System

Abstract

A system is provided.SOLUTION: A system including photographing means for a user to photograph a food package, upload means for uploading a photographed image to a server, analysis means for analyzing the image in the server and acquiring ingredient information of the food, evaluation means for performing evaluation according to a health risk on the basis of the acquired ingredient information, generation means for generating an alert and advice in consideration of health condition information of the user, and notification means for notifying the user of the generated alert and advice.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] Please write "Problem to be solved" and "Means to solve the problem" in the following format.

[0005] In modern society, many foods contain a variety of additives and ingredients, making it extremely difficult to understand how they affect health. For people with certain health conditions, such as high blood pressure, gout, or anemia, identifying foods containing ingredients to avoid can be particularly challenging, potentially increasing health risks. Furthermore, routinely checking food ingredients and making appropriate decisions requires specialized knowledge, placing a significant burden on many people. Furthermore, because the ingredients to be avoided vary depending on health conditions and dietary goals, general food selection guidelines are insufficient. [Means for solving the problem]

[0006] To address the above-mentioned issues, the present invention provides a system that allows a user to photograph a food package, analyzes its ingredient information, and provides appropriate alerts and advice tailored to the user's health condition. Specifically, the system includes a photographing device for the user to photograph the food package, an uploading device for uploading the photographed image to a server, an analysis device for analyzing the image on the server to obtain food ingredient information, an evaluation device for assessing health risks based on the obtained ingredient information, a generation device for generating alerts and advice taking into account the user's health condition information, and a notification device for notifying the user of the generated alerts and advice. This allows users to easily check food ingredient information and make appropriate choices for their health condition. Furthermore, by using OCR technology on the server to extract ingredient information from the image, the accuracy of obtaining ingredient information can be improved, and by filtering the ingredient evaluation results based on the user's profile information, more personalized alerts and advice can be provided.

[0007] "Photographing means" refers to a device or function that allows a user to photograph a food package.

[0008] "Uploading means" refers to a device or function for sending captured images to a server.

[0009] The "analysis means" refers to a device or function that allows the server to analyze image data and obtain information about food ingredients.

[0010] The "evaluation means" refers to a device or function that evaluates each ingredient according to its health risk based on the acquired ingredient information.

[0011] A "generator" is a device or function that generates alerts and advice taking into account the user's health status information.

[0012] "Notification means" refers to a device or function for notifying a user of generated alerts and advice.

[0013] "OCR technology" is optical character recognition technology, which converts text in an image into digital data.

[0014] "Ingredient information" refers to information about the various ingredients contained in food and their amounts.

[0015] "User profile information" is individual setting information such as the user's health condition, allergy information, and diet goals.

[0016] An "alert" is a message that warns the user of a risk to their health.

[0017] "Advice" is a recommendation or guidance for a user to make healthy choices. [Brief explanation of the drawings]

[0018] [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

[0019] 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.

[0020] First, the terms used in the following description will be explained.

[0021] 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).

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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."

[0026] [First embodiment]

[0027] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0028] 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.

[0029] 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).

[0030] 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.

[0031] 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.

[0032] 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.

[0033] 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.

[0034] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0035] 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.

[0036] 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.

[0037] 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.

[0038] 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."

[0039] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0040] Overall system configuration

[0041] This system consists of a user's terminal, a server, and a network that connects them. The terminal is equipped with a means of taking pictures and uploading, and the server is equipped with a means of analyzing, evaluating, generating, and notifying.

[0042] Program processing flow

[0043] Food photography and image uploading

[0044] 1. The user launches the application on their device and takes a photo of the food package. The device uses the camera function to capture the image.

[0045] 2. The terminal automatically uploads the captured image to the server, and the uploading means transmits the image data to the server via a network connection.

[0046] Image analysis and component information acquisition

[0047] 3. The server receives the uploaded image. The analysis means uses OCR technology to convert the ingredient list in the image into text data.

[0048] 4. The server analyzes the converted text data and extracts information about the various ingredients contained in the food, such as preservatives, colorings, sodium, and phosphates.

[0049] Ingredient evaluation and alert generation

[0050] 5. The server evaluates the intake risk of each ingredient based on the extracted ingredient information. The evaluation tool refers to pre-set standard values ​​and databases to determine whether or not there is a health risk.

[0051] 6. Based on the user's profile information (e.g., high blood pressure, diabetes, anemia, etc.), an individual risk assessment is performed. The generator generates an appropriate alert message. For example, it generates a specific alert such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0052] Alert and advice notifications

[0053] 7. The server sends the generated alert or advice to the terminal. The notification means sends an alert message to the terminal, and the terminal notifies the user.

[0054] Specific examples

[0055] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera. The device uploads the image to the server, which then analyzes it using OCR technology to obtain the ingredient information.

[0056] The server then evaluates the snack based on this information and determines that it contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure.

[0057] Therefore, the server generates an alert to notify the user, saying, "This snack contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it." This notification is displayed on the device, allowing the user to reconsider the purchase or choose a different food item.

[0058] The above is an embodiment of the present invention. The present invention allows a user to easily select foods according to their own health condition.

[0059] The processing flow will be explained below.

[0060] Step 1:

[0061] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0062] Step 2:

[0063] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0064] Step 3:

[0065] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0066] Step 4:

[0067] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0068] Step 5:

[0069] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0070] Step 6:

[0071] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0072] Step 7:

[0073] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0074] Step 8:

[0075] The server uses the generation means to generate alerts and advice based on the ingredient evaluation results, for example, creating a specific alert message such as "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0076] Step 9:

[0077] The server activates a notification means for sending the generated alerts and advice to the terminal.The server sends an alert message to the terminal.

[0078] Step 10:

[0079] The device notifies the user of alerts and advice received from the server. The device displays messages in a pop-up on the screen or in the notification bar so that the user can easily check them.

[0080] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[0081] Example 1

[0082] 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."

[0083] Conventional food selection support systems are inefficient and require a lot of effort for users to select foods according to their health condition. Furthermore, extraction of ingredient information and health risk assessments are sometimes inaccurate, resulting in the provision of information that is not useful to users. Therefore, there is a need for a system that can provide highly accurate ingredient analysis according to the user's health condition and quickly provide appropriate alerts and advice.

[0084] 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.

[0085] In this invention, the server includes a photographing means for a user to photograph a food package, an uploading means for uploading the photographed image to the server, an analyzing means for analyzing the image in the server and obtaining ingredient information of the food, an evaluating means for making an assessment according to health risks based on the obtained ingredient information, a generating means for generating an alert and advice taking into account the user's health condition information, a notifying means for notifying the user of the generated alert and advice, an input means for inputting a prompt sentence to the generative AI model, and a generating AI means for performing ingredient analysis and health risk assessment using the generative AI model, thereby enabling users to efficiently and accurately select appropriate foods according to their health condition.

[0086] 1. The photographing means refers to a device or function that allows the user to photograph food packaging.

[0087] 2. Uploading means refers to the device or function for sending captured images to the server.

[0088] 3. Analysis means refers to the device or function that analyzes images on the server and obtains food ingredient information.

[0089] 4. Evaluation means refers to a device or function for making an assessment according to health risks based on the acquired ingredient information.

[0090] 5. Generating means refers to a device or function for generating alerts and advice taking into account the user's health status information.

[0091] 6. Notification means refers to a device or function for notifying the user of generated alerts and advice.

[0092] 7. Input means refers to a device or function for inputting prompt sentences into a generative AI model.

[0093] 8. Generative AI means refers to a device or function that uses a generative AI model to perform component analysis and health risk assessment.

[0094] 9. OCR technology refers to the technology that converts character information in an image into text data using optical character recognition technology.

[0095] 10. Profile information refers to information about a user's health status and individual health risks.

[0096] 11. Health risk refers to the potential danger that a particular ingredient poses to the user's health.

[0097] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0098] System configuration

[0099] This system consists of a user's device, a server, and a network connecting them. The device has a camera function and an upload function, while the server has analysis, evaluation, generation, and notification functions. The server also has a generative AI means for performing component analysis and health risk assessment using a generative AI model.

[0100] Hardware and software used

[0101] Devices: Mobile devices such as smartphones and tablets, with camera functions and network connectivity

[0102] Server: High-performance computer, database, OCR engine (e.g., Google Cloud Vision API), generative AI model (e.g., OpenAI GPT model)

[0103] Network: WiFi, mobile data

[0104] Program processing

[0105] Food photography and image uploading

[0106] 1. The user launches the application on their device and takes a picture of the food package. The user captures the image using the device's camera.

[0107] 2. The terminal automatically uploads the captured image to the server. The uploading means transmits the image data to the server.

[0108] Image analysis and component information acquisition

[0109] 3. The server receives the image and uses an analysis method (e.g., Google Cloud Vision API) to convert the character information in the ingredient list into text data using OCR technology.

[0110] 4. The server analyzes the text data and extracts information about the ingredients contained in the food.

[0111] Ingredient evaluation and alert generation

[0112] 5. The server uses the extracted ingredient information to evaluate the risk of intake by the assessment tool, referring to pre-existing standards and databases (e.g., USDA food database).

[0113] 6. The server performs an individual risk assessment based on the user's profile information. The generator generates appropriate alerts and advice based on the ingredient information and the user's health condition. For example, it generates a message such as, "This food contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it."

[0114] Alert and advice notifications

[0115] 7. The server sends the generated alert or advice to the terminal. The notification means sends a message to the terminal, and the terminal notifies the user.

[0116] Examples and prompts

[0117] Specifically, consider the case where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to a server. The server analyzes the image using OCR technology and obtains ingredient information. The server then evaluates the ingredient information and assesses risk by referencing the user's profile information. As a result, the server generates an alert for high sodium content and notifies the user.

[0118] As a concrete example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0119] "Please analyze the ingredients contained in this food and assess the health risks to users."

[0120] This system enables users to efficiently and accurately select foods appropriate for their health condition.

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

[0122] Step 1:

[0123] A user launches an application on their device and takes a picture of a food package. The user captures the image using the device's camera. The input is the image taken by the user, and the output is the image data stored on the device. The specific operation is that the user opens the app and taps the camera button to take a picture of the package.

[0124] Step 2:

[0125] Images captured by the device are automatically uploaded to the server. The input is image data stored on the device, and the output is image data sent to the server. The specific operation is that the device's upload function sends the image data to the server via the network the moment the image is saved.

[0126] Step 3:

[0127] The server receives the image and uses an analysis means to convert the character information in the image into text data using OCR technology. The input is the image data sent to the server, and the output is the converted text data. Specifically, the server processes the received request and extracts component information from the image using an OCR engine (e.g., Google Cloud Vision API).

[0128] Step 4:

[0129] The server analyzes the text data and extracts information about the ingredients contained in the food. The input is text data converted using OCR technology, and the output is the extracted ingredient information. Specifically, the server processes the text data and performs data calculations to generate an ingredient list.

[0130] Step 5:

[0131] The server uses the extracted ingredient information to evaluate the risk of intake. The input is ingredient information, and the output is the risk assessment result. Specifically, the server evaluates the risk of each ingredient by referencing standard values ​​and databases (e.g., the USDA food database).

[0132] Step 6:

[0133] The server performs an individual risk assessment based on the user's profile information. The input is the risk assessment result and the user's profile information, and the output is a risk assessment result specific to the user. Specifically, the server collates the user's health information and performs an individual risk assessment.

[0134] Step 7:

[0135] The server's generation means generates appropriate alerts and advice. The input is the risk assessment result, and the output is the generated alert message. Specifically, the server uses the generative AI model to generate a message such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0136] Step 8:

[0137] The server sends the generated alerts and advice to the terminal. The input is the generated alert message, and the output is the alert message sent to the terminal. The specific operation is that the notification means of the server delivers the generated message to the terminal.

[0138] Step 9:

[0139] The device receives the notification and displays it to the user. The input is the alert message sent from the server, and the output is the alert message displayed to the user. The specific behavior is that when the device receives a notification, it displays the alert message in the app or notification bar.

[0140] (Application example 1)

[0141] 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."

[0142] Conventional food selection methods require users to manually check the ingredient information of foods and determine whether they are suitable for their health condition. This method is very time-consuming and inconvenient, especially for users who lead busy lives. Furthermore, users who are not familiar with food ingredients may not be able to accurately judge the health impact of ingredient information. There is a need for a system that solves this problem and allows users to more easily and effectively manage health risks when purchasing food.

[0143] 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.

[0144] In this invention, the server includes a photographing means for a user to photograph a food package, a transmission means for uploading the photographed image to the server, an analysis means for analyzing the image in the server and obtaining ingredient information of the food, an evaluation means for making an evaluation according to health risks based on the obtained ingredient information, a generation means for generating an alert and advice taking into account the user's health condition information, a notification means for notifying the user of the generated alert and advice, and a display means for displaying the evaluation results of the food the user is considering purchasing. This allows a user to receive appropriate advice and risk assessment based on their own health condition simply by photographing the food package, making food selection easy and quick.

[0145] "Photographing means" refers to a device or function that allows a user to photograph a food package.

[0146] "Transmission means" is a function for uploading the captured video to a server.

[0147] The "analysis means" is a function for analyzing video on the server and obtaining information on food ingredients.

[0148] The "evaluation means" is a function that performs an evaluation according to health risk based on the acquired component information.

[0149] The "generation means" is a function for generating alerts and advice in consideration of the user's health condition information.

[0150] The "notification means" is a function for notifying the user of the generated alerts and advice.

[0151] The "display means" is a function for displaying the evaluation results of the food that the user is considering purchasing.

[0152] The present invention is directed to a system that allows a user to photograph a food package and analyze its ingredient information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail preferred embodiments of the present invention.

[0153] First, this system consists of a user terminal, a server, and a network connecting them. The terminal is equipped with a photographing means and a transmission means, and the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and a display means.

[0154] Hardware and Software

[0155] Terminal

[0156] The user's terminal may be a mobile device such as a smartphone or tablet. The terminal may have a camera function that functions as a photographing means for photographing food packages. The terminal may also have a transmitting means for communicating with the server via an internet connection.

[0157] server

[0158] The server has the computing resources to receive and analyze the uploaded images. The specific software configuration is as follows:

[0159] Analysis method: Extract component information from images using optical character recognition (OCR) technology. Pytesseract is an effective technology to use.

[0160] Evaluation method: Health risks are evaluated based on extracted ingredient information. To determine the impact of specific ingredient amounts on the user's health, the information is compared with a database or pre-set reference values.

[0161] Generation method: Generate alerts and advice by taking into account the assessment results and the user's health status information. A generative AI model is used to generate easy-to-understand notification text in natural language.

[0162] Notification methods: Sending generated alerts and advice to the device, for example, as push notifications or in-app messages to the user.

[0163] Display method: Displays the evaluation results of the food the user is considering purchasing, allowing the user to check the health risks before purchasing.

[0164] Processing Flow

[0165] When a user takes a photo of a food package with their smartphone camera, the image is sent to a server. The server then uses OCR technology to convert the ingredient information in the image into text data. The server then analyzes this ingredient information and extracts detailed information about each ingredient in the food. An evaluation tool evaluates health risks based on this ingredient information and performs an individual risk assessment based on the user's profile information. For example, a user with high blood pressure is warned about foods with high sodium content.

[0166] The alerts and advice generated by the generating means are sent from the server to the user terminal and displayed on the user's terminal screen by the display means, allowing the user to quickly check the necessary information and make appropriate decisions.

[0167] Specific examples

[0168] For example, consider a scenario where a user is about to purchase some snacks. When the user takes a picture of the snack's packaging with the device's camera, the image is uploaded to the server. The server then uses OCR technology to extract the ingredient information from the image: "Sodium 500mg, Preservative 10mg, Coloring 5mg." The evaluation tool generates a specific alert for a user with high blood pressure: "This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake."

[0169] Example prompt sentence:

[0170] This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake.

[0171] The above is an embodiment of the present invention. The present invention allows users to easily and effectively select foods according to their own health condition, making it easier to manage their health in daily life.

[0172] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0173] Step 1:

[0174] The user takes a photo of a food package

[0175] Input: User device camera function, food package

[0176] How it works: A user uses their device's camera to take a picture of a food package.

[0177] Output: Captured image data

[0178] Step 2:

[0179] Upload the captured image to the server

[0180] Input: Captured image data, device's internet connection

[0181] Operation: The device sends the captured image data to a server via the Internet.

[0182] Output: Image data transferred to the server

[0183] Step 3:

[0184] The server analyzes the image and extracts ingredient information

[0185] Input: Image data stored on the server

[0186] How it works: The server uses OCR (Optical Character Recognition) technology to extract component information from the image as text data, for example using the pytesseract library for character recognition.

[0187] Output: Text data of extracted ingredient information

[0188] Step 4:

[0189] Evaluating health risks based on ingredient information

[0190] Input: Text data of extracted ingredient information, health risk assessment database on the server

[0191] How it works: The server evaluates the ingredient information and determines the health risk of each ingredient. It compares it with the safety standards based on the database and calculates the risk level.

[0192] Output: Health risk assessment results data

[0193] Step 5:

[0194] Generate alerts and advice taking into account the user's health status information

[0195] Input: Health risk assessment results data, user health profile information

[0196] How it works: The server generates alerts and advice based on a risk assessment, taking into account the user's health conditions (e.g., high blood pressure, diabetes, etc.), and uses a generative AI model to create appropriate notification text.

[0197] Output: Text data of generated alerts and advice

[0198] Step 6:

[0199] Notify users of generated alerts and advice

[0200] Input: Text data of generated alerts and advice, notification function of user terminal

[0201] What it does: Based on your settings, the server will send you alerts and advice via push notifications and in-app messages on your device.

[0202] Output: Alerts and advice displayed on the user's terminal

[0203] Step 7:

[0204] Display food evaluation results

[0205] Input: Alerts and advice sent to user terminals

[0206] How it works: The app on the device displays alerts and advice to the user, specifically displaying the rating results on the food selection screen before purchase.

[0207] Output: Evaluation results and advice displayed on the user's device screen

[0208] 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.

[0209] The present invention is a system that combines a system in which a user photographs a food package and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0210] Overall system configuration

[0211] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[0212] Program processing flow

[0213] Food photography and image uploading

[0214] 1. The user launches the application on the device and takes a photo of the food package. The device uses the camera function to capture the image and temporarily stores it in the internal memory.

[0215] 2. The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0216] Image analysis and component information acquisition

[0217] 3. The server waits for reception via the network and receives the image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0218] 4. The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data. The server saves the extracted ingredient information as text data.

[0219] 5. The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0220] Ingredient evaluation and sentiment analysis

[0221] 6. The server launches the evaluation tool based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0222] 7. The server acquires the user's profile information and evaluates health risks based on the component evaluation results. The server performs an individual risk assessment according to the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0223] 8. The server launches the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0224] Alert and advice generation and notifications

[0225] 9. The server uses a generation means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today."

[0226] 10. The server activates a notification means for transmitting the generated alert and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0227] Specific examples

[0228] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera, and the device uploads the image to a server. The server then analyzes the image using OCR technology to obtain the ingredient information.

[0229] The server then evaluates the snack based on the ingredient information, detecting that the snack contains a lot of sodium, and referring to the user's profile information, determining that the user has high blood pressure.

[0230] Furthermore, the emotion engine analyzes the user's facial expressions and tone of voice to determine that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[0231] The above is an embodiment of the present invention. The present invention allows a user to easily select foods that take into consideration not only their own health condition but also their emotional state at the time.

[0232] The processing flow will be explained below.

[0233] Step 1:

[0234] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0235] Step 2:

[0236] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0237] Step 3:

[0238] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0239] Step 4:

[0240] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0241] Step 5:

[0242] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0243] Step 6:

[0244] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0245] Step 7:

[0246] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0247] Step 8:

[0248] The server activates the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0249] Step 9:

[0250] The server uses a generating means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today to relieve stress."

[0251] Step 10:

[0252] The server activates a notification means for sending the generated alerts and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0253] Step 11:

[0254] Notify users of alerts and advice received by the device. The device displays messages in pop-ups on the screen or in the notification bar for easy viewing by the user.

[0255] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[0256] Example 2

[0257] 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."

[0258] Conventional food ingredient analysis systems were able to provide advice taking into account the user's health status information, but were unable to consider the user's emotional state. As a result, they were unable to provide flexible advice based on the user's stress and psychological state, and were unable to provide effective support in actual usage situations. In addition, individual health risk assessment based on the user's profile was limited, so a system that could provide more detailed advice was needed.

[0259] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for extracting food ingredient information using OCR technology, means for evaluating health risks based on the ingredient information, and means for analyzing the user's emotional state. This makes it possible to dynamically provide alerts and advice based on both the user's emotional state and health condition information.

[0260] "Photographing means" refers to a device or function that allows a user to photograph food packaging.

[0261] The "uploading means" is a device or function for transmitting captured images to a server.

[0262] The "analysis means" is a device or function that analyzes images on the server and obtains information about food ingredients.

[0263] "OCR technology" refers to optical character recognition technology, a technology for extracting text information from images.

[0264] The "evaluation means" is a device or function that performs an evaluation according to health risk based on the acquired component information.

[0265] A "generator" is a device or function for generating alerts and advice taking into account the user's health status information and emotional state.

[0266] The "means for analyzing emotional state" is a device or function for determining emotions by analyzing the user's facial expressions and tone of voice.

[0267] A "notification means" is a device or function for sending generated alerts and advice to a user.

[0268] The present invention is a system that combines a system in which a user photographs food packaging and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0269] Overall system configuration

[0270] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[0271] Photographing food packaging and uploading images

[0272] A user launches an application on their device and takes a picture of a food package. The device uses its camera function to capture the image and temporarily stores it in its internal memory. The device then establishes a network connection and uses an upload method to send the temporarily stored image to a server. This operation uses common network connection methods such as Wi-Fi or mobile data communication.

[0273] Receiving image data and acquiring component information

[0274] The server waits for reception via the network and receives the image data sent from the device. The received image data is stored in a buffer for analysis. The server then activates an analysis method using OCR technology to extract the text information of the ingredient list from the received image data. This operation uses OCR technology such as Adobe Sensei or Google Cloud Vision API. The extracted ingredient information is saved as text data.

[0275] Listing and evaluation of ingredient information

[0276] The server analyzes the text data and creates a list of ingredient information. The list includes specific ingredients such as preservatives, coloring agents, sodium, and phosphates, along with their amounts. The server then launches an evaluation tool based on the ingredient information list to assess the intake risk of each ingredient. This evaluation refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0277] User profile matching and sentiment analysis

[0278] The server acquires the user's profile information and compares it with the component evaluation results to assess health risks. It also references the user's health condition (e.g., high blood pressure, diabetes, allergies) to perform an individual risk assessment. The server then activates an emotion engine to analyze the user's emotional information while using the application. The emotion engine uses the device's camera and microphone to capture the user's facial expressions and tone of voice and determine their emotional state.

[0279] Alert and advice generation and notification

[0280] The server uses the generating means to integrate the ingredient evaluation results with the user's emotional state and generate an alert and advice. For example, if the user is under stress, a flexible alert message such as "This food has a high sodium content, but a small amount is acceptable today" can be created. The server activates the notification means to send the generated alert and advice to the device. The device sends a push notification or an in-app notification to the user, allowing the user to receive the message.

[0281] Specific examples

[0282] For example, consider a scenario where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to the server. The server analyzes the image using OCR technology and obtains ingredient information. The server evaluates the ingredient information and determines that the snack contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure. Additionally, the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack contains a high amount of sodium, but a small amount is acceptable today to help relieve stress."

[0283] Prompt Sentence Examples

[0284] "I took a photo of a snack package. What's in it?"

[0285] "This snack contains sodium, preservatives, and colorings."

[0286] The present invention allows users to easily select foods that take into account their own health condition and current emotional state.

[0287] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0288] Step 1:

[0289] The user launches the application on their device and takes a photo of the food package. Specifically, the user taps the "take a photo" button on the application to activate the camera function. The user then points the camera at the food package and presses the shutter button to capture the image.

[0290] Input: User taps the capture button and a food package captured on camera.

[0291] Output: Image data of food packaging stored in the device's temporary memory.

[0292] Step 2:

[0293] The device establishes a network connection to upload the temporarily stored image data to the server. Specifically, the device connects to the Internet via Wi-Fi or mobile data communication and sends the image data to the server.

[0294] Input: Temporarily saved image data, network connection.

[0295] Output: Image data sent to the server.

[0296] Step 3:

[0297] The server waits for reception via the network and receives the image data sent from the terminal. Specifically, the server listens for HTTP requests, receives the image data, and stores it in a buffer for analysis.

[0298] Input: Image data sent from the device.

[0299] Output: Image data stored in a buffer for analysis.

[0300] Step 4:

[0301] The server starts an analysis method using OCR technology and extracts the text information of the ingredient list from the received image data. Specifically, it analyzes the image using an OCR engine (e.g., Google Cloud Vision API) and obtains the text data.

[0302] Input: Image data stored in the analysis buffer.

[0303] Output: Text data of ingredient list.

[0304] Step 5:

[0305] The server analyzes the text data and creates a list of ingredient information. Specifically, it analyzes the text data using a string analysis algorithm, extracts each ingredient and its content, and adds it to the list.

[0306] Input: Text data of ingredient list obtained from the OCR engine.

[0307] Output: A list of ingredients.

[0308] Step 6:

[0309] The server launches an evaluation tool based on the ingredient information list to evaluate the intake risk of each ingredient. Specifically, it compares the ingredient information list with pre-set reference values ​​and databases to evaluate the health risk of each ingredient.

[0310] Input: List of ingredient information, reference value database.

[0311] Output: Intake risk assessment results for each ingredient.

[0312] Step 7:

[0313] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. Specifically, it refers to the user's health information (e.g., high blood pressure, diabetes, allergies) and performs an individual risk assessment.

[0314] Input: Ingredient evaluation results, user profile information.

[0315] Output: User-specific health risk assessment results.

[0316] Step 8:

[0317] The server activates the emotion engine and analyzes the user's emotional information while using the application. Specifically, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, which the emotion engine analyzes to determine the user's emotional state.

[0318] Input: Data captured from the device's camera and microphone.

[0319] Output: The user's emotional state.

[0320] Step 9:

[0321] The server uses a generating means to integrate the component evaluation result and the user's emotional state to generate alerts and advice, for example, if the user is in a stress state, a special flexible alert message is created.

[0322] Input: Ingredient assessment results, user health risk assessment results, user emotional state.

[0323] Output: Alert and advisory messages.

[0324] Step 10:

[0325] The server activates a notification means for transmitting the generated alerts and advice to the device, specifically, by sending a push notification or an in-app notification to the device so that the user can receive the message.

[0326] Input: Alert and advice messages, network connections.

[0327] Output: Alert and advice notifications sent to the terminal.

[0328] (Application example 2)

[0329] 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."

[0330] In recent years, interest in health has increased, and health management based on food ingredient information is becoming increasingly important. However, conventional systems simply provide ingredient information and are unable to provide advice that takes into account the user's health and emotional state, and therefore do not provide sufficient value to users. Another issue is that real-time advice is not available when selecting food in a physical store. For this reason, there is a need for a system that helps users make appropriate food choices.

[0331] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an imaging means for a user to photograph a food package, an uploading means for uploading the captured image to the server, an analysis means for analyzing the image in the server and acquiring ingredient information of the food, an evaluation means for making an assessment according to health risks based on the acquired ingredient information, a generation means for generating an alert and advice taking into account the user's health status information and emotional state information, a notification means for notifying the user of the generated alert and advice, and a user interface means for a user to operate the system using smart glasses or a head-mounted display in a physical store. This enables a user to make appropriate food selections based on their health status and emotional state in real time in a physical store.

[0332] The "photography means" refers to a device used by a user to photograph a food package, and is hardware that includes a camera function, such as a smartphone, smart glasses, or a head-mounted display.

[0333] "Uploading means" refers to a device or software that has the function of sending captured images to a server.

[0334] "Analysis means" refers to the technology used to analyze images on the server and extract information about food ingredients, and specifically includes OCR technology.

[0335] The "evaluation means" refers to a device or software that has the function of making an evaluation according to health risks based on the acquired component information.

[0336] A "generator" is a device or software that has the functionality to generate alerts and advice taking into account the user's health status information and emotional status information.

[0337] The "notification means" is a device or software that has a function for notifying the user of the generated alerts and advice.

[0338] "User interface means" refers to devices or software that have the functionality to allow users to operate the system in a physical store using smart glasses or a head-mounted display.

[0339] MODE FOR CARRYING OUT THE INVENTION

[0340] This invention combines an emotion engine with a system that allows a user to take a photo of a food package and analyze its ingredient information. An embodiment of this system will be described in detail below.

[0341] Overall system configuration

[0342] This system consists of a user's terminal, a server, an emotion engine, and a network connecting them. The terminal is equipped with a photographing means and an uploading means, while the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and an emotion engine. In addition, a user interface means is provided in the physical store, allowing users to operate the system using smart glasses or a head-mounted display.

[0343] Program processing flow

[0344] Hardware and Software

[0345] Hardware used:

[0346] Smartphones, smart glasses, head-mounted displays

[0347] Cameras, network connection devices

[0348] Software used:

[0349] OpenCV (camera control)

[0350] Pytesseract (OCR analysis)

[0351] EmotionRecognizer (emotion recognition engine)

[0352] Data calculation and processing

[0353] 1. Image capture:

[0354] The user captures an image of the food package using the camera on their device, such as a smartphone, smart glasses, or head-mounted display.

[0355] 2. Image upload:

[0356] The captured image is uploaded from the device to the server. At this time, a network connection is established and the image data is sent.

[0357] 3. Image Analysis:

[0358] The server uses OCR technology on the received image data to extract the text information from the ingredient list, using libraries such as Pytesseract.

[0359] 4. Ingredient information analysis and evaluation:

[0360] The extracted text information is analyzed and a list of ingredient information is compiled. Health risks are then assessed based on this ingredient information. The assessment method refers to pre-set standard values ​​and databases.

[0361] 5. Emotional State Analysis:

[0362] The server uses an emotion engine called EmotionRecognizer to analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[0363] 6. Advice Generation:

[0364] Based on the evaluated ingredient information and emotional state, personalized advice and alerts are generated. This is done by a generating means, which generates appropriate messages.

[0365] 7. Notice:

[0366] The generated advice is notified to the user by a notification means, which displays a message on the display of the smartphone or smart glasses.

[0367] Examples and prompts

[0368] For example, consider a case where a user picks up a snack and takes a photo of the packaging with the smart glasses' camera. The image is uploaded to a server, where the ingredient information is analyzed. The server detects that the snack has a high sodium content, and also analyzes that the user is currently experiencing stress. Based on this, a notification appears on the smart glasses' display saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[0369] Prompt Sentence Examples

[0370] "Create an application that allows a user to take a photo of a food package and extract ingredient information using OCR technology. The application evaluates the risk of the ingredients, analyzes the user's emotional state, and generates personalized health advice based on that."

[0371] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0372] Step 1:

[0373] The user takes a picture of a food package using the device's camera. The input is an image of the food package, which is captured and temporarily stored in the device's internal memory. The output is the temporarily stored image data.

[0374] Step 2:

[0375] The terminal establishes a network connection and uploads the captured image to the server. The input is temporarily saved image data that is sent to the server via the uploading means. The output is image data waiting to be received on the server side.

[0376] Step 3:

[0377] The server receives the image data and stores it in a buffer. The input is the image data sent from the terminal and stored in the buffer. The output is the image data stored in the server's buffer.

[0378] Step 4:

[0379] The server analyzes the image using OCR technology and extracts the component information. The input is the stored image data, and the component information is extracted as text data using OCR technology. The output is the extracted text data.

[0380] Step 5:

[0381] The server analyzes the extracted ingredient information and generates a list for each specific ingredient. The input is text data extracted using OCR technology, and an ingredient information list is created using an analysis method. The output is an ingredient information list.

[0382] Step 6:

[0383] The server performs a health risk assessment based on the ingredient information list. The input is the ingredient information list, and the risk assessment is performed using the assessment means. This involves reference to pre-set standard values ​​and health databases. The output is the health risk assessment results.

[0384] Step 7:

[0385] The server analyzes the user's emotional state. The input is the user's facial expression image or tone of voice, which is analyzed by the emotion engine. The output is the user's emotional state information.

[0386] Step 8:

[0387] The server integrates the component assessment results and emotional state information to generate personalized advice and alerts. The input is the health risk assessment results and emotional state information, and optimal advice and alerts are generated using a generation means. The output is the generated advice and alert messages.

[0388] Step 9:

[0389] The server sends the generated advice and alert to the terminal and notifies the user. The input is the generated advice and alert message, which is sent to the terminal using the notification means. The output is the advice and alert message displayed on the terminal.

[0390] The above are the specific processing steps of the system based on the application example. By clarifying what data is input and what output is obtained at each step, the operation of this system is easier to understand. In addition, the specific operation content of each step is added to explain the embodiment of the invention in detail.

[0391] 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.

[0392] 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.

[0393] 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.

[0394] [Second embodiment]

[0395] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0396] 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.

[0397] 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).

[0398] 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.

[0399] 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.

[0400] 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).

[0401] 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.

[0402] 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.

[0403] 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.

[0404] 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.

[0405] 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.

[0406] 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."

[0407] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0408] Overall system configuration

[0409] This system consists of a user's terminal, a server, and a network that connects them. The terminal is equipped with a means of taking pictures and uploading, and the server is equipped with a means of analyzing, evaluating, generating, and notifying.

[0410] Program processing flow

[0411] Food photography and image uploading

[0412] 1. The user launches the application on their device and takes a photo of the food package. The device uses the camera function to capture the image.

[0413] 2. The terminal automatically uploads the captured image to the server, and an uploading means transmits the image data to the server via a network connection.

[0414] Image analysis and component information acquisition

[0415] 3. The server receives the uploaded image. The analysis means uses OCR technology to convert the ingredient list in the image into text data.

[0416] 4. The server analyzes the converted text data and extracts information about the various ingredients contained in the food, such as preservatives, colorings, sodium, and phosphates.

[0417] Ingredient evaluation and alert generation

[0418] 5. The server evaluates the intake risk of each ingredient based on the extracted ingredient information. The evaluation tool refers to pre-set standard values ​​and databases to determine whether or not there is a health risk.

[0419] 6. Based on the user's profile information (e.g., high blood pressure, diabetes, anemia, etc.), an individual risk assessment is performed. The generator generates an appropriate alert message. For example, it generates a specific alert such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0420] Alert and advice notifications

[0421] 7. The server sends the generated alert or advice to the terminal. The notification means sends an alert message to the terminal, and the terminal notifies the user.

[0422] Specific examples

[0423] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera. The device uploads the image to the server, which then analyzes it using OCR technology to obtain the ingredient information.

[0424] The server then evaluates the snack based on this information and determines that it contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure.

[0425] Therefore, the server generates an alert to notify the user, saying, "This snack contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it." This notification is displayed on the device, allowing the user to reconsider the purchase or choose a different food item.

[0426] The above is an embodiment of the present invention. The present invention allows a user to easily select foods according to their own health condition.

[0427] The processing flow will be explained below.

[0428] Step 1:

[0429] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0430] Step 2:

[0431] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0432] Step 3:

[0433] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0434] Step 4:

[0435] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0436] Step 5:

[0437] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0438] Step 6:

[0439] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0440] Step 7:

[0441] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0442] Step 8:

[0443] The server uses the generation means to generate alerts and advice based on the ingredient evaluation results, for example, creating a specific alert message such as "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0444] Step 9:

[0445] The server activates a notification means for sending the generated alerts and advice to the terminal.The server sends an alert message to the terminal.

[0446] Step 10:

[0447] The device notifies the user of alerts and advice received from the server. The device displays messages in a pop-up on the screen or in the notification bar so that the user can easily check them.

[0448] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[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] Conventional food selection support systems are inefficient and require a lot of effort for users to select foods according to their health condition. Furthermore, extraction of ingredient information and health risk assessments are sometimes inaccurate, resulting in the provision of information that is not useful to users. Therefore, there is a need for a system that can provide highly accurate ingredient analysis according to the user's health condition and quickly provide appropriate alerts and advice.

[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 a photographing means for a user to photograph a food package, an uploading means for uploading the photographed image to the server, an analyzing means for analyzing the image in the server and obtaining ingredient information of the food, an evaluating means for making an assessment according to health risks based on the obtained ingredient information, a generating means for generating an alert and advice taking into account the user's health condition information, a notifying means for notifying the user of the generated alert and advice, an input means for inputting a prompt sentence to the generative AI model, and a generating AI means for performing ingredient analysis and health risk assessment using the generative AI model, thereby enabling users to efficiently and accurately select appropriate foods according to their health condition.

[0454] 1. The photographing means refers to a device or function that allows the user to photograph food packaging.

[0455] 2. Uploading means refers to the device or function for sending captured images to the server.

[0456] 3. Analysis means refers to the device or function that analyzes images on the server and obtains food ingredient information.

[0457] 4. Evaluation means refers to a device or function for making an assessment according to health risks based on the acquired ingredient information.

[0458] 5. Generating means refers to a device or function for generating alerts and advice taking into account the user's health status information.

[0459] 6. Notification means refers to a device or function for notifying the user of generated alerts and advice.

[0460] 7. Input means refers to a device or function for inputting prompt sentences into a generative AI model.

[0461] 8. Generative AI means refers to a device or function that uses a generative AI model to perform component analysis and health risk assessment.

[0462] 9. OCR technology refers to the technology that converts character information in an image into text data using optical character recognition technology.

[0463] 10. Profile information refers to information about a user's health status and individual health risks.

[0464] 11. Health risk refers to the potential danger that a particular ingredient poses to the user's health.

[0465] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0466] System configuration

[0467] This system consists of a user's device, a server, and a network connecting them. The device has a camera function and an upload function, while the server has analysis, evaluation, generation, and notification functions. The server also has a generative AI means for performing component analysis and health risk assessment using a generative AI model.

[0468] Hardware and software used

[0469] Devices: Mobile devices such as smartphones and tablets, with camera functions and network connectivity

[0470] Server: High-performance computer, database, OCR engine (e.g., Google Cloud Vision API), generative AI model (e.g., OpenAI GPT model)

[0471] Network: WiFi, mobile data

[0472] Program processing

[0473] Food photography and image uploading

[0474] 1. The user launches the application on their device and takes a picture of the food package. The user captures the image using the device's camera.

[0475] 2. The terminal automatically uploads the captured image to the server. The uploading means transmits the image data to the server.

[0476] Image analysis and component information acquisition

[0477] 3. The server receives the image and uses an analysis method (e.g., Google Cloud Vision API) to convert the character information in the ingredient list into text data using OCR technology.

[0478] 4. The server analyzes the text data and extracts information about the ingredients contained in the food.

[0479] Ingredient evaluation and alert generation

[0480] 5. The server uses the extracted ingredient information to evaluate the risk of intake by the assessment tool, referring to pre-existing standards and databases (e.g., USDA food database).

[0481] 6. The server performs an individual risk assessment based on the user's profile information. The generator generates appropriate alerts and advice based on the ingredient information and the user's health condition. For example, it generates a message such as, "This food contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it."

[0482] Alert and advice notifications

[0483] 7. The server sends the generated alert or advice to the terminal. The notification means sends a message to the terminal, and the terminal notifies the user.

[0484] Examples and prompts

[0485] Specifically, consider the case where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to a server. The server analyzes the image using OCR technology and obtains ingredient information. The server then evaluates the ingredient information and assesses risk by referencing the user's profile information. As a result, the server generates an alert for high sodium content and notifies the user.

[0486] As a concrete example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0487] "Please analyze the ingredients contained in this food and assess the health risks to users."

[0488] This system enables users to efficiently and accurately select foods appropriate for their health condition.

[0489] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0490] Step 1:

[0491] A user launches an application on their device and takes a picture of a food package. The user captures the image using the device's camera. The input is the image taken by the user, and the output is the image data stored on the device. The specific operation is that the user opens the app and taps the camera button to take a picture of the package.

[0492] Step 2:

[0493] Images captured by the device are automatically uploaded to the server. The input is image data stored on the device, and the output is image data sent to the server. The specific operation is that the device's upload function sends the image data to the server via the network the moment the image is saved.

[0494] Step 3:

[0495] The server receives the image and uses an analysis means to convert the character information in the image into text data using OCR technology. The input is the image data sent to the server, and the output is the converted text data. Specifically, the server processes the received request and extracts component information from the image using an OCR engine (e.g., Google Cloud Vision API).

[0496] Step 4:

[0497] The server analyzes the text data and extracts information about the ingredients contained in the food. The input is text data converted using OCR technology, and the output is the extracted ingredient information. Specifically, the server processes the text data and performs data calculations to generate an ingredient list.

[0498] Step 5:

[0499] The server uses the extracted ingredient information to evaluate the risk of intake. The input is ingredient information, and the output is the risk assessment result. Specifically, the server evaluates the risk of each ingredient by referencing standard values ​​and databases (e.g., the USDA food database).

[0500] Step 6:

[0501] The server performs an individual risk assessment based on the user's profile information. The input is the risk assessment result and the user's profile information, and the output is a risk assessment result specific to the user. Specifically, the server collates the user's health information and performs an individual risk assessment.

[0502] Step 7:

[0503] The server's generation means generates appropriate alerts and advice. The input is the risk assessment result, and the output is the generated alert message. Specifically, the server uses the generative AI model to generate a message such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0504] Step 8:

[0505] The server sends the generated alerts and advice to the terminal. The input is the generated alert message, and the output is the alert message sent to the terminal. The specific operation is that the notification means of the server delivers the generated message to the terminal.

[0506] Step 9:

[0507] The device receives the notification and displays it to the user. The input is the alert message sent from the server, and the output is the alert message displayed to the user. The specific behavior is that when the device receives a notification, it displays the alert message in the app or notification bar.

[0508] (Application example 1)

[0509] 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."

[0510] Conventional food selection methods require users to manually check the ingredient information of foods and determine whether they are suitable for their health condition. This method is very time-consuming and inconvenient, especially for users who lead busy lives. Furthermore, users who are not familiar with food ingredients may not be able to accurately judge the health impact of ingredient information. There is a need for a system that solves this problem and allows users to more easily and effectively manage health risks when purchasing food.

[0511] 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.

[0512] In this invention, the server includes a photographing means for a user to photograph a food package, a transmission means for uploading the photographed image to the server, an analysis means for analyzing the image in the server and obtaining ingredient information of the food, an evaluation means for making an evaluation according to health risks based on the obtained ingredient information, a generation means for generating an alert and advice taking into account the user's health condition information, a notification means for notifying the user of the generated alert and advice, and a display means for displaying the evaluation results of the food the user is considering purchasing. This allows a user to receive appropriate advice and risk assessment based on their own health condition simply by photographing the food package, making food selection easy and quick.

[0513] "Photographing means" refers to a device or function that allows a user to photograph a food package.

[0514] "Transmission means" is a function for uploading the captured video to a server.

[0515] The "analysis means" is a function for analyzing video on the server and obtaining information on food ingredients.

[0516] The "evaluation means" is a function that performs an evaluation according to health risk based on the acquired component information.

[0517] The "generation means" is a function for generating alerts and advice in consideration of the user's health condition information.

[0518] The "notification means" is a function for notifying the user of the generated alerts and advice.

[0519] The "display means" is a function for displaying the evaluation results of the food that the user is considering purchasing.

[0520] The present invention is directed to a system that allows a user to photograph a food package and analyze its ingredient information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail preferred embodiments of the present invention.

[0521] First, this system consists of a user terminal, a server, and a network connecting them. The terminal is equipped with a photographing means and a transmission means, and the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and a display means.

[0522] Hardware and Software

[0523] Terminal

[0524] The user's terminal may be a mobile device such as a smartphone or tablet. The terminal may have a camera function that functions as a photographing means for photographing food packages. The terminal may also have a transmitting means for communicating with the server via an internet connection.

[0525] server

[0526] The server has the computing resources to receive and analyze the uploaded images. The specific software configuration is as follows:

[0527] Analysis method: Extract component information from images using optical character recognition (OCR) technology. Pytesseract is an effective technology to use.

[0528] Evaluation method: Health risks are evaluated based on extracted ingredient information. To determine the impact of specific ingredient amounts on the user's health, the information is compared with a database or pre-set reference values.

[0529] Generation method: Generate alerts and advice by taking into account the assessment results and the user's health status information. A generative AI model is used to generate easy-to-understand notification text in natural language.

[0530] Notification methods: Sending generated alerts and advice to the device, for example, as push notifications or in-app messages to the user.

[0531] Display method: Displays the evaluation results of the food the user is considering purchasing, allowing the user to check the health risks before purchasing.

[0532] Processing Flow

[0533] When a user takes a photo of a food package with their smartphone camera, the image is sent to a server. The server then uses OCR technology to convert the ingredient information in the image into text data. The server then analyzes this ingredient information and extracts detailed information about each ingredient in the food. An evaluation tool evaluates health risks based on this ingredient information and performs an individual risk assessment based on the user's profile information. For example, a user with high blood pressure is warned about foods with high sodium content.

[0534] The alerts and advice generated by the generating means are sent from the server to the user terminal and displayed on the user's terminal screen by the display means, allowing the user to quickly check the necessary information and make appropriate decisions.

[0535] Specific examples

[0536] For example, consider a scenario where a user is about to purchase some snacks. When the user takes a picture of the snack's packaging with the device's camera, the image is uploaded to the server. The server then uses OCR technology to extract the ingredient information from the image: "Sodium 500mg, Preservative 10mg, Coloring 5mg." The evaluation tool generates a specific alert for a user with high blood pressure: "This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake."

[0537] Example prompt sentence:

[0538] This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake.

[0539] The above is an embodiment of the present invention. The present invention allows users to easily and effectively select foods according to their own health condition, making it easier to manage their health in daily life.

[0540] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0541] Step 1:

[0542] The user takes a photo of a food package

[0543] Input: User device camera function, food package

[0544] How it works: A user uses their device's camera to take a picture of a food package.

[0545] Output: Captured image data

[0546] Step 2:

[0547] Upload the captured image to the server

[0548] Input: Captured image data, device's internet connection

[0549] Operation: The device sends the captured image data to a server via the Internet.

[0550] Output: Image data transferred to the server

[0551] Step 3:

[0552] The server analyzes the image and extracts ingredient information

[0553] Input: Image data stored on the server

[0554] How it works: The server uses OCR (Optical Character Recognition) technology to extract component information from the image as text data, for example using the pytesseract library for character recognition.

[0555] Output: Text data of extracted ingredient information

[0556] Step 4:

[0557] Evaluating health risks based on ingredient information

[0558] Input: Text data of extracted ingredient information, health risk assessment database on the server

[0559] How it works: The server evaluates the ingredient information and determines the health risk of each ingredient. It compares it with the safety standards based on the database and calculates the risk level.

[0560] Output: Health risk assessment results data

[0561] Step 5:

[0562] Generate alerts and advice taking into account the user's health status information

[0563] Input: Health risk assessment results data, user health profile information

[0564] How it works: The server generates alerts and advice based on a risk assessment, taking into account the user's health conditions (e.g., high blood pressure, diabetes, etc.), and uses a generative AI model to create appropriate notification text.

[0565] Output: Text data of generated alerts and advice

[0566] Step 6:

[0567] Notify users of generated alerts and advice

[0568] Input: Text data of generated alerts and advice, notification function of user terminal

[0569] What it does: Based on your settings, the server will send you alerts and advice via push notifications and in-app messages on your device.

[0570] Output: Alerts and advice displayed on the user's terminal

[0571] Step 7:

[0572] Display food evaluation results

[0573] Input: Alerts and advice sent to user terminals

[0574] How it works: The app on the device displays alerts and advice to the user, specifically displaying the rating results on the food selection screen before purchase.

[0575] Output: Evaluation results and advice displayed on the user's device screen

[0576] 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.

[0577] The present invention is a system that combines a system in which a user photographs a food package and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0578] Overall system configuration

[0579] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[0580] Program processing flow

[0581] Food photography and image uploading

[0582] 1. The user launches the application on the device and takes a photo of the food package. The device uses the camera function to capture the image and temporarily stores it in the internal memory.

[0583] 2. The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0584] Image analysis and component information acquisition

[0585] 3. The server waits for reception via the network and receives the image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0586] 4. The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data. The server saves the extracted ingredient information as text data.

[0587] 5. The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0588] Ingredient evaluation and sentiment analysis

[0589] 6. The server launches the evaluation tool based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0590] 7. The server acquires the user's profile information and evaluates health risks based on the component evaluation results. The server performs an individual risk assessment according to the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0591] 8. The server launches the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0592] Alert and advice generation and notifications

[0593] 9. The server uses a generation means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today."

[0594] 10. The server activates a notification means for transmitting the generated alert and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0595] Specific examples

[0596] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera, and the device uploads the image to a server. The server then analyzes the image using OCR technology to obtain the ingredient information.

[0597] The server then evaluates the snack based on the ingredient information, detecting that the snack contains a lot of sodium, and referring to the user's profile information, determining that the user has high blood pressure.

[0598] Furthermore, the emotion engine analyzes the user's facial expressions and tone of voice to determine that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[0599] The above is an embodiment of the present invention. The present invention allows a user to easily select foods that take into consideration not only their own health condition but also their emotional state at the time.

[0600] The processing flow will be explained below.

[0601] Step 1:

[0602] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0603] Step 2:

[0604] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0605] Step 3:

[0606] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0607] Step 4:

[0608] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0609] Step 5:

[0610] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0611] Step 6:

[0612] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0613] Step 7:

[0614] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0615] Step 8:

[0616] The server activates the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0617] Step 9:

[0618] The server uses a generating means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today to relieve stress."

[0619] Step 10:

[0620] The server activates a notification means for sending the generated alerts and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0621] Step 11:

[0622] Notify users of alerts and advice received by the device. The device displays messages in pop-ups on the screen or in the notification bar for easy viewing by the user.

[0623] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[0624] Example 2

[0625] 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."

[0626] Conventional food ingredient analysis systems were able to provide advice taking into account the user's health status information, but were unable to consider the user's emotional state. As a result, they were unable to provide flexible advice based on the user's stress and psychological state, and were unable to provide effective support in actual usage situations. In addition, individual health risk assessment based on the user's profile was limited, so a system that could provide more detailed advice was needed.

[0627] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for extracting food ingredient information using OCR technology, means for evaluating health risks based on the ingredient information, and means for analyzing the user's emotional state. This makes it possible to dynamically provide alerts and advice based on both the user's emotional state and health condition information.

[0628] "Photographing means" refers to a device or function that allows a user to photograph food packaging.

[0629] The "uploading means" is a device or function for transmitting captured images to a server.

[0630] The "analysis means" is a device or function that analyzes images on the server and obtains information about food ingredients.

[0631] "OCR technology" refers to optical character recognition technology, a technology for extracting text information from images.

[0632] The "evaluation means" is a device or function that performs an evaluation according to health risk based on the acquired component information.

[0633] A "generator" is a device or function for generating alerts and advice taking into account the user's health status information and emotional state.

[0634] The "means for analyzing emotional state" is a device or function for determining emotions by analyzing the user's facial expressions and tone of voice.

[0635] A "notification means" is a device or function for sending generated alerts and advice to a user.

[0636] The present invention is a system that combines a system in which a user photographs food packaging and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0637] Overall system configuration

[0638] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[0639] Photographing food packaging and uploading images

[0640] A user launches an application on their device and takes a picture of a food package. The device uses its camera function to capture the image and temporarily stores it in its internal memory. The device then establishes a network connection and uses an upload method to send the temporarily stored image to a server. This operation uses common network connection methods such as Wi-Fi or mobile data communication.

[0641] Receiving image data and acquiring component information

[0642] The server waits for reception via the network and receives the image data sent from the device. The received image data is stored in a buffer for analysis. The server then activates an analysis method using OCR technology to extract the text information of the ingredient list from the received image data. This operation uses OCR technology such as Adobe Sensei or Google Cloud Vision API. The extracted ingredient information is saved as text data.

[0643] Listing and evaluation of ingredient information

[0644] The server analyzes the text data and creates a list of ingredient information. The list includes specific ingredients such as preservatives, coloring agents, sodium, and phosphates, along with their amounts. The server then launches an evaluation tool based on the ingredient information list to assess the intake risk of each ingredient. This evaluation refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0645] User profile matching and sentiment analysis

[0646] The server acquires the user's profile information and compares it with the component evaluation results to assess health risks. It also references the user's health condition (e.g., high blood pressure, diabetes, allergies) to perform an individual risk assessment. The server then activates an emotion engine to analyze the user's emotional information while using the application. The emotion engine uses the device's camera and microphone to capture the user's facial expressions and tone of voice and determine their emotional state.

[0647] Alert and advice generation and notification

[0648] The server uses the generating means to integrate the ingredient evaluation results with the user's emotional state and generate an alert and advice. For example, if the user is under stress, a flexible alert message such as "This food has a high sodium content, but a small amount is acceptable today" can be created. The server activates the notification means to send the generated alert and advice to the device. The device sends a push notification or an in-app notification to the user, allowing the user to receive the message.

[0649] Specific examples

[0650] For example, consider a scenario where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to the server. The server analyzes the image using OCR technology and obtains ingredient information. The server evaluates the ingredient information and determines that the snack contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure. Additionally, the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack contains a high amount of sodium, but a small amount is acceptable today to help relieve stress."

[0651] Prompt Sentence Examples

[0652] "I took a photo of a snack package. What's in it?"

[0653] "This snack contains sodium, preservatives, and colorings."

[0654] The present invention allows users to easily select foods that take into account their own health condition and current emotional state.

[0655] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0656] Step 1:

[0657] The user launches the application on their device and takes a photo of the food package. Specifically, the user taps the "take a photo" button on the application to activate the camera function. The user then points the camera at the food package and presses the shutter button to capture the image.

[0658] Input: User taps the capture button and a food package captured on camera.

[0659] Output: Image data of food packaging stored in the device's temporary memory.

[0660] Step 2:

[0661] The device establishes a network connection to upload the temporarily stored image data to the server. Specifically, the device connects to the Internet via Wi-Fi or mobile data communication and sends the image data to the server.

[0662] Input: Temporarily saved image data, network connection.

[0663] Output: Image data sent to the server.

[0664] Step 3:

[0665] The server waits for reception via the network and receives the image data sent from the terminal. Specifically, the server listens for HTTP requests, receives the image data, and stores it in a buffer for analysis.

[0666] Input: Image data sent from the device.

[0667] Output: Image data stored in a buffer for analysis.

[0668] Step 4:

[0669] The server starts an analysis method using OCR technology and extracts the text information of the ingredient list from the received image data. Specifically, it analyzes the image using an OCR engine (e.g., Google Cloud Vision API) and obtains the text data.

[0670] Input: Image data stored in the analysis buffer.

[0671] Output: Text data of ingredient list.

[0672] Step 5:

[0673] The server analyzes the text data and creates a list of ingredient information. Specifically, it analyzes the text data using a string analysis algorithm, extracts each ingredient and its content, and adds it to the list.

[0674] Input: Text data of ingredient list obtained from the OCR engine.

[0675] Output: A list of ingredients.

[0676] Step 6:

[0677] The server launches an evaluation tool based on the ingredient information list to evaluate the intake risk of each ingredient. Specifically, it compares the ingredient information list with pre-set reference values ​​and databases to evaluate the health risk of each ingredient.

[0678] Input: List of ingredient information, reference value database.

[0679] Output: Intake risk assessment results for each ingredient.

[0680] Step 7:

[0681] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. Specifically, it refers to the user's health information (e.g., high blood pressure, diabetes, allergies) and performs an individual risk assessment.

[0682] Input: Ingredient evaluation results, user profile information.

[0683] Output: User-specific health risk assessment results.

[0684] Step 8:

[0685] The server activates the emotion engine and analyzes the user's emotional information while using the application. Specifically, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, which the emotion engine analyzes to determine the user's emotional state.

[0686] Input: Data captured from the device's camera and microphone.

[0687] Output: The user's emotional state.

[0688] Step 9:

[0689] The server uses a generating means to integrate the component evaluation result and the user's emotional state to generate alerts and advice, for example, if the user is in a stress state, a special flexible alert message is created.

[0690] Input: Ingredient assessment results, user health risk assessment results, user emotional state.

[0691] Output: Alert and advisory messages.

[0692] Step 10:

[0693] The server activates a notification means for transmitting the generated alerts and advice to the device, specifically, by sending a push notification or an in-app notification to the device so that the user can receive the message.

[0694] Input: Alert and advice messages, network connections.

[0695] Output: Alert and advice notifications sent to the terminal.

[0696] (Application example 2)

[0697] 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."

[0698] In recent years, interest in health has increased, and health management based on food ingredient information is becoming increasingly important. However, conventional systems simply provide ingredient information and are unable to provide advice that takes into account the user's health and emotional state, and therefore do not provide sufficient value to users. Another issue is that real-time advice is not available when selecting food in a physical store. For this reason, there is a need for a system that helps users make appropriate food choices.

[0699] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an imaging means for a user to photograph a food package, an uploading means for uploading the captured image to the server, an analysis means for analyzing the image in the server and acquiring ingredient information of the food, an evaluation means for making an assessment according to health risks based on the acquired ingredient information, a generation means for generating an alert and advice taking into account the user's health status information and emotional state information, a notification means for notifying the user of the generated alert and advice, and a user interface means for a user to operate the system using smart glasses or a head-mounted display in a physical store. This enables a user to make appropriate food selections based on their health status and emotional state in real time in a physical store.

[0700] The "photography means" refers to a device used by a user to photograph a food package, and is hardware that includes a camera function, such as a smartphone, smart glasses, or a head-mounted display.

[0701] "Uploading means" refers to a device or software that has the function of sending captured images to a server.

[0702] "Analysis means" refers to the technology used to analyze images on the server and extract information about food ingredients, and specifically includes OCR technology.

[0703] The "evaluation means" refers to a device or software that has the function of making an evaluation according to health risks based on the acquired component information.

[0704] A "generator" is a device or software that has the functionality to generate alerts and advice taking into account the user's health status information and emotional status information.

[0705] The "notification means" is a device or software that has a function for notifying the user of the generated alerts and advice.

[0706] "User interface means" refers to devices or software that have the functionality to allow users to operate the system in a physical store using smart glasses or a head-mounted display.

[0707] MODE FOR CARRYING OUT THE INVENTION

[0708] This invention combines an emotion engine with a system that allows a user to take a photo of a food package and analyze its ingredient information. An embodiment of this system will be described in detail below.

[0709] Overall system configuration

[0710] This system consists of a user's terminal, a server, an emotion engine, and a network connecting them. The terminal is equipped with a photographing means and an uploading means, while the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and an emotion engine. In addition, a user interface means is provided in the physical store, allowing users to operate the system using smart glasses or a head-mounted display.

[0711] Program processing flow

[0712] Hardware and Software

[0713] Hardware used:

[0714] Smartphones, smart glasses, head-mounted displays

[0715] Cameras, network connection devices

[0716] Software used:

[0717] OpenCV (camera control)

[0718] Pytesseract (OCR analysis)

[0719] EmotionRecognizer (emotion recognition engine)

[0720] Data calculation and processing

[0721] 1. Image capture:

[0722] The user captures an image of the food package using the camera on their device, such as a smartphone, smart glasses, or head-mounted display.

[0723] 2. Image upload:

[0724] The captured image is uploaded from the device to the server. At this time, a network connection is established and the image data is sent.

[0725] 3. Image Analysis:

[0726] The server uses OCR technology on the received image data to extract the text information from the ingredient list, using libraries such as Pytesseract.

[0727] 4. Ingredient information analysis and evaluation:

[0728] The extracted text information is analyzed and a list of ingredient information is compiled. Health risks are then assessed based on this ingredient information. The assessment method refers to pre-set standard values ​​and databases.

[0729] 5. Emotional State Analysis:

[0730] The server uses an emotion engine called EmotionRecognizer to analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[0731] 6. Advice Generation:

[0732] Based on the evaluated ingredient information and emotional state, personalized advice and alerts are generated. This is done by a generating means, which generates appropriate messages.

[0733] 7. Notice:

[0734] The generated advice is notified to the user by a notification means, which displays a message on the display of the smartphone or smart glasses.

[0735] Examples and prompts

[0736] For example, consider a case where a user picks up a snack and takes a photo of the packaging with the smart glasses' camera. The image is uploaded to a server, where the ingredient information is analyzed. The server detects that the snack has a high sodium content, and also analyzes that the user is currently experiencing stress. Based on this, a notification appears on the smart glasses' display saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[0737] Prompt Sentence Examples

[0738] "Create an application that allows a user to take a photo of a food package and extract ingredient information using OCR technology. The application evaluates the risk of the ingredients, analyzes the user's emotional state, and generates personalized health advice based on that."

[0739] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0740] Step 1:

[0741] The user takes a picture of a food package using the device's camera. The input is an image of the food package, which is captured and temporarily stored in the device's internal memory. The output is the temporarily stored image data.

[0742] Step 2:

[0743] The terminal establishes a network connection and uploads the captured image to the server. The input is temporarily saved image data that is sent to the server via the uploading means. The output is image data waiting to be received on the server side.

[0744] Step 3:

[0745] The server receives the image data and stores it in a buffer. The input is the image data sent from the terminal and stored in the buffer. The output is the image data stored in the server's buffer.

[0746] Step 4:

[0747] The server analyzes the image using OCR technology and extracts the component information. The input is the stored image data, and the component information is extracted as text data using OCR technology. The output is the extracted text data.

[0748] Step 5:

[0749] The server analyzes the extracted ingredient information and generates a list for each specific ingredient. The input is text data extracted using OCR technology, and an ingredient information list is created using an analysis method. The output is an ingredient information list.

[0750] Step 6:

[0751] The server performs a health risk assessment based on the ingredient information list. The input is the ingredient information list, and the risk assessment is performed using the assessment means. This involves reference to pre-set standard values ​​and health databases. The output is the health risk assessment results.

[0752] Step 7:

[0753] The server analyzes the user's emotional state. The input is the user's facial expression image or tone of voice, which is analyzed by the emotion engine. The output is the user's emotional state information.

[0754] Step 8:

[0755] The server integrates the component assessment results and emotional state information to generate personalized advice and alerts. The input is the health risk assessment results and emotional state information, and optimal advice and alerts are generated using a generation means. The output is the generated advice and alert messages.

[0756] Step 9:

[0757] The server sends the generated advice and alert to the terminal and notifies the user. The input is the generated advice and alert message, which is sent to the terminal using the notification means. The output is the advice and alert message displayed on the terminal.

[0758] The above are the specific processing steps of the system based on the application example. By clarifying what data is input and what output is obtained at each step, the operation of this system is easier to understand. In addition, the specific operation content of each step is added to explain the embodiment of the invention in detail.

[0759] 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.

[0760] 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.

[0761] 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.

[0762] [Third embodiment]

[0763] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0764] 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.

[0765] 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).

[0766] 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.

[0767] 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.

[0768] 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).

[0769] 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.

[0770] 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.

[0771] 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.

[0772] 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.

[0773] 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.

[0774] 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."

[0775] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0776] Overall system configuration

[0777] This system consists of a user's terminal, a server, and a network that connects them. The terminal is equipped with a means of taking pictures and uploading, and the server is equipped with a means of analyzing, evaluating, generating, and notifying.

[0778] Program processing flow

[0779] Food photography and image uploading

[0780] 1. The user launches the application on their device and takes a photo of the food package. The device uses the camera function to capture the image.

[0781] 2. The terminal automatically uploads the captured image to the server, and the uploading means transmits the image data to the server via a network connection.

[0782] Image analysis and component information acquisition

[0783] 3. The server receives the uploaded image. The analysis means uses OCR technology to convert the ingredient list in the image into text data.

[0784] 4. The server analyzes the converted text data and extracts information about the various ingredients contained in the food, such as preservatives, colorings, sodium, and phosphates.

[0785] Ingredient evaluation and alert generation

[0786] 5. The server evaluates the intake risk of each ingredient based on the extracted ingredient information. The evaluation tool refers to pre-set standard values ​​and databases to determine whether or not there is a health risk.

[0787] 6. Based on the user's profile information (e.g., high blood pressure, diabetes, anemia, etc.), an individual risk assessment is performed. The generator generates an appropriate alert message. For example, it generates a specific alert such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0788] Alert and advice notifications

[0789] 7. The server sends the generated alert or advice to the terminal. The notification means sends an alert message to the terminal, and the terminal notifies the user.

[0790] Specific examples

[0791] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera. The device uploads the image to the server, which then analyzes it using OCR technology to obtain the ingredient information.

[0792] The server then evaluates the snack based on this information and determines that it contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure.

[0793] Therefore, the server generates an alert to notify the user, saying, "This snack contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it." This notification is displayed on the device, allowing the user to reconsider the purchase or choose a different food item.

[0794] The above is an embodiment of the present invention. The present invention allows a user to easily select foods according to their own health condition.

[0795] The processing flow will be explained below.

[0796] Step 1:

[0797] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0798] Step 2:

[0799] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0800] Step 3:

[0801] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0802] Step 4:

[0803] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0804] Step 5:

[0805] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0806] Step 6:

[0807] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0808] Step 7:

[0809] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0810] Step 8:

[0811] The server uses the generation means to generate alerts and advice based on the ingredient evaluation results, for example, creating a specific alert message such as "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0812] Step 9:

[0813] The server activates a notification means for sending the generated alerts and advice to the terminal.The server sends an alert message to the terminal.

[0814] Step 10:

[0815] The device notifies the user of alerts and advice received from the server. The device displays messages in a pop-up on the screen or in the notification bar so that the user can easily check them.

[0816] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[0817] Example 1

[0818] 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."

[0819] Conventional food selection support systems are inefficient and require a lot of effort for users to select foods according to their health condition. Furthermore, extraction of ingredient information and health risk assessments are sometimes inaccurate, resulting in the provision of information that is not useful to users. Therefore, there is a need for a system that can provide highly accurate ingredient analysis according to the user's health condition and quickly provide appropriate alerts and advice.

[0820] 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.

[0821] In this invention, the server includes a photographing means for a user to photograph a food package, an uploading means for uploading the photographed image to the server, an analyzing means for analyzing the image in the server and obtaining ingredient information of the food, an evaluating means for making an assessment according to health risks based on the obtained ingredient information, a generating means for generating an alert and advice taking into account the user's health condition information, a notifying means for notifying the user of the generated alert and advice, an input means for inputting a prompt sentence to the generative AI model, and a generating AI means for performing ingredient analysis and health risk assessment using the generative AI model, thereby enabling users to efficiently and accurately select appropriate foods according to their health condition.

[0822] 1. The photographing means refers to a device or function that allows the user to photograph food packaging.

[0823] 2. Uploading means refers to the device or function for sending captured images to the server.

[0824] 3. Analysis means refers to the device or function that analyzes images on the server and obtains food ingredient information.

[0825] 4. Evaluation means refers to a device or function for making an assessment according to health risks based on the acquired ingredient information.

[0826] 5. Generating means refers to a device or function for generating alerts and advice taking into account the user's health status information.

[0827] 6. Notification means refers to a device or function for notifying the user of generated alerts and advice.

[0828] 7. Input means refers to a device or function for inputting prompt sentences into a generative AI model.

[0829] 8. Generative AI means refers to a device or function that uses a generative AI model to perform component analysis and health risk assessment.

[0830] 9. OCR technology refers to the technology that converts character information in an image into text data using optical character recognition technology.

[0831] 10. Profile information refers to information about a user's health status and individual health risks.

[0832] 11. Health risk refers to the potential danger that a particular ingredient poses to the user's health.

[0833] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[0834] System configuration

[0835] This system consists of a user's device, a server, and a network connecting them. The device has a camera function and an upload function, while the server has analysis, evaluation, generation, and notification functions. The server also has a generative AI means for performing component analysis and health risk assessment using a generative AI model.

[0836] Hardware and software used

[0837] Devices: Mobile devices such as smartphones and tablets, with camera functions and network connectivity

[0838] Server: High-performance computer, database, OCR engine (e.g., Google Cloud Vision API), generative AI model (e.g., OpenAI GPT model)

[0839] Network: WiFi, mobile data

[0840] Program processing

[0841] Food photography and image uploading

[0842] 1. The user launches the application on their device and takes a picture of the food package. The user captures the image using the device's camera.

[0843] 2. The terminal automatically uploads the captured image to the server. The uploading means transmits the image data to the server.

[0844] Image analysis and component information acquisition

[0845] 3. The server receives the image and uses an analysis method (e.g., Google Cloud Vision API) to convert the character information in the ingredient list into text data using OCR technology.

[0846] 4. The server analyzes the text data and extracts information about the ingredients contained in the food.

[0847] Ingredient evaluation and alert generation

[0848] 5. The server uses the extracted ingredient information to evaluate the risk of intake by the assessment tool, referring to pre-existing standards and databases (e.g., USDA food database).

[0849] 6. The server performs an individual risk assessment based on the user's profile information. The generator generates appropriate alerts and advice based on the ingredient information and the user's health condition. For example, it generates a message such as, "This food contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it."

[0850] Alert and advice notifications

[0851] 7. The server sends the generated alert or advice to the terminal. The notification means sends a message to the terminal, and the terminal notifies the user.

[0852] Examples and prompts

[0853] Specifically, consider the case where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to a server. The server analyzes the image using OCR technology and obtains ingredient information. The server then evaluates the ingredient information and assesses risk by referencing the user's profile information. As a result, the server generates an alert for high sodium content and notifies the user.

[0854] As a concrete example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[0855] "Please analyze the ingredients contained in this food and assess the health risks to users."

[0856] This system enables users to efficiently and accurately select foods appropriate for their health condition.

[0857] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0858] Step 1:

[0859] A user launches an application on their device and takes a picture of a food package. The user captures the image using the device's camera. The input is the image taken by the user, and the output is the image data stored on the device. The specific operation is that the user opens the app and taps the camera button to take a picture of the package.

[0860] Step 2:

[0861] Images captured by the device are automatically uploaded to the server. The input is image data stored on the device, and the output is image data sent to the server. The specific operation is that the device's upload function sends the image data to the server via the network the moment the image is saved.

[0862] Step 3:

[0863] The server receives the image and uses an analysis means to convert the character information in the image into text data using OCR technology. The input is the image data sent to the server, and the output is the converted text data. Specifically, the server processes the received request and extracts component information from the image using an OCR engine (e.g., Google Cloud Vision API).

[0864] Step 4:

[0865] The server analyzes the text data and extracts information about the ingredients contained in the food. The input is text data converted using OCR technology, and the output is the extracted ingredient information. Specifically, the server processes the text data and performs data calculations to generate an ingredient list.

[0866] Step 5:

[0867] The server uses the extracted ingredient information to evaluate the risk of intake. The input is ingredient information, and the output is the risk assessment result. Specifically, the server evaluates the risk of each ingredient by referencing standard values ​​and databases (e.g., the USDA food database).

[0868] Step 6:

[0869] The server performs an individual risk assessment based on the user's profile information. The input is the risk assessment result and the user's profile information, and the output is a risk assessment result specific to the user. Specifically, the server collates the user's health information and performs an individual risk assessment.

[0870] Step 7:

[0871] The server's generation means generates appropriate alerts and advice. The input is the risk assessment result, and the output is the generated alert message. Specifically, the server uses the generative AI model to generate a message such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[0872] Step 8:

[0873] The server sends the generated alerts and advice to the terminal. The input is the generated alert message, and the output is the alert message sent to the terminal. The specific operation is that the notification means of the server delivers the generated message to the terminal.

[0874] Step 9:

[0875] The device receives the notification and displays it to the user. The input is the alert message sent from the server, and the output is the alert message displayed to the user. The specific behavior is that when the device receives a notification, it displays the alert message in the app or notification bar.

[0876] (Application example 1)

[0877] 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."

[0878] Conventional food selection methods require users to manually check the ingredient information of foods and determine whether they are suitable for their health condition. This method is very time-consuming and inconvenient, especially for users who lead busy lives. Furthermore, users who are not familiar with food ingredients may not be able to accurately judge the health impact of ingredient information. There is a need for a system that solves this problem and allows users to more easily and effectively manage health risks when purchasing food.

[0879] 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.

[0880] In this invention, the server includes a photographing means for a user to photograph a food package, a transmission means for uploading the photographed image to the server, an analysis means for analyzing the image in the server and obtaining ingredient information of the food, an evaluation means for making an evaluation according to health risks based on the obtained ingredient information, a generation means for generating an alert and advice taking into account the user's health condition information, a notification means for notifying the user of the generated alert and advice, and a display means for displaying the evaluation results of the food the user is considering purchasing. This allows a user to receive appropriate advice and risk assessment based on their own health condition simply by photographing the food package, making food selection easy and quick.

[0881] "Photographing means" refers to a device or function that allows a user to photograph a food package.

[0882] "Transmission means" is a function for uploading the captured video to a server.

[0883] The "analysis means" is a function for analyzing video on the server and obtaining information on food ingredients.

[0884] The "evaluation means" is a function that performs an evaluation according to health risk based on the acquired component information.

[0885] The "generation means" is a function for generating alerts and advice in consideration of the user's health condition information.

[0886] The "notification means" is a function for notifying the user of the generated alerts and advice.

[0887] The "display means" is a function for displaying the evaluation results of the food that the user is considering purchasing.

[0888] The present invention is directed to a system that allows a user to photograph a food package and analyze its ingredient information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail preferred embodiments of the present invention.

[0889] First, this system consists of a user terminal, a server, and a network connecting them. The terminal is equipped with a photographing means and a transmission means, and the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and a display means.

[0890] Hardware and Software

[0891] Terminal

[0892] The user's terminal may be a mobile device such as a smartphone or tablet. The terminal may have a camera function that functions as a photographing means for photographing food packages. The terminal may also have a transmitting means for communicating with the server via an internet connection.

[0893] server

[0894] The server has the computing resources to receive and analyze the uploaded images. The specific software configuration is as follows:

[0895] Analysis method: Extract component information from images using optical character recognition (OCR) technology. Pytesseract is an effective technology to use.

[0896] Evaluation method: Health risks are evaluated based on extracted ingredient information. To determine the impact of specific ingredient amounts on the user's health, the information is compared with a database or pre-set reference values.

[0897] Generation method: Generate alerts and advice by taking into account the assessment results and the user's health status information. A generative AI model is used to generate easy-to-understand notification text in natural language.

[0898] Notification methods: Sending generated alerts and advice to the device, for example, as push notifications or in-app messages to the user.

[0899] Display method: Displays the evaluation results of the food the user is considering purchasing, allowing the user to check the health risks before purchasing.

[0900] Processing Flow

[0901] When a user takes a photo of a food package with their smartphone camera, the image is sent to a server. The server then uses OCR technology to convert the ingredient information in the image into text data. The server then analyzes this ingredient information and extracts detailed information about each ingredient in the food. An evaluation tool evaluates health risks based on this ingredient information and performs an individual risk assessment based on the user's profile information. For example, a user with high blood pressure is warned about foods with high sodium content.

[0902] The alerts and advice generated by the generating means are sent from the server to the user terminal and displayed on the user's terminal screen by the display means, allowing the user to quickly check the necessary information and make appropriate decisions.

[0903] Specific examples

[0904] For example, consider a scenario where a user is about to purchase some snacks. When the user takes a picture of the snack's packaging with the device's camera, the image is uploaded to the server. The server then uses OCR technology to extract the ingredient information from the image: "Sodium 500mg, Preservative 10mg, Coloring 5mg." The evaluation tool generates a specific alert for a user with high blood pressure: "This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake."

[0905] Example prompt sentence:

[0906] This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake.

[0907] The above is an embodiment of the present invention. The present invention allows users to easily and effectively select foods according to their own health condition, making it easier to manage their health in daily life.

[0908] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0909] Step 1:

[0910] The user takes a photo of a food package

[0911] Input: User device camera function, food package

[0912] How it works: A user uses their device's camera to take a picture of a food package.

[0913] Output: Captured image data

[0914] Step 2:

[0915] Upload the captured image to the server

[0916] Input: Captured image data, device's internet connection

[0917] Operation: The device sends the captured image data to a server via the Internet.

[0918] Output: Image data transferred to the server

[0919] Step 3:

[0920] The server analyzes the image and extracts ingredient information

[0921] Input: Image data stored on the server

[0922] How it works: The server uses OCR (Optical Character Recognition) technology to extract component information from the image as text data, for example using the pytesseract library for character recognition.

[0923] Output: Text data of extracted ingredient information

[0924] Step 4:

[0925] Evaluating health risks based on ingredient information

[0926] Input: Text data of extracted ingredient information, health risk assessment database on the server

[0927] How it works: The server evaluates the ingredient information and determines the health risk of each ingredient. It compares it with the safety standards based on the database and calculates the risk level.

[0928] Output: Health risk assessment results data

[0929] Step 5:

[0930] Generate alerts and advice taking into account the user's health status information

[0931] Input: Health risk assessment results data, user health profile information

[0932] How it works: The server takes into account the user's health conditions (e.g., high blood pressure, diabetes, etc.) and generates alerts and advice based on a risk assessment. It uses a generative AI model to create appropriate notification text.

[0933] Output: Text data of generated alerts and advice

[0934] Step 6:

[0935] Notify users of generated alerts and advice

[0936] Input: Text data of generated alerts and advice, notification function of user terminal

[0937] What it does: Based on your settings, the server will send you alerts and advice via push notifications and in-app messages on your device.

[0938] Output: Alerts and advice displayed on the user's terminal

[0939] Step 7:

[0940] Display food evaluation results

[0941] Input: Alerts and advice sent to user terminals

[0942] How it works: The app on the device displays alerts and advice to the user, specifically displaying the rating results on the food selection screen before purchase.

[0943] Output: Evaluation results and advice displayed on the user's device screen

[0944] 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.

[0945] The present invention is a system that combines a system in which a user photographs a food package and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[0946] Overall system configuration

[0947] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[0948] Program processing flow

[0949] Food photography and image uploading

[0950] 1. The user launches the application on the device and takes a photo of the food package. The device uses the camera function to capture the image and temporarily stores it in the internal memory.

[0951] 2. The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0952] Image analysis and component information acquisition

[0953] 3. The server waits for reception via the network and receives the image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0954] 4. The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data. The server saves the extracted ingredient information as text data.

[0955] 5. The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0956] Ingredient evaluation and sentiment analysis

[0957] 6. The server launches the evaluation tool based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0958] 7. The server acquires the user's profile information and evaluates health risks based on the component evaluation results. The server performs an individual risk assessment according to the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0959] 8. The server launches the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0960] Alert and advice generation and notifications

[0961] 9. The server uses a generation means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today."

[0962] 10. The server activates a notification means for transmitting the generated alert and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0963] Specific examples

[0964] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera, and the device uploads the image to a server. The server then analyzes the image using OCR technology to obtain the ingredient information.

[0965] The server then evaluates the snack based on the ingredient information, detecting that the snack contains a lot of sodium, and referring to the user's profile information, determining that the user has high blood pressure.

[0966] Furthermore, the emotion engine analyzes the user's facial expressions and tone of voice to determine that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[0967] The above is an embodiment of the present invention. The present invention allows a user to easily select foods that take into consideration not only their own health condition but also their emotional state at the time.

[0968] The processing flow will be explained below.

[0969] Step 1:

[0970] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[0971] Step 2:

[0972] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[0973] Step 3:

[0974] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[0975] Step 4:

[0976] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[0977] Step 5:

[0978] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[0979] Step 6:

[0980] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[0981] Step 7:

[0982] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[0983] Step 8:

[0984] The server activates the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[0985] Step 9:

[0986] The server uses a generating means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today to relieve stress."

[0987] Step 10:

[0988] The server activates a notification means for sending the generated alerts and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[0989] Step 11:

[0990] Notify users of alerts and advice received by the device. The device displays messages in pop-ups on the screen or in the notification bar for easy viewing by the user.

[0991] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[0992] Example 2

[0993] 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."

[0994] Conventional food ingredient analysis systems were able to provide advice taking into account the user's health status information, but were unable to consider the user's emotional state. As a result, they were unable to provide flexible advice based on the user's stress and psychological state, and were unable to provide effective support in actual usage situations. In addition, individual health risk assessment based on the user's profile was limited, so a system that could provide more detailed advice was needed.

[0995] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for extracting food ingredient information using OCR technology, means for evaluating health risks based on the ingredient information, and means for analyzing the user's emotional state. This makes it possible to dynamically provide alerts and advice based on both the user's emotional state and health condition information.

[0996] "Photographing means" refers to a device or function that allows a user to photograph food packaging.

[0997] The "uploading means" is a device or function for transmitting captured images to a server.

[0998] The "analysis means" is a device or function that analyzes images on the server and obtains information about food ingredients.

[0999] "OCR technology" refers to optical character recognition technology, a technology for extracting text information from images.

[1000] The "evaluation means" is a device or function that performs an evaluation according to health risk based on the acquired component information.

[1001] A "generator" is a device or function for generating alerts and advice taking into account the user's health status information and emotional state.

[1002] The "means for analyzing emotional state" is a device or function for determining emotions by analyzing the user's facial expressions and tone of voice.

[1003] A "notification means" is a device or function for sending generated alerts and advice to a user.

[1004] The present invention is a system that combines a system in which a user photographs food packaging and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[1005] Overall system configuration

[1006] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[1007] Photographing food packaging and uploading images

[1008] A user launches an application on their device and takes a picture of a food package. The device uses its camera function to capture the image and temporarily stores it in its internal memory. The device then establishes a network connection and uses an upload method to send the temporarily stored image to a server. This operation uses common network connection methods such as Wi-Fi or mobile data communication.

[1009] Receiving image data and acquiring component information

[1010] The server waits for reception via the network and receives the image data sent from the device. The received image data is stored in a buffer for analysis. The server then activates an analysis method using OCR technology to extract the text information of the ingredient list from the received image data. This operation uses OCR technology such as Adobe Sensei or Google Cloud Vision API. The extracted ingredient information is saved as text data.

[1011] Listing and evaluation of ingredient information

[1012] The server analyzes the text data and creates a list of ingredient information. The list includes specific ingredients such as preservatives, coloring agents, sodium, and phosphates, along with their amounts. The server then launches an evaluation tool based on the ingredient information list to assess the intake risk of each ingredient. This evaluation refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[1013] User profile matching and sentiment analysis

[1014] The server acquires the user's profile information and compares it with the component evaluation results to assess health risks. It also references the user's health condition (e.g., high blood pressure, diabetes, allergies) to perform an individual risk assessment. The server then activates an emotion engine to analyze the user's emotional information while using the application. The emotion engine uses the device's camera and microphone to capture the user's facial expressions and tone of voice and determine their emotional state.

[1015] Alert and advice generation and notification

[1016] The server uses the generation means to integrate the ingredient evaluation results with the user's emotional state and generate an alert and advice. For example, if the user is in a stressful state, a flexible alert message such as "This food has a high sodium content, but a special small amount is acceptable today" can be created. The server activates the notification means to send the generated alert and advice to the terminal. The terminal sends a push notification or an in-app notification to the user, allowing the user to receive the message.

[1017] Specific examples

[1018] For example, consider a scenario where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to the server. The server analyzes the image using OCR technology and obtains ingredient information. The server evaluates the ingredient information and determines that the snack contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure. Additionally, the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack contains a high amount of sodium, but a small amount is acceptable today to help relieve stress."

[1019] Prompt Sentence Examples

[1020] "I took a photo of a snack package. What's in it?"

[1021] "This snack contains sodium, preservatives, and colorings."

[1022] The present invention allows users to easily select foods that take into account their own health condition and current emotional state.

[1023] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1024] Step 1:

[1025] The user launches the application on their device and takes a photo of the food package. Specifically, the user taps the "take a photo" button on the application to activate the camera function. The user then points the camera at the food package and presses the shutter button to capture the image.

[1026] Input: User taps the capture button and a food package captured on camera.

[1027] Output: Image data of food packaging stored in the device's temporary memory.

[1028] Step 2:

[1029] The device establishes a network connection to upload the temporarily stored image data to the server. Specifically, the device connects to the Internet via Wi-Fi or mobile data communication and sends the image data to the server.

[1030] Input: Temporarily saved image data, network connection.

[1031] Output: Image data sent to the server.

[1032] Step 3:

[1033] The server waits for reception via the network and receives the image data sent from the terminal. Specifically, the server listens for HTTP requests, receives the image data, and stores it in a buffer for analysis.

[1034] Input: Image data sent from the device.

[1035] Output: Image data stored in a buffer for analysis.

[1036] Step 4:

[1037] The server starts an analysis method using OCR technology and extracts the text information of the ingredient list from the received image data. Specifically, it analyzes the image using an OCR engine (e.g., Google Cloud Vision API) and obtains the text data.

[1038] Input: Image data stored in the analysis buffer.

[1039] Output: Text data of ingredient list.

[1040] Step 5:

[1041] The server analyzes the text data and creates a list of ingredient information. Specifically, it analyzes the text data using a string analysis algorithm, extracts each ingredient and its content, and adds it to the list.

[1042] Input: Text data of ingredient list obtained from the OCR engine.

[1043] Output: A list of ingredients.

[1044] Step 6:

[1045] The server launches an evaluation tool based on the ingredient information list to evaluate the intake risk of each ingredient. Specifically, it compares the ingredient information list with pre-set reference values ​​and databases to evaluate the health risk of each ingredient.

[1046] Input: List of ingredient information, reference value database.

[1047] Output: Intake risk assessment results for each ingredient.

[1048] Step 7:

[1049] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. Specifically, it refers to the user's health information (e.g., high blood pressure, diabetes, allergies) and performs an individual risk assessment.

[1050] Input: Ingredient evaluation results, user profile information.

[1051] Output: User-specific health risk assessment results.

[1052] Step 8:

[1053] The server activates the emotion engine and analyzes the user's emotional information while using the application. Specifically, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, which the emotion engine analyzes to determine the user's emotional state.

[1054] Input: Data captured from the device's camera and microphone.

[1055] Output: The user's emotional state.

[1056] Step 9:

[1057] The server uses a generating means to integrate the component evaluation result and the user's emotional state to generate alerts and advice, for example, if the user is in a stress state, a special flexible alert message is created.

[1058] Input: Ingredient assessment results, user health risk assessment results, user emotional state.

[1059] Output: Alert and advisory messages.

[1060] Step 10:

[1061] The server activates a notification means for transmitting the generated alerts and advice to the device, specifically, by sending a push notification or an in-app notification to the device so that the user can receive the message.

[1062] Input: Alert and advice messages, network connections.

[1063] Output: Alert and advice notifications sent to the terminal.

[1064] (Application example 2)

[1065] 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."

[1066] In recent years, interest in health has increased, and health management based on food ingredient information is becoming increasingly important. However, conventional systems simply provide ingredient information and are unable to provide advice that takes into account the user's health and emotional state, and therefore do not provide sufficient value to users. Another issue is that real-time advice is not available when selecting food in a physical store. For this reason, there is a need for a system that helps users make appropriate food choices.

[1067] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an imaging means for a user to photograph a food package, an uploading means for uploading the captured image to the server, an analysis means for analyzing the image in the server and acquiring ingredient information of the food, an evaluation means for making an assessment according to health risks based on the acquired ingredient information, a generation means for generating an alert and advice taking into account the user's health status information and emotional state information, a notification means for notifying the user of the generated alert and advice, and a user interface means for a user to operate the system using smart glasses or a head-mounted display in a physical store. This enables a user to make appropriate food selections based on their health status and emotional state in real time in a physical store.

[1068] The "photography means" refers to a device used by a user to photograph a food package, and is hardware that includes a camera function, such as a smartphone, smart glasses, or a head-mounted display.

[1069] "Uploading means" refers to a device or software that has the function of sending captured images to a server.

[1070] "Analysis means" refers to the technology used to analyze images on the server and extract information about food ingredients, and specifically includes OCR technology.

[1071] The "evaluation means" refers to a device or software that has the function of making an evaluation according to health risks based on the acquired component information.

[1072] A "generator" is a device or software that has the functionality to generate alerts and advice taking into account the user's health and emotional state information.

[1073] The "notification means" is a device or software that has a function for notifying the user of the generated alerts and advice.

[1074] "User interface means" refers to devices or software that have the functionality to allow users to operate the system in a physical store using smart glasses or a head-mounted display.

[1075] MODE FOR CARRYING OUT THE INVENTION

[1076] This invention combines an emotion engine with a system that allows a user to take a photo of a food package and analyze its ingredient information. An embodiment of this system will be described in detail below.

[1077] Overall system configuration

[1078] This system consists of a user's terminal, a server, an emotion engine, and a network connecting them. The terminal is equipped with a photographing means and an uploading means, while the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and an emotion engine. In addition, a user interface means is provided in the physical store, allowing users to operate the system using smart glasses or a head-mounted display.

[1079] Program processing flow

[1080] Hardware and Software

[1081] Hardware used:

[1082] Smartphones, smart glasses, head-mounted displays

[1083] Cameras, network connection devices

[1084] Software used:

[1085] OpenCV (camera control)

[1086] Pytesseract (OCR analysis)

[1087] EmotionRecognizer (emotion recognition engine)

[1088] Data calculation and processing

[1089] 1. Image capture:

[1090] The user captures an image of the food package using the camera on their device, such as a smartphone, smart glasses, or head-mounted display.

[1091] 2. Image upload:

[1092] The captured image is uploaded from the device to the server. At this time, a network connection is established and the image data is sent.

[1093] 3. Image Analysis:

[1094] The server uses OCR technology on the received image data to extract the text information from the ingredient list, using libraries such as Pytesseract.

[1095] 4. Ingredient information analysis and evaluation:

[1096] The extracted text information is analyzed and a list of ingredient information is compiled. Health risks are then assessed based on this ingredient information. The assessment method refers to pre-set standard values ​​and databases.

[1097] 5. Emotional State Analysis:

[1098] The server uses an emotion engine called EmotionRecognizer to analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[1099] 6. Advice Generation:

[1100] Based on the evaluated ingredient information and emotional state, personalized advice and alerts are generated. This is done by a generating means, which generates appropriate messages.

[1101] 7. Notice:

[1102] The generated advice is notified to the user by a notification means, which displays a message on the display of the smartphone or smart glasses.

[1103] Examples and prompts

[1104] For example, consider a case where a user picks up a snack and takes a photo of the packaging with the smart glasses' camera. The image is uploaded to a server, where the ingredient information is analyzed. The server detects that the snack has a high sodium content, and also analyzes that the user is currently experiencing stress. Based on this, a notification appears on the smart glasses' display saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[1105] Prompt Sentence Examples

[1106] "Create an application that allows a user to take a photo of a food package and extract ingredient information using OCR technology. The application evaluates the risk of the ingredients, analyzes the user's emotional state, and generates personalized health advice based on that."

[1107] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1108] Step 1:

[1109] The user takes a picture of a food package using the device's camera. The input is an image of the food package, which is captured and temporarily stored in the device's internal memory. The output is the temporarily stored image data.

[1110] Step 2:

[1111] The terminal establishes a network connection and uploads the captured image to the server. The input is temporarily saved image data that is sent to the server via the uploading means. The output is image data waiting to be received on the server side.

[1112] Step 3:

[1113] The server receives the image data and stores it in a buffer. The input is the image data sent from the terminal and stored in the buffer. The output is the image data stored in the server's buffer.

[1114] Step 4:

[1115] The server analyzes the image using OCR technology and extracts the component information. The input is the stored image data, and the component information is extracted as text data using OCR technology. The output is the extracted text data.

[1116] Step 5:

[1117] The server analyzes the extracted ingredient information and generates a list for each specific ingredient. The input is text data extracted using OCR technology, and an ingredient information list is created using an analysis method. The output is an ingredient information list.

[1118] Step 6:

[1119] The server performs a health risk assessment based on the ingredient information list. The input is the ingredient information list, and the risk assessment is performed using the assessment means. This involves reference to pre-set standard values ​​and health databases. The output is the health risk assessment results.

[1120] Step 7:

[1121] The server analyzes the user's emotional state. The input is the user's facial expression image or tone of voice, which is analyzed by the emotion engine. The output is the user's emotional state information.

[1122] Step 8:

[1123] The server integrates the component assessment results and emotional state information to generate personalized advice and alerts. The input is the health risk assessment results and emotional state information, and optimal advice and alerts are generated using a generation means. The output is the generated advice and alert messages.

[1124] Step 9:

[1125] The server sends the generated advice and alert to the terminal and notifies the user. The input is the generated advice and alert message, which is sent to the terminal using the notification means. The output is the advice and alert message displayed on the terminal.

[1126] The above are the specific processing steps of the system based on the application example. By clarifying what data is input and what output is obtained at each step, the operation of this system is easier to understand. In addition, the specific operation content of each step is added to explain the embodiment of the invention in detail.

[1127] 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.

[1128] 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.

[1129] 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.

[1130] [Fourth embodiment]

[1131] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1132] 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.

[1133] 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).

[1134] 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.

[1135] 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.

[1136] 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).

[1137] 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.

[1138] 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.

[1139] 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.

[1140] 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.

[1141] 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.

[1142] 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.

[1143] 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."

[1144] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[1145] Overall system configuration

[1146] This system consists of a user's terminal, a server, and a network that connects them. The terminal is equipped with a means of taking pictures and uploading, and the server is equipped with a means of analyzing, evaluating, generating, and notifying.

[1147] Program processing flow

[1148] Food photography and image uploading

[1149] 1. The user launches the application on their device and takes a photo of the food package. The device uses the camera function to capture the image.

[1150] 2. The terminal automatically uploads the captured image to the server, and the uploading means transmits the image data to the server via a network connection.

[1151] Image analysis and component information acquisition

[1152] 3. The server receives the uploaded image. The analysis means uses OCR technology to convert the ingredient list in the image into text data.

[1153] 4. The server analyzes the converted text data and extracts information about the various ingredients contained in the food, such as preservatives, colorings, sodium, and phosphates.

[1154] Ingredient evaluation and alert generation

[1155] 5. The server evaluates the intake risk of each ingredient based on the extracted ingredient information. The evaluation tool refers to pre-set standard values ​​and databases to determine whether or not there is a health risk.

[1156] 6. Based on the user's profile information (e.g., high blood pressure, diabetes, anemia, etc.), an individual risk assessment is performed. The generator generates an appropriate alert message. For example, it generates a specific alert such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[1157] Alert and advice notifications

[1158] 7. The server sends the generated alert or advice to the terminal. The notification means sends an alert message to the terminal, and the terminal notifies the user.

[1159] Specific examples

[1160] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera. The device uploads the image to the server, which then analyzes it using OCR technology to obtain the ingredient information.

[1161] The server then evaluates the snack based on this information and determines that it contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure.

[1162] Therefore, the server generates an alert to notify the user, saying, "This snack contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it." This notification is displayed on the device, allowing the user to reconsider the purchase or choose a different food item.

[1163] The above is an embodiment of the present invention. The present invention allows a user to easily select foods according to their own health condition.

[1164] The processing flow will be explained below.

[1165] Step 1:

[1166] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[1167] Step 2:

[1168] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[1169] Step 3:

[1170] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[1171] Step 4:

[1172] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[1173] Step 5:

[1174] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[1175] Step 6:

[1176] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[1177] Step 7:

[1178] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[1179] Step 8:

[1180] The server uses the generation means to generate alerts and advice based on the ingredient evaluation results, for example, creating a specific alert message such as "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[1181] Step 9:

[1182] The server activates a notification means for sending the generated alerts and advice to the terminal.The server sends an alert message to the terminal.

[1183] Step 10:

[1184] The device notifies the user of alerts and advice received from the server. The device displays messages in a pop-up on the screen or in the notification bar so that the user can easily check them.

[1185] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[1186] Example 1

[1187] 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."

[1188] Conventional food selection support systems are inefficient and require a lot of effort for users to select foods according to their health condition. Furthermore, extraction of ingredient information and health risk assessments are sometimes inaccurate, resulting in the provision of information that is not useful to users. Therefore, there is a need for a system that can provide highly accurate ingredient analysis according to the user's health condition and quickly provide appropriate alerts and advice.

[1189] 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.

[1190] In this invention, the server includes a photographing means for a user to photograph a food package, an uploading means for uploading the photographed image to the server, an analyzing means for analyzing the image in the server and obtaining ingredient information of the food, an evaluating means for making an assessment according to health risks based on the obtained ingredient information, a generating means for generating an alert and advice taking into account the user's health condition information, a notifying means for notifying the user of the generated alert and advice, an input means for inputting a prompt sentence to the generative AI model, and a generating AI means for performing ingredient analysis and health risk assessment using the generative AI model, thereby enabling users to efficiently and accurately select appropriate foods according to their health condition.

[1191] 1. The photographing means refers to a device or function that allows the user to photograph food packaging.

[1192] 2. Uploading means refers to the device or function for sending captured images to the server.

[1193] 3. Analysis means refers to the device or function that analyzes images on the server and obtains food ingredient information.

[1194] 4. Evaluation means refers to a device or function for making an assessment according to health risks based on the acquired ingredient information.

[1195] 5. Generating means refers to a device or function for generating alerts and advice taking into account the user's health status information.

[1196] 6. Notification means refers to a device or function for notifying the user of generated alerts and advice.

[1197] 7. Input means refers to a device or function for inputting prompt sentences into a generative AI model.

[1198] 8. Generative AI means refers to a device or function that uses a generative AI model to perform component analysis and health risk assessment.

[1199] 9. OCR technology refers to the technology that converts character information in an image into text data using optical character recognition technology.

[1200] 10. Profile information refers to information about a user's health status and individual health risks.

[1201] 11. Health risk refers to the potential danger that a particular ingredient poses to the user's health.

[1202] The present invention is a system that allows a user to photograph a food package and analyze its ingredient information. An embodiment of the system will be specifically described below.

[1203] System configuration

[1204] This system consists of a user's device, a server, and a network connecting them. The device has a camera function and an upload function, while the server has analysis, evaluation, generation, and notification functions. The server also has a generative AI means for performing component analysis and health risk assessment using a generative AI model.

[1205] Hardware and software used

[1206] Devices: Mobile devices such as smartphones and tablets, with camera functions and network connectivity

[1207] Server: High-performance computer, database, OCR engine (e.g., Google Cloud Vision API), generative AI model (e.g., OpenAI GPT model)

[1208] Network: WiFi, mobile data

[1209] Program processing

[1210] Food photography and image uploading

[1211] 1. The user launches the application on their device and takes a picture of the food package. The user captures the image using the device's camera.

[1212] 2. The terminal automatically uploads the captured image to the server. The uploading means transmits the image data to the server.

[1213] Image analysis and component information acquisition

[1214] 3. The server receives the image and uses an analysis method (e.g., Google Cloud Vision API) to convert the character information in the ingredient list into text data using OCR technology.

[1215] 4. The server analyzes the text data and extracts information about the ingredients contained in the food.

[1216] Ingredient evaluation and alert generation

[1217] 5. The server uses the extracted ingredient information to evaluate the risk of intake by the assessment tool, referring to pre-existing standards and databases (e.g., USDA food database).

[1218] 6. The server performs an individual risk assessment based on the user's profile information. The generator generates appropriate alerts and advice based on the ingredient information and the user's health condition. For example, it generates a message such as, "This food contains a high amount of sodium. People with high blood pressure are advised to avoid consuming it."

[1219] Alert and advice notifications

[1220] 7. The server sends the generated alert or advice to the terminal. The notification means sends a message to the terminal, and the terminal notifies the user.

[1221] Examples and prompts

[1222] Specifically, consider the case where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to a server. The server analyzes the image using OCR technology and obtains ingredient information. The server then evaluates the ingredient information and assesses risk by referencing the user's profile information. As a result, the server generates an alert for high sodium content and notifies the user.

[1223] As a concrete example of a prompt sentence, the following prompt sentence can be input to the generative AI model:

[1224] "Please analyze the ingredients contained in this food and assess the health risks to users."

[1225] This system enables users to efficiently and accurately select foods appropriate for their health condition.

[1226] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1227] Step 1:

[1228] A user launches an application on their device and takes a picture of a food package. The user captures the image using the device's camera. The input is the image taken by the user, and the output is the image data stored on the device. The specific operation is that the user opens the app and taps the camera button to take a picture of the package.

[1229] Step 2:

[1230] Images captured by the device are automatically uploaded to the server. The input is image data stored on the device, and the output is image data sent to the server. The specific operation is that the device's upload function sends the image data to the server via the network the moment the image is saved.

[1231] Step 3:

[1232] The server receives the image and uses an analysis means to convert the character information in the image into text data using OCR technology. The input is the image data sent to the server, and the output is the converted text data. Specifically, the server processes the received request and extracts component information from the image using an OCR engine (e.g., Google Cloud Vision API).

[1233] Step 4:

[1234] The server analyzes the text data and extracts information about the ingredients contained in the food. The input is text data converted using OCR technology, and the output is the extracted ingredient information. Specifically, the server processes the text data and performs data calculations to generate an ingredient list.

[1235] Step 5:

[1236] The server uses the extracted ingredient information to evaluate the risk of intake. The input is ingredient information, and the output is the risk assessment result. Specifically, the server evaluates the risk of each ingredient by referencing standard values ​​and databases (e.g., the USDA food database).

[1237] Step 6:

[1238] The server performs an individual risk assessment based on the user's profile information. The input is the risk assessment result and the user's profile information, and the output is a risk assessment result specific to the user. Specifically, the server collates the user's health information and performs an individual risk assessment.

[1239] Step 7:

[1240] The server's generation means generates appropriate alerts and advice. The input is the risk assessment result, and the output is the generated alert message. Specifically, the server uses the generative AI model to generate a message such as, "This food has a high sodium content. People with high blood pressure are advised to avoid consuming it."

[1241] Step 8:

[1242] The server sends the generated alerts and advice to the terminal. The input is the generated alert message, and the output is the alert message sent to the terminal. The specific operation is that the notification means of the server delivers the generated message to the terminal.

[1243] Step 9:

[1244] The device receives the notification and displays it to the user. The input is the alert message sent from the server, and the output is the alert message displayed to the user. The specific behavior is that when the device receives a notification, it displays the alert message in the app or notification bar.

[1245] (Application example 1)

[1246] 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."

[1247] Conventional food selection methods require users to manually check the ingredient information of foods and determine whether they are suitable for their health condition. This method is very time-consuming and inconvenient, especially for users who lead busy lives. Furthermore, users who are not familiar with food ingredients may not be able to accurately judge the health impact of ingredient information. There is a need for a system that solves this problem and allows users to more easily and effectively manage health risks when purchasing food.

[1248] 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.

[1249] In this invention, the server includes a photographing means for a user to photograph a food package, a transmission means for uploading the photographed image to the server, an analysis means for analyzing the image in the server and obtaining ingredient information of the food, an evaluation means for making an evaluation according to health risks based on the obtained ingredient information, a generation means for generating an alert and advice taking into account the user's health condition information, a notification means for notifying the user of the generated alert and advice, and a display means for displaying the evaluation results of the food the user is considering purchasing. This allows a user to receive appropriate advice and risk assessment based on their own health condition simply by photographing the food package, making food selection easy and quick.

[1250] "Photographing means" refers to a device or function that allows a user to photograph a food package.

[1251] "Transmission means" is a function for uploading the captured video to a server.

[1252] The "analysis means" is a function for analyzing video on the server and obtaining information on food ingredients.

[1253] The "evaluation means" is a function that performs an evaluation according to health risk based on the acquired component information.

[1254] The "generation means" is a function for generating alerts and advice in consideration of the user's health condition information.

[1255] The "notification means" is a function for notifying the user of the generated alerts and advice.

[1256] The "display means" is a function for displaying the evaluation results of the food that the user is considering purchasing.

[1257] The present invention is directed to a system that allows a user to photograph a food package and analyze its ingredient information. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The following describes in detail preferred embodiments of the present invention.

[1258] First, this system consists of a user terminal, a server, and a network connecting them. The terminal is equipped with a photographing means and a transmission means, and the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and a display means.

[1259] Hardware and Software

[1260] Terminal

[1261] The user's terminal may be a mobile device such as a smartphone or tablet. The terminal may have a camera function that functions as a photographing means for photographing food packages. The terminal may also have a transmitting means for communicating with the server via an internet connection.

[1262] server

[1263] The server has the computing resources to receive and analyze the uploaded images. The specific software configuration is as follows:

[1264] Analysis method: Extract component information from images using optical character recognition (OCR) technology. Pytesseract is an effective technology to use.

[1265] Evaluation method: Health risks are evaluated based on extracted ingredient information. To determine the impact of specific ingredient amounts on the user's health, the information is compared with a database or pre-set reference values.

[1266] Generation method: Generate alerts and advice by taking into account the assessment results and the user's health status information. A generative AI model is used to generate easy-to-understand notification text in natural language.

[1267] Notification methods: Sending generated alerts and advice to the device, for example, as push notifications or in-app messages to the user.

[1268] Display method: Displays the evaluation results of the food the user is considering purchasing, allowing the user to check the health risks before purchasing.

[1269] Processing Flow

[1270] When a user takes a photo of a food package with their smartphone camera, the image is sent to a server. The server then uses OCR technology to convert the ingredient information in the image into text data. The server then analyzes this ingredient information and extracts detailed information about each ingredient in the food. An evaluation tool evaluates health risks based on this ingredient information and performs an individual risk assessment based on the user's profile information. For example, a user with high blood pressure is warned about foods with high sodium content.

[1271] The alerts and advice generated by the generating means are sent from the server to the user terminal and displayed on the user's terminal screen by the display means, allowing the user to quickly check the necessary information and make appropriate decisions.

[1272] Specific examples

[1273] For example, consider a scenario where a user is about to purchase some snacks. When the user takes a picture of the snack's packaging with the device's camera, the image is uploaded to the server. The server then uses OCR technology to extract the ingredient information from the image: "Sodium 500mg, Preservative 10mg, Coloring 5mg." The evaluation tool generates a specific alert for a user with high blood pressure: "This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake."

[1274] Example prompt sentence:

[1275] This food contains 500mg of sodium. People with high blood pressure are advised to limit their intake.

[1276] The above is an embodiment of the present invention. The present invention allows users to easily and effectively select foods according to their own health condition, making it easier to manage their health in daily life.

[1277] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1278] Step 1:

[1279] The user takes a photo of a food package

[1280] Input: User device camera function, food package

[1281] How it works: A user uses their device's camera to take a picture of a food package.

[1282] Output: Captured image data

[1283] Step 2:

[1284] Upload the captured image to the server

[1285] Input: Captured image data, device's internet connection

[1286] Operation: The device sends the captured image data to a server via the Internet.

[1287] Output: Image data transferred to the server

[1288] Step 3:

[1289] The server analyzes the image and extracts ingredient information

[1290] Input: Image data stored on the server

[1291] How it works: The server uses OCR (Optical Character Recognition) technology to extract component information from the image as text data, for example using the pytesseract library for character recognition.

[1292] Output: Text data of extracted ingredient information

[1293] Step 4:

[1294] Evaluating health risks based on ingredient information

[1295] Input: Text data of extracted ingredient information, health risk assessment database on the server

[1296] How it works: The server evaluates the ingredient information and determines the health risk of each ingredient. It compares it with the safety standards based on the database and calculates the risk level.

[1297] Output: Health risk assessment results data

[1298] Step 5:

[1299] Generate alerts and advice taking into account the user's health status information

[1300] Input: Health risk assessment results data, user health profile information

[1301] How it works: The server generates alerts and advice based on a risk assessment, taking into account the user's health conditions (e.g., high blood pressure, diabetes, etc.), and uses a generative AI model to create appropriate notification text.

[1302] Output: Text data of generated alerts and advice

[1303] Step 6:

[1304] Notify users of generated alerts and advice

[1305] Input: Text data of generated alerts and advice, notification function of user terminal

[1306] What it does: Based on your settings, the server will send you alerts and advice via push notifications and in-app messages on your device.

[1307] Output: Alerts and advice displayed on the user's terminal

[1308] Step 7:

[1309] Display food evaluation results

[1310] Input: Alerts and advice sent to user terminals

[1311] How it works: The app on the device displays alerts and advice to the user, specifically displaying the rating results on the food selection screen before purchase.

[1312] Output: Evaluation results and advice displayed on the user's device screen

[1313] 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.

[1314] The present invention is a system that combines a system in which a user photographs a food package and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[1315] Overall system configuration

[1316] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[1317] Program processing flow

[1318] Food photography and image uploading

[1319] 1. The user launches the application on the device and takes a photo of the food package. The device uses the camera function to capture the image and temporarily stores it in the internal memory.

[1320] 2. The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[1321] Image analysis and component information acquisition

[1322] 3. The server waits for reception via the network and receives the image data sent from the terminal. The received image data is stored in a buffer for analysis.

[1323] 4. The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data. The server saves the extracted ingredient information as text data.

[1324] 5. The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[1325] Ingredient evaluation and sentiment analysis

[1326] 6. The server launches the evaluation tool based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[1327] 7. The server acquires the user's profile information and evaluates health risks based on the component evaluation results. The server performs an individual risk assessment according to the user's health condition (high blood pressure, diabetes, anemia, etc.).

[1328] 8. The server launches the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[1329] Alert and advice generation and notifications

[1330] 9. The server uses a generation means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today."

[1331] 10. The server activates a notification means for transmitting the generated alert and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[1332] Specific examples

[1333] For example, consider a scenario where a user wants to buy some snacks. The user takes a picture of the snacks' packaging with the device's camera, and the device uploads the image to a server. The server then analyzes the image using OCR technology to obtain the ingredient information.

[1334] The server then evaluates the snack based on the ingredient information, detecting that the snack contains a lot of sodium, and referring to the user's profile information, determining that the user has high blood pressure.

[1335] Furthermore, the emotion engine analyzes the user's facial expressions and tone of voice to determine that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[1336] The above is an embodiment of the present invention. The present invention allows a user to easily select foods that take into consideration not only their own health condition but also their emotional state at the time.

[1337] The processing flow will be explained below.

[1338] Step 1:

[1339] The user launches the application on their device and takes a picture of the food package using the camera function. The device captures the image and temporarily stores it in its internal memory.

[1340] Step 2:

[1341] The terminal establishes a network connection to upload the temporarily stored image to the server, and the terminal transmits the image data to the server using the uploading means.

[1342] Step 3:

[1343] The server waits for reception via the network and receives image data sent from the terminal. The received image data is stored in a buffer for analysis.

[1344] Step 4:

[1345] The server starts an analysis method using OCR technology to extract the character information of the ingredient list from the received image data, and saves the extracted ingredient information as text data.

[1346] Step 5:

[1347] The server analyzes the text data and creates a list of ingredients, including specific ingredients such as preservatives, colorings, sodium, and phosphates, and their amounts.

[1348] Step 6:

[1349] The server launches the evaluation means based on the ingredient information list and evaluates the intake risk of each ingredient. The server refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[1350] Step 7:

[1351] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. The server then performs an individual risk assessment based on the user's health condition (high blood pressure, diabetes, anemia, etc.).

[1352] Step 8:

[1353] The server activates the emotion engine and analyzes the user's emotional information while using the application. The emotion engine uses the camera and microphone to analyze the user's facial expressions and tone of voice to determine their emotional state.

[1354] Step 9:

[1355] The server uses a generating means to integrate the ingredient evaluation results with the user's emotional state and generate alerts and advice. For example, if the user is under stress, a flexible alert message can be created such as, "This food has a high sodium content, but a small amount is acceptable today to relieve stress."

[1356] Step 10:

[1357] The server activates a notification means for sending the generated alerts and advice to the terminal, and the server sends an alert message to the terminal, which notifies the user.

[1358] Step 11:

[1359] Notify users of alerts and advice received by the device. The device displays messages in pop-ups on the screen or in the notification bar for easy viewing by the user.

[1360] The above is the specific flow of processing steps by the "Food Fit Analyzer" program.

[1361] Example 2

[1362] 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."

[1363] Conventional food ingredient analysis systems were able to provide advice taking into account the user's health status information, but were unable to consider the user's emotional state. As a result, they were unable to provide flexible advice based on the user's stress and psychological state, and were unable to provide effective support in actual usage situations. In addition, individual health risk assessment based on the user's profile was limited, so a system that could provide more detailed advice was needed.

[1364] The identification process by the identification processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means. In this invention, the server includes means for extracting food ingredient information using OCR technology, means for evaluating health risks based on the ingredient information, and means for analyzing the user's emotional state. This makes it possible to dynamically provide alerts and advice based on both the user's emotional state and health condition information.

[1365] "Photographing means" refers to a device or function that allows a user to photograph food packaging.

[1366] The "uploading means" is a device or function for transmitting captured images to a server.

[1367] The "analysis means" is a device or function that analyzes images on the server and obtains information about food ingredients.

[1368] "OCR technology" refers to optical character recognition technology, a technology for extracting text information from images.

[1369] The "evaluation means" is a device or function that performs an evaluation according to health risk based on the acquired component information.

[1370] A "generator" is a device or function for generating alerts and advice taking into account the user's health status information and emotional state.

[1371] The "means for analyzing emotional state" is a device or function for determining emotions by analyzing the user's facial expressions and tone of voice.

[1372] A "notification means" is a device or function for sending generated alerts and advice to a user.

[1373] The present invention is a system that combines a system in which a user photographs food packaging and analyzes its ingredient information with an emotion engine that recognizes the user's emotions. An embodiment of this system will be described in detail below.

[1374] Overall system configuration

[1375] This system consists of a user's device, a server, an emotion engine, and a network connecting them. The device is equipped with a means for taking pictures and uploading, while the server is equipped with a means for analyzing, evaluating, generating, and notifying users, and the emotion engine.

[1376] Photographing food packaging and uploading images

[1377] A user launches an application on their device and takes a picture of a food package. The device uses its camera function to capture the image and temporarily stores it in its internal memory. The device then establishes a network connection and uses an upload method to send the temporarily stored image to a server. This operation uses common network connection methods such as Wi-Fi or mobile data communication.

[1378] Receiving image data and acquiring component information

[1379] The server waits for reception via the network and receives the image data sent from the device. The received image data is stored in a buffer for analysis. The server then activates an analysis method using OCR technology to extract the text information of the ingredient list from the received image data. This operation uses OCR technology such as Adobe Sensei or Google Cloud Vision API. The extracted ingredient information is saved as text data.

[1380] Listing and evaluation of ingredient information

[1381] The server analyzes the text data and creates a list of ingredient information. The list includes specific ingredients such as preservatives, coloring agents, sodium, and phosphates, along with their amounts. The server then launches an evaluation tool based on the ingredient information list to assess the intake risk of each ingredient. This evaluation refers to pre-set standard values ​​and databases to determine the health risk associated with each ingredient.

[1382] User profile matching and sentiment analysis

[1383] The server acquires the user's profile information and compares it with the component evaluation results to assess health risks. It also references the user's health condition (e.g., high blood pressure, diabetes, allergies) to perform an individual risk assessment. The server then activates an emotion engine to analyze the user's emotional information while using the application. The emotion engine uses the device's camera and microphone to capture the user's facial expressions and tone of voice and determine their emotional state.

[1384] Alert and advice generation and notification

[1385] The server uses the generation means to integrate the ingredient evaluation results with the user's emotional state and generate an alert and advice. For example, if the user is in a stressful state, a flexible alert message such as "This food has a high sodium content, but a special small amount is acceptable today" can be created. The server activates the notification means to send the generated alert and advice to the terminal. The terminal sends a push notification or an in-app notification to the user, allowing the user to receive the message.

[1386] Specific examples

[1387] For example, consider a scenario where a user is about to purchase a snack. The user takes a photo of the snack's packaging with the device's camera, and the device uploads the image to the server. The server analyzes the image using OCR technology and obtains ingredient information. The server evaluates the ingredient information and determines that the snack contains a lot of sodium. The server then references the user's profile information and determines that the user has high blood pressure. Additionally, the emotion engine analyzes the user's facial expressions and tone of voice and determines that the user is currently experiencing stress. Therefore, the server generates a flexible alert to notify the user, saying, "This snack contains a high amount of sodium, but a small amount is acceptable today to help relieve stress."

[1388] Prompt Sentence Examples

[1389] "I took a photo of a snack package. What's in it?"

[1390] "This snack contains sodium, preservatives, and colorings."

[1391] The present invention allows users to easily select foods that take into account their own health condition and current emotional state.

[1392] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1393] Step 1:

[1394] The user launches the application on their device and takes a photo of the food package. Specifically, the user taps the "take a photo" button on the application to activate the camera function. The user then points the camera at the food package and presses the shutter button to capture the image.

[1395] Input: User taps the capture button and a food package captured on camera.

[1396] Output: Image data of food packaging stored in the device's temporary memory.

[1397] Step 2:

[1398] The device establishes a network connection to upload the temporarily stored image data to the server. Specifically, the device connects to the Internet via Wi-Fi or mobile data communication and sends the image data to the server.

[1399] Input: Temporarily saved image data, network connection.

[1400] Output: Image data sent to the server.

[1401] Step 3:

[1402] The server waits for reception via the network and receives the image data sent from the terminal. Specifically, the server listens for HTTP requests, receives the image data, and stores it in a buffer for analysis.

[1403] Input: Image data sent from the device.

[1404] Output: Image data stored in a buffer for analysis.

[1405] Step 4:

[1406] The server starts an analysis method using OCR technology and extracts the text information of the ingredient list from the received image data. Specifically, it analyzes the image using an OCR engine (e.g., Google Cloud Vision API) and obtains the text data.

[1407] Input: Image data stored in the analysis buffer.

[1408] Output: Text data of ingredient list.

[1409] Step 5:

[1410] The server analyzes the text data and creates a list of ingredient information. Specifically, it uses a string analysis algorithm to analyze the text data, extracts each ingredient and its content, and adds it to the list.

[1411] Input: Text data of ingredient list obtained from the OCR engine.

[1412] Output: A list of ingredients.

[1413] Step 6:

[1414] The server launches an evaluation tool based on the ingredient information list to evaluate the intake risk of each ingredient. Specifically, it compares the ingredient information list with pre-set reference values ​​and databases to evaluate the health risk of each ingredient.

[1415] Input: List of ingredient information, reference value database.

[1416] Output: Intake risk assessment results for each ingredient.

[1417] Step 7:

[1418] The server acquires the user's profile information and compares it with the component evaluation results to evaluate health risks. Specifically, it refers to the user's health information (e.g., high blood pressure, diabetes, allergies) and performs an individual risk assessment.

[1419] Input: Ingredient evaluation results, user profile information.

[1420] Output: User-specific health risk assessment results.

[1421] Step 8:

[1422] The server activates the emotion engine and analyzes the user's emotional information while using the application. Specifically, the device's camera and microphone are used to capture the user's facial expressions and tone of voice, which the emotion engine analyzes to determine the user's emotional state.

[1423] Input: Data captured from the device's camera and microphone.

[1424] Output: The user's emotional state.

[1425] Step 9:

[1426] The server uses a generating means to integrate the component evaluation result and the user's emotional state to generate alerts and advice, for example, if the user is in a stress state, a special flexible alert message is created.

[1427] Input: Ingredient assessment results, user health risk assessment results, user emotional state.

[1428] Output: Alert and advisory messages.

[1429] Step 10:

[1430] The server activates a notification means for transmitting the generated alerts and advice to the device, specifically, by sending a push notification or an in-app notification to the device so that the user can receive the message.

[1431] Input: Alert and advice messages, network connections.

[1432] Output: Alert and advice notifications sent to the terminal.

[1433] (Application example 2)

[1434] 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."

[1435] In recent years, interest in health has increased, and health management based on food ingredient information is becoming increasingly important. However, conventional systems simply provide ingredient information and are unable to provide advice that takes into account the user's health and emotional state, and therefore do not provide sufficient value to users. Another issue is that real-time advice is not available when selecting food in a physical store. For this reason, there is a need for a system that helps users make appropriate food choices.

[1436] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes an imaging means for a user to photograph a food package, an uploading means for uploading the captured image to the server, an analysis means for analyzing the image in the server and acquiring ingredient information of the food, an evaluation means for making an assessment according to health risks based on the acquired ingredient information, a generation means for generating an alert and advice taking into account the user's health status information and emotional state information, a notification means for notifying the user of the generated alert and advice, and a user interface means for a user to operate the system using smart glasses or a head-mounted display in a physical store. This enables a user to make appropriate food selections based on their health status and emotional state in real time in a physical store.

[1437] The "photography means" refers to a device used by a user to photograph a food package, and is hardware that includes a camera function, such as a smartphone, smart glasses, or a head-mounted display.

[1438] "Uploading means" refers to a device or software that has the function of sending captured images to a server.

[1439] "Analysis means" refers to the technology used to analyze images on the server and extract information about food ingredients, and specifically includes OCR technology.

[1440] The "evaluation means" refers to a device or software that has the function of making an evaluation according to health risks based on the acquired component information.

[1441] A "generator" is a device or software that has the functionality to generate alerts and advice taking into account the user's health status information and emotional status information.

[1442] The "notification means" is a device or software that has a function for notifying the user of the generated alerts and advice.

[1443] "User interface means" refers to devices or software that have the functionality to allow users to operate the system in a physical store using smart glasses or a head-mounted display.

[1444] MODE FOR CARRYING OUT THE INVENTION

[1445] This invention combines an emotion engine with a system that allows a user to take a photo of a food package and analyze its ingredient information. An embodiment of this system will be described in detail below.

[1446] Overall system configuration

[1447] This system consists of a user's terminal, a server, an emotion engine, and a network connecting them. The terminal is equipped with a photographing means and an uploading means, while the server is equipped with an analysis means, an evaluation means, a generation means, a notification means, and an emotion engine. In addition, a user interface means is provided in the physical store, allowing users to operate the system using smart glasses or a head-mounted display.

[1448] Program processing flow

[1449] Hardware and Software

[1450] Hardware used:

[1451] Smartphones, smart glasses, head-mounted displays

[1452] Cameras, network connection devices

[1453] Software used:

[1454] OpenCV (camera control)

[1455] Pytesseract (OCR analysis)

[1456] EmotionRecognizer (emotion recognition engine)

[1457] Data calculation and processing

[1458] 1. Image capture:

[1459] The user captures an image of the food package using the camera on their device, such as a smartphone, smart glasses, or head-mounted display.

[1460] 2. Image upload:

[1461] The captured image is uploaded from the device to the server. At this time, a network connection is established and the image data is sent.

[1462] 3. Image Analysis:

[1463] The server uses OCR technology on the received image data to extract the text information from the ingredient list, using libraries such as Pytesseract.

[1464] 4. Ingredient information analysis and evaluation:

[1465] The extracted text information is analyzed and a list of ingredient information is compiled. Health risks are then assessed based on this ingredient information. The assessment method refers to pre-set standard values ​​and databases.

[1466] 5. Emotional State Analysis:

[1467] The server uses an emotion engine called EmotionRecognizer to analyze the user's facial expressions and tone of voice in real time to determine their emotional state.

[1468] 6. Advice Generation:

[1469] Based on the evaluated ingredient information and emotional state, personalized advice and alerts are generated. This is done by a generating means, which generates appropriate messages.

[1470] 7. Notice:

[1471] The generated advice is notified to the user by a notification means, which displays a message on the display of the smartphone or smart glasses.

[1472] Examples and prompts

[1473] For example, consider a case where a user picks up a snack and takes a photo of the packaging with the smart glasses' camera. The image is uploaded to a server, where the ingredient information is analyzed. The server detects that the snack has a high sodium content, and also analyzes that the user is currently experiencing stress. Based on this, a notification appears on the smart glasses' display saying, "This snack has a high sodium content, but a small amount is acceptable today to help relieve stress."

[1474] Prompt Sentence Examples

[1475] "Create an application that allows a user to take a photo of a food package and extract ingredient information using OCR technology. The application evaluates the risk of the ingredients, analyzes the user's emotional state, and generates personalized health advice based on that."

[1476] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1477] Step 1:

[1478] The user takes a picture of a food package using the device's camera. The input is an image of the food package, which is captured and temporarily stored in the device's internal memory. The output is the temporarily stored image data.

[1479] Step 2:

[1480] The terminal establishes a network connection and uploads the captured image to the server. The input is temporarily saved image data that is sent to the server via the uploading means. The output is image data waiting to be received on the server side.

[1481] Step 3:

[1482] The server receives the image data and stores it in a buffer. The input is the image data sent from the terminal and stored in the buffer. The output is the image data stored in the server's buffer.

[1483] Step 4:

[1484] The server analyzes the image using OCR technology and extracts the component information. The input is the stored image data, and the component information is extracted as text data using OCR technology. The output is the extracted text data.

[1485] Step 5:

[1486] The server analyzes the extracted ingredient information and generates a list for each specific ingredient. The input is text data extracted using OCR technology, and an ingredient information list is created using an analysis method. The output is an ingredient information list.

[1487] Step 6:

[1488] The server performs a health risk assessment based on the ingredient information list. The input is the ingredient information list, and the risk assessment is performed using the assessment means. This involves reference to pre-set standard values ​​and health databases. The output is the health risk assessment results.

[1489] Step 7:

[1490] The server analyzes the user's emotional state. The input is the user's facial expression image or tone of voice, which is analyzed by the emotion engine. The output is the user's emotional state information.

[1491] Step 8:

[1492] The server integrates the component assessment results and emotional state information to generate personalized advice and alerts. The input is the health risk assessment results and emotional state information, and optimal advice and alerts are generated using a generation means. The output is the generated advice and alert messages.

[1493] Step 9:

[1494] The server sends the generated advice and alert to the terminal and notifies the user. The input is the generated advice and alert message, which is sent to the terminal using the notification means. The output is the advice and alert message displayed on the terminal.

[1495] The above are the specific processing steps of the system based on the application example. By clarifying what data is input and what output is obtained at each step, the operation of this system is easier to understand. In addition, the specific operation content of each step is added to explain the embodiment of the invention in detail.

[1496] 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.

[1497] 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.

[1498] 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.

[1499] 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.

[1500] 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.

[1501] 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.

[1502] 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).

[1503] 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.

[1504] 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."

[1505] 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.

[1506] 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).

[1507] 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.

[1508] 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.

[1509] 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.

[1510] 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.

[1511] The hardware resource for executing a specific process can be any of the following processors: A CPU is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. A dedicated electrical circuit, such as a field-programmable gate array (FPGA), a programmable logic device (PLD), or an application-specific integrated circuit (ASIC), is a processor with a circuit configuration specifically designed to execute a specific process. Each processor has built-in or connected memory, and uses the memory to execute the specific process.

[1512] 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.

[1513] 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.

[1514] 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.

[1515] 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.

[1516] 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.

[1517] The following is further disclosed regarding the above embodiment.

[1518] (Claim 1)

[1519] a photographing means for a user to photograph a food package;

[1520] uploading means for uploading the captured image to a server;

[1521] an analysis means for analyzing the image in the server and acquiring information on ingredients of the food;

[1522] an evaluation means for performing an evaluation according to health risks based on the acquired component information;

[1523] generating means for generating alerts and advice taking into account the health status information of the user;

[1524] notification means for notifying a user of the generated alerts and advice;

[1525] A system including:

[1526] (Claim 2)

[1527] 10. The system of claim 1, wherein the server extracts component information from the image using OCR technology.

[1528] (Claim 3)

[1529] 2. The system of claim 1, wherein the component evaluation results are filtered based on user profile information.

[1530] "Example 1"

[1531] (Claim 1)

[1532] a photographing means for a user to photograph a food package;

[1533] uploading means for uploading the captured image to a server;

[1534] an analysis means for analyzing the image in the server and acquiring information on ingredients of the food;

[1535] an evaluation means for performing an evaluation according to health risks based on the acquired component information;

[1536] generating means for generating alerts and advice taking into account the health status information of the user;

[1537] notification means for notifying a user of the generated alerts and advice;

[1538] an input means for inputting a prompt sentence to the generative AI model;

[1539] a generative AI means for performing component analysis and health risk assessment using a generative AI model;

[1540] A system including:

[1541] (Claim 2)

[1542] 10. The system of claim 1, wherein the component information is extracted from the image at the server using OCR technology.

[1543] (Claim 3)

[1544] 2. The system of claim 1, wherein the component evaluation results are filtered based on user profile information.

[1545] "Application Example 1"

[1546] (Claim 1)

[1547] a photographing means for a user to photograph a food package;

[1548] a transmitting means for uploading the captured video to a server;

[1549] an analysis means for analyzing the video in the server and acquiring information on ingredients of the food;

[1550] an evaluation means for performing an evaluation according to health risks based on the acquired component information;

[1551] generating means for generating alerts and advice taking into account the health status information of the user;

[1552] notification means for notifying a user of the generated alerts and advice;

[1553] a display means for displaying the evaluation results of the food that the user is considering purchasing;

[1554] A system including:

[1555] (Claim 2)

[1556] The system according to claim 1, wherein the server extracts component information from the image using optical character recognition technology and generates an evaluation result.

[1557] (Claim 3)

[1558] The system according to claim 1, wherein the component evaluation results are filtered based on the user's profile information, and appropriate advice is presented when the user is considering a purchase.

[1559] "Example 2: Combining Emotion Engines"

[1560] (Claim 1)

[1561] a photographing means for a user to photograph a food package;

[1562] uploading means for transmitting the captured image to a server;

[1563] an analysis means for analyzing the image in the server and acquiring information on ingredients of the food;

[1564] A means for extracting food ingredient information using OCR technology;

[1565] an evaluation means for performing an evaluation according to health risks based on the acquired component information;

[1566] generating means for generating alerts and advice taking into account the health status information of the user;

[1567] means for analyzing the emotional state of a user;

[1568] notification means for sending generated alerts and advice to a user;

[1569] A system including:

[1570] (Claim 2)

[1571] 10. The system of claim 1, wherein the system dynamically adjusts alerts and advice based on ingredient information and the user's emotional state.

[1572] (Claim 3)

[1573] The system according to claim 1, wherein the component evaluation results are filtered based on user profile information, and advice is provided according to individual health conditions.

[1574] "Application example 2 when combining emotion engines"

[1575] (Claim 1)

[1576] a photographing means for a user to photograph a food package;

[1577] uploading means for uploading the captured image to a server;

[1578] an analysis means for analyzing the image in the server and acquiring information on ingredients of the food;

[1579] an evaluation means for performing an evaluation according to health risks based on the acquired component information;

[1580] generating means for generating alerts and advice taking into account the user's health state information and emotional state information;

[1581] notification means for notifying a user of the generated alerts and advice;

[1582] a user interface means for a user to operate the system in a physical store using smart glasses or a head-mounted display;

[1583] A system including:

[1584] (Claim 2)

[1585] 10. The system of claim 1, wherein the server extracts component information from the image using OCR technology.

[1586] (Claim 3)

[1587] 10. The system of claim 1, wherein the component evaluation results are filtered based on the user's profile information and emotional state information. [Explanation of symbols]

[1588] 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 photographing means for a user to photograph a food package; uploading means for uploading the captured image to a server; an analysis means for analyzing the image in the server and acquiring information on ingredients of the food; an evaluation means for performing an evaluation according to health risks based on the acquired component information; generating means for generating alerts and advice taking into account the health status information of the user; notification means for notifying a user of the generated alerts and advice; A system including:

2. 10. The system of claim 1, wherein the server extracts component information from the image using OCR technology.

3. The system of claim 1, wherein the component evaluation results are filtered based on user profile information.

Images