System

Abstract

A system is provided.SOLUTION: A system, comprising: means for a user to input his / her allergy information; means for a terminal to verify and store the inputted allergy information; means for the terminal to photograph an appearance of a store and identify the store; means for a server to obtain menu information of the identified store; means for the server to filter menus based on the allergy information of the user; and means for the terminal to display the filtered menu information.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The present invention aims to alleviate the difficulties faced by people with food allergies in determining what to eat when dining out. Current methods require users to check the menu after entering a restaurant, ask a waiter, or search for allergy information online. However, these methods are time-consuming and inconvenient because each restaurant labels its food differently. In particular, when there are multiple allergens, it becomes even more difficult for users to find a menu that suits them. The present invention aims to solve these problems and provide a means for users to easily check the appropriate menu before entering a restaurant. [Means for solving the problem]

[0005] The present invention solves the problem using a user's smartphone app by following these steps:

[0006] 1. Provide a means for users to enter their own allergy information and register allergy ingredients.

[0007] 2. Provide a means for the device to validate entered allergy information and store that information in a local database or on a server.

[0008] 3. The device takes a photo of the store's exterior and uses image analysis technology to provide a means to identify the store.

[0009] 4. The server retrieves the menu information of the identified restaurant from the database and provides a means to filter the menu based on the user's allergy information.

[0010] 5. Provide a means for returning filtered menu information to the terminal and for the terminal to display the information in a visually understandable format.

[0011] By using the above methods, users can easily check menu items that do not contain ingredients that they are allergic to before entering a restaurant, greatly improving the peace of mind and convenience of eating out.

[0012] A "user" is an individual who uses a smartphone app to register their own allergy information and check allergy-friendly menu items when eating out.

[0013] A "terminal" is a portable device such as a smartphone used by a user, which registers allergy information, takes store images, analyzes the images, and displays menu information.

[0014] The "server" is a central data management system that receives store information sent from the terminal, obtains corresponding menu information, and filters the menu based on the user's allergy information.

[0015] "Allergy information" is information indicating the ingredients to which the user has allergies (for example, eggs, wheat, milk, etc.).

[0016] "Photographing" refers to the act of acquiring image data using the camera function of the terminal.

[0017] "Store identification" is the process of analyzing the image captured by the terminal and identifying the relevant restaurant.

[0018] "Menu information" is a list of the dishes and drinks offered by the restaurant and information about their ingredients.

[0019] "Filtering" is the process of selecting items from the menu information that do not contain the relevant allergen based on the allergy information registered by the user.

[0020] "Image analysis" is a technology that extracts specific information (such as store name or logo) from images taken by a device.

[0021] "Allergy icons" are standardized symbols that visually represent specific allergens.

[0022] A "local database" is a database stored within a device such as a smartphone, and holds data such as a user's allergy information. [Brief explanation of the drawings]

[0023] [Figure 1] 1 is a conceptual diagram showing an example of the configuration of a data processing system according to a first embodiment. [Figure 2] 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device according to a first embodiment. [Figure 3] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a second embodiment. [Figure 4]FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and smart glasses according to a second embodiment. [Figure 5] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a third embodiment. [Figure 6] FIG. 11 is a conceptual diagram showing an example of main functions of a data processing device and a headset-type terminal according to a third embodiment. [Figure 7] FIG. 10 is a conceptual diagram showing an example of the configuration of a data processing system according to a fourth embodiment. [Figure 8] FIG. 10 is a conceptual diagram showing an example of main functions of a data processing device and a robot according to a fourth embodiment. [Figure 9] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 10] 1 shows an emotion map onto which multiple emotions are mapped. [Figure 11] FIG. 3 is a sequence diagram showing a processing flow of the data processing system according to the first embodiment. [Figure 12] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 1. [Figure 13] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system according to the second embodiment when an emotion engine is combined. [Figure 14] FIG. 10 is a sequence diagram showing the flow of processing in the data processing system in Application Example 2 when an emotion engine is combined. DETAILED DESCRIPTION OF THE INVENTION

[0024] 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.

[0025] First, the terms used in the following description will be explained.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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."

[0031] [First embodiment]

[0032] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0033] 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.

[0034] 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).

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0040] 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.

[0041] 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.

[0042] 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.

[0043] 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."

[0044] An example of this system will be described in detail below. In the following example, a system is provided that allows users to register their own allergy information through a smartphone application and visually check menu information that accommodates allergies by taking a photo of the exterior of a restaurant when eating out.

[0045] User enters allergy information

[0046] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0047] Photographing and analyzing store exteriors

[0048] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0049] The server obtains store information and performs filtering.

[0050] Based on the received store information, the server retrieves the menu and allergy information for the specific store from the database. Next, based on the allergy information (e.g., egg, wheat, milk, etc.) registered in advance by the user, it filters out menu items that do not contain the relevant ingredients. This filtered menu information is then returned to the terminal in a format that is easy for the user to understand.

[0051] User Interface Display

[0052] The device receives the menu information returned from the server and visually displays it on the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. For example, "Caesar Salad (Egg-Free, Wheat-Free)" and "Fruit Parfait (Egg-Free, Wheat-Free)" are displayed with photos.

[0053] Specific use cases

[0054] For example, a user (Hanako) registers her egg and wheat allergies in a smartphone app. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone. As a result, Hanako can check the menu items that are suitable for her before entering the store.

[0055] In this way, the present invention allows users to safely select meals based on allergy information when dining out, providing convenience and peace of mind.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app.

[0059] Step 2:

[0060] The device validates the entered allergy information, ensuring that the information is in the correct format and, if there are no problems, stores the information in a local database or on a server.

[0061] Step 3:

[0062] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0063] Step 4:

[0064] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0065] Step 5:

[0066] The device sends a request including specific store information to the server, specifically, data including the store's name, location information, etc.

[0067] Step 6:

[0068] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0069] Step 7:

[0070] The server filters the menu based on the user's allergy information, specifically selecting menu items that do not contain the allergic ingredients.

[0071] Step 8:

[0072] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0073] Step 9:

[0074] The terminal receives the data returned from the server and verifies the integrity and accuracy of the data.

[0075] Step 10:

[0076] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. Users can visually check the menu and select meals that suit them.

[0077] Through the above steps, this system allows users to easily check allergy-friendly menu items when dining out and safely select meals.

[0078] Example 1

[0079] 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."

[0080] With the conventional method of managing allergy information when eating out, users had to check directly with the staff to find out what menu items were suitable for them, which was time-consuming and prone to mistakes. This made it difficult for users with allergies to enjoy eating out with peace of mind. Furthermore, it was difficult for restaurants to provide allergy information to all users, which resulted in situations where users were unable to safely select their meals.

[0081] 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.

[0082] In this invention, the server includes means for retrieving the menu information and allergy information of the identified restaurant from a database, means for filtering the menu based on the user's allergy information and returning the filtered menu information to the terminal, and means for visually displaying the filtered menu information. This allows users to input their own allergy information in advance and instantly check the menu that suits them simply by taking a photo of the restaurant's exterior.

[0083] A "user" is a person who uses the system to input their own allergy information and check restaurant menu information.

[0084] A "terminal" is an electronic device owned by a user, which has functions such as taking pictures, transmitting data, and displaying information.

[0085] "Allergy information" refers to the type and information of allergies a user has to specific food ingredients.

[0086] "Store exterior" refers to image data capturing the exterior appearance of a restaurant.

[0087] "Image analysis" is a technology that recognizes characters, logos, etc. from photographed images of store exteriors and extracts specific information.

[0088] A "server" is a computer system that receives information sent from users and terminals, retrieves menu information for specific restaurants from a database, and performs processing.

[0089] A "database" is an information system that structurally stores and manages menu information and allergy information for a specific restaurant.

[0090] "Filtering" is a process of selecting specific menu items that do not contain ingredients that match the user's allergy information.

[0091] "Visually displaying" refers to displaying information on the device screen in an easy-to-understand format.

[0092] "Allergy icons" are visual symbols used to indicate specific allergens.

[0093] A specific embodiment of this invention will be described in detail. This system allows users to register their allergy information through a smartphone application and visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. The main hardware and software used in this invention are a smartphone, a camera, a cloud server, a database, and image analysis technology.

[0094] Enter and save allergy information

[0095] First, the user opens the smartphone app and enters the ingredients they are allergic to (e.g., eggs, wheat, milk, etc.). This information is then stored in the smartphone's local database or on a cloud server. Specific databases suitable for use include SQLite (local) and Firebase (cloud). This method allows the user to change or add information later.

[0096] Photographing and analyzing store exteriors

[0097] The user takes a photo of the exterior of a restaurant using their smartphone camera. This image is saved in the device's internal buffer. The restaurant is then identified using image analysis technology. Specifically, OCR (optical character recognition) and logo recognition technology are used. Libraries such as TensorFlow can be used for image analysis. This analyzed restaurant information is then sent to the server.

[0098] Server-based menu information retrieval and filtering

[0099] The server queries the database based on the received store information to obtain the menu information and allergy information for the specific store. The server uses a database such as MongoDB. Next, it filters the menu based on the user's pre-registered allergy information. The filtered results are formatted in JSON format and sent back to the user's device.

[0100] Displaying menu information

[0101] The device receives the menu information returned from the server and parses the JSON data. The received menu information is displayed in a visually easy-to-understand format in the user interface. For example, it can be displayed in list format using UI components such as RecyclerView, and a unified allergy icon is displayed for each menu item. This allows users to check the menu items that are suitable for them at a glance.

[0102] Specific examples

[0103] For example, a user (let's call her Hanako) registers her egg and wheat allergies in a smartphone app. She takes a photo of the exterior of a nearby cafe, and the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone, allowing her to check the menu items that are suitable for her before entering the store.

[0104] Examples of prompts for generative AI models

[0105] Here are some examples of prompts to input to a generative AI model:

[0106] Please explain in concrete steps the program processing flow for a system that allows users to register their allergy information through a smartphone application and then visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. Please provide a detailed explanation of all the processes involved, from the user entering their allergy information and taking a photo of the restaurant's exterior, to data processing on the server and displaying it to the user.

[0107] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0108] Step 1:

[0109] The user launches the smartphone app and enters their allergy information. Specifically, the user opens the app's input screen, selects the allergen (e.g., egg, wheat, milk, etc.), and presses the "Save" button. This input information is collected on the device and stored in a local database (e.g., SQLite) or a cloud database (e.g., Firebase). The input is the user's allergy information, and the output is the saved allergy information data.

[0110] Step 2:

[0111] A user stands in front of a restaurant and uses the app's camera function to take a photo of the restaurant's exterior. Specifically, the user taps the camera button to take a photo of the restaurant's exterior. The captured image is saved in the device's internal buffer. The input is the restaurant's exterior image, and the output is the image data saved in the internal buffer.

[0112] Step 3:

[0113] The device analyzes the captured image of the store's exterior to identify the store. Specifically, the device uses image analysis technology (e.g., OCR or logo recognition) to extract text and logos from the image. Libraries such as TensorFlow can be used for this process. The device then generates identified store information and sends it to the server. The input is the image data stored in the internal buffer, and the output is the identified store information.

[0114] Step 4:

[0115] Based on the identified store information, the server queries the database to obtain the store's menu information and its allergy information. The server uses a database such as MongoDB to search for menu information corresponding to a specific store name. The input is the identified store information, and the output is the obtained menu information and its allergy information.

[0116] Step 5:

[0117] The server filters the menu based on the user's allergy information. Specifically, the server selects items from the menu that do not contain any ingredients that match the user's allergy information. The filtered menu information is formatted in JSON format and sent back to the user's device. The input is the acquired menu information and the user's allergy information, and the output is the filtered menu information.

[0118] Step 6:

[0119] The terminal receives the filtered menu information returned from the server. The terminal parses the received JSON data and displays it in the user interface. Specifically, it displays the menu information in list format using UI components such as RecyclerView, and visually indicates allergic ingredients in each menu using standardized allergy icons. The input is the filtered menu information, and the output is the visually displayed menu information.

[0120] (Application example 1)

[0121] 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."

[0122] In modern society, there is a demand for a way to easily search and check menu items that accommodate allergies when dining out. In particular, there is a need for a system that allows users with allergies to select menu items with peace of mind when dining out. Furthermore, as the number of restaurants increases and they offer different menus, it is becoming more difficult for users to quickly find a menu that suits them. This has led to a demand for a system that reduces users' health risks and provides a convenient and safe dining experience.

[0123] 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.

[0124] In this invention, the server includes: means for a user to input his / her own allergy information; means for the terminal to verify and save the input allergy information; means for the terminal to photograph the exterior of a store and identify the store; means for the terminal to identify the store using image analysis technology; means for the server to obtain menu information for the identified store; means for the server to filter menus based on the user's allergy information; and means for the terminal to display the filtered menu information together with a unified allergy icon. This allows users to quickly check menus that cater to their allergies based on the photographed exterior image of the store.

[0125] The "means for the user to input his / her own allergy information" is an interface that allows the user to input his / her own allergy information into the terminal.

[0126] "Means for verifying and saving allergy information entered by the terminal" refers to the function by which the terminal checks the allergy information entered by the user and saves it appropriately in a database.

[0127] "Means for the terminal to photograph the exterior of the store and identify the store" refers to a function that uses the camera function of the terminal to photograph the exterior of the store and identify the store based on that image.

[0128] "Means by which the terminal identifies a store using image analysis technology" refers to technologies used to analyze captured images to identify a store, such as OCR or logo recognition.

[0129] The "means for the server to obtain menu information for a specified store" is a function that allows the server to obtain menu information for a specified store from a database or the web.

[0130] The "means for the server to filter the menu based on the user's allergy information" is a function in which the server selects menu items based on the user's allergy information and extracts menu items that do not contain harmful substances.

[0131] "Means for the terminal to display filtered menu information together with a unified allergy icon" is a function that allows the terminal to display filtered menu items using a unified icon that is easy for the user to understand.

[0132] This invention is a system that allows users to safely select meals based on their own allergy information when dining out. The system has the function of acquiring menu information for a restaurant by having the user input their own allergy information and taking a photo of the restaurant's exterior when dining out, and then displaying a menu that matches the user's allergy information.

[0133] A means for users to enter allergy information

[0134] Users open the smartphone application and enter their allergy ingredients (e.g., eggs, wheat, milk, etc.). The entered allergy information is saved in the device's local database or on the server. The saved information can be changed or added to later by the user.

[0135] A means for the device to photograph and identify the store's exterior

[0136] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and identifies the restaurant using image analysis technology such as Google Cloud Vision API. This identified restaurant information is then sent to the server.

[0137] A method for the server to obtain and filter store information

[0138] The server retrieves the menu for a specific restaurant from its database based on the restaurant information it receives. It then filters menu items containing specific ingredients based on the allergy information previously registered by the user. For example, if a user is allergic to eggs and wheat, the server extracts only menu items that do not contain these ingredients.

[0139] A means for the device to display filtered menu information

[0140] The filtered menu information is sent back to the device and displayed on the smartphone application's user interface. The menu information includes standardized allergy icons, allowing users to easily identify menu items suitable for them.

[0141] Specific examples

[0142] For example, a user (hereinafter referred to as "User A") registers in a smartphone app that he or she has egg and wheat allergies. When User A takes a photo of the exterior of a nearby restaurant, the image is analyzed and the specific restaurant is identified. This information is sent to a server, which retrieves the restaurant's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on User A's smartphone. As a result, User A can check the menu that suits him or her before entering the restaurant.

[0143] Prompt Sentence Examples

[0144] Below is an example prompt for a specific generative AI model that takes an image of a restaurant's exterior and identifies it using the Google Cloud Vision API.

[0145] "Analyze the image of the store exterior to obtain the name of the target restaurant."

[0146] By using this system, users can choose their meals with peace of mind when eating out, providing convenience and safety.

[0147] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0148] Program processing flow

[0149] Step 1:

[0150] The user opens the smartphone application and enters their allergy information. The entered allergy information is saved in the device's local database. Specifically, the user enters the allergens they are allergic to, such as eggs, wheat, or milk, into a form within the app and presses the save button. This input information is saved in a local database such as SQLite.

[0151] Input: User allergy information (e.g., egg, wheat, milk)

[0152] Data processing: Save allergy information from form input to local database

[0153] Output: Allergy information stored in a local database

[0154] Step 2:

[0155] A user takes a photo of the exterior of a restaurant using their smartphone camera. The captured image is saved in the device's internal buffer. The user then presses the camera button to capture the exterior of the restaurant. At this point, the image file is stored in the device's memory.

[0156] Input: Store exterior image

[0157] Data processing: Save image files to internal buffer

[0158] Output: Saved image file

[0159] Step 3:

[0160] The device uses the Google Cloud Vision API to analyze the captured image and identify the store. This analysis process extracts the store's name and other identifying information. Specifically, the device uploads the captured image and receives the results of OCR and logo recognition.

[0161] Input: Store exterior image

[0162] Data processing: Identifying stores using image analysis technology (Google Cloud Vision API)

[0163] Output: Identified store information (e.g. store name, address)

[0164] Step 4:

[0165] The server receives the information about the identified store and retrieves the menu information for that store from the database. The server executes an appropriate query to the database based on the received store information to retrieve the menu information.

[0166] Input: Identified store information

[0167] Data manipulation: Performing database queries

[0168] Output: Retrieved menu information

[0169] Step 5:

[0170] The server filters the acquired menu information based on the user's allergy information. Specifically, the server takes the user's allergy information into consideration and extracts menu items that do not contain harmful substances.

[0171] Input: User allergy information, menu information

[0172] Data processing: filtering menu information

[0173] Output: Filtered menu information

[0174] Step 6:

[0175] The device will display the filtered menu information along with a unified allergy icon. Specifically, the filtered menu information will be displayed on the device's user interface, allowing users to check the appropriate menu at a glance.

[0176] Input: Filtered menu information

[0177] Data processing: Integrating menu information and allergy icons

[0178] Output: Menu information displayed in the user interface

[0179] In this way, the user can quickly check the menu items that cater to his or her allergies based on the photographed image of the exterior of the store.

[0180] 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.

[0181] An example of this system will be described in detail below. In the following example, a system is provided that allows a user to register their own allergy information via a smartphone application, and further recognizes the user's emotions and provides appropriate menu information when dining out.

[0182] User enters allergy information

[0183] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0184] Photographing and analyzing store exteriors

[0185] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0186] Acquiring user emotion information

[0187] The emotion engine installed on the device extracts emotional information from the user's facial expressions and tone of voice based on sensor data from cameras, microphones, etc. This emotional information is then sent to the server along with allergy information.

[0188] The server obtains store information and performs filtering.

[0189] The server retrieves the menu information for a specific restaurant from a database based on the restaurant information received. It then filters out menu items that do not contain any allergens (e.g., eggs, wheat, milk, etc.) based on the allergy information registered by the user in advance. It also takes into account the user's emotional information and adjusts the priority and display method of the filtering results.

[0190] User Interface Display

[0191] The device receives the menu information returned from the server and visually displays it in the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. Specific menu items may also be recommended based on emotional information. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed preferentially.

[0192] Specific use cases

[0193] For example, a user (Hanako) registers in a smartphone app that she has egg and wheat allergies. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is sent back to the device and displayed on Hanako's smartphone. If Hanako's facial expression indicates that she is stressed, menu items such as "herbal tea" that has a relaxing effect are recommended.

[0194] In this way, the present invention allows users to make safe meal choices when dining out based on allergy information, and can even take emotional state into account to provide a pleasant dining experience.

[0195] The processing flow will be explained below.

[0196] Step 1:

[0197] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app. This information is stored in the device's local database or on the server.

[0198] Step 2:

[0199] The device verifies the allergy information entered, confirms that the information entered is in the correct format, and if there are no problems, proceeds to save the information.

[0200] Step 3:

[0201] A user takes a photo of the exterior of a restaurant using their smartphone camera. The device stores the captured image data in an internal buffer.

[0202] Step 4:

[0203] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0204] Step 5:

[0205] The device sends the specified store information to the server. The request includes the store name, location, and other information.

[0206] Step 6:

[0207] The device's emotion engine extracts emotional information from the user's facial expressions and tone of voice, which indicates states such as stress, joy, and excitement, and transmits this information to the server.

[0208] Step 7:

[0209] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0210] Step 8:

[0211] The server filters the menu based on the user's allergy information, for example, selecting menu items that do not contain eggs or wheat, and also considers the user's emotional information, prioritizing menu items that correspond to a specific emotional state.

[0212] Step 9:

[0213] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0214] Step 10:

[0215] The terminal validates the data received from the server and checks the consistency and accuracy of the menu information.

[0216] Step 11:

[0217] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. The system also takes into account the user's emotional information and recommends menu items such as "herbal tea" when relaxation is needed.

[0218] Through the above steps, the system not only allows users to easily and safely check allergy-friendly menu items when eating out, but also helps users select more appropriate menu items by taking into account the user's emotional state.

[0219] Example 2

[0220] 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."

[0221] Conventional restaurant selection support systems have the ability to filter menus based on the user's allergy information, but lack the ability to provide menus that take the user's emotional information into consideration. This makes it difficult to support users in choosing meals that satisfy them psychologically when eating out, and there is a need for an integrated approach to allergy and emotional information. Furthermore, there are challenges in properly managing the information entered by the user and improving the accuracy of restaurant identification through exterior image analysis.

[0222] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for acquiring menu information of the identified restaurant, a means for filtering menus based on the user's allergy information, and a means for adjusting the filtering result based on the user's emotional information. This allows the user to select a menu that is safe and psychologically satisfying when eating out by taking the user's allergy information and emotional information into consideration in an integrated manner.

[0223] Below are definitions of important words.

[0224] "User" refers to an individual who uses this system.

[0225] "Allergy Information" refers to information about a user's self-reported allergic reactions to specific ingredients.

[0226] "Terminal" refers to a mobile computing device used by a user, such as a smartphone or tablet.

[0227] "Input means" refers to the interface and functions required for users to input allergy information into the system using a terminal.

[0228] "Means to validate and store" refers to the ability to accurately verify entered allergy information and store it in a local or remote database.

[0229] "Means for taking photographs" refers to the function of acquiring images using the camera function built into the terminal.

[0230] "Image analysis technology" refers to technology for extracting and identifying useful information from captured images.

[0231] "Means for identifying" refers to the function of extracting and identifying specific information (e.g., store information) using image analysis technology.

[0232] "Sensor data" refers to digital data obtained from sensors such as cameras and microphones installed on devices.

[0233] "Emotional information" refers to information that analyzes and determines the user's emotional state (e.g., joy, sadness, stress) based on sensor data.

[0234] "Means for transmitting" refers to a communication function for transmitting information (e.g., store information, emotional information) from a terminal to a server.

[0235] A "server" refers to a computer system that communicates with terminals via a network and performs data processing, menu information acquisition, filtering, etc.

[0236] "Menu information" refers to information about the food and drinks served at a restaurant.

[0237] "Filtering means" refers to the ability to sort data (e.g., menu items) based on specific conditions and exclude unwanted items.

[0238] "Adjustment means" refers to a function that changes the display order or recommended items based on the filtering results, taking into account specific conditions (e.g., emotional information).

[0239] "Means for visual display" refers to a function that displays data on the terminal screen in a format that can be visually understood by the user.

[0240] The present invention relates to a system that allows users to register their own allergy information and provides appropriate menu information when dining out based on emotional information. This system involves the user inputting allergy information, photographing and analyzing the exterior of the restaurant, acquiring emotional information, filtering and adjusting the information by the server, and displaying the filtered results on a terminal.

[0241] First, when a user opens the smartphone application, an interface for entering their allergy ingredients (e.g., eggs, wheat, milk, etc.) is displayed. The user manually enters this information and presses the save button. The device (smartphone) then stores this information in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0242] Next, users can take a photo of the restaurant's exterior with their smartphone camera. The device stores the captured image in an internal buffer and then analyzes it using OCR (optical character recognition) and logo recognition technology to identify the restaurant. This analysis is performed using image analysis software such as Tesseract-OCR and Google Cloud Vision API.

[0243] Store information obtained through image analysis is sent from the device to a server. The device's built-in emotion engine then acquires the user's emotional information based on sensor data from the camera, microphone, and other devices. For example, OpenCV is used for facial expression analysis, and a different algorithm is applied to voice tone analysis. This emotional information is also sent to the server.

[0244] The server retrieves the menu information for the relevant store from a database (e.g., PostgreSQL, MySQL) based on the received store information. It then filters the menu based on the user's allergy information, excluding menu items containing allergens. The filtered results are then adjusted to take into account the user's emotional information. For example, if it is determined that the user is feeling stressed, adjustments will be made to prioritize the display of menu items with a relaxation effect (e.g., herbal tea).

[0245] Finally, the filtered and adjusted menu information is sent back to the device, which receives it and displays it in a visually friendly user interface. The displayed menu includes standardized allergy icons, allowing users to see at a glance which menu is suitable for them.

[0246] Specific use cases

[0247] For example, a user named Hanako registers her egg and wheat allergies in a smartphone application. When she takes a photo of the exterior of a nearby cafe, the device analyzes the image to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. If the emotion engine then determines that Hanako is feeling stressed, it will recommend a "herbal tea" with a relaxing effect.

[0248] Prompt Sentence Examples

[0249] Hanako registered her egg and wheat allergy information in a smartphone application and took a photo of the exterior of a nearby cafe with her camera. The server then analyzed the cafe's menu information and displayed egg- and wheat-free menu items on Hanako's smartphone. The application also determined that Hanako was feeling stressed, so it recommended a menu item with a relaxation effect.

[0250] This system allows users to make safe and satisfying food choices that take into account their allergy information and emotional state.

[0251] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0252] Step 1: The user enters their allergy information

[0253] The user opens the smartphone application and enters the ingredients to which they are allergic (eggs, wheat, milk, etc.). The allergy information entered by the user is treated as "input data." The device (smartphone) validates this input data, and if there are no problems, it stores it in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0254] Input: Allergy ingredient information entered by the user

[0255] Output: Save verified allergy information

[0256] Specific operation: When the user enters the allergens and presses the save button, the device saves the entered information in the database.

[0257] Step 2: The user takes a photo of the restaurant's exterior

[0258] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0259] Input: Restaurant exterior image

[0260] Output: Saved image data

[0261] Specific operation: The user opens the camera app, takes a picture of the restaurant's exterior, and the image is saved in the device's internal buffer.

[0262] Step 3: The device analyzes the image to identify and send store information

[0263] The device uses the images stored in the internal buffer to analyze the text and logos in the images using OCR (Optical Character Recognition) and logo recognition technology, identifies the store from the analyzed data, generates store information, and then sends the identified store information to a remote server.

[0264] Input: Saved image data

[0265] Output: Sending the identified store information

[0266] Specific operation: The device analyzes the stored image data using OCR technology, obtains store information, and sends it to the server.

[0267] Step 4: The device acquires and transmits the user's emotional information.

[0268] The emotion engine installed on the device acquires the user's emotional information based on sensor data from the camera and microphone. The acquired emotional information is analyzed using facial expression analysis technology (e.g., OpenCV) and voice analysis technology. The generated emotional information is sent to the server.

[0269] Input: Sensor data from camera and microphone

[0270] Output: Sending acquired emotion information

[0271] Specific operation: The device captures the user's facial expressions with a camera and records their voice with a microphone, analyzes this data to generate emotional information, and sends it to the server.

[0272] Step 5: The server retrieves the store menu information and performs filtering.

[0273] Based on the received store information, the server retrieves the menu information for the store from a database (e.g., PostgreSQL, MySQL), then references the user's allergy information and filters out menu items that do not contain allergens.

[0274] Input: Store information, allergy information

[0275] Output: Filtered menu information

[0276] Specific operation: The server retrieves menu information from the database and uses that information to extract items that do not contain allergens.

[0277] Step 6: The server adjusts the filtering results based on the user's emotions.

[0278] The server uses emotion information to adjust the priority of filtered menu items. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed at the top.

[0279] Input: filtered menu information, emotion information

[0280] Output: Adjusted menu information

[0281] Specific behavior: The server analyzes the emotional information and adjusts the display order of the filtered menu items.

[0282] Step 7: The device displays the filtered menu information

[0283] The device receives the filtered menu information returned from the server and displays the menu items in a visually identifiable format on the user interface. The displayed menu includes allergy icons and also provides emotion-based recommendations.

[0284] Input: Adjusted menu information

[0285] Output: Menu information to be displayed

[0286] Specific operation: Based on the menu information received by the terminal, it displays it in an easy-to-understand user interface.

[0287] (Application example 2)

[0288] 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."

[0289] Existing menu suggestion systems for dining out allow users to input and manage allergy information, but do not suggest menus that take into account the user's emotional state. This poses a problem of a lack of psychological support for users to enjoy their meals. Furthermore, there is insufficient consideration given to allowing users to easily select safe menus that are suitable for them.

[0290] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0291] In this invention, the server includes a means for acquiring the user's allergy information and emotional information, a means for photographing the exterior of a restaurant to identify the restaurant, and a means for filtering menus based on the allergy information and emotional information. This allows the user to not only select a safe menu based on their own allergy information, but also to receive menu suggestions tailored to their emotional state. Furthermore, the quality of the dining experience when eating out is improved because the user can see the menu that best suits them at a glance.

[0292] A "user" is someone who uses the system to input their allergy and emotional information and receive appropriate menu suggestions.

[0293] "Allergy information" is information about ingredients that users should avoid consuming.

[0294] "Terminal" means an electronic device that processes user input information and receives and analyzes external information in a ubiquitous computing environment.

[0295] A "store" is a facility that provides meals and is a place that users visit to eat out.

[0296] "Emotion information" is information about the user's psychological state that is recognized based on the user's facial expression, tone of voice, and the like.

[0297] A "server" is a central computing system for receiving and processing data sent from multiple terminals.

[0298] "Menu information" is a list of food and drink items served at a particular establishment.

[0299] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary data.

[0300] "Display" means providing information visually on the screen of a terminal.

[0301] A "system" is an integrated structure in which multiple devices and software work together to provide a specific function.

[0302] A "standardized allergy icon" is an allergy display symbol with a uniform design that is visually easy for users to recognize.

[0303] "Recommended Menu" refers to food and drink options that are specifically recommended based on the user's allergy and emotional information.

[0304] A specific embodiment of the present invention will be described. The system acquires allergy information and emotional information of a user and provides appropriate menu information when dining out. The details of this system are described below.

[0305] Hardware and software used

[0306] This system uses a smartphone, server, camera, and microphone as its main hardware. The software includes an image analysis engine (e.g., OpenCV), an emotion engine (e.g., emotion_engine), a server-side database system, and a menu information filtering function.

[0307] Details of data processing and calculation

[0308] Entering and confirming user allergy information

[0309] Users first enter their allergy information using a smartphone app. This information is stored in the smartphone's local database or on a cloud server. Users can also change or add to this information later.

[0310] Store exterior photography and analysis

[0311] The user takes a photo of the exterior of the restaurant they want to visit with their smartphone camera. The device acquires the captured image data and identifies the restaurant using an image analysis engine (such as OpenCV). Specifically, it identifies the restaurant's logo, sign, etc. from the image and sends this information to the server.

[0312] Acquiring emotional information

[0313] Using the smartphone's camera and microphone, emotional information is collected from the user's facial expressions and voice. An emotion engine (e.g., emotion_engine) is used for this. The acquired emotional information is sent to the server along with allergy information.

[0314] Retrieving and filtering menu information

[0315] The server retrieves the menu information of the identified restaurant from the corresponding database, then filters out safe menu items based on the user's allergy information, and further prioritizes the menu items based on the user's emotional information to determine the recommended menu.

[0316] User Interface Display

[0317] The filtered menu information is displayed on the smartphone user interface, along with standardized allergy icons, allowing users to quickly identify menu options suitable for them. Specific menu options are also recommended based on emotional information.

[0318] Specific examples

[0319] For example, suppose a user enters their allergy information (egg, wheat, etc.) into their smartphone. If the user takes a photo of the exterior of a nearby cafe and shows a stressed expression, the system will filter out menu items from that cafe that do not contain allergens, and prioritize the display of relaxation-enhancing herbal teas.

[0320] Prompt Sentence Examples

[0321] markdown

[0322] You are a UX designer responsible for designing the UI for a smartphone app where users enter allergy information and emotional state. Create a wireframe for the app that has the following features:

[0323] 1. A screen where users can enter allergens (eggs, wheat, milk, etc.)

[0324] 2. Ability to take photos of store exteriors

[0325] 3. Ability to capture emotional state from camera and microphone

[0326] 4. Menu suggestion screen based on allergy information and emotional state

[0327] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0328] Step 1:

[0329] The user launches the smartphone app and enters their allergy information. The entered information is stored in the smartphone's local database or in a cloud server. Specific inputs include "egg," "wheat," and "milk." The output of this step is the stored allergy information.

[0330] Step 2:

[0331] The user takes a photo of the exterior of the restaurant they are visiting with their smartphone camera. The device acquires the captured image data and stores it in an internal buffer. The input is an image of the restaurant's exterior, which is used for analysis in the next step. The output is the image data stored in the buffer.

[0332] Step 3:

[0333] The device analyzes the stored exterior image. It uses an image analysis engine (such as OpenCV) to identify the store's logo and sign and identify the store. The input is the image data stored in the buffer, and the output is the identified store information (store name, address, etc.). This information is sent to the server.

[0334] Step 4:

[0335] The device uses the camera and microphone to acquire the user's emotional information. An emotion engine (such as emotion_engine) is used to analyze the user's facial expressions and tone of voice to recognize their emotional state (e.g., stress, joy, etc.). The input is sensor data acquired from the camera and microphone, and the output is the recognized emotional information. This information is also sent to the server.

[0336] Step 5:

[0337] The server retrieves the menu information of the identified restaurant from the database. The input is the restaurant information, and the output is the restaurant's menu information. The server then filters the menu based on the user's allergy information. This filtering process excludes items containing allergens. The input is the menu information and allergy information, and the output is the filtered safe menu items.

[0338] Step 6:

[0339] The server then adjusts the priority of the menu items based on the emotional information. For example, if the user is feeling stressed, it will prioritize menus with a relaxation effect. The input is the filtered menu items and emotional information, and the output is a recommended menu with adjusted priorities.

[0340] Step 7:

[0341] The terminal receives the recommended menu information returned from the server and visually displays it on the user interface. Standardized allergy icons are also displayed, allowing users to check the menu that is suitable for them at a glance. The input is the recommended menu information, and the output is a visual menu list displayed on the smartphone screen.

[0342] 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.

[0343] 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.

[0344] 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.

[0345] [Second embodiment]

[0346] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0347] 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.

[0348] 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).

[0349] 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.

[0350] 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.

[0351] 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).

[0352] 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.

[0353] 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.

[0354] 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.

[0355] 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.

[0356] 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.

[0357] 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."

[0358] An example of this system will be described in detail below. In the following example, a system is provided that allows users to register their own allergy information through a smartphone application and visually check menu information that accommodates allergies by taking a photo of the exterior of a restaurant when eating out.

[0359] User enters allergy information

[0360] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0361] Photographing and analyzing store exteriors

[0362] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0363] The server obtains store information and performs filtering.

[0364] Based on the received store information, the server retrieves the menu and allergy information for the specific store from the database. Next, based on the allergy information (e.g., egg, wheat, milk, etc.) registered in advance by the user, it filters out menu items that do not contain the relevant ingredients. This filtered menu information is then returned to the terminal in a format that is easy for the user to understand.

[0365] User Interface Display

[0366] The device receives the menu information returned from the server and visually displays it on the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. For example, "Caesar Salad (Egg-Free, Wheat-Free)" and "Fruit Parfait (Egg-Free, Wheat-Free)" are displayed with photos.

[0367] Specific use cases

[0368] For example, a user (Hanako) registers her egg and wheat allergies in a smartphone app. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone. As a result, Hanako can check the menu items that are suitable for her before entering the store.

[0369] In this way, the present invention allows users to safely select meals based on allergy information when dining out, providing convenience and peace of mind.

[0370] The processing flow will be explained below.

[0371] Step 1:

[0372] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app.

[0373] Step 2:

[0374] The device validates the entered allergy information, ensuring that the information is in the correct format and, if there are no problems, stores the information in a local database or on a server.

[0375] Step 3:

[0376] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0377] Step 4:

[0378] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0379] Step 5:

[0380] The device sends a request including specific store information to the server, specifically, data including the store's name, location information, etc.

[0381] Step 6:

[0382] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0383] Step 7:

[0384] The server filters the menu based on the user's allergy information, specifically selecting menu items that do not contain the allergic ingredients.

[0385] Step 8:

[0386] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0387] Step 9:

[0388] The terminal receives the data returned from the server and verifies the integrity and accuracy of the data.

[0389] Step 10:

[0390] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. Users can visually check the menu and select meals that suit them.

[0391] Through the above steps, this system allows users to easily check allergy-friendly menu items when dining out and safely select meals.

[0392] Example 1

[0393] 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."

[0394] With the conventional method of managing allergy information when eating out, users had to check directly with the staff to find out what menu items were suitable for them, which was time-consuming and prone to mistakes. This made it difficult for users with allergies to enjoy eating out with peace of mind. Furthermore, it was difficult for restaurants to provide allergy information to all users, which resulted in situations where users were unable to safely select their meals.

[0395] 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.

[0396] In this invention, the server includes means for retrieving the menu information and allergy information of the identified restaurant from a database, means for filtering the menu based on the user's allergy information and returning the filtered menu information to the terminal, and means for visually displaying the filtered menu information. This allows users to input their own allergy information in advance and instantly check the menu that suits them simply by taking a photo of the restaurant's exterior.

[0397] A "user" is a person who uses the system to input their own allergy information and check restaurant menu information.

[0398] A "terminal" is an electronic device owned by a user, which has functions such as taking pictures, transmitting data, and displaying information.

[0399] "Allergy information" refers to the type and information of allergies a user has to specific food ingredients.

[0400] "Store exterior" refers to image data capturing the exterior appearance of a restaurant.

[0401] "Image analysis" is a technology that recognizes characters, logos, etc. from photographed images of store exteriors and extracts specific information.

[0402] A "server" is a computer system that receives information sent from users and terminals, retrieves menu information for specific restaurants from a database, and performs processing.

[0403] A "database" is an information system that structurally stores and manages menu information and allergy information for a specific restaurant.

[0404] "Filtering" is a process of selecting specific menu items that do not contain ingredients that match the user's allergy information.

[0405] "Visually displaying" refers to displaying information on the device screen in an easy-to-understand format.

[0406] "Allergy icons" are visual symbols used to indicate specific allergens.

[0407] A specific embodiment of this invention will be described in detail. This system allows users to register their allergy information through a smartphone application and visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. The main hardware and software used in this invention are a smartphone, a camera, a cloud server, a database, and image analysis technology.

[0408] Enter and save allergy information

[0409] First, the user opens the smartphone app and enters the ingredients they are allergic to (e.g., eggs, wheat, milk, etc.). This information is then stored in the smartphone's local database or on a cloud server. Specific databases suitable for use include SQLite (local) and Firebase (cloud). This method allows the user to change or add information later.

[0410] Photographing and analyzing store exteriors

[0411] The user takes a photo of the exterior of a restaurant using their smartphone camera. This image is saved in the device's internal buffer. The restaurant is then identified using image analysis technology. Specifically, OCR (optical character recognition) and logo recognition technology are used. Libraries such as TensorFlow can be used for image analysis. This analyzed restaurant information is then sent to the server.

[0412] Server-based menu information retrieval and filtering

[0413] The server queries the database based on the received store information to obtain the menu information and allergy information for the specific store. The server uses a database such as MongoDB. Next, it filters the menu based on the user's pre-registered allergy information. The filtered results are formatted in JSON format and sent back to the user's device.

[0414] Displaying menu information

[0415] The device receives the menu information returned from the server and parses the JSON data. The received menu information is displayed in a visually easy-to-understand format in the user interface. For example, it can be displayed in list format using UI components such as RecyclerView, and a unified allergy icon is displayed for each menu item. This allows users to check the menu items that are suitable for them at a glance.

[0416] Specific examples

[0417] For example, a user (let's call her Hanako) registers her egg and wheat allergies in a smartphone app. She takes a photo of the exterior of a nearby cafe, and the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone, allowing her to check the menu items that are suitable for her before entering the store.

[0418] Examples of prompts for generative AI models

[0419] Here are some examples of prompts to input to a generative AI model:

[0420] Please explain in concrete steps the program processing flow for a system that allows users to register their allergy information through a smartphone application and then visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. Please provide a detailed explanation of all the processes involved, from the user entering their allergy information and taking a photo of the restaurant's exterior, to data processing on the server and displaying it to the user.

[0421] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0422] Step 1:

[0423] The user launches the smartphone app and enters their allergy information. Specifically, the user opens the app's input screen, selects the allergen (e.g., egg, wheat, milk, etc.), and presses the "Save" button. This input information is collected on the device and stored in a local database (e.g., SQLite) or a cloud database (e.g., Firebase). The input is the user's allergy information, and the output is the saved allergy information data.

[0424] Step 2:

[0425] A user stands in front of a restaurant and uses the app's camera function to take a photo of the restaurant's exterior. Specifically, the user taps the camera button to take a photo of the restaurant's exterior. The captured image is saved in the device's internal buffer. The input is the restaurant's exterior image, and the output is the image data saved in the internal buffer.

[0426] Step 3:

[0427] The device analyzes the captured image of the store's exterior to identify the store. Specifically, the device uses image analysis technology (e.g., OCR or logo recognition) to extract text and logos from the image. Libraries such as TensorFlow can be used for this process. The device then generates identified store information and sends it to the server. The input is the image data stored in the internal buffer, and the output is the identified store information.

[0428] Step 4:

[0429] Based on the identified store information, the server queries the database to obtain the store's menu information and its allergy information. The server uses a database such as MongoDB to search for menu information corresponding to a specific store name. The input is the identified store information, and the output is the obtained menu information and its allergy information.

[0430] Step 5:

[0431] The server filters the menu based on the user's allergy information. Specifically, the server selects items from the menu that do not contain any ingredients that match the user's allergy information. The filtered menu information is formatted in JSON format and sent back to the user's device. The input is the acquired menu information and the user's allergy information, and the output is the filtered menu information.

[0432] Step 6:

[0433] The terminal receives the filtered menu information returned from the server. The terminal parses the received JSON data and displays it in the user interface. Specifically, it displays the menu information in list format using UI components such as RecyclerView, and visually indicates allergic ingredients in each menu using standardized allergy icons. The input is the filtered menu information, and the output is the visually displayed menu information.

[0434] (Application example 1)

[0435] 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."

[0436] In modern society, there is a demand for a way to easily search and check menu items that accommodate allergies when dining out. In particular, there is a need for a system that allows users with allergies to select menu items with peace of mind when dining out. Furthermore, as the number of restaurants increases and they offer different menus, it is becoming more difficult for users to quickly find a menu that suits them. This has led to a demand for a system that reduces users' health risks and provides a convenient and safe dining experience.

[0437] 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.

[0438] In this invention, the server includes: means for a user to input his / her own allergy information; means for the terminal to verify and save the input allergy information; means for the terminal to photograph the exterior of a store and identify the store; means for the terminal to identify the store using image analysis technology; means for the server to obtain menu information for the identified store; means for the server to filter menus based on the user's allergy information; and means for the terminal to display the filtered menu information together with a unified allergy icon. This allows users to quickly check menus that cater to their allergies based on the photographed exterior image of the store.

[0439] The "means for the user to input his / her own allergy information" is an interface that allows the user to input his / her own allergy information into the terminal.

[0440] "Means for verifying and saving allergy information entered by the terminal" refers to the function by which the terminal checks the allergy information entered by the user and saves it appropriately in a database.

[0441] "Means for the terminal to photograph the exterior of the store and identify the store" refers to a function that uses the camera function of the terminal to photograph the exterior of the store and identify the store based on that image.

[0442] "Means by which the terminal identifies a store using image analysis technology" refers to technologies used to analyze captured images to identify a store, such as OCR or logo recognition.

[0443] The "means for the server to obtain menu information for a specified store" is a function that allows the server to obtain menu information for a specified store from a database or the web.

[0444] The "means for the server to filter the menu based on the user's allergy information" is a function in which the server selects menu items based on the user's allergy information and extracts menu items that do not contain harmful substances.

[0445] "Means for the terminal to display filtered menu information together with a unified allergy icon" is a function that allows the terminal to display filtered menu items using a unified icon that is easy for the user to understand.

[0446] This invention is a system that allows users to safely select meals based on their own allergy information when dining out. The system has the function of acquiring menu information for a restaurant by having the user input their own allergy information and taking a photo of the restaurant's exterior when dining out, and then displaying a menu that matches the user's allergy information.

[0447] A means for users to enter allergy information

[0448] Users open the smartphone application and enter their allergy ingredients (e.g., eggs, wheat, milk, etc.). The entered allergy information is saved in the device's local database or on the server. The saved information can be changed or added to later by the user.

[0449] A means for the device to photograph and identify the store's exterior

[0450] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and identifies the restaurant using image analysis technology such as Google Cloud Vision API. This identified restaurant information is then sent to the server.

[0451] A method for the server to obtain and filter store information

[0452] The server retrieves the menu for a specific restaurant from its database based on the restaurant information it receives. It then filters menu items containing specific ingredients based on the allergy information previously registered by the user. For example, if a user is allergic to eggs and wheat, the server extracts only menu items that do not contain these ingredients.

[0453] A means for the device to display filtered menu information

[0454] The filtered menu information is sent back to the device and displayed on the smartphone application's user interface. The menu information includes standardized allergy icons, allowing users to easily identify menu items suitable for them.

[0455] Specific examples

[0456] For example, a user (hereinafter referred to as "User A") registers in a smartphone app that he or she has egg and wheat allergies. When User A takes a photo of the exterior of a nearby restaurant, the image is analyzed and the specific restaurant is identified. This information is sent to a server, which retrieves the restaurant's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on User A's smartphone. As a result, User A can check the menu that suits him or her before entering the restaurant.

[0457] Prompt Sentence Examples

[0458] Below is an example prompt for a specific generative AI model that takes an image of a restaurant's exterior and identifies it using the Google Cloud Vision API.

[0459] "Analyze the image of the store exterior to obtain the name of the target restaurant."

[0460] By using this system, users can choose their meals with peace of mind when eating out, providing convenience and safety.

[0461] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0462] Program processing flow

[0463] Step 1:

[0464] The user opens the smartphone application and enters their allergy information. The entered allergy information is saved in the device's local database. Specifically, the user enters the allergens they are allergic to, such as eggs, wheat, or milk, into a form within the app and presses the save button. This input information is saved in a local database such as SQLite.

[0465] Input: User allergy information (e.g., egg, wheat, milk)

[0466] Data processing: Save allergy information from form input to local database

[0467] Output: Allergy information stored in a local database

[0468] Step 2:

[0469] A user takes a photo of the exterior of a restaurant using their smartphone camera. The captured image is saved in the device's internal buffer. The user then presses the camera button to capture the exterior of the restaurant. At this point, the image file is stored in the device's memory.

[0470] Input: Store exterior image

[0471] Data processing: Save image files to internal buffer

[0472] Output: Saved image file

[0473] Step 3:

[0474] The device uses the Google Cloud Vision API to analyze the captured image and identify the store. This analysis process extracts the store's name and other identifying information. Specifically, the device uploads the captured image and receives the results of OCR and logo recognition.

[0475] Input: Store exterior image

[0476] Data processing: Identifying stores using image analysis technology (Google Cloud Vision API)

[0477] Output: Identified store information (e.g. store name, address)

[0478] Step 4:

[0479] The server receives the information about the identified store and retrieves the menu information for that store from the database. The server executes an appropriate query to the database based on the received store information to retrieve the menu information.

[0480] Input: Identified store information

[0481] Data manipulation: Performing database queries

[0482] Output: Retrieved menu information

[0483] Step 5:

[0484] The server filters the acquired menu information based on the user's allergy information. Specifically, the server takes the user's allergy information into consideration and extracts menu items that do not contain harmful substances.

[0485] Input: User allergy information, menu information

[0486] Data processing: filtering menu information

[0487] Output: Filtered menu information

[0488] Step 6:

[0489] The device will display the filtered menu information along with a unified allergy icon. Specifically, the filtered menu information will be displayed on the device's user interface, allowing users to check the appropriate menu at a glance.

[0490] Input: Filtered menu information

[0491] Data processing: Integrating menu information and allergy icons

[0492] Output: Menu information displayed in the user interface

[0493] In this way, the user can quickly check the menu items that cater to his or her allergies based on the photographed image of the exterior of the store.

[0494] 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.

[0495] An example of this system will be described in detail below. In the following example, a system is provided that allows a user to register their own allergy information via a smartphone application, and further recognizes the user's emotions and provides appropriate menu information when dining out.

[0496] User enters allergy information

[0497] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0498] Photographing and analyzing store exteriors

[0499] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0500] Acquiring user emotion information

[0501] The emotion engine installed on the device extracts emotional information from the user's facial expressions and tone of voice based on sensor data from cameras, microphones, etc. This emotional information is then sent to the server along with allergy information.

[0502] The server obtains store information and performs filtering.

[0503] The server retrieves the menu information for a specific restaurant from a database based on the restaurant information received. It then filters out menu items that do not contain any allergens (e.g., eggs, wheat, milk, etc.) based on the allergy information registered by the user in advance. It also takes into account the user's emotional information and adjusts the priority and display method of the filtering results.

[0504] User Interface Display

[0505] The device receives the menu information returned from the server and visually displays it in the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. Specific menu items may also be recommended based on emotional information. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed preferentially.

[0506] Specific use cases

[0507] For example, a user (Hanako) registers in a smartphone app that she has egg and wheat allergies. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is sent back to the device and displayed on Hanako's smartphone. If Hanako's facial expression indicates that she is stressed, menu items such as "herbal tea" that has a relaxing effect are recommended.

[0508] In this way, the present invention allows users to make safe meal choices when dining out based on allergy information, and can even take emotional state into account to provide a pleasant dining experience.

[0509] The processing flow will be explained below.

[0510] Step 1:

[0511] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app. This information is stored in the device's local database or on the server.

[0512] Step 2:

[0513] The device verifies the allergy information entered, confirms that the information entered is in the correct format, and if there are no problems, proceeds to save the information.

[0514] Step 3:

[0515] A user takes a photo of the exterior of a restaurant using their smartphone camera. The device stores the captured image data in an internal buffer.

[0516] Step 4:

[0517] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0518] Step 5:

[0519] The device sends the specified store information to the server. The request includes the store name, location, and other information.

[0520] Step 6:

[0521] The device's emotion engine extracts emotional information from the user's facial expressions and tone of voice, which indicates states such as stress, joy, and excitement, and transmits this information to the server.

[0522] Step 7:

[0523] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0524] Step 8:

[0525] The server filters the menu based on the user's allergy information, for example, selecting menu items that do not contain eggs or wheat, and also considers the user's emotional information, prioritizing menu items that correspond to a specific emotional state.

[0526] Step 9:

[0527] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0528] Step 10:

[0529] The terminal validates the data received from the server and checks the consistency and accuracy of the menu information.

[0530] Step 11:

[0531] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. The system also takes into account the user's emotional information and recommends menu items such as "herbal tea" when relaxation is needed.

[0532] Through the above steps, the system not only allows users to easily and safely check allergy-friendly menu items when eating out, but also helps users select more appropriate menu items by taking into account the user's emotional state.

[0533] Example 2

[0534] 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."

[0535] Conventional restaurant selection support systems have the ability to filter menus based on the user's allergy information, but lack the ability to provide menus that take the user's emotional information into consideration. This makes it difficult to support users in choosing meals that satisfy them psychologically when eating out, and there is a need for an integrated approach to allergy and emotional information. Furthermore, there are challenges in properly managing the information entered by the user and improving the accuracy of restaurant identification through exterior image analysis.

[0536] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for acquiring menu information of the identified restaurant, a means for filtering menus based on the user's allergy information, and a means for adjusting the filtering result based on the user's emotional information. This allows the user to select a menu that is safe and psychologically satisfying when eating out by taking the user's allergy information and emotional information into consideration in an integrated manner.

[0537] Below are definitions of important words.

[0538] "User" refers to an individual who uses this system.

[0539] "Allergy Information" refers to information about a user's self-reported allergic reactions to specific ingredients.

[0540] "Terminal" refers to a mobile computing device used by a user, such as a smartphone or tablet.

[0541] "Input means" refers to the interface and functions required for users to input allergy information into the system using a terminal.

[0542] "Means to validate and store" refers to the ability to accurately verify entered allergy information and store it in a local or remote database.

[0543] "Means for taking photographs" refers to the function of acquiring images using the camera function built into the terminal.

[0544] "Image analysis technology" refers to technology for extracting and identifying useful information from captured images.

[0545] "Means for identifying" refers to the function of extracting and identifying specific information (e.g., store information) using image analysis technology.

[0546] "Sensor data" refers to digital data obtained from sensors such as cameras and microphones installed on devices.

[0547] "Emotional information" refers to information that analyzes and determines the user's emotional state (e.g., joy, sadness, stress) based on sensor data.

[0548] "Means for transmitting" refers to a communication function for transmitting information (e.g., store information, emotional information) from a terminal to a server.

[0549] A "server" refers to a computer system that communicates with terminals via a network and performs data processing, menu information acquisition, filtering, etc.

[0550] "Menu information" refers to information about the food and drinks served at a restaurant.

[0551] "Filtering means" refers to the ability to sort data (e.g., menu items) based on specific conditions and exclude unwanted items.

[0552] "Adjustment means" refers to a function that changes the display order or recommended items based on the filtering results, taking into account specific conditions (e.g., emotional information).

[0553] "Means for visual display" refers to a function that displays data on the terminal screen in a format that can be visually understood by the user.

[0554] The present invention relates to a system that allows users to register their own allergy information and provides appropriate menu information when dining out based on emotional information. This system involves the user inputting allergy information, photographing and analyzing the exterior of the restaurant, acquiring emotional information, filtering and adjusting the information by the server, and displaying the filtered results on a terminal.

[0555] First, when a user opens the smartphone application, an interface for entering their allergy ingredients (e.g., eggs, wheat, milk, etc.) is displayed. The user manually enters this information and presses the save button. The device (smartphone) then stores this information in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0556] Next, users can take a photo of the restaurant's exterior with their smartphone camera. The device stores the captured image in an internal buffer and then analyzes it using OCR (optical character recognition) and logo recognition technology to identify the restaurant. This analysis is performed using image analysis software such as Tesseract-OCR and Google Cloud Vision API.

[0557] Store information obtained through image analysis is sent from the device to a server. The device's built-in emotion engine then acquires the user's emotional information based on sensor data from the camera, microphone, and other devices. For example, OpenCV is used for facial expression analysis, and a different algorithm is applied to voice tone analysis. This emotional information is also sent to the server.

[0558] The server retrieves the menu information for the relevant store from a database (e.g., PostgreSQL, MySQL) based on the received store information. It then filters the menu based on the user's allergy information, excluding menu items containing allergens. The filtered results are then adjusted to take into account the user's emotional information. For example, if it is determined that the user is feeling stressed, adjustments will be made to prioritize the display of menu items with a relaxation effect (e.g., herbal tea).

[0559] Finally, the filtered and adjusted menu information is sent back to the device, which receives it and displays it in a visually friendly user interface. The displayed menu includes standardized allergy icons, allowing users to see at a glance which menu is suitable for them.

[0560] Specific use cases

[0561] For example, a user named Hanako registers her egg and wheat allergies in a smartphone application. When she takes a photo of the exterior of a nearby cafe, the device analyzes the image to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. If the emotion engine then determines that Hanako is feeling stressed, it will recommend a "herbal tea" with a relaxing effect.

[0562] Prompt Sentence Examples

[0563] Hanako registered her egg and wheat allergy information in a smartphone application and took a photo of the exterior of a nearby cafe with her camera. The server then analyzed the cafe's menu information and displayed egg- and wheat-free menu items on Hanako's smartphone. The application also determined that Hanako was feeling stressed, so it recommended a menu item with a relaxation effect.

[0564] This system allows users to make safe and satisfying food choices that take into account their allergy information and emotional state.

[0565] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0566] Step 1: The user enters their allergy information

[0567] The user opens the smartphone application and enters the ingredients to which they are allergic (eggs, wheat, milk, etc.). The allergy information entered by the user is treated as "input data." The device (smartphone) validates this input data, and if there are no problems, it stores it in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0568] Input: Allergy ingredient information entered by the user

[0569] Output: Save verified allergy information

[0570] Specific operation: When the user enters the allergens and presses the save button, the device saves the entered information in the database.

[0571] Step 2: The user takes a photo of the restaurant's exterior

[0572] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0573] Input: Restaurant exterior image

[0574] Output: Saved image data

[0575] Specific operation: The user opens the camera app, takes a picture of the restaurant's exterior, and the image is saved in the device's internal buffer.

[0576] Step 3: The device analyzes the image to identify and send store information

[0577] The device uses the images stored in the internal buffer to analyze the text and logos in the images using OCR (Optical Character Recognition) and logo recognition technology, identifies the store from the analyzed data, generates store information, and then sends the identified store information to a remote server.

[0578] Input: Saved image data

[0579] Output: Sending the identified store information

[0580] Specific operation: The device analyzes the stored image data using OCR technology, obtains store information, and sends it to the server.

[0581] Step 4: The device acquires and transmits the user's emotional information.

[0582] The emotion engine installed on the device acquires the user's emotional information based on sensor data from the camera and microphone. The acquired emotional information is analyzed using facial expression analysis technology (e.g., OpenCV) and voice analysis technology. The generated emotional information is sent to the server.

[0583] Input: Sensor data from camera and microphone

[0584] Output: Sending acquired emotion information

[0585] Specific operation: The device captures the user's facial expressions with a camera and records their voice with a microphone, analyzes this data to generate emotional information, and sends it to the server.

[0586] Step 5: The server retrieves the store menu information and performs filtering.

[0587] Based on the received store information, the server retrieves the menu information for the store from a database (e.g., PostgreSQL, MySQL), then references the user's allergy information and filters out menu items that do not contain allergens.

[0588] Input: Store information, allergy information

[0589] Output: Filtered menu information

[0590] Specific operation: The server retrieves menu information from the database and uses that information to extract items that do not contain allergens.

[0591] Step 6: The server adjusts the filtering results based on the user's emotions.

[0592] The server uses emotion information to adjust the priority of filtered menu items. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed at the top.

[0593] Input: filtered menu information, emotion information

[0594] Output: Adjusted menu information

[0595] Specific behavior: The server analyzes the emotional information and adjusts the display order of the filtered menu items.

[0596] Step 7: The device displays the filtered menu information

[0597] The device receives the filtered menu information returned from the server and displays the menu items in a visually identifiable format on the user interface. The displayed menu includes allergy icons and also provides emotion-based recommendations.

[0598] Input: Adjusted menu information

[0599] Output: Menu information to be displayed

[0600] Specific operation: Based on the menu information received by the terminal, it displays it in an easy-to-understand user interface.

[0601] (Application example 2)

[0602] 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."

[0603] Existing menu suggestion systems for dining out allow users to input and manage allergy information, but do not suggest menus that take into account the user's emotional state. This poses a problem of a lack of psychological support for users to enjoy their meals. Furthermore, there is insufficient consideration given to allowing users to easily select safe menus that are suitable for them.

[0604] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0605] In this invention, the server includes a means for acquiring the user's allergy information and emotional information, a means for photographing the exterior of a restaurant to identify the restaurant, and a means for filtering menus based on the allergy information and emotional information. This allows the user to not only select a safe menu based on their own allergy information, but also to receive menu suggestions tailored to their emotional state. Furthermore, the quality of the dining experience when eating out is improved because the user can see the menu that best suits them at a glance.

[0606] A "user" is someone who uses the system to input their allergy and emotional information and receive appropriate menu suggestions.

[0607] "Allergy information" is information about ingredients that users should avoid consuming.

[0608] "Terminal" means an electronic device that processes user input information and receives and analyzes external information in a ubiquitous computing environment.

[0609] A "store" is a facility that provides meals and is a place that users visit to eat out.

[0610] "Emotion information" is information about the user's psychological state that is recognized based on the user's facial expression, tone of voice, and the like.

[0611] A "server" is a central computing system for receiving and processing data sent from multiple terminals.

[0612] "Menu information" is a list of food and drink items served at a particular establishment.

[0613] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary data.

[0614] "Display" means providing information visually on the screen of a terminal.

[0615] A "system" is an integrated structure in which multiple devices and software work together to provide a specific function.

[0616] A "standardized allergy icon" is an allergy display symbol with a uniform design that is visually easy for users to recognize.

[0617] "Recommended Menu" refers to food and drink options that are specifically recommended based on the user's allergy and emotional information.

[0618] A specific embodiment of the present invention will be described. The system acquires allergy information and emotional information of a user and provides appropriate menu information when dining out. The details of this system are described below.

[0619] Hardware and software used

[0620] This system uses a smartphone, server, camera, and microphone as its main hardware. The software includes an image analysis engine (e.g., OpenCV), an emotion engine (e.g., emotion_engine), a server-side database system, and a menu information filtering function.

[0621] Details of data processing and calculation

[0622] Entering and confirming user allergy information

[0623] Users first enter their allergy information using a smartphone app. This information is stored in the smartphone's local database or on a cloud server. Users can also change or add to this information later.

[0624] Store exterior photography and analysis

[0625] The user takes a photo of the exterior of the restaurant they want to visit with their smartphone camera. The device acquires the captured image data and identifies the restaurant using an image analysis engine (such as OpenCV). Specifically, it identifies the restaurant's logo, sign, etc. from the image and sends this information to the server.

[0626] Acquiring emotional information

[0627] Using the smartphone's camera and microphone, emotional information is collected from the user's facial expressions and voice. An emotion engine (e.g., emotion_engine) is used for this. The acquired emotional information is sent to the server along with allergy information.

[0628] Retrieving and filtering menu information

[0629] The server retrieves the menu information of the identified restaurant from the corresponding database, then filters out safe menu items based on the user's allergy information, and further prioritizes the menu items based on the user's emotional information to determine the recommended menu.

[0630] User Interface Display

[0631] The filtered menu information is displayed on the smartphone user interface, along with standardized allergy icons, allowing users to quickly identify menu options suitable for them. Specific menu options are also recommended based on emotional information.

[0632] Specific examples

[0633] For example, suppose a user enters their allergy information (egg, wheat, etc.) into their smartphone. If the user takes a photo of the exterior of a nearby cafe and shows a stressed expression, the system will filter out menu items from that cafe that do not contain allergens, and prioritize the display of relaxation-enhancing herbal teas.

[0634] Prompt Sentence Examples

[0635] markdown

[0636] You are a UX designer responsible for designing the UI for a smartphone app where users enter allergy information and emotional state. Create a wireframe for the app that has the following features:

[0637] 1. A screen where users can enter allergens (eggs, wheat, milk, etc.)

[0638] 2. Ability to take photos of store exteriors

[0639] 3. Ability to capture emotional state from camera and microphone

[0640] 4. Menu suggestion screen based on allergy information and emotional state

[0641] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0642] Step 1:

[0643] The user launches the smartphone app and enters their allergy information. The entered information is stored in the smartphone's local database or in a cloud server. Specific inputs include "egg," "wheat," and "milk." The output of this step is the stored allergy information.

[0644] Step 2:

[0645] The user takes a photo of the exterior of the restaurant they are visiting with their smartphone camera. The device acquires the captured image data and stores it in an internal buffer. The input is an image of the restaurant's exterior, which is used for analysis in the next step. The output is the image data stored in the buffer.

[0646] Step 3:

[0647] The device analyzes the stored exterior image. It uses an image analysis engine (such as OpenCV) to identify the store's logo and sign and identify the store. The input is the image data stored in the buffer, and the output is the identified store information (store name, address, etc.). This information is sent to the server.

[0648] Step 4:

[0649] The device uses the camera and microphone to acquire the user's emotional information. An emotion engine (such as emotion_engine) is used to analyze the user's facial expressions and tone of voice to recognize their emotional state (e.g., stress, joy, etc.). The input is sensor data acquired from the camera and microphone, and the output is the recognized emotional information. This information is also sent to the server.

[0650] Step 5:

[0651] The server retrieves the menu information of the identified restaurant from the database. The input is the restaurant information, and the output is the restaurant's menu information. The server then filters the menu based on the user's allergy information. This filtering process excludes items containing allergens. The input is the menu information and allergy information, and the output is the filtered safe menu items.

[0652] Step 6:

[0653] The server then adjusts the priority of the menu items based on the emotional information. For example, if the user is feeling stressed, it will prioritize menus with a relaxation effect. The input is the filtered menu items and emotional information, and the output is a recommended menu with adjusted priorities.

[0654] Step 7:

[0655] The terminal receives the recommended menu information returned from the server and visually displays it on the user interface. Standardized allergy icons are also displayed, allowing users to check the menu that is suitable for them at a glance. The input is the recommended menu information, and the output is a visual menu list displayed on the smartphone screen.

[0656] 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.

[0657] 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.

[0658] 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.

[0659] [Third embodiment]

[0660] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0661] 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.

[0662] 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).

[0663] 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.

[0664] 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.

[0665] 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).

[0666] 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.

[0667] 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.

[0668] 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.

[0669] 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.

[0670] 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.

[0671] 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."

[0672] An example of this system will be described in detail below. In the following example, a system is provided that allows users to register their own allergy information through a smartphone application and visually check menu information that accommodates allergies by taking a photo of the exterior of a restaurant when eating out.

[0673] User enters allergy information

[0674] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0675] Photographing and analyzing store exteriors

[0676] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0677] The server obtains store information and performs filtering.

[0678] Based on the received store information, the server retrieves the menu and allergy information for the specific store from the database. Next, based on the allergy information (e.g., egg, wheat, milk, etc.) registered in advance by the user, it filters out menu items that do not contain the relevant ingredients. This filtered menu information is then returned to the terminal in a format that is easy for the user to understand.

[0679] User Interface Display

[0680] The device receives the menu information returned from the server and visually displays it on the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. For example, "Caesar Salad (Egg-Free, Wheat-Free)" and "Fruit Parfait (Egg-Free, Wheat-Free)" are displayed with photos.

[0681] Specific use cases

[0682] For example, a user (Hanako) registers her egg and wheat allergies in a smartphone app. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone. As a result, Hanako can check the menu items that are suitable for her before entering the store.

[0683] In this way, the present invention allows users to safely select meals based on allergy information when dining out, providing convenience and peace of mind.

[0684] The processing flow will be explained below.

[0685] Step 1:

[0686] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app.

[0687] Step 2:

[0688] The device validates the entered allergy information, ensuring that the information is in the correct format and, if there are no problems, stores the information in a local database or on a server.

[0689] Step 3:

[0690] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0691] Step 4:

[0692] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0693] Step 5:

[0694] The device sends a request including specific store information to the server, specifically, data including the store's name, location information, etc.

[0695] Step 6:

[0696] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0697] Step 7:

[0698] The server filters the menu based on the user's allergy information, specifically selecting menu items that do not contain the allergic ingredients.

[0699] Step 8:

[0700] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0701] Step 9:

[0702] The terminal receives the data returned from the server and verifies the integrity and accuracy of the data.

[0703] Step 10:

[0704] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. Users can visually check the menu and select meals that suit them.

[0705] Through the above steps, this system allows users to easily check allergy-friendly menu items when dining out and safely select meals.

[0706] Example 1

[0707] 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."

[0708] With the conventional method of managing allergy information when eating out, users had to check directly with the staff to find out what menu items were suitable for them, which was time-consuming and prone to mistakes. This made it difficult for users with allergies to enjoy eating out with peace of mind. Furthermore, it was difficult for restaurants to provide allergy information to all users, which resulted in situations where users were unable to safely select their meals.

[0709] 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.

[0710] In this invention, the server includes means for retrieving the menu information and allergy information of the identified restaurant from a database, means for filtering the menu based on the user's allergy information and returning the filtered menu information to the terminal, and means for visually displaying the filtered menu information. This allows users to input their own allergy information in advance and instantly check the menu that suits them simply by taking a photo of the restaurant's exterior.

[0711] A "user" is a person who uses the system to input their own allergy information and check restaurant menu information.

[0712] A "terminal" is an electronic device owned by a user, which has functions such as taking pictures, transmitting data, and displaying information.

[0713] "Allergy information" refers to the type and information of allergies a user has to specific food ingredients.

[0714] "Store exterior" refers to image data capturing the exterior appearance of a restaurant.

[0715] "Image analysis" is a technology that recognizes characters, logos, etc. from photographed images of store exteriors and extracts specific information.

[0716] A "server" is a computer system that receives information sent from users and terminals, retrieves menu information for specific restaurants from a database, and performs processing.

[0717] A "database" is an information system that structurally stores and manages menu information and allergy information for a specific restaurant.

[0718] "Filtering" is a process of selecting specific menu items that do not contain ingredients that match the user's allergy information.

[0719] "Visually displaying" refers to displaying information on the device screen in an easy-to-understand format.

[0720] "Allergy icons" are visual symbols used to indicate specific allergens.

[0721] A specific embodiment of this invention will be described in detail. This system allows users to register their allergy information through a smartphone application and visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. The main hardware and software used in this invention are a smartphone, a camera, a cloud server, a database, and image analysis technology.

[0722] Enter and save allergy information

[0723] First, the user opens the smartphone app and enters the ingredients they are allergic to (e.g., eggs, wheat, milk, etc.). This information is then stored in the smartphone's local database or on a cloud server. Specific databases suitable for use include SQLite (local) and Firebase (cloud). This method allows the user to change or add information later.

[0724] Photographing and analyzing store exteriors

[0725] The user takes a photo of the exterior of a restaurant using their smartphone camera. This image is saved in the device's internal buffer. The restaurant is then identified using image analysis technology. Specifically, OCR (optical character recognition) and logo recognition technology are used. Libraries such as TensorFlow can be used for image analysis. This analyzed restaurant information is then sent to the server.

[0726] Server-based menu information retrieval and filtering

[0727] The server queries the database based on the received store information to obtain the menu information and allergy information for the specific store. The server uses a database such as MongoDB. Next, it filters the menu based on the user's pre-registered allergy information. The filtered results are formatted in JSON format and sent back to the user's device.

[0728] Displaying menu information

[0729] The device receives the menu information returned from the server and parses the JSON data. The received menu information is displayed in a visually easy-to-understand format in the user interface. For example, it can be displayed in list format using UI components such as RecyclerView, and a unified allergy icon is displayed for each menu item. This allows users to check the menu items that are suitable for them at a glance.

[0730] Specific examples

[0731] For example, a user (let's call her Hanako) registers her egg and wheat allergies in a smartphone app. She takes a photo of the exterior of a nearby cafe, and the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone, allowing her to check the menu items that are suitable for her before entering the store.

[0732] Examples of prompts for generative AI models

[0733] Here are some examples of prompts to input to a generative AI model:

[0734] Please explain in concrete steps the program processing flow for a system that allows users to register their allergy information through a smartphone application and then visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. Please provide a detailed explanation of all the processes involved, from the user entering their allergy information and taking a photo of the restaurant's exterior, to data processing on the server and displaying it to the user.

[0735] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0736] Step 1:

[0737] The user launches the smartphone app and enters their allergy information. Specifically, the user opens the app's input screen, selects the allergen (e.g., egg, wheat, milk, etc.), and presses the "Save" button. This input information is collected on the device and stored in a local database (e.g., SQLite) or a cloud database (e.g., Firebase). The input is the user's allergy information, and the output is the saved allergy information data.

[0738] Step 2:

[0739] A user stands in front of a restaurant and uses the app's camera function to take a photo of the restaurant's exterior. Specifically, the user taps the camera button to take a photo of the restaurant's exterior. The captured image is saved in the device's internal buffer. The input is the restaurant's exterior image, and the output is the image data saved in the internal buffer.

[0740] Step 3:

[0741] The device analyzes the captured image of the store's exterior to identify the store. Specifically, the device uses image analysis technology (e.g., OCR or logo recognition) to extract text and logos from the image. Libraries such as TensorFlow can be used for this process. The device then generates identified store information and sends it to the server. The input is the image data stored in the internal buffer, and the output is the identified store information.

[0742] Step 4:

[0743] Based on the identified store information, the server queries the database to obtain the store's menu information and its allergy information. The server uses a database such as MongoDB to search for menu information corresponding to a specific store name. The input is the identified store information, and the output is the obtained menu information and its allergy information.

[0744] Step 5:

[0745] The server filters the menu based on the user's allergy information. Specifically, the server selects items from the menu that do not contain any ingredients that match the user's allergy information. The filtered menu information is formatted in JSON format and sent back to the user's device. The input is the acquired menu information and the user's allergy information, and the output is the filtered menu information.

[0746] Step 6:

[0747] The terminal receives the filtered menu information returned from the server. The terminal parses the received JSON data and displays it in the user interface. Specifically, it displays the menu information in list format using UI components such as RecyclerView, and visually indicates allergic ingredients in each menu using standardized allergy icons. The input is the filtered menu information, and the output is the visually displayed menu information.

[0748] (Application example 1)

[0749] 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."

[0750] In modern society, there is a demand for a way to easily search and check menu items that accommodate allergies when dining out. In particular, there is a need for a system that allows users with allergies to select menu items with peace of mind when dining out. Furthermore, as the number of restaurants increases and they offer different menus, it is becoming more difficult for users to quickly find a menu that suits them. This has led to a demand for a system that reduces users' health risks and provides a convenient and safe dining experience.

[0751] 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.

[0752] In this invention, the server includes: means for a user to input his / her own allergy information; means for the terminal to verify and save the input allergy information; means for the terminal to photograph the exterior of a store and identify the store; means for the terminal to identify the store using image analysis technology; means for the server to obtain menu information for the identified store; means for the server to filter menus based on the user's allergy information; and means for the terminal to display the filtered menu information together with a unified allergy icon. This allows users to quickly check menus that cater to their allergies based on the photographed exterior image of the store.

[0753] The "means for the user to input his / her own allergy information" is an interface that allows the user to input his / her own allergy information into the terminal.

[0754] "Means for verifying and saving allergy information entered by the terminal" refers to the function by which the terminal checks the allergy information entered by the user and saves it appropriately in a database.

[0755] "Means for the terminal to photograph the exterior of the store and identify the store" refers to a function that uses the camera function of the terminal to photograph the exterior of the store and identify the store based on that image.

[0756] "Means by which the terminal identifies a store using image analysis technology" refers to technologies used to analyze captured images to identify a store, such as OCR or logo recognition.

[0757] The "means for the server to obtain menu information for a specified store" is a function that allows the server to obtain menu information for a specified store from a database or the web.

[0758] The "means for the server to filter the menu based on the user's allergy information" is a function in which the server selects menu items based on the user's allergy information and extracts menu items that do not contain harmful substances.

[0759] "Means for the terminal to display filtered menu information together with a unified allergy icon" is a function that allows the terminal to display filtered menu items using a unified icon that is easy for the user to understand.

[0760] This invention is a system that allows users to safely select meals based on their own allergy information when dining out. The system has the function of acquiring menu information for a restaurant by having the user input their own allergy information and taking a photo of the restaurant's exterior when dining out, and then displaying a menu that matches the user's allergy information.

[0761] A means for users to enter allergy information

[0762] Users open the smartphone application and enter their allergy ingredients (e.g., eggs, wheat, milk, etc.). The entered allergy information is saved in the device's local database or on the server. The saved information can be changed or added to later by the user.

[0763] A means for the device to photograph and identify the store's exterior

[0764] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and identifies the restaurant using image analysis technology such as Google Cloud Vision API. This identified restaurant information is then sent to the server.

[0765] A method for the server to obtain and filter store information

[0766] The server retrieves the menu for a specific restaurant from its database based on the restaurant information it receives. It then filters menu items containing specific ingredients based on the allergy information previously registered by the user. For example, if a user is allergic to eggs and wheat, the server extracts only menu items that do not contain these ingredients.

[0767] A means for the device to display filtered menu information

[0768] The filtered menu information is sent back to the device and displayed on the smartphone application's user interface. The menu information includes standardized allergy icons, allowing users to easily identify menu items suitable for them.

[0769] Specific examples

[0770] For example, a user (hereinafter referred to as "User A") registers in a smartphone app that he or she has egg and wheat allergies. When User A takes a photo of the exterior of a nearby restaurant, the image is analyzed and the specific restaurant is identified. This information is sent to a server, which retrieves the restaurant's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on User A's smartphone. As a result, User A can check the menu that suits him or her before entering the restaurant.

[0771] Prompt Sentence Examples

[0772] Below is an example prompt for a specific generative AI model that takes an image of a restaurant's exterior and identifies it using the Google Cloud Vision API.

[0773] "Analyze the image of the store exterior to obtain the name of the target restaurant."

[0774] By using this system, users can choose their meals with peace of mind when eating out, providing convenience and safety.

[0775] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0776] Program processing flow

[0777] Step 1:

[0778] The user opens the smartphone application and enters their allergy information. The entered allergy information is saved in the device's local database. Specifically, the user enters the allergens they are allergic to, such as eggs, wheat, or milk, into a form within the app and presses the save button. This input information is saved in a local database such as SQLite.

[0779] Input: User allergy information (e.g., egg, wheat, milk)

[0780] Data processing: Save allergy information from form input to local database

[0781] Output: Allergy information stored in a local database

[0782] Step 2:

[0783] A user takes a photo of the exterior of a restaurant using their smartphone camera. The captured image is saved in the device's internal buffer. The user then presses the camera button to capture the exterior of the restaurant. At this point, the image file is stored in the device's memory.

[0784] Input: Store exterior image

[0785] Data processing: Save image files to internal buffer

[0786] Output: Saved image file

[0787] Step 3:

[0788] The device uses the Google Cloud Vision API to analyze the captured image and identify the store. This analysis process extracts the store's name and other identifying information. Specifically, the device uploads the captured image and receives the results of OCR and logo recognition.

[0789] Input: Store exterior image

[0790] Data processing: Identifying stores using image analysis technology (Google Cloud Vision API)

[0791] Output: Identified store information (e.g. store name, address)

[0792] Step 4:

[0793] The server receives the information about the identified store and retrieves the menu information for that store from the database. The server executes an appropriate query to the database based on the received store information to retrieve the menu information.

[0794] Input: Identified store information

[0795] Data manipulation: Performing database queries

[0796] Output: Retrieved menu information

[0797] Step 5:

[0798] The server filters the acquired menu information based on the user's allergy information. Specifically, the server takes the user's allergy information into consideration and extracts menu items that do not contain harmful substances.

[0799] Input: User allergy information, menu information

[0800] Data processing: filtering menu information

[0801] Output: Filtered menu information

[0802] Step 6:

[0803] The device will display the filtered menu information along with a unified allergy icon. Specifically, the filtered menu information will be displayed on the device's user interface, allowing users to check the appropriate menu at a glance.

[0804] Input: Filtered menu information

[0805] Data processing: Integrating menu information and allergy icons

[0806] Output: Menu information displayed in the user interface

[0807] In this way, the user can quickly check the menu items that cater to his or her allergies based on the photographed image of the exterior of the store.

[0808] 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.

[0809] An example of this system will be described in detail below. In the following example, a system is provided that allows a user to register their own allergy information via a smartphone application, and further recognizes the user's emotions and provides appropriate menu information when dining out.

[0810] User enters allergy information

[0811] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0812] Photographing and analyzing store exteriors

[0813] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0814] Acquiring user emotion information

[0815] The emotion engine installed on the device extracts emotional information from the user's facial expressions and tone of voice based on sensor data from cameras, microphones, etc. This emotional information is then sent to the server along with allergy information.

[0816] The server obtains store information and performs filtering.

[0817] The server retrieves the menu information for a specific restaurant from a database based on the restaurant information received. It then filters out menu items that do not contain any allergens (e.g., eggs, wheat, milk, etc.) based on the allergy information registered by the user in advance. It also takes into account the user's emotional information and adjusts the priority and display method of the filtering results.

[0818] User Interface Display

[0819] The device receives the menu information returned from the server and visually displays it in the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. Specific menu items may also be recommended based on emotional information. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed preferentially.

[0820] Specific use cases

[0821] For example, a user (Hanako) registers in a smartphone app that she has egg and wheat allergies. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is sent back to the device and displayed on Hanako's smartphone. If Hanako's facial expression indicates that she is stressed, menu items such as "herbal tea" that has a relaxing effect are recommended.

[0822] In this way, the present invention allows users to make safe meal choices when dining out based on allergy information, and can even take emotional state into account to provide a pleasant dining experience.

[0823] The processing flow will be explained below.

[0824] Step 1:

[0825] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app. This information is stored in the device's local database or on the server.

[0826] Step 2:

[0827] The device verifies the allergy information entered, confirms that the information entered is in the correct format, and if there are no problems, proceeds to save the information.

[0828] Step 3:

[0829] A user takes a photo of the exterior of a restaurant using their smartphone camera. The device stores the captured image data in an internal buffer.

[0830] Step 4:

[0831] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[0832] Step 5:

[0833] The device sends the specified store information to the server. The request includes the store name, location, and other information.

[0834] Step 6:

[0835] The device's emotion engine extracts emotional information from the user's facial expressions and tone of voice, which indicates states such as stress, joy, and excitement, and transmits this information to the server.

[0836] Step 7:

[0837] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[0838] Step 8:

[0839] The server filters the menu based on the user's allergy information, for example, selecting menu items that do not contain eggs or wheat, and also considers the user's emotional information, prioritizing menu items that correspond to a specific emotional state.

[0840] Step 9:

[0841] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[0842] Step 10:

[0843] The terminal validates the data received from the server and checks the consistency and accuracy of the menu information.

[0844] Step 11:

[0845] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. The system also takes into account the user's emotional information and recommends menu items such as "herbal tea" when relaxation is needed.

[0846] Through the above steps, the system not only allows users to easily and safely check allergy-friendly menu items when eating out, but also helps users select more appropriate menu items by taking into account the user's emotional state.

[0847] Example 2

[0848] 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."

[0849] Conventional restaurant selection support systems have the ability to filter menus based on the user's allergy information, but lack the ability to provide menus that take the user's emotional information into consideration. This makes it difficult to support users in choosing meals that satisfy them psychologically when eating out, and there is a need for an integrated approach to allergy and emotional information. Furthermore, there are challenges in properly managing the information entered by the user and improving the accuracy of restaurant identification through exterior image analysis.

[0850] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for acquiring menu information of the identified restaurant, a means for filtering menus based on the user's allergy information, and a means for adjusting the filtering result based on the user's emotional information. This allows the user to select a menu that is safe and psychologically satisfying when eating out by taking the user's allergy information and emotional information into consideration in an integrated manner.

[0851] Below are definitions of important words.

[0852] "User" refers to an individual who uses this system.

[0853] "Allergy Information" refers to information about a user's self-reported allergic reactions to specific ingredients.

[0854] "Terminal" refers to a mobile computing device used by a user, such as a smartphone or tablet.

[0855] "Input means" refers to the interface and functions required for users to input allergy information into the system using a terminal.

[0856] "Means to validate and store" refers to the ability to accurately verify entered allergy information and store it in a local or remote database.

[0857] "Means for taking photographs" refers to the function of acquiring images using the camera function built into the terminal.

[0858] "Image analysis technology" refers to technology for extracting and identifying useful information from captured images.

[0859] "Means for identifying" refers to the function of extracting and identifying specific information (e.g., store information) using image analysis technology.

[0860] "Sensor data" refers to digital data obtained from sensors such as cameras and microphones installed on devices.

[0861] "Emotional information" refers to information that analyzes and determines the user's emotional state (e.g., joy, sadness, stress) based on sensor data.

[0862] "Means for transmitting" refers to a communication function for transmitting information (e.g., store information, emotional information) from a terminal to a server.

[0863] A "server" refers to a computer system that communicates with terminals via a network and performs data processing, menu information acquisition, filtering, etc.

[0864] "Menu information" refers to information about the food and drinks served at a restaurant.

[0865] "Filtering means" refers to the ability to sort data (e.g., menu items) based on specific conditions and exclude unwanted items.

[0866] "Adjustment means" refers to a function that changes the display order or recommended items based on the filtering results, taking into account specific conditions (e.g., emotional information).

[0867] "Means for visual display" refers to a function that displays data on the terminal screen in a format that can be visually understood by the user.

[0868] The present invention relates to a system that allows users to register their own allergy information and provides appropriate menu information when dining out based on emotional information. This system involves the user inputting allergy information, photographing and analyzing the exterior of the restaurant, acquiring emotional information, filtering and adjusting the information by the server, and displaying the filtered results on a terminal.

[0869] First, when a user opens the smartphone application, an interface for entering their allergy ingredients (e.g., eggs, wheat, milk, etc.) is displayed. The user manually enters this information and presses the save button. The device (smartphone) then stores this information in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0870] Next, users can take a photo of the restaurant's exterior with their smartphone camera. The device stores the captured image in an internal buffer and then analyzes it using OCR (optical character recognition) and logo recognition technology to identify the restaurant. This analysis is performed using image analysis software such as Tesseract-OCR and Google Cloud Vision API.

[0871] Store information obtained through image analysis is sent from the device to a server. The device's built-in emotion engine then acquires the user's emotional information based on sensor data from the camera, microphone, and other devices. For example, OpenCV is used for facial expression analysis, and a different algorithm is applied to voice tone analysis. This emotional information is also sent to the server.

[0872] The server retrieves the menu information for the relevant store from a database (e.g., PostgreSQL, MySQL) based on the received store information. It then filters the menu based on the user's allergy information, excluding menu items containing allergens. The filtered results are then adjusted to take into account the user's emotional information. For example, if it is determined that the user is feeling stressed, adjustments will be made to prioritize the display of menu items with a relaxation effect (e.g., herbal tea).

[0873] Finally, the filtered and adjusted menu information is sent back to the device, which receives it and displays it in a visually friendly user interface. The displayed menu includes standardized allergy icons, allowing users to see at a glance which menu is suitable for them.

[0874] Specific use cases

[0875] For example, a user named Hanako registers her egg and wheat allergies in a smartphone application. When she takes a photo of the exterior of a nearby cafe, the device analyzes the image to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. If the emotion engine then determines that Hanako is feeling stressed, it will recommend a "herbal tea" with a relaxing effect.

[0876] Prompt Sentence Examples

[0877] Hanako registered her egg and wheat allergy information in a smartphone application and took a photo of the exterior of a nearby cafe with her camera. The server then analyzed the cafe's menu information and displayed egg- and wheat-free menu items on Hanako's smartphone. The application also determined that Hanako was feeling stressed, so it recommended a menu item with a relaxation effect.

[0878] This system allows users to make safe and satisfying food choices that take into account their allergy information and emotional state.

[0879] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0880] Step 1: The user enters their allergy information

[0881] The user opens the smartphone application and enters the ingredients to which they are allergic (eggs, wheat, milk, etc.). The allergy information entered by the user is treated as "input data." The device (smartphone) validates this input data, and if there are no problems, it stores it in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[0882] Input: Allergy ingredient information entered by the user

[0883] Output: Save verified allergy information

[0884] Specific operation: When the user enters the allergens and presses the save button, the device saves the entered information in the database.

[0885] Step 2: The user takes a photo of the restaurant's exterior

[0886] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[0887] Input: Restaurant exterior image

[0888] Output: Saved image data

[0889] Specific operation: The user opens the camera app, takes a picture of the restaurant's exterior, and the image is saved in the device's internal buffer.

[0890] Step 3: The device analyzes the image to identify and send store information

[0891] The device uses the images stored in the internal buffer to analyze the text and logos in the images using OCR (Optical Character Recognition) and logo recognition technology, identifies the store from the analyzed data, generates store information, and then sends the identified store information to a remote server.

[0892] Input: Saved image data

[0893] Output: Sending the identified store information

[0894] Specific operation: The device analyzes the stored image data using OCR technology, obtains store information, and sends it to the server.

[0895] Step 4: The device acquires and transmits the user's emotional information.

[0896] The emotion engine installed on the device acquires the user's emotional information based on sensor data from the camera and microphone. The acquired emotional information is analyzed using facial expression analysis technology (e.g., OpenCV) and voice analysis technology. The generated emotional information is sent to the server.

[0897] Input: Sensor data from camera and microphone

[0898] Output: Sending acquired emotion information

[0899] Specific operation: The device captures the user's facial expressions with a camera and records their voice with a microphone, analyzes this data to generate emotional information, and sends it to the server.

[0900] Step 5: The server retrieves the store menu information and performs filtering.

[0901] Based on the received store information, the server retrieves the menu information for the store from a database (e.g., PostgreSQL, MySQL), then references the user's allergy information and filters out menu items that do not contain allergens.

[0902] Input: Store information, allergy information

[0903] Output: Filtered menu information

[0904] Specific operation: The server retrieves menu information from the database and uses that information to extract items that do not contain allergens.

[0905] Step 6: The server adjusts the filtering results based on the user's emotions.

[0906] The server uses emotion information to adjust the priority of filtered menu items. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed at the top.

[0907] Input: filtered menu information, emotion information

[0908] Output: Adjusted menu information

[0909] Specific behavior: The server analyzes the emotional information and adjusts the display order of the filtered menu items.

[0910] Step 7: The device displays the filtered menu information

[0911] The device receives the filtered menu information returned from the server and displays the menu items in a visually identifiable format on the user interface. The displayed menu includes allergy icons and also provides emotion-based recommendations.

[0912] Input: Adjusted menu information

[0913] Output: Menu information to be displayed

[0914] Specific operation: Based on the menu information received by the terminal, it displays it in an easy-to-understand user interface.

[0915] (Application example 2)

[0916] 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."

[0917] Existing menu suggestion systems for dining out allow users to input and manage allergy information, but do not suggest menus that take into account the user's emotional state. This poses a problem of a lack of psychological support for users to enjoy their meals. Furthermore, there is insufficient consideration given to allowing users to easily select safe menus that are suitable for them.

[0918] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0919] In this invention, the server includes a means for acquiring the user's allergy information and emotional information, a means for photographing the exterior of a restaurant to identify the restaurant, and a means for filtering menus based on the allergy information and emotional information. This allows the user to not only select a safe menu based on their own allergy information, but also to receive menu suggestions tailored to their emotional state. Furthermore, the quality of the dining experience when eating out is improved because the user can see the menu that best suits them at a glance.

[0920] A "user" is someone who uses the system to input their allergy and emotional information and receive appropriate menu suggestions.

[0921] "Allergy information" is information about ingredients that users should avoid consuming.

[0922] "Terminal" means an electronic device that processes user input information and receives and analyzes external information in a ubiquitous computing environment.

[0923] A "store" is a facility that provides meals and is a place that users visit to eat out.

[0924] "Emotion information" is information about the user's psychological state that is recognized based on the user's facial expression, tone of voice, and the like.

[0925] A "server" is a central computing system for receiving and processing data sent from multiple terminals.

[0926] "Menu information" is a list of food and drink items served at a particular establishment.

[0927] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary data.

[0928] "Display" means providing information visually on the screen of a terminal.

[0929] A "system" is an integrated structure in which multiple devices and software work together to provide a specific function.

[0930] A "standardized allergy icon" is an allergy display symbol with a uniform design that is visually easy for users to recognize.

[0931] "Recommended Menu" refers to food and drink options that are specifically recommended based on the user's allergy and emotional information.

[0932] A specific embodiment of the present invention will be described. The system acquires allergy information and emotional information of a user and provides appropriate menu information when dining out. The details of this system are described below.

[0933] Hardware and software used

[0934] This system uses a smartphone, server, camera, and microphone as its main hardware. The software includes an image analysis engine (e.g., OpenCV), an emotion engine (e.g., emotion_engine), a server-side database system, and a menu information filtering function.

[0935] Details of data processing and calculation

[0936] Entering and confirming user allergy information

[0937] Users first enter their allergy information using a smartphone app. This information is stored in the smartphone's local database or on a cloud server. Users can also change or add to this information later.

[0938] Store exterior photography and analysis

[0939] The user takes a photo of the exterior of the restaurant they want to visit with their smartphone camera. The device acquires the captured image data and identifies the restaurant using an image analysis engine (such as OpenCV). Specifically, it identifies the restaurant's logo, sign, etc. from the image and sends this information to the server.

[0940] Acquiring emotional information

[0941] Using the smartphone's camera and microphone, emotional information is collected from the user's facial expressions and voice. An emotion engine (e.g., emotion_engine) is used for this. The acquired emotional information is sent to the server along with allergy information.

[0942] Retrieving and filtering menu information

[0943] The server retrieves the menu information of the identified restaurant from the corresponding database, then filters out safe menu items based on the user's allergy information, and further prioritizes the menu items based on the user's emotional information to determine the recommended menu.

[0944] User Interface Display

[0945] The filtered menu information is displayed on the smartphone user interface, along with standardized allergy icons, allowing users to quickly identify menu options suitable for them. Specific menu options are also recommended based on emotional information.

[0946] Specific examples

[0947] For example, suppose a user enters their allergy information (egg, wheat, etc.) into their smartphone. If the user takes a photo of the exterior of a nearby cafe and shows a stressed expression, the system will filter out menu items from that cafe that do not contain allergens, and prioritize the display of relaxation-enhancing herbal teas.

[0948] Prompt Sentence Examples

[0949] markdown

[0950] You are a UX designer responsible for designing the UI for a smartphone app where users enter allergy information and emotional state. Create a wireframe for the app that has the following features:

[0951] 1. A screen where users can enter allergens (eggs, wheat, milk, etc.)

[0952] 2. Ability to take photos of store exteriors

[0953] 3. Ability to capture emotional state from camera and microphone

[0954] 4. Menu suggestion screen based on allergy information and emotional state

[0955] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0956] Step 1:

[0957] The user launches the smartphone app and enters their allergy information. The entered information is stored in the smartphone's local database or in a cloud server. Specific inputs include "egg," "wheat," and "milk." The output of this step is the stored allergy information.

[0958] Step 2:

[0959] The user takes a photo of the exterior of the restaurant they are visiting with their smartphone camera. The device acquires the captured image data and stores it in an internal buffer. The input is an image of the restaurant's exterior, which is used for analysis in the next step. The output is the image data stored in the buffer.

[0960] Step 3:

[0961] The device analyzes the stored exterior image. It uses an image analysis engine (such as OpenCV) to identify the store's logo and sign and identify the store. The input is the image data stored in the buffer, and the output is the identified store information (store name, address, etc.). This information is sent to the server.

[0962] Step 4:

[0963] The device uses the camera and microphone to acquire the user's emotional information. An emotion engine (such as emotion_engine) is used to analyze the user's facial expressions and tone of voice to recognize their emotional state (e.g., stress, joy, etc.). The input is sensor data acquired from the camera and microphone, and the output is the recognized emotional information. This information is also sent to the server.

[0964] Step 5:

[0965] The server retrieves the menu information of the identified restaurant from the database. The input is the restaurant information, and the output is the restaurant's menu information. The server then filters the menu based on the user's allergy information. This filtering process excludes items containing allergens. The input is the menu information and allergy information, and the output is the filtered safe menu items.

[0966] Step 6:

[0967] The server then adjusts the priority of the menu items based on the emotional information. For example, if the user is feeling stressed, it will prioritize menus with a relaxation effect. The input is the filtered menu items and emotional information, and the output is a recommended menu with adjusted priorities.

[0968] Step 7:

[0969] The terminal receives the recommended menu information returned from the server and visually displays it on the user interface. Standardized allergy icons are also displayed, allowing users to check the menu that is suitable for them at a glance. The input is the recommended menu information, and the output is a visual menu list displayed on the smartphone screen.

[0970] 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.

[0971] 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.

[0972] 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.

[0973] [Fourth embodiment]

[0974] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0975] 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.

[0976] 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).

[0977] 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.

[0978] 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.

[0979] 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).

[0980] 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.

[0981] 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.

[0982] 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.

[0983] 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.

[0984] 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.

[0985] 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.

[0986] 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."

[0987] An example of this system will be described in detail below. In the following example, a system is provided that allows users to register their own allergy information through a smartphone application and visually check menu information that accommodates allergies by taking a photo of the exterior of a restaurant when eating out.

[0988] User enters allergy information

[0989] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[0990] Photographing and analyzing store exteriors

[0991] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[0992] The server obtains store information and performs filtering.

[0993] Based on the received store information, the server retrieves the menu and allergy information for the specific store from the database. Next, based on the allergy information (e.g., egg, wheat, milk, etc.) registered in advance by the user, it filters out menu items that do not contain the relevant ingredients. This filtered menu information is then returned to the terminal in a format that is easy for the user to understand.

[0994] User Interface Display

[0995] The device receives the menu information returned from the server and visually displays it on the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. For example, "Caesar Salad (Egg-Free, Wheat-Free)" and "Fruit Parfait (Egg-Free, Wheat-Free)" are displayed with photos.

[0996] Specific use cases

[0997] For example, a user (Hanako) registers her egg and wheat allergies in a smartphone app. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone. As a result, Hanako can check the menu items that are suitable for her before entering the store.

[0998] In this way, the present invention allows users to safely select meals based on allergy information when dining out, providing convenience and peace of mind.

[0999] The processing flow will be explained below.

[1000] Step 1:

[1001] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app.

[1002] Step 2:

[1003] The device validates the entered allergy information, ensuring that the information is in the correct format and, if there are no problems, stores the information in a local database or on a server.

[1004] Step 3:

[1005] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[1006] Step 4:

[1007] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[1008] Step 5:

[1009] The device sends a request including specific store information to the server, specifically, data including the store's name, location information, etc.

[1010] Step 6:

[1011] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[1012] Step 7:

[1013] The server filters the menu based on the user's allergy information, specifically selecting menu items that do not contain the allergic ingredients.

[1014] Step 8:

[1015] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[1016] Step 9:

[1017] The terminal receives the data returned from the server and verifies the integrity and accuracy of the data.

[1018] Step 10:

[1019] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. Users can visually check the menu and select meals that suit them.

[1020] Through the above steps, this system allows users to easily check allergy-friendly menu items when dining out and safely select meals.

[1021] Example 1

[1022] 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."

[1023] With the conventional method of managing allergy information when eating out, users had to check directly with the staff to find out what menu items were suitable for them, which was time-consuming and prone to mistakes. This made it difficult for users with allergies to enjoy eating out with peace of mind. Furthermore, it was difficult for restaurants to provide allergy information to all users, which resulted in situations where users were unable to safely select their meals.

[1024] 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.

[1025] In this invention, the server includes means for retrieving the menu information and allergy information of the identified restaurant from a database, means for filtering the menu based on the user's allergy information and returning the filtered menu information to the terminal, and means for visually displaying the filtered menu information. This allows users to input their own allergy information in advance and instantly check the menu that suits them simply by taking a photo of the restaurant's exterior.

[1026] A "user" is a person who uses the system to input their own allergy information and check restaurant menu information.

[1027] A "terminal" is an electronic device owned by a user, which has functions such as taking pictures, transmitting data, and displaying information.

[1028] "Allergy information" refers to the type and information of allergies a user has to specific food ingredients.

[1029] "Store exterior" refers to image data capturing the exterior appearance of a restaurant.

[1030] "Image analysis" is a technology that recognizes characters, logos, etc. from photographed images of store exteriors and extracts specific information.

[1031] A "server" is a computer system that receives information sent from users and terminals, retrieves menu information for specific restaurants from a database, and performs processing.

[1032] A "database" is an information system that structurally stores and manages menu information and allergy information for a specific restaurant.

[1033] "Filtering" is a process of selecting specific menu items that do not contain ingredients that match the user's allergy information.

[1034] "Visually displaying" refers to displaying information on the device screen in an easy-to-understand format.

[1035] "Allergy icons" are visual symbols used to indicate specific allergens.

[1036] A specific embodiment of this invention will be described in detail. This system allows users to register their allergy information through a smartphone application and visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. The main hardware and software used in this invention are a smartphone, a camera, a cloud server, a database, and image analysis technology.

[1037] Enter and save allergy information

[1038] First, the user opens the smartphone app and enters the ingredients they are allergic to (e.g., eggs, wheat, milk, etc.). This information is then stored in the smartphone's local database or on a cloud server. Specific databases suitable for use include SQLite (local) and Firebase (cloud). This method allows the user to change or add information later.

[1039] Photographing and analyzing store exteriors

[1040] The user takes a photo of the exterior of a restaurant using their smartphone camera. This image is saved in the device's internal buffer. The restaurant is then identified using image analysis technology. Specifically, OCR (optical character recognition) and logo recognition technology are used. Libraries such as TensorFlow can be used for image analysis. This analyzed restaurant information is then sent to the server.

[1041] Server-based menu information retrieval and filtering

[1042] The server queries the database based on the received store information to obtain the menu information and allergy information for the specific store. The server uses a database such as MongoDB. Next, it filters the menu based on the user's pre-registered allergy information. The filtered results are formatted in JSON format and sent back to the user's device.

[1043] Displaying menu information

[1044] The device receives the menu information returned from the server and parses the JSON data. The received menu information is displayed in a visually easy-to-understand format in the user interface. For example, it can be displayed in list format using UI components such as RecyclerView, and a unified allergy icon is displayed for each menu item. This allows users to check the menu items that are suitable for them at a glance.

[1045] Specific examples

[1046] For example, a user (let's call her Hanako) registers her egg and wheat allergies in a smartphone app. She takes a photo of the exterior of a nearby cafe, and the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on Hanako's smartphone, allowing her to check the menu items that are suitable for her before entering the store.

[1047] Examples of prompts for generative AI models

[1048] Here are some examples of prompts to input to a generative AI model:

[1049] Please explain in concrete steps the program processing flow for a system that allows users to register their allergy information through a smartphone application and then visually check allergy-friendly menu information by taking a photo of the restaurant's exterior when dining out. Please provide a detailed explanation of all the processes involved, from the user entering their allergy information and taking a photo of the restaurant's exterior, to data processing on the server and displaying it to the user.

[1050] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1051] Step 1:

[1052] The user launches the smartphone app and enters their allergy information. Specifically, the user opens the app's input screen, selects the allergen (e.g., egg, wheat, milk, etc.), and presses the "Save" button. This input information is collected on the device and stored in a local database (e.g., SQLite) or a cloud database (e.g., Firebase). The input is the user's allergy information, and the output is the saved allergy information data.

[1053] Step 2:

[1054] A user stands in front of a restaurant and uses the app's camera function to take a photo of the restaurant's exterior. Specifically, the user taps the camera button to take a photo of the restaurant's exterior. The captured image is saved in the device's internal buffer. The input is the restaurant's exterior image, and the output is the image data saved in the internal buffer.

[1055] Step 3:

[1056] The device analyzes the captured image of the store's exterior to identify the store. Specifically, the device uses image analysis technology (e.g., OCR or logo recognition) to extract text and logos from the image. Libraries such as TensorFlow can be used for this process. The device then generates identified store information and sends it to the server. The input is the image data stored in the internal buffer, and the output is the identified store information.

[1057] Step 4:

[1058] Based on the identified store information, the server queries the database to obtain the store's menu information and its allergy information. The server uses a database such as MongoDB to search for menu information corresponding to a specific store name. The input is the identified store information, and the output is the obtained menu information and its allergy information.

[1059] Step 5:

[1060] The server filters the menu based on the user's allergy information. Specifically, the server selects items from the menu that do not contain any ingredients that match the user's allergy information. The filtered menu information is formatted in JSON format and sent back to the user's device. The input is the acquired menu information and the user's allergy information, and the output is the filtered menu information.

[1061] Step 6:

[1062] The terminal receives the filtered menu information returned from the server. The terminal parses the received JSON data and displays it in the user interface. Specifically, it displays the menu information in list format using UI components such as RecyclerView, and visually indicates allergic ingredients in each menu using standardized allergy icons. The input is the filtered menu information, and the output is the visually displayed menu information.

[1063] (Application example 1)

[1064] 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."

[1065] In modern society, there is a demand for a way to easily search and check menu items that accommodate allergies when dining out. In particular, there is a need for a system that allows users with allergies to select menu items with peace of mind when dining out. Furthermore, as the number of restaurants increases and they offer different menus, it is becoming more difficult for users to quickly find a menu that suits them. This has led to a demand for a system that reduces users' health risks and provides a convenient and safe dining experience.

[1066] 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.

[1067] In this invention, the server includes: means for a user to input his / her own allergy information; means for the terminal to verify and save the input allergy information; means for the terminal to photograph the exterior of a store and identify the store; means for the terminal to identify the store using image analysis technology; means for the server to obtain menu information for the identified store; means for the server to filter menus based on the user's allergy information; and means for the terminal to display the filtered menu information together with a unified allergy icon. This allows users to quickly check menus that cater to their allergies based on the photographed exterior image of the store.

[1068] The "means for the user to input his / her own allergy information" is an interface that allows the user to input his / her own allergy information into the terminal.

[1069] "Means for verifying and saving allergy information entered by the terminal" refers to the function by which the terminal checks the allergy information entered by the user and saves it appropriately in a database.

[1070] "Means for the terminal to photograph the exterior of the store and identify the store" refers to a function that uses the camera function of the terminal to photograph the exterior of the store and identify the store based on that image.

[1071] "Means by which the terminal identifies a store using image analysis technology" refers to technologies used to analyze captured images to identify a store, such as OCR or logo recognition.

[1072] The "means for the server to obtain menu information for a specified store" is a function that allows the server to obtain menu information for a specified store from a database or the web.

[1073] The "means for the server to filter the menu based on the user's allergy information" is a function in which the server selects menu items based on the user's allergy information and extracts menu items that do not contain harmful substances.

[1074] "Means for the terminal to display filtered menu information together with a unified allergy icon" is a function that allows the terminal to display filtered menu items using a unified icon that is easy for the user to understand.

[1075] This invention is a system that allows users to safely select meals based on their own allergy information when dining out. The system has the function of acquiring menu information for a restaurant by having the user input their own allergy information and taking a photo of the restaurant's exterior when dining out, and then displaying a menu that matches the user's allergy information.

[1076] A means for users to enter allergy information

[1077] Users open the smartphone application and enter their allergy ingredients (e.g., eggs, wheat, milk, etc.). The entered allergy information is saved in the device's local database or on the server. The saved information can be changed or added to later by the user.

[1078] A means for the device to photograph and identify the store's exterior

[1079] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and identifies the restaurant using image analysis technology such as Google Cloud Vision API. This identified restaurant information is then sent to the server.

[1080] A method for the server to obtain and filter store information

[1081] The server retrieves the menu for a specific restaurant from its database based on the restaurant information it receives. It then filters menu items containing specific ingredients based on the allergy information previously registered by the user. For example, if a user is allergic to eggs and wheat, the server extracts only menu items that do not contain these ingredients.

[1082] A means for the device to display filtered menu information

[1083] The filtered menu information is sent back to the device and displayed on the smartphone application's user interface. The menu information includes standardized allergy icons, allowing users to easily identify menu items suitable for them.

[1084] Specific examples

[1085] For example, a user (hereinafter referred to as "User A") registers in a smartphone app that he or she has egg and wheat allergies. When User A takes a photo of the exterior of a nearby restaurant, the image is analyzed and the specific restaurant is identified. This information is sent to a server, which retrieves the restaurant's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is then sent back to the device and displayed on User A's smartphone. As a result, User A can check the menu that suits him or her before entering the restaurant.

[1086] Prompt Sentence Examples

[1087] Below is an example prompt for a specific generative AI model that takes an image of a restaurant's exterior and identifies it using the Google Cloud Vision API.

[1088] "Analyze the image of the store exterior to obtain the name of the target restaurant."

[1089] By using this system, users can choose their meals with peace of mind when eating out, providing convenience and safety.

[1090] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1091] Program processing flow

[1092] Step 1:

[1093] The user opens the smartphone application and enters their allergy information. The entered allergy information is saved in the device's local database. Specifically, the user enters the allergens they are allergic to, such as eggs, wheat, or milk, into a form within the app and presses the save button. This input information is saved in a local database such as SQLite.

[1094] Input: User allergy information (e.g., egg, wheat, milk)

[1095] Data processing: Save allergy information from form input to local database

[1096] Output: Allergy information stored in a local database

[1097] Step 2:

[1098] A user takes a photo of the exterior of a restaurant using their smartphone camera. The captured image is saved in the device's internal buffer. The user then presses the camera button to capture the exterior of the restaurant. At this point, the image file is stored in the device's memory.

[1099] Input: Store exterior image

[1100] Data processing: Save image files to internal buffer

[1101] Output: Saved image file

[1102] Step 3:

[1103] The device uses the Google Cloud Vision API to analyze the captured image and identify the store. This analysis process extracts the store's name and other identifying information. Specifically, the device uploads the captured image and receives the results of OCR and logo recognition.

[1104] Input: Store exterior image

[1105] Data processing: Identifying stores using image analysis technology (Google Cloud Vision API)

[1106] Output: Identified store information (e.g. store name, address)

[1107] Step 4:

[1108] The server receives the information about the identified store and retrieves the menu information for that store from the database. The server executes an appropriate query to the database based on the received store information to retrieve the menu information.

[1109] Input: Identified store information

[1110] Data manipulation: Performing database queries

[1111] Output: Retrieved menu information

[1112] Step 5:

[1113] The server filters the acquired menu information based on the user's allergy information. Specifically, the server takes the user's allergy information into consideration and extracts menu items that do not contain harmful substances.

[1114] Input: User allergy information, menu information

[1115] Data processing: filtering menu information

[1116] Output: Filtered menu information

[1117] Step 6:

[1118] The device will display the filtered menu information along with a unified allergy icon. Specifically, the filtered menu information will be displayed on the device's user interface, allowing users to check the appropriate menu at a glance.

[1119] Input: Filtered menu information

[1120] Data processing: Integrating menu information and allergy icons

[1121] Output: Menu information displayed in the user interface

[1122] In this way, the user can quickly check the menu items that cater to his or her allergies based on the photographed image of the exterior of the store.

[1123] 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.

[1124] An example of this system will be described in detail below. In the following example, a system is provided that allows a user to register their own allergy information via a smartphone application, and further recognizes the user's emotions and provides appropriate menu information when dining out.

[1125] User enters allergy information

[1126] First, users open the smartphone app and enter their allergy information (e.g., eggs, wheat, milk, etc.). This information is stored in the smartphone's local database or on the server. Users can later change or add to the stored allergy information.

[1127] Photographing and analyzing store exteriors

[1128] A user takes a photo of a restaurant's exterior with their smartphone camera. The device stores the image in an internal buffer and uses image analysis techniques (e.g., OCR, logo recognition, etc.) to identify the restaurant. This identified restaurant information is then sent to the server.

[1129] Acquiring user emotion information

[1130] The emotion engine installed on the device extracts emotional information from the user's facial expressions and tone of voice based on sensor data from cameras, microphones, etc. This emotional information is then sent to the server along with allergy information.

[1131] The server obtains store information and performs filtering.

[1132] The server retrieves the menu information for a specific restaurant from a database based on the restaurant information received. It then filters out menu items that do not contain any allergens (e.g., eggs, wheat, milk, etc.) based on the allergy information registered by the user in advance. It also takes into account the user's emotional information and adjusts the priority and display method of the filtering results.

[1133] User Interface Display

[1134] The device receives the menu information returned from the server and visually displays it in the user interface. The menu information includes standardized allergy icons, allowing users to quickly identify menu items suitable for them. Specific menu items may also be recommended based on emotional information. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed preferentially.

[1135] Specific use cases

[1136] For example, a user (Hanako) registers in a smartphone app that she has egg and wheat allergies. When she takes a photo of the exterior of a nearby cafe, the image is analyzed to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. The filtered menu information is sent back to the device and displayed on Hanako's smartphone. If Hanako's facial expression indicates that she is stressed, menu items such as "herbal tea" that has a relaxing effect are recommended.

[1137] In this way, the present invention allows users to make safe meal choices when dining out based on allergy information, and can even take emotional state into account to provide a pleasant dining experience.

[1138] The processing flow will be explained below.

[1139] Step 1:

[1140] The user opens the smartphone app and enters allergy information. Specifically, the user selects the allergens (e.g., eggs, wheat, milk, etc.) and enters them into the app. This information is stored in the device's local database or on the server.

[1141] Step 2:

[1142] The device verifies the allergy information entered, confirms that the information entered is in the correct format, and if there are no problems, proceeds to save the information.

[1143] Step 3:

[1144] A user takes a photo of the exterior of a restaurant using their smartphone camera. The device stores the captured image data in an internal buffer.

[1145] Step 4:

[1146] The device performs image analysis (e.g., OCR, logo recognition, etc.) to identify the store from the captured image, extracts the identified store information, and prepares a request to send to the server.

[1147] Step 5:

[1148] The device sends the specified store information to the server. The request includes the store name, location, and other information.

[1149] Step 6:

[1150] The device's emotion engine extracts emotional information from the user's facial expressions and tone of voice, which indicates states such as stress, joy, and excitement, and transmits this information to the server.

[1151] Step 7:

[1152] Based on the store information received by the server, the menu information for the specific store is retrieved from the database. If necessary, the data is updated from a third-party allergy information provider.

[1153] Step 8:

[1154] The server filters the menu based on the user's allergy information, for example, selecting menu items that do not contain eggs or wheat, and also considers the user's emotional information, prioritizing menu items that correspond to a specific emotional state.

[1155] Step 9:

[1156] The server prepares a response for returning the filtered menu information together with the image data to the terminal, which includes the menu information with the photo.

[1157] Step 10:

[1158] The terminal validates the data received from the server and checks the consistency and accuracy of the menu information.

[1159] Step 11:

[1160] The device displays the filtered menu information on the user interface. Specifically, menu items are displayed in a unified format, including allergy icons. The system also takes into account the user's emotional information and recommends menu items such as "herbal tea" when relaxation is needed.

[1161] Through the above steps, the system not only allows users to easily and safely check allergy-friendly menu items when eating out, but also helps users select more appropriate menu items by taking into account the user's emotional state.

[1162] Example 2

[1163] 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."

[1164] Conventional restaurant selection support systems have the ability to filter menus based on the user's allergy information, but lack the ability to provide menus that take the user's emotional information into consideration. This makes it difficult to support users in choosing meals that satisfy them psychologically when eating out, and there is a need for an integrated approach to allergy and emotional information. Furthermore, there are challenges in properly managing the information entered by the user and improving the accuracy of restaurant identification through exterior image analysis.

[1165] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes a means for acquiring menu information of the identified restaurant, a means for filtering menus based on the user's allergy information, and a means for adjusting the filtering result based on the user's emotional information. This allows the user to select a menu that is safe and psychologically satisfying when eating out by taking the user's allergy information and emotional information into consideration in an integrated manner.

[1166] Below are definitions of important words.

[1167] "User" refers to an individual who uses this system.

[1168] "Allergy Information" refers to information about a user's self-reported allergic reactions to specific ingredients.

[1169] "Terminal" refers to a mobile computing device used by a user, such as a smartphone or tablet.

[1170] "Input means" refers to the interface and functions required for users to input allergy information into the system using a terminal.

[1171] "Means to validate and store" refers to the ability to accurately verify entered allergy information and store it in a local or remote database.

[1172] "Means for taking photographs" refers to the function of acquiring images using the camera function built into the terminal.

[1173] "Image analysis technology" refers to technology for extracting and identifying useful information from captured images.

[1174] "Means for identifying" refers to the function of extracting and identifying specific information (e.g., store information) using image analysis technology.

[1175] "Sensor data" refers to digital data obtained from sensors such as cameras and microphones installed on devices.

[1176] "Emotional information" refers to information that analyzes and determines the user's emotional state (e.g., joy, sadness, stress) based on sensor data.

[1177] "Means for transmitting" refers to a communication function for transmitting information (e.g., store information, emotional information) from a terminal to a server.

[1178] A "server" refers to a computer system that communicates with terminals via a network and performs data processing, menu information acquisition, filtering, etc.

[1179] "Menu information" refers to information about the food and drinks served at a restaurant.

[1180] "Filtering means" refers to the ability to sort data (e.g., menu items) based on specific conditions and exclude unwanted items.

[1181] "Adjustment means" refers to a function that changes the display order or recommended items based on the filtering results, taking into account specific conditions (e.g., emotional information).

[1182] "Means for visual display" refers to a function that displays data on the terminal screen in a format that can be visually understood by the user.

[1183] The present invention relates to a system that allows users to register their own allergy information and provides appropriate menu information when dining out based on emotional information. This system involves the user inputting allergy information, photographing and analyzing the exterior of the restaurant, acquiring emotional information, filtering and adjusting the information by the server, and displaying the filtered results on a terminal.

[1184] First, when a user opens the smartphone application, an interface for entering their allergy ingredients (e.g., eggs, wheat, milk, etc.) is displayed. The user manually enters this information and presses the save button. The device (smartphone) then stores this information in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[1185] Next, users can take a photo of the restaurant's exterior with their smartphone camera. The device stores the captured image in an internal buffer and then analyzes it using OCR (optical character recognition) and logo recognition technology to identify the restaurant. This analysis is performed using image analysis software such as Tesseract-OCR and Google Cloud Vision API.

[1186] Store information obtained through image analysis is sent from the device to a server. The device's built-in emotion engine then acquires the user's emotional information based on sensor data from the camera, microphone, and other devices. For example, OpenCV is used for facial expression analysis, and a different algorithm is applied to voice tone analysis. This emotional information is also sent to the server.

[1187] The server retrieves the menu information for the relevant store from a database (e.g., PostgreSQL, MySQL) based on the received store information. It then filters the menu based on the user's allergy information, excluding menu items containing allergens. The filtered results are then adjusted to take into account the user's emotional information. For example, if it is determined that the user is feeling stressed, adjustments will be made to prioritize the display of menu items with a relaxation effect (e.g., herbal tea).

[1188] Finally, the filtered and adjusted menu information is sent back to the device, which receives it and displays it in a visually friendly user interface. The displayed menu includes standardized allergy icons, allowing users to see at a glance which menu is suitable for them.

[1189] Specific use cases

[1190] For example, a user named Hanako registers her egg and wheat allergies in a smartphone application. When she takes a photo of the exterior of a nearby cafe, the device analyzes the image to identify the specific cafe. This information is sent to a server, which retrieves the cafe's menu and filters out menu items that do not contain eggs or wheat. If the emotion engine then determines that Hanako is feeling stressed, it will recommend a "herbal tea" with a relaxing effect.

[1191] Prompt Sentence Examples

[1192] Hanako registered her egg and wheat allergy information in a smartphone application and took a photo of the exterior of a nearby cafe with her camera. The server then analyzed the cafe's menu information and displayed egg- and wheat-free menu items on Hanako's smartphone. The application also determined that Hanako was feeling stressed, so it recommended a menu item with a relaxation effect.

[1193] This system allows users to make safe and satisfying food choices that take into account their allergy information and emotional state.

[1194] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1195] Step 1: The user enters their allergy information

[1196] The user opens the smartphone application and enters the ingredients to which they are allergic (eggs, wheat, milk, etc.). The allergy information entered by the user is treated as "input data." The device (smartphone) validates this input data, and if there are no problems, it stores it in a local database (e.g., SQLite) or a remote database (e.g., Firebase).

[1197] Input: Allergy ingredient information entered by the user

[1198] Output: Save verified allergy information

[1199] Specific operation: When the user enters the allergens and presses the save button, the device saves the entered information in the database.

[1200] Step 2: The user takes a photo of the restaurant's exterior

[1201] A user takes a photo of the exterior of a restaurant using their smartphone camera, and the device stores the image in an internal buffer.

[1202] Input: Restaurant exterior image

[1203] Output: Saved image data

[1204] Specific operation: The user opens the camera app, takes a picture of the restaurant's exterior, and the image is saved in the device's internal buffer.

[1205] Step 3: The device analyzes the image to identify and send store information

[1206] The device uses the images stored in the internal buffer to analyze the text and logos in the images using OCR (Optical Character Recognition) and logo recognition technology, identifies the store from the analyzed data, generates store information, and then sends the identified store information to a remote server.

[1207] Input: Saved image data

[1208] Output: Sending the identified store information

[1209] Specific operation: The device analyzes the stored image data using OCR technology, obtains store information, and sends it to the server.

[1210] Step 4: The device acquires and transmits the user's emotional information.

[1211] The emotion engine installed on the device acquires the user's emotional information based on sensor data from the camera and microphone. The acquired emotional information is analyzed using facial expression analysis technology (e.g., OpenCV) and voice analysis technology. The generated emotional information is sent to the server.

[1212] Input: Sensor data from camera and microphone

[1213] Output: Sending acquired emotion information

[1214] Specific operation: The device captures the user's facial expressions with a camera and records their voice with a microphone, analyzes this data to generate emotional information, and sends it to the server.

[1215] Step 5: The server retrieves the store menu information and performs filtering.

[1216] Based on the received store information, the server retrieves the menu information for the store from a database (e.g., PostgreSQL, MySQL), then references the user's allergy information and filters out menu items that do not contain allergens.

[1217] Input: Store information, allergy information

[1218] Output: Filtered menu information

[1219] Specific operation: The server retrieves menu information from the database and uses that information to extract items that do not contain allergens.

[1220] Step 6: The server adjusts the filtering results based on the user's emotions.

[1221] The server uses emotion information to adjust the priority of filtered menu items. For example, if a user is feeling stressed, menu items with a relaxation effect will be displayed at the top.

[1222] Input: filtered menu information, emotion information

[1223] Output: Adjusted menu information

[1224] Specific behavior: The server analyzes the emotional information and adjusts the display order of the filtered menu items.

[1225] Step 7: The device displays the filtered menu information

[1226] The device receives the filtered menu information returned from the server and displays the menu items in a visually identifiable format on the user interface. The displayed menu includes allergy icons and also provides emotion-based recommendations.

[1227] Input: Adjusted menu information

[1228] Output: Menu information to be displayed

[1229] Specific operation: Based on the menu information received by the terminal, it displays it in an easy-to-understand user interface.

[1230] (Application example 2)

[1231] 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."

[1232] Existing menu suggestion systems for dining out allow users to input and manage allergy information, but do not suggest menus that take into account the user's emotional state. This poses a problem of a lack of psychological support for users to enjoy their meals. Furthermore, there is insufficient consideration given to allowing users to easily select safe menus that are suitable for them.

[1233] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1234] In this invention, the server includes a means for acquiring the user's allergy information and emotional information, a means for photographing the exterior of a restaurant to identify the restaurant, and a means for filtering menus based on the allergy information and emotional information. This allows the user to not only select a safe menu based on their own allergy information, but also to receive menu suggestions tailored to their emotional state. Furthermore, the quality of the dining experience when eating out is improved because the user can see the menu that best suits them at a glance.

[1235] A "user" is someone who uses the system to input their allergy and emotional information and receive appropriate menu suggestions.

[1236] "Allergy information" is information about ingredients that users should avoid consuming.

[1237] "Terminal" means an electronic device that processes user input information and receives and analyzes external information in a ubiquitous computing environment.

[1238] A "store" is a facility that provides meals and is a place that users visit to eat out.

[1239] "Emotion information" is information about the user's psychological state that is recognized based on the user's facial expression, tone of voice, and the like.

[1240] A "server" is a central computing system for receiving and processing data sent from multiple terminals.

[1241] "Menu information" is a list of food and drink items served at a particular establishment.

[1242] "Filtering" is the process of selecting data based on specific conditions and removing unnecessary data.

[1243] "Display" means providing information visually on the screen of a terminal.

[1244] A "system" is an integrated structure in which multiple devices and software work together to provide a specific function.

[1245] A "standardized allergy icon" is an allergy display symbol with a uniform design that is visually easy for users to recognize.

[1246] "Recommended Menu" refers to food and drink options that are specifically recommended based on the user's allergy and emotional information.

[1247] A specific embodiment of the present invention will be described. The system acquires allergy information and emotional information of a user and provides appropriate menu information when dining out. The details of this system are described below.

[1248] Hardware and software used

[1249] This system uses a smartphone, server, camera, and microphone as its main hardware. The software includes an image analysis engine (e.g., OpenCV), an emotion engine (e.g., emotion_engine), a server-side database system, and a menu information filtering function.

[1250] Details of data processing and calculation

[1251] Entering and confirming user allergy information

[1252] Users first enter their allergy information using a smartphone app. This information is stored in the smartphone's local database or on a cloud server. Users can also change or add to this information later.

[1253] Store exterior photography and analysis

[1254] The user takes a photo of the exterior of the restaurant they want to visit with their smartphone camera. The device acquires the captured image data and identifies the restaurant using an image analysis engine (such as OpenCV). Specifically, it identifies the restaurant's logo, sign, etc. from the image and sends this information to the server.

[1255] Acquiring emotional information

[1256] Using the smartphone's camera and microphone, emotional information is collected from the user's facial expressions and voice. An emotion engine (e.g., emotion_engine) is used for this. The acquired emotional information is sent to the server along with allergy information.

[1257] Retrieving and filtering menu information

[1258] The server retrieves the menu information of the identified restaurant from the corresponding database, then filters out safe menu items based on the user's allergy information, and further prioritizes the menu items based on the user's emotional information to determine the recommended menu.

[1259] User Interface Display

[1260] The filtered menu information is displayed on the smartphone user interface, along with standardized allergy icons, allowing users to quickly identify menu options suitable for them. Specific menu options are also recommended based on emotional information.

[1261] Specific examples

[1262] For example, suppose a user enters their allergy information (egg, wheat, etc.) into their smartphone. If the user takes a photo of the exterior of a nearby cafe and shows a stressed expression, the system will filter out menu items from that cafe that do not contain allergens, and prioritize the display of relaxation-enhancing herbal teas.

[1263] Prompt Sentence Examples

[1264] markdown

[1265] You are a UX designer responsible for designing the UI for a smartphone app where users enter allergy information and emotional state. Create a wireframe for the app that has the following features:

[1266] 1. A screen where users can enter allergens (eggs, wheat, milk, etc.)

[1267] 2. Ability to take photos of store exteriors

[1268] 3. Ability to capture emotional state from camera and microphone

[1269] 4. Menu suggestion screen based on allergy information and emotional state

[1270] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1271] Step 1:

[1272] The user launches the smartphone app and enters their allergy information. The entered information is stored in the smartphone's local database or in a cloud server. Specific inputs include "egg," "wheat," and "milk." The output of this step is the stored allergy information.

[1273] Step 2:

[1274] The user takes a photo of the exterior of the restaurant they are visiting with their smartphone camera. The device acquires the captured image data and stores it in an internal buffer. The input is an image of the restaurant's exterior, which is used for analysis in the next step. The output is the image data stored in the buffer.

[1275] Step 3:

[1276] The device analyzes the stored exterior image. It uses an image analysis engine (such as OpenCV) to identify the store's logo and sign and identify the store. The input is the image data stored in the buffer, and the output is the identified store information (store name, address, etc.). This information is sent to the server.

[1277] Step 4:

[1278] The device uses the camera and microphone to acquire the user's emotional information. An emotion engine (such as emotion_engine) is used to analyze the user's facial expressions and tone of voice to recognize their emotional state (e.g., stress, joy, etc.). The input is sensor data acquired from the camera and microphone, and the output is the recognized emotional information. This information is also sent to the server.

[1279] Step 5:

[1280] The server retrieves the menu information of the identified restaurant from the database. The input is the restaurant information, and the output is the restaurant's menu information. The server then filters the menu based on the user's allergy information. This filtering process excludes items containing allergens. The input is the menu information and allergy information, and the output is the filtered safe menu items.

[1281] Step 6:

[1282] The server then adjusts the priority of the menu items based on the emotional information. For example, if the user is feeling stressed, it will prioritize menus with a relaxation effect. The input is the filtered menu items and emotional information, and the output is a recommended menu with adjusted priorities.

[1283] Step 7:

[1284] The terminal receives the recommended menu information returned from the server and visually displays it on the user interface. Standardized allergy icons are also displayed, allowing users to check the menu that is suitable for them at a glance. The input is the recommended menu information, and the output is a visual menu list displayed on the smartphone screen.

[1285] 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.

[1286] 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.

[1287] 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.

[1288] 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.

[1289] 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.

[1290] 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.

[1291] 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).

[1292] 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.

[1293] 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."

[1294] 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.

[1295] 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).

[1296] 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.

[1297] 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.

[1298] 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.

[1299] 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.

[1300] 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.

[1301] 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.

[1302] 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.

[1303] 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.

[1304] 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.

[1305] 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.

[1306] The following is further disclosed regarding the above embodiment.

[1307] (Claim 1)

[1308] A means for a user to input his / her allergy information;

[1309] means for the terminal to verify and store the entered allergy information;

[1310] A means for the terminal to photograph the exterior of the store and identify the store;

[1311] A means for the server to acquire menu information of the identified store;

[1312] means for the server to filter menus based on the user's allergy information;

[1313] means for the terminal to display filtered menu information;

[1314] A system including:

[1315] (Claim 2)

[1316] 2. The system according to claim 1, further comprising means for analyzing an exterior image of a store to identify the store.

[1317] (Claim 3)

[1318] 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

[1319] "Example 1"

[1320] (Claim 1)

[1321] A means for a user to input and save his / her allergy information;

[1322] means for the terminal to photograph the exterior of the store and store the image in an internal buffer;

[1323] A means for analyzing the image captured by the terminal to identify the store and transmitting the information to a server;

[1324] A means for the server to acquire menu information and allergy information of the identified restaurant from a database;

[1325] a means for the server to filter the menu based on the user's allergy information and return the filtered menu information to the terminal;

[1326] means for visually displaying the filtered menu information received by the terminal;

[1327] A system including:

[1328] (Claim 2)

[1329] 2. The system according to claim 1, further comprising means for analyzing an exterior image of the store using image analysis technology to identify the store.

[1330] (Claim 3)

[1331] 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

[1332] "Application Example 1"

[1333] (Claim 1)

[1334] A means for a user to input his / her allergy information;

[1335] means for the terminal to verify and store the entered allergy information;

[1336] A means for the terminal to photograph the exterior of the store and identify the store;

[1337] A means for the terminal to identify a store using image analysis technology;

[1338] A means for the server to acquire menu information of the identified store;

[1339] means for the server to filter menus based on the user's allergy information;

[1340] a means for the terminal to display the filtered menu information together with a unified allergy icon;

[1341] A system including:

[1342] (Claim 2)

[1343] 2. The system according to claim 1, further comprising means for analyzing an exterior image of a store to identify the store.

[1344] (Claim 3)

[1345] 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

[1346] "Example 2: Combining Emotion Engines"

[1347] (Claim 1)

[1348] A means for a user to input his / her allergy information;

[1349] means for the terminal to verify and store the entered allergy information;

[1350] A means for the terminal to take an image of the exterior of the store and identify the store using image analysis technology;

[1351] A means for the device to acquire user emotional information based on sensor data from cameras, microphones, etc.

[1352] a means for the terminal to transmit store information and user emotion information to a server;

[1353] A means for the server to acquire menu information of the identified store;

[1354] means for the server to filter menus based on the user's allergy information;

[1355] A means for the server to adjust the filtering result based on the user's emotion information;

[1356] means for the terminal to visually display the filtered menu information;

[1357] A system including:

[1358] (Claim 2)

[1359] 2. The system according to claim 1, further comprising means for analyzing an exterior image of a store to identify the store.

[1360] (Claim 3)

[1361] 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

[1362] "Application example 2 when combining emotion engines"

[1363] (Claim 1)

[1364] A means for a user to input his / her allergy information;

[1365] means for the terminal to verify and store the entered allergy information;

[1366] A means for the terminal to photograph the exterior of the store and identify the store;

[1367] A means for the terminal to acquire emotion information of a user;

[1368] A means for the server to acquire menu information of the identified store;

[1369] A means for the server to filter the menu based on the user's allergy information and emotion information;

[1370] means for the terminal to display filtered menu information;

[1371] A system including:

[1372] (Claim 2)

[1373] 2. The system according to claim 1, further comprising means for analyzing an exterior image of a store to identify the store.

[1374] (Claim 3)

[1375] 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

[1376] (Claim 4)

[1377] 10. The system of claim 1, further comprising: means for providing a recommended menu to the user based on the affective information. [Explanation of symbols]

[1378] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for a user to input his / her allergy information; means for the terminal to verify and store the entered allergy information; A means for the terminal to photograph the exterior of the store and identify the store; A means for the server to acquire menu information of the identified store; means for the server to filter menus based on the user's allergy information; means for the terminal to display filtered menu information; A system including:

2. The system according to claim 1 , further comprising means for analyzing an exterior image of a store to identify the store.

3. 10. The system of claim 1, wherein the terminal further comprises means for displaying menu information using standardized allergy icons.

Images