System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring a product image by an image acquisition device; means for extracting text information from the product image using an optical character recognition means; means for searching product information based on the extracted text information; means for collating registered allergy information of a user with the product information; and means for displaying a warning when an allergic substance is contained based on the collation result.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] When purchasing food or daily necessities, there is a risk that consumers will mistakenly purchase a product that contains an ingredient to which they are allergic. This risk is particularly pronounced for consumers with multiple allergies or for products with unclear ingredient labels. Furthermore, there are often no systems that can accommodate minor allergies, resulting in a lack of an environment in which consumers can choose products with confidence. To solve this issue, a system is needed that allows consumers to check allergy information simply by scanning the product using a device such as a smartphone. [Means for solving the problem]

[0005] In order to solve the above-mentioned problems, the present invention provides the following means. First, a means for acquiring a product image using an image acquisition device is provided. Next, a means for extracting text information from the product image using optical character recognition means is provided. Furthermore, a means for searching for product information based on the extracted text information is provided. Product information can be searched for from a product database via a network. Next, a means for comparing the product information with the user's registered allergy information is provided, and a means for displaying a warning if the product contains an allergen is provided. This warning can include a message containing specific information about the allergen. With these means, consumers can easily check whether a product contains ingredients that are relevant to their allergies simply by scanning it.

[0006] "Image capture device" refers to a device, such as a camera or scanner, used to capture product images.

[0007] "Optical character recognition means" refers to a means for extracting character information from an image using OCR (optical character recognition) technology.

[0008] "Text information" refers to character data extracted from product images, and includes information such as product names and ingredient lists.

[0009] "Product information" refers to detailed product information obtained through a search, and is data that mainly includes ingredient information and product name.

[0010] "Users" refer to consumers who use the system to register their allergy information and scan and check products.

[0011] "Allergy information" refers to information registered by the user about allergies to specific ingredients or substances, and is an important criterion when selecting products.

[0012] The "means for displaying a warning" is a means for visually notifying the user of information when an allergen is detected.

[0013] "Network" refers to communication infrastructure such as the Internet or a local area network (LAN), and is a communication path used to obtain product information.

[0014] A "product database" refers to a database that stores product information in a structured manner, and is an information source used for product searches.

[0015] "Matching" refers to the process of comparing a user's allergy information with product information to see if it contains any matching allergens. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0038] System Configuration

[0039] The system is broadly composed of the following elements:

[0040] 1. On the user's device:

[0041] The device is equipped with a camera for scanning products on a user's smartphone or tablet, and a display for displaying the results. An application is installed on the device, and it has the function of managing the user's allergy information.

[0042] 2. Server:

[0043] It is installed on the cloud and has a database that stores product information, a search engine for searching it, and logic to match user allergy information with product information.

[0044] Implementation of the invention

[0045] 1. Scan the product

[0046] Users use their device's camera to scan a product's barcode, QR code, or entire packaging. The device then uses the captured image data to extract product information, using optical character recognition (OCR) technology to extract text information such as the product name and ingredient list.

[0047] 2. Search for product information

[0048] The text information extracted by the terminal is sent to the server. The server searches the product database based on the received text information to obtain the ingredient information and other related information of the corresponding product. If the corresponding product is not found, the server can search for similar products and use that information.

[0049] 3. Checking allergy information

[0050] The server compares the allergy information registered by the user with the ingredient list of the product information it retrieves, and if an allergen is found to be present, it generates a warning message with detailed information.

[0051] 4. Displaying the results

[0052] The matching results sent from the server are received by the terminal. The terminal visually displays the results to the user, and if an allergen is found to be present, a warning such as red is displayed. This allows the user to intuitively confirm the safety of the product.

[0053] Specific examples

[0054] For example, when a user wants to buy a chocolate bar at a supermarket, they scan the product with their smartphone camera. At this time, the device extracts the product name "Chocolate Bar" and its ingredients using OCR and sends this information to the server. The server then searches its database to see if the product contains peanuts and compares it with the user's allergy information. If it does contain peanuts, a warning message is generated and sent to the device. The user's device then displays a red warning message saying "Warning: This product contains peanuts."

[0055] This system allows users to easily check whether a product contains any of their allergens when purchasing it, allowing them to make purchases with peace of mind.

[0056] The processing flow will be explained below.

[0057] Step 1:

[0058] The user uses the device's camera to capture an image of the product. The user launches the camera application and points the camera at the product packaging, barcode, or QR code to take a picture.

[0059] Step 2:

[0060] The device temporarily stores the acquired product images in its internal memory. At this point, the images are not yet processed and are stored in their raw form.

[0061] Step 3:

[0062] The device invokes an optical character recognition (OCR) tool to extract text information such as the product name, ingredients, and barcode from the saved product image. The text information obtained by OCR is saved in a variable.

[0063] Step 4:

[0064] The device analyzes the extracted text information to identify product names and ingredient information, which is then prepared as structured data to be sent to the server.

[0065] Step 5:

[0066] The device then makes a network request to send the identified product name and ingredient information to the server, along with the user's identity and other contextual information.

[0067] Step 6:

[0068] The server analyzes the received request and searches the database for product information. Based on the product name and ingredient information, the server retrieves detailed information about the corresponding product from the database.

[0069] Step 7:

[0070] The server compares the acquired product information with the allergy information registered by the user, checks whether the product contains any allergens, and generates a warning if any allergens match.

[0071] Step 8:

[0072] The server creates a response containing the matching results and sends it to the user's device. The response includes detailed information about the allergens and a warning message if any allergens are present.

[0073] Step 9:

[0074] The device analyzes the received response and displays a warning message to the user if an allergen is found to be present. The warning message is displayed in a visually noticeable manner, such as in red.

[0075] Step 10:

[0076] The user reviews the displayed warning message and decides whether to continue with the purchase. At this point, the user is armed with the information to make a safe product choice.

[0077] The above is a specific processing flow for carrying out the present invention.

[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] There are currently many products on the market, and there is a demand for a method to quickly check the extent to which each ingredient contributes to a user's allergies. However, conventional methods require users to personally check the product packaging and compare the ingredient list with their own allergy information, which is time-consuming and laborious, and also carries a high risk of overlooking something. The present invention aims to solve these problems and provide a system that can quickly and accurately check the presence of allergens while reducing the user's effort.

[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 extracting text information from product images using optical character recognition means, means for transmitting the extracted text information to a central processing unit via a network, means for the central processing unit to search a product database based on the transmitted text information and obtain product information, means for the central processing unit to compare the product information with the user's registered allergy information, means for generating a warning message if an allergen is contained based on the comparison result and transmitting the warning message to the user's device, and means for the user's device to visually display the result including the warning message. This allows the user to check the allergen content status of a product in a short time after scanning it, enabling safe and fast product selection.

[0083] An "image capture device" is a device for capturing product images, including a camera, scanner, etc.

[0084] "Optical character recognition" is a technology for analyzing character information from image data and extracting text information.

[0085] A "Central Processing Unit" is a computer system that runs on a server or cloud and analyzes and processes received data.

[0086] "Text information" is character information extracted from product images, including product names and ingredient lists.

[0087] "Product database" means a database that stores information about products, including ingredient information and other product information.

[0088] A "network" is an infrastructure for data communication, including the Internet.

[0089] "Allergy information" is information about one's own allergies that is registered in advance by the user, and is a list showing allergic reactions to specific ingredients or substances.

[0090] A "warning message" is a notification message generated for a product that contains an allergen, and issues a warning to the user.

[0091] "User device" refers to a terminal used by a user, including a smartphone, tablet, etc.

[0092] "Visually displaying" means displaying information such as a warning message in a form that can be seen by the user on a display or the like.

[0093] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0094] System Configuration

[0095] The system is broadly composed of the following elements:

[0096] 1. On the user's device:

[0097] The device is a smartphone or tablet held by the user, equipped with a camera for scanning products and a display for displaying the results. The device also has an application installed to manage the user's allergy information.

[0098] 2. Server:

[0099] It is installed on the cloud and has a database that stores product information, a search engine that searches it, and logic that checks the user's allergy information against product information.

[0100] Hardware and software used

[0101] Device: Smartphone or tablet

[0102] Camera: Built-in camera

[0103] OCR software: Tesseract OCR

[0104] Cloud server: AWS (registered trademark), Google (registered trademark) Cloud, Azure (registered trademark)

[0105] Database: MySQL (registered trademark), PostgreSQL

[0106] Search engine: ElasticSearch (registered trademark)

[0107] Specific examples of processing

[0108] Product scanning

[0109] When a user goes to the supermarket to buy a chocolate bar, they scan the item with their smartphone camera. The device captures the image data and analyzes it with optical character recognition (OCR) software. For example, Tesseract OCR can be used to extract the ingredients, such as "chocolate bar" and "peanuts, sugar, cocoa."

[0110] Submitting and searching product information

[0111] The device uses an HTTP POST request to send this extracted text information to the server. For example, "{"product_name": "Chocolate bar", "ingredients": "Peanuts, Sugar, Cocoa"}". The server searches the product database based on the received information and retrieves the ingredient information for the corresponding product. It uses MySQL for the search, and if the corresponding product is not found, it uses Elasticsearch to search for similar products.

[0112] Matching with allergy information and generating results

[0113] The server compares the user's allergy information with the product's ingredient list. For example, if the user has registered a peanut allergy, the server verifies that the ingredient list includes "peanuts." Based on the comparison result, the server generates a warning message saying "Warning: This product contains peanuts" and sends it to the terminal.

[0114] Displaying the results

[0115] The user's device visually displays the warning message received from the server. For example, it displays "Warning: This product contains peanuts" on a red background to warn the user. This allows the user to intuitively confirm the safety of the product.

[0116] Prompt Sentence Examples

[0117] "What ingredients does this product contain?"

[0118] "Please tell me the list of ingredients in the product called 'Chocolate Bar'."

[0119] Does this product contain allergens?

[0120] This system allows users to easily check whether a product contains substances that they are allergic to when purchasing it, allowing them to make purchases with peace of mind.

[0121] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0122] Step 1: Product Scan

[0123] User: The user uses the camera on their smartphone or tablet to scan the barcode, QR code, or entire packaging of the product.

[0124] Input: Image data of product packaging

[0125] Output: Image data is saved to the device

[0126] Specific behavior: The user launches the camera app, points the camera at the product, and presses the scan button. The camera captures an image of the product packaging.

[0127] Step 2: Extracting text information

[0128] Terminal: The terminal analyzes the acquired image data using optical character recognition (OCR) software (e.g., Tesseract OCR) to extract text information such as the product name and ingredient list.

[0129] Input: Image data

[0130] Output: Extracted text information (e.g. "Chocolate bar", "Peanuts, sugar, cocoa")

[0131] Specific operation: Through OCR processing, text information is analyzed from image data and structured in JSON format.

[0132] Step 3: Send text information

[0133] Terminal: The extracted text information is sent to the server via the network. Specifically, JSON data is sent using an HTTP POST request.

[0134] Input: Text information (JSON format)

[0135] Output: Text information sent to the server

[0136] Specific operation: An application in the device generates an HTTP request, attaches the extracted text information, and sends it to the server.

[0137] Step 4: Find product information

[0138] Server: The server searches the product database based on the text information sent and retrieves the ingredient information for the corresponding product. MySQL and Elasticsearch are used for the search.

[0139] Input: Text information (product name and ingredient list)

[0140] Output: Product information (ingredients list and related information)

[0141] Specific operation: The server executes a database query based on the received text information and retrieves detailed information about the corresponding product. Example of database query execution: "SELECT FROM products WHERE name="Chocolate bar""

[0142] Step 5: Check against allergy information

[0143] Server: The server compares the ingredient list of the acquired product information with the allergy information registered in advance by the user, and performs a process to check whether the product contains any allergens.

[0144] Input: Product information (ingredients list), user allergy information

[0145] Output: Matching result (whether or not allergens are included)

[0146] Specific operation: The server compares the product ingredients with the user's allergy information, and if there are any matching substances, determines the risk of an allergic reaction.

[0147] Step 6: Generate a warning message

[0148] Server: Based on the matching results, if an allergen is found, generate a warning message. For example, create a message saying "Warning: This product contains peanuts."

[0149] Input: Matching result

[0150] Output: Warning message

[0151] Specific operation: Based on the matching results, the system runs a process to automatically generate a warning message. The generated message is saved in text format.

[0152] Step 7: Sending and displaying warning messages

[0153] Server: The generated warning message is sent to the user's terminal as an HTTP response.

[0154] Terminal: Visually display the warning message received from the server to the user, for example displaying the message "Warning: This product contains peanuts" on a red background.

[0155] Input: warning message

[0156] Output: Display of a warning message on the user's terminal

[0157] Specific behavior: The device receives the HTTP response, the application analyzes its contents, and displays a visual warning to the user.

[0158] In this way, users can easily check whether a product contains their allergens and choose products safely.

[0159] (Application example 1)

[0160] 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."

[0161] There is a lack of means for passengers of self-driving vehicles to quickly and accurately check the ingredient information of food and beverages they purchase or bring on board, and to prevent the ingestion of allergens. Therefore, it is necessary to provide an environment where passengers can enjoy food and beverages in safety on board self-driving vehicles.

[0162] 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.

[0163] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for passengers to scan the product using a tablet terminal or a dedicated display, means for transmitting the acquired ingredient information to a cloud server, and means for comparing the ingredient information with the user's allergy information and generating a result. This enables passengers to safely check the ingredient information of food and drink even inside an autonomous vehicle and avoid the risk of allergic reactions.

[0164] An "image capture device" is a device that captures product images using a camera or the like.

[0165] "Optical character recognition" is a technology that analyzes and extracts text information from images.

[0166] The "means for searching for product information" is a function for finding relevant product information from a database based on the extracted text information.

[0167] "User's registered allergy information" refers to information about allergies that the user has previously entered and saved in the system.

[0168] The "verification means" is a function that compares the user's allergy information with product information to check whether there are any matches.

[0169] The "means for displaying a warning" is a function that displays a visual warning to the user if the result of the comparison indicates that an allergen is contained.

[0170] "Tablet device or dedicated display" refers to a portable display device used for scanning products and displaying results.

[0171] A "cloud server" is a server that stores and provides data over the Internet.

[0172] The "means for transmitting ingredient information" is a function for transmitting the acquired product ingredient information to the cloud server.

[0173] The "means for generating results" is a function that generates warnings or other notifications based on the results of matching ingredient information with the user's allergy information.

[0174] System Overview

[0175] The present invention is a system that allows users to quickly check the ingredient information of food and beverages purchased or brought into an autonomous vehicle. Specifically, it is composed of an image capture device, optical character recognition (OCR) means, database search means, allergy information checking means, warning display means, a tablet terminal or dedicated display, a cloud server, ingredient information transmission means, and result generation means.

[0176] Hardware and software used

[0177] Image capture device: Camera installed in the vehicle or camera on a tablet device.

[0178] Optical Character Recognition: Tesseract OCR is used to extract text information from product images.

[0179] Cloud server: AWS is used as the cloud environment, AWS RDS is used as the database, and Elasticsearch is used as the search engine.

[0180] Tablet or dedicated display: A means for passengers to scan items and view results.

[0181] Application framework: Use Flutter® or React Native to build the user interface.

[0182] Specific Examples of the Invention

[0183] To implement this system, the user performs the following operations: First, the passenger scans the product using a tablet device or dedicated display. The scanned product image is captured by an image capture device. Next, text information is extracted from the product image using optical character recognition (Tesseract OCR). This text information is sent to a cloud server, where a database search is performed. The captured product information is compared with allergy information previously registered by the user.

[0184] If an allergen is found in a product, a warning message will be generated and displayed on the tablet or a dedicated display, allowing users to safely check the product's ingredient information.

[0185] Specific examples

[0186] For example, a user scans a drink (such as juice) they have purchased in an autonomous vehicle. At this time, the ingredient information of the scanned product is sent to a cloud server and extracted using OCR. The cloud server then searches a product database to obtain the ingredient information. This ingredient information is then compared with the user's allergy information, and if the drink contains an allergen, a warning message is displayed on the tablet device.

[0187] Prompt Sentence Examples

[0188] It uses a camera to scan drinks (juices) purchased by passengers in the vehicle, then uses OCR technology to extract the ingredients and search the AWS RDS database, matching them with the user's allergy information and displaying the results on the passenger's smart display.

[0189] This system allows passengers to enjoy meals and drinks safely inside self-driving vehicles.

[0190] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0191] Step 1:

[0192] The user scans the product using a tablet device or dedicated display.

[0193] Input: Product packaging image

[0194] What it does: The user uses the camera to scan the barcode of an item or the entire package.

[0195] Step 2:

[0196] The image capture device captures product images.

[0197] Input: scanned package image

[0198] Specific operation: The tablet device's camera captures product images and saves them to its internal memory.

[0199] Step 3:

[0200] Extract text information from product images using optical character recognition (OCR).

[0201] Input: Captured product image

[0202] Specific operation: The device calls Tesseract OCR, analyzes the text information in the image, and extracts product name and ingredient information.

[0203] Output: Extracted text information

[0204] Step 4:

[0205] The extracted text information is sent to a cloud server.

[0206] Input: Extracted text information

[0207] Specific operation: The device sends the extracted text information via the Internet to the cloud server through AWS API Gateway.

[0208] Step 5:

[0209] The server searches the product database and obtains the relevant product information.

[0210] Input: Extracted text information

[0211] Specific operation: Based on the text information received by the server, Elasticsearch is used to search the product database (AWS RDS) and obtain the corresponding product information.

[0212] Output: Retrieved product information

[0213] Step 6:

[0214] The server compares the user's allergy information with the product information.

[0215] Input: Retrieved product information and user allergy information

[0216] Specific operation: The server compares the user allergy information in the database with the ingredient list of the retrieved product information to determine whether any matching allergens exist.

[0217] Output: Matching result

[0218] Step 7:

[0219] The server generates a warning message based on the result of the check and sends it to the terminal.

[0220] Input: Matching result

[0221] Specific operation: If an allergen is contained, the server generates a warning message (e.g., "Warning: Contains allergen") and sends it to the terminal.

[0222] Output: Warning message

[0223] Step 8:

[0224] The terminal visually displays a warning message to the user, and if an allergen is included, the warning is displayed in red or other colors.

[0225] Input: The warning message received from the server

[0226] Specific operation: The device will display a warning message on the screen and highlight any allergens with a red background color, for example.

[0227] This allows users to safely check the ingredient information of food and drink inside their self-driving vehicle and avoid allergic reactions.

[0228] 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.

[0229] The present invention is a system that combines an emotion engine that recognizes emotions when a user scans an item and tailors warnings based on the user's allergy information. The steps and specific operations required to implement this system are described in detail below.

[0230] System Configuration

[0231] The system consists of the following components:

[0232] 1. On the user's device:

[0233] The device, such as a smartphone or tablet held by the user, is equipped with a camera for scanning products and a camera and microphone for recognizing emotions. A dedicated application is installed on the device, which has a function for managing the user's allergy information and an emotion engine.

[0234] 2. Server:

[0235] The cloud-based server has a database that stores product information, a search engine for searching it, and logic for matching user allergy information with product information. It can also process emotional information.

[0236] 3. Emotion Engine:

[0237] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reaction.

[0238] Implementation of the invention

[0239] 1. Scan the product

[0240] Users can use their device's camera to scan product packaging, barcodes, and QR codes, and the product images captured by the camera are saved on the device.

[0241] 2. Information extraction from images

[0242] The device passes the stored product image to an optical character recognition (OCR) tool to extract text information such as the product name and ingredients, which is then prepared for transmission to the server.

[0243] 3. Search for product information

[0244] The terminal sends the extracted text information to the server, which then searches the product database based on the received information to obtain ingredient information and related information for the relevant product.

[0245] 4. Checking allergy information

[0246] The server compares the searched product information with the user's registered allergy information, and generates a result indicating whether the product contains any allergens, and if so, detailed information about the ingredients.

[0247] 5. Emotional Recognition

[0248] When a warning is displayed, the device captures the user's reaction using the device's camera and microphone, and the emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[0249] 6. Adjusting the display of warning messages

[0250] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. For example, if the user looks anxious, the device will display the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[0251] Specific examples

[0252] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[0253] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[0254] This allows users to intuitively understand important information about their allergies and decide whether to make a purchase with confidence.By taking user emotions into consideration, this system enables more effective and flexible warning messages to be displayed, improving consumer safety and peace of mind.

[0255] The processing flow will be explained below.

[0256] Step 1:

[0257] The user launches the device's camera application and scans the product packaging, barcode, or QR code. The camera captures the product image and saves the image data on the device.

[0258] Step 2:

[0259] The device launches an OCR (optical character recognition) tool to analyze the captured product image, extracting text information from the image and identifying product name and ingredient information.

[0260] Step 3:

[0261] The device sends the text information extracted by the OCR tool to the server over the network, along with the user's identification information.

[0262] Step 4:

[0263] The server analyzes the received text information and searches the product database to obtain detailed information about the corresponding product. The server searches based on the product name and ingredient information, and if no corresponding product is found, it searches for similar products.

[0264] Step 5:

[0265] The server compares the product information obtained from the search with the allergy information registered by the user, and then compares the product ingredient list with the allergy information to see if it contains any matching allergens.

[0266] Step 6:

[0267] If an allergen is present, the server generates a warning about the ingredient, including details of the specific allergen and its health risks.

[0268] Step 7:

[0269] The server transmits the generated warning information to the terminal, where it is transmitted quickly and securely, allowing the user to quickly check it.

[0270] Step 8:

[0271] The terminal analyzes the received warning information and prepares it for visual display to the user. The terminal determines the best way to display the warning message.

[0272] Step 9:

[0273] The device will capture the user's reaction using the device's camera and microphone just before displaying the warning message, collecting data for the emotion engine to analyze the user's facial expressions and voice.

[0274] Step 10:

[0275] The emotion engine installed on the device analyzes the captured user's facial expressions and voice signals to recognize the user's emotional state. For example, if the user has a surprised expression, the emotion is recognized as "surprise."

[0276] Step 11:

[0277] The device adjusts the way the warning message is displayed based on the user's emotional state as recognized by the emotion engine: if the user is surprised, the warning message is displayed in red and bold to emphasize it.

[0278] Step 12:

[0279] The device displays a tailored warning message to the user, such as "This product contains peanuts" in bold red text to grab the user's attention.

[0280] Step 13:

[0281] The user checks the displayed warning message and decides whether to continue with the purchase of the product. The user can make a safe product selection based on the provided warning information.

[0282] The above is a specific processing flow for an embodiment of the invention that combines an emotion engine, allowing users to enjoy a safer and more secure shopping experience by taking into consideration not only the product scanning process but also the emotions involved.

[0283] Example 2

[0284] 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."

[0285] Conventional systems allow users to check whether an item contains allergens when they scan it, but the warning display does not take into account the user's emotional state, which means the warning is not communicated effectively. Furthermore, while there is a need for warnings to be displayed in a way that is intuitively easy for users to understand, there is also the issue of not using emotion recognition technology to adjust the warning display.

[0286] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring product images, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for recognizing the user's emotional state, and means for displaying a warning in accordance with the user's emotional state if the product contains an allergen based on the comparison result. This makes it possible to display a warning that takes the user's emotional state into consideration, thereby ensuring effective communication of the warning.

[0287] "Means for acquiring product images" refers to devices or functions that acquire images of the product packaging, barcodes, or QR codes scanned by the user.

[0288] "Optical character recognition means" refers to a technology for extracting text information from acquired product images, and in particular uses optical character recognition (OCR) technology.

[0289] The "means for extracting text information" is a function that uses optical character recognition means to extract text information such as product names and ingredient information from the product images as digital data.

[0290] The "means for searching for product information" is a technique for searching for and acquiring the relevant product information from a product database via a network based on the extracted text information.

[0291] "User's registered allergy information" refers to information about allergies that the user has previously entered into a dedicated application and that is stored on the server.

[0292] The "means for checking product information against the allergy information" is a function that compares the acquired product information with the user's allergy information to determine whether or not the product contains an allergen.

[0293] "Means for recognizing the user's emotional state" refers to devices or technologies that analyze the user's facial expressions and voice signals to recognize the user's emotional state (surprise, anxiety, relief, etc.).

[0294] "Means for displaying a warning" refers to a device or technology that visually or audibly notifies the user if the product contains an allergen based on the comparison results.

[0295] The "means for displaying a warning depending on the user's emotional state" is a function that dynamically changes the way the warning message is displayed (color, font, emphasis, etc.) based on the user's perceived emotional state.

[0296] The present invention relates to a system that allows a user to scan a product and adjusts a warning message using an emotion engine. Specific embodiments of the system are described below.

[0297] System Configuration

[0298] The system consists of the following components:

[0299] 1. On the user's device:

[0300] The user's smartphone, tablet, or other device is equipped with a high-resolution camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed on the device, and processing is performed using an OCR tool (e.g., Tesseract) and an emotion engine (e.g., Emotion API).

[0301] 2. Server:

[0302] It is a server installed in the cloud that has a database (e.g., Elasticsearch) that stores product information and a search engine for searching it. It also has logic that matches the user's allergy information with product information. It can also process emotional information.

[0303] 3. Emotion Engine:

[0304] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reactions.

[0305] Product scanning and information extraction

[0306] First, the user uses the device's camera to scan the product packaging, barcode, or QR code. The captured product image is saved on the device, and text information such as the product name and ingredient list is extracted using an OCR tool. This allows the product information to be obtained as digital data.

[0307] Product information search and matching

[0308] The device sends the extracted text information in JSON format to the server. Based on the received information, the server uses a search engine such as Elasticsearch to search a product database and retrieves the ingredient information and related information for the relevant product. The server then compares the information with the user's registered allergy information, determines whether the product contains any allergens, and generates a result.

[0309] Emotion recognition and warning display adjustment

[0310] When displaying warning information, the device's camera and microphone are used to capture the user's reactions. The emotion engine (e.g., Emotion API) analyzes the user's facial expressions and voice to recognize their emotional state. Based on the recognition results, the way the warning message is displayed can be dynamically changed depending on the user's emotional state, such as displaying the warning message in bold red if the user looks anxious.

[0311] Specific examples

[0312] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[0313] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[0314] Prompt Sentence Examples

[0315] The following prompt sentence is input to the generative AI model to generate a warning message:

[0316] Please provide the information of the product scanned by the user. Then generate a warning message based on the user's allergy information. Based on the user's sentiment, customize the message as follows:

[0317] 1. If the user looks surprised: Display a bold red warning message

[0318] 2. If the user looks relieved: Display the warning message in normal font and color.

[0319] Example output: "This product contains peanuts."

[0320] As described above, the present invention provides a system that realizes the display of warning messages that take into account the emotional state of the user, thereby improving consumer safety and security.

[0321] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0322] Step 1: Start scanning your products

[0323] The user launches a dedicated application on a smartphone or tablet device and scans the product packaging, barcode, or QR code with the camera. The input is an image of the product captured by the user's device's camera. The output is the captured image of the product stored in the device's internal memory. Specifically, the user launches the camera application on the device, points the camera at the product, and captures the image.

[0324] Step 2: Extracting information from the image

[0325] The device inputs product images stored in its internal memory into an OCR tool (e.g., Tesseract). As input, it receives the product images stored in memory. As output, it extracts text information such as the product name and ingredient list. This text information is structured in JSON format and is ready to be sent to the server. Specifically, the device passes the stored image to the OCR tool, which then extracts the text information from the image.

[0326] Step 3: Get product information

[0327] The terminal sends the extracted text information to the server. The extracted text information (JSON format) is obtained as input. As output, a query is executed to obtain the ingredient information and related information of the target product. The server uses a search engine such as Elasticsearch based on that information to search a product database and obtains the ingredient information and related information of the relevant product. Specifically, the terminal sends JSON format data to the server, and the server executes a search query on the database.

[0328] Step 4: Check against allergy information

[0329] The server compares the searched product information with the user's registered allergy information. The input is the product information and the user's allergy information. The output is a determination of whether the product contains an allergen and detailed information about the ingredients. Specifically, the server retrieves allergy information from the user database and compares it with the product information to determine whether the product contains an allergen.

[0330] Step 5: Recognize emotions

[0331] When warning information is displayed, the device uses the device's camera and microphone to capture the user's reaction. As input, the user's facial expression data and voice data when the warning information is displayed are obtained. As output, the user's emotional state (surprise, anxiety, relief, etc.) is recognized. Specifically, the device captures the user's facial expression with the camera and records voice with the microphone, and inputs this data into an emotion engine (e.g., Emotion API) for emotion analysis.

[0332] Step 6: Adjust the display of warning messages

[0333] The device dynamically changes the way it displays warning messages based on the user's emotions recognized by the emotion engine. The input is the user's emotional state and the warning information generated in the previous stage. The output is a warning message that corresponds to the user's emotional state. Specifically, the device receives the results of the emotion engine, adjusts the display method (color, font, emphasis, etc.) of the warning message to match the user's emotions, and displays it on the screen.

[0334] As described above, this system performs detailed data processing and calculations at each processing step, enabling it to display warning messages that take into account the user's emotional state, thereby improving consumer safety and peace of mind.

[0335] (Application example 2)

[0336] 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."

[0337] While conventional product scanning systems in logistics centers display product ingredient information and allergy warnings, they do not adjust the display method to take into account employee emotions and health conditions. This creates a risk that employees may continue working while feeling stressed or tired, which can lead to problems with productivity and safety. The objective of this invention is to provide a system that solves these problems and enables employee health management.

[0338] 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.

[0339] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for recognizing the user's emotion, and means for adjusting the display method of the warning message based on the recognized emotion. This enables warnings to be displayed according to the employee's health condition, thereby improving workability and safety.

[0340] An "image capture device" is a device for capturing images of products using a photographic device such as a camera.

[0341] "Optical character recognition" is a technology that analyzes character information from captured images and converts it into digital text.

[0342] "Product information" is detailed data about a product, including information on ingredients, price, barcode information, and so on.

[0343] "Allergy information" is data relating to individual allergies registered by the user, and includes allergic reaction information to specific substances.

[0344] "Verification" is the process of comparing product information with the user's allergy information to see if they match.

[0345] A "warning message" is a notification to inform the user that an allergen is contained.

[0346] "Emotion recognition" is a technology that uses a camera and microphone to analyze a user's emotional state from their facial expressions and voice.

[0347] "Adjusting the way warning messages are displayed" refers to dynamically changing the color, font, and display format of warning messages based on the perceived emotion.

[0348] A "system" is a set of components that combine multiple means and devices to provide specific functions or services.

[0349] This invention is a system that supports employee health management and efficient work performance in logistics centers. This system has the function of recognizing the employee's emotions when scanning products and dynamically adjusting warning messages based on those emotions. The specific operation and configuration of this system are described below.

[0350] System Configuration

[0351] The system consists of the following elements:

[0352] 1. User's device

[0353] The smartphone is equipped with a camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed, which includes an optical character recognition (OCR) tool, an emotion engine, and allergy information management functions.

[0354] 2. Server

[0355] It has a database (MongoDB) that stores product information and is equipped with logic to check against the user's allergy information. It is installed on a cloud server and communicates with devices via the network.

[0356] 3. Emotion Engine

[0357] The Emotion SDK is used to recognize emotions by analyzing the user's facial expressions and voice. Implemented on the device, it adjusts the way warning messages are displayed based on the user's reactions.

[0358] Specific system behavior

[0359] 1. Scan the product

[0360] Users use their device's camera to scan the product's barcode or QR code, and the product image captured by the camera is saved on the device.

[0361] 2. Information extraction from images

[0362] The device passes the saved product image to an OCR tool (Tesseract) to extract text information such as the product name and ingredients. The extracted text information is then prepared for transmission to the server.

[0363] 3. Search for product information

[0364] The server searches the product database based on the received text information, retrieves the ingredient information and related information for the relevant product, and returns this information to the terminal.

[0365] 4. Checking allergy information

[0366] The server compares the searched product information with the user's registered allergy information, and as a result, generates a result of the comparison as to whether the product contains any allergens, and if so, generates detailed information about the ingredients, and sends it to the terminal.

[0367] 5. Emotional Recognition

[0368] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction, and an emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[0369] 6. Adjusting the display of warning messages

[0370] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. If the user has a surprised expression, the device displays the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[0371] Specific examples

[0372] For example, let's say an employee is in the middle of scanning products during peak hours. At this time, they use their smartphone camera to scan the products and extract ingredient information using OCR. The extracted information is sent to a server, and if the match indicates that the product contains an allergen, a warning message is generated. At the same time, the device's emotion engine analyzes the employee's facial expressions and voice, and if it detects high levels of stress or fatigue, it displays a message such as "Let's take a short break." An example of a prompt sentence to be used at this time could be, "An app that allows employees working at a logistics center to scan products and check for allergens. If an employee is feeling stressed, display a message encouraging them to take a break."

[0373] In this way, the system can support both employee health and work efficiency.

[0374] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0375] Step 1:

[0376] The user uses the device's camera to scan the barcode or QR code of a product, and the device processes the captured product image as input.

[0377] Step 2:

[0378] The terminal passes the acquired product image to an optical character recognition (OCR) tool (Tesseract) to extract text information such as the product name and ingredient list. In OCR processing, image data is input and the extracted text information is output.

[0379] Step 3:

[0380] The terminal sends the extracted text information to the server. The server searches the product database (MongoDB) based on the received text information and retrieves the ingredient information and related information of the corresponding product. In this data search process, the text information is used as input and the corresponding product information is output.

[0381] Step 4:

[0382] The server compares the searched product information with the user's registered allergy information. In the comparison process, the product information and allergy information are input, and the output is a determination of whether the product contains an allergen.

[0383] Step 5:

[0384] Based on the comparison result, the server generates a warning message if an allergen is found to be present and sends it to the terminal. In this warning generation process, the comparison result is used as input and the warning message is used as output.

[0385] Step 6:

[0386] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction. The capture process takes the user's facial expressions and voice data as input and prepares them for passing to the emotion engine.

[0387] Step 7:

[0388] The device uses an emotion engine (Emotion SDK) to analyze the user's emotions. The emotion analysis process takes the user's facial expressions and voice data as input and outputs analyzed emotional information.

[0389] Step 8:

[0390] The terminal adjusts the display method of the warning message based on the recognized emotion information. The display adjustment process takes the emotion information and the warning message as input and outputs the adjusted warning message. The adjusted message is displayed on the connected user interface.

[0391] This process allows employees to check allergy information when scanning products and receive appropriate warning messages based on their emotional state.

[0392] 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.

[0393] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0394] 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.

[0395] [Second embodiment]

[0396] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0397] 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.

[0398] 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).

[0399] 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.

[0400] 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.

[0401] 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).

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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.

[0407] 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."

[0408] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0409] System Configuration

[0410] The system is broadly composed of the following elements:

[0411] 1. On the user's device:

[0412] The device is equipped with a camera for scanning products on a user's smartphone or tablet, and a display for displaying the results. An application is installed on the device, and it has the function of managing the user's allergy information.

[0413] 2. Server:

[0414] It is installed on the cloud and has a database that stores product information, a search engine for searching it, and logic to match user allergy information with product information.

[0415] Implementation of the invention

[0416] 1. Scan the product

[0417] Users use their device's camera to scan a product's barcode, QR code, or entire packaging. The device then uses the captured image data to extract product information, using optical character recognition (OCR) technology to extract text information such as the product name and ingredient list.

[0418] 2. Search for product information

[0419] The text information extracted by the terminal is sent to the server. The server searches the product database based on the received text information to obtain the ingredient information and other related information of the corresponding product. If the corresponding product is not found, the server can search for similar products and use that information.

[0420] 3. Checking allergy information

[0421] The server compares the allergy information registered by the user with the ingredient list of the product information it retrieves, and if an allergen is found to be present, it generates a warning message with detailed information.

[0422] 4. Displaying the results

[0423] The matching results sent from the server are received by the terminal. The terminal visually displays the results to the user, and if an allergen is found to be present, a warning such as red is displayed. This allows the user to intuitively confirm the safety of the product.

[0424] Specific examples

[0425] For example, when a user wants to buy a chocolate bar at a supermarket, they scan the product with their smartphone camera. At this time, the device extracts the product name "Chocolate Bar" and its ingredients using OCR and sends this information to the server. The server then searches its database to see if the product contains peanuts and compares it with the user's allergy information. If it does contain peanuts, a warning message is generated and sent to the device. The user's device then displays a red warning message saying "Warning: This product contains peanuts."

[0426] This system allows users to easily check whether a product contains any of their allergens when purchasing it, allowing them to make purchases with peace of mind.

[0427] The processing flow will be explained below.

[0428] Step 1:

[0429] The user uses the device's camera to capture an image of the product. The user launches the camera application and points the camera at the product packaging, barcode, or QR code to take a picture.

[0430] Step 2:

[0431] The device temporarily stores the acquired product images in its internal memory. At this point, the images are not yet processed and are stored in their raw form.

[0432] Step 3:

[0433] The device invokes an optical character recognition (OCR) tool to extract text information such as the product name, ingredients, and barcode from the saved product image. The text information obtained by OCR is saved in a variable.

[0434] Step 4:

[0435] The device analyzes the extracted text information to identify product names and ingredient information, which is then prepared as structured data to be sent to the server.

[0436] Step 5:

[0437] The device then makes a network request to send the identified product name and ingredient information to the server, along with the user's identity and other contextual information.

[0438] Step 6:

[0439] The server analyzes the received request and searches the database for product information. Based on the product name and ingredient information, the server retrieves detailed information about the corresponding product from the database.

[0440] Step 7:

[0441] The server compares the acquired product information with the allergy information registered by the user, checks whether the product contains any allergens, and generates a warning if any allergens match.

[0442] Step 8:

[0443] The server creates a response containing the matching results and sends it to the user's device. The response includes detailed information about the allergens and a warning message if any allergens are present.

[0444] Step 9:

[0445] The device analyzes the received response and displays a warning message to the user if an allergen is found to be present. The warning message is displayed in a visually noticeable manner, such as in red.

[0446] Step 10:

[0447] The user reviews the displayed warning message and decides whether to continue with the purchase. At this point, the user is armed with the information to make a safe product choice.

[0448] The above is a specific processing flow for carrying out the present invention.

[0449] Example 1

[0450] 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."

[0451] There are currently many products on the market, and there is a demand for a method to quickly check the extent to which each ingredient contributes to a user's allergies. However, conventional methods require users to personally check the product packaging and compare the ingredient list with their own allergy information, which is time-consuming and laborious, and also carries a high risk of overlooking something. The present invention aims to solve these problems and provide a system that can quickly and accurately check the presence of allergens while reducing the user's effort.

[0452] 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.

[0453] In this invention, the server includes means for extracting text information from product images using optical character recognition means, means for transmitting the extracted text information to a central processing unit via a network, means for the central processing unit to search a product database based on the transmitted text information and obtain product information, means for the central processing unit to compare the product information with the user's registered allergy information, means for generating a warning message if an allergen is contained based on the comparison result and transmitting the warning message to the user's device, and means for the user's device to visually display the result including the warning message. This allows the user to check the allergen content status of a product in a short time after scanning it, enabling safe and fast product selection.

[0454] An "image capture device" is a device for capturing product images, including a camera, scanner, etc.

[0455] "Optical character recognition" is a technology for analyzing character information from image data and extracting text information.

[0456] A "Central Processing Unit" is a computer system that runs on a server or cloud and analyzes and processes received data.

[0457] "Text information" is character information extracted from product images, including product names and ingredient lists.

[0458] "Product database" means a database that stores information about products, including ingredient information and other product information.

[0459] A "network" is an infrastructure for data communication, including the Internet.

[0460] "Allergy information" is information about one's own allergies that is registered in advance by the user, and is a list showing allergic reactions to specific ingredients or substances.

[0461] A "warning message" is a notification message generated for a product that contains an allergen, and issues a warning to the user.

[0462] "User device" refers to a terminal used by a user, including a smartphone, tablet, etc.

[0463] "Visually displaying" means displaying information such as a warning message in a form that can be seen by the user on a display or the like.

[0464] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0465] System Configuration

[0466] The system is broadly composed of the following elements:

[0467] 1. On the user's device:

[0468] The device is a smartphone or tablet held by the user, equipped with a camera for scanning products and a display for displaying the results. The device also has an application installed to manage the user's allergy information.

[0469] 2. Server:

[0470] It is installed on the cloud and has a database that stores product information, a search engine that searches it, and logic that checks the user's allergy information against product information.

[0471] Hardware and software used

[0472] Device: Smartphone or tablet

[0473] Camera: Built-in camera

[0474] OCR software: Tesseract OCR

[0475] Cloud servers: AWS, Google Cloud, Azure

[0476] Database: MySQL, PostgreSQL

[0477] Search engine: Elasticsearch

[0478] Specific examples of processing

[0479] Product scanning

[0480] When a user goes to the supermarket to buy a chocolate bar, they scan the item with their smartphone camera. The device captures the image data and analyzes it with optical character recognition (OCR) software. For example, Tesseract OCR can be used to extract the ingredients, such as "chocolate bar" and "peanuts, sugar, cocoa."

[0481] Submitting and searching product information

[0482] The device uses an HTTP POST request to send this extracted text information to the server. For example, "{"product_name": "Chocolate bar", "ingredients": "Peanuts, Sugar, Cocoa"}". The server searches the product database based on the received information and retrieves the ingredient information for the corresponding product. It uses MySQL for the search, and if the corresponding product is not found, it uses Elasticsearch to search for similar products.

[0483] Matching with allergy information and generating results

[0484] The server compares the user's allergy information with the product's ingredient list. For example, if the user has registered a peanut allergy, the server verifies that the ingredient list includes "peanuts." Based on the comparison result, the server generates a warning message saying "Warning: This product contains peanuts" and sends it to the terminal.

[0485] Displaying the results

[0486] The user's device visually displays the warning message received from the server. For example, it displays "Warning: This product contains peanuts" on a red background to warn the user. This allows the user to intuitively confirm the safety of the product.

[0487] Prompt Sentence Examples

[0488] "What ingredients does this product contain?"

[0489] "Please tell me the list of ingredients in the product called 'Chocolate Bar'."

[0490] Does this product contain allergens?

[0491] This system allows users to easily check whether a product contains substances that they are allergic to when purchasing it, allowing them to make purchases with peace of mind.

[0492] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0493] Step 1: Product Scan

[0494] User: The user uses the camera on their smartphone or tablet to scan the barcode, QR code, or entire packaging of the product.

[0495] Input: Image data of product packaging

[0496] Output: Image data is saved to the device

[0497] Specific behavior: The user launches the camera app, points the camera at the product, and presses the scan button. The camera captures an image of the product packaging.

[0498] Step 2: Extracting text information

[0499] Terminal: The terminal analyzes the acquired image data using optical character recognition (OCR) software (e.g., Tesseract OCR) to extract text information such as the product name and ingredient list.

[0500] Input: Image data

[0501] Output: Extracted text information (e.g. "Chocolate bar", "Peanuts, sugar, cocoa")

[0502] Specific operation: Through OCR processing, text information is analyzed from image data and structured in JSON format.

[0503] Step 3: Send text information

[0504] Terminal: The extracted text information is sent to the server via the network. Specifically, JSON data is sent using an HTTP POST request.

[0505] Input: Text information (JSON format)

[0506] Output: Text information sent to the server

[0507] Specific operation: An application in the device generates an HTTP request, attaches the extracted text information, and sends it to the server.

[0508] Step 4: Find product information

[0509] Server: The server searches the product database based on the text information sent and retrieves the ingredient information for the corresponding product. MySQL and Elasticsearch are used for the search.

[0510] Input: Text information (product name and ingredient list)

[0511] Output: Product information (ingredients list and related information)

[0512] Specific operation: The server executes a database query based on the received text information and retrieves detailed information about the corresponding product. Example of database query execution: "SELECT FROM products WHERE name="Chocolate bar""

[0513] Step 5: Check against allergy information

[0514] Server: The server compares the ingredient list of the acquired product information with the allergy information registered in advance by the user, and performs a process to check whether the product contains any allergens.

[0515] Input: Product information (ingredients list), user allergy information

[0516] Output: Matching result (whether or not allergens are included)

[0517] Specific operation: The server compares the product ingredients with the user's allergy information, and if there are any matching substances, determines the risk of an allergic reaction.

[0518] Step 6: Generate a warning message

[0519] Server: Based on the matching results, if an allergen is found, generate a warning message. For example, create a message saying "Warning: This product contains peanuts."

[0520] Input: Matching result

[0521] Output: Warning message

[0522] Specific operation: Based on the matching results, the system runs a process to automatically generate a warning message. The generated message is saved in text format.

[0523] Step 7: Sending and displaying warning messages

[0524] Server: The generated warning message is sent to the user's terminal as an HTTP response.

[0525] Terminal: Visually display the warning message received from the server to the user, for example displaying the message "Warning: This product contains peanuts" on a red background.

[0526] Input: warning message

[0527] Output: Display of a warning message on the user's terminal

[0528] Specific behavior: The device receives the HTTP response, the application analyzes its contents, and displays a visual warning to the user.

[0529] In this way, users can easily check whether a product contains their allergens and choose products safely.

[0530] (Application example 1)

[0531] 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."

[0532] There is a lack of means for passengers of self-driving vehicles to quickly and accurately check the ingredient information of food and beverages they purchase or bring on board, and to prevent the ingestion of allergens. Therefore, it is necessary to provide an environment where passengers can enjoy food and beverages in safety on board self-driving vehicles.

[0533] 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.

[0534] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for passengers to scan the product using a tablet terminal or a dedicated display, means for transmitting the acquired ingredient information to a cloud server, and means for comparing the ingredient information with the user's allergy information and generating a result. This enables passengers to safely check the ingredient information of food and drink even inside an autonomous vehicle and avoid the risk of allergic reactions.

[0535] An "image capture device" is a device that captures product images using a camera or the like.

[0536] "Optical character recognition" is a technology that analyzes and extracts text information from images.

[0537] The "means for searching for product information" is a function for finding relevant product information from a database based on the extracted text information.

[0538] "User's registered allergy information" refers to information about allergies that the user has previously entered and saved in the system.

[0539] The "verification means" is a function that compares the user's allergy information with product information to check whether there are any matches.

[0540] The "means for displaying a warning" is a function that displays a visual warning to the user if the result of the comparison indicates that an allergen is contained.

[0541] "Tablet device or dedicated display" refers to a portable display device used for scanning products and displaying results.

[0542] A "cloud server" is a server that stores and provides data over the Internet.

[0543] The "means for transmitting ingredient information" is a function for transmitting the acquired product ingredient information to the cloud server.

[0544] The "means for generating results" is a function that generates warnings or other notifications based on the results of matching ingredient information with the user's allergy information.

[0545] System Overview

[0546] The present invention is a system that allows users to quickly check the ingredient information of food and beverages purchased or brought into an autonomous vehicle. Specifically, it is composed of an image capture device, optical character recognition (OCR) means, database search means, allergy information checking means, warning display means, a tablet terminal or dedicated display, a cloud server, ingredient information transmission means, and result generation means.

[0547] Hardware and software used

[0548] Image capture device: Camera installed in the vehicle or camera on a tablet device.

[0549] Optical Character Recognition: Tesseract OCR is used to extract text information from product images.

[0550] Cloud server: AWS is used as the cloud environment, AWS RDS is used as the database, and Elasticsearch is used as the search engine.

[0551] Tablet or dedicated display: A means for passengers to scan items and view results.

[0552] Application framework: Use Flutter or React Native to build the user interface.

[0553] Specific Examples of the Invention

[0554] To implement this system, the user performs the following operations: First, the passenger scans the product using a tablet device or dedicated display. The scanned product image is captured by an image capture device. Next, text information is extracted from the product image using optical character recognition (Tesseract OCR). This text information is sent to a cloud server, where a database search is performed. The captured product information is compared with allergy information previously registered by the user.

[0555] If an allergen is found in a product, a warning message will be generated and displayed on the tablet or a dedicated display, allowing users to safely check the product's ingredient information.

[0556] Specific examples

[0557] For example, a user scans a drink (such as juice) they have purchased in an autonomous vehicle. At this time, the ingredient information of the scanned product is sent to a cloud server and extracted using OCR. The cloud server then searches a product database to obtain the ingredient information. This ingredient information is then compared with the user's allergy information, and if the drink contains an allergen, a warning message is displayed on the tablet device.

[0558] Prompt Sentence Examples

[0559] It uses a camera to scan drinks (juices) purchased by passengers in the vehicle, then uses OCR technology to extract the ingredients and search the AWS RDS database, matching them with the user's allergy information and displaying the results on the passenger's smart display.

[0560] This system allows passengers to enjoy meals and drinks safely inside self-driving vehicles.

[0561] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0562] Step 1:

[0563] The user scans the product using a tablet device or dedicated display.

[0564] Input: Product packaging image

[0565] What it does: The user uses the camera to scan the barcode of an item or the entire package.

[0566] Step 2:

[0567] The image capture device captures product images.

[0568] Input: scanned package image

[0569] Specific operation: The tablet device's camera captures product images and saves them to its internal memory.

[0570] Step 3:

[0571] Extract text information from product images using optical character recognition (OCR).

[0572] Input: Captured product image

[0573] Specific operation: The device calls Tesseract OCR, analyzes the text information in the image, and extracts product name and ingredient information.

[0574] Output: Extracted text information

[0575] Step 4:

[0576] The extracted text information is sent to a cloud server.

[0577] Input: Extracted text information

[0578] Specific operation: The device sends the extracted text information via the Internet to the cloud server through AWS API Gateway.

[0579] Step 5:

[0580] The server searches the product database and obtains the relevant product information.

[0581] Input: Extracted text information

[0582] Specific operation: Based on the text information received by the server, Elasticsearch is used to search the product database (AWS RDS) and obtain the corresponding product information.

[0583] Output: Retrieved product information

[0584] Step 6:

[0585] The server compares the user's allergy information with the product information.

[0586] Input: Retrieved product information and user allergy information

[0587] Specific operation: The server compares the user allergy information in the database with the ingredient list of the retrieved product information to determine whether any matching allergens exist.

[0588] Output: Matching result

[0589] Step 7:

[0590] The server generates a warning message based on the result of the check and sends it to the terminal.

[0591] Input: Matching result

[0592] Specific operation: If an allergen is contained, the server generates a warning message (e.g., "Warning: Contains allergen") and sends it to the terminal.

[0593] Output: Warning message

[0594] Step 8:

[0595] The terminal visually displays a warning message to the user, and if an allergen is included, the warning is displayed in red or other colors.

[0596] Input: The warning message received from the server

[0597] Specific operation: The device will display a warning message on the screen and highlight any allergens with a red background color, for example.

[0598] This allows users to safely check the ingredient information of food and drink inside their self-driving vehicle and avoid allergic reactions.

[0599] 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.

[0600] The present invention is a system that combines an emotion engine that recognizes emotions when a user scans an item and tailors warnings based on the user's allergy information. The steps and specific operations required to implement this system are described in detail below.

[0601] System Configuration

[0602] The system consists of the following components:

[0603] 1. On the user's device:

[0604] The device, such as a smartphone or tablet held by the user, is equipped with a camera for scanning products and a camera and microphone for recognizing emotions. A dedicated application is installed on the device, which has a function for managing the user's allergy information and an emotion engine.

[0605] 2. Server:

[0606] The cloud-based server has a database that stores product information, a search engine for searching it, and logic for matching user allergy information with product information. It can also process emotional information.

[0607] 3. Emotion Engine:

[0608] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reaction.

[0609] Implementation of the invention

[0610] 1. Scan the product

[0611] Users can use their device's camera to scan product packaging, barcodes, and QR codes, and the product images captured by the camera are saved on the device.

[0612] 2. Information extraction from images

[0613] The device passes the stored product image to an optical character recognition (OCR) tool to extract text information such as the product name and ingredients, which is then prepared for transmission to the server.

[0614] 3. Search for product information

[0615] The terminal sends the extracted text information to the server, which then searches the product database based on the received information to obtain ingredient information and related information for the relevant product.

[0616] 4. Checking allergy information

[0617] The server compares the searched product information with the user's registered allergy information, and generates a result indicating whether the product contains any allergens, and if so, detailed information about the ingredients.

[0618] 5. Emotional Recognition

[0619] When a warning is displayed, the device captures the user's reaction using the device's camera and microphone, and the emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[0620] 6. Adjusting the display of warning messages

[0621] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. For example, if the user looks anxious, the device will display the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[0622] Specific examples

[0623] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[0624] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[0625] This allows users to intuitively understand important information about their allergies and decide whether to make a purchase with confidence.By taking user emotions into consideration, this system enables more effective and flexible warning messages to be displayed, improving consumer safety and peace of mind.

[0626] The processing flow will be explained below.

[0627] Step 1:

[0628] The user launches the device's camera application and scans the product packaging, barcode, or QR code. The camera captures the product image and saves the image data on the device.

[0629] Step 2:

[0630] The device launches an OCR (optical character recognition) tool to analyze the captured product image, extracting text information from the image and identifying product name and ingredient information.

[0631] Step 3:

[0632] The device sends the text information extracted by the OCR tool to the server over the network, along with the user's identification information.

[0633] Step 4:

[0634] The server analyzes the received text information and searches the product database to obtain detailed information about the corresponding product. The server searches based on the product name and ingredient information, and if no corresponding product is found, it searches for similar products.

[0635] Step 5:

[0636] The server compares the product information obtained from the search with the allergy information registered by the user, and then compares the product ingredient list with the allergy information to see if it contains any matching allergens.

[0637] Step 6:

[0638] If an allergen is present, the server generates a warning about the ingredient, including details of the specific allergen and its health risks.

[0639] Step 7:

[0640] The server transmits the generated warning information to the terminal, where it is transmitted quickly and securely, allowing the user to quickly check it.

[0641] Step 8:

[0642] The terminal analyzes the received warning information and prepares it for visual display to the user. The terminal determines the best way to display the warning message.

[0643] Step 9:

[0644] The device will capture the user's reaction using the device's camera and microphone just before displaying the warning message, collecting data for the emotion engine to analyze the user's facial expressions and voice.

[0645] Step 10:

[0646] The emotion engine installed on the device analyzes the captured user's facial expressions and voice signals to recognize the user's emotional state. For example, if the user has a surprised expression, the emotion is recognized as "surprise."

[0647] Step 11:

[0648] The device adjusts the way the warning message is displayed based on the user's emotional state as recognized by the emotion engine: if the user is surprised, the warning message is displayed in red and bold to emphasize it.

[0649] Step 12:

[0650] The device displays a tailored warning message to the user, such as "This product contains peanuts" in bold red text to grab the user's attention.

[0651] Step 13:

[0652] The user checks the displayed warning message and decides whether to continue with the purchase of the product. The user can make a safe product selection based on the provided warning information.

[0653] The above is a specific processing flow for an embodiment of the invention that combines an emotion engine, allowing users to enjoy a safer and more secure shopping experience by taking into consideration not only the product scanning process but also the emotions involved.

[0654] Example 2

[0655] 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."

[0656] Conventional systems allow users to check whether an item contains allergens when they scan it, but the warning display does not take into account the user's emotional state, which means the warning is not communicated effectively. Furthermore, while there is a need for warnings to be displayed in a way that is intuitively easy for users to understand, there is also the issue of not using emotion recognition technology to adjust the warning display.

[0657] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring product images, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for recognizing the user's emotional state, and means for displaying a warning in accordance with the user's emotional state if the product contains an allergen based on the comparison result. This makes it possible to display a warning that takes the user's emotional state into consideration, thereby ensuring effective communication of the warning.

[0658] "Means for acquiring product images" refers to devices or functions that acquire images of the product packaging, barcodes, or QR codes scanned by the user.

[0659] "Optical character recognition means" refers to a technology for extracting text information from acquired product images, and in particular uses optical character recognition (OCR) technology.

[0660] The "means for extracting text information" is a function that uses optical character recognition means to extract text information such as product names and ingredient information from the product images as digital data.

[0661] The "means for searching for product information" is a technique for searching for and acquiring the relevant product information from a product database via a network based on the extracted text information.

[0662] "User's registered allergy information" refers to information about allergies that the user has previously entered into a dedicated application and that is stored on the server.

[0663] The "means for checking product information against the allergy information" is a function that compares the acquired product information with the user's allergy information to determine whether or not the product contains an allergen.

[0664] "Means for recognizing the user's emotional state" refers to devices or technologies that analyze the user's facial expressions and voice signals to recognize the user's emotional state (surprise, anxiety, relief, etc.).

[0665] "Means for displaying a warning" refers to a device or technology that visually or audibly notifies the user if the product contains an allergen based on the comparison results.

[0666] The "means for displaying a warning depending on the user's emotional state" is a function that dynamically changes the way the warning message is displayed (color, font, emphasis, etc.) based on the user's perceived emotional state.

[0667] The present invention relates to a system that allows a user to scan a product and adjusts a warning message using an emotion engine. Specific embodiments of the system are described below.

[0668] System Configuration

[0669] The system consists of the following components:

[0670] 1. On the user's device:

[0671] The user's smartphone, tablet, or other device is equipped with a high-resolution camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed on the device, and processing is performed using an OCR tool (e.g., Tesseract) and an emotion engine (e.g., Emotion API).

[0672] 2. Server:

[0673] It is a server installed in the cloud that has a database (e.g., Elasticsearch) that stores product information and a search engine for searching it. It also has logic that matches the user's allergy information with product information. It can also process emotional information.

[0674] 3. Emotion Engine:

[0675] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reactions.

[0676] Product scanning and information extraction

[0677] First, the user uses the device's camera to scan the product packaging, barcode, or QR code. The captured product image is saved on the device, and text information such as the product name and ingredient list is extracted using an OCR tool. This allows the product information to be obtained as digital data.

[0678] Product information search and matching

[0679] The device sends the extracted text information in JSON format to the server. Based on the received information, the server uses a search engine such as Elasticsearch to search a product database and retrieves the ingredient information and related information for the relevant product. The server then compares the information with the user's registered allergy information, determines whether the product contains any allergens, and generates a result.

[0680] Emotion recognition and warning display adjustment

[0681] When displaying warning information, the device's camera and microphone are used to capture the user's reactions. The emotion engine (e.g., Emotion API) analyzes the user's facial expressions and voice to recognize their emotional state. Based on the recognition results, the way the warning message is displayed can be dynamically changed depending on the user's emotional state, such as displaying the warning message in bold red if the user looks anxious.

[0682] Specific examples

[0683] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[0684] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[0685] Prompt Sentence Examples

[0686] The following prompt sentence is input to the generative AI model to generate a warning message:

[0687] Please provide the information of the product scanned by the user. Then generate a warning message based on the user's allergy information. Based on the user's sentiment, customize the message as follows:

[0688] 1. If the user looks surprised: Display a bold red warning message

[0689] 2. If the user looks relieved: Display the warning message in normal font and color.

[0690] Example output: "This product contains peanuts."

[0691] As described above, the present invention provides a system that realizes the display of warning messages that take into account the emotional state of the user, thereby improving consumer safety and security.

[0692] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0693] Step 1: Start scanning your products

[0694] The user launches a dedicated application on a smartphone or tablet device and scans the product packaging, barcode, or QR code with the camera. The input is an image of the product captured by the user's device's camera. The output is the captured image of the product stored in the device's internal memory. Specifically, the user launches the camera application on the device, points the camera at the product, and captures the image.

[0695] Step 2: Extracting information from the image

[0696] The device inputs product images stored in its internal memory into an OCR tool (e.g., Tesseract). As input, it receives the product images stored in memory. As output, it extracts text information such as the product name and ingredient list. This text information is structured in JSON format and is ready to be sent to the server. Specifically, the device passes the stored image to the OCR tool, which then extracts the text information from the image.

[0697] Step 3: Get product information

[0698] The terminal sends the extracted text information to the server. The extracted text information (JSON format) is obtained as input. As output, a query is executed to obtain the ingredient information and related information of the target product. The server uses a search engine such as Elasticsearch based on that information to search a product database and obtains the ingredient information and related information of the relevant product. Specifically, the terminal sends JSON format data to the server, and the server executes a search query on the database.

[0699] Step 4: Check against allergy information

[0700] The server compares the searched product information with the user's registered allergy information. The input is the product information and the user's allergy information. The output is a determination of whether the product contains an allergen and detailed information about the ingredients. Specifically, the server retrieves allergy information from the user database and compares it with the product information to determine whether the product contains an allergen.

[0701] Step 5: Recognize emotions

[0702] When warning information is displayed, the device uses the device's camera and microphone to capture the user's reaction. As input, the user's facial expression data and voice data when the warning information is displayed are obtained. As output, the user's emotional state (surprise, anxiety, relief, etc.) is recognized. Specifically, the device captures the user's facial expression with the camera and records voice with the microphone, and inputs this data into an emotion engine (e.g., Emotion API) for emotion analysis.

[0703] Step 6: Adjust the display of warning messages

[0704] The device dynamically changes the way it displays warning messages based on the user's emotions recognized by the emotion engine. The input is the user's emotional state and the warning information generated in the previous stage. The output is a warning message that corresponds to the user's emotional state. Specifically, the device receives the results of the emotion engine, adjusts the display method (color, font, emphasis, etc.) of the warning message to match the user's emotions, and displays it on the screen.

[0705] As described above, this system performs detailed data processing and calculations at each processing step, enabling it to display warning messages that take into account the user's emotional state, thereby improving consumer safety and peace of mind.

[0706] (Application example 2)

[0707] 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."

[0708] While conventional product scanning systems in logistics centers display product ingredient information and allergy warnings, they do not adjust the display method to take into account employee emotions and health conditions. This creates a risk that employees may continue working while feeling stressed or tired, which can lead to problems with productivity and safety. The objective of this invention is to provide a system that solves these problems and enables employee health management.

[0709] 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.

[0710] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for recognizing the user's emotion, and means for adjusting the display method of the warning message based on the recognized emotion. This enables warnings to be displayed according to the employee's health condition, thereby improving workability and safety.

[0711] An "image capture device" is a device for capturing images of products using a photographic device such as a camera.

[0712] "Optical character recognition" is a technology that analyzes character information from captured images and converts it into digital text.

[0713] "Product information" is detailed data about a product, including information on ingredients, price, barcode information, and so on.

[0714] "Allergy information" is data relating to individual allergies registered by the user, and includes allergic reaction information to specific substances.

[0715] "Verification" is the process of comparing product information with the user's allergy information to see if they match.

[0716] A "warning message" is a notification to inform the user that an allergen is contained.

[0717] "Emotion recognition" is a technology that uses a camera and microphone to analyze a user's emotional state from their facial expressions and voice.

[0718] "Adjusting the way warning messages are displayed" refers to dynamically changing the color, font, and display format of warning messages based on the perceived emotion.

[0719] A "system" is a set of components that combine multiple means and devices to provide specific functions or services.

[0720] This invention is a system that supports employee health management and efficient work performance in logistics centers. This system has the function of recognizing the employee's emotions when scanning products and dynamically adjusting warning messages based on those emotions. The specific operation and configuration of this system are described below.

[0721] System Configuration

[0722] The system consists of the following elements:

[0723] 1. User's device

[0724] The smartphone is equipped with a camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed, which includes an optical character recognition (OCR) tool, an emotion engine, and allergy information management functions.

[0725] 2. Server

[0726] It has a database (MongoDB) that stores product information and is equipped with logic to check against the user's allergy information. It is installed on a cloud server and communicates with devices via the network.

[0727] 3. Emotion Engine

[0728] The Emotion SDK is used to recognize emotions by analyzing the user's facial expressions and voice. Implemented on the device, it adjusts the way warning messages are displayed based on the user's reactions.

[0729] Specific system behavior

[0730] 1. Scan the product

[0731] Users use their device's camera to scan the product's barcode or QR code, and the product image captured by the camera is saved on the device.

[0732] 2. Information extraction from images

[0733] The device passes the saved product image to an OCR tool (Tesseract) to extract text information such as the product name and ingredients. The extracted text information is then prepared for transmission to the server.

[0734] 3. Search for product information

[0735] The server searches the product database based on the received text information, retrieves the ingredient information and related information for the relevant product, and returns this information to the terminal.

[0736] 4. Checking allergy information

[0737] The server compares the searched product information with the user's registered allergy information, and as a result, generates a result of the comparison as to whether the product contains any allergens, and if so, generates detailed information about the ingredients, and sends it to the terminal.

[0738] 5. Emotional Recognition

[0739] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction, and an emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[0740] 6. Adjusting the display of warning messages

[0741] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. If the user has a surprised expression, the device displays the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[0742] Specific examples

[0743] For example, let's say an employee is in the middle of scanning products during peak hours. At this time, they use their smartphone camera to scan the products and extract ingredient information using OCR. The extracted information is sent to a server, and if the match indicates that the product contains an allergen, a warning message is generated. At the same time, the device's emotion engine analyzes the employee's facial expressions and voice, and if it detects high levels of stress or fatigue, it displays a message such as "Let's take a short break." An example of a prompt sentence to be used at this time could be, "An app that allows employees working at a logistics center to scan products and check for allergens. If an employee is feeling stressed, display a message encouraging them to take a break."

[0744] In this way, the system can support both employee health and work efficiency.

[0745] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0746] Step 1:

[0747] The user uses the device's camera to scan the barcode or QR code of a product, and the device processes the captured product image as input.

[0748] Step 2:

[0749] The terminal passes the acquired product image to an optical character recognition (OCR) tool (Tesseract) to extract text information such as the product name and ingredient list. In OCR processing, image data is input and the extracted text information is output.

[0750] Step 3:

[0751] The terminal sends the extracted text information to the server. The server searches the product database (MongoDB) based on the received text information and retrieves the ingredient information and related information of the corresponding product. In this data search process, the text information is used as input and the corresponding product information is output.

[0752] Step 4:

[0753] The server compares the searched product information with the user's registered allergy information. In the comparison process, the product information and allergy information are input, and the output is a determination of whether the product contains an allergen.

[0754] Step 5:

[0755] Based on the comparison result, the server generates a warning message if an allergen is found to be present and sends it to the terminal. In this warning generation process, the comparison result is used as input and the warning message is used as output.

[0756] Step 6:

[0757] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction. The capture process takes the user's facial expressions and voice data as input and prepares them for passing to the emotion engine.

[0758] Step 7:

[0759] The device uses an emotion engine (Emotion SDK) to analyze the user's emotions. The emotion analysis process takes the user's facial expressions and voice data as input and outputs analyzed emotional information.

[0760] Step 8:

[0761] The terminal adjusts the display method of the warning message based on the recognized emotion information. The display adjustment process takes the emotion information and the warning message as input and outputs the adjusted warning message. The adjusted message is displayed on the connected user interface.

[0762] This process allows employees to check allergy information when scanning products and receive appropriate warning messages based on their emotional state.

[0763] 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.

[0764] 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.

[0765] 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.

[0766] [Third embodiment]

[0767] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0768] 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.

[0769] 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).

[0770] 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.

[0771] 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.

[0772] 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).

[0773] 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.

[0774] 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.

[0775] 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.

[0776] 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.

[0777] 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.

[0778] 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."

[0779] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0780] System Configuration

[0781] The system is broadly composed of the following elements:

[0782] 1. On the user's device:

[0783] The device is equipped with a camera for scanning products on a user's smartphone or tablet, and a display for displaying the results. An application is installed on the device, and it has the function of managing the user's allergy information.

[0784] 2. Server:

[0785] It is installed on the cloud and has a database that stores product information, a search engine for searching it, and logic to match user allergy information with product information.

[0786] Implementation of the invention

[0787] 1. Scan the product

[0788] Users use their device's camera to scan a product's barcode, QR code, or entire packaging. The device then uses the captured image data to extract product information, using optical character recognition (OCR) technology to extract text information such as the product name and ingredient list.

[0789] 2. Search for product information

[0790] The text information extracted by the terminal is sent to the server. The server searches the product database based on the received text information to obtain the ingredient information and other related information of the corresponding product. If the corresponding product is not found, the server can search for similar products and use that information.

[0791] 3. Checking allergy information

[0792] The server compares the allergy information registered by the user with the ingredient list of the product information it retrieves, and if an allergen is found to be present, it generates a warning message with detailed information.

[0793] 4. Displaying the results

[0794] The matching results sent from the server are received by the terminal. The terminal visually displays the results to the user, and if an allergen is found to be present, a warning such as red is displayed. This allows the user to intuitively confirm the safety of the product.

[0795] Specific examples

[0796] For example, when a user wants to buy a chocolate bar at a supermarket, they scan the product with their smartphone camera. At this time, the device extracts the product name "Chocolate Bar" and its ingredients using OCR and sends this information to the server. The server then searches its database to see if the product contains peanuts and compares it with the user's allergy information. If it does contain peanuts, a warning message is generated and sent to the device. The user's device then displays a red warning message saying "Warning: This product contains peanuts."

[0797] This system allows users to easily check whether a product contains any of their allergens when purchasing it, allowing them to make purchases with peace of mind.

[0798] The processing flow will be explained below.

[0799] Step 1:

[0800] The user uses the device's camera to capture an image of the product. The user launches the camera application and points the camera at the product packaging, barcode, or QR code to take a picture.

[0801] Step 2:

[0802] The device temporarily stores the acquired product images in its internal memory. At this point, the images are not yet processed and are stored in their raw form.

[0803] Step 3:

[0804] The device invokes an optical character recognition (OCR) tool to extract text information such as the product name, ingredients, and barcode from the saved product image. The text information obtained by OCR is saved in a variable.

[0805] Step 4:

[0806] The device analyzes the extracted text information to identify product names and ingredient information, which is then prepared as structured data to be sent to the server.

[0807] Step 5:

[0808] The device then makes a network request to send the identified product name and ingredient information to the server, along with the user's identity and other contextual information.

[0809] Step 6:

[0810] The server analyzes the received request and searches the database for product information. Based on the product name and ingredient information, the server retrieves detailed information about the corresponding product from the database.

[0811] Step 7:

[0812] The server compares the acquired product information with the allergy information registered by the user, checks whether the product contains any allergens, and generates a warning if any allergens match.

[0813] Step 8:

[0814] The server creates a response containing the matching results and sends it to the user's device. The response includes detailed information about the allergens and a warning message if any allergens are present.

[0815] Step 9:

[0816] The device analyzes the received response and displays a warning message to the user if an allergen is found to be present. The warning message is displayed in a visually noticeable manner, such as in red.

[0817] Step 10:

[0818] The user reviews the displayed warning message and decides whether to continue with the purchase. At this point, the user is armed with the information to make a safe product choice.

[0819] The above is a specific processing flow for carrying out the present invention.

[0820] Example 1

[0821] 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."

[0822] There are currently many products on the market, and there is a demand for a method to quickly check the extent to which each ingredient contributes to a user's allergies. However, conventional methods require users to personally check the product packaging and compare the ingredient list with their own allergy information, which is time-consuming and laborious, and also carries a high risk of overlooking something. The present invention aims to solve these problems and provide a system that can quickly and accurately check the presence of allergens while reducing the user's effort.

[0823] 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.

[0824] In this invention, the server includes means for extracting text information from product images using optical character recognition means, means for transmitting the extracted text information to a central processing unit via a network, means for the central processing unit to search a product database based on the transmitted text information and obtain product information, means for the central processing unit to compare the product information with the user's registered allergy information, means for generating a warning message if an allergen is contained based on the comparison result and transmitting the warning message to the user's device, and means for the user's device to visually display the result including the warning message. This allows the user to check the allergen content status of a product in a short time after scanning it, enabling safe and fast product selection.

[0825] An "image capture device" is a device for capturing product images, including a camera, scanner, etc.

[0826] "Optical character recognition" is a technology for analyzing character information from image data and extracting text information.

[0827] A "Central Processing Unit" is a computer system that runs on a server or cloud and analyzes and processes received data.

[0828] "Text information" is character information extracted from product images, including product names and ingredient lists.

[0829] "Product database" means a database that stores information about products, including ingredient information and other product information.

[0830] A "network" is an infrastructure for data communication, including the Internet.

[0831] "Allergy information" is information about one's own allergies that is registered in advance by the user, and is a list showing allergic reactions to specific ingredients or substances.

[0832] A "warning message" is a notification message generated for a product that contains an allergen, and issues a warning to the user.

[0833] "User device" refers to a terminal used by a user, including a smartphone, tablet, etc.

[0834] "Visually displaying" means displaying information such as a warning message in a form that can be seen by the user on a display or the like.

[0835] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[0836] System Configuration

[0837] The system is broadly composed of the following elements:

[0838] 1. On the user's device:

[0839] The device is a smartphone or tablet held by the user, equipped with a camera for scanning products and a display for displaying the results. The device also has an application installed to manage the user's allergy information.

[0840] 2. Server:

[0841] It is installed on the cloud and has a database that stores product information, a search engine that searches it, and logic that checks the user's allergy information against product information.

[0842] Hardware and software used

[0843] Device: Smartphone or tablet

[0844] Camera: Built-in camera

[0845] OCR software: Tesseract OCR

[0846] Cloud servers: AWS, Google Cloud, Azure

[0847] Database: MySQL, PostgreSQL

[0848] Search engine: Elasticsearch

[0849] Specific examples of processing

[0850] Product scanning

[0851] When a user goes to the supermarket to buy a chocolate bar, they scan the item with their smartphone camera. The device captures the image data and analyzes it with optical character recognition (OCR) software. For example, Tesseract OCR can be used to extract the ingredients, such as "chocolate bar" and "peanuts, sugar, cocoa."

[0852] Submitting and searching product information

[0853] The device uses an HTTP POST request to send this extracted text information to the server. For example, "{"product_name": "Chocolate bar", "ingredients": "Peanuts, Sugar, Cocoa"}". The server searches the product database based on the received information and retrieves the ingredient information for the corresponding product. It uses MySQL for the search, and if the corresponding product is not found, it uses Elasticsearch to search for similar products.

[0854] Matching with allergy information and generating results

[0855] The server compares the user's allergy information with the product's ingredient list. For example, if the user has registered a peanut allergy, the server verifies that the ingredient list includes "peanuts." Based on the comparison result, the server generates a warning message saying "Warning: This product contains peanuts" and sends it to the terminal.

[0856] Displaying the results

[0857] The user's device visually displays the warning message received from the server. For example, it displays "Warning: This product contains peanuts" on a red background to warn the user. This allows the user to intuitively confirm the safety of the product.

[0858] Prompt Sentence Examples

[0859] "What ingredients does this product contain?"

[0860] "Please tell me the list of ingredients in the product called 'Chocolate Bar'."

[0861] Does this product contain allergens?

[0862] This system allows users to easily check whether a product contains substances that they are allergic to when purchasing it, allowing them to make purchases with peace of mind.

[0863] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0864] Step 1: Product Scan

[0865] User: The user uses the camera on their smartphone or tablet to scan the barcode, QR code, or entire packaging of the product.

[0866] Input: Image data of product packaging

[0867] Output: Image data is saved to the device

[0868] Specific behavior: The user launches the camera app, points the camera at the product, and presses the scan button. The camera captures an image of the product packaging.

[0869] Step 2: Extracting text information

[0870] Terminal: The terminal analyzes the acquired image data using optical character recognition (OCR) software (e.g., Tesseract OCR) to extract text information such as the product name and ingredient list.

[0871] Input: Image data

[0872] Output: Extracted text information (e.g. "Chocolate bar", "Peanuts, sugar, cocoa")

[0873] Specific operation: Through OCR processing, text information is analyzed from image data and structured in JSON format.

[0874] Step 3: Send text information

[0875] Terminal: The extracted text information is sent to the server via the network. Specifically, JSON data is sent using an HTTP POST request.

[0876] Input: Text information (JSON format)

[0877] Output: Text information sent to the server

[0878] Specific operation: An application in the device generates an HTTP request, attaches the extracted text information, and sends it to the server.

[0879] Step 4: Find product information

[0880] Server: The server searches the product database based on the text information sent and retrieves the ingredient information for the corresponding product. MySQL and Elasticsearch are used for the search.

[0881] Input: Text information (product name and ingredient list)

[0882] Output: Product information (ingredients list and related information)

[0883] Specific operation: The server executes a database query based on the received text information and retrieves detailed information about the corresponding product. Example of database query execution: "SELECT FROM products WHERE name="Chocolate bar""

[0884] Step 5: Check against allergy information

[0885] Server: The server compares the ingredient list of the acquired product information with the allergy information registered in advance by the user, and performs a process to check whether the product contains any allergens.

[0886] Input: Product information (ingredients list), user allergy information

[0887] Output: Matching result (whether or not allergens are included)

[0888] Specific operation: The server compares the product ingredients with the user's allergy information, and if there are any matching substances, determines the risk of an allergic reaction.

[0889] Step 6: Generate a warning message

[0890] Server: Based on the matching results, if an allergen is found, generate a warning message. For example, create a message saying "Warning: This product contains peanuts."

[0891] Input: Matching result

[0892] Output: Warning message

[0893] Specific operation: Based on the matching results, the system runs a process to automatically generate a warning message. The generated message is saved in text format.

[0894] Step 7: Sending and displaying warning messages

[0895] Server: The generated warning message is sent to the user's terminal as an HTTP response.

[0896] Terminal: Visually display the warning message received from the server to the user, for example displaying the message "Warning: This product contains peanuts" on a red background.

[0897] Input: warning message

[0898] Output: Display of a warning message on the user's terminal

[0899] Specific behavior: The device receives the HTTP response, the application analyzes its contents, and displays a visual warning to the user.

[0900] In this way, users can easily check whether a product contains their allergens and choose products safely.

[0901] (Application example 1)

[0902] 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."

[0903] There is a lack of means for passengers of self-driving vehicles to quickly and accurately check the ingredient information of food and beverages they purchase or bring on board, and to prevent the ingestion of allergens. Therefore, it is necessary to provide an environment where passengers can enjoy food and beverages in safety on board self-driving vehicles.

[0904] 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.

[0905] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for passengers to scan the product using a tablet terminal or a dedicated display, means for transmitting the acquired ingredient information to a cloud server, and means for comparing the ingredient information with the user's allergy information and generating a result. This enables passengers to safely check the ingredient information of food and drink even inside an autonomous vehicle and avoid the risk of allergic reactions.

[0906] An "image capture device" is a device that captures product images using a camera or the like.

[0907] "Optical character recognition" is a technology that analyzes and extracts text information from images.

[0908] The "means for searching for product information" is a function for finding relevant product information from a database based on the extracted text information.

[0909] "User's registered allergy information" refers to information about allergies that the user has previously entered and saved in the system.

[0910] The "verification means" is a function that compares the user's allergy information with product information to check whether there are any matches.

[0911] The "means for displaying a warning" is a function that displays a visual warning to the user if the result of the comparison indicates that an allergen is contained.

[0912] "Tablet device or dedicated display" refers to a portable display device used for scanning products and displaying results.

[0913] A "cloud server" is a server that stores and provides data over the Internet.

[0914] The "means for transmitting ingredient information" is a function for transmitting the acquired product ingredient information to the cloud server.

[0915] The "means for generating results" is a function that generates warnings or other notifications based on the results of matching ingredient information with the user's allergy information.

[0916] System Overview

[0917] The present invention is a system that allows users to quickly check the ingredient information of food and beverages purchased or brought into an autonomous vehicle. Specifically, it is composed of an image capture device, optical character recognition (OCR) means, database search means, allergy information checking means, warning display means, a tablet terminal or dedicated display, a cloud server, ingredient information transmission means, and result generation means.

[0918] Hardware and software used

[0919] Image capture device: Camera installed in the vehicle or camera on a tablet device.

[0920] Optical Character Recognition: Tesseract OCR is used to extract text information from product images.

[0921] Cloud server: AWS is used as the cloud environment, AWS RDS is used as the database, and Elasticsearch is used as the search engine.

[0922] Tablet or dedicated display: A means for passengers to scan items and view results.

[0923] Application framework: Use Flutter or React Native to build the user interface.

[0924] Specific Examples of the Invention

[0925] To implement this system, the user performs the following operations: First, the passenger scans the product using a tablet device or dedicated display. The scanned product image is captured by an image capture device. Next, text information is extracted from the product image using optical character recognition (Tesseract OCR). This text information is sent to a cloud server, where a database search is performed. The captured product information is compared with allergy information previously registered by the user.

[0926] If an allergen is found in a product, a warning message will be generated and displayed on the tablet or a dedicated display, allowing users to safely check the product's ingredient information.

[0927] Specific examples

[0928] For example, a user scans a drink (such as juice) they have purchased in an autonomous vehicle. At this time, the ingredient information of the scanned product is sent to a cloud server and extracted using OCR. The cloud server then searches a product database to obtain the ingredient information. This ingredient information is then compared with the user's allergy information, and if the drink contains an allergen, a warning message is displayed on the tablet device.

[0929] Prompt Sentence Examples

[0930] It uses a camera to scan drinks (juices) purchased by passengers in the vehicle, then uses OCR technology to extract the ingredients and search the AWS RDS database, matching them with the user's allergy information and displaying the results on the passenger's smart display.

[0931] This system allows passengers to enjoy meals and drinks safely inside self-driving vehicles.

[0932] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0933] Step 1:

[0934] The user scans the product using a tablet device or dedicated display.

[0935] Input: Product packaging image

[0936] What it does: The user uses the camera to scan the barcode of an item or the entire package.

[0937] Step 2:

[0938] The image capture device captures product images.

[0939] Input: scanned package image

[0940] Specific operation: The tablet device's camera captures product images and saves them to its internal memory.

[0941] Step 3:

[0942] Extract text information from product images using optical character recognition (OCR).

[0943] Input: Captured product image

[0944] Specific operation: The device calls Tesseract OCR, analyzes the text information in the image, and extracts product name and ingredient information.

[0945] Output: Extracted text information

[0946] Step 4:

[0947] The extracted text information is sent to a cloud server.

[0948] Input: Extracted text information

[0949] Specific operation: The device sends the extracted text information via the Internet to the cloud server through AWS API Gateway.

[0950] Step 5:

[0951] The server searches the product database and obtains the relevant product information.

[0952] Input: Extracted text information

[0953] Specific operation: Based on the text information received by the server, Elasticsearch is used to search the product database (AWS RDS) and obtain the corresponding product information.

[0954] Output: Retrieved product information

[0955] Step 6:

[0956] The server compares the user's allergy information with the product information.

[0957] Input: Retrieved product information and user allergy information

[0958] Specific operation: The server compares the user allergy information in the database with the ingredient list of the retrieved product information to determine whether any matching allergens exist.

[0959] Output: Matching result

[0960] Step 7:

[0961] The server generates a warning message based on the result of the check and sends it to the terminal.

[0962] Input: Matching result

[0963] Specific operation: If an allergen is contained, the server generates a warning message (e.g., "Warning: Contains allergen") and sends it to the terminal.

[0964] Output: Warning message

[0965] Step 8:

[0966] The terminal visually displays a warning message to the user, and if an allergen is included, the warning is displayed in red or other colors.

[0967] Input: The warning message received from the server

[0968] Specific operation: The device will display a warning message on the screen and highlight any allergens with a red background color, for example.

[0969] This allows users to safely check the ingredient information of food and drink inside their self-driving vehicle and avoid allergic reactions.

[0970] 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.

[0971] The present invention is a system that combines an emotion engine that recognizes emotions when a user scans an item and tailors warnings based on the user's allergy information. The steps and specific operations required to implement this system are described in detail below.

[0972] System Configuration

[0973] The system consists of the following components:

[0974] 1. On the user's device:

[0975] The device, such as a smartphone or tablet held by the user, is equipped with a camera for scanning products and a camera and microphone for recognizing emotions. A dedicated application is installed on the device, which has a function for managing the user's allergy information and an emotion engine.

[0976] 2. Server:

[0977] The cloud-based server has a database that stores product information, a search engine for searching it, and logic for matching user allergy information with product information. It can also process emotional information.

[0978] 3. Emotion Engine:

[0979] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reaction.

[0980] Implementation of the invention

[0981] 1. Scan the product

[0982] Users can use their device's camera to scan product packaging, barcodes, and QR codes, and the product images captured by the camera are saved on the device.

[0983] 2. Information extraction from images

[0984] The device passes the stored product image to an optical character recognition (OCR) tool to extract text information such as the product name and ingredients, which is then prepared for transmission to the server.

[0985] 3. Search for product information

[0986] The terminal sends the extracted text information to the server, which then searches the product database based on the received information to obtain ingredient information and related information for the relevant product.

[0987] 4. Checking allergy information

[0988] The server compares the searched product information with the user's registered allergy information, and generates a result indicating whether the product contains any allergens, and if so, detailed information about the ingredients.

[0989] 5. Emotional Recognition

[0990] When a warning is displayed, the device captures the user's reaction using the device's camera and microphone, and the emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[0991] 6. Adjusting the display of warning messages

[0992] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. For example, if the user looks anxious, the device will display the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[0993] Specific examples

[0994] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[0995] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[0996] This allows users to intuitively understand important information about their allergies and decide whether to make a purchase with confidence.By taking user emotions into consideration, this system enables more effective and flexible warning messages to be displayed, improving consumer safety and peace of mind.

[0997] The processing flow will be explained below.

[0998] Step 1:

[0999] The user launches the device's camera application and scans the product packaging, barcode, or QR code. The camera captures the product image and saves the image data on the device.

[1000] Step 2:

[1001] The device launches an OCR (optical character recognition) tool to analyze the captured product image, extracting text information from the image and identifying product name and ingredient information.

[1002] Step 3:

[1003] The device sends the text information extracted by the OCR tool to the server over the network, along with the user's identification information.

[1004] Step 4:

[1005] The server analyzes the received text information and searches the product database to obtain detailed information about the corresponding product. The server searches based on the product name and ingredient information, and if no corresponding product is found, it searches for similar products.

[1006] Step 5:

[1007] The server compares the product information obtained from the search with the allergy information registered by the user, and then compares the product ingredient list with the allergy information to see if it contains any matching allergens.

[1008] Step 6:

[1009] If an allergen is present, the server generates a warning about the ingredient, including details of the specific allergen and its health risks.

[1010] Step 7:

[1011] The server transmits the generated warning information to the terminal, where it is transmitted quickly and securely, allowing the user to quickly check it.

[1012] Step 8:

[1013] The terminal analyzes the received warning information and prepares it for visual display to the user. The terminal determines the best way to display the warning message.

[1014] Step 9:

[1015] The device will capture the user's reaction using the device's camera and microphone just before displaying the warning message, collecting data for the emotion engine to analyze the user's facial expressions and voice.

[1016] Step 10:

[1017] The emotion engine installed on the device analyzes the captured user's facial expressions and voice signals to recognize the user's emotional state. For example, if the user has a surprised expression, the emotion is recognized as "surprise."

[1018] Step 11:

[1019] The device adjusts the way the warning message is displayed based on the user's emotional state as recognized by the emotion engine: if the user is surprised, the warning message is displayed in red and bold to emphasize it.

[1020] Step 12:

[1021] The device displays a tailored warning message to the user, such as "This product contains peanuts" in bold red text to grab the user's attention.

[1022] Step 13:

[1023] The user checks the displayed warning message and decides whether to continue with the purchase of the product. The user can make a safe product selection based on the provided warning information.

[1024] The above is a specific processing flow for an embodiment of the invention that combines an emotion engine, allowing users to enjoy a safer and more secure shopping experience by taking into consideration not only the product scanning process but also the emotions involved.

[1025] Example 2

[1026] 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."

[1027] Conventional systems allow users to check whether an item contains allergens when they scan it, but the warning display does not take into account the user's emotional state, which means the warning is not communicated effectively. Furthermore, while there is a need for warnings to be displayed in a way that is intuitively easy for users to understand, there is also the issue of not using emotion recognition technology to adjust the warning display.

[1028] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring product images, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for recognizing the user's emotional state, and means for displaying a warning in accordance with the user's emotional state if the product contains an allergen based on the comparison result. This makes it possible to display a warning that takes the user's emotional state into consideration, thereby ensuring effective communication of the warning.

[1029] "Means for acquiring product images" refers to devices or functions that acquire images of the product packaging, barcodes, or QR codes scanned by the user.

[1030] "Optical character recognition means" refers to a technology for extracting text information from acquired product images, and in particular uses optical character recognition (OCR) technology.

[1031] The "means for extracting text information" is a function that uses optical character recognition means to extract text information such as product names and ingredient information from the product images as digital data.

[1032] The "means for searching for product information" is a technique for searching for and acquiring the relevant product information from a product database via a network based on the extracted text information.

[1033] "User's registered allergy information" refers to information about allergies that the user has previously entered into a dedicated application and that is stored on the server.

[1034] The "means for checking product information against the allergy information" is a function that compares the acquired product information with the user's allergy information to determine whether or not the product contains an allergen.

[1035] "Means for recognizing the user's emotional state" refers to devices or technologies that analyze the user's facial expressions and voice signals to recognize the user's emotional state (surprise, anxiety, relief, etc.).

[1036] "Means for displaying a warning" refers to a device or technology that visually or audibly notifies the user if the product contains an allergen based on the comparison results.

[1037] The "means for displaying a warning depending on the user's emotional state" is a function that dynamically changes the way the warning message is displayed (color, font, emphasis, etc.) based on the user's perceived emotional state.

[1038] The present invention relates to a system that allows a user to scan a product and adjusts a warning message using an emotion engine. Specific embodiments of the system are described below.

[1039] System Configuration

[1040] The system consists of the following components:

[1041] 1. On the user's device:

[1042] The user's smartphone, tablet, or other device is equipped with a high-resolution camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed on the device, and processing is performed using an OCR tool (e.g., Tesseract) and an emotion engine (e.g., Emotion API).

[1043] 2. Server:

[1044] It is a server installed in the cloud that has a database (e.g., Elasticsearch) that stores product information and a search engine for searching it. It also has logic that matches the user's allergy information with product information. It can also process emotional information.

[1045] 3. Emotion Engine:

[1046] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reactions.

[1047] Product scanning and information extraction

[1048] First, the user uses the device's camera to scan the product packaging, barcode, or QR code. The captured product image is saved on the device, and text information such as the product name and ingredient list is extracted using an OCR tool. This allows the product information to be obtained as digital data.

[1049] Product information search and matching

[1050] The device sends the extracted text information in JSON format to the server. Based on the received information, the server uses a search engine such as Elasticsearch to search a product database and retrieves the ingredient information and related information for the relevant product. The server then compares the information with the user's registered allergy information, determines whether the product contains any allergens, and generates a result.

[1051] Emotion recognition and warning display adjustment

[1052] When displaying warning information, the device's camera and microphone are used to capture the user's reactions. The emotion engine (e.g., Emotion API) analyzes the user's facial expressions and voice to recognize their emotional state. Based on the recognition results, the way the warning message is displayed can be dynamically changed depending on the user's emotional state, such as displaying the warning message in bold red if the user looks anxious.

[1053] Specific examples

[1054] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[1055] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[1056] Prompt Sentence Examples

[1057] The following prompt sentence is input to the generative AI model to generate a warning message:

[1058] Please provide the information of the product scanned by the user. Then generate a warning message based on the user's allergy information. Based on the user's sentiment, customize the message as follows:

[1059] 1. If the user looks surprised: Display a bold red warning message

[1060] 2. If the user looks relieved: Display the warning message in normal font and color.

[1061] Example output: "This product contains peanuts."

[1062] As described above, the present invention provides a system that realizes the display of warning messages that take into account the emotional state of the user, thereby improving consumer safety and security.

[1063] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1064] Step 1: Start scanning your products

[1065] The user launches a dedicated application on a smartphone or tablet device and scans the product packaging, barcode, or QR code with the camera. The input is an image of the product captured by the user's device's camera. The output is the captured image of the product stored in the device's internal memory. Specifically, the user launches the camera application on the device, points the camera at the product, and captures the image.

[1066] Step 2: Extracting information from the image

[1067] The device inputs product images stored in its internal memory into an OCR tool (e.g., Tesseract). As input, it receives the product images stored in memory. As output, it extracts text information such as the product name and ingredient list. This text information is structured in JSON format and is ready to be sent to the server. Specifically, the device passes the stored image to the OCR tool, which then extracts the text information from the image.

[1068] Step 3: Get product information

[1069] The terminal sends the extracted text information to the server. The extracted text information (JSON format) is obtained as input. As output, a query is executed to obtain the ingredient information and related information of the target product. The server uses a search engine such as Elasticsearch based on that information to search a product database and obtains the ingredient information and related information of the relevant product. Specifically, the terminal sends JSON format data to the server, and the server executes a search query on the database.

[1070] Step 4: Check against allergy information

[1071] The server compares the searched product information with the user's registered allergy information. The input is the product information and the user's allergy information. The output is a determination of whether the product contains an allergen and detailed information about the ingredients. Specifically, the server retrieves allergy information from the user database and compares it with the product information to determine whether the product contains an allergen.

[1072] Step 5: Recognize emotions

[1073] When warning information is displayed, the device uses the device's camera and microphone to capture the user's reaction. As input, the user's facial expression data and voice data when the warning information is displayed are obtained. As output, the user's emotional state (surprise, anxiety, relief, etc.) is recognized. Specifically, the device captures the user's facial expression with the camera and records voice with the microphone, and inputs this data into an emotion engine (e.g., Emotion API) for emotion analysis.

[1074] Step 6: Adjust the display of warning messages

[1075] The device dynamically changes the way it displays warning messages based on the user's emotions recognized by the emotion engine. The input is the user's emotional state and the warning information generated in the previous stage. The output is a warning message that corresponds to the user's emotional state. Specifically, the device receives the results of the emotion engine, adjusts the display method (color, font, emphasis, etc.) of the warning message to match the user's emotions, and displays it on the screen.

[1076] As described above, this system performs detailed data processing and calculations at each processing step, enabling it to display warning messages that take into account the user's emotional state, thereby improving consumer safety and peace of mind.

[1077] (Application example 2)

[1078] 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."

[1079] While conventional product scanning systems in logistics centers display product ingredient information and allergy warnings, they do not adjust the display method to take into account employee emotions and health conditions. This creates a risk that employees may continue working while feeling stressed or tired, which can lead to problems with productivity and safety. The objective of this invention is to provide a system that solves these problems and enables employee health management.

[1080] 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.

[1081] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for recognizing the user's emotion, and means for adjusting the display method of the warning message based on the recognized emotion. This enables warnings to be displayed according to the employee's health condition, thereby improving workability and safety.

[1082] An "image capture device" is a device for capturing images of products using a photographic device such as a camera.

[1083] "Optical character recognition" is a technology that analyzes character information from captured images and converts it into digital text.

[1084] "Product information" is detailed data about a product, including information on ingredients, price, barcode information, and so on.

[1085] "Allergy information" is data relating to individual allergies registered by the user, and includes allergic reaction information to specific substances.

[1086] "Verification" is the process of comparing product information with the user's allergy information to see if they match.

[1087] A "warning message" is a notification to inform the user that an allergen is contained.

[1088] "Emotion recognition" is a technology that uses a camera and microphone to analyze a user's emotional state from their facial expressions and voice.

[1089] "Adjusting the way warning messages are displayed" refers to dynamically changing the color, font, and display format of warning messages based on the perceived emotion.

[1090] A "system" is a set of components that combine multiple means and devices to provide specific functions or services.

[1091] This invention is a system that supports employee health management and efficient work performance in logistics centers. This system has the function of recognizing the employee's emotions when scanning products and dynamically adjusting warning messages based on those emotions. The specific operation and configuration of this system are described below.

[1092] System Configuration

[1093] The system consists of the following elements:

[1094] 1. User's device

[1095] The smartphone is equipped with a camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed, which includes an optical character recognition (OCR) tool, an emotion engine, and allergy information management functions.

[1096] 2. Server

[1097] It has a database (MongoDB) that stores product information and is equipped with logic to check against the user's allergy information. It is installed on a cloud server and communicates with devices via the network.

[1098] 3. Emotion Engine

[1099] The Emotion SDK is used to recognize emotions by analyzing the user's facial expressions and voice. Implemented on the device, it adjusts the way warning messages are displayed based on the user's reactions.

[1100] Specific system behavior

[1101] 1. Scan the product

[1102] Users use their device's camera to scan the product's barcode or QR code, and the product image captured by the camera is saved on the device.

[1103] 2. Information extraction from images

[1104] The device passes the saved product image to an OCR tool (Tesseract) to extract text information such as the product name and ingredients. The extracted text information is then prepared for transmission to the server.

[1105] 3. Search for product information

[1106] The server searches the product database based on the received text information, retrieves the ingredient information and related information for the relevant product, and returns this information to the terminal.

[1107] 4. Checking allergy information

[1108] The server compares the searched product information with the user's registered allergy information, and as a result, generates a result of the comparison as to whether the product contains any allergens, and if so, generates detailed information about the ingredients, and sends it to the terminal.

[1109] 5. Emotional Recognition

[1110] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction, and an emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[1111] 6. Adjusting the display of warning messages

[1112] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. If the user has a surprised expression, the device displays the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[1113] Specific examples

[1114] For example, let's say an employee is in the middle of scanning products during peak hours. At this time, they use their smartphone camera to scan the products and extract ingredient information using OCR. The extracted information is sent to a server, and if the match indicates that the product contains an allergen, a warning message is generated. At the same time, the device's emotion engine analyzes the employee's facial expressions and voice, and if it detects high levels of stress or fatigue, it displays a message such as "Let's take a short break." An example of a prompt sentence to be used at this time could be, "An app that allows employees working at a logistics center to scan products and check for allergens. If an employee is feeling stressed, display a message encouraging them to take a break."

[1115] In this way, the system can support both employee health and work efficiency.

[1116] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1117] Step 1:

[1118] The user uses the device's camera to scan the barcode or QR code of a product, and the device processes the captured product image as input.

[1119] Step 2:

[1120] The terminal passes the acquired product image to an optical character recognition (OCR) tool (Tesseract) to extract text information such as the product name and ingredient list. In OCR processing, image data is input and the extracted text information is output.

[1121] Step 3:

[1122] The terminal sends the extracted text information to the server. The server searches the product database (MongoDB) based on the received text information and retrieves the ingredient information and related information of the corresponding product. In this data search process, the text information is used as input and the corresponding product information is output.

[1123] Step 4:

[1124] The server compares the searched product information with the user's registered allergy information. In the comparison process, the product information and allergy information are input, and the output is a determination of whether the product contains an allergen.

[1125] Step 5:

[1126] Based on the comparison result, the server generates a warning message if an allergen is found to be present and sends it to the terminal. In this warning generation process, the comparison result is used as input and the warning message is used as output.

[1127] Step 6:

[1128] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction. The capture process takes the user's facial expressions and voice data as input and prepares them for passing to the emotion engine.

[1129] Step 7:

[1130] The device uses an emotion engine (Emotion SDK) to analyze the user's emotions. The emotion analysis process takes the user's facial expressions and voice data as input and outputs analyzed emotional information.

[1131] Step 8:

[1132] The terminal adjusts the display method of the warning message based on the recognized emotion information. The display adjustment process takes the emotion information and the warning message as input and outputs the adjusted warning message. The adjusted message is displayed on the connected user interface.

[1133] This process allows employees to check allergy information when scanning products and receive appropriate warning messages based on their emotional state.

[1134] 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.

[1135] 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.

[1136] 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.

[1137] [Fourth embodiment]

[1138] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1139] 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.

[1140] 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).

[1141] 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.

[1142] 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.

[1143] 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).

[1144] 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.

[1145] 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.

[1146] 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.

[1147] 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.

[1148] 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.

[1149] 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.

[1150] 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."

[1151] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[1152] System Configuration

[1153] The system is broadly composed of the following elements:

[1154] 1. On the user's device:

[1155] The device is equipped with a camera for scanning products on a user's smartphone or tablet, and a display for displaying the results. An application is installed on the device, and it has the function of managing the user's allergy information.

[1156] 2. Server:

[1157] It is installed on the cloud and has a database that stores product information, a search engine for searching it, and logic to match user allergy information with product information.

[1158] Implementation of the invention

[1159] 1. Scan the product

[1160] Users use their device's camera to scan a product's barcode, QR code, or entire packaging. The device then uses the captured image data to extract product information, using optical character recognition (OCR) technology to extract text information such as the product name and ingredient list.

[1161] 2. Search for product information

[1162] The text information extracted by the terminal is sent to the server. The server searches the product database based on the received text information to obtain the ingredient information and other related information of the corresponding product. If the corresponding product is not found, the server can search for similar products and use that information.

[1163] 3. Checking allergy information

[1164] The server compares the allergy information registered by the user with the ingredient list of the product information it retrieves, and if an allergen is found to be present, it generates a warning message with detailed information.

[1165] 4. Displaying the results

[1166] The matching results sent from the server are received by the terminal. The terminal visually displays the results to the user, and if an allergen is found to be present, a warning such as red is displayed. This allows the user to intuitively confirm the safety of the product.

[1167] Specific examples

[1168] For example, when a user wants to buy a chocolate bar at a supermarket, they scan the product with their smartphone camera. At this time, the device extracts the product name "Chocolate Bar" and its ingredients using OCR and sends this information to the server. The server then searches its database to see if the product contains peanuts and compares it with the user's allergy information. If it does contain peanuts, a warning message is generated and sent to the device. The user's device then displays a red warning message saying "Warning: This product contains peanuts."

[1169] This system allows users to easily check whether a product contains any of their allergens when purchasing it, allowing them to make purchases with peace of mind.

[1170] The processing flow will be explained below.

[1171] Step 1:

[1172] The user uses the device's camera to capture an image of the product. The user launches the camera application and points the camera at the product packaging, barcode, or QR code to take a picture.

[1173] Step 2:

[1174] The device temporarily stores the acquired product images in its internal memory. At this point, the images are not yet processed and are stored in their raw form.

[1175] Step 3:

[1176] The device invokes an optical character recognition (OCR) tool to extract text information such as the product name, ingredients, and barcode from the saved product image. The text information obtained by OCR is saved in a variable.

[1177] Step 4:

[1178] The device analyzes the extracted text information to identify product names and ingredient information, which is then prepared as structured data to be sent to the server.

[1179] Step 5:

[1180] The device then makes a network request to send the identified product name and ingredient information to the server, along with the user's identity and other contextual information.

[1181] Step 6:

[1182] The server analyzes the received request and searches the database for product information. Based on the product name and ingredient information, the server retrieves detailed information about the corresponding product from the database.

[1183] Step 7:

[1184] The server compares the acquired product information with the allergy information registered by the user, checks whether the product contains any allergens, and generates a warning if any allergens match.

[1185] Step 8:

[1186] The server creates a response containing the matching results and sends it to the user's device. The response includes detailed information about the allergens and a warning message if any allergens are present.

[1187] Step 9:

[1188] The device analyzes the received response and displays a warning message to the user if an allergen is found to be present. The warning message is displayed in a visually noticeable manner, such as in red.

[1189] Step 10:

[1190] The user reviews the displayed warning message and decides whether to continue with the purchase. At this point, the user is armed with the information to make a safe product choice.

[1191] The above is a specific processing flow for carrying out the present invention.

[1192] Example 1

[1193] 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."

[1194] There are currently many products on the market, and there is a demand for a method to quickly check the extent to which each ingredient contributes to a user's allergies. However, conventional methods require users to personally check the product packaging and compare the ingredient list with their own allergy information, which is time-consuming and laborious, and also carries a high risk of overlooking something. The present invention aims to solve these problems and provide a system that can quickly and accurately check the presence of allergens while reducing the user's effort.

[1195] 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.

[1196] In this invention, the server includes means for extracting text information from product images using optical character recognition means, means for transmitting the extracted text information to a central processing unit via a network, means for the central processing unit to search a product database based on the transmitted text information and obtain product information, means for the central processing unit to compare the product information with the user's registered allergy information, means for generating a warning message if an allergen is contained based on the comparison result and transmitting the warning message to the user's device, and means for the user's device to visually display the result including the warning message. This allows the user to check the allergen content status of a product in a short time after scanning it, enabling safe and fast product selection.

[1197] An "image capture device" is a device for capturing product images, including a camera, scanner, etc.

[1198] "Optical character recognition" is a technology for analyzing character information from image data and extracting text information.

[1199] A "Central Processing Unit" is a computer system that runs on a server or cloud and analyzes and processes received data.

[1200] "Text information" is character information extracted from product images, including product names and ingredient lists.

[1201] "Product database" means a database that stores information about products, including ingredient information and other product information.

[1202] A "network" is an infrastructure for data communication, including the Internet.

[1203] "Allergy information" is information about one's own allergies that is registered in advance by the user, and is a list showing allergic reactions to specific ingredients or substances.

[1204] A "warning message" is a notification message generated for a product that contains an allergen, and issues a warning to the user.

[1205] "User device" refers to a terminal used by a user, including a smartphone, tablet, etc.

[1206] "Visually displaying" means displaying information such as a warning message in a form that can be seen by the user on a display or the like.

[1207] The present invention relates to a system that allows a user to scan a product using a device such as a smartphone or tablet to check whether the product contains any ingredients that are related to an allergy that the user has registered.

[1208] System Configuration

[1209] The system is broadly composed of the following elements:

[1210] 1. On the user's device:

[1211] The device is a smartphone or tablet held by the user, equipped with a camera for scanning products and a display for displaying the results. The device also has an application installed to manage the user's allergy information.

[1212] 2. Server:

[1213] It is installed on the cloud and has a database that stores product information, a search engine that searches it, and logic that checks the user's allergy information against product information.

[1214] Hardware and software used

[1215] Device: Smartphone or tablet

[1216] Camera: Built-in camera

[1217] OCR software: Tesseract OCR

[1218] Cloud servers: AWS, Google Cloud, Azure

[1219] Database: MySQL, PostgreSQL

[1220] Search engine: Elasticsearch

[1221] Specific examples of processing

[1222] Product scanning

[1223] When a user goes to the supermarket to buy a chocolate bar, they scan the item with their smartphone camera. The device captures the image data and analyzes it with optical character recognition (OCR) software. For example, Tesseract OCR can be used to extract the ingredients, such as "chocolate bar" and "peanuts, sugar, cocoa."

[1224] Submitting and searching product information

[1225] The device uses an HTTP POST request to send this extracted text information to the server. For example, "{"product_name": "Chocolate bar", "ingredients": "Peanuts, Sugar, Cocoa"}". The server searches the product database based on the received information and retrieves the ingredient information for the corresponding product. It uses MySQL for the search, and if the corresponding product is not found, it uses Elasticsearch to search for similar products.

[1226] Matching with allergy information and generating results

[1227] The server compares the user's allergy information with the product's ingredient list. For example, if the user has registered a peanut allergy, the server verifies that the ingredient list includes "peanuts." Based on the comparison result, the server generates a warning message saying "Warning: This product contains peanuts" and sends it to the terminal.

[1228] Displaying the results

[1229] The user's device visually displays the warning message received from the server. For example, it displays "Warning: This product contains peanuts" on a red background to warn the user. This allows the user to intuitively confirm the safety of the product.

[1230] Prompt Sentence Examples

[1231] "What ingredients does this product contain?"

[1232] "Please tell me the list of ingredients in the product called 'Chocolate Bar'."

[1233] Does this product contain allergens?

[1234] This system allows users to easily check whether a product contains substances that they are allergic to when purchasing it, allowing them to make purchases with peace of mind.

[1235] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1236] Step 1: Product Scan

[1237] User: The user uses the camera on their smartphone or tablet to scan the barcode, QR code, or entire packaging of the product.

[1238] Input: Image data of product packaging

[1239] Output: Image data is saved to the device

[1240] Specific behavior: The user launches the camera app, points the camera at the product, and presses the scan button. The camera captures an image of the product packaging.

[1241] Step 2: Extracting text information

[1242] Terminal: The terminal analyzes the acquired image data using optical character recognition (OCR) software (e.g., Tesseract OCR) to extract text information such as the product name and ingredient list.

[1243] Input: Image data

[1244] Output: Extracted text information (e.g. "Chocolate bar", "Peanuts, sugar, cocoa")

[1245] Specific operation: Through OCR processing, text information is analyzed from image data and structured in JSON format.

[1246] Step 3: Send text information

[1247] Terminal: The extracted text information is sent to the server via the network. Specifically, JSON data is sent using an HTTP POST request.

[1248] Input: Text information (JSON format)

[1249] Output: Text information sent to the server

[1250] Specific operation: An application in the device generates an HTTP request, attaches the extracted text information, and sends it to the server.

[1251] Step 4: Find product information

[1252] Server: The server searches the product database based on the text information sent and retrieves the ingredient information for the corresponding product. MySQL and Elasticsearch are used for the search.

[1253] Input: Text information (product name and ingredient list)

[1254] Output: Product information (ingredients list and related information)

[1255] Specific operation: The server executes a database query based on the received text information and retrieves detailed information about the corresponding product. Example of database query execution: "SELECT FROM products WHERE name="Chocolate bar""

[1256] Step 5: Check against allergy information

[1257] Server: The server compares the ingredient list of the acquired product information with the allergy information registered in advance by the user, and performs a process to check whether the product contains any allergens.

[1258] Input: Product information (ingredients list), user allergy information

[1259] Output: Matching result (whether or not allergens are included)

[1260] Specific operation: The server compares the product ingredients with the user's allergy information, and if there are any matching substances, determines the risk of an allergic reaction.

[1261] Step 6: Generate a warning message

[1262] Server: Based on the matching results, if an allergen is found, generate a warning message. For example, create a message saying "Warning: This product contains peanuts."

[1263] Input: Matching result

[1264] Output: Warning message

[1265] Specific operation: Based on the matching results, the system runs a process to automatically generate a warning message. The generated message is saved in text format.

[1266] Step 7: Sending and displaying warning messages

[1267] Server: The generated warning message is sent to the user's terminal as an HTTP response.

[1268] Terminal: Visually display the warning message received from the server to the user, for example displaying the message "Warning: This product contains peanuts" on a red background.

[1269] Input: warning message

[1270] Output: Display of a warning message on the user's terminal

[1271] Specific behavior: The device receives the HTTP response, the application analyzes its contents, and displays a visual warning to the user.

[1272] In this way, users can easily check whether a product contains their allergens and choose products safely.

[1273] (Application example 1)

[1274] 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."

[1275] There is a lack of means for passengers of self-driving vehicles to quickly and accurately check the ingredient information of food and beverages they purchase or bring on board, and to prevent the ingestion of allergens. Therefore, it is necessary to provide an environment where passengers can enjoy food and beverages in safety on board self-driving vehicles.

[1276] 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.

[1277] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for passengers to scan the product using a tablet terminal or a dedicated display, means for transmitting the acquired ingredient information to a cloud server, and means for comparing the ingredient information with the user's allergy information and generating a result. This enables passengers to safely check the ingredient information of food and drink even inside an autonomous vehicle and avoid the risk of allergic reactions.

[1278] An "image capture device" is a device that captures product images using a camera or the like.

[1279] "Optical character recognition" is a technology that analyzes and extracts text information from images.

[1280] The "means for searching for product information" is a function for finding relevant product information from a database based on the extracted text information.

[1281] "User's registered allergy information" refers to information about allergies that the user has previously entered and saved in the system.

[1282] The "verification means" is a function that compares the user's allergy information with product information to check whether there are any matches.

[1283] The "means for displaying a warning" is a function that displays a visual warning to the user if the result of the comparison indicates that an allergen is contained.

[1284] "Tablet device or dedicated display" refers to a portable display device used for scanning products and displaying results.

[1285] A "cloud server" is a server that stores and provides data over the Internet.

[1286] The "means for transmitting ingredient information" is a function for transmitting the acquired product ingredient information to the cloud server.

[1287] The "means for generating results" is a function that generates warnings or other notifications based on the results of matching ingredient information with the user's allergy information.

[1288] System Overview

[1289] The present invention is a system that allows users to quickly check the ingredient information of food and beverages purchased or brought into an autonomous vehicle. Specifically, it is composed of an image capture device, optical character recognition (OCR) means, database search means, allergy information checking means, warning display means, a tablet terminal or dedicated display, a cloud server, ingredient information transmission means, and result generation means.

[1290] Hardware and software used

[1291] Image capture device: Camera installed in the vehicle or camera on a tablet device.

[1292] Optical Character Recognition: Tesseract OCR is used to extract text information from product images.

[1293] Cloud server: AWS is used as the cloud environment, AWS RDS is used as the database, and Elasticsearch is used as the search engine.

[1294] Tablet or dedicated display: A means for passengers to scan items and view results.

[1295] Application framework: Use Flutter or React Native to build the user interface.

[1296] Specific Examples of the Invention

[1297] To implement this system, the user performs the following operations: First, the passenger scans the product using a tablet device or dedicated display. The scanned product image is captured by an image capture device. Next, text information is extracted from the product image using optical character recognition (Tesseract OCR). This text information is sent to a cloud server, where a database search is performed. The captured product information is compared with allergy information previously registered by the user.

[1298] If an allergen is found in a product, a warning message will be generated and displayed on the tablet or a dedicated display, allowing users to safely check the product's ingredient information.

[1299] Specific examples

[1300] For example, a user scans a drink (such as juice) they have purchased in an autonomous vehicle. At this time, the ingredient information of the scanned product is sent to a cloud server and extracted using OCR. The cloud server then searches a product database to obtain the ingredient information. This ingredient information is then compared with the user's allergy information, and if the drink contains an allergen, a warning message is displayed on the tablet device.

[1301] Prompt Sentence Examples

[1302] It uses a camera to scan drinks (juices) purchased by passengers in the vehicle, then uses OCR technology to extract the ingredients and search the AWS RDS database, matching them with the user's allergy information and displaying the results on the passenger's smart display.

[1303] This system allows passengers to enjoy meals and drinks safely inside self-driving vehicles.

[1304] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1305] Step 1:

[1306] The user scans the product using a tablet device or dedicated display.

[1307] Input: Product packaging image

[1308] What it does: The user uses the camera to scan the barcode of an item or the entire package.

[1309] Step 2:

[1310] The image capture device captures product images.

[1311] Input: scanned package image

[1312] Specific operation: The tablet device's camera captures product images and saves them to its internal memory.

[1313] Step 3:

[1314] Extract text information from product images using optical character recognition (OCR).

[1315] Input: Captured product image

[1316] Specific operation: The device calls Tesseract OCR, analyzes the text information in the image, and extracts product name and ingredient information.

[1317] Output: Extracted text information

[1318] Step 4:

[1319] The extracted text information is sent to a cloud server.

[1320] Input: Extracted text information

[1321] Specific operation: The device sends the extracted text information via the Internet to the cloud server through AWS API Gateway.

[1322] Step 5:

[1323] The server searches the product database and obtains the relevant product information.

[1324] Input: Extracted text information

[1325] Specific operation: Based on the text information received by the server, Elasticsearch is used to search the product database (AWS RDS) and obtain the corresponding product information.

[1326] Output: Retrieved product information

[1327] Step 6:

[1328] The server compares the user's allergy information with the product information.

[1329] Input: Retrieved product information and user allergy information

[1330] Specific operation: The server compares the user allergy information in the database with the ingredient list of the retrieved product information to determine whether any matching allergens exist.

[1331] Output: Matching result

[1332] Step 7:

[1333] The server generates a warning message based on the result of the check and sends it to the terminal.

[1334] Input: Matching result

[1335] Specific operation: If an allergen is contained, the server generates a warning message (e.g., "Warning: Contains allergen") and sends it to the terminal.

[1336] Output: Warning message

[1337] Step 8:

[1338] The terminal visually displays a warning message to the user, and if an allergen is included, the warning is displayed in red or other colors.

[1339] Input: The warning message received from the server

[1340] Specific operation: The device will display a warning message on the screen and highlight any allergens with a red background color, for example.

[1341] This allows users to safely check the ingredient information of food and drink inside their self-driving vehicle and avoid allergic reactions.

[1342] 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.

[1343] The present invention is a system that combines an emotion engine that recognizes emotions when a user scans an item and tailors warnings based on the user's allergy information. The steps and specific operations required to implement this system are described in detail below.

[1344] System Configuration

[1345] The system consists of the following components:

[1346] 1. On the user's device:

[1347] The device, such as a smartphone or tablet held by the user, is equipped with a camera for scanning products and a camera and microphone for recognizing emotions. A dedicated application is installed on the device, which has a function for managing the user's allergy information and an emotion engine.

[1348] 2. Server:

[1349] The cloud-based server has a database that stores product information, a search engine for searching it, and logic for matching user allergy information with product information. It can also process emotional information.

[1350] 3. Emotion Engine:

[1351] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reaction.

[1352] Implementation of the invention

[1353] 1. Scan the product

[1354] Users can use their device's camera to scan product packaging, barcodes, and QR codes, and the product images captured by the camera are saved on the device.

[1355] 2. Information extraction from images

[1356] The device passes the stored product image to an optical character recognition (OCR) tool to extract text information such as the product name and ingredients, which is then prepared for transmission to the server.

[1357] 3. Search for product information

[1358] The terminal sends the extracted text information to the server, which then searches the product database based on the received information to obtain ingredient information and related information for the relevant product.

[1359] 4. Checking allergy information

[1360] The server compares the searched product information with the user's registered allergy information, and generates a result indicating whether the product contains any allergens, and if so, detailed information about the ingredients.

[1361] 5. Emotional Recognition

[1362] When a warning is displayed, the device captures the user's reaction using the device's camera and microphone, and the emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[1363] 6. Adjusting the display of warning messages

[1364] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. For example, if the user looks anxious, the device will display the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[1365] Specific examples

[1366] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[1367] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[1368] This allows users to intuitively understand important information about their allergies and decide whether to make a purchase with confidence.By taking user emotions into consideration, this system enables more effective and flexible warning messages to be displayed, improving consumer safety and peace of mind.

[1369] The processing flow will be explained below.

[1370] Step 1:

[1371] The user launches the device's camera application and scans the product packaging, barcode, or QR code. The camera captures the product image and saves the image data on the device.

[1372] Step 2:

[1373] The device launches an OCR (optical character recognition) tool to analyze the captured product image, extracting text information from the image and identifying product name and ingredient information.

[1374] Step 3:

[1375] The device sends the text information extracted by the OCR tool to the server over the network, along with the user's identification information.

[1376] Step 4:

[1377] The server analyzes the received text information and searches the product database to obtain detailed information about the corresponding product. The server searches based on the product name and ingredient information, and if no corresponding product is found, it searches for similar products.

[1378] Step 5:

[1379] The server compares the product information obtained from the search with the allergy information registered by the user, and then compares the product ingredient list with the allergy information to see if it contains any matching allergens.

[1380] Step 6:

[1381] If an allergen is present, the server generates a warning about the ingredient, including details of the specific allergen and its health risks.

[1382] Step 7:

[1383] The server transmits the generated warning information to the terminal, where it is transmitted quickly and securely, allowing the user to quickly check it.

[1384] Step 8:

[1385] The terminal analyzes the received warning information and prepares it for visual display to the user. The terminal determines the best way to display the warning message.

[1386] Step 9:

[1387] The device will capture the user's reaction using the device's camera and microphone just before displaying the warning message, collecting data for the emotion engine to analyze the user's facial expressions and voice.

[1388] Step 10:

[1389] The emotion engine installed on the device analyzes the captured user's facial expressions and voice signals to recognize the user's emotional state. For example, if the user has a surprised expression, the emotion is recognized as "surprise."

[1390] Step 11:

[1391] The device adjusts the way the warning message is displayed based on the user's emotional state as recognized by the emotion engine: if the user is surprised, the warning message is displayed in red and bold to emphasize it.

[1392] Step 12:

[1393] The device displays a tailored warning message to the user, such as "This product contains peanuts" in bold red text to grab the user's attention.

[1394] Step 13:

[1395] The user checks the displayed warning message and decides whether to continue with the purchase of the product. The user can make a safe product selection based on the provided warning information.

[1396] The above is a specific processing flow for an embodiment of the invention that combines an emotion engine, allowing users to enjoy a safer and more secure shopping experience by taking into consideration not only the product scanning process but also the emotions involved.

[1397] Example 2

[1398] 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."

[1399] Conventional systems allow users to check whether an item contains allergens when they scan it, but the warning display does not take into account the user's emotional state, which means the warning is not communicated effectively. Furthermore, while there is a need for warnings to be displayed in a way that is intuitively easy for users to understand, there is also the issue of not using emotion recognition technology to adjust the warning display.

[1400] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for acquiring product images, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for recognizing the user's emotional state, and means for displaying a warning in accordance with the user's emotional state if the product contains an allergen based on the comparison result. This makes it possible to display a warning that takes the user's emotional state into consideration, thereby ensuring effective communication of the warning.

[1401] "Means for acquiring product images" refers to devices or functions that acquire images of the product packaging, barcodes, or QR codes scanned by the user.

[1402] "Optical character recognition means" refers to a technology for extracting text information from acquired product images, and in particular uses optical character recognition (OCR) technology.

[1403] The "means for extracting text information" is a function that uses optical character recognition means to extract text information such as product names and ingredient information from the product images as digital data.

[1404] The "means for searching for product information" is a technique for searching for and acquiring the relevant product information from a product database via a network based on the extracted text information.

[1405] "User's registered allergy information" refers to information about allergies that the user has previously entered into a dedicated application and that is stored on the server.

[1406] The "means for checking product information against the allergy information" is a function that compares the acquired product information with the user's allergy information to determine whether or not the product contains an allergen.

[1407] "Means for recognizing the user's emotional state" refers to devices or technologies that analyze the user's facial expressions and voice signals to recognize the user's emotional state (surprise, anxiety, relief, etc.).

[1408] "Means for displaying a warning" refers to a device or technology that visually or audibly notifies the user if the product contains an allergen based on the comparison results.

[1409] The "means for displaying a warning depending on the user's emotional state" is a function that dynamically changes the way the warning message is displayed (color, font, emphasis, etc.) based on the user's perceived emotional state.

[1410] The present invention relates to a system that allows a user to scan a product and adjusts a warning message using an emotion engine. Specific embodiments of the system are described below.

[1411] System Configuration

[1412] The system consists of the following components:

[1413] 1. On the user's device:

[1414] The user's smartphone, tablet, or other device is equipped with a high-resolution camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed on the device, and processing is performed using an OCR tool (e.g., Tesseract) and an emotion engine (e.g., Emotion API).

[1415] 2. Server:

[1416] It is a server installed in the cloud that has a database (e.g., Elasticsearch) that stores product information and a search engine for searching it. It also has logic that matches the user's allergy information with product information. It can also process emotional information.

[1417] 3. Emotion Engine:

[1418] An engine that recognizes emotions by analyzing the user's facial expressions and voice. The emotion engine is implemented on the device and has the function of adjusting the way warning messages are displayed based on the user's reactions.

[1419] Product scanning and information extraction

[1420] First, the user uses the device's camera to scan the product packaging, barcode, or QR code. The captured product image is saved on the device, and text information such as the product name and ingredient list is extracted using an OCR tool. This allows the product information to be obtained as digital data.

[1421] Product information search and matching

[1422] The device sends the extracted text information in JSON format to the server. Based on the received information, the server uses a search engine such as Elasticsearch to search a product database and retrieves the ingredient information and related information for the relevant product. The server then compares the information with the user's registered allergy information, determines whether the product contains any allergens, and generates a result.

[1423] Emotion recognition and warning display adjustment

[1424] When displaying warning information, the device's camera and microphone are used to capture the user's reactions. The emotion engine (e.g., Emotion API) analyzes the user's facial expressions and voice to recognize their emotional state. Based on the recognition results, the way the warning message is displayed can be dynamically changed depending on the user's emotional state, such as displaying the warning message in bold red if the user looks anxious.

[1425] Specific examples

[1426] For example, when a user attempts to purchase a tin of store-bought cookies at a supermarket, they scan the item with their smartphone camera. The device extracts the product name "Chocolate Chip Cookies" and ingredient information using OCR and sends them to a server. The server then searches the product information in a database and verifies that peanuts are included in the ingredient list. If the user has registered a peanut allergy, the server generates an allergy warning and sends it to the device.

[1427] The device receives the warning information and captures the user's reaction using a camera and microphone when displaying it. The emotion engine analyzes the user's facial expressions and voice and recognizes that the user is surprised by the warning. Based on this, the device displays the warning message in bold red, emphasizing the message "This product contains peanuts."

[1428] Prompt Sentence Examples

[1429] The following prompt sentence is input to the generative AI model to generate a warning message:

[1430] Please provide the information of the product scanned by the user. Then generate a warning message based on the user's allergy information. Based on the user's sentiment, customize the message as follows:

[1431] 1. If the user looks surprised: Display a bold red warning message

[1432] 2. If the user looks relieved: Display the warning message in normal font and color.

[1433] Example output: "This product contains peanuts."

[1434] As described above, the present invention provides a system that realizes the display of warning messages that take into account the emotional state of the user, thereby improving consumer safety and security.

[1435] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1436] Step 1: Start scanning your products

[1437] The user launches a dedicated application on a smartphone or tablet device and scans the product packaging, barcode, or QR code with the camera. The input is an image of the product captured by the user's device's camera. The output is the captured image of the product stored in the device's internal memory. Specifically, the user launches the camera application on the device, points the camera at the product, and captures the image.

[1438] Step 2: Extracting information from the image

[1439] The device inputs product images stored in its internal memory into an OCR tool (e.g., Tesseract). As input, it receives the product images stored in memory. As output, it extracts text information such as the product name and ingredient list. This text information is structured in JSON format and is ready to be sent to the server. Specifically, the device passes the stored image to the OCR tool, which then extracts the text information from the image.

[1440] Step 3: Get product information

[1441] The terminal sends the extracted text information to the server. The extracted text information (JSON format) is obtained as input. As output, a query is executed to obtain the ingredient information and related information of the target product. The server uses a search engine such as Elasticsearch based on that information to search a product database and obtains the ingredient information and related information of the relevant product. Specifically, the terminal sends JSON format data to the server, and the server executes a search query on the database.

[1442] Step 4: Check against allergy information

[1443] The server compares the searched product information with the user's registered allergy information. The input is the product information and the user's allergy information. The output is a determination of whether the product contains an allergen and detailed information about the ingredients. Specifically, the server retrieves allergy information from the user database and compares it with the product information to determine whether the product contains an allergen.

[1444] Step 5: Recognize emotions

[1445] When warning information is displayed, the device uses the device's camera and microphone to capture the user's reaction. As input, the user's facial expression data and voice data when the warning information is displayed are obtained. As output, the user's emotional state (surprise, anxiety, relief, etc.) is recognized. Specifically, the device captures the user's facial expression with the camera and records voice with the microphone, and inputs this data into an emotion engine (e.g., Emotion API) for emotion analysis.

[1446] Step 6: Adjust the display of warning messages

[1447] The device dynamically changes the way it displays warning messages based on the user's emotions recognized by the emotion engine. The input is the user's emotional state and the warning information generated in the previous stage. The output is a warning message that corresponds to the user's emotional state. Specifically, the device receives the results of the emotion engine, adjusts the display method (color, font, emphasis, etc.) of the warning message to match the user's emotions, and displays it on the screen.

[1448] As described above, this system performs detailed data processing and calculations at each processing step, enabling it to display warning messages that take into account the user's emotional state, thereby improving consumer safety and peace of mind.

[1449] (Application example 2)

[1450] 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."

[1451] While conventional product scanning systems in logistics centers display product ingredient information and allergy warnings, they do not adjust the display method to take into account employee emotions and health conditions. This creates a risk that employees may continue working while feeling stressed or tired, which can lead to problems with productivity and safety. The objective of this invention is to provide a system that solves these problems and enables employee health management.

[1452] 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.

[1453] In this invention, the server includes means for acquiring product images using an image acquisition device, means for extracting text information from the product images using optical character recognition means, means for searching for product information based on the extracted text information, means for comparing the product information with the user's registered allergy information, means for displaying a warning if the product contains an allergen based on the comparison result, means for recognizing the user's emotion, and means for adjusting the display method of the warning message based on the recognized emotion. This enables warnings to be displayed according to the employee's health condition, thereby improving workability and safety.

[1454] An "image capture device" is a device for capturing images of products using a photographic device such as a camera.

[1455] "Optical character recognition" is a technology that analyzes character information from captured images and converts it into digital text.

[1456] "Product information" is detailed data about a product, including information on ingredients, price, barcode information, and so on.

[1457] "Allergy information" is data relating to individual allergies registered by the user, and includes allergic reaction information to specific substances.

[1458] "Verification" is the process of comparing product information with the user's allergy information to see if they match.

[1459] A "warning message" is a notification to inform the user that an allergen is contained.

[1460] "Emotion recognition" is a technology that uses a camera and microphone to analyze a user's emotional state from their facial expressions and voice.

[1461] "Adjusting the way warning messages are displayed" refers to dynamically changing the color, font, and display format of warning messages based on the perceived emotion.

[1462] A "system" is a set of components that combine multiple means and devices to provide specific functions or services.

[1463] This invention is a system that supports employee health management and efficient work performance in logistics centers. This system has the function of recognizing the employee's emotions when scanning products and dynamically adjusting warning messages based on those emotions. The specific operation and configuration of this system are described below.

[1464] System Configuration

[1465] The system consists of the following elements:

[1466] 1. User's device

[1467] The smartphone is equipped with a camera for scanning products and a camera and microphone for emotion recognition. A dedicated application is installed, which includes an optical character recognition (OCR) tool, an emotion engine, and allergy information management functions.

[1468] 2. Server

[1469] It has a database (MongoDB) that stores product information and is equipped with logic to check against the user's allergy information. It is installed on a cloud server and communicates with devices via the network.

[1470] 3. Emotion Engine

[1471] The Emotion SDK is used to recognize emotions by analyzing the user's facial expressions and voice. Implemented on the device, it adjusts the way warning messages are displayed based on the user's reactions.

[1472] Specific system behavior

[1473] 1. Scan the product

[1474] Users use their device's camera to scan the product's barcode or QR code, and the product image captured by the camera is saved on the device.

[1475] 2. Information extraction from images

[1476] The device passes the saved product image to an OCR tool (Tesseract) to extract text information such as the product name and ingredients. The extracted text information is then prepared for transmission to the server.

[1477] 3. Search for product information

[1478] The server searches the product database based on the received text information, retrieves the ingredient information and related information for the relevant product, and returns this information to the terminal.

[1479] 4. Checking allergy information

[1480] The server compares the searched product information with the user's registered allergy information, and as a result, generates a result of the comparison as to whether the product contains any allergens, and if so, generates detailed information about the ingredients, and sends it to the terminal.

[1481] 5. Emotional Recognition

[1482] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction, and an emotion engine analyzes the user's facial expressions and voice signals to recognize the user's emotional state.

[1483] 6. Adjusting the display of warning messages

[1484] The device dynamically changes the way warning messages are displayed based on the user's emotions as recognized by the emotion engine. If the user has a surprised expression, the device displays the warning message in a more striking color and font, encouraging the user to take appropriate action based on their emotions.

[1485] Specific examples

[1486] For example, let's say an employee is in the middle of scanning products during peak hours. At this time, they use their smartphone camera to scan the products and extract ingredient information using OCR. The extracted information is sent to a server, and if the match indicates that the product contains an allergen, a warning message is generated. At the same time, the device's emotion engine analyzes the employee's facial expressions and voice, and if it detects high levels of stress or fatigue, it displays a message such as "Let's take a short break." An example of a prompt sentence to be used at this time could be, "An app that allows employees working at a logistics center to scan products and check for allergens. If an employee is feeling stressed, display a message encouraging them to take a break."

[1487] In this way, the system can support both employee health and work efficiency.

[1488] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1489] Step 1:

[1490] The user uses the device's camera to scan the barcode or QR code of a product, and the device processes the captured product image as input.

[1491] Step 2:

[1492] The terminal passes the acquired product image to an optical character recognition (OCR) tool (Tesseract) to extract text information such as the product name and ingredient list. In OCR processing, image data is input and the extracted text information is output.

[1493] Step 3:

[1494] The terminal sends the extracted text information to the server. The server searches the product database (MongoDB) based on the received text information and retrieves the ingredient information and related information of the corresponding product. In this data search process, the text information is used as input and the corresponding product information is output.

[1495] Step 4:

[1496] The server compares the searched product information with the user's registered allergy information. In the comparison process, the product information and allergy information are input, and the output is a determination of whether the product contains an allergen.

[1497] Step 5:

[1498] Based on the comparison result, the server generates a warning message if an allergen is found to be present and sends it to the terminal. In this warning generation process, the comparison result is used as input and the warning message is used as output.

[1499] Step 6:

[1500] When a warning is displayed, the device uses a camera and microphone to capture the user's reaction. The capture process takes the user's facial expressions and voice data as input and prepares them for passing to the emotion engine.

[1501] Step 7:

[1502] The device uses an emotion engine (Emotion SDK) to analyze the user's emotions. The emotion analysis process takes the user's facial expressions and voice data as input and outputs analyzed emotional information.

[1503] Step 8:

[1504] The terminal adjusts the display method of the warning message based on the recognized emotion information. The display adjustment process takes the emotion information and the warning message as input and outputs the adjusted warning message. The adjusted message is displayed on the connected user interface.

[1505] This process allows employees to check allergy information when scanning products and receive appropriate warning messages based on their emotional state.

[1506] 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.

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] 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.

[1512] 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).

[1513] 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.

[1514] 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."

[1515] 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.

[1516] 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).

[1517] 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.

[1518] 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.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] 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.

[1523] 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.

[1524] 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.

[1525] 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.

[1526] 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.

[1527] The following is further disclosed regarding the above embodiment.

[1528] (Claim 1)

[1529] A means for acquiring a product image by an image acquisition device;

[1530] means for extracting text information from the product images using optical character recognition means;

[1531] a means for searching for product information based on the extracted text information;

[1532] means for comparing the registered allergy information of the user with the product information;

[1533] a means for displaying a warning when an allergen is contained based on the result of the comparison;

[1534] A system including:

[1535] (Claim 2)

[1536] 2. The system according to claim 1, wherein the means for searching for product information acquires the product information from a product database via a network.

[1537] (Claim 3)

[1538] 2. The system according to claim 1, wherein the means for displaying a warning when an allergen is contained displays a warning message including specific information about the allergen.

[1539] "Example 1"

[1540] (Claim 1)

[1541] A means for acquiring a product image by an image acquisition device;

[1542] means for extracting text information from the product images using optical character recognition means;

[1543] means for transmitting the extracted text information to a central processing unit via a network;

[1544] a means for the central processing unit to search a product database based on the transmitted text information and acquire product information;

[1545] a means for the central processing unit to compare the registered allergy information of the user with the product information;

[1546] means for generating a warning message when an allergen is contained based on the result of the comparison and transmitting the warning message to the user's device;

[1547] means for the user's device to visually display the results, including the warning message;

[1548] A system including:

[1549] (Claim 2)

[1550] 2. The system according to claim 1, wherein the means for searching for product information acquires the product information from a product database via a network.

[1551] (Claim 3)

[1552] 2. The system according to claim 1, wherein the means for displaying a warning when an allergen is contained displays a warning message including specific information about the allergen.

[1553] "Application Example 1"

[1554] (Claim 1)

[1555] A means for acquiring a product image by an image acquisition device;

[1556] means for extracting text information from the product images using optical character recognition means;

[1557] a means for searching for product information based on the extracted text information;

[1558] means for comparing the registered allergy information of the user with the product information;

[1559] a means for displaying a warning when an allergen is contained based on the result of the comparison;

[1560] A means for passengers to scan items using a tablet device or dedicated display;

[1561] means for transmitting the acquired component information to a cloud server;

[1562] a means for matching the ingredient information with the user's allergy information and generating a result;

[1563] A system including:

[1564] (Claim 2)

[1565] 2. The system according to claim 1, wherein the means for searching for product information acquires the product information from a product database via a network.

[1566] (Claim 3)

[1567] 2. The system according to claim 1, wherein the means for displaying a warning when an allergen is contained displays a warning message including specific information about the allergen.

[1568] "Example 2: Combining Emotion Engines"

[1569] (Claim 1)

[1570] A means for acquiring product images;

[1571] means for extracting text information from the product images using optical character recognition means;

[1572] a means for searching for product information based on the extracted text information;

[1573] means for comparing the registered allergy information of the user with the product information;

[1574] means for recognizing the emotional state of a user;

[1575] a means for displaying a warning in accordance with the emotional state of the user when an allergen is found based on the comparison result;

[1576] A system including:

[1577] (Claim 2)

[1578] 2. The system according to claim 1, wherein the means for searching for product information acquires the product information from a product database via a network.

[1579] (Claim 3)

[1580] 2. The system according to claim 1, wherein the means for displaying a warning when an allergen is contained displays a warning message including specific information about the allergen.

[1581] "Application example 2 when combining emotion engines"

[1582] (Claim 1)

[1583] A means for acquiring a product image by an image acquisition device;

[1584] means for extracting text information from the product images using optical character recognition means;

[1585] a means for searching for product information based on the extracted text information;

[1586] means for comparing the registered allergy information of the user with the product information;

[1587] a means for displaying a warning when an allergen is contained based on the result of the comparison;

[1588] means for recognizing a user's emotion;

[1589] means for adjusting a display manner of a warning message based on the recognized emotion;

[1590] A system including:

[1591] (Claim 2)

[1592] 2. The system according to claim 1, wherein the means for searching for product information acquires the product information from a product database via a network.

[1593] (Claim 3)

[1594] The system of claim 1, wherein the means for displaying a warning when an allergen is contained displays a warning message including specific information about the allergen, and further adjusts the display method according to the user's emotional state. [Explanation of symbols]

[1595] 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 acquiring a product image by an image acquisition device; means for extracting text information from the product images using optical character recognition means; a means for searching for product information based on the extracted text information; means for comparing the registered allergy information of the user with the product information; a means for displaying a warning when an allergen is contained based on the result of the comparison; A system including:

2. 2. The system according to claim 1, wherein said means for searching for product information acquires product information from a product database via a network.

3. 2. The system according to claim 1, wherein the means for displaying a warning when an allergen is present displays a warning message including specific information about the allergen.

Images