system

Abstract

Provide a system. [Solution] an input means for a user to input information about physical condition and food preferences; a selection means for selecting optimal ingredients, recipes, and dishes based on user input information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; an order receiving means for receiving a delivery request for the proposed dishes; A means of cooperation with delivery services to confirm orders and notify delivery progress; A system including:

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] Pregnant women's physical condition and food preferences often change significantly, and morning sickness and other physical discomfort can make it difficult to eat an appropriate diet, especially in the early stages of pregnancy. Therefore, there is a need for a system that allows pregnant women to easily find ingredients and dishes that suit their physical condition and preferences. In particular, a system that can be operated intuitively in a short amount of time and that also allows delivery requests is needed. [Means for solving the problem]

[0005] The present invention solves the above-mentioned problems by providing a system including an input means for a user to input information about their physical condition and food preferences, a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information, a proposal means for suggesting the selected ingredients, recipes, and dishes to the user, an order receiving means for accepting a delivery request for the proposed dishes, and a linking means for coordinating with a delivery service to confirm the order and notify the user of the progress of the delivery. Furthermore, by providing a selection means that stores the user's input information in a database and selects optimal ingredients, recipes, and dishes by referencing the user's past meal history, it is possible to make suggestions that match the user's preferences. Furthermore, by coordinating with the delivery service using its API and confirming the order, the user can easily request delivery.

[0006] "User" refers to individuals, primarily pregnant women, who use the system.

[0007] "Health" refers to the user's current physical health, including symptoms and moods, especially during pregnancy.

[0008] "Food preferences" refers to information about the user's preferences, such as what ingredients and dishes they like.

[0009] "Input means" refers to an interface that allows users to input information about their physical condition, food preferences, allergies, etc. via a smartphone or computer.

[0010] "Selection method" refers to the algorithm or process used to search and select the most suitable ingredients, recipes, and dishes from a database based on user input.

[0011] The "suggestion means" refers to an interface for presenting the ingredients, recipes, and dishes selected by the selection means to the user.

[0012] The "order receiving means" refers to an interface through which the user can request delivery of the proposed dishes.

[0013] "Means of collaboration" refers to the system part that uses the delivery service's API to confirm orders and notify the progress of delivery.

[0014] A "database" refers to a structured collection of information for storing user inputs, ingredients, recipes, and cooking data.

[0015] "API" refers to an interface for sharing functions and data between different systems, and is used to connect with delivery services. [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 illustrating 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] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[0038] System Overview

[0039] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[0040] Program processing overview

[0041] 1. Launch the app and log in

[0042] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[0043] 2. Enter your user information

[0044] The device prompts the user to enter information about their physical condition, food preferences, and allergies, and the information is then sent from the device to the server.

[0045] 3. Proposal Data Generation

[0046] The server stores the user's input information in a database and searches the database to select the most suitable ingredients, recipes, and dishes.

[0047] The server generates the selection results in list format and sends them to the terminal.

[0048] 4. Viewing and selecting suggestions

[0049] The device displays suggested ingredients, recipes, and dishes to the user.

[0050] The user selects their favorite dish from the list.

[0051] 5. Executing a delivery request

[0052] The terminal sends a delivery request for the selected dish to the server.

[0053] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[0054] 6. Order Confirmation and Tracking

[0055] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[0056] Specific examples

[0057] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[0058] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[0059] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[0060] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[0061] 5. The server contacts a nearby delivery service and confirms the order.

[0062] 6. The order details are sent to the user's device and delivery begins.

[0063] The present invention provides a system that allows for the selection of appropriate meals in response to changes in physical condition during pregnancy and can be operated intuitively in a short time, thereby enabling pregnant women to eat comfortably.

[0064] The above is a description of the preferred embodiment of the present invention, which provides details for specifically implementing the present invention based on the content set forth in the claims.

[0065] The processing flow will be explained below.

[0066] Step 1:

[0067] The user launches the app on their smartphone.

[0068] How it works: The user taps the app icon to launch it.

[0069] Step 2:

[0070] The terminal prompts the user to log in.

[0071] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[0072] Step 3:

[0073] The user logs in with LINE or Yahoo!

[0074] Operation details: The user enters their account information using the authentication method they selected and logs in.

[0075] Step 4:

[0076] The device will ask you to enter information about your physical condition, food preferences, and allergies.

[0077] Operation details: The device displays an input form screen and asks the user to enter information.

[0078] Step 5:

[0079] The user inputs information such as physical condition, food preferences, and allergy information.

[0080] Action details: The user fills in the required information in the input form.

[0081] Step 6:

[0082] The terminal transmits the input information to the server.

[0083] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[0084] Step 7:

[0085] The server stores the received user information in a database.

[0086] What happens: The server opens a database connection and saves the user information in the corresponding table.

[0087] Step 8:

[0088] The server searches a database of ingredients, recipes, and dishes.

[0089] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, and allergies.

[0090] Step 9:

[0091] The server generates a list of the selection results and sends it to the terminal.

[0092] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[0093] Step 10:

[0094] The device displays suggested ingredients, recipes, and dishes to the user.

[0095] Operation details: The device receives the suggestion list and displays it on the screen.

[0096] Step 11:

[0097] The user selects their preferred dish from the list of suggestions.

[0098] What it does: The user taps to select one or more dishes from the list.

[0099] Step 12:

[0100] The terminal sends a delivery request to the server.

[0101] Operation details: The device sends a delivery request including the selected dish information to the server.

[0102] Step 13:

[0103] The server connects to the delivery service's API to confirm the order.

[0104] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[0105] Step 14:

[0106] The server notifies the user terminal of the order details.

[0107] Operation details: The server generates order confirmation information and sends it to the user terminal.

[0108] Step 15:

[0109] The terminal displays the order confirmation information to the user.

[0110] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[0111] Step 16:

[0112] The server updates the delivery progress in real time and notifies the device.

[0113] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[0114] Step 17:

[0115] The user checks the delivery status.

[0116] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[0117] The above are the detailed processing steps performed by the system of the present invention.

[0118] Example 1

[0119] 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."

[0120] In recent years, as part of health management, there has been a demand for meal selection based on individual physical condition and food preferences. However, conventional systems require users to collect information themselves and select the optimal ingredients and cooking methods, which takes time and effort. Furthermore, when using delivery services, a separate order is required. Furthermore, to track the progress of delivery after ordering, users must check the individual applications of each service. To solve these problems, a system is needed that automatically selects the optimal ingredients and dishes based on the information entered by the user and provides consistent support right up to delivery.

[0121] 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.

[0122] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a storage means for storing the user's input information, a selection means for selecting optimal ingredients, cooking methods, and dishes based on the stored information, a suggestion means for suggesting the selected ingredients, cooking methods, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, and a linking means for confirming the order using the delivery service's API and notifying the user of the progress of the delivery. This enables users to easily select the meal that is optimal for them, quickly order using the delivery service, and keep track of the progress in real time.

[0123] "User" refers to a person who uses the system to input information about their physical condition and food preferences, and then checks and selects suggested dishes.

[0124] "Input means" refers to a device or interface that allows a user to input information about their physical condition, food preferences, allergies, and the like.

[0125] "Storage means" refers to a device or function for storing information input by a user.

[0126] "Selection means" refers to a device or function that selects optimal ingredients, cooking means, and dishes based on stored user input information.

[0127] The "suggestion means" refers to a device or function for suggesting selected ingredients, cooking means, and dishes to the user.

[0128] "Order receiving means" refers to a device or function for receiving a delivery request for the proposed dishes.

[0129] "Linkage means" refers to a device or function for confirming an order using the delivery service's API and notifying the progress of delivery.

[0130] "Database" refers to an information management system for storing, searching, and analyzing user input information and past meal history.

[0131] "Delivery service" refers to a business that provides a service of delivering food ordered by a user.

[0132] "Delivery progress" refers to the status of each stage until the ordered food is delivered to the user.

[0133] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[0134] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[0135] System Overview

[0136] When a user uses the system, they install and launch an application on their smartphone or computer. When the user enters information about their physical condition and food preferences, that information is sent to the server. The server selects the most suitable ingredients, cooking methods, and dishes from a database based on the user's input, and suggests them to the user. When the user checks the suggestions, selects a specific dish, and requests delivery, the server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[0137] System configuration

[0138] 1. Input Method

[0139] A device or interface that allows users to input information about their physical condition and food preferences. This is implemented on a smartphone or computer application screen.

[0140] 2. Preservation means

[0141] A device or function for saving user-entered information. Information is saved in a database (e.g., MySQL (registered trademark) database) on a cloud server.

[0142] 3. Selection method

[0143] A device or function that selects the best ingredients, cooking methods, and dishes based on stored information. Python scripts are used to search the database and parse user information.

[0144] 4. Proposal method

[0145] A device or function for suggesting selected ingredients, cooking methods, and dishes to the user. It generates a list in JSON format and displays it in the user interface.

[0146] 5. Ordering Method

[0147] A device or function for accepting delivery requests for suggested dishes, and sending information about the dishes selected by the user to the server.

[0148] 6. Collaboration Methods

[0149] A device or function that uses the delivery service's API to confirm orders and notify delivery progress. It works in conjunction with delivery services using APIs such as Uber Eats.

[0150] Specific examples

[0151] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[0152] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[0153] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[0154] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[0155] 5. The server contacts a nearby delivery service and confirms the order.

[0156] 6. The order details are sent to the user's device and delivery begins.

[0157] Specific prompt examples

[0158] "If I want to eat something disgusting and sour, please suggest what would be good."

[0159] "They suggested lemon chicken salad, so I ordered it for delivery."

[0160] The present invention provides an environment in which users can easily select meals that suit their physical condition and operate intuitively. This is particularly useful during periods of rapid physical changes such as pregnancy. This allows users to eat comfortably.

[0161] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0162] Step 1: Launch the app and log in

[0163] The user launches the app on their smartphone.

[0164] The device displays the splash screen and provides a login screen. The user enters their LINE or general account information. Input: User's login information. Output: Authentication token.

[0165] The server uses the authentication API to check the entered login information, and if authentication is successful, it generates an authentication token and sends it to the terminal.

[0166] The device receives the authentication token and displays the main screen.

[0167] Step 2: Enter your user information

[0168] The device displays a form for entering information about your physical condition, food preferences, and allergies.

[0169] The user enters "feeling sick" as their physical condition, "sour foods" as their food preference, and allergy information. Input: User's physical condition and preference information. Output: Input information in JSON format.

[0170] The terminal converts the input information into JSON format and sends it to the server.

[0171] Step 3: Save your information

[0172] Parse the JSON format user information received by the server. Input: JSON format user information. Output: Save to database.

[0173] The server stores user information in a MySQL database.

[0174] Step 4: Generate proposal data

[0175] The server starts parsing based on the stored user information. Input: User information stored in the database. Output: A list of suggestions in JSON format.

[0176] The server uses a Python script to select the best ingredients, cooking methods, and dishes based on the user's physical condition and food preferences.

[0177] The server compiles the selection results into a JSON format list and sends it to the terminal.

[0178] Step 5: View and select suggestions

[0179] The device displays the received suggestion list in the UI. Input: Suggestion list sent from the server. Output: Display of suggestion list.

[0180] User taps to select the dish they are interested in from the suggestion list. Input: User selection. Output: Details of the selected dish.

[0181] The device sends information about the selected dish in JSON format to the server.

[0182] Step 6: Execute delivery request

[0183] The server calls the delivery service's API based on the selected dish information. Input: Information about the dish selected by the user. Output: Confirmed order and delivery details.

[0184] The server confirms the order using the delivery service's API and generates delivery progress information.

[0185] The server sends delivery progress information to the terminal.

[0186] Step 7: Order confirmation and tracking

[0187] The terminal notifies the user of the order confirmation details and delivery progress. Input: Delivery progress information sent from the server. Output: Order details and progress notification.

[0188] Monitor delivery status in real time and display status updates to users.

[0189] This is the specific process flow of this system, allowing users to easily select the perfect meal and track the delivery progress.

[0190] (Application example 1)

[0191] 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."

[0192] Conventional food delivery systems have had difficulty proposing individually optimized ingredients, recipes, and dishes based on a user's physical condition and food preferences. They also lacked a means to notify users of the progress of delivery of the proposed dishes in real time, making it difficult to improve user satisfaction.

[0193] 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.

[0194] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information, a suggestion means for suggesting the selected ingredients, recipes, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, a linking means for linking with a delivery service to confirm the order and notify the user of the delivery progress, and a tracking means for notifying the user of the delivery progress in real time, thereby enabling personalized suggestions for dishes tailored to the user's physical condition and preferences and real-time notification of the delivery progress.

[0195] "User" refers to an individual who uses the system by inputting information about their physical condition and food preferences.

[0196] "Physical condition" refers to the user's health condition and any physical symptoms they may be experiencing.

[0197] "Food preference information" refers to data including the user's favorite ingredients, types of cuisine, taste preferences, allergy information, etc.

[0198] "Input means" refers to an interface that allows a user to input information about their physical condition and food preferences into the system.

[0199] The "selection means" refers to a means for selecting optimal ingredients, recipes, and dishes based on information input by the user.

[0200] "Proposal means" refers to a means for presenting selected ingredients, recipes, and dishes to the user.

[0201] "Means for receiving orders" refers to the means for accepting delivery requests for the proposed dishes.

[0202] "Means of collaboration" refers to the means of collaborating with a delivery service to confirm an order and notify the delivery progress.

[0203] "Tracking Method" means a method selected by the User that notifies the User of delivery progress in real time.

[0204] "Delivery service" refers to a service that delivers food or products to a specified location.

[0205] "API" stands for Application Programming Interface and refers to the rules for exchanging functions between different software.

[0206] "Server" refers to a computer system that stores and analyzes data.

[0207] A "database" refers to a structured collection of information for efficient storage and retrieval of data.

[0208] That's all.

[0209] To put the present invention into practice, an application is installed on the user's smartphone or computer, and the following process is performed.

[0210] System Overview

[0211] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress. A tracking method is also included to notify the user of the delivery progress of their selected order in real time.

[0212] Program processing overview

[0213] This section explains the roles of servers and user terminals, as well as the hardware and software they use.

[0214] 1. Launch the app and log in

[0215] The user launches the app on their smartphone and logs in using their social networking account on the login screen. Firebase Authentication is used for logging in. The device verifies the login information and issues an authentication token.

[0216] 2. Enter your user information

[0217] The terminal asks the user to enter information about their physical condition, food preferences, and allergies. The user enters the information into a form and sends it to the server. React Native is used for the input form. The input data passes validation before being sent to the server.

[0218] 3. Proposal Data Generation

[0219] The server stores the user's input information in a database and searches the database to select the best ingredients, recipes, and dishes. This is done using Node.js and MongoDB. The server matches the user data with the database and generates a list of suggestions.

[0220] 4. Viewing and selecting suggestions

[0221] The device displays the suggested ingredients, recipes, and dishes to the user. The user selects the dish they like from the list. This list display is done using React Native. The selected dish data is sent to the server.

[0222] 5. Executing a delivery request

[0223] The device sends a delivery request for the selected food to the server. The server confirms the order using the delivery service's API. Axios is used for API communication. Order details are sent to the delivery service.

[0224] 6. Order Confirmation and Tracking

[0225] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time, using the Firebase Realtime Database. The delivery status is periodically checked and notifications are sent.

[0226] Specific examples

[0227] 1. If a user is feeling unwell and wants to eat something sour, they launch the app and log in with their social media account.

[0228] 2. Type "I want to eat something sour."

[0229] 3. The server suggests dishes using lemon or plum, and "Lemon Chicken Salad" is displayed.

[0230] 4. The user selects the suggested dish and places a delivery request.

[0231] 5. The server contacts a nearby delivery service and confirms the order.

[0232] 6. Order details and progress are notified in real time to the user's smartphone.

[0233] Prompt Sentence Examples

[0234] User: "I want to eat something sour, but my stomach is upset."

[0235] App: "Would you like some lemon chicken salad? Would you like it delivered?"

[0236] This will enable personalized food suggestions tailored to the user's physical condition and preferences, as well as real-time notifications of delivery progress.

[0237] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0238] The processing flow of the program of the system that realizes the application example will be specifically explained below, broken down into steps.

[0239] Step 1:

[0240] A user launches the application on their device and logs in using their social network account on the login screen. The user's social network account information is required as input. The device verifies the login information using Firebase Authentication and generates an authentication token. The authentication token is obtained as output.

[0241] Step 2:

[0242] After logging in, the user enters information about their physical condition, food preferences, and allergies on the terminal. The information the user enters into the form is required as input. The input form created using React Native validates the data and sends it to the server. The output is user information that has passed validation.

[0243] Step 3:

[0244] The server receives user input information and stores it in a database. The submitted user information is required as input. The server uses Node.js to store the information in a database (MongoDB). The output is the user information stored in the database.

[0245] Step 4:

[0246] The server searches the database and selects the best ingredients, recipes, and dishes based on the user's input. As input, the server requires user information and dish information from the database. The server uses a matching algorithm to generate the best suggestions list. As output, the suggestions list is obtained and sent to the user's device.

[0247] Step 5:

[0248] The device displays suggested ingredients, recipes, and dishes to the user. As input, it requires a list of suggestions sent from the server. It displays the information in a list format using React Native. The user selects their favorite dish, and the selected dish information is obtained as output.

[0249] Step 6:

[0250] The device sends a delivery request to the server for the dish selected by the user. The user-selected dish information is required as input. The device sends the selected dish data to the server, and the server confirms the order through the delivery service's API. The confirmed order information is obtained as output.

[0251] Step 7:

[0252] The server confirms the order using the delivery service's API. As input, it requires the selected dish information and the user's delivery information. The server uses the Axios library to send the order information to the delivery service. As output, the delivery is initiated.

[0253] Step 8:

[0254] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time. The input requires order confirmation information and delivery progress information sent from the server. The Firebase Realtime Database is used to periodically check the progress and notify them. The output provides information that allows the user to check the delivery progress in real time.

[0255] The above is the flow of specific processing steps of the system that realizes the application example.

[0256] 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.

[0257] The system of the present invention recognizes the user's physical condition, food preferences, and emotions, suggests optimal ingredients, recipes, and dishes, and works in conjunction with delivery services. Specifically, the process is carried out as follows.

[0258] System Overview

[0259] When a user uses the system, they launch an application on their smartphone or computer and input information about their physical condition, food preferences, allergies, and emotional information recognized by the emotion engine from voice, facial expressions, and text input. This information is sent to the server, which then selects optimal ingredients, recipes, and dishes from a database based on the user's input, including past eating history and emotional history, and suggests them to the user. The user then selects the suggested ingredients and dishes and requests delivery. The server then connects with the delivery service, confirms the order, and notifies the user of the progress of the delivery.

[0260] Program processing overview

[0261] 1. Launch the app and log in

[0262] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[0263] 2. Input of user information and emotion information

[0264] The device asks for input of physical condition, food preferences, allergy information, and emotions recognized by the emotion engine from voice, facial expressions, and text input.

[0265] The user enters this information and the terminal transmits the data to the server.

[0266] 3. Proposal Data Generation

[0267] The server stores the received user information in a database, and searches the database based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history to select optimal ingredients, recipes, and dishes.

[0268] The server generates the selection results in list format and sends them to the terminal.

[0269] 4. Viewing and selecting suggestions

[0270] The device displays suggested ingredients, recipes, and dishes to the user.

[0271] The user selects their favorite dish from the list.

[0272] 5. Executing a delivery request

[0273] The terminal sends a delivery request for the selected dish to the server.

[0274] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[0275] 6. Order Confirmation and Tracking

[0276] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[0277] Specific examples

[0278] 1. The user thinks, "I'm feeling down and I want to eat something sweet," and launches the app.

[0279] 2. The user logs in to LINE and enters their physical condition, the keyword "sweets," and the "depressed mood" information recognized by the emotion engine.

[0280] 3. The server analyzes the user's past data, input information, and emotional information, and suggests recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered.

[0281] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[0282] 5. The server contacts the delivery service and confirms the order.

[0283] 6. The order details are sent to the user's device and delivery begins.

[0284] The present invention provides a system that enables appropriate meal selection in response to changes in physical condition and emotions during pregnancy, and can provide a comfortable dining experience by making suggestions that match the user's preferences and mood.

[0285] The processing flow will be explained below.

[0286] Step 1:

[0287] The user launches the app on their smartphone.

[0288] What happens: A user launches an app by tapping its icon.

[0289] Step 2:

[0290] The terminal prompts the user to log in.

[0291] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[0292] Step 3:

[0293] The user logs in with LINE or Yahoo!

[0294] Operation details: The user enters their account information using the authentication method they selected and logs in.

[0295] Step 4:

[0296] The device asks you to enter information about your physical condition, food preferences, allergies, and emotions.

[0297] Operation details: The device displays an input form screen and prompts the user to enter information. The emotion engine also recognizes emotions from the user's voice, facial expressions, and text input.

[0298] Step 5:

[0299] The user inputs information about their physical condition, food preferences, allergy information, and emotional information.

[0300] Operation details: The user fills in the required information in the input form. Emotional information is automatically recognized from voice, facial expressions, text input, etc.

[0301] Step 6:

[0302] The terminal transmits the input information to the server.

[0303] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[0304] Step 7:

[0305] The server stores the received user information in a database.

[0306] What happens: The server opens a database connection and saves the user information in the corresponding table.

[0307] Step 8:

[0308] The server searches a database of ingredients, recipes and dishes, taking emotional information into account.

[0309] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, emotions and allergy information.

[0310] Step 9:

[0311] The server generates a list of the selection results and sends it to the terminal.

[0312] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[0313] Step 10:

[0314] The device displays suggested ingredients, recipes, and dishes to the user.

[0315] Operation details: The device receives the suggestion list and displays it on the screen.

[0316] Step 11:

[0317] The user selects their preferred dish from the list of suggestions.

[0318] What it does: The user taps to select one or more dishes from the list.

[0319] Step 12:

[0320] The terminal sends a delivery request to the server.

[0321] Operation details: The device sends a delivery request including the selected dish information to the server.

[0322] Step 13:

[0323] The server connects to the delivery service's API to confirm the order.

[0324] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[0325] Step 14:

[0326] The server notifies the user terminal of the order details.

[0327] Operation details: The server generates order confirmation information and sends it to the user terminal.

[0328] Step 15:

[0329] The terminal displays the order confirmation information to the user.

[0330] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[0331] Step 16:

[0332] The server updates the delivery progress in real time and notifies the device.

[0333] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[0334] Step 17:

[0335] The user checks the delivery status.

[0336] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[0337] The above are the detailed processing steps performed by the system of the present invention.

[0338] Example 2

[0339] 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."

[0340] Conventional ingredient and dish recommendation systems make recommendations based solely on a user's physical condition and food preferences, making it difficult to make recommendations that reflect the user's emotions. While utilizing a user's past meal history can provide more appropriate recommendations, it is difficult to make meal recommendations that reflect the user's mood because the history management does not include emotional information. The present invention solves these problems by providing a system that makes it possible to recommend and request delivery of appropriate ingredients, recipes, and dishes based on a user's physical condition, food preferences, and even emotions.

[0341] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0342] In this invention, the server includes an input means for the user to input information about their physical condition and food preferences, an emotion recognition means for analyzing the input emotion information, and a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotion information, thereby making it possible to suggest meals that take into account the user's emotions in addition to their physical condition and food preferences.

[0343] The "input means" is an interface that allows the user to input information about their physical condition and food preferences into the system.

[0344] "Emotion recognition means" is a technology that analyzes and recognizes emotional information from the user's input voice, facial expressions, etc.

[0345] The "selection means" is a function for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preference information, and emotional information.

[0346] The "suggestion means" is a function for presenting selected ingredients, recipes, and dishes to the user.

[0347] The "order receiving means" is a system for receiving a delivery request when a user makes a delivery request for the proposed dish.

[0348] The "linking means" is a technology that links with a delivery service to confirm an order and notify the user of the progress of the delivery.

[0349] The "database" is a storage system for storing user input information, past meal history, and emotional history.

[0350] An "API" is an application programming interface that allows different systems to communicate with each other and utilize their functions.

[0351] The system of the present invention proposes optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, and emotional information, and works in conjunction with delivery services. Specific embodiments of this system are described in detail below.

[0352] 1. Program Generation

[0353] The system's program is developed using Python. It uses SQLite for database operations and a generative AI model (such as the OpenAI (registered trademark) emotion recognition model) for emotion recognition. It also uses common APIs such as the Zinc API for integration with delivery services.

[0354] 2. Program Processing Overview

[0355] The processing outline of this system is as follows.

[0356] 1. Launch the app and log in

[0357] The user launches the app on their smartphone and logs in using a regular account (such as a LINE or Yahoo! account) on the login screen. The device sends the login information to the server, which then performs the authentication process.

[0358] 2. Input of user information and emotion information

[0359] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[0360] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data. The input information and emotional data are sent from the device to the server.

[0361] 3. Proposal Data Generation

[0362] The server stores the received user information in a database, and then searches the database to select optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history.

[0363] The server generates a list of selected ingredients, recipes, and dishes and sends it to the terminal.

[0364] 4. Viewing and selecting suggestions

[0365] The terminal displays a list of suggested ingredients, recipes, and dishes for the user to choose from.

[0366] 5. Executing a delivery request

[0367] The device sends a delivery request for the selected food to the server, which then uses the delivery service's API to confirm the order and notify the user of the delivery details.

[0368] 6. Order Confirmation and Tracking

[0369] The terminal displays order confirmation information to the user, and the server monitors the delivery progress in real time and sends updates to the terminal.

[0370] 3. Specific Examples

[0371] Specific examples are shown below.

[0372] 1. If a user feels depressed and wants to eat something sweet, they launch the app and log in with their LINE account.

[0373] 2. The user inputs their physical condition, the keyword "sweets," and the information about "depressed mood" that the emotion engine recognizes.

[0374] 3. The server analyzes the user's past data, input information, and emotional information to suggest recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered. A list is displayed to the user.

[0375] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[0376] 5. The server contacts the delivery service to confirm the order. The user is notified of the delivery progress.

[0377] 4. Examples of prompts

[0378] Below is an example of a prompt sentence to input to the generative AI model.

[0379] 1. Emotion recognition prompt:

[0380] "The user inputs, 'I'm tired from work today and I want to eat something sweet.' Please determine this emotion."

[0381] 2. Prompt for the best dish suggestion:

[0382] "The user's physical condition is 'tired,' their preference is 'sweets,' and their emotion is 'depressed.' Please suggest the best recipe based on this information."

[0383] As described above, the present invention realizes optimal meal suggestions and delivery requests based on the user's physical condition, food preferences, and even emotional information.

[0384] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0385] Step 1: Launch the app and log in

[0386] 1-1. Launching the app

[0387] The user taps the app on their smartphone to launch it, and the app's main screen appears.

[0388] Input: None

[0389] Output: Main screen of the app

[0390] 1-2. Login

[0391] The device displays a login screen, and the user selects a generic account (e.g., LINE or Yahoo! account), enters authentication information, and presses the login button.

[0392] The authentication information is sent from the terminal to the server.

[0393] The server performs user authentication based on the received authentication information, and if successful, loads the user's past data and sends a login completion message to the terminal.

[0394] Input: User credentials

[0395] Output: Login completion message, user's past data

[0396] Step 2: Enter user information and emotion information

[0397] 2-1. Displaying the information input form

[0398] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[0399] Input: None

[0400] Output: Information input form

[0401] 2-2. Entering information

[0402] The user inputs information about their physical condition, food preferences, and allergies, as well as voice and facial expressions.

[0403] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data.

[0404] The input information and emotion data are transmitted from the terminal to the server.

[0405] Input: User's physical condition information, food preferences, allergy information, voice and facial expression data

[0406] Data processing: Voice and facial expression analysis using generative AI models

[0407] Output: Analyzed emotion data, user-entered physical condition information, food preferences, and allergy information

[0408] Step 3: Generate proposal data

[0409] 3-1. Data storage

[0410] The server stores the received user information in a database, including information on physical condition, food preferences, allergies, and emotional data.

[0411] Input: User information, analyzed emotion data

[0412] Output: Information stored in the database

[0413] 3-2. Data analysis and search

[0414] The server performs analysis based on the stored data and past eating and emotional history.

[0415] It uses generative AI models to find the best ingredients, recipes, and dishes for a user's emotions and physical condition.

[0416] Compile a list of selected ingredients, recipes, and dishes.

[0417] Input: User information extracted from the database, past meal history, emotional history

[0418] Data processing: Analysis with generative AI models

[0419] Output: A list of selected ingredients, recipes, and dishes

[0420] 3-3. Sending proposal data

[0421] The server transmits the generated list to the terminal.

[0422] Input: Selected list

[0423] Output: List sent to terminal

[0424] Step 4: View and select suggestions

[0425] 4-1. Display of proposed data

[0426] The terminal displays the received list to the user, which includes a list of ingredients, recipes, and dishes.

[0427] Input: List sent from the server

[0428] Output: The list displayed to the user

[0429] 4-2. User selection

[0430] The user selects ingredients and dishes from a list of suggestions, for example, chocolate cake.

[0431] Input: User selected data

[0432] Output: Selected ingredients and dish information

[0433] 4-3. Sending selected data

[0434] The device sends information about the selected ingredients, recipe, and dish to the server.

[0435] Input: Selected ingredients, dish information

[0436] Output: Selection data sent to the server

[0437] Step 5: Execute delivery request

[0438] 5-1. Creating a delivery request

[0439] The server generates a delivery request based on the received selection data.

[0440] Input:Selection data

[0441] Output: Generated delivery request information

[0442] 5-2. Confirming your order

[0443] The server uses the delivery service's API to confirm the order, and the confirmation information is sent to the delivery service.

[0444] Input: Delivery request information

[0445] Output: Order confirmation information

[0446] 5-3. Detailed notification

[0447] The server transmits order confirmation information to the terminal, and the terminal notifies the user.

[0448] Input: Order confirmation information

[0449] Output: Detailed notification sent to the device

[0450] Step 6: Order confirmation and tracking

[0451] 6-1. Displaying order information

[0452] The terminal displays the order confirmation information to the user.

[0453] Input: Order confirmation information

[0454] Output: Order confirmation information displayed to the user

[0455] 6-2. Progress notification

[0456] The server works with the delivery service to monitor the delivery progress in real time. As each progress update occurs, the server notifies the device. The device then displays the progress information to the user.

[0457] Input: Delivery progress information

[0458] Output: Progress notification displayed to the user

[0459] The above are the specific processing steps of this system.

[0460] (Application example 2)

[0461] 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."

[0462] Conventional delivery systems make suggestions based on the user's physical condition, food preferences, and allergy information, but do not suggest optimal meals that take into account the user's emotional information. As a result, it is not possible to suggest meals that correspond to the user's mood and emotions, and it is not possible to improve user satisfaction. In addition, there was no suggestion system that linked with real-time emotion recognition, making it difficult to select the optimal meal.

[0463] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: input means for the user to input information about their physical condition, food preferences, and emotional information; emotion recognition means for collecting the user's emotions in real time using voice analysis and face recognition technology and analyzing them using an emotion engine; selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotional information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; order receiving means for accepting a delivery request for the suggested dishes; and collaboration means for coordinating with a delivery service to confirm the order and notify the user of the delivery progress. This enables optimal meal suggestions and delivery requests to be made taking into account the user's physical condition, preferences, and emotional information.

[0464] "Input means" refers to a device or mechanism that allows a user to input information about their physical condition, food preferences, and emotional information into the system.

[0465] "Emotion recognition means" refers to a function or device that uses voice analysis or face recognition technology to collect user emotions in real time and analyzes them using an emotion engine.

[0466] The "selection means" refers to a function or device for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, and emotional information.

[0467] The "suggestion means" refers to a function or device for visually or audibly suggesting selected ingredients, recipes, and dishes to the user.

[0468] The "order receiving means" refers to a function or device that accepts the operations required for the user to request delivery of the selected dish.

[0469] The "cooperation means" refers to a function or device that cooperates with a delivery service to confirm an order and notify the user of the progress of delivery.

[0470] "Ingredients" are raw materials used to prepare a dish, and are selected based on the user's physical condition, food preferences, and allergy information.

[0471] A "recipe" is a manual showing how to cook a dish, suggesting the best ingredients and cooking methods for the user.

[0472] A "dish" is food that is cooked using selected ingredients and served to the user.

[0473] An "emotion engine" is software or algorithms that analyze a user's emotions from voice, facial expressions, text input, etc.

[0474] The "database" is a data storage system for managing and storing information such as a user's physical condition, food preferences, dietary history, and emotional history.

[0475] The "delivery service" is a service that delivers the food selected by the user to a specified location.

[0476] "Progress" is status information that indicates the stage at which the delivery request is at, such as order received, cooking, delivery in progress, or delivery completed.

[0477] An "application program interface (API)" is an interface that allows different software programs to share functions and exchange data.

[0478] In the embodiment of the present invention, the flow of a system for realizing an application example will be specifically shown.

[0479] System Overview

[0480] The system begins with the user entering information about their physical condition, food preferences, and emotions using a device such as a smartphone. The device then uses a camera and microphone to collect the user's emotions in real time and analyzes them using an EmotionEngine (emotion recognition engine). This information is sent to a server, which then queries a FoodDatabase (a database of ingredients and recipes) to select the most suitable ingredients, recipes, and dishes. The system then presents the selected information to the user and accepts a delivery request for the dishes selected by the user. Finally, the system confirms the order using a delivery service API and notifies the user of the progress in real time.

[0481] Program processing overview

[0482] 1. Launch the app and log in

[0483] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account.

[0484] 2. Input of user information and emotion information

[0485] The device asks the user to input their physical condition, food preferences, allergy information, and emotional information. Emotional information is collected in real time using the device's camera and microphone and analyzed by EmotionEngine.

[0486] 3. Data processing on the server

[0487] The server stores the user's physical condition, food preferences, allergy information, and emotional information in a database. It also queries the user's past eating history and emotional history, and searches the Food Database to select the most suitable ingredients, recipes, and dishes.

[0488] 4. Display of suggestions

[0489] The server sends the selected ingredients, recipes, and dishes in list form to the user's terminal and displays the suggestions.

[0490] 5. Executing a delivery request

[0491] The user selects from the suggested dishes and places a delivery request. The server confirms the order using the delivery service API and notifies the device of the details.

[0492] 6. Order Confirmation and Tracking

[0493] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[0494] Hardware and software used

[0495] Hardware: Smartphone (camera, microphone, network connection), server

[0496] Software: EmotionEngine (emotion recognition engine), FoodDatabase (SQL database), DeliveryAPI (delivery service API)

[0497] Specific examples

[0498] For example, consider a case where a user is feeling depressed during the rainy season and wants to eat something sweet. The user launches the app and logs in with LINE. They enter "Physical condition: feeling depressed," "Food preference: sweets," and "Allergies: none." The smartphone's camera and microphone are used to recognize emotions, and the emotional information is analyzed using EmotionEngine. Based on this information, the server makes appropriate suggestions, such as chocolate cake, and requests delivery of the dish selected by the user. The server then confirms the order using the delivery service API and notifies the user of the progress in real time.

[0499] Prompt Sentence Examples

[0500] "If a user says they're feeling down and want something sweet, suggest the best ingredients, recipes, and dishes. Also, offer delivery options."

[0501] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0502] Step 1:

[0503] The user launches the app on their smartphone and logs in by entering their account information on the login screen.

[0504] Input: Account information (ID, password)

[0505] Specific operation: The user taps the app to launch it and enters their LINE or Yahoo! authentication information on the login screen.

[0506] Output: Login success message, transition to the next input screen

[0507] Step 2:

[0508] The terminal prompts the user to enter physical condition, food preferences, allergy information, and emotional information.

[0509] Input: Enter your physical condition, food preferences, and allergy information in the input form

[0510] Specific operation: The user enters information about their physical condition, food preferences, and allergies into an input form. The device's camera and microphone collect the user's facial expressions and voice.

[0511] Output: Input information, emotional data collected in real time

[0512] Step 3:

[0513] The emotional information collected by the device is sent to EmotionEngine for emotional analysis.

[0514] Input: Emotion information (facial expression data, voice data)

[0515] Specific operation: The device calls the EmotionEngine and analyzes the collected emotional information in real time.

[0516] Data processing: Analysis of voice and facial expression data, identification of emotional state (e.g., depressed, happy, etc.)

[0517] Output: Emotional state data as analysis result

[0518] Step 4:

[0519] The terminal transmits information on physical condition, food preferences, allergies, and emotions to the server.

[0520] Input: Physical condition information, food preferences, allergy information, emotional state data

[0521] Specific operation: The device saves the entered data in temporary storage and sends it to the server as an HTTP request.

[0522] Output: Dataset of user information received by the server

[0523] Step 5:

[0524] The server stores the received user information in a database and selects optimal ingredients, recipes, and dishes by referencing the user's past eating history and emotional history.

[0525] Input: User information (physical condition, food preferences, allergies, emotional state), past dietary history, emotional history

[0526] What happens: The server executes a database search query to extract the best ingredients, recipes, and dishes from the FoodDatabase.

[0527] Data operations: performing search queries, filtering and ranking data

[0528] Output: A list of selected ingredients, recipes, and dishes

[0529] Step 6:

[0530] The server sends the selected optimal ingredients, recipes, and dishes to the user's terminal, which then displays the suggestions in list form.

[0531] Input: List of selected ingredients, recipes, and dishes

[0532] Specific operation: The server generates the selection result in JSON format and sends it to the device. The device updates the UI to display the list.

[0533] Output: The list of suggestions displayed on the user's device

[0534] Step 7:

[0535] The user selects the desired dish from the suggested list and places a delivery request.

[0536] Input: User's selected dish

[0537] Specific operation: The user selects the desired dish from the list of suggestions by tapping it. The selected dish information is sent to the server.

[0538] Output: Food selection information

[0539] Step 8:

[0540] The server confirms the order using the delivery service API and notifies the user of the delivery progress.

[0541] Input: Selected dish information, user's delivery address information

[0542] Specific operation: The server calls the delivery service API, sends the order information and confirms the order, collects delivery status information and sends it to the user's device.

[0543] Output: Order confirmation message, delivery progress

[0544] Step 9:

[0545] The terminal will notify the user of order confirmation information and real-time delivery progress.

[0546] Input: Order confirmation message, delivery progress

[0547] Specific behavior: The device receives a notification from the server and displays the information to the user using a notification popup or status bar.

[0548] Output: Delivery confirmation and progress notification to the user

[0549] 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.

[0550] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0551] 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.

[0552] [Second embodiment]

[0553] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0554] 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.

[0555] 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).

[0556] 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.

[0557] 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.

[0558] 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).

[0559] 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.

[0560] 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.

[0561] 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.

[0562] 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.

[0563] 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.

[0564] 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."

[0565] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[0566] System Overview

[0567] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[0568] Program processing overview

[0569] 1. Launch the app and log in

[0570] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[0571] 2. Enter your user information

[0572] The device prompts the user to enter information about their physical condition, food preferences, and allergies, and the information is then sent from the device to the server.

[0573] 3. Proposal Data Generation

[0574] The server stores the user's input information in a database and searches the database to select the most suitable ingredients, recipes, and dishes.

[0575] The server generates the selection results in list format and sends them to the terminal.

[0576] 4. Viewing and selecting suggestions

[0577] The device displays suggested ingredients, recipes, and dishes to the user.

[0578] The user selects their favorite dish from the list.

[0579] 5. Executing a delivery request

[0580] The terminal sends a delivery request for the selected dish to the server.

[0581] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[0582] 6. Order Confirmation and Tracking

[0583] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[0584] Specific examples

[0585] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[0586] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[0587] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[0588] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[0589] 5. The server contacts a nearby delivery service and confirms the order.

[0590] 6. The order details are sent to the user's device and delivery begins.

[0591] The present invention provides a system that allows for the selection of appropriate meals in response to changes in physical condition during pregnancy and can be operated intuitively in a short time, thereby enabling pregnant women to eat comfortably.

[0592] The above is a description of the preferred embodiment of the present invention, which provides details for specifically implementing the present invention based on the content set forth in the claims.

[0593] The processing flow will be explained below.

[0594] Step 1:

[0595] The user launches the app on their smartphone.

[0596] How it works: The user taps the app icon to launch it.

[0597] Step 2:

[0598] The terminal prompts the user to log in.

[0599] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[0600] Step 3:

[0601] The user logs in with LINE or Yahoo!

[0602] Operation details: The user enters their account information using the authentication method they selected and logs in.

[0603] Step 4:

[0604] The device will ask you to enter information about your physical condition, food preferences, and allergies.

[0605] Operation details: The device displays an input form screen and asks the user to enter information.

[0606] Step 5:

[0607] The user inputs information such as physical condition, food preferences, and allergy information.

[0608] Action details: The user fills in the required information in the input form.

[0609] Step 6:

[0610] The terminal transmits the input information to the server.

[0611] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[0612] Step 7:

[0613] The server stores the received user information in a database.

[0614] What happens: The server opens a database connection and saves the user information in the corresponding table.

[0615] Step 8:

[0616] The server searches a database of ingredients, recipes, and dishes.

[0617] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, and allergies.

[0618] Step 9:

[0619] The server generates a list of the selection results and sends it to the terminal.

[0620] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[0621] Step 10:

[0622] The device displays suggested ingredients, recipes, and dishes to the user.

[0623] Operation details: The device receives the suggestion list and displays it on the screen.

[0624] Step 11:

[0625] The user selects their preferred dish from the list of suggestions.

[0626] What it does: The user taps to select one or more dishes from the list.

[0627] Step 12:

[0628] The terminal sends a delivery request to the server.

[0629] Operation details: The device sends a delivery request including the selected dish information to the server.

[0630] Step 13:

[0631] The server connects to the delivery service's API to confirm the order.

[0632] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[0633] Step 14:

[0634] The server notifies the user terminal of the order details.

[0635] Operation details: The server generates order confirmation information and sends it to the user terminal.

[0636] Step 15:

[0637] The terminal displays the order confirmation information to the user.

[0638] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[0639] Step 16:

[0640] The server updates the delivery progress in real time and notifies the device.

[0641] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[0642] Step 17:

[0643] The user checks the delivery status.

[0644] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[0645] The above are the detailed processing steps performed by the system of the present invention.

[0646] Example 1

[0647] 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."

[0648] In recent years, as part of health management, there has been a demand for meal selection based on individual physical condition and food preferences. However, conventional systems require users to collect information themselves and select the optimal ingredients and cooking methods, which takes time and effort. Furthermore, when using delivery services, a separate order is required. Furthermore, to track the progress of delivery after ordering, users must check the individual applications of each service. To solve these problems, a system is needed that automatically selects the optimal ingredients and dishes based on the information entered by the user and provides consistent support right up to delivery.

[0649] 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.

[0650] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a storage means for storing the user's input information, a selection means for selecting optimal ingredients, cooking methods, and dishes based on the stored information, a suggestion means for suggesting the selected ingredients, cooking methods, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, and a linking means for confirming the order using the delivery service's API and notifying the user of the progress of the delivery. This enables users to easily select the meal that is optimal for them, quickly order using the delivery service, and keep track of the progress in real time.

[0651] "User" refers to a person who uses the system to input information about their physical condition and food preferences, and then checks and selects suggested dishes.

[0652] "Input means" refers to a device or interface that allows a user to input information about their physical condition, food preferences, allergies, and the like.

[0653] "Storage means" refers to a device or function for storing information input by a user.

[0654] "Selection means" refers to a device or function that selects optimal ingredients, cooking means, and dishes based on stored user input information.

[0655] The "suggestion means" refers to a device or function for suggesting selected ingredients, cooking means, and dishes to the user.

[0656] "Order receiving means" refers to a device or function for receiving a delivery request for the proposed dishes.

[0657] "Linkage means" refers to a device or function for confirming an order using the delivery service's API and notifying the progress of delivery.

[0658] "Database" refers to an information management system for storing, searching, and analyzing user input information and past meal history.

[0659] "Delivery service" refers to a business that provides a service of delivering food ordered by a user.

[0660] "Delivery progress" refers to the status of each stage until the ordered food is delivered to the user.

[0661] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[0662] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[0663] System Overview

[0664] When a user uses the system, they install and launch an application on their smartphone or computer. When the user enters information about their physical condition and food preferences, that information is sent to the server. The server selects the most suitable ingredients, cooking methods, and dishes from a database based on the user's input, and suggests them to the user. When the user checks the suggestions, selects a specific dish, and requests delivery, the server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[0665] System configuration

[0666] 1. Input Method

[0667] A device or interface that allows users to input information about their physical condition and food preferences. This is implemented on a smartphone or computer application screen.

[0668] 2. Preservation means

[0669] A device or function for saving user-entered information. Information is saved in a database (e.g., MySQL database) on a cloud server.

[0670] 3. Selection method

[0671] A device or function that selects the best ingredients, cooking methods, and dishes based on stored information. Python scripts are used to search the database and parse user information.

[0672] 4. Proposal method

[0673] A device or function for suggesting selected ingredients, cooking methods, and dishes to the user. It generates a list in JSON format and displays it in the user interface.

[0674] 5. Ordering Method

[0675] A device or function for accepting delivery requests for suggested dishes, and sending information about the dishes selected by the user to the server.

[0676] 6. Collaboration Methods

[0677] A device or function that uses the delivery service's API to confirm orders and notify delivery progress. It works in conjunction with delivery services using APIs such as Uber Eats.

[0678] Specific examples

[0679] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[0680] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[0681] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[0682] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[0683] 5. The server contacts a nearby delivery service and confirms the order.

[0684] 6. The order details are sent to the user's device and delivery begins.

[0685] Specific prompt examples

[0686] "If I want to eat something disgusting and sour, please suggest what would be good."

[0687] "They suggested lemon chicken salad, so I ordered it for delivery."

[0688] The present invention provides an environment in which users can easily select meals that suit their physical condition and operate intuitively. This is particularly useful during periods of rapid physical changes such as pregnancy. This allows users to eat comfortably.

[0689] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0690] Step 1: Launch the app and log in

[0691] The user launches the app on their smartphone.

[0692] The device displays the splash screen and provides a login screen. The user enters their LINE or general account information. Input: User's login information. Output: Authentication token.

[0693] The server uses the authentication API to check the entered login information, and if authentication is successful, it generates an authentication token and sends it to the terminal.

[0694] The device receives the authentication token and displays the main screen.

[0695] Step 2: Enter your user information

[0696] The device displays a form for entering information about your physical condition, food preferences, and allergies.

[0697] The user enters "feeling sick" as their physical condition, "sour foods" as their food preference, and allergy information. Input: User's physical condition and preference information. Output: Input information in JSON format.

[0698] The terminal converts the input information into JSON format and sends it to the server.

[0699] Step 3: Save your information

[0700] Parse the JSON format user information received by the server. Input: JSON format user information. Output: Save to database.

[0701] The server stores user information in a MySQL database.

[0702] Step 4: Generate proposal data

[0703] The server starts parsing based on the stored user information. Input: User information stored in the database. Output: A list of suggestions in JSON format.

[0704] The server uses a Python script to select the best ingredients, cooking methods, and dishes based on the user's physical condition and food preferences.

[0705] The server compiles the selection results into a JSON format list and sends it to the terminal.

[0706] Step 5: View and select suggestions

[0707] The device displays the received suggestion list in the UI. Input: Suggestion list sent from the server. Output: Display of suggestion list.

[0708] User taps to select the dish they are interested in from the suggestion list. Input: User selection. Output: Details of the selected dish.

[0709] The device sends information about the selected dish in JSON format to the server.

[0710] Step 6: Execute delivery request

[0711] The server calls the delivery service's API based on the selected dish information. Input: Information about the dish selected by the user. Output: Confirmed order and delivery details.

[0712] The server confirms the order using the delivery service's API and generates delivery progress information.

[0713] The server sends delivery progress information to the terminal.

[0714] Step 7: Order confirmation and tracking

[0715] The terminal notifies the user of the order confirmation details and delivery progress. Input: Delivery progress information sent from the server. Output: Order details and progress notification.

[0716] Monitor delivery status in real time and display status updates to users.

[0717] This is the specific process flow of this system, allowing users to easily select the perfect meal and track the delivery progress.

[0718] (Application example 1)

[0719] 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."

[0720] Conventional food delivery systems have had difficulty proposing individually optimized ingredients, recipes, and dishes based on a user's physical condition and food preferences. They also lacked a means to notify users of the progress of delivery of the proposed dishes in real time, making it difficult to improve user satisfaction.

[0721] 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.

[0722] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information, a suggestion means for suggesting the selected ingredients, recipes, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, a linking means for linking with a delivery service to confirm the order and notify the user of the delivery progress, and a tracking means for notifying the user of the delivery progress in real time, thereby enabling personalized suggestions for dishes tailored to the user's physical condition and preferences and real-time notification of the delivery progress.

[0723] "User" refers to an individual who uses the system by inputting information about their physical condition and food preferences.

[0724] "Physical condition" refers to the user's health condition and any physical symptoms they may be experiencing.

[0725] "Food preference information" refers to data including the user's favorite ingredients, types of cuisine, taste preferences, allergy information, etc.

[0726] "Input means" refers to an interface that allows a user to input information about their physical condition and food preferences into the system.

[0727] The "selection means" refers to a means for selecting optimal ingredients, recipes, and dishes based on information input by the user.

[0728] "Proposal means" refers to a means for presenting selected ingredients, recipes, and dishes to the user.

[0729] "Means for receiving orders" refers to the means for accepting delivery requests for the proposed dishes.

[0730] "Means of collaboration" refers to the means of collaborating with a delivery service to confirm an order and notify the delivery progress.

[0731] "Tracking Method" means a method selected by the User that notifies the User of delivery progress in real time.

[0732] "Delivery service" refers to a service that delivers food or products to a specified location.

[0733] "API" stands for Application Programming Interface and refers to the rules for exchanging functions between different software.

[0734] "Server" refers to a computer system that stores and analyzes data.

[0735] A "database" refers to a structured collection of information for efficient storage and retrieval of data.

[0736] That's all.

[0737] To put the present invention into practice, an application is installed on the user's smartphone or computer, and the following process is performed.

[0738] System Overview

[0739] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress. A tracking method is also included to notify the user of the delivery progress of their selected order in real time.

[0740] Program processing overview

[0741] This section explains the roles of servers and user terminals, as well as the hardware and software they use.

[0742] 1. Launch the app and log in

[0743] The user launches the app on their smartphone and logs in using their social networking account on the login screen. Firebase Authentication is used for logging in. The device verifies the login information and issues an authentication token.

[0744] 2. Enter your user information

[0745] The terminal asks the user to enter information about their physical condition, food preferences, and allergies. The user enters the information into a form and sends it to the server. React Native is used for the input form. The input data passes validation before being sent to the server.

[0746] 3. Proposal Data Generation

[0747] The server stores the user's input information in a database and searches the database to select the best ingredients, recipes, and dishes. This is done using Node.js and MongoDB. The server matches the user data with the database and generates a list of suggestions.

[0748] 4. Viewing and selecting suggestions

[0749] The device displays the suggested ingredients, recipes, and dishes to the user. The user selects the dish they like from the list. This list display is done using React Native. The selected dish data is sent to the server.

[0750] 5. Executing a delivery request

[0751] The device sends a delivery request for the selected food to the server. The server confirms the order using the delivery service's API. Axios is used for API communication. Order details are sent to the delivery service.

[0752] 6. Order Confirmation and Tracking

[0753] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time, using the Firebase Realtime Database. The delivery status is periodically checked and notifications are sent.

[0754] Specific examples

[0755] 1. If a user is feeling unwell and wants to eat something sour, they launch the app and log in with their social media account.

[0756] 2. Type "I want to eat something sour."

[0757] 3. The server suggests dishes using lemon or plum, and "Lemon Chicken Salad" is displayed.

[0758] 4. The user selects the suggested dish and places a delivery request.

[0759] 5. The server contacts a nearby delivery service and confirms the order.

[0760] 6. Order details and progress are notified in real time to the user's smartphone.

[0761] Prompt Sentence Examples

[0762] User: "I want to eat something sour, but my stomach is upset."

[0763] App: "Would you like some lemon chicken salad? Would you like it delivered?"

[0764] This will enable personalized food suggestions tailored to the user's physical condition and preferences, as well as real-time notifications of delivery progress.

[0765] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0766] The processing flow of the program of the system that realizes the application example will be specifically explained below, broken down into steps.

[0767] Step 1:

[0768] A user launches the application on their device and logs in using their social network account on the login screen. The user's social network account information is required as input. The device verifies the login information using Firebase Authentication and generates an authentication token. The authentication token is obtained as output.

[0769] Step 2:

[0770] After logging in, the user enters information about their physical condition, food preferences, and allergies on the terminal. The information the user enters into the form is required as input. The input form created using React Native validates the data and sends it to the server. The output is user information that has passed validation.

[0771] Step 3:

[0772] The server receives user input information and stores it in a database. The submitted user information is required as input. The server uses Node.js to store the information in a database (MongoDB). The output is the user information stored in the database.

[0773] Step 4:

[0774] The server searches the database and selects the best ingredients, recipes, and dishes based on the user's input. As input, the server requires user information and dish information from the database. The server uses a matching algorithm to generate the best suggestions list. As output, the suggestions list is obtained and sent to the user's device.

[0775] Step 5:

[0776] The device displays suggested ingredients, recipes, and dishes to the user. As input, it requires a list of suggestions sent from the server. It displays the information in a list format using React Native. The user selects their favorite dish, and the selected dish information is obtained as output.

[0777] Step 6:

[0778] The device sends a delivery request to the server for the dish selected by the user. The user-selected dish information is required as input. The device sends the selected dish data to the server, and the server confirms the order through the delivery service's API. The confirmed order information is obtained as output.

[0779] Step 7:

[0780] The server confirms the order using the delivery service's API. As input, it requires the selected dish information and the user's delivery information. The server uses the Axios library to send the order information to the delivery service. As output, the delivery is initiated.

[0781] Step 8:

[0782] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time. The input requires order confirmation information and delivery progress information sent from the server. The Firebase Realtime Database is used to periodically check the progress and notify them. The output provides information that allows the user to check the delivery progress in real time.

[0783] The above is the flow of specific processing steps of the system that realizes the application example.

[0784] 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.

[0785] The system of the present invention recognizes the user's physical condition, food preferences, and emotions, suggests optimal ingredients, recipes, and dishes, and works in conjunction with delivery services. Specifically, the process is carried out as follows.

[0786] System Overview

[0787] When a user uses the system, they launch an application on their smartphone or computer and input information about their physical condition, food preferences, allergies, and emotional information recognized by the emotion engine from voice, facial expressions, and text input. This information is sent to the server, which then selects optimal ingredients, recipes, and dishes from a database based on the user's input, including past eating history and emotional history, and suggests them to the user. The user then selects the suggested ingredients and dishes and requests delivery. The server then connects with the delivery service, confirms the order, and notifies the user of the progress of the delivery.

[0788] Program processing overview

[0789] 1. Launch the app and log in

[0790] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[0791] 2. Input of user information and emotion information

[0792] The device asks for input of physical condition, food preferences, allergy information, and emotions recognized by the emotion engine from voice, facial expressions, and text input.

[0793] The user enters this information and the terminal transmits the data to the server.

[0794] 3. Proposal Data Generation

[0795] The server stores the received user information in a database, and searches the database based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history to select optimal ingredients, recipes, and dishes.

[0796] The server generates the selection results in list format and sends them to the terminal.

[0797] 4. Viewing and selecting suggestions

[0798] The device displays suggested ingredients, recipes, and dishes to the user.

[0799] The user selects their favorite dish from the list.

[0800] 5. Executing a delivery request

[0801] The terminal sends a delivery request for the selected dish to the server.

[0802] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[0803] 6. Order Confirmation and Tracking

[0804] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[0805] Specific examples

[0806] 1. The user thinks, "I'm feeling down and I want to eat something sweet," and launches the app.

[0807] 2. The user logs in to LINE and enters their physical condition, the keyword "sweets," and the "depressed mood" information recognized by the emotion engine.

[0808] 3. The server analyzes the user's past data, input information, and emotional information, and suggests recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered.

[0809] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[0810] 5. The server contacts the delivery service and confirms the order.

[0811] 6. The order details are sent to the user's device and delivery begins.

[0812] The present invention provides a system that enables appropriate meal selection in response to changes in physical condition and emotions during pregnancy, and can provide a comfortable dining experience by making suggestions that match the user's preferences and mood.

[0813] The processing flow will be explained below.

[0814] Step 1:

[0815] The user launches the app on their smartphone.

[0816] What happens: A user launches an app by tapping its icon.

[0817] Step 2:

[0818] The terminal prompts the user to log in.

[0819] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[0820] Step 3:

[0821] The user logs in with LINE or Yahoo!

[0822] Operation details: The user enters their account information using the authentication method they selected and logs in.

[0823] Step 4:

[0824] The device asks you to enter information about your physical condition, food preferences, allergies, and emotions.

[0825] Operation details: The device displays an input form screen and prompts the user to enter information. The emotion engine also recognizes emotions from the user's voice, facial expressions, and text input.

[0826] Step 5:

[0827] The user inputs information about their physical condition, food preferences, allergy information, and emotional information.

[0828] Operation details: The user fills in the required information in the input form. Emotional information is automatically recognized from voice, facial expressions, text input, etc.

[0829] Step 6:

[0830] The terminal transmits the input information to the server.

[0831] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[0832] Step 7:

[0833] The server stores the received user information in a database.

[0834] What happens: The server opens a database connection and saves the user information in the corresponding table.

[0835] Step 8:

[0836] The server searches a database of ingredients, recipes and dishes, taking emotional information into account.

[0837] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, emotions and allergy information.

[0838] Step 9:

[0839] The server generates a list of the selection results and sends it to the terminal.

[0840] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[0841] Step 10:

[0842] The device displays suggested ingredients, recipes, and dishes to the user.

[0843] Operation details: The device receives the suggestion list and displays it on the screen.

[0844] Step 11:

[0845] The user selects their preferred dish from the list of suggestions.

[0846] What it does: The user taps to select one or more dishes from the list.

[0847] Step 12:

[0848] The terminal sends a delivery request to the server.

[0849] Operation details: The device sends a delivery request including the selected dish information to the server.

[0850] Step 13:

[0851] The server connects to the delivery service's API to confirm the order.

[0852] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[0853] Step 14:

[0854] The server notifies the user terminal of the order details.

[0855] Operation details: The server generates order confirmation information and sends it to the user terminal.

[0856] Step 15:

[0857] The terminal displays the order confirmation information to the user.

[0858] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[0859] Step 16:

[0860] The server updates the delivery progress in real time and notifies the device.

[0861] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[0862] Step 17:

[0863] The user checks the delivery status.

[0864] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[0865] The above are the detailed processing steps performed by the system of the present invention.

[0866] Example 2

[0867] 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."

[0868] Conventional ingredient and dish recommendation systems make recommendations based solely on a user's physical condition and food preferences, making it difficult to make recommendations that reflect the user's emotions. While utilizing a user's past meal history can provide more appropriate recommendations, it is difficult to make meal recommendations that reflect the user's mood because the history management does not include emotional information. The present invention solves these problems by providing a system that makes it possible to recommend and request delivery of appropriate ingredients, recipes, and dishes based on a user's physical condition, food preferences, and even emotions.

[0869] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0870] In this invention, the server includes an input means for the user to input information about their physical condition and food preferences, an emotion recognition means for analyzing the input emotion information, and a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotion information, thereby making it possible to suggest meals that take into account the user's emotions in addition to their physical condition and food preferences.

[0871] The "input means" is an interface that allows the user to input information about their physical condition and food preferences into the system.

[0872] "Emotion recognition means" is a technology that analyzes and recognizes emotional information from the user's input voice, facial expressions, etc.

[0873] The "selection means" is a function for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preference information, and emotional information.

[0874] The "suggestion means" is a function for presenting selected ingredients, recipes, and dishes to the user.

[0875] The "order receiving means" is a system for receiving a delivery request when a user makes a delivery request for the proposed dish.

[0876] The "linking means" is a technology that links with a delivery service to confirm an order and notify the user of the progress of the delivery.

[0877] The "database" is a storage system for storing user input information, past meal history, and emotional history.

[0878] An "API" is an application programming interface that allows different systems to communicate with each other and utilize their functions.

[0879] The system of the present invention proposes optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, and emotional information, and works in conjunction with delivery services. Specific embodiments of this system are described in detail below.

[0880] 1. Program Generation

[0881] The system's program is developed using Python. It uses SQLite for database operations and a generative AI model (such as OpenAI's emotion recognition model) for emotion recognition. It also uses common APIs such as Zinc API for integration with delivery services.

[0882] 2. Program Processing Overview

[0883] The processing outline of this system is as follows.

[0884] 1. Launch the app and log in

[0885] The user launches the app on their smartphone and logs in using a regular account (such as a LINE or Yahoo! account) on the login screen. The device sends the login information to the server, which then performs the authentication process.

[0886] 2. Input of user information and emotion information

[0887] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[0888] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data. The input information and emotional data are sent from the device to the server.

[0889] 3. Proposal Data Generation

[0890] The server stores the received user information in a database, and then searches the database to select optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history.

[0891] The server generates a list of selected ingredients, recipes, and dishes and sends it to the terminal.

[0892] 4. Viewing and selecting suggestions

[0893] The terminal displays a list of suggested ingredients, recipes, and dishes for the user to choose from.

[0894] 5. Executing a delivery request

[0895] The device sends a delivery request for the selected food to the server, which then uses the delivery service's API to confirm the order and notify the user of the delivery details.

[0896] 6. Order Confirmation and Tracking

[0897] The terminal displays order confirmation information to the user, and the server monitors the delivery progress in real time and sends updates to the terminal.

[0898] 3. Specific Examples

[0899] Specific examples are shown below.

[0900] 1. If a user feels depressed and wants to eat something sweet, they launch the app and log in with their LINE account.

[0901] 2. The user inputs their physical condition, the keyword "sweets," and the information about "depressed mood" that the emotion engine recognizes.

[0902] 3. The server analyzes the user's past data, input information, and emotional information to suggest recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered. A list is displayed to the user.

[0903] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[0904] 5. The server contacts the delivery service to confirm the order. The user is notified of the delivery progress.

[0905] 4. Examples of prompts

[0906] Below is an example of a prompt sentence to input to the generative AI model.

[0907] 1. Emotion recognition prompt:

[0908] "The user inputs, 'I'm tired from work today and I want to eat something sweet.' Please determine this emotion."

[0909] 2. Prompt for the best dish suggestion:

[0910] "The user's physical condition is 'tired,' their preference is 'sweets,' and their emotion is 'depressed.' Please suggest the best recipe based on this information."

[0911] As described above, the present invention realizes optimal meal suggestions and delivery requests based on the user's physical condition, food preferences, and even emotional information.

[0912] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0913] Step 1: Launch the app and log in

[0914] 1-1. Launching the app

[0915] The user taps the app on their smartphone to launch it, and the app's main screen appears.

[0916] Input: None

[0917] Output: Main screen of the app

[0918] 1-2. Login

[0919] The device displays a login screen, and the user selects a generic account (e.g., LINE or Yahoo! account), enters authentication information, and presses the login button.

[0920] The authentication information is sent from the terminal to the server.

[0921] The server performs user authentication based on the received authentication information, and if successful, loads the user's past data and sends a login completion message to the terminal.

[0922] Input: User credentials

[0923] Output: Login completion message, user's past data

[0924] Step 2: Enter user information and emotion information

[0925] 2-1. Displaying the information input form

[0926] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[0927] Input: None

[0928] Output: Information input form

[0929] 2-2. Entering information

[0930] The user inputs information about their physical condition, food preferences, and allergies, as well as voice and facial expressions.

[0931] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data.

[0932] The input information and emotion data are transmitted from the terminal to the server.

[0933] Input: User's physical condition information, food preferences, allergy information, voice and facial expression data

[0934] Data processing: Voice and facial expression analysis using generative AI models

[0935] Output: Analyzed emotion data, user-entered physical condition information, food preferences, and allergy information

[0936] Step 3: Generate proposal data

[0937] 3-1. Data storage

[0938] The server stores the received user information in a database, including information on physical condition, food preferences, allergies, and emotional data.

[0939] Input: User information, analyzed emotion data

[0940] Output: Information stored in the database

[0941] 3-2. Data analysis and search

[0942] The server performs analysis based on the stored data and past eating and emotional history.

[0943] It uses generative AI models to find the best ingredients, recipes, and dishes for a user's emotions and physical condition.

[0944] Compile a list of selected ingredients, recipes, and dishes.

[0945] Input: User information extracted from the database, past meal history, emotional history

[0946] Data processing: Analysis with generative AI models

[0947] Output: A list of selected ingredients, recipes, and dishes

[0948] 3-3. Sending proposal data

[0949] The server transmits the generated list to the terminal.

[0950] Input: Selected list

[0951] Output: List sent to terminal

[0952] Step 4: View and select suggestions

[0953] 4-1. Display of proposed data

[0954] The terminal displays the received list to the user, which includes a list of ingredients, recipes, and dishes.

[0955] Input: List sent from the server

[0956] Output: The list displayed to the user

[0957] 4-2. User selection

[0958] The user selects ingredients and dishes from a list of suggestions, for example, chocolate cake.

[0959] Input: User selected data

[0960] Output: Selected ingredients and dish information

[0961] 4-3. Sending selected data

[0962] The device sends information about the selected ingredients, recipe, and dish to the server.

[0963] Input: Selected ingredients, dish information

[0964] Output: Selection data sent to the server

[0965] Step 5: Execute delivery request

[0966] 5-1. Creating a delivery request

[0967] The server generates a delivery request based on the received selection data.

[0968] Input:Selection data

[0969] Output: Generated delivery request information

[0970] 5-2. Confirming your order

[0971] The server uses the delivery service's API to confirm the order, and the confirmation information is sent to the delivery service.

[0972] Input: Delivery request information

[0973] Output: Order confirmation information

[0974] 5-3. Detailed notification

[0975] The server transmits order confirmation information to the terminal, and the terminal notifies the user.

[0976] Input: Order confirmation information

[0977] Output: Detailed notification sent to the device

[0978] Step 6: Order confirmation and tracking

[0979] 6-1. Displaying order information

[0980] The terminal displays the order confirmation information to the user.

[0981] Input: Order confirmation information

[0982] Output: Order confirmation information displayed to the user

[0983] 6-2. Progress notification

[0984] The server works with the delivery service to monitor the delivery progress in real time. As each progress update occurs, the server notifies the device. The device then displays the progress information to the user.

[0985] Input: Delivery progress information

[0986] Output: Progress notification displayed to the user

[0987] The above are the specific processing steps of this system.

[0988] (Application example 2)

[0989] 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."

[0990] Conventional delivery systems make suggestions based on the user's physical condition, food preferences, and allergy information, but do not suggest optimal meals that take into account the user's emotional information. As a result, it is not possible to suggest meals that correspond to the user's mood and emotions, and it is not possible to improve user satisfaction. In addition, there was no suggestion system that linked with real-time emotion recognition, making it difficult to select the optimal meal.

[0991] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: input means for the user to input information about their physical condition, food preferences, and emotional information; emotion recognition means for collecting the user's emotions in real time using voice analysis and face recognition technology and analyzing them using an emotion engine; selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotional information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; order receiving means for accepting a delivery request for the suggested dishes; and collaboration means for coordinating with a delivery service to confirm the order and notify the user of the delivery progress. This enables optimal meal suggestions and delivery requests to be made taking into account the user's physical condition, preferences, and emotional information.

[0992] "Input means" refers to a device or mechanism that allows a user to input information about their physical condition, food preferences, and emotional information into the system.

[0993] "Emotion recognition means" refers to a function or device that uses voice analysis or face recognition technology to collect user emotions in real time and analyzes them using an emotion engine.

[0994] The "selection means" refers to a function or device for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, and emotional information.

[0995] The "suggestion means" refers to a function or device for visually or audibly suggesting selected ingredients, recipes, and dishes to the user.

[0996] The "order receiving means" refers to a function or device that accepts the operations required for the user to request delivery of the selected dish.

[0997] The "cooperation means" refers to a function or device that cooperates with a delivery service to confirm an order and notify the user of the progress of delivery.

[0998] "Ingredients" are raw materials used to prepare a dish, and are selected based on the user's physical condition, food preferences, and allergy information.

[0999] A "recipe" is a manual showing how to cook a dish, suggesting the best ingredients and cooking methods for the user.

[1000] A "dish" is food that is cooked using selected ingredients and served to the user.

[1001] An "emotion engine" is software or algorithms that analyze a user's emotions from voice, facial expressions, text input, etc.

[1002] The "database" is a data storage system for managing and storing information such as a user's physical condition, food preferences, dietary history, and emotional history.

[1003] The "delivery service" is a service that delivers the food selected by the user to a specified location.

[1004] "Progress" is status information that indicates the stage at which the delivery request is at, such as order received, cooking, delivery in progress, or delivery completed.

[1005] An "application program interface (API)" is an interface that allows different software programs to share functions and exchange data.

[1006] In the embodiment of the present invention, the flow of a system for realizing an application example will be specifically shown.

[1007] System Overview

[1008] The system begins with the user entering information about their physical condition, food preferences, and emotions using a device such as a smartphone. The device then uses a camera and microphone to collect the user's emotions in real time and analyzes them using an EmotionEngine (emotion recognition engine). This information is sent to a server, which then queries a FoodDatabase (a database of ingredients and recipes) to select the most suitable ingredients, recipes, and dishes. The system then presents the selected information to the user and accepts a delivery request for the dishes selected by the user. Finally, the system confirms the order using a delivery service API and notifies the user of the progress in real time.

[1009] Program processing overview

[1010] 1. Launch the app and log in

[1011] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account.

[1012] 2. Input of user information and emotion information

[1013] The device asks the user to input their physical condition, food preferences, allergy information, and emotional information. Emotional information is collected in real time using the device's camera and microphone and analyzed by EmotionEngine.

[1014] 3. Data processing on the server

[1015] The server stores the user's physical condition, food preferences, allergy information, and emotional information in a database. It also queries the user's past eating history and emotional history, and searches the Food Database to select the most suitable ingredients, recipes, and dishes.

[1016] 4. Display of suggestions

[1017] The server sends the selected ingredients, recipes, and dishes in list form to the user's terminal and displays the suggestions.

[1018] 5. Executing a delivery request

[1019] The user selects from the suggested dishes and places a delivery request. The server confirms the order using the delivery service API and notifies the device of the details.

[1020] 6. Order Confirmation and Tracking

[1021] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1022] Hardware and software used

[1023] Hardware: Smartphone (camera, microphone, network connection), server

[1024] Software: EmotionEngine (emotion recognition engine), FoodDatabase (SQL database), DeliveryAPI (delivery service API)

[1025] Specific examples

[1026] For example, consider a case where a user is feeling depressed during the rainy season and wants to eat something sweet. The user launches the app and logs in with LINE. They enter "Physical condition: feeling depressed," "Food preference: sweets," and "Allergies: none." The smartphone's camera and microphone are used to recognize emotions, and the emotional information is analyzed using EmotionEngine. Based on this information, the server makes appropriate suggestions, such as chocolate cake, and requests delivery of the dish selected by the user. The server then confirms the order using the delivery service API and notifies the user of the progress in real time.

[1027] Prompt Sentence Examples

[1028] "If a user says they're feeling down and want something sweet, suggest the best ingredients, recipes, and dishes. Also, offer delivery options."

[1029] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1030] Step 1:

[1031] The user launches the app on their smartphone and logs in by entering their account information on the login screen.

[1032] Input: Account information (ID, password)

[1033] Specific operation: The user taps the app to launch it and enters their LINE or Yahoo! authentication information on the login screen.

[1034] Output: Login success message, transition to the next input screen

[1035] Step 2:

[1036] The terminal prompts the user to enter physical condition, food preferences, allergy information, and emotional information.

[1037] Input: Enter your physical condition, food preferences, and allergy information in the input form

[1038] Specific operation: The user enters information about their physical condition, food preferences, and allergies into an input form. The device's camera and microphone collect the user's facial expressions and voice.

[1039] Output: Input information, emotional data collected in real time

[1040] Step 3:

[1041] The emotional information collected by the device is sent to EmotionEngine for emotional analysis.

[1042] Input: Emotion information (facial expression data, voice data)

[1043] Specific operation: The device calls the EmotionEngine and analyzes the collected emotional information in real time.

[1044] Data processing: Analysis of voice and facial expression data, identification of emotional state (e.g., depressed, happy, etc.)

[1045] Output: Emotional state data as analysis result

[1046] Step 4:

[1047] The terminal transmits information on physical condition, food preferences, allergies, and emotions to the server.

[1048] Input: Physical condition information, food preferences, allergy information, emotional state data

[1049] Specific operation: The device saves the entered data in temporary storage and sends it to the server as an HTTP request.

[1050] Output: Dataset of user information received by the server

[1051] Step 5:

[1052] The server stores the received user information in a database and selects optimal ingredients, recipes, and dishes by referencing the user's past eating history and emotional history.

[1053] Input: User information (physical condition, food preferences, allergies, emotional state), past dietary history, emotional history

[1054] What happens: The server executes a database search query to extract the best ingredients, recipes, and dishes from the FoodDatabase.

[1055] Data operations: performing search queries, filtering and ranking data

[1056] Output: A list of selected ingredients, recipes, and dishes

[1057] Step 6:

[1058] The server sends the selected optimal ingredients, recipes, and dishes to the user's terminal, which then displays the suggestions in list form.

[1059] Input: List of selected ingredients, recipes, and dishes

[1060] Specific operation: The server generates the selection result in JSON format and sends it to the device. The device updates the UI to display the list.

[1061] Output: The list of suggestions displayed on the user's device

[1062] Step 7:

[1063] The user selects the desired dish from the suggested list and places a delivery request.

[1064] Input: User's selected dish

[1065] Specific operation: The user selects the desired dish from the list of suggestions by tapping it. The selected dish information is sent to the server.

[1066] Output: Food selection information

[1067] Step 8:

[1068] The server confirms the order using the delivery service API and notifies the user of the delivery progress.

[1069] Input: Selected dish information, user's delivery address information

[1070] Specific operation: The server calls the delivery service API, sends the order information and confirms the order, collects delivery status information and sends it to the user's device.

[1071] Output: Order confirmation message, delivery progress

[1072] Step 9:

[1073] The terminal will notify the user of order confirmation information and real-time delivery progress.

[1074] Input: Order confirmation message, delivery progress

[1075] Specific behavior: The device receives a notification from the server and displays the information to the user using a notification popup or status bar.

[1076] Output: Delivery confirmation and progress notification to the user

[1077] 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.

[1078] 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.

[1079] 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.

[1080] [Third embodiment]

[1081] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1082] 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.

[1083] 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).

[1084] 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.

[1085] 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.

[1086] 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).

[1087] 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.

[1088] 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.

[1089] 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.

[1090] 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.

[1091] 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.

[1092] 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."

[1093] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[1094] System Overview

[1095] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[1096] Program processing overview

[1097] 1. Launch the app and log in

[1098] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[1099] 2. Enter your user information

[1100] The device prompts the user to enter information about their physical condition, food preferences, and allergies, and the information is then sent from the device to the server.

[1101] 3. Proposal Data Generation

[1102] The server stores the user's input information in a database and searches the database to select the most suitable ingredients, recipes, and dishes.

[1103] The server generates the selection results in list format and sends them to the terminal.

[1104] 4. Viewing and selecting suggestions

[1105] The device displays suggested ingredients, recipes, and dishes to the user.

[1106] The user selects their favorite dish from the list.

[1107] 5. Executing a delivery request

[1108] The terminal sends a delivery request for the selected dish to the server.

[1109] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[1110] 6. Order Confirmation and Tracking

[1111] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1112] Specific examples

[1113] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[1114] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[1115] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[1116] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[1117] 5. The server contacts a nearby delivery service and confirms the order.

[1118] 6. The order details are sent to the user's device and delivery begins.

[1119] The present invention provides a system that allows for the selection of appropriate meals in response to changes in physical condition during pregnancy and can be operated intuitively in a short time, thereby enabling pregnant women to eat comfortably.

[1120] The above is a description of the preferred embodiment of the present invention, which provides details for specifically implementing the present invention based on the content set forth in the claims.

[1121] The processing flow will be explained below.

[1122] Step 1:

[1123] The user launches the app on their smartphone.

[1124] How it works: The user taps the app icon to launch it.

[1125] Step 2:

[1126] The terminal prompts the user to log in.

[1127] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[1128] Step 3:

[1129] The user logs in with LINE or Yahoo!

[1130] Operation details: The user enters their account information using the authentication method they selected and logs in.

[1131] Step 4:

[1132] The device will ask you to enter information about your physical condition, food preferences, and allergies.

[1133] Operation details: The device displays an input form screen and asks the user to enter information.

[1134] Step 5:

[1135] The user inputs information such as physical condition, food preferences, and allergy information.

[1136] Action details: The user fills in the required information in the input form.

[1137] Step 6:

[1138] The terminal transmits the input information to the server.

[1139] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[1140] Step 7:

[1141] The server stores the received user information in a database.

[1142] What happens: The server opens a database connection and saves the user information in the corresponding table.

[1143] Step 8:

[1144] The server searches a database of ingredients, recipes, and dishes.

[1145] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, and allergies.

[1146] Step 9:

[1147] The server generates a list of the selection results and sends it to the terminal.

[1148] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[1149] Step 10:

[1150] The device displays suggested ingredients, recipes, and dishes to the user.

[1151] Operation details: The device receives the suggestion list and displays it on the screen.

[1152] Step 11:

[1153] The user selects their preferred dish from the list of suggestions.

[1154] What it does: The user taps to select one or more dishes from the list.

[1155] Step 12:

[1156] The terminal sends a delivery request to the server.

[1157] Operation details: The device sends a delivery request including the selected dish information to the server.

[1158] Step 13:

[1159] The server connects to the delivery service's API to confirm the order.

[1160] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[1161] Step 14:

[1162] The server notifies the user terminal of the order details.

[1163] Operation details: The server generates order confirmation information and sends it to the user terminal.

[1164] Step 15:

[1165] The terminal displays the order confirmation information to the user.

[1166] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[1167] Step 16:

[1168] The server updates the delivery progress in real time and notifies the device.

[1169] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[1170] Step 17:

[1171] The user checks the delivery status.

[1172] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[1173] The above are the detailed processing steps performed by the system of the present invention.

[1174] Example 1

[1175] 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."

[1176] In recent years, as part of health management, there has been a demand for meal selection based on individual physical condition and food preferences. However, conventional systems require users to collect information themselves and select the optimal ingredients and cooking methods, which takes time and effort. Furthermore, when using delivery services, a separate order is required. Furthermore, to track the progress of delivery after ordering, users must check the individual applications of each service. To solve these problems, a system is needed that automatically selects the optimal ingredients and dishes based on the information entered by the user and provides consistent support right up to delivery.

[1177] 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.

[1178] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a storage means for storing the user's input information, a selection means for selecting optimal ingredients, cooking methods, and dishes based on the stored information, a suggestion means for suggesting the selected ingredients, cooking methods, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, and a linking means for confirming the order using the delivery service's API and notifying the user of the progress of the delivery. This enables users to easily select the meal that is optimal for them, quickly order using the delivery service, and keep track of the progress in real time.

[1179] "User" refers to a person who uses the system to input information about their physical condition and food preferences, and then checks and selects suggested dishes.

[1180] "Input means" refers to a device or interface that allows a user to input information about their physical condition, food preferences, allergies, and the like.

[1181] "Storage means" refers to a device or function for storing information input by a user.

[1182] "Selection means" refers to a device or function that selects optimal ingredients, cooking means, and dishes based on stored user input information.

[1183] The "suggestion means" refers to a device or function for suggesting selected ingredients, cooking means, and dishes to the user.

[1184] "Order receiving means" refers to a device or function for receiving a delivery request for the proposed dishes.

[1185] "Linkage means" refers to a device or function for confirming an order using the delivery service's API and notifying the progress of delivery.

[1186] "Database" refers to an information management system for storing, searching, and analyzing user input information and past meal history.

[1187] "Delivery service" refers to a business that provides a service of delivering food ordered by a user.

[1188] "Delivery progress" refers to the status of each stage until the ordered food is delivered to the user.

[1189] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[1190] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[1191] System Overview

[1192] When a user uses the system, they install and launch an application on their smartphone or computer. When the user enters information about their physical condition and food preferences, that information is sent to the server. The server selects the most suitable ingredients, cooking methods, and dishes from a database based on the user's input, and suggests them to the user. When the user checks the suggestions, selects a specific dish, and requests delivery, the server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[1193] System configuration

[1194] 1. Input Method

[1195] A device or interface that allows users to input information about their physical condition and food preferences. This is implemented on a smartphone or computer application screen.

[1196] 2. Preservation means

[1197] A device or function for saving user-entered information. Information is saved in a database (e.g., MySQL database) on a cloud server.

[1198] 3. Selection method

[1199] A device or function that selects the best ingredients, cooking methods, and dishes based on stored information. Python scripts are used to search the database and parse user information.

[1200] 4. Proposal method

[1201] A device or function for suggesting selected ingredients, cooking methods, and dishes to the user. It generates a list in JSON format and displays it in the user interface.

[1202] 5. Ordering Method

[1203] A device or function for accepting delivery requests for suggested dishes, and sending information about the dishes selected by the user to the server.

[1204] 6. Collaboration Methods

[1205] A device or function that uses the delivery service's API to confirm orders and notify delivery progress. It works in conjunction with delivery services using APIs such as Uber Eats.

[1206] Specific examples

[1207] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[1208] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[1209] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[1210] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[1211] 5. The server contacts a nearby delivery service and confirms the order.

[1212] 6. The order details are sent to the user's device and delivery begins.

[1213] Specific prompt examples

[1214] "If I want to eat something disgusting and sour, please suggest what would be good."

[1215] "They suggested lemon chicken salad, so I ordered it for delivery."

[1216] The present invention provides an environment in which users can easily select meals that suit their physical condition and operate intuitively. This is particularly useful during periods of rapid physical changes such as pregnancy. This allows users to eat comfortably.

[1217] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1218] Step 1: Launch the app and log in

[1219] The user launches the app on their smartphone.

[1220] The device displays the splash screen and provides a login screen. The user enters their LINE or general account information. Input: User's login information. Output: Authentication token.

[1221] The server uses the authentication API to check the entered login information, and if authentication is successful, it generates an authentication token and sends it to the terminal.

[1222] The device receives the authentication token and displays the main screen.

[1223] Step 2: Enter your user information

[1224] The device displays a form for entering information about your physical condition, food preferences, and allergies.

[1225] The user enters "feeling sick" as their physical condition, "sour foods" as their food preference, and allergy information. Input: User's physical condition and preference information. Output: Input information in JSON format.

[1226] The terminal converts the input information into JSON format and sends it to the server.

[1227] Step 3: Save your information

[1228] Parse the JSON format user information received by the server. Input: JSON format user information. Output: Save to database.

[1229] The server stores user information in a MySQL database.

[1230] Step 4: Generate proposal data

[1231] The server starts parsing based on the stored user information. Input: User information stored in the database. Output: A list of suggestions in JSON format.

[1232] The server uses a Python script to select the best ingredients, cooking methods, and dishes based on the user's physical condition and food preferences.

[1233] The server compiles the selection results into a JSON format list and sends it to the terminal.

[1234] Step 5: View and select suggestions

[1235] The device displays the received suggestion list in the UI. Input: Suggestion list sent from the server. Output: Display of suggestion list.

[1236] User taps to select the dish they are interested in from the suggestion list. Input: User selection. Output: Details of the selected dish.

[1237] The device sends information about the selected dish in JSON format to the server.

[1238] Step 6: Execute delivery request

[1239] The server calls the delivery service's API based on the selected dish information. Input: Information about the dish selected by the user. Output: Confirmed order and delivery details.

[1240] The server confirms the order using the delivery service's API and generates delivery progress information.

[1241] The server sends delivery progress information to the terminal.

[1242] Step 7: Order confirmation and tracking

[1243] The terminal notifies the user of the order confirmation details and delivery progress. Input: Delivery progress information sent from the server. Output: Order details and progress notification.

[1244] Monitor delivery status in real time and display status updates to users.

[1245] This is the specific process flow of this system, allowing users to easily select the perfect meal and track the delivery progress.

[1246] (Application example 1)

[1247] 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."

[1248] Conventional food delivery systems have had difficulty proposing individually optimized ingredients, recipes, and dishes based on a user's physical condition and food preferences. They also lacked a means to notify users of the progress of delivery of the proposed dishes in real time, making it difficult to improve user satisfaction.

[1249] 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.

[1250] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information, a suggestion means for suggesting the selected ingredients, recipes, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, a linking means for linking with a delivery service to confirm the order and notify the user of the delivery progress, and a tracking means for notifying the user of the delivery progress in real time, thereby enabling personalized suggestions for dishes tailored to the user's physical condition and preferences and real-time notification of the delivery progress.

[1251] "User" refers to an individual who uses the system by inputting information about their physical condition and food preferences.

[1252] "Physical condition" refers to the user's health condition and any physical symptoms they may be experiencing.

[1253] "Food preference information" refers to data including the user's favorite ingredients, types of cuisine, taste preferences, allergy information, etc.

[1254] "Input means" refers to an interface that allows a user to input information about their physical condition and food preferences into the system.

[1255] The "selection means" refers to a means for selecting optimal ingredients, recipes, and dishes based on information input by the user.

[1256] "Proposal means" refers to a means for presenting selected ingredients, recipes, and dishes to the user.

[1257] "Means for receiving orders" refers to the means for accepting delivery requests for the proposed dishes.

[1258] "Means of collaboration" refers to the means of collaborating with a delivery service to confirm an order and notify the delivery progress.

[1259] "Tracking Method" means a method selected by the User that notifies the User of delivery progress in real time.

[1260] "Delivery service" refers to a service that delivers food or products to a specified location.

[1261] "API" stands for Application Programming Interface and refers to the rules for exchanging functions between different software.

[1262] "Server" refers to a computer system that stores and analyzes data.

[1263] A "database" refers to a structured collection of information for efficient storage and retrieval of data.

[1264] That's all.

[1265] To put the present invention into practice, an application is installed on the user's smartphone or computer, and the following process is performed.

[1266] System Overview

[1267] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress. A tracking method is also included to notify the user of the delivery progress of their selected order in real time.

[1268] Program processing overview

[1269] This section explains the roles of servers and user terminals, as well as the hardware and software they use.

[1270] 1. Launch the app and log in

[1271] The user launches the app on their smartphone and logs in using their social networking account on the login screen. Firebase Authentication is used for logging in. The device verifies the login information and issues an authentication token.

[1272] 2. Enter your user information

[1273] The terminal asks the user to enter information about their physical condition, food preferences, and allergies. The user enters the information into a form and sends it to the server. React Native is used for the input form. The input data passes validation before being sent to the server.

[1274] 3. Proposal Data Generation

[1275] The server stores the user's input information in a database and searches the database to select the best ingredients, recipes, and dishes. This is done using Node.js and MongoDB. The server matches the user data with the database and generates a list of suggestions.

[1276] 4. Viewing and selecting suggestions

[1277] The device displays the suggested ingredients, recipes, and dishes to the user. The user selects the dish they like from the list. This list display is done using React Native. The selected dish data is sent to the server.

[1278] 5. Executing a delivery request

[1279] The device sends a delivery request for the selected food to the server. The server confirms the order using the delivery service's API. Axios is used for API communication. Order details are sent to the delivery service.

[1280] 6. Order Confirmation and Tracking

[1281] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time, using the Firebase Realtime Database. The delivery status is periodically checked and notifications are sent.

[1282] Specific examples

[1283] 1. If a user is feeling unwell and wants to eat something sour, they launch the app and log in with their social media account.

[1284] 2. Type "I want to eat something sour."

[1285] 3. The server suggests dishes using lemon or plum, and "Lemon Chicken Salad" is displayed.

[1286] 4. The user selects the suggested dish and places a delivery request.

[1287] 5. The server contacts a nearby delivery service and confirms the order.

[1288] 6. Order details and progress are notified in real time to the user's smartphone.

[1289] Prompt Sentence Examples

[1290] User: "I want to eat something sour, but my stomach is upset."

[1291] App: "Would you like some lemon chicken salad? Would you like it delivered?"

[1292] This will enable personalized food suggestions tailored to the user's physical condition and preferences, as well as real-time notifications of delivery progress.

[1293] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1294] The processing flow of the program of the system that realizes the application example will be specifically explained below, broken down into steps.

[1295] Step 1:

[1296] A user launches the application on their device and logs in using their social network account on the login screen. The user's social network account information is required as input. The device verifies the login information using Firebase Authentication and generates an authentication token. The authentication token is obtained as output.

[1297] Step 2:

[1298] After logging in, the user enters information about their physical condition, food preferences, and allergies on the terminal. The information the user enters into the form is required as input. The input form created using React Native validates the data and sends it to the server. The output is user information that has passed validation.

[1299] Step 3:

[1300] The server receives user input information and stores it in a database. The submitted user information is required as input. The server uses Node.js to store the information in a database (MongoDB). The output is the user information stored in the database.

[1301] Step 4:

[1302] The server searches the database and selects the best ingredients, recipes, and dishes based on the user's input. As input, the server requires user information and dish information from the database. The server uses a matching algorithm to generate the best suggestions list. As output, the suggestions list is obtained and sent to the user's device.

[1303] Step 5:

[1304] The device displays suggested ingredients, recipes, and dishes to the user. As input, it requires a list of suggestions sent from the server. It displays the information in a list format using React Native. The user selects their favorite dish, and the selected dish information is obtained as output.

[1305] Step 6:

[1306] The device sends a delivery request to the server for the dish selected by the user. The user-selected dish information is required as input. The device sends the selected dish data to the server, and the server confirms the order through the delivery service's API. The confirmed order information is obtained as output.

[1307] Step 7:

[1308] The server confirms the order using the delivery service's API. As input, it requires the selected dish information and the user's delivery information. The server uses the Axios library to send the order information to the delivery service. As output, the delivery is initiated.

[1309] Step 8:

[1310] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time. The input requires order confirmation information and delivery progress information sent from the server. The Firebase Realtime Database is used to periodically check the progress and notify them. The output provides information that allows the user to check the delivery progress in real time.

[1311] The above is the flow of specific processing steps of the system that realizes the application example.

[1312] 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.

[1313] The system of the present invention recognizes the user's physical condition, food preferences, and emotions, suggests optimal ingredients, recipes, and dishes, and works in conjunction with delivery services. Specifically, the process is carried out as follows.

[1314] System Overview

[1315] When a user uses the system, they launch an application on their smartphone or computer and input information about their physical condition, food preferences, allergies, and emotional information recognized by the emotion engine from voice, facial expressions, and text input. This information is sent to the server, which then selects optimal ingredients, recipes, and dishes from a database based on the user's input, including past eating history and emotional history, and suggests them to the user. The user then selects the suggested ingredients and dishes and requests delivery. The server then connects with the delivery service, confirms the order, and notifies the user of the progress of the delivery.

[1316] Program processing overview

[1317] 1. Launch the app and log in

[1318] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[1319] 2. Input of user information and emotion information

[1320] The device asks for input of physical condition, food preferences, allergy information, and emotions recognized by the emotion engine from voice, facial expressions, and text input.

[1321] The user enters this information and the terminal transmits the data to the server.

[1322] 3. Proposal Data Generation

[1323] The server stores the received user information in a database, and searches the database based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history to select optimal ingredients, recipes, and dishes.

[1324] The server generates the selection results in list format and sends them to the terminal.

[1325] 4. Viewing and selecting suggestions

[1326] The device displays suggested ingredients, recipes, and dishes to the user.

[1327] The user selects their favorite dish from the list.

[1328] 5. Executing a delivery request

[1329] The terminal sends a delivery request for the selected dish to the server.

[1330] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[1331] 6. Order Confirmation and Tracking

[1332] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1333] Specific examples

[1334] 1. The user thinks, "I'm feeling down and I want to eat something sweet," and launches the app.

[1335] 2. The user logs in to LINE and enters their physical condition, the keyword "sweets," and the "depressed mood" information recognized by the emotion engine.

[1336] 3. The server analyzes the user's past data, input information, and emotional information, and suggests recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered.

[1337] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[1338] 5. The server contacts the delivery service and confirms the order.

[1339] 6. The order details are sent to the user's device and delivery begins.

[1340] The present invention provides a system that enables appropriate meal selection in response to changes in physical condition and emotions during pregnancy, and can provide a comfortable dining experience by making suggestions that match the user's preferences and mood.

[1341] The processing flow will be explained below.

[1342] Step 1:

[1343] The user launches the app on their smartphone.

[1344] What happens: A user launches an app by tapping its icon.

[1345] Step 2:

[1346] The terminal prompts the user to log in.

[1347] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[1348] Step 3:

[1349] The user logs in with LINE or Yahoo!

[1350] Operation details: The user enters their account information using the authentication method they selected and logs in.

[1351] Step 4:

[1352] The device asks you to enter information about your physical condition, food preferences, allergies, and emotions.

[1353] Operation details: The device displays an input form screen and prompts the user to enter information. The emotion engine also recognizes emotions from the user's voice, facial expressions, and text input.

[1354] Step 5:

[1355] The user inputs information about their physical condition, food preferences, allergy information, and emotional information.

[1356] Operation details: The user fills in the required information in the input form. Emotional information is automatically recognized from voice, facial expressions, text input, etc.

[1357] Step 6:

[1358] The terminal transmits the input information to the server.

[1359] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[1360] Step 7:

[1361] The server stores the received user information in a database.

[1362] What happens: The server opens a database connection and saves the user information in the corresponding table.

[1363] Step 8:

[1364] The server searches a database of ingredients, recipes and dishes, taking emotional information into account.

[1365] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, emotions and allergy information.

[1366] Step 9:

[1367] The server generates a list of the selection results and sends it to the terminal.

[1368] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[1369] Step 10:

[1370] The device displays suggested ingredients, recipes, and dishes to the user.

[1371] Operation details: The device receives the suggestion list and displays it on the screen.

[1372] Step 11:

[1373] The user selects their preferred dish from the list of suggestions.

[1374] What it does: The user taps to select one or more dishes from the list.

[1375] Step 12:

[1376] The terminal sends a delivery request to the server.

[1377] Operation details: The device sends a delivery request including the selected dish information to the server.

[1378] Step 13:

[1379] The server connects to the delivery service's API to confirm the order.

[1380] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[1381] Step 14:

[1382] The server notifies the user terminal of the order details.

[1383] Operation details: The server generates order confirmation information and sends it to the user terminal.

[1384] Step 15:

[1385] The terminal displays the order confirmation information to the user.

[1386] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[1387] Step 16:

[1388] The server updates the delivery progress in real time and notifies the device.

[1389] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[1390] Step 17:

[1391] The user checks the delivery status.

[1392] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[1393] The above are the detailed processing steps performed by the system of the present invention.

[1394] Example 2

[1395] 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."

[1396] Conventional ingredient and dish recommendation systems make recommendations based solely on a user's physical condition and food preferences, making it difficult to make recommendations that reflect the user's emotions. While utilizing a user's past meal history can provide more appropriate recommendations, it is difficult to make meal recommendations that reflect the user's mood because the history management does not include emotional information. The present invention solves these problems by providing a system that makes it possible to recommend and request delivery of appropriate ingredients, recipes, and dishes based on a user's physical condition, food preferences, and even emotions.

[1397] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1398] In this invention, the server includes an input means for the user to input information about their physical condition and food preferences, an emotion recognition means for analyzing the input emotion information, and a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotion information, thereby making it possible to suggest meals that take into account the user's emotions in addition to their physical condition and food preferences.

[1399] The "input means" is an interface that allows the user to input information about their physical condition and food preferences into the system.

[1400] "Emotion recognition means" is a technology that analyzes and recognizes emotional information from the user's input voice, facial expressions, etc.

[1401] The "selection means" is a function for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preference information, and emotional information.

[1402] The "suggestion means" is a function for presenting selected ingredients, recipes, and dishes to the user.

[1403] The "order receiving means" is a system for receiving a delivery request when a user makes a delivery request for the proposed dish.

[1404] The "linking means" is a technology that links with a delivery service to confirm an order and notify the user of the progress of the delivery.

[1405] The "database" is a storage system for storing user input information, past meal history, and emotional history.

[1406] An "API" is an application programming interface that allows different systems to communicate with each other and utilize their functions.

[1407] The system of the present invention proposes optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, and emotional information, and works in conjunction with delivery services. Specific embodiments of this system are described in detail below.

[1408] 1. Program Generation

[1409] The system's program is developed using Python. It uses SQLite for database operations and a generative AI model (such as OpenAI's emotion recognition model) for emotion recognition. It also uses common APIs such as Zinc API for integration with delivery services.

[1410] 2. Program Processing Overview

[1411] The processing outline of this system is as follows.

[1412] 1. Launch the app and log in

[1413] The user launches the app on their smartphone and logs in using a regular account (such as a LINE or Yahoo! account) on the login screen. The device sends the login information to the server, which then performs the authentication process.

[1414] 2. Input of user information and emotion information

[1415] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[1416] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data. The input information and emotional data are sent from the device to the server.

[1417] 3. Proposal Data Generation

[1418] The server stores the received user information in a database, and then searches the database to select optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history.

[1419] The server generates a list of selected ingredients, recipes, and dishes and sends it to the terminal.

[1420] 4. Viewing and selecting suggestions

[1421] The terminal displays a list of suggested ingredients, recipes, and dishes for the user to choose from.

[1422] 5. Executing a delivery request

[1423] The device sends a delivery request for the selected food to the server, which then uses the delivery service's API to confirm the order and notify the user of the delivery details.

[1424] 6. Order Confirmation and Tracking

[1425] The terminal displays order confirmation information to the user, and the server monitors the delivery progress in real time and sends updates to the terminal.

[1426] 3. Specific Examples

[1427] Specific examples are shown below.

[1428] 1. If a user feels depressed and wants to eat something sweet, they launch the app and log in with their LINE account.

[1429] 2. The user inputs their physical condition, the keyword "sweets," and the information about "depressed mood" that the emotion engine recognizes.

[1430] 3. The server analyzes the user's past data, input information, and emotional information to suggest recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered. A list is displayed to the user.

[1431] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[1432] 5. The server contacts the delivery service to confirm the order. The user is notified of the delivery progress.

[1433] 4. Examples of prompts

[1434] Below is an example of a prompt sentence to input to the generative AI model.

[1435] 1. Emotion recognition prompt:

[1436] "The user inputs, 'I'm tired from work today and I want to eat something sweet.' Please determine this emotion."

[1437] 2. Prompt for the best dish suggestion:

[1438] "The user's physical condition is 'tired,' their preference is 'sweets,' and their emotion is 'depressed.' Please suggest the best recipe based on this information."

[1439] As described above, the present invention realizes optimal meal suggestions and delivery requests based on the user's physical condition, food preferences, and even emotional information.

[1440] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1441] Step 1: Launch the app and log in

[1442] 1-1. Launching the app

[1443] The user taps the app on their smartphone to launch it, and the app's main screen appears.

[1444] Input: None

[1445] Output: Main screen of the app

[1446] 1-2. Login

[1447] The device displays a login screen, and the user selects a generic account (e.g., LINE or Yahoo! account), enters authentication information, and presses the login button.

[1448] The authentication information is sent from the terminal to the server.

[1449] The server performs user authentication based on the received authentication information, and if successful, loads the user's past data and sends a login completion message to the terminal.

[1450] Input: User credentials

[1451] Output: Login completion message, user's past data

[1452] Step 2: Enter user information and emotion information

[1453] 2-1. Displaying the information input form

[1454] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[1455] Input: None

[1456] Output: Information input form

[1457] 2-2. Entering information

[1458] The user inputs information about their physical condition, food preferences, and allergies, as well as voice and facial expressions.

[1459] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data.

[1460] The input information and emotion data are transmitted from the terminal to the server.

[1461] Input: User's physical condition information, food preferences, allergy information, voice and facial expression data

[1462] Data processing: Voice and facial expression analysis using generative AI models

[1463] Output: Analyzed emotion data, user-entered physical condition information, food preferences, and allergy information

[1464] Step 3: Generate proposal data

[1465] 3-1. Data storage

[1466] The server stores the received user information in a database, including information on physical condition, food preferences, allergies, and emotional data.

[1467] Input: User information, analyzed emotion data

[1468] Output: Information stored in the database

[1469] 3-2. Data analysis and search

[1470] The server performs analysis based on the stored data and past eating and emotional history.

[1471] It uses generative AI models to find the best ingredients, recipes, and dishes for a user's emotions and physical condition.

[1472] Compile a list of selected ingredients, recipes, and dishes.

[1473] Input: User information extracted from the database, past meal history, emotional history

[1474] Data processing: Analysis with generative AI models

[1475] Output: A list of selected ingredients, recipes, and dishes

[1476] 3-3. Sending proposal data

[1477] The server transmits the generated list to the terminal.

[1478] Input: Selected list

[1479] Output: List sent to terminal

[1480] Step 4: View and select suggestions

[1481] 4-1. Display of proposed data

[1482] The terminal displays the received list to the user, which includes a list of ingredients, recipes, and dishes.

[1483] Input: List sent from the server

[1484] Output: The list displayed to the user

[1485] 4-2. User selection

[1486] The user selects ingredients and dishes from a list of suggestions, for example, chocolate cake.

[1487] Input: User selected data

[1488] Output: Selected ingredients and dish information

[1489] 4-3. Sending selected data

[1490] The device sends information about the selected ingredients, recipe, and dish to the server.

[1491] Input: Selected ingredients, dish information

[1492] Output: Selection data sent to the server

[1493] Step 5: Execute delivery request

[1494] 5-1. Creating a delivery request

[1495] The server generates a delivery request based on the received selection data.

[1496] Input:Selection data

[1497] Output: Generated delivery request information

[1498] 5-2. Confirming your order

[1499] The server uses the delivery service's API to confirm the order, and the confirmation information is sent to the delivery service.

[1500] Input: Delivery request information

[1501] Output: Order confirmation information

[1502] 5-3. Detailed notification

[1503] The server transmits order confirmation information to the terminal, and the terminal notifies the user.

[1504] Input: Order confirmation information

[1505] Output: Detailed notification sent to the device

[1506] Step 6: Order confirmation and tracking

[1507] 6-1. Displaying order information

[1508] The terminal displays the order confirmation information to the user.

[1509] Input: Order confirmation information

[1510] Output: Order confirmation information displayed to the user

[1511] 6-2. Progress notification

[1512] The server works with the delivery service to monitor the delivery progress in real time. As each progress update occurs, the server notifies the device. The device then displays the progress information to the user.

[1513] Input: Delivery progress information

[1514] Output: Progress notification displayed to the user

[1515] The above are the specific processing steps of this system.

[1516] (Application example 2)

[1517] 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."

[1518] Conventional delivery systems make suggestions based on the user's physical condition, food preferences, and allergy information, but do not suggest optimal meals that take into account the user's emotional information. As a result, it is not possible to suggest meals that correspond to the user's mood and emotions, and it is not possible to improve user satisfaction. In addition, there was no suggestion system that linked with real-time emotion recognition, making it difficult to select the optimal meal.

[1519] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: input means for the user to input information about their physical condition, food preferences, and emotional information; emotion recognition means for collecting the user's emotions in real time using voice analysis and face recognition technology and analyzing them using an emotion engine; selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotional information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; order receiving means for accepting a delivery request for the suggested dishes; and collaboration means for coordinating with a delivery service to confirm the order and notify the user of the delivery progress. This enables optimal meal suggestions and delivery requests to be made taking into account the user's physical condition, preferences, and emotional information.

[1520] "Input means" refers to a device or mechanism that allows a user to input information about their physical condition, food preferences, and emotional information into the system.

[1521] "Emotion recognition means" refers to a function or device that uses voice analysis or face recognition technology to collect user emotions in real time and analyzes them using an emotion engine.

[1522] The "selection means" refers to a function or device for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, and emotional information.

[1523] The "suggestion means" refers to a function or device for visually or audibly suggesting selected ingredients, recipes, and dishes to the user.

[1524] The "order receiving means" refers to a function or device that accepts the operations required for the user to request delivery of the selected dish.

[1525] The "cooperation means" refers to a function or device that cooperates with a delivery service to confirm an order and notify the user of the progress of delivery.

[1526] "Ingredients" are raw materials used to prepare a dish, and are selected based on the user's physical condition, food preferences, and allergy information.

[1527] A "recipe" is a manual showing how to cook a dish, suggesting the best ingredients and cooking methods for the user.

[1528] A "dish" is food that is cooked using selected ingredients and served to the user.

[1529] An "emotion engine" is software or algorithms that analyze a user's emotions from voice, facial expressions, text input, etc.

[1530] The "database" is a data storage system for managing and storing information such as a user's physical condition, food preferences, dietary history, and emotional history.

[1531] The "delivery service" is a service that delivers the food selected by the user to a specified location.

[1532] "Progress" is status information that indicates the stage at which the delivery request is at, such as order received, cooking, delivery in progress, or delivery completed.

[1533] An "application program interface (API)" is an interface that allows different software programs to share functions and exchange data.

[1534] In the embodiment of the present invention, the flow of a system for realizing an application example will be specifically shown.

[1535] System Overview

[1536] The system begins with the user entering information about their physical condition, food preferences, and emotions using a device such as a smartphone. The device then uses a camera and microphone to collect the user's emotions in real time and analyzes them using an EmotionEngine (emotion recognition engine). This information is sent to a server, which then queries a FoodDatabase (a database of ingredients and recipes) to select the most suitable ingredients, recipes, and dishes. The system then presents the selected information to the user and accepts a delivery request for the dishes selected by the user. Finally, the system confirms the order using a delivery service API and notifies the user of the progress in real time.

[1537] Program processing overview

[1538] 1. Launch the app and log in

[1539] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account.

[1540] 2. Input of user information and emotion information

[1541] The device asks the user to input their physical condition, food preferences, allergy information, and emotional information. Emotional information is collected in real time using the device's camera and microphone and analyzed by EmotionEngine.

[1542] 3. Data processing on the server

[1543] The server stores the user's physical condition, food preferences, allergy information, and emotional information in a database. It also queries the user's past eating history and emotional history, and searches the Food Database to select the most suitable ingredients, recipes, and dishes.

[1544] 4. Display of suggestions

[1545] The server sends the selected ingredients, recipes, and dishes in list form to the user's terminal and displays the suggestions.

[1546] 5. Executing a delivery request

[1547] The user selects from the suggested dishes and places a delivery request. The server confirms the order using the delivery service API and notifies the device of the details.

[1548] 6. Order Confirmation and Tracking

[1549] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1550] Hardware and software used

[1551] Hardware: Smartphone (camera, microphone, network connection), server

[1552] Software: EmotionEngine (emotion recognition engine), FoodDatabase (SQL database), DeliveryAPI (delivery service API)

[1553] Specific examples

[1554] For example, consider a case where a user is feeling depressed during the rainy season and wants to eat something sweet. The user launches the app and logs in with LINE. They enter "Physical condition: feeling depressed," "Food preference: sweets," and "Allergies: none." The smartphone's camera and microphone are used to recognize emotions, and the emotional information is analyzed using EmotionEngine. Based on this information, the server makes appropriate suggestions, such as chocolate cake, and requests delivery of the dish selected by the user. The server then confirms the order using the delivery service API and notifies the user of the progress in real time.

[1555] Prompt Sentence Examples

[1556] "If a user says they're feeling down and want something sweet, suggest the best ingredients, recipes, and dishes. Also, offer delivery options."

[1557] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1558] Step 1:

[1559] The user launches the app on their smartphone and logs in by entering their account information on the login screen.

[1560] Input: Account information (ID, password)

[1561] Specific operation: The user taps the app to launch it and enters their LINE or Yahoo! authentication information on the login screen.

[1562] Output: Login success message, transition to the next input screen

[1563] Step 2:

[1564] The terminal prompts the user to enter physical condition, food preferences, allergy information, and emotional information.

[1565] Input: Enter your physical condition, food preferences, and allergy information in the input form

[1566] Specific operation: The user enters information about their physical condition, food preferences, and allergies into an input form. The device's camera and microphone collect the user's facial expressions and voice.

[1567] Output: Input information, emotional data collected in real time

[1568] Step 3:

[1569] The emotional information collected by the device is sent to EmotionEngine for emotional analysis.

[1570] Input: Emotion information (facial expression data, voice data)

[1571] Specific operation: The device calls the EmotionEngine and analyzes the collected emotional information in real time.

[1572] Data processing: Analysis of voice and facial expression data, identification of emotional state (e.g., depressed, happy, etc.)

[1573] Output: Emotional state data as analysis result

[1574] Step 4:

[1575] The terminal transmits information on physical condition, food preferences, allergies, and emotions to the server.

[1576] Input: Physical condition information, food preferences, allergy information, emotional state data

[1577] Specific operation: The device saves the entered data in temporary storage and sends it to the server as an HTTP request.

[1578] Output: Dataset of user information received by the server

[1579] Step 5:

[1580] The server stores the received user information in a database and selects optimal ingredients, recipes, and dishes by referencing the user's past eating history and emotional history.

[1581] Input: User information (physical condition, food preferences, allergies, emotional state), past dietary history, emotional history

[1582] What happens: The server executes a database search query to extract the best ingredients, recipes, and dishes from the FoodDatabase.

[1583] Data operations: performing search queries, filtering and ranking data

[1584] Output: A list of selected ingredients, recipes, and dishes

[1585] Step 6:

[1586] The server sends the selected optimal ingredients, recipes, and dishes to the user's terminal, which then displays the suggestions in list form.

[1587] Input: List of selected ingredients, recipes, and dishes

[1588] Specific operation: The server generates the selection result in JSON format and sends it to the device. The device updates the UI to display the list.

[1589] Output: The list of suggestions displayed on the user's device

[1590] Step 7:

[1591] The user selects the desired dish from the suggested list and places a delivery request.

[1592] Input: User's selected dish

[1593] Specific operation: The user selects the desired dish from the list of suggestions by tapping it. The selected dish information is sent to the server.

[1594] Output: Food selection information

[1595] Step 8:

[1596] The server confirms the order using the delivery service API and notifies the user of the delivery progress.

[1597] Input: Selected dish information, user's delivery address information

[1598] Specific operation: The server calls the delivery service API, sends the order information and confirms the order, collects delivery status information and sends it to the user's device.

[1599] Output: Order confirmation message, delivery progress

[1600] Step 9:

[1601] The terminal will notify the user of order confirmation information and real-time delivery progress.

[1602] Input: Order confirmation message, delivery progress

[1603] Specific behavior: The device receives a notification from the server and displays the information to the user using a notification popup or status bar.

[1604] Output: Delivery confirmation and progress notification to the user

[1605] 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.

[1606] 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.

[1607] 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.

[1608] [Fourth embodiment]

[1609] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1610] 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.

[1611] 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).

[1612] 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.

[1613] 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.

[1614] 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).

[1615] 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.

[1616] 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.

[1617] 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.

[1618] 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.

[1619] 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.

[1620] 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.

[1621] 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."

[1622] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[1623] System Overview

[1624] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[1625] Program processing overview

[1626] 1. Launch the app and log in

[1627] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[1628] 2. Enter your user information

[1629] The device prompts the user to enter information about their physical condition, food preferences, and allergies, and the information is then sent from the device to the server.

[1630] 3. Proposal Data Generation

[1631] The server stores the user's input information in a database and searches the database to select the most suitable ingredients, recipes, and dishes.

[1632] The server generates the selection results in list format and sends them to the terminal.

[1633] 4. Viewing and selecting suggestions

[1634] The device displays suggested ingredients, recipes, and dishes to the user.

[1635] The user selects their favorite dish from the list.

[1636] 5. Executing a delivery request

[1637] The terminal sends a delivery request for the selected dish to the server.

[1638] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[1639] 6. Order Confirmation and Tracking

[1640] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1641] Specific examples

[1642] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[1643] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[1644] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[1645] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[1646] 5. The server contacts a nearby delivery service and confirms the order.

[1647] 6. The order details are sent to the user's device and delivery begins.

[1648] The present invention provides a system that allows for the selection of appropriate meals in response to changes in physical condition during pregnancy and can be operated intuitively in a short time, thereby enabling pregnant women to eat comfortably.

[1649] The above is a description of the preferred embodiment of the present invention, which provides details for specifically implementing the present invention based on the content set forth in the claims.

[1650] The processing flow will be explained below.

[1651] Step 1:

[1652] The user launches the app on their smartphone.

[1653] How it works: The user taps the app icon to launch it.

[1654] Step 2:

[1655] The terminal prompts the user to log in.

[1656] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[1657] Step 3:

[1658] The user logs in with LINE or Yahoo!

[1659] Operation details: The user enters their account information using the authentication method they selected and logs in.

[1660] Step 4:

[1661] The device will ask you to enter information about your physical condition, food preferences, and allergies.

[1662] Operation details: The device displays an input form screen and asks the user to enter information.

[1663] Step 5:

[1664] The user inputs information such as physical condition, food preferences, and allergy information.

[1665] Action details: The user fills in the required information in the input form.

[1666] Step 6:

[1667] The terminal transmits the input information to the server.

[1668] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[1669] Step 7:

[1670] The server stores the received user information in a database.

[1671] What happens: The server opens a database connection and saves the user information in the corresponding table.

[1672] Step 8:

[1673] The server searches a database of ingredients, recipes, and dishes.

[1674] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, and allergies.

[1675] Step 9:

[1676] The server generates a list of the selection results and sends it to the terminal.

[1677] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[1678] Step 10:

[1679] The device displays suggested ingredients, recipes, and dishes to the user.

[1680] Operation details: The device receives the suggestion list and displays it on the screen.

[1681] Step 11:

[1682] The user selects their preferred dish from the list of suggestions.

[1683] What it does: The user taps to select one or more dishes from the list.

[1684] Step 12:

[1685] The terminal sends a delivery request to the server.

[1686] Operation details: The device sends a delivery request including the selected dish information to the server.

[1687] Step 13:

[1688] The server connects to the delivery service's API to confirm the order.

[1689] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[1690] Step 14:

[1691] The server notifies the user terminal of the order details.

[1692] Operation details: The server generates order confirmation information and sends it to the user terminal.

[1693] Step 15:

[1694] The terminal displays the order confirmation information to the user.

[1695] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[1696] Step 16:

[1697] The server updates the delivery progress in real time and notifies the device.

[1698] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[1699] Step 17:

[1700] The user checks the delivery status.

[1701] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[1702] The above are the detailed processing steps performed by the system of the present invention.

[1703] Example 1

[1704] 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."

[1705] In recent years, as part of health management, there has been a demand for meal selection based on individual physical condition and food preferences. However, conventional systems require users to collect information themselves and select the optimal ingredients and cooking methods, which takes time and effort. Furthermore, when using delivery services, a separate order is required. Furthermore, to track the progress of delivery after ordering, users must check the individual applications of each service. To solve these problems, a system is needed that automatically selects the optimal ingredients and dishes based on the information entered by the user and provides consistent support right up to delivery.

[1706] 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.

[1707] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a storage means for storing the user's input information, a selection means for selecting optimal ingredients, cooking methods, and dishes based on the stored information, a suggestion means for suggesting the selected ingredients, cooking methods, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, and a linking means for confirming the order using the delivery service's API and notifying the user of the progress of the delivery. This enables users to easily select the meal that is optimal for them, quickly order using the delivery service, and keep track of the progress in real time.

[1708] "User" refers to a person who uses the system to input information about their physical condition and food preferences, and then checks and selects suggested dishes.

[1709] "Input means" refers to a device or interface that allows a user to input information about their physical condition, food preferences, allergies, and the like.

[1710] "Storage means" refers to a device or function for storing information input by a user.

[1711] "Selection means" refers to a device or function that selects optimal ingredients, cooking means, and dishes based on stored user input information.

[1712] The "suggestion means" refers to a device or function for suggesting selected ingredients, cooking means, and dishes to the user.

[1713] "Order receiving means" refers to a device or function for receiving a delivery request for the proposed dishes.

[1714] "Linkage means" refers to a device or function for confirming an order using the delivery service's API and notifying the progress of delivery.

[1715] "Database" refers to an information management system for storing, searching, and analyzing user input information and past meal history.

[1716] "Delivery service" refers to a business that provides a service of delivering food ordered by a user.

[1717] "Delivery progress" refers to the status of each stage until the ordered food is delivered to the user.

[1718] "API" stands for Application Programming Interface, and refers to an interface for exchanging information and functions between different software systems.

[1719] To implement the system of the present invention, an application is installed using a user's smartphone or computer, and the following process is performed.

[1720] System Overview

[1721] When a user uses the system, they install and launch an application on their smartphone or computer. When the user enters information about their physical condition and food preferences, that information is sent to the server. The server selects the most suitable ingredients, cooking methods, and dishes from a database based on the user's input, and suggests them to the user. When the user checks the suggestions, selects a specific dish, and requests delivery, the server uses the delivery service's API to confirm the order and notify the user of the delivery progress.

[1722] System configuration

[1723] 1. Input Method

[1724] A device or interface that allows users to input information about their physical condition and food preferences. This is implemented on a smartphone or computer application screen.

[1725] 2. Preservation means

[1726] A device or function for saving user-entered information. Information is saved in a database (e.g., MySQL database) on a cloud server.

[1727] 3. Selection method

[1728] A device or function that selects the best ingredients, cooking methods, and dishes based on stored information. Python scripts are used to search the database and parse user information.

[1729] 4. Proposal method

[1730] A device or function for suggesting selected ingredients, cooking methods, and dishes to the user. It generates a list in JSON format and displays it in the user interface.

[1731] 5. Ordering Method

[1732] A device or function for accepting delivery requests for suggested dishes, and sending information about the dishes selected by the user to the server.

[1733] 6. Collaboration Methods

[1734] A device or function that uses the delivery service's API to confirm orders and notify delivery progress. It works in conjunction with delivery services using APIs such as Uber Eats.

[1735] Specific examples

[1736] 1. The user thinks, "I feel sick and can't eat much food, but maybe sour things would be okay," and launches the app.

[1737] 2. The user logs in to LINE and enters their physical condition and "sour" as keywords.

[1738] 3. The server analyzes the user's past data and input information and suggests simple recipes using sour ingredients such as lemons, plums, and tomatoes, as well as commercially available dishes that can be delivered.

[1739] 4. The user selects "Lemon Chicken Salad" from the suggested list and places a delivery order.

[1740] 5. The server contacts a nearby delivery service and confirms the order.

[1741] 6. The order details are sent to the user's device and delivery begins.

[1742] Specific prompt examples

[1743] "If I want to eat something disgusting and sour, please suggest what would be good."

[1744] "They suggested lemon chicken salad, so I ordered it for delivery."

[1745] The present invention provides an environment in which users can easily select meals that suit their physical condition and operate intuitively. This is particularly useful during periods of rapid physical changes such as pregnancy. This allows users to eat comfortably.

[1746] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1747] Step 1: Launch the app and log in

[1748] The user launches the app on their smartphone.

[1749] The device displays the splash screen and provides a login screen. The user enters their LINE or general account information. Input: User's login information. Output: Authentication token.

[1750] The server uses the authentication API to check the entered login information, and if authentication is successful, it generates an authentication token and sends it to the terminal.

[1751] The device receives the authentication token and displays the main screen.

[1752] Step 2: Enter your user information

[1753] The device displays a form for entering information about your physical condition, food preferences, and allergies.

[1754] The user enters "feeling sick" as their physical condition, "sour foods" as their food preference, and allergy information. Input: User's physical condition and preference information. Output: Input information in JSON format.

[1755] The terminal converts the input information into JSON format and sends it to the server.

[1756] Step 3: Save your information

[1757] Parse the JSON format user information received by the server. Input: JSON format user information. Output: Save to database.

[1758] The server stores user information in a MySQL database.

[1759] Step 4: Generate proposal data

[1760] The server starts parsing based on the stored user information. Input: User information stored in the database. Output: A list of suggestions in JSON format.

[1761] The server uses a Python script to select the best ingredients, cooking methods, and dishes based on the user's physical condition and food preferences.

[1762] The server compiles the selection results into a JSON format list and sends it to the terminal.

[1763] Step 5: View and select suggestions

[1764] The device displays the received suggestion list in the UI. Input: Suggestion list sent from the server. Output: Display of suggestion list.

[1765] User taps to select the dish they are interested in from the suggestion list. Input: User selection. Output: Details of the selected dish.

[1766] The device sends information about the selected dish in JSON format to the server.

[1767] Step 6: Execute delivery request

[1768] The server calls the delivery service's API based on the selected dish information. Input: Information about the dish selected by the user. Output: Confirmed order and delivery details.

[1769] The server confirms the order using the delivery service's API and generates delivery progress information.

[1770] The server sends delivery progress information to the terminal.

[1771] Step 7: Order confirmation and tracking

[1772] The terminal notifies the user of the order confirmation details and delivery progress. Input: Delivery progress information sent from the server. Output: Order details and progress notification.

[1773] Monitor delivery status in real time and display status updates to users.

[1774] This is the specific process flow of this system, allowing users to easily select the perfect meal and track the delivery progress.

[1775] (Application example 1)

[1776] 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."

[1777] Conventional food delivery systems have had difficulty proposing individually optimized ingredients, recipes, and dishes based on a user's physical condition and food preferences. They also lacked a means to notify users of the progress of delivery of the proposed dishes in real time, making it difficult to improve user satisfaction.

[1778] 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.

[1779] In this invention, the server includes an input means for a user to input information about their physical condition and food preferences, a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information, a suggestion means for suggesting the selected ingredients, recipes, and dishes to the user, an order receiving means for accepting a delivery request for the suggested dishes, a linking means for linking with a delivery service to confirm the order and notify the user of the delivery progress, and a tracking means for notifying the user of the delivery progress in real time, thereby enabling personalized suggestions for dishes tailored to the user's physical condition and preferences and real-time notification of the delivery progress.

[1780] "User" refers to an individual who uses the system by inputting information about their physical condition and food preferences.

[1781] "Physical condition" refers to the user's health condition and any physical symptoms they may be experiencing.

[1782] "Food preference information" refers to data including the user's favorite ingredients, types of cuisine, taste preferences, allergy information, etc.

[1783] "Input means" refers to an interface that allows a user to input information about their physical condition and food preferences into the system.

[1784] The "selection means" refers to a means for selecting optimal ingredients, recipes, and dishes based on information input by the user.

[1785] "Proposal means" refers to a means for presenting selected ingredients, recipes, and dishes to the user.

[1786] "Means for receiving orders" refers to the means for accepting delivery requests for the proposed dishes.

[1787] "Means of collaboration" refers to the means of collaborating with a delivery service to confirm an order and notify the delivery progress.

[1788] "Tracking Method" means a method selected by the User that notifies the User of delivery progress in real time.

[1789] "Delivery service" refers to a service that delivers food or products to a specified location.

[1790] "API" stands for Application Programming Interface and refers to the rules for exchanging functions between different software.

[1791] "Server" refers to a computer system that stores and analyzes data.

[1792] A "database" refers to a structured collection of information for efficient storage and retrieval of data.

[1793] That's all.

[1794] To put the present invention into practice, an application is installed on the user's smartphone or computer, and the following process is performed.

[1795] System Overview

[1796] When a user uses the system, they first launch the application and enter information about their physical condition and food preferences. The entered information is sent to the server, which then selects the most suitable ingredients, recipes, and dishes from a database based on the user's input and suggests them to the user. The user can then review the suggested ingredients, recipes, and dishes, select their favorite, and request delivery. The server uses the delivery service's API to confirm the order and notify the user of the delivery progress. A tracking method is also included to notify the user of the delivery progress of their selected order in real time.

[1797] Program processing overview

[1798] This section explains the roles of servers and user terminals, as well as the hardware and software they use.

[1799] 1. Launch the app and log in

[1800] The user launches the app on their smartphone and logs in using their social networking account on the login screen. Firebase Authentication is used for logging in. The device verifies the login information and issues an authentication token.

[1801] 2. Enter your user information

[1802] The terminal asks the user to enter information about their physical condition, food preferences, and allergies. The user enters the information into a form and sends it to the server. React Native is used for the input form. The input data passes validation before being sent to the server.

[1803] 3. Proposal Data Generation

[1804] The server stores the user's input information in a database and searches the database to select the best ingredients, recipes, and dishes. This is done using Node.js and MongoDB. The server matches the user data with the database and generates a list of suggestions.

[1805] 4. Viewing and selecting suggestions

[1806] The device displays the suggested ingredients, recipes, and dishes to the user. The user selects the dish they like from the list. This list display is done using React Native. The selected dish data is sent to the server.

[1807] 5. Executing a delivery request

[1808] The device sends a delivery request for the selected food to the server. The server confirms the order using the delivery service's API. Axios is used for API communication. Order details are sent to the delivery service.

[1809] 6. Order Confirmation and Tracking

[1810] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time, using the Firebase Realtime Database. The delivery status is periodically checked and notifications are sent.

[1811] Specific examples

[1812] 1. If a user is feeling unwell and wants to eat something sour, they launch the app and log in with their social media account.

[1813] 2. Type "I want to eat something sour."

[1814] 3. The server suggests dishes using lemon or plum, and "Lemon Chicken Salad" is displayed.

[1815] 4. The user selects the suggested dish and places a delivery request.

[1816] 5. The server contacts a nearby delivery service and confirms the order.

[1817] 6. Order details and progress are notified in real time to the user's smartphone.

[1818] Prompt Sentence Examples

[1819] User: "I want to eat something sour, but my stomach is upset."

[1820] App: "Would you like some lemon chicken salad? Would you like it delivered?"

[1821] This will enable personalized food suggestions tailored to the user's physical condition and preferences, as well as real-time notifications of delivery progress.

[1822] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1823] The processing flow of the program of the system that realizes the application example will be specifically explained below, broken down into steps.

[1824] Step 1:

[1825] A user launches the application on their device and logs in using their social network account on the login screen. The user's social network account information is required as input. The device verifies the login information using Firebase Authentication and generates an authentication token. The authentication token is obtained as output.

[1826] Step 2:

[1827] After logging in, the user enters information about their physical condition, food preferences, and allergies on the terminal. The information the user enters into the form is required as input. The input form created using React Native validates the data and sends it to the server. The output is user information that has passed validation.

[1828] Step 3:

[1829] The server receives user input information and stores it in a database. The submitted user information is required as input. The server uses Node.js to store the information in a database (MongoDB). The output is the user information stored in the database.

[1830] Step 4:

[1831] The server searches the database and selects the best ingredients, recipes, and dishes based on the user's input. As input, the server requires user information and dish information from the database. The server uses a matching algorithm to generate the best suggestions list. As output, the suggestions list is obtained and sent to the user's device.

[1832] Step 5:

[1833] The device displays suggested ingredients, recipes, and dishes to the user. As input, it requires a list of suggestions sent from the server. It displays the information in a list format using React Native. The user selects their favorite dish, and the selected dish information is obtained as output.

[1834] Step 6:

[1835] The device sends a delivery request to the server for the dish selected by the user. The user-selected dish information is required as input. The device sends the selected dish data to the server, and the server confirms the order through the delivery service's API. The confirmed order information is obtained as output.

[1836] Step 7:

[1837] The server confirms the order using the delivery service's API. As input, it requires the selected dish information and the user's delivery information. The server uses the Axios library to send the order information to the delivery service. As output, the delivery is initiated.

[1838] Step 8:

[1839] The terminal displays order confirmation information to the user and notifies them of the delivery progress in real time. The input requires order confirmation information and delivery progress information sent from the server. The Firebase Realtime Database is used to periodically check the progress and notify them. The output provides information that allows the user to check the delivery progress in real time.

[1840] The above is the flow of specific processing steps of the system that realizes the application example.

[1841] 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.

[1842] The system of the present invention recognizes the user's physical condition, food preferences, and emotions, suggests optimal ingredients, recipes, and dishes, and works in conjunction with delivery services. Specifically, the process is carried out as follows.

[1843] System Overview

[1844] When a user uses the system, they launch an application on their smartphone or computer and input information about their physical condition, food preferences, allergies, and emotional information recognized by the emotion engine from voice, facial expressions, and text input. This information is sent to the server, which then selects optimal ingredients, recipes, and dishes from a database based on the user's input, including past eating history and emotional history, and suggests them to the user. The user then selects the suggested ingredients and dishes and requests delivery. The server then connects with the delivery service, confirms the order, and notifies the user of the progress of the delivery.

[1845] Program processing overview

[1846] 1. Launch the app and log in

[1847] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account on the login screen.

[1848] 2. Input of user information and emotion information

[1849] The device asks for input of physical condition, food preferences, allergy information, and emotions recognized by the emotion engine from voice, facial expressions, and text input.

[1850] The user enters this information and the terminal transmits the data to the server.

[1851] 3. Proposal Data Generation

[1852] The server stores the received user information in a database, and searches the database based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history to select optimal ingredients, recipes, and dishes.

[1853] The server generates the selection results in list format and sends them to the terminal.

[1854] 4. Viewing and selecting suggestions

[1855] The device displays suggested ingredients, recipes, and dishes to the user.

[1856] The user selects their favorite dish from the list.

[1857] 5. Executing a delivery request

[1858] The terminal sends a delivery request for the selected dish to the server.

[1859] The server confirms the order using the delivery service's API and notifies the user of delivery details.

[1860] 6. Order Confirmation and Tracking

[1861] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[1862] Specific examples

[1863] 1. The user thinks, "I'm feeling down and I want to eat something sweet," and launches the app.

[1864] 2. The user logs in to LINE and enters their physical condition, the keyword "sweets," and the "depressed mood" information recognized by the emotion engine.

[1865] 3. The server analyzes the user's past data, input information, and emotional information, and suggests recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered.

[1866] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[1867] 5. The server contacts the delivery service and confirms the order.

[1868] 6. The order details are sent to the user's device and delivery begins.

[1869] The present invention provides a system that enables appropriate meal selection in response to changes in physical condition and emotions during pregnancy, and can provide a comfortable dining experience by making suggestions that match the user's preferences and mood.

[1870] The processing flow will be explained below.

[1871] Step 1:

[1872] The user launches the app on their smartphone.

[1873] What happens: A user launches an app by tapping its icon.

[1874] Step 2:

[1875] The terminal prompts the user to log in.

[1876] Operation details: The device will display a login screen and prompt you to log in with your LINE or Yahoo! account.

[1877] Step 3:

[1878] The user logs in with LINE or Yahoo!

[1879] Operation details: The user enters their account information using the authentication method they selected and logs in.

[1880] Step 4:

[1881] The device asks you to enter information about your physical condition, food preferences, allergies, and emotions.

[1882] Operation details: The device displays an input form screen and prompts the user to enter information. The emotion engine also recognizes emotions from the user's voice, facial expressions, and text input.

[1883] Step 5:

[1884] The user inputs information about their physical condition, food preferences, allergy information, and emotional information.

[1885] Operation details: The user fills in the required information in the input form. Emotional information is automatically recognized from voice, facial expressions, text input, etc.

[1886] Step 6:

[1887] The terminal transmits the input information to the server.

[1888] Operation details: When the send button is pressed on the terminal, the input data is sent to the server.

[1889] Step 7:

[1890] The server stores the received user information in a database.

[1891] What happens: The server opens a database connection and saves the user information in the corresponding table.

[1892] Step 8:

[1893] The server searches a database of ingredients, recipes and dishes, taking emotional information into account.

[1894] How it works: The server queries the database to select the best candidates based on the user's physical condition, preferences, emotions and allergy information.

[1895] Step 9:

[1896] The server generates a list of the selection results and sends it to the terminal.

[1897] Operation details: The server compiles the search results into a list and sends it to the user's terminal.

[1898] Step 10:

[1899] The device displays suggested ingredients, recipes, and dishes to the user.

[1900] Operation details: The device receives the suggestion list and displays it on the screen.

[1901] Step 11:

[1902] The user selects their preferred dish from the list of suggestions.

[1903] What it does: The user taps to select one or more dishes from the list.

[1904] Step 12:

[1905] The terminal sends a delivery request to the server.

[1906] Operation details: The device sends a delivery request including the selected dish information to the server.

[1907] Step 13:

[1908] The server connects to the delivery service's API to confirm the order.

[1909] Operation details: The server calls the delivery service's API, sends the necessary order data, and confirms the order.

[1910] Step 14:

[1911] The server notifies the user terminal of the order details.

[1912] Operation details: The server generates order confirmation information and sends it to the user terminal.

[1913] Step 15:

[1914] The terminal displays the order confirmation information to the user.

[1915] Operation details: The terminal displays the order details screen and asks the user for confirmation.

[1916] Step 16:

[1917] The server updates the delivery progress in real time and notifies the device.

[1918] Operation details: The server receives status updates from the delivery service and notifies the user terminal accordingly.

[1919] Step 17:

[1920] The user checks the delivery status.

[1921] How it works: Users can view the in-app tracking screen to follow the delivery progress in real time.

[1922] The above are the detailed processing steps performed by the system of the present invention.

[1923] Example 2

[1924] 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."

[1925] Conventional ingredient and dish recommendation systems make recommendations based solely on a user's physical condition and food preferences, making it difficult to make recommendations that reflect the user's emotions. While utilizing a user's past meal history can provide more appropriate recommendations, it is difficult to make meal recommendations that reflect the user's mood because the history management does not include emotional information. The present invention solves these problems by providing a system that makes it possible to recommend and request delivery of appropriate ingredients, recipes, and dishes based on a user's physical condition, food preferences, and even emotions.

[1926] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1927] In this invention, the server includes an input means for the user to input information about their physical condition and food preferences, an emotion recognition means for analyzing the input emotion information, and a selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotion information, thereby making it possible to suggest meals that take into account the user's emotions in addition to their physical condition and food preferences.

[1928] The "input means" is an interface that allows the user to input information about their physical condition and food preferences into the system.

[1929] "Emotion recognition means" is a technology that analyzes and recognizes emotional information from the user's input voice, facial expressions, etc.

[1930] The "selection means" is a function for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preference information, and emotional information.

[1931] The "suggestion means" is a function for presenting selected ingredients, recipes, and dishes to the user.

[1932] The "order receiving means" is a system for receiving a delivery request when a user makes a delivery request for the proposed dish.

[1933] The "linking means" is a technology that links with a delivery service to confirm an order and notify the user of the progress of the delivery.

[1934] The "database" is a storage system for storing user input information, past meal history, and emotional history.

[1935] An "API" is an application programming interface that allows different systems to communicate with each other and utilize their functions.

[1936] The system of the present invention proposes optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, and emotional information, and works in conjunction with delivery services. Specific embodiments of this system are described in detail below.

[1937] 1. Program Generation

[1938] The system's program is developed using Python. It uses SQLite for database operations and a generative AI model (such as OpenAI's emotion recognition model) for emotion recognition. It also uses common APIs such as Zinc API for integration with delivery services.

[1939] 2. Program Processing Overview

[1940] The processing outline of this system is as follows.

[1941] 1. Launch the app and log in

[1942] The user launches the app on their smartphone and logs in using a regular account (such as a LINE or Yahoo! account) on the login screen. The device sends the login information to the server, which then performs the authentication process.

[1943] 2. Input of user information and emotion information

[1944] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[1945] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data. The input information and emotional data are sent from the device to the server.

[1946] 3. Proposal Data Generation

[1947] The server stores the received user information in a database, and then searches the database to select optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, past eating history, and emotional history.

[1948] The server generates a list of selected ingredients, recipes, and dishes and sends it to the terminal.

[1949] 4. Viewing and selecting suggestions

[1950] The terminal displays a list of suggested ingredients, recipes, and dishes for the user to choose from.

[1951] 5. Executing a delivery request

[1952] The device sends a delivery request for the selected food to the server, which then uses the delivery service's API to confirm the order and notify the user of the delivery details.

[1953] 6. Order Confirmation and Tracking

[1954] The terminal displays order confirmation information to the user, and the server monitors the delivery progress in real time and sends updates to the terminal.

[1955] 3. Specific Examples

[1956] Specific examples are shown below.

[1957] 1. If a user feels depressed and wants to eat something sweet, they launch the app and log in with their LINE account.

[1958] 2. The user inputs their physical condition, the keyword "sweets," and the information about "depressed mood" that the emotion engine recognizes.

[1959] 3. The server analyzes the user's past data, input information, and emotional information to suggest recipes for chocolate-based desserts and sweets, as well as dishes that can be delivered. A list is displayed to the user.

[1960] 4. The user selects "Chocolate Cake" from the suggested list and places a delivery request.

[1961] 5. The server contacts the delivery service to confirm the order. The user is notified of the delivery progress.

[1962] 4. Examples of prompts

[1963] Below is an example of a prompt sentence to input to the generative AI model.

[1964] 1. Emotion recognition prompt:

[1965] "The user inputs, 'I'm tired from work today and I want to eat something sweet.' Please determine this emotion."

[1966] 2. Prompt for the best dish suggestion:

[1967] "The user's physical condition is 'tired,' their preference is 'sweets,' and their emotion is 'depressed.' Please suggest the best recipe based on this information."

[1968] As described above, the present invention realizes optimal meal suggestions and delivery requests based on the user's physical condition, food preferences, and even emotional information.

[1969] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1970] Step 1: Launch the app and log in

[1971] 1-1. Launching the app

[1972] The user taps the app on their smartphone to launch it, and the app's main screen appears.

[1973] Input: None

[1974] Output: Main screen of the app

[1975] 1-2. Login

[1976] The device displays a login screen, and the user selects a generic account (e.g., LINE or Yahoo! account), enters authentication information, and presses the login button.

[1977] The authentication information is sent from the terminal to the server.

[1978] The server performs user authentication based on the received authentication information, and if successful, loads the user's past data and sends a login completion message to the terminal.

[1979] Input: User credentials

[1980] Output: Login completion message, user's past data

[1981] Step 2: Enter user information and emotion information

[1982] 2-1. Displaying the information input form

[1983] The device displays a form asking the user to enter information about their physical condition, food preferences, and allergies, as well as a user interface for voice and facial expression input.

[1984] Input: None

[1985] Output: Information input form

[1986] 2-2. Entering information

[1987] The user inputs information about their physical condition, food preferences, and allergies, as well as voice and facial expressions.

[1988] As a means of emotion recognition, the generative AI model analyzes the user's voice and facial expressions to generate emotional data.

[1989] The input information and emotion data are transmitted from the terminal to the server.

[1990] Input: User's physical condition information, food preferences, allergy information, voice and facial expression data

[1991] Data processing: Voice and facial expression analysis using generative AI models

[1992] Output: Analyzed emotion data, user-entered physical condition information, food preferences, and allergy information

[1993] Step 3: Generate proposal data

[1994] 3-1. Data storage

[1995] The server stores the received user information in a database, including information on physical condition, food preferences, allergies, and emotional data.

[1996] Input: User information, analyzed emotion data

[1997] Output: Information stored in the database

[1998] 3-2. Data analysis and search

[1999] The server performs analysis based on the stored data and past eating and emotional history.

[2000] It uses generative AI models to find the best ingredients, recipes, and dishes for a user's emotions and physical condition.

[2001] Compile a list of selected ingredients, recipes, and dishes.

[2002] Input: User information extracted from the database, past meal history, emotional history

[2003] Data processing: Analysis with generative AI models

[2004] Output: A list of selected ingredients, recipes, and dishes

[2005] 3-3. Sending proposal data

[2006] The server transmits the generated list to the terminal.

[2007] Input: Selected list

[2008] Output: List sent to terminal

[2009] Step 4: View and select suggestions

[2010] 4-1. Display of proposed data

[2011] The terminal displays the received list to the user, which includes a list of ingredients, recipes, and dishes.

[2012] Input: List sent from the server

[2013] Output: The list displayed to the user

[2014] 4-2. User selection

[2015] The user selects ingredients and dishes from a list of suggestions, for example, chocolate cake.

[2016] Input: User selected data

[2017] Output: Selected ingredients and dish information

[2018] 4-3. Sending selected data

[2019] The device sends information about the selected ingredients, recipe, and dish to the server.

[2020] Input: Selected ingredients, dish information

[2021] Output: Selection data sent to the server

[2022] Step 5: Execute delivery request

[2023] 5-1. Creating a delivery request

[2024] The server generates a delivery request based on the received selection data.

[2025] Input:Selection data

[2026] Output: Generated delivery request information

[2027] 5-2. Confirming your order

[2028] The server uses the delivery service's API to confirm the order, and the confirmation information is sent to the delivery service.

[2029] Input: Delivery request information

[2030] Output: Order confirmation information

[2031] 5-3. Detailed notification

[2032] The server transmits order confirmation information to the terminal, and the terminal notifies the user.

[2033] Input: Order confirmation information

[2034] Output: Detailed notification sent to the device

[2035] Step 6: Order confirmation and tracking

[2036] 6-1. Displaying order information

[2037] The terminal displays the order confirmation information to the user.

[2038] Input: Order confirmation information

[2039] Output: Order confirmation information displayed to the user

[2040] 6-2. Progress notification

[2041] The server works with the delivery service to monitor the delivery progress in real time. As each progress update occurs, the server notifies the device. The device then displays the progress information to the user.

[2042] Input: Delivery progress information

[2043] Output: Progress notification displayed to the user

[2044] The above are the specific processing steps of this system.

[2045] (Application example 2)

[2046] 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."

[2047] Conventional delivery systems make suggestions based on the user's physical condition, food preferences, and allergy information, but do not suggest optimal meals that take into account the user's emotional information. As a result, it is not possible to suggest meals that correspond to the user's mood and emotions, and it is not possible to improve user satisfaction. In addition, there was no suggestion system that linked with real-time emotion recognition, making it difficult to select the optimal meal.

[2048] The specification processing by the specification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes: input means for the user to input information about their physical condition, food preferences, and emotional information; emotion recognition means for collecting the user's emotions in real time using voice analysis and face recognition technology and analyzing them using an emotion engine; selection means for selecting optimal ingredients, recipes, and dishes based on the user's input information and emotional information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; order receiving means for accepting a delivery request for the suggested dishes; and collaboration means for coordinating with a delivery service to confirm the order and notify the user of the delivery progress. This enables optimal meal suggestions and delivery requests to be made taking into account the user's physical condition, preferences, and emotional information.

[2049] "Input means" refers to a device or mechanism that allows a user to input information about their physical condition, food preferences, and emotional information into the system.

[2050] "Emotion recognition means" refers to a function or device that uses voice analysis or face recognition technology to collect user emotions in real time and analyzes them using an emotion engine.

[2051] The "selection means" refers to a function or device for selecting optimal ingredients, recipes, and dishes based on the user's physical condition, food preferences, allergy information, and emotional information.

[2052] The "suggestion means" refers to a function or device for visually or audibly suggesting selected ingredients, recipes, and dishes to the user.

[2053] The "order receiving means" refers to a function or device that accepts the operations required for the user to request delivery of the selected dish.

[2054] The "cooperation means" refers to a function or device that cooperates with a delivery service to confirm an order and notify the user of the progress of delivery.

[2055] "Ingredients" are raw materials used to prepare a dish, and are selected based on the user's physical condition, food preferences, and allergy information.

[2056] A "recipe" is a manual showing how to cook a dish, suggesting the best ingredients and cooking methods for the user.

[2057] A "dish" is food that is cooked using selected ingredients and served to the user.

[2058] An "emotion engine" is software or algorithms that analyze a user's emotions from voice, facial expressions, text input, etc.

[2059] The "database" is a data storage system for managing and storing information such as a user's physical condition, food preferences, dietary history, and emotional history.

[2060] The "delivery service" is a service that delivers the food selected by the user to a specified location.

[2061] "Progress" is status information that indicates the stage at which the delivery request is at, such as order received, cooking, delivery in progress, or delivery completed.

[2062] An "application program interface (API)" is an interface that allows different software programs to share functions and exchange data.

[2063] In the embodiment of the present invention, the flow of a system for realizing an application example will be specifically shown.

[2064] System Overview

[2065] The system begins with the user entering information about their physical condition, food preferences, and emotions using a device such as a smartphone. The device then uses a camera and microphone to collect the user's emotions in real time and analyzes them using an EmotionEngine (emotion recognition engine). This information is sent to a server, which then queries a FoodDatabase (a database of ingredients and recipes) to select the most suitable ingredients, recipes, and dishes. The system then presents the selected information to the user and accepts a delivery request for the dishes selected by the user. Finally, the system confirms the order using a delivery service API and notifies the user of the progress in real time.

[2066] Program processing overview

[2067] 1. Launch the app and log in

[2068] The user launches the app on their smartphone and logs in using their LINE or Yahoo! account.

[2069] 2. Input of user information and emotion information

[2070] The device asks the user to input their physical condition, food preferences, allergy information, and emotional information. Emotional information is collected in real time using the device's camera and microphone and analyzed by EmotionEngine.

[2071] 3. Data processing on the server

[2072] The server stores the user's physical condition, food preferences, allergy information, and emotional information in a database. It also queries the user's past eating history and emotional history, and searches the Food Database to select the most suitable ingredients, recipes, and dishes.

[2073] 4. Display of suggestions

[2074] The server sends the selected ingredients, recipes, and dishes in list form to the user's terminal and displays the suggestions.

[2075] 5. Executing a delivery request

[2076] The user selects from the suggested dishes and places a delivery request. The server confirms the order using the delivery service API and notifies the device of the details.

[2077] 6. Order Confirmation and Tracking

[2078] The terminal displays order confirmation information to the user and notifies them of delivery progress in real time.

[2079] Hardware and software used

[2080] Hardware: Smartphone (camera, microphone, network connection), server

[2081] Software: EmotionEngine (emotion recognition engine), FoodDatabase (SQL database), DeliveryAPI (delivery service API)

[2082] Specific examples

[2083] For example, consider a case where a user is feeling depressed during the rainy season and wants to eat something sweet. The user launches the app and logs in with LINE. They enter "Physical condition: feeling depressed," "Food preference: sweets," and "Allergies: none." The smartphone's camera and microphone are used to recognize emotions, and the emotional information is analyzed using EmotionEngine. Based on this information, the server makes appropriate suggestions, such as chocolate cake, and requests delivery of the dish selected by the user. The server then confirms the order using the delivery service API and notifies the user of the progress in real time.

[2084] Prompt Sentence Examples

[2085] "If a user says they're feeling down and want something sweet, suggest the best ingredients, recipes, and dishes. Also, offer delivery options."

[2086] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2087] Step 1:

[2088] The user launches the app on their smartphone and logs in by entering their account information on the login screen.

[2089] Input: Account information (ID, password)

[2090] Specific operation: The user taps the app to launch it and enters their LINE or Yahoo! authentication information on the login screen.

[2091] Output: Login success message, transition to the next input screen

[2092] Step 2:

[2093] The terminal prompts the user to enter physical condition, food preferences, allergy information, and emotional information.

[2094] Input: Enter your physical condition, food preferences, and allergy information in the input form

[2095] Specific operation: The user enters information about their physical condition, food preferences, and allergies into an input form. The device's camera and microphone collect the user's facial expressions and voice.

[2096] Output: Input information, emotional data collected in real time

[2097] Step 3:

[2098] The emotional information collected by the device is sent to EmotionEngine for emotional analysis.

[2099] Input: Emotion information (facial expression data, voice data)

[2100] Specific operation: The device calls the EmotionEngine and analyzes the collected emotional information in real time.

[2101] Data processing: Analysis of voice and facial expression data, identification of emotional state (e.g., depressed, happy, etc.)

[2102] Output: Emotional state data as analysis result

[2103] Step 4:

[2104] The terminal transmits information on physical condition, food preferences, allergies, and emotions to the server.

[2105] Input: Physical condition information, food preferences, allergy information, emotional state data

[2106] Specific operation: The device saves the entered data in temporary storage and sends it to the server as an HTTP request.

[2107] Output: Dataset of user information received by the server

[2108] Step 5:

[2109] The server stores the received user information in a database and selects optimal ingredients, recipes, and dishes by referencing the user's past eating history and emotional history.

[2110] Input: User information (physical condition, food preferences, allergies, emotional state), past dietary history, emotional history

[2111] What happens: The server executes a database search query to extract the best ingredients, recipes, and dishes from the FoodDatabase.

[2112] Data operations: performing search queries, filtering and ranking data

[2113] Output: A list of selected ingredients, recipes, and dishes

[2114] Step 6:

[2115] The server sends the selected optimal ingredients, recipes, and dishes to the user's terminal, which then displays the suggestions in list form.

[2116] Input: List of selected ingredients, recipes, and dishes

[2117] Specific operation: The server generates the selection result in JSON format and sends it to the device. The device updates the UI to display the list.

[2118] Output: The list of suggestions displayed on the user's device

[2119] Step 7:

[2120] The user selects the desired dish from the suggested list and places a delivery request.

[2121] Input: User's selected dish

[2122] Specific operation: The user selects the desired dish from the list of suggestions by tapping it. The selected dish information is sent to the server.

[2123] Output: Food selection information

[2124] Step 8:

[2125] The server confirms the order using the delivery service API and notifies the user of the delivery progress.

[2126] Input: Selected dish information, user's delivery address information

[2127] Specific operation: The server calls the delivery service API, sends the order information and confirms the order, collects delivery status information and sends it to the user's device.

[2128] Output: Order confirmation message, delivery progress

[2129] Step 9:

[2130] The terminal will notify the user of order confirmation information and real-time delivery progress.

[2131] Input: Order confirmation message, delivery progress

[2132] Specific behavior: The device receives a notification from the server and displays the information to the user using a notification popup or status bar.

[2133] Output: Delivery confirmation and progress notification to the user

[2134] 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.

[2135] 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.

[2136] 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.

[2137] 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.

[2138] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[2139] 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.

[2140] 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).

[2141] 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.

[2142] 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."

[2143] 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.

[2144] 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).

[2145] 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.

[2146] 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.

[2147] 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.

[2148] 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.

[2149] 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.

[2150] 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.

[2151] 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.

[2152] 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.

[2153] 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.

[2154] 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.

[2155] The following is further disclosed regarding the above embodiment.

[2156] (Claim 1)

[2157] an input means for a user to input information about physical condition and food preferences;

[2158] a selection means for selecting optimal ingredients, recipes, and dishes based on user input information;

[2159] suggestion means for suggesting the selected ingredients, recipes, and dishes to the user;

[2160] an order receiving means for receiving a delivery request for the proposed dishes;

[2161] A means of cooperation with delivery services to confirm orders and notify delivery progress;

[2162] A system including:

[2163] (Claim 2)

[2164] 2. The system according to claim 1, further comprising a selection means for storing the user's input information in a database and selecting optimal ingredients, recipes, and dishes by referring to the user's past meal history.

[2165] (Claim 3)

[2166] The system according to claim 1, further comprising a linking means for linking using an API of a delivery service and confirming an order.

[2167] "Example 1"

[2168] (Claim 1)

[2169] an input means for a user to input information about physical condition and food preferences;

[2170] a storage means for storing user input information;

[2171] a selection means for selecting optimal ingredients, cooking methods, and dishes based on the stored information;

[2172] a suggestion means for suggesting the selected ingredients, cooking methods, and dishes to a user;

[2173] an order receiving means for receiving a delivery request for the proposed dishes;

[2174] A means of integration to confirm orders using the delivery service's API and notify delivery progress;

[2175] A system including:

[2176] (Claim 2)

[2177] 2. The system according to claim 1, further comprising a selection means for storing the user's input information in a database and selecting optimal ingredients, cooking methods, and dishes by referring to the user's past meal history.

[2178] (Claim 3)

[2179] The system according to claim 1, further comprising a linking means for linking using an API of a delivery service and confirming an order.

[2180] "Application Example 1"

[2181] 2. Extract the novel parts from the application example description.

[2182] 3. Combine the extracted new part into the original claim.

[2183] 4. Convert proper names and proper titles into generic names and superordinate expressions.

[2184] (Claim 1)

[2185] an input means for a user to input information about physical condition and food preferences;

[2186] a selection means for selecting optimal ingredients, recipes, and dishes based on user input information;

[2187] suggestion means for suggesting the selected ingredients, recipes, and dishes to the user;

[2188] an order receiving means for receiving a delivery request for the proposed dishes;

[2189] A means of cooperation with delivery services to confirm orders and notify delivery progress;

[2190] Tracking means to notify the user of the delivery progress in real time as selected by the user;

[2191] A system including:

[2192] (Claim 2)

[2193] 2. The system according to claim 1, further comprising a selection means for storing the user's input information in a database and selecting optimal ingredients, recipes, and dishes by referring to the user's past meal history.

[2194] (Claim 3)

[2195] The system according to claim 1, further comprising a linking means for linking using an external API of a delivery service and confirming an order.

[2196] I wrote it according to the format. I didn't write anything other than this format. That's all.

[2197] "Example 2: Combining Emotion Engines"

[2198] (Claim 1)

[2199] an input means for a user to input information about physical condition and food preferences;

[2200] emotion recognition means for analyzing input emotion information;

[2201] A selection means for selecting optimal ingredients, recipes, and dishes based on user input information and emotion information;

[2202] suggestion means for suggesting the selected ingredients, recipes, and dishes to the user;

[2203] an order receiving means for receiving a delivery request for the proposed dishes;

[2204] A means of cooperation with delivery services to confirm orders and notify delivery progress;

[2205] A system including:

[2206] (Claim 2)

[2207] 2. The system according to claim 1, further comprising a selection means for storing the user's input information in a database and selecting optimal ingredients, recipes, and dishes by referring to the user's past eating history and emotional history.

[2208] (Claim 3)

[2209] The system according to claim 1, further comprising a linking means for linking using an API of a delivery service and confirming an order.

[2210] "Application example 2 when combining emotion engines"

[2211] (Claim 1)

[2212] an input means for a user to input information about physical condition, food preferences, and emotional information;

[2213] An emotion recognition means that uses voice analysis and facial recognition technology to collect user emotions in real time and analyze them using an emotion engine;

[2214] A selection means for selecting optimal ingredients, recipes, and dishes based on user input information and emotion information;

[2215] suggestion means for suggesting the selected ingredients, recipes, and dishes to the user;

[2216] an order receiving means for receiving a delivery request for the proposed dishes;

[2217] A means of cooperation with delivery services to confirm orders and notify delivery progress;

[2218] A system including:

[2219] (Claim 2)

[2220] 2. The system according to claim 1, further comprising a selection means for storing the user's input information and emotional information in a database and selecting optimal ingredients, recipes, and dishes by referring to the user's past eating history and emotional history.

[2221] (Claim 3)

[2222] 2. The system according to claim 1, further comprising a linking means for linking using an application program interface provided by the delivery service and confirming the order. [Explanation of symbols]

[2223] 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 input means for a user to input information about physical condition and food preferences; a selection means for selecting optimal ingredients, recipes, and dishes based on user input information; suggestion means for suggesting the selected ingredients, recipes, and dishes to the user; an order receiving means for receiving a delivery request for the proposed dishes; A means of cooperation with delivery services to confirm orders and notify delivery progress; A system including:

2. 2. The system according to claim 1, further comprising a selection means for storing the user's input information in a database and selecting optimal ingredients, recipes, and dishes by referring to the user's past meal history.

3. The system according to claim 1, further comprising a linking means for linking using an API of a delivery service and confirming an order.

Images