.g. "Grilled chicken breast with vegetable salad")

[1569] Step 5:

[1570] The user selects a recipe

[1571] On your device: The user selects one of the suggested recipes and selects "I'd like this recipe." Specifically, they tap "Grilled chicken breast and vegetable salad" from the list of recipes displayed.

[1572] Input: List of suggested recipes

[1573] Output: The recipe selected by the user (e.g., "Grilled chicken breast and vegetable salad")

[1574] Step 6:

[1575] The ordering system processes the order.

[1576] Server: Receives the recipe selected by the user and sends the order to the corresponding restaurant business through the ordering system. For example, it transfers the order information for the specified recipe to the restaurant's ordering system.

[1577] Input: User-selected recipe information

[1578] Data processing: The data is sent to the restaurant industry's API as order data.

[1579] Output: Order information sent to the restaurant

[1580] Step 7:

[1581] The delivery system arranges the delivery

[1582] Server: After the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location, for example, by adding the user's address to a delivery list at the specified time.

[1583] Input: Food preparation notification from the restaurant industry

[1584] Data processing: A delivery request is sent to the delivery company's system.

[1585] Output: Instructions for the meal to be delivered to the user's location.

[1586] Through this series of processes, users can easily obtain nutritionally balanced meals and maintain healthy eating habits.

[1587] (Application example 1)

[1588] 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."

[1589] Elderly people and people living in depopulated areas have difficulty eating a nutritionally balanced diet because they find it difficult to shop. They also have difficulty determining what kind of food is best for them, making it difficult for them to choose the right meal. For these users, there is a need for a system that can easily suggest meals and deliver them to their homes.

[1590] 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.

[1591] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, and a user interface means and smartphone application for suggesting appropriate recipes based on the user's consultation content and processing voice or text input. This allows users to easily select a nutritionally balanced meal that suits them and receive that meal at home.

[1592] The "interface means for receiving dietary consultations from users" is an input interface that allows users to input questions or requests about their own diet.

[1593] The "interactive artificial intelligence means for analyzing the received consultation content" is an interactive artificial intelligence (AI) system that analyzes the input content from the user and generates appropriate responses and suggestions.

[1594] The "recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content" is a system that suggests appropriate recipes based on the user's input, preferences, and nutritional balance.

[1595] The "ordering means for placing an order for the proposed meal contents with the corresponding restaurant industry" is a system for placing an order for the proposed recipe with the restaurant industry.

[1596] "Delivery means for delivering the ordered meal contents to the user's residence" is a system that delivers the ordered meal to the address specified by the user.

[1597] A "user interface means for processing voice or text input" is an interface for receiving information input by a user in voice or text form.

[1598] A "smartphone application" is application software that runs on a smartphone.

[1599] A "server" is a central computer system that performs various processes and mediates data exchange between users, the restaurant industry, and delivery companies.

[1600] A specific system for realizing the present invention is composed of multiple components, each of which will be described in detail below, along with its operation.

[1601] User Interface Means

[1602] The server provides a simple user interface that allows users to input meal-related inquiries and requests. This interface is implemented as a smartphone application. Users can make requests via text or voice input, for example, by entering questions such as "What should I have for dinner tonight?"

[1603] Interactive Artificial Intelligence Tools

[1604] The server uses conversational artificial intelligence (AI) to analyze the inquiries received from users. The AI ​​uses natural language processing to understand the user's request and generate appropriate questions and responses. For example, if a user requests, "I'd like a menu that's mainly vegetables," the server analyzes this and moves on to the next step.

[1605] User profile management methods

[1606] The conversational AI means utilizes a user profile management system to reference the user's past interaction history and profile information. This system stores the user's preferences, allergy information, past order history, etc. For example, if the user has registered that they are allergic to seafood, suggestions will be made based on that information.

[1607] Recipe suggestion method

[1608] The server proposes nutritionally balanced recipes based on the information obtained from the conversational AI means and the user profile. For example, in response to a request for a vegetable-based menu, the server proposes "Summer vegetable ratatouille" and asks, "Is this recipe okay?"

[1609] Ordering Method

[1610] When the user selects a suggested recipe, the server places a meal order with the corresponding restaurant. For example, if the user selects "Yes, please," an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[1611] Delivery method

[1612] After the ordered meal is ready, the server coordinates with a food delivery company to deliver the meal to the user's residence. For example, once the meal is ready, the server may issue instructions to a delivery company to arrange for the meal to be delivered to the user's home.

[1613] Hardware and software used

[1614] This system utilizes the following hardware and software:

[1615] Hardware: Smartphone

[1616] Software: Flask (web framework), requests (HTTP request library)

[1617] Database: In actual implementation, SQL or NoSQL databases are used.

[1618] API integration: API integration with the restaurant industry and food delivery companies

[1619] Specific examples

[1620] For example, if a user opens a smartphone app and types, "What should I have for dinner tonight?", the conversational AI engine will respond with, "What would you like to eat today?" If the user types, "I'd like a vegetable-based menu," the recipe suggestion engine will suggest "Summer vegetable ratatouille" and place the order according to the user's selection. Allergy information and past history are also referenced to suggest the most suitable and safe meal for the user.

[1621] Prompt Sentence Examples

[1622] If the user types "Suggest a vegetable-based, meatless dinner," the prompt text might look like this:

[1623] "I'd like some suggestions for a vegetable-based, meatless dinner."

[1624] Based on this, a system will be built that suggests appropriate recipes and delivers the meals to the user's home.

[1625] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1626] Step 1:

[1627] A user opens a smartphone app on their device and inputs a dietary inquiry. This input is sent to the server as a text question or request. For example, the input might be, "What should I have for dinner tonight?" The server accepts this input and prepares the data for the next processing step.

[1628] Step 2:

[1629] The server sends the received consultation details to the interactive AI means. The interactive AI uses natural language processing to analyze the user's input and understand the content of the question or request. Through this analysis, the AI ​​extracts specific information from the user's needs and converts them into a specific request, such as "I'd like a menu that is mainly vegetables."

[1630] Step 3:

[1631] Based on the analyzed request, the server accesses the user profile management means to obtain profile information such as the user's past interaction history, allergy information, and preferences. This provides data to determine whether the suggested recipe meets the user's individual requirements. For example, this information may include information such as "the user does not like seafood."

[1632] Step 4:

[1633] The server generates appropriate recipes using the recipe suggestion means based on information obtained from the interactive artificial intelligence and the user profile management means. The recipes take into consideration the nutritional balance and the user's preferences. For example, specific menus such as "Summer vegetable ratatouille" and "Grilled chicken breast and vegetable salad" are suggested.

[1634] Step 5:

[1635] The server sends the proposed recipe to the terminal for confirmation by the user. The user confirms the proposed recipe and enters a confirmation such as "Yes, please." This input is sent to the server and used as data to proceed to the next processing step.

[1636] Step 6:

[1637] The server receives confirmation from the user and uses the ordering means to place a meal order with the corresponding restaurant. The order is processed automatically online, so the user does not need to manually place the order. For example, an order for "Summer Vegetable Ratatouille" is sent to the restaurant.

[1638] Step 7:

[1639] After the order is confirmed by the restaurant and the meal is prepared, the server uses a delivery method to instruct the food delivery company to deliver the meal to the user's residence. Based on this instruction, the food delivery company delivers the meal to the user's home. The user's address information is used to arrange the delivery.

[1640] These processing steps allow users to easily select a nutritionally balanced meal that is right for them and have it delivered to their home.

[1641] 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.

[1642] This invention is a system that uses interactive AI to suggest meal plans for elderly people who have difficulty shopping and those living in depopulated areas, and delivers those meals to the user's residence from a restaurant. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[1643] System Configuration

[1644] The system includes the following major components:

[1645] 1. User Interface (UI)

[1646] 2. Conversational AI Engine

[1647] 3. User Profile Management System

[1648] 4. Recipe suggestion engine

[1649] 5. Ordering System

[1650] 6. Delivery System

[1651] 7. Emotion Engine

[1652] User Interface (UI)

[1653] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[1654] Conversational Artificial Intelligence Engine

[1655] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1656] User Profile Management System

[1657] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[1658] Recipe suggestion engine

[1659] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1660] Ordering System

[1661] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1662] Delivery System

[1663] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1664] Emotion Engine

[1665] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[1666] Specific examples

[1667] 1. User accesses the system:

[1668] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1669] 2. Start a conversation:

[1670] Server: A conversational AI engine responds, "What would you like to eat today?"

[1671] 3. User Answer:

[1672] Terminal: The user types, "I'd like a vegetable-based menu."

[1673] 4. User Profile Reference:

[1674] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1675] 5. Emotion Analysis:

[1676] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[1677] 6. Recipe suggestions

[1678] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[1679] 7. User Choice:

[1680] Terminal: User selects "Yes, please."

[1681] 8. Submitting an Order:

[1682] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1683] 9. Delivery Arrangements:

[1684] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1685] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[1686] The processing flow will be explained below.

[1687] Step 1:

[1688] Terminal: The user launches the smartphone app and accesses the system. The terminal prompts for user authentication information. The user enters their user ID and password. The terminal sends the authentication information to the server.

[1689] Step 2:

[1690] Server: The server checks the authentication information and authenticates the user. The server refers to the user authentication database and returns the success or failure of the authentication to the terminal.

[1691] Step 3:

[1692] Server: Once authentication is complete, the server launches the conversational AI engine. The server sends a session start signal to the conversational AI engine. The conversational AI engine then asks the device, "What would you like to eat today?"

[1693] Step 4:

[1694] Terminal: The terminal displays questions from the conversational AI engine to the user. The user inputs, "I'd like a menu that's mainly vegetables." The terminal sends the user's input data to the server.

[1695] Step 5:

[1696] Server: The server passes the input data to the conversational AI engine, which analyzes the user's request. The conversational AI engine extracts the keyword "vegetable-based" from the user's comment.

[1697] Step 6:

[1698] Server: The conversational AI engine queries the user profile management system. The server accesses the user profile database to obtain information about dietary preferences and allergies. The server sends the obtained information back to the conversational AI engine.

[1699] Step 7:

[1700] Server: The emotion engine analyzes the user's dialogue and voice data to recognize the user's emotional state. For example, if the user is feeling stressed, it passes that information to the conversational AI engine.

[1701] Step 8:

[1702] Server: The recipe suggestion engine generates recipes based on the user's requests, profile information, and emotional state. The recipe suggestion engine searches for "vegetable-based" recipes and selects "Summer Vegetable Ratatouille" while taking into consideration nutritional balance. The selected recipe is sent to the device.

[1703] Step 9:

[1704] Device: The device displays the suggested recipe to the user. The user checks the suggested recipe and selects "I'll take this." The device then sends the selection to the server.

[1705] Step 10:

[1706] Server: The server confirms the selection and passes it on to the ordering system. The ordering system sends an order for "Summer Vegetable Ratatouille" to the restaurant that it serves. The restaurant confirms receipt of the order and returns a confirmation response to the server.

[1707] Step 11:

[1708] Server: The delivery system communicates with the delivery company after the meal is ready. The restaurant sends a notification to the delivery system when the meal is ready. The delivery system sends a delivery request to the delivery company. The delivery company delivers the meal to the user's home.

[1709] Step 12:

[1710] Terminal: The terminal notifies the user of the delivery information. The terminal notifies the user that "your meal is ready and will be delivered shortly."

[1711] Example 2

[1712] 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."

[1713] Currently, many elderly people and those living in depopulated areas face difficulties with daily shopping and meal preparation. Furthermore, food choices are often made without considering individual preferences or health conditions, leading to nutritional imbalances. In particular, the lack of meal suggestions tailored to the user's emotional state may also affect their mental health.

[1714] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for ordering the suggested meal plans from a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's dialogue content and voice data and recognizing the user's emotional state, and a suggestion adjustment means for adjusting the suggestion content based on the emotion analysis results and making personalized suggestions. As a result, meal options are suggested in a form that is appropriate not only to the user's individual preferences and health condition but also to the user's emotional state, allowing the user to maintain a healthier and more satisfying dietary lifestyle.

[1715] The "interface means" refers to an input means by which a user accesses the system and makes dietary consultations.

[1716] "Interactive artificial intelligence means" refers to artificial intelligence technology that uses natural language processing to analyze the content of the consultation received and generate an appropriate response.

[1717] The "recipe suggestion means" is a means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content.

[1718] The "ordering means" is a means for placing an order with the restaurant industry based on the proposed meal contents.

[1719] "Delivery means" refers to a means for delivering the ordered meal to the user's residence after it has been prepared.

[1720] The "emotion analysis means" is a means for analyzing the content of the user's dialogue and voice data to recognize the user's emotional state.

[1721] The "proposal adjustment means" is a means for adjusting the content of meal proposals based on the emotion analysis results and making personalized proposals.

[1722] The "user profile management means" is a means for storing and referencing a user's past interaction history and profile information.

[1723] The "means for notifying the order status" is a means for monitoring the order acceptance status of the restaurant industry and contacting the user.

[1724] MODE FOR CARRYING OUT THE INVENTION

[1725] This system, which targets elderly people and those living in depopulated areas, uses conversational AI to suggest meal plans and delivers those meals to the user's residence from the restaurant industry. Furthermore, by adding an emotion engine that analyzes the user's emotions and adjusts the suggestions based on those emotions, it is possible to provide a more personalized service.

[1726] The system includes the following major components:

[1727] User Interface (UI)

[1728] Device: Users interact with the system using a dedicated device or a smartphone app. The UI is simple and designed to be easy to use, even for seniors. For example, a user might input a request such as, "I'd like some advice on what to eat today."

[1729] Conversational Artificial Intelligence Engine

[1730] Server: The conversational AI engine receives the user's request and analyzes it using natural language processing. For example, if the user types "I don't like seafood," the engine understands the content and generates appropriate questions and responses.

[1731] User Profile Management System

[1732] Server: Contains a database for storing user preferences, allergy information, and past interaction history, allowing the conversational AI engine to respond to each user's individual requests.

[1733] Recipe suggestion engine

[1734] Server: The recipe suggestion engine uses information obtained from the conversational AI engine, user profile data, and emotion data to suggest nutritionally balanced recipes. For example, if a user requests a meat-based dinner, it will suggest a menu item such as grilled chicken breast and vegetable salad.

[1735] Ordering System

[1736] Server: When the user selects a suggested recipe, the ordering system places an order for the meal with the corresponding restaurant. For example, if the user selects "This recipe, please," the ordering system will order "grilled chicken breast and vegetable salad."

[1737] Delivery System

[1738] Server: Once the ordered meal is ready, the delivery system coordinates with the food delivery company to deliver the meal to the user's location. For example, once the meal is ready, it sends instructions to the delivery company to deliver the meal to the user's home.

[1739] Emotion Engine

[1740] Server: The emotion engine analyzes the user's dialogue and voice data to recognize their emotional state. This allows the recipe suggestion engine to adjust its suggestions based on the user's emotional state and suggest more appropriate meal plans. For example, if the user is feeling stressed, it will suggest a menu using ingredients that have a relaxing effect.

[1741] Specific examples

[1742] 1. User accesses the system:

[1743] Device: The user opens a smartphone app and types, "What should I have for dinner tonight?"

[1744] 2. Start a conversation:

[1745] Server: A conversational AI engine responds, "What would you like to eat today?"

[1746] 3. User Answer:

[1747] Terminal: The user types, "I'd like a vegetable-based menu."

[1748] 4. User Profile Reference:

[1749] Server: The user profile management system checks past data to see if the user has registered any foods as allergies.

[1750] 5. Emotion Analysis:

[1751] Server: The emotion engine analyzes the user's voice data and dialogue content to recognize the user's emotional state.

[1752] 6. Recipe suggestions

[1753] Server: The recipe suggestion engine suggests "Summer vegetable ratatouille" and asks the user, "Is this recipe okay?" If the emotion engine recognizes the emotion "I want to relax," it can suggest "Vegetable soup with herbs that has a relaxing effect."

[1754] 7. User Choice:

[1755] Terminal: User selects "Yes, please."

[1756] 8. Submitting an Order:

[1757] Server: The ordering system sends an order for "Summer Vegetable Ratatouille" to the corresponding restaurant.

[1758] 9. Delivery Arrangements:

[1759] Server: Once the meal is ready, the delivery system sends instructions to the food delivery company to arrange for the meal to be delivered to the user's home.

[1760] This system allows users to easily obtain nutritionally balanced meals and maintain a healthy diet. In addition, the addition of an emotion engine makes it possible to provide personalized services that take into account the user's emotional state.

[1761] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1762] Step 1:

[1763] A user accesses the system

[1764] Input: A user launches a smartphone app and enters a prompt such as "What should we have for dinner tonight?"

[1765] Processing: The terminal receives the user's input and sends it to the server.

[1766] Output: The user request is sent to the server.

[1767] Step 2:

[1768] Receive and analyze user interaction requests

[1769] Input: The server receives a request sent by the user.

[1770] Processing: The conversational AI engine analyzes the received request using natural language processing technology. It understands that the request is for dietary advice and extracts keywords related to the user's preferences and dietary restrictions.

[1771] Output: Parsed request content and extracted keywords.

[1772] Specific operation: For example, if a user inputs "I'd like a menu that mainly consists of vegetables," the system will extract the keywords "vegetables" and "menu."

[1773] Step 3:

[1774] Viewing a user profile

[1775] Input: Parsed request content and extracted keywords.

[1776] Processing: The server accesses the user profile management system and references the user's profile information (past interaction history, preferences, allergy information, etc.).

[1777] Output: User profile information.

[1778] Specific behavior: For example, if the user previously set "nut allergy," obtain that information.

[1779] Step 4:

[1780] Analyzing user emotions with an emotion engine

[1781] Input: User request details and user profile information.

[1782] Processing: The emotion engine analyzes the emotion from the user's input. If there is voice data, it performs voice analysis, and if there is text data, it performs text analysis.

[1783] Output: User's emotional state information.

[1784] Specific behavior: For example, if a user inputs "I feel kind of tired today," the emotional state "tired" is recognized.

[1785] Step 5:

[1786] Suggest a recipe

[1787] Input: Extracted keywords, user profile information, and emotional state information.

[1788] Processing: The recipe suggestion engine selects recipes suitable for the user based on the input information above. It also adjusts the suggestions taking into account nutritional balance and emotional state.

[1789] Output: A suggested recipe.

[1790] Specific behavior: For example, if a user types "I want to relax," the app will suggest "relaxing vegetable soup with herbs."

[1791] Step 6:

[1792] The user selects a recipe

[1793] Input: A suggested recipe.

[1794] Process: The suggested recipes are displayed on the device, and the user selects one.

[1795] Output: The recipe selected by the user.

[1796] Specific operation: For example, the user selects "Summer vegetable ratatouille."

[1797] Step 7:

[1798] The ordering system sends the order

[1799] Input: The recipe selected by the user.

[1800] Processing: The server's ordering system sends the order to the corresponding restaurant based on the selected recipe. The order is accepted in real time.

[1801] Output: Order notification to the food service industry.

[1802] Specific operation: For example, a server sends an order for "Summer vegetable ratatouille" to a restaurant.

[1803] Step 8:

[1804] The delivery system arranges the delivery

[1805] Input: Meals prepared in the food service industry.

[1806] Processing: Once the meal is ready, the server's delivery system sends instructions to a food delivery company to arrange delivery to the user's location. Delivery status can be tracked in real time.

[1807] Output: Delivery status notification to user.

[1808] Specific operation: For example, after the meal is ready, the server instructs the delivery company to "deliver to the user's home," and the user can check the delivery status in the app.

[1809] (Application example 2)

[1810] 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."

[1811] Elderly people and those living in depopulated areas often face difficulties in preparing and selecting meals. This creates a need for an easy way to obtain nutritionally balanced meals. Furthermore, the lack of a system that can provide meal suggestions based on the user's emotional state prevents the provision of more personalized services. Additionally, there is a need for a smartphone application with advanced interactive capabilities.

[1812] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1813] In this invention, the server includes an interface means for accepting dietary consultations from users, an interactive artificial intelligence means for analyzing the received consultation content, a recipe suggestion means for suggesting meal plans that take the user's preferences and nutritional balance into consideration based on the analyzed consultation content, an ordering means for placing an order for the suggested meal plans with a corresponding restaurant, a delivery means for delivering the ordered meal plans to the user's residence, an emotion analysis means for analyzing the user's emotional state and adjusting the suggested meal plans based on the emotion, and a user interface means in the form of a smartphone application, thereby enabling personalized meal suggestions and delivery according to the user's emotional state.

[1814] The "interface means" refers to an input and display device that allows the user to input dietary advice and receive suggestions from the system.

[1815] The "interactive artificial intelligence means" is a component that uses an artificial intelligence algorithm and natural language processing technology to analyze the content of the consultation received from the user and generate a response.

[1816] The "recipe suggestion means" is a function for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on information analyzed by the interactive artificial intelligence means.

[1817] The "ordering means" is a communication function for placing an order for the proposed meal contents with the corresponding restaurant.

[1818] "Delivery method" refers to a logistics system and a function linked to a delivery company for delivering the ordered meal contents to the user's residence.

[1819] "Emotion analysis means" refers to algorithms and computational techniques that analyze a user's emotional state and tailor suggestions based on that data.

[1820] A "smartphone application" is a software application that runs on a smartphone device and functions in conjunction with user interface means and other system components.

[1821] The "user profile management means" refers to a database and management system for storing and referencing a user's past interaction history and profile information.

[1822] The embodiment of the present invention mainly comprises the following components:

[1823] 1. User interface means (smartphone application)

[1824] 2. Interactive AI methods

[1825] 3. User profile management methods

[1826] 4. Recipe suggestion method

[1827] 5. Order Methods

[1828] 6. Delivery method

[1829] 7. Emotion analysis method

[1830] Overall Architecture

[1831] Accepting requests from users

[1832] Users use a smartphone application to input dietary inquiries, such as a request like, "What should I have for dinner tonight?" The application has an intuitive, easy-to-use interface and is designed to be easy to operate even for elderly people.

[1833] Analysis of Conversational Artificial Intelligence

[1834] The server analyzes the received request using an interactive AI means, which uses natural language processing technology to understand the user's input and generate an appropriate response, taking into account the user's preferences, allergy information, etc.

[1835] Viewing User Profiles

[1836] The server uses user profile management means to refer to past interaction history and profile information, which allows for more personalized responses. For example, if the user previously input information such as "I don't like seafood," this information will be taken into consideration.

[1837] Tailoring recommendations through sentiment analysis

[1838] The server uses emotion analysis to analyze the user's emotional state. This analysis is based on voice data and dialogue content, and the suggestions are adjusted to reflect the user's emotional state. For example, if the user is feeling stressed, a menu using ingredients with a relaxing effect will be suggested.

[1839] Recipe Suggestions

[1840] The server uses the recipe suggestion tool to suggest recipes that take nutritional balance into consideration based on the results of sentiment analysis and user profile information, such as "relaxing vegetable soup with herbs" or "grilled chicken breast and vegetable salad."

[1841] Ordering and Shipping

[1842] When the user selects a suggested recipe, the server uses the ordering means to place an order with the corresponding restaurant, and then uses the delivery means to deliver the order to the user's address, allowing the user to easily complete the entire process from request to final meal delivery.

[1843] Hardware and software used

[1844] The implementation of this system uses the following hardware and software:

[1845] Server: Flask (a Python micro web framework), Database (RDBMS or NoSQL)

[1846] User Interface: Smartphone application

[1847] Conversational AI: Natural language processing technology (GPT-3, etc.)

[1848] Sentiment analysis engine: IBM Watson, Azure AI, etc.

[1849] Specific examples

[1850] For example, an elderly user might use a smartphone application to input a request such as, "What should we have for dinner tonight?"

[1851] Assume that the interactive artificial intelligence means responds with "What would you like to eat today?" and the user replies, "I'd like a menu that is mainly vegetables."

[1852] Next, the emotion analysis means analyzes the user's emotion as "stress," and the recipe suggestion means suggests "relaxing vegetable soup using herbs."

[1853] Prompt Sentence Examples

[1854] "Based on the analysis results of the emotion engine, suggest meals that will have a relaxing effect on the elderly. Consider the user's data profile and emotional state and suggest recipes using appropriate ingredients."

[1855] In this way, users can easily obtain the optimal diet according to their emotional state and maintain their health.

[1856] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1857] Step 1:

[1858] The user starts the smartphone application and inputs a request about food, for example, "What should I have for dinner tonight?"

[1859] Input: User's meal request

[1860] Output: Request sent by smartphone application to server

[1861] Step 2:

[1862] The server passes the received request to an interactive artificial intelligence means for analysis, which uses natural language processing techniques to analyze the user's input and generate a response.

[1863] Input: User request

[1864] Output: Parsed request and appropriate response

[1865] Step 3:

[1866] Based on the analysis results, the server uses the user profile management means to refer to the user's past interaction history and profile information. For example, if the user has previously registered food allergies or dislikes, that information is obtained.

[1867] Input: Parsed request content

[1868] Output: User's past interaction history and profile information

[1869] Step 4:

[1870] The emotion analysis means analyzes the user's emotional state based on the dialogue content and voice data, and is then ready to adjust the suggestions according to the user's emotional state.

[1871] Input: Dialogue content and voice data

[1872] Output: Parsed user's emotional state

[1873] Step 5:

[1874] The server uses the recipe suggestion means to suggest a nutritionally balanced meal, taking into account the results of the sentiment analysis and the user profile information. For example, it suggests a "relaxing vegetable soup using herbs."

[1875] Input: User's emotional state and profile information

[1876] Output: Suggested recipe content

[1877] Step 6:

[1878] The user reviews the suggested recipe via a smartphone application and enters a response such as "I'd like this recipe, please."

[1879] Input: User response to suggested recipe

[1880] Output: Sending user selections to the server

[1881] Step 7:

[1882] The server uses the ordering means to place an order for the selected recipe with the corresponding restaurant business, and the ordering means transmits the order data using a communication function.

[1883] Input: Recipe content selected by the user

[1884] Output: Order data for the restaurant industry

[1885] Step 8:

[1886] After the order is completed, the delivery method will coordinate with the food delivery company to arrange delivery to the user's residence. The server will monitor the delivery status and notify the user as necessary.

[1887] Input: Order data and shipping information

[1888] Output: Delivery instructions and delivery status notification to the user

[1889] Through these steps, users are easily recommended nutritionally balanced meals and have meals delivered to their home that correspond to their emotional state.

[1890] 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.

[1891] 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.

[1892] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1893] 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.

[1894] FIG. 9 illustrates an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1895] 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.

[1896] 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).

[1897] 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.

[1898] 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."

[1899] 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.

[1900] 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).

[1901] 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.

[1902] 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.

[1903] 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.

[1904] 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.

[1905] 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.

[1906] 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.

[1907] 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.

[1908] 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.

[1909] 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.

[1910] 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.

[1911] The following is further disclosed regarding the above embodiment.

[1912] (Claim 1)

[1913] an interface means for receiving dietary advice from a user;

[1914] An interactive artificial intelligence means for analyzing the received consultation content;

[1915] a recipe suggestion means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content;

[1916] ordering means for placing an order for the proposed meal contents to a corresponding restaurant;

[1917] and a delivery means for delivering the ordered meal to the user's residence.

[1918] (Claim 2)

[1919] 2. The system of claim 1, wherein the interactive artificial intelligence means further comprises a user profile management means for referencing a user's past interaction history and profile information.

[1920] (Claim 3)

[1921] 2. The system according to claim 1, further comprising means for monitoring the order acceptance status of the food service business that the ordering means corresponds to, and notifying the user of the order status.

[1922] "Example 1"

[1923] (Claim 1)

[1924] an interface means for receiving dietary advice from a user;

[1925] An interactive artificial intelligence means for analyzing the received consultation content;

[1926] a recipe suggestion means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content;

[1927] ordering means for placing an order for the proposed meal contents to a corresponding restaurant;

[1928] and a delivery means for delivering the ordered meal to the user's residence.

[1929] (Claim 2)

[1930] 2. The system of claim 1, wherein the interactive artificial intelligence means further comprises a user profile management means for referencing a user's past interaction history and profile information.

[1931] (Claim 3)

[1932] 2. The system according to claim 1, further comprising means for monitoring the order acceptance status of the food service business that the ordering means corresponds to, and notifying the user of the order status.

[1933] "Application Example 1"

[1934] (Claim 1)

[1935] an interface means for receiving dietary advice from a user;

[1936] An interactive artificial intelligence means for analyzing the received consultation content;

[1937] a recipe suggestion means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content;

[1938] ordering means for placing an order for the proposed meal contents to a corresponding restaurant;

[1939] a delivery means for delivering the ordered meal to the user's residence;

[1940] The system includes a user interface means and a smartphone application for suggesting suitable recipes based on the user's consultation and for processing voice or text input.

[1941] (Claim 2)

[1942] The interactive artificial intelligence means further includes a user profile management means for referring to the user's past interaction history and profile information;

[1943] 10. The system of claim 1.

[1944] (Claim 3)

[1945] The ordering means further includes a means for monitoring the order acceptance status of the food service industry that the ordering means corresponds to, and notifying the user of the order status.

[1946] 10. The system of claim 1.

[1947] "Example 2: Combining Emotion Engines"

[1948] (Claim 1)

[1949] an interface means for receiving dietary advice from a user;

[1950] An interactive artificial intelligence means for analyzing the received consultation content;

[1951] a recipe suggestion means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content;

[1952] ordering means for placing an order for the proposed meal contents to a corresponding restaurant;

[1953] a delivery means for delivering the ordered meal to the user's residence;

[1954] emotion analysis means for analyzing the content of a user's dialogue and voice data and recognizing the user's emotional state;

[1955] a proposal adjustment means for adjusting the proposal content based on the emotion analysis result and making an individualized proposal;

[1956] A system including:

[1957] (Claim 2)

[1958] 2. The system of claim 1, wherein the interactive artificial intelligence means further comprises a user profile management means for referencing a user's past interaction history and profile information.

[1959] (Claim 3)

[1960] 2. The system according to claim 1, further comprising means for monitoring the order acceptance status of the food service business that the ordering means corresponds to, and notifying the user of the order status.

[1961] "Application example 2 when combining emotion engines"

[1962] (Claim 1)

[1963] an interface means for receiving dietary advice from a user;

[1964] An interactive artificial intelligence means for analyzing the received consultation content;

[1965] a recipe suggestion means for suggesting meal contents that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content;

[1966] ordering means for placing an order for the proposed meal contents to a corresponding restaurant;

[1967] a delivery means for delivering the ordered meal to the user's residence;

[1968] emotion analysis means for analyzing the user's emotional state and adjusting the suggestions based on the emotion;

[1969] user interface means in the form of a smartphone application;

[1970] A system including:

[1971] (Claim 2)

[1972] 2. The system of claim 1, wherein the interactive artificial intelligence means further comprises a user profile management means for referencing a user's past interaction history and profile information.

[1973] (Claim 3)

[1974] 2. The system according to claim 1, further comprising means for monitoring the order acceptance status of the food service business that the ordering means corresponds to, and notifying the user of the order status. [Explanation of symbols]

[1975] 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. an interface means for receiving dietary advice from a user; An interactive artificial intelligence means for analyzing the received consultation content; a recipe suggestion means for suggesting meal plans that take into consideration the user's preferences and nutritional balance based on the analyzed consultation content; ordering means for placing an order for the proposed meal contents to a corresponding restaurant; and a delivery means for delivering the ordered meal to the user's residence.

2. 2. The system according to claim 1, further comprising a user profile management means for the interactive artificial intelligence means to refer to a user's past interaction history and profile information.

3. 2. The system according to claim 1, further comprising means for monitoring the order acceptance status of the food service business handled by said ordering means and notifying the user of the order status.

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