system

Abstract

We provide the system. [Solution] A means for the user to input a meal menu, A means of sending the meal menu entered by the user to the server, A method for the server to analyze the received meal menu and identify deficient nutrients, A means for generating a meal plan to supplement the nutrient deficiencies identified by the server, A means of providing the user with a meal menu generated by the server, A method for searching for and suggesting supermarkets or restaurants based on the user's location information, A system that includes this.

Description

Technical Field

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

Background Art

[0002] Patent Document 1 discloses a method for controlling a persona chatbot, which is performed by at least one processor, and includes steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to an explanation of a 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

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, it is a difficult task to maintain an appropriate nutritional balance in busy daily life and to take prompt and appropriate measures in case of minor physical discomfort. There is also a problem that there is a lack of an integrated system for efficiently proposing a diet menu for easily supplementing lacking nutrients and for efficiently searching for an appropriate hospital. The present invention aims to provide a system that manages a user's diet content and symptoms of minor physical discomfort and performs appropriate nutritional management and preliminary diagnosis before hospital examination in order to solve these problems.

[0005]

Means for Solving the Problems

[0006] The present invention solves the above problems by the following means: It provides means for the user to input a meal menu and means for transmitting the meal menu entered by the user to a server. The server has means for analyzing the received meal menu and identifying any deficient nutrients. It also includes means for generating a meal menu to supplement the deficient nutrients identified by the server and providing it to the user. Furthermore, it includes means for searching for and suggesting nearby supermarkets or restaurants based on the user's location information. In addition, this system provides means for the user to input symptoms of illness and transmit the entered symptoms to the server, which analyzes the symptoms and suggests possible illnesses. The server also includes means for searching for and suggesting the most suitable hospital based on the user's preferences and reputation. Moreover, it has means for verifying the meal menu and symptom information entered by the user and checking for any incomplete or inappropriate data, thereby improving the overall reliability and accuracy of the system.

[0007] A "user" is someone who uses this system to input meal menus, symptoms of illness, or receive suggestions.

[0008] A "terminal" is a device used by a user to record input information and send it to a server, and specifically refers to smartphones, tablets, personal computers, etc.

[0009] A "server" is a computer system that receives, analyzes, and processes data sent by a user.

[0010] "Meal menu" refers to the foods a user consumes daily and their detailed information (e.g., food name, quantity, time of consumption, etc.).

[0011] A "nutrition database" is a database that stores information on the nutrients contained in various foods.

[0012] "Nutrients" are components necessary for maintaining human health and growth (e.g., vitamins, minerals, proteins, lipids, carbohydrates, etc.).

[0013] "Symptom" refers to information that specifically describes specific physical abnormalities or discomfort felt by a user when they are in poor health.

[0014] "Disease" is a general term for abnormal conditions or illnesses that harm health.

[0015] "Supermarket" refers to a retail store where foodstuffs and daily necessities can be purchased.

[0016] "Restaurant" refers to a store that provides services such as cooking and drinks.

[0017] "Location information" refers to information about the location where the user is currently located and is obtained through GPS or an Internet connection.

[0018] "Verification" is a process of checking whether the data input by the user is complete and appropriate.

[0019] "Hospital" is a medical facility where doctors provide diagnosis, treatment, and preventive medicine.

Brief Description of the Drawings

[0020] [Figure 1] It is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] It is a conceptual diagram showing an example of the main functions of a data processing device and a smart device according to the first embodiment. [Figure 3] It is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] It is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] It is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] It is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7]It is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] It is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] It shows an emotion map to which a plurality of emotions are mapped. [Figure 10] It shows an emotion map to which a plurality of emotions are mapped. [Figure 11] It is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] It is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] It is a sequence diagram showing the processing flow of the data processing system in Example 2 when an emotion engine is combined. [Figure 14] It is a sequence diagram showing the processing flow of the data processing system in Application Example 2 when an emotion engine is combined.

Embodiments for Carrying Out the Invention

[0021] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0022] First, the language used in the following description will be explained.

[0023] In the following embodiments, the signed processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Furthermore, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units include CPU (Central Processing Unit), GPU (Graphics Processing Unit), GPGPU (General-Purpose computing on Graphics Processing Units), and APU (Accelerated Processing Unit).

[0024] In the following embodiments, signed RAM (Random Access Memory) is a memory that temporarily stores information and is used as work memory by the processor.

[0025] In the following embodiments, the signed storage is one or more non-volatile storage devices that store various programs and various parameters. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes.

[0026] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0027] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0028] [First Embodiment]

[0029] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0030] As shown in Figure 1, the 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.

[0031] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0032] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0033] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and 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.

[0034] 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 perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0035] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0036] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] As shown in Figure 2, in the data processing device 12, a specific processing 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" related to the technology of this 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 according to the specific processing program 56 executed on the RAM 30.

[0038] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0039] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0040] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0041] This invention is a system for users to manage and analyze their meal menus and minor health symptoms, and to provide appropriate meal suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[0042] 1. Overall System Overview

[0043] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user.

[0044] 2. Inputting meal menus and managing nutrition

[0045] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[0046] The server analyzes the received meal data and extracts nutrient information for each meal using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0047] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[0048] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[0049] 3. Support for initial medical consultation when feeling unwell

[0050] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[0051] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0052] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[0053] Specific example

[0054] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides the user with that menu. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0055] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[0056] Thus, a system that efficiently manages and analyzes users' dietary information and health status, and provides appropriate suggestions, is extremely useful in the advanced lifestyles of modern society.

[0057] The following describes the processing flow.

[0058] 1. Processing related to nutritional management of meals.

[0059] Step 1:

[0060] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[0061] Step 2:

[0062] The terminal verifies the meal menu data entered by the user, checking for any missing or inappropriate information.

[0063] Step 3:

[0064] The terminal sends the verified meal menu data to the server.

[0065] Step 4:

[0066] The server analyzes the data of the received meal menu.

[0067] Step 5:

[0068] The server uses its built-in nutritional database to identify the nutrients in each food item.

[0069] Step 6:

[0070] The server calculates the total daily nutrient intake based on the analysis results and compares it to the recommended daily intake standards.

[0071] Step 7:

[0072] The server identifies deficient nutrients based on comparisons with nutritional intake standards.

[0073] Step 8:

[0074] The server generates meal plans to supplement any missing nutrients.

[0075] Step 9:

[0076] The server sends the generated meal menu to the terminal.

[0077] Step 10:

[0078] The device searches for nearby supermarkets and restaurants based on the user's location information.

[0079] Step 11:

[0080] The device sends the search results to the server for filtering and optimization.

[0081] Step 12:

[0082] The server returns a list of the best places to shop to the device.

[0083] Step 13:

[0084] The device displays a list of optimal shopping destinations to the user.

[0085] 2. Procedures related to the initial consultation before hospital visit

[0086] Step 1:

[0087] The user enters their symptoms of illness (headache, sore throat, fever, etc.) into the terminal.

[0088] Step 2:

[0089] The terminal verifies the symptom data entered by the user and asks for additional information as needed.

[0090] Step 3:

[0091] The device sends complete symptom data to the server.

[0092] Step 4:

[0093] The server analyzes the received symptom data.

[0094] Step 5:

[0095] The server cross-references the data with its built-in medical database and generates a list of possible illnesses.

[0096] Step 6:

[0097] The server sends the generated disease list and initial countermeasures corresponding to the symptoms to the terminal.

[0098] Step 7:

[0099] The device displays a list of diseases and initial countermeasures to the user.

[0100] Step 8:

[0101] If a user wishes to receive a hospital consultation, they enter that information into the terminal.

[0102] Step 9:

[0103] The terminal sends the user's consultation request information and location information to the server.

[0104] Step 10:

[0105] The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for cases.

[0106] Step 11:

[0107] The server sends the generated list of hospitals to the terminal.

[0108] Step 12:

[0109] The terminal displays a list of the most suitable hospitals to the user.

[0110] (Example 1)

[0111] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0112] In today's busy lifestyle, proper nutritional management and appropriate responses to health problems are difficult. In particular, there is a lack of means for users to efficiently manage their diet and health status and quickly obtain necessary information. Furthermore, supplementing with appropriate nutrients, providing initial responses to health problems, and selecting the most suitable medical institution require specialized knowledge, making these tasks difficult for the average user. Therefore, there is a need for a system that allows users to easily and quickly manage their diet and health.

[0113] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0114] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting a store or restaurant based on the user's location information, means for the user to input any symptoms of poor health, means for the server to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable treatment facility based on the user's wishes and evaluations, and means for verifying the meal menu and symptom information entered by the user to check for any incomplete or inappropriate data. This enables the user to efficiently and effectively manage their diet and health.

[0115] A "user" refers to an individual or group that uses the system.

[0116] A "meal menu" refers to information that lists the types and quantities of food and beverages a user consumes.

[0117] "Means" refers to a method, device, or software used to perform a specific function or action.

[0118] A "server" refers to a computer system that receives requests from clients via a network, processes the necessary information, and responds.

[0119] "Nutrients" refer to components such as vitamins, minerals, proteins, fats, and carbohydrates that are necessary to maintain human health.

[0120] A "sales outlet" refers to a store where users can purchase the food ingredients and products they need.

[0121] "Dining places" refer to facilities such as restaurants and cafes where users can eat meals.

[0122] "Location information" refers to data that indicates the user's current geographical location.

[0123] "Symptoms" refer to the specific physical or psychological abnormalities that a user experiences when feeling unwell.

[0124] "Disease" refers to a condition in which health deteriorates due to abnormalities in bodily functions or organs.

[0125] A "treatment facility" refers to a place that provides medical care, such as a hospital, clinic, or medical office.

[0126] "Data" refers to a collection of numbers, characters, symbols, and other elements used to represent information.

[0127] This invention is a system that allows users to manage and analyze their meal menus and symptoms of poor health, and provides appropriate dietary suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[0128] Hardware and software configuration

[0129] In this system, users input their daily meal menus and symptoms of illness using devices such as smartphones and personal computers. The data entered by users is sent via the internet to a cloud-based server. On the server side, data analysis and suggestion generation are performed using specific software.

[0130] Device configuration

[0131] The user's device has a dedicated application installed for entering data on meals and symptoms. This application has fields for entering the food name, quantity, time of intake, and the severity and time of symptom onset.

[0132] Server Configuration

[0133] On the server side, the following software and databases are used to analyze the received data:

[0134] Nutritional databases (e.g., USDA National Nutrient Database): Used to analyze the nutritional content of meal menus.

[0135] Medical databases (e.g., MedlinePlus): Used to identify possible illnesses based on symptoms of illness.

[0136] Location information databases (e.g., Google® Maps API): Used to suggest nearby shops, restaurants, and medical facilities based on the user's location.

[0137] System operation

[0138] The operation of this system is outlined below:

[0139] 1. Data Entry: Users enter meal menus and symptoms of illness using their smartphones or computers. Meal menus include food names, quantities, and times of consumption, while symptoms include specific details of illnesses and the time they occurred.

[0140] 2. Data Transmission: The device transmits the entered data to the server via the internet. The transmitted data includes the user ID, input data, and location information.

[0141] 3. Data Analysis: The server analyzes the received data. In the case of meal menus, it uses a nutrition database to analyze nutrients and identify any nutrient deficiencies. In the case of illness, it uses a medical database to identify possible diseases.

[0142] 4. Suggestion Generation: Based on the analysis results, the server generates meal menus to supplement any deficient nutrients. If the user is unwell, it also suggests initial countermeasures tailored to their symptoms. Furthermore, based on location information, it suggests nearby shops, restaurants, and medical facilities.

[0143] 5. Provision to the user: The generated suggestions are provided to the user via their device. This allows the user to efficiently manage their diet and health.

[0144] Specific example

[0145] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that data to the server. The server uses a nutritional database to identify a deficiency in vitamin D and calcium and suggests "eating salmon steak and broccoli salad for dinner." At the same time, information about nearby stores is also displayed.

[0146] Furthermore, if a user enters "headache, sore throat, and 38-degree fever," the server uses its medical database to identify the possibility of a cold, influenza, or pharyngitis and suggests "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, the server will also suggest nearby hospitals with good reputations based on their location.

[0147] Example of a prompt

[0148] Meal menu management

[0149] Prompt: "I had one slice of toast and coffee for breakfast. Please analyze its nutrients and suggest a complementary dinner menu."

[0150] Measures to take when you are feeling unwell

[0151] Prompt: "I currently have a headache, sore throat, and a fever of 38 degrees Celsius. Please tell me what the possible illnesses are and what initial treatments I should take. Also, please recommend a nearby hospital with a good reputation."

[0152] In this way, the system enables users to efficiently manage and analyze information about their diet and health problems, and to provide optimal suggestions.

[0153] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0154] Step 1:

[0155] Users input their daily meal menus and symptoms of illness into a dedicated application using their smartphones or computers. The input data includes the name of the food, the quantity, the time of consumption, and the symptoms and the time of their onset.

[0156] Input: Information on meal menus and symptoms of illness

[0157] Output: Data entered into the terminal

[0158] Step 2:

[0159] The terminal packages the data entered by the user and sends it to the server via the internet. The transmitted data includes the user ID, information about meals or symptoms, and location information.

[0160] Input: Data entered by the user on the device.

[0161] Output: Packaged data sent to the server

[0162] Step 3:

[0163] The server receives the data and stores it in the database. The stored data is then retrieved for analysis.

[0164] Input: Data sent from the device

[0165] Output: Data stored on the server

[0166] Step 4:

[0167] For food data, the server uses an internal nutrition database to analyze the nutrients in each food item and calculate the total daily nutrient intake. For data related to poor health, it uses a medical database to identify possible illnesses.

[0168] Input: Meal data or symptom data stored on the server

[0169] Data processing / calculation: Analysis by cross-referencing with nutritional or medical databases.

[0170] Output: List of deficient nutrients or possible diseases

[0171] Step 5:

[0172] The server generates meal plans to supplement any nutritional deficiencies based on the analysis results. If the user is unwell, it generates initial countermeasures tailored to their symptoms.

[0173] Input: List of deficient nutrients or diseases

[0174] Data processing / data calculation: Generation of meal suggestions or initial countermeasures

[0175] Output: Meal suggestion menu or initial countermeasures

[0176] Step 6:

[0177] The server searches for shops, restaurants, and medical facilities based on the user's location information and provides this information to the user along with the analysis results.

[0178] Input: Location information, generated suggestion information

[0179] Data processing / data calculation: Location-based search and integration of suggestion information

[0180] Output: Location-based suggestion information

[0181] Step 7:

[0182] The terminal displays suggested information received from the server to the user. For meal suggestions, it displays specific menus and purchase locations; for health issues, it displays initial countermeasures and hospital information.

[0183] Input: Suggestion information sent from the server

[0184] Output: Displayed suggestion information

[0185] Step 8:

[0186] Users take action based on information suggested through their device. For example, if a meal is suggested, they prepare a meal based on the suggested menu; if they feel unwell, they take initial measures and visit a hospital if necessary.

[0187] Input: Suggested information

[0188] Output: User behavior

[0189] (Application Example 1)

[0190] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0191] In modern society, users need to manage their daily diets and symptoms of illness themselves for health management. However, it is not easy for them to find appropriate dietary suggestions or early countermeasures for symptoms on their own. Furthermore, there is a lack of systems that efficiently provide information on foods to supplement necessary nutrients and appropriate medical facilities. As a result, it is difficult for users to effectively maintain their health and take preventative measures against illness.

[0192] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0193] In this invention, the server includes means for analyzing the user's meal menu and identifying deficient nutrients, means for generating meal menus to supplement the deficient nutrients, and means for providing health supplements and medical information based on the analysis results. This enables the user to efficiently manage their daily diet and physical condition and to perform appropriate health management.

[0194] "Means for inputting meal menus" refers to devices or application functions that allow users to record or input their daily meal contents.

[0195] "Means for sending meal menus to the server" refers to a communication function for sending meal information entered by the user to a central server.

[0196] "Means for identifying deficient nutrients" refers to a function where the server analyzes the received meal information and identifies nutrients that the user is not consuming or is deficient in.

[0197] "Method for generating meal menus" refers to a function where the server creates new meal suggestions to supplement any missing nutrients.

[0198] "Means of providing meal menus to users" refers to a function for notifying or displaying generated meal suggestions to users.

[0199] The "means of searching for and suggesting places where ingredients can be purchased" refers to a function that uses the user's location information to search for and suggest places where the ingredients needed for the generated meal menu can be purchased.

[0200] "Means for inputting symptoms of poor health" refers to devices or application functions that allow users to record or input health problems related to their own or their family's physical condition.

[0201] "Means for sending symptoms to the server" refers to a communication function for sending health information entered by the user to a central server.

[0202] "Means of presenting possible illnesses" refers to a function that, based on the symptom information received by the server, lists possible illnesses and health problems and notifies the user.

[0203] "Means for searching for and suggesting medical institutions" refers to a function that searches for and provides appropriate hospitals and clinics to users based on their health condition and preferences.

[0204] "Means of providing health supplements and medical information" refers to a function that recommends appropriate supplements and medical institutions to address users' health conditions and nutritional deficiencies.

[0205] To realize this invention, a system is needed in which users manage and input their daily health information, and a server analyzes and makes suggestions based on that information. The system mainly consists of a terminal used by the user (such as a smartphone or computer) and a server that processes the data.

[0206] Hardware and software

[0207] 1. Hardware:

[0208] Smartphone: Used by users to record and transmit input data.

[0209] Server: A central processing unit for data analysis and proposal generation.

[0210] 2. Software:

[0211] Python: Used for data processing and API requests.

[0212] Requests library: Used for communication with APIs.

[0213] Geopy library: Used to obtain the user's location information.

[0214] Data processing and calculation flow

[0215] 1. User input:

[0216] Users input their daily meal menus and symptoms of illness into a smartphone app.

[0217] Regarding dietary information, details such as food names, quantities, and timing of consumption are included.

[0218] Information about feeling unwell includes symptoms such as headache, sore throat, and fever.

[0219] 2. Data transmission:

[0220] The user enters information and sends it from their smartphone to the server.

[0221] 3. Server analysis:

[0222] The server analyzes the received meal data and identifies any nutritional deficiencies.

[0223] The system utilizes a built-in nutrition database to extract nutrient information for each meal. Next, it calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0224] The server automatically generates meal plans to supplement any missing nutrients. The generated suggested menus include specific food names and their corresponding nutrients.

[0225] Furthermore, based on the symptom information entered by the user, the system cross-references it with a built-in medical database to generate a list of possible illnesses. It also provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0226] 4. Providing suggestions:

[0227] The created suggested menus, health supplements, and medical institution information are sent back from the server to the user's terminal and displayed.

[0228] At the same time, based on the user's location information, it provides information on stores where the suggested food items can be purchased and information on appropriate hospitals.

[0229] Specific example

[0230] For example, if a user enters, "I had one slice of toast and coffee for breakfast. Recently, I've had a headache, sore throat, and a fever of 38 degrees Celsius," the server will identify a deficiency in "vitamin D and calcium" and suggest "salmon steak and broccoli salad for dinner." At the same time, it will suggest the possibility of "a cold, the flu, or pharyngitis" and advise "drink plenty of fluids and rest." Based on the user's location, a list of the nearest supermarkets and highly-rated hospitals will also be provided.

[0231] Example of a generated AI prompt

[0232] Write code for a program that provides personalized suggestions based on the user's health status.

[0233] It has a function to input user dietary data and symptoms of illness.

[0234] Send data to the server for analysis and recommendations.

[0235] Based on the results, we will provide appropriate nutritional supplements and information on medical facilities.

[0236] Use location information to display nearby hospitals

[0237] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0238] Step 1:

[0239] The user inputs their meal menu. The user enters details of their daily meals (food name, quantity, time of consumption, etc.) into a device (smartphone, computer, etc.). This input data is formatted by the application.

[0240] Step 2:

[0241] The device sends meal data to the server. The meal information entered by the user is sent from the device to the server. In this process, the device often converts the input data into JSON format and sends it via an HTTP request.

[0242] Step 3:

[0243] The server analyzes the meal data. The server analyzes the received meal data and identifies any deficient nutrients. It extracts nutrient information for each meal using its built-in nutrition database. It calculates the total daily nutrient intake and identifies any deficiencies by comparing it to recommended nutritional intake standards.

[0244] Step 4:

[0245] The server generates meal plans that supplement any missing nutrients. The server creates new meal suggestions to address any nutritional deficiencies. This generation process automatically generates menus that include specific food names and corresponding nutrients, referencing a built-in recipe database.

[0246] Step 5:

[0247] The server generates a meal menu and provides it to the user. The generated meal menu is sent back from the server to the terminal and notified or displayed to the user. The user can review the suggested menu through the application.

[0248] Step 6:

[0249] The user enters their symptoms of illness. The user enters detailed information about their or their family member's illness (e.g., headache, sore throat, fever, etc.) into the device. This input data is also formatted by the application.

[0250] Step 7:

[0251] The terminal sends symptom data to the server. The symptom information entered by the user is sent from the terminal to the server. During this process, the terminal converts the input data into JSON format and sends it via an HTTP request.

[0252] Step 8:

[0253] The server analyzes the symptom data. Based on the received symptom information, the server compares it with its built-in medical database and generates a list of possible illnesses. Furthermore, it provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0254] Step 9:

[0255] The server searches for and suggests the most suitable medical institutions. Based on the user's health condition and preferences, the server searches for appropriate medical institutions and generates a list to provide to the user. This list is compiled considering factors such as hospital reputation and the success rate of cases.

[0256] Step 10:

[0257] The server generates a list of medical institutions and provides it to the user. The generated list of medical institutions is then sent back from the server to the terminal and notified or displayed to the user. The user can then review the suggested medical institutions through the application.

[0258] Step 11:

[0259] Based on the user's location information, the server suggests places where the product can be purchased and medical facilities. Using the user's location information, the server provides information on stores where the suggested food product can be purchased and appropriate medical facilities. This information is generated through database lookup and location data analysis.

[0260] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0261] This invention combines a system that manages and analyzes a user's meal menu and minor health symptoms, providing appropriate meal suggestions and useful information before hospital visits, with an emotion engine that recognizes the user's emotions. This system mainly consists of a terminal used by the user, a server that processes data, and an emotion engine that acquires and analyzes emotional data.

[0262] 1. Overall System Overview

[0263] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user. An emotion engine analyzes the user's emotional state and provides appropriate responses accordingly.

[0264] 2. Inputting meal menus and managing nutrition

[0265] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[0266] The server analyzes the received meal data and extracts nutrient information for each food item using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0267] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[0268] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[0269] 3. Support for initial medical consultation when feeling unwell

[0270] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[0271] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0272] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[0273] 4. Emotion recognition by an emotion engine

[0274] When a user enters meal menus or symptom information, the emotion engine activates and analyzes the user's emotional state from their voice tone and input content. The emotion engine recognizes emotions such as joy, sadness, stress, and anger.

[0275] The acquired emotional data is sent to a server, which adjusts the suggestions based on the user's emotional state. For example, if a user is feeling stressed, they will be offered advice on stress-reducing foods and relaxation techniques. Suggestions for when the user is feeling unwell will also take their emotional state into consideration.

[0276] Specific example

[0277] For example, assume that the user inputs "I had 1 slice of toast and coffee for breakfast". The terminal transmits this information to the server, and the server, as a result of analysis, identifies that "vitamin D" and "calcium" are insufficient. Based on this, the server proposes "salmon steak and broccoli salad for dinner" and provides that menu to the user through the terminal. Furthermore, information on the nearest supermarket is also presented based on the user's location information.

[0278] Also, on another day, if the user inputs "headache, sore throat, and a fever of 38 degrees", the server presents the possibilities of "cold, influenza, pharyngitis" and proposes "drink plenty of water and rest" as initial measures. And if the user wishes to visit a hospital, a list of hospitals with good reputations in the neighborhood and a high complete cure rate for cases is presented.

[0279] Furthermore, when the emotion engine recognizes that the user is feeling stressed when inputting, advice on foods and actions effective for stress reduction is also provided simultaneously. In this way, by utilizing emotion recognition, more individualized care becomes possible.

[0280] The following describes the processing flow. <{

[0281] 1. Processing related to nutritional management of diet content

[0282] Step 1:

[0283] The user inputs the current diet menu (food name, portion, intake time, etc.) into the terminal.

[0284] Step 2:

[0285] The terminal verifies the data input by the user and checks for incomplete information or incorrect data.

[0286] Step 3:

[0287] The terminal sends the verified meal menu data to the server.

[0288] Step 4:

[0289] The server analyzes the data of the received meal menu.

[0290] Step 5:

[0291] The server uses a nutrition database to identify the nutritional information of each food item.

[0292] Step 6:

[0293] The server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to standard nutritional intakes.

[0294] Step 7:

[0295] The server generates meal plans to supplement any missing nutrients.

[0296] Step 8:

[0297] The server sends the generated meal menu to the terminal.

[0298] Step 9:

[0299] The terminal displays the generated meal menu to the user.

[0300] Step 10:

[0301] The device sends data to a server based on the user's location information to search for nearby supermarkets and restaurants.

[0302] Step 11:

[0303] The server searches for the best supermarkets and restaurants and sends that information back to the terminal.

[0304] Step 12:

[0305] The terminal displays the search results to the user and proposes places where the recommended food can be purchased.

[0306] 2. Processing related to the first diagnosis when in poor health

[0307] Step 1:

[0308] The user enters the symptoms of poor health (such as headache, sore throat, fever, etc.) in detail into the terminal.

[0309] Step 2:

[0310] The terminal verifies the symptoms entered by the user and asks for additional information if necessary.

[0311] Step 3:

[0312] The terminal sends the complete symptom data to the server.

[0313] Step 4:

[0314] The server analyzes the received symptom data.

[0315] Step 5:

[0316] The server checks against the medical database and generates a list of possible diseases.

[0317] Step 6:

[0318] The server sends the generated disease list and initial countermeasure information to the terminal.

[0319] Step 7:

[0320] The terminal displays the disease list and initial countermeasures to the user.

[0321] Step 8:

[0322] If a user wishes to schedule a hospital appointment, they enter that information into the terminal.

[0323] Step 9:

[0324] The terminal transmits the user's consultation request information and location information to the server.

[0325] Step 10:

[0326] The server generates a list of optimal hospitals, taking into account the user's desired treatment, hospital reputation, and the cure rate for cases.

[0327] Step 11:

[0328] The server sends the generated hospital list to the terminal.

[0329] Step 12:

[0330] The terminal displays a list of suitable hospitals to the user and assists with the appointment booking process.

[0331] 3. Processing related to emotion recognition by the emotion engine

[0332] Step 1:

[0333] When a user enters meal menus or symptom information into the terminal, the emotion engine automatically activates to analyze the user's emotional state while they are entering the information.

[0334] Step 2:

[0335] The emotion engine acquires emotion data from the user's voice tone and input content.

[0336] Step 3:

[0337] The device sends the acquired emotion data to the server.

[0338] Step 4:

[0339] The server analyzes emotional data and adjusts the content of its meal menu and disease predictions based on the user's emotional state.

[0340] Step 5:

[0341] The server generates optimal menus and advice based on sentiment data.

[0342] Step 6:

[0343] The server sends the generated suggestions to the terminal.

[0344] Step 7:

[0345] The device displays meal menus and advice tailored to the user's emotional state.

[0346] Specific example

[0347] For example, if a user inputs "I had one slice of toast and coffee for breakfast," the device sends this information to the server, which analyzes it and identifies a deficiency in "vitamin D" and "calcium." The server then suggests "salmon steak and broccoli salad for dinner" and provides this menu to the user via the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0348] On another day, if a user enters "headache, sore throat, and 38-degree fever," the server suggests the possibility of "cold, flu, or pharyngitis" and recommends "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases is provided.

[0349] Furthermore, if the emotion engine is activated and recognizes that the user is experiencing stress during input, it will also provide advice on foods that are effective in reducing stress and relaxation techniques. In this way, utilizing emotion recognition enables more personalized care.

[0350] (Example 2)

[0351] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0352] Current meal and health management systems are insufficient in managing nutrients and analyzing symptoms, and they fail to provide individualized support that takes into account the user's emotional state. As a result, users often do not receive appropriate nutritional support or timely, appropriate medical care. Furthermore, there is a need for systems that can address not only nutrient deficiencies and potential illnesses, but also the stress and other emotions that users are experiencing.

[0353] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server with the generated meal menu to the user, means for searching for and suggesting sales facilities or restaurants based on the user's location information, means for the user to input symptoms of poor health, means for the user to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable medical facility based on the user's preferences and reputation, means for the emotion engine to recognize the emotional state when the user inputs meal menu and symptom information, means for the emotion engine to transmit the analyzed emotional data to the server, and means for the server to adjust the suggested content based on the emotional state. This will not only enable users to properly replenish the nutrients they need for diet and health management, but also allow them to receive prompt and appropriate medical care when they are unwell, and furthermore, enable personalized support tailored to their emotional state.

[0354] A "user" refers to an individual who uses this system to manage their diet and health.

[0355] A "terminal" refers to a device used by a user to input data and communicate with a server. Examples include smartphones and personal computers.

[0356] A "server" refers to a computer system that receives data sent by a user, analyzes and processes it, and provides the results.

[0357] "Meal menu" refers to the detailed information about meals entered by the user. Specifically, this includes the name of the food, the quantity, and the time of consumption.

[0358] "Nutrients" refer to components found in food that are necessary for maintaining bodily functions. Examples include vitamins, calcium, and protein.

[0359] "Symptoms" refer to physical abnormalities or discomforts that a user experiences when feeling unwell. Examples include headaches, sore throats, and fever.

[0360] An "emotion engine" refers to a technology that analyzes a user's emotional state from their input or voice.

[0361] A "sales facility" refers to a place where you can buy ingredients and food products. Examples include supermarkets and grocery stores.

[0362] A "food and beverage establishment" refers to a place where users can eat. This includes, for example, restaurants and cafes.

[0363] A "medical facility" refers to a place that provides diagnosis and treatment for illnesses and health problems. Examples include hospitals and clinics.

[0364] "Generative AI models" refer to artificial intelligence technologies that provide appropriate suggestions and analyses based on user requests.

[0365] A "prompt sentence" refers to an instruction or question that is input into a generative AI model. Examples include sentences requesting meal menu suggestions or sentences requesting symptom analysis.

[0366] This invention relates to a system that manages and analyzes a user's meal menu and symptoms of poor health, and provides appropriate meal suggestions and medical information. This system further achieves more personalized care by incorporating an emotion engine that recognizes the user's emotions.

[0367] This system primarily consists of a user terminal, a server that processes data, and an emotion engine that acquires and analyzes emotional data. The overall system flow begins with the user entering their meal menu or symptoms of illness into the terminal and sending that data to the server. The server analyzes this data, generates appropriate suggestions, and finally delivers them to the user through the terminal.

[0368] The terminal uses common devices such as smartphones and personal computers. Users input meal menus and symptom information into the terminal, and the terminal sends this information to the server. Examples of software used include web browsers and dedicated applications.

[0369] The server incorporates various databases (nutrition database, medical database, sentiment analysis database) and uses them for data analysis and processing. For example, FoodData Central is commonly used for the nutrition database, and general medical information is stored in the medical database. Furthermore, the Google Cloud Speech-to-Text API and IBM Watson® Natural Language Understanding are used for the sentiment engine. The server uses Python's pandas library and the NLP library spaCy to analyze data received from users.

[0370] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that information to the server. The server analyzes the data and identifies a deficiency in "vitamin D" and "calcium," and based on that, suggests "salmon steak and broccoli salad for dinner." It also uses the user's location information to show where these ingredients can be purchased at the nearest supermarket.

[0371] If a user is feeling unwell and enters "headache, sore throat, and 38-degree fever," the server will suggest possibilities such as "cold," "flu," or "pharyngitis," and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, the server will list nearby medical facilities with good reputations based on the user's location and preferences, and provide this information to the user via their device.

[0372] As an example of analysis by the emotion engine, if a user enters "I've been really busy with work lately and feeling stressed" when inputting meal menus or symptom information, the emotion engine analyzes the text and recognizes that the user is feeling stressed. Based on this, the server provides stress-reducing foods (for example, chamomile tea) and relaxation advice.

[0373] Examples of prompts generated using a generative AI model include the following:

[0374] mark down

[0375] Please analyze the following dietary information and suggest a daily meal plan to identify any nutritional deficiencies and supplement them.

[0376] Meal information: Had one slice of toast and coffee for breakfast.

[0377] mark down

[0378] Please analyze the following symptom information, provide a list of possible illnesses, and suggest initial countermeasures.

[0379] Symptoms: Headache and sore throat, fever of 38 degrees Celsius.

[0380] mark down

[0381] The user made the following request: "Please use an emotion engine to analyze my emotional state (joy, sadness, stress, anger, etc.) and suggest appropriate countermeasures."

[0382] Statement: Lately, I feel like I'm stressed because work has been so busy.

[0383] Thus, this system not only manages nutrition and health based on the meal menus and symptom information entered by the user, but also enables personalized responses that take into account the user's emotional state.

[0384] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0385] Step 1: Enter and submit your meal menu.

[0386] Users input meal menus using their smartphones or PCs. Specifically, they input information such as, "I had one slice of toast and coffee for breakfast." The device sends this input information to the server. The output is the server receiving the meal menu entered by the user.

[0387] Step 2: Analysis of meal plans and identification of nutritional deficiencies

[0388] The server analyzes the received meal menu. First, it reads the received data into a DataFrame using the pandas library and extracts nutrient information for each food item from a nutrition database (e.g., FoodData Central). Next, it calculates the total daily nutrient intake and compares it to the recommended daily intake. Based on this comparison, it identifies any deficient nutrients. The input is the meal menu entered and submitted by the user, and the output is a list of identified deficient nutrients.

[0389] Step 3: Generating complementary meal menus

[0390] The server generates meal plans to supplement identified nutrient deficiencies. Specifically, it uses Python's scikit-learn to build a machine learning model for recipe suggestions and generates specific food suggestions to supplement the missing nutrients (e.g., "Salmon steak and broccoli salad for dinner"). The input is a list of the missing nutrients, and the output is the generated supplementary meal plan.

[0391] Step 4: Suggesting places to buy groceries

[0392] The server uses the user's location information based on the generated meal menu to search for nearby retail and dining establishments. Specifically, it uses the Google Places API to list stores where the necessary ingredients can be purchased. This information is then provided to the user via their device. The input is the generated meal menu and the user's location information, and the output is a list of suggested places to buy.

[0393] Step 5: Enter and submit your symptoms.

[0394] The user enters their symptoms into the terminal. Specifically, they enter detailed symptom information such as "headache, sore throat, and a fever of 38 degrees Celsius." The terminal sends this symptom information to the server. The output is the user's entered symptom information sent to the server.

[0395] Step 6: Analysis of symptom information and presentation of possibilities

[0396] The server analyzes the received symptoms. Using an NLP library (e.g., spaCy), it analyzes the symptom information and compares it with a medical database. It generates a list of possible illnesses and suggests appropriate initial countermeasures (e.g., "Drink plenty of fluids and rest"). The input is the symptom information entered and submitted by the user, and the output is the likelihood of possible illnesses and initial countermeasures.

[0397] Step 7: Propose hospital information

[0398] When a user requests a medical consultation, the device sends their request information and location to the server. The server uses the Google Maps API to search for nearby medical facilities and generates a list of the best hospitals based on reputation and success rates. This list is then provided to the user via the device. The input is the user's consultation request information and location, and the output is a list of suggested hospitals.

[0399] Step 8: Input and analysis of emotional data

[0400] When a user enters meal menus or symptom information, the emotion engine activates and analyzes their emotional state from the input content and tone of voice. It uses Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding to generate emotion data. The server receives this emotion data and adjusts the suggestions based on the estimated emotional state. The input is the user's emotional state, and the output is the analyzed emotional state.

[0401] Step 9: Adjusting proposals based on emotional state

[0402] The server adjusts the suggested meal menus and medical information based on the user's emotional state, using the results of the emotion engine's analysis. For example, if the user is feeling stressed, it will provide stress-reducing foods and relaxation advice. This enables more personalized care. The input is the analysis results from the emotion engine, and the output is the adjusted suggestions.

[0403] Through the processing steps described above, this system comprehensively supports the user's dietary and health management, and provides personalized support tailored to their emotional state.

[0404] (Application Example 2)

[0405] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as a "server" and the smart device 14 as a "terminal".

[0406] In today's busy lifestyle, it is difficult for individuals to properly manage their own nutritional balance and health. Furthermore, receiving personalized advice on diet and health is time-consuming and requires direct support from a specialist. Moreover, few health management systems take into account the user's emotional state, and personalized suggestions tailored to those emotions are needed. Therefore, there is a need for a system that allows users to efficiently manage their diet and health and receive detailed advice that reflects their emotional state.

[0407] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0408] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting supermarkets or restaurants based on the user's location information, means for the user to input and view information within a virtual store through a virtual reality device, means for analyzing the user's emotional state using an emotion recognition engine, and means for adjusting the suggested meal menu and advice based on the emotional state. As a result, the user can more efficiently manage their health and eating habits and receive personalized advice tailored to their emotional state.

[0409] "Methods for inputting meal menus" refers to interfaces that allow users to directly input details of their meals into a device, and this includes text input and voice input.

[0410] "Means of sending to a server" refers to infrastructure that has the function of sending data entered by a user to a remote server via the internet.

[0411] "Methods for analyzing meal menus" refers to software or hardware that analyzes the nutrient content and composition based on meal data received by a server, and identifies any deficient nutrients.

[0412] "Method for generating meal menus" refers to an algorithm and software that enables a server to automatically generate appropriate meal menus to supplement identified nutritional deficiencies.

[0413] "Means of providing to the user" refers to means of presenting the generated meal menu and related information to the user's device, and this includes display and audio notifications.

[0414] The "means for searching for and suggesting supermarkets or restaurants" refers to a system that uses the user's location information to search the internet for information on stores and restaurants where suggested food items or dishes can be purchased, and then notifies the user.

[0415] A "virtual reality device" is a device, such as a head-mounted display or VR goggles, that allows users to enter a virtual space and realistically recreates the experience of being in a virtual store.

[0416] An "emotion recognition engine" is a software system that uses artificial intelligence to analyze a user's voice and input data and determine the emotional state contained within it.

[0417] A "means for analyzing emotional states" refers to a system that analyzes a user's emotional state from their input data and behavior, and transmits that information to a server.

[0418] "Means for adjusting suggested meal menus and advice" refers to a system that customizes the content of meal menus and health advice to best suit the user based on their analyzed emotional state.

[0419] This invention is a system that allows users to input meal menus and symptoms of illness, and then provides nutritional management and health advice based on that input. Furthermore, it can analyze the user's emotional state and make suggestions accordingly. This system can be implemented using a smartphone, personal computer, or virtual reality device (such as VR goggles or a head-mounted display).

[0420] System Overview

[0421] 1. The user enters their meal menu and symptoms of illness into the device.

[0422] 2. The entered data is sent to the server via the internet.

[0423] 3. The server analyzes the data to identify potential nutrient deficiencies or health problems.

[0424] 4. Generate dietary suggestions to supplement necessary nutrients and create appropriate initial countermeasures.

[0425] 5. Provide users with suggestions and information on supermarkets, restaurants, or hospitals.

[0426] 6. The emotion recognition engine analyzes the user's emotional state and adjusts the suggested content accordingly.

[0427] Hardware and software to be used

[0428] Virtual reality devices: Oculus Rift, HTC Vive, Sony PlayStation VR, etc.

[0429] Speech-to-Text API: Google Speech-to-Text

[0430] Emotion recognition engine: Azure Cognitive Services Emotion API (registered trademark)

[0431] Server-side frameworks: Django, Flask

[0432] Data analysis and management: Dedicated nutritional and medical databases

[0433] Language processing solutions: Google Cloud Natural Language API

[0434] Program Processing Overview

[0435] User input

[0436] The user puts on VR goggles, logs into a virtual store, and uses a voice recognition API to input their meal order and health status. For example, they might say, "I had toast and coffee for breakfast today."

[0437] Data transmission

[0438] The input data is transmitted to the server in real time via the internet. The server receives the transmitted data and proceeds to the next analysis step.

[0439] Data Analysis

[0440] The server analyzes the received dietary and symptom data. Here, it uses dedicated nutritional and medical databases to identify nutrient content and possible diseases.

[0441] Proposal generation

[0442] To supplement any missing nutrients, the server automatically generates appropriate meal plans. Furthermore, if you feel unwell, it will suggest possible illnesses and provide initial treatment options.

[0443] Presentation to the user

[0444] The generated meal menus and health information are presented to the user within the virtual store. Furthermore, information on nearby supermarkets, restaurants, and hospitals is included.

[0445] Emotional analysis and proposal adjustment

[0446] The emotion recognition engine analyzes the user's voice data and input to determine their emotional state. For example, if the system detects that the user is stressed, it adds suggestions for stress-reducing meals and activities.

[0447] Specific example

[0448] If user A enters "I had a café au lait and a croissant for lunch today," the server identifies a vitamin B deficiency. Simultaneously, the emotion recognition engine recognizes the user's stress level from their voice data. Based on this information, the server suggests "grilled chicken and avocado salad" and also notifies the user of nearby supermarkets.

[0449] Examples of prompts for a generative AI model:

[0450] "The user entered their meal plan and it was identified that they are deficient in B vitamins. Since the user is under stress, please suggest meal options that would help reduce stress."

[0451] Expected output:

[0452] "Grilled chicken and avocado salad would be good. Vitamin B complex and potassium are effective for stress reduction. You can buy these ingredients at your local supermarket."

[0453] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0454] Step 1:

[0455] The user puts on VR goggles and logs into the virtual store. They enter their user ID and password as login information. This allows the user to access the system, and the system obtains the user's identification information.

[0456] Step 2:

[0457] The user enters their meal menu and symptoms of illness. A speech recognition API (e.g., Google Speech-to-Text) is used to convert the voice data into text, inputting the meal menu and health status. The input data includes food names, time of consumption, and detailed symptoms. This input data is then sent to the server.

[0458] Step 3:

[0459] The server analyzes the received data. First, it extracts the nutritional components of the food using a dedicated nutrition database. Next, it uses a medical database to extract possible diseases based on the entered symptoms. The identified nutrient deficiencies and disease possibilities are the output of this step.

[0460] Step 4:

[0461] The server identifies deficient nutrients and generates meal plans to compensate for them. Using a generation AI model, it automatically generates menus to optimize the user's nutritional balance. The input here is the analyzed information on deficient nutrients, and the output is the recommended meal plan.

[0462] Step 5:

[0463] The server analyzes the user's emotional state. Using an emotion recognition engine (e.g., Azure Cognitive Services Emotion API), it analyzes the user's voice tone and input data to determine their emotional state. The input data can be voice or text, and the output is the user's emotional level (e.g., stress, joy, anger).

[0464] Step 6:

[0465] The server adjusts suggestions based on the user's emotional state. Based on the generated emotional analysis data, it optimizes meal menus and health advice to match the user's emotional state. For example, if a user is feeling stressed, it adds stress-reducing foods and relaxation methods to the menu.

[0466] Step 7:

[0467] This service searches for information on supermarkets, restaurants, and hospitals recommended by the server. Based on the user's location, it searches the internet for nearby stores and hospitals and provides the most suitable options for the user. The input is the user's location and suggested menus, and the output is a list of stores and hospitals.

[0468] Step 8:

[0469] The system provides users with generated meal menus and advice. The suggestions are displayed to the user within the virtual store, and notifications are also sent to other devices. This step utilizes a user-friendly interface, providing information in an intuitive and easily accessible manner.

[0470] Step 9:

[0471] The feedback function allows users to input feedback on their emotional state and physical condition after implementing the suggested actions. This enables the system to update the data, allowing for more accurate and personalized future suggestions. The input data is feedback information, and the output represents improvements in the system's analysis accuracy.

[0472] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating 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.

[0473] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0474] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0475] [Second Embodiment]

[0476] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0477] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0478] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0479] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0480] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0481] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0482] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0483] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0484] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0485] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0486] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0487] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. 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".

[0488] This invention is a system for users to manage and analyze their meal menus and minor health symptoms, and to provide appropriate meal suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[0489] 1. Overall System Overview

[0490] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user.

[0491] 2. Inputting meal menus and managing nutrition

[0492] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[0493] The server analyzes the received meal data and extracts nutrient information for each meal using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0494] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[0495] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[0496] 3. Support for initial medical consultation when feeling unwell

[0497] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[0498] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0499] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[0500] Specific example

[0501] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides the user with that menu. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0502] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[0503] Thus, a system that efficiently manages and analyzes users' dietary information and health status, and provides appropriate suggestions, is extremely useful in the advanced lifestyles of modern society.

[0504] The following describes the processing flow.

[0505] 1. Processing related to nutritional management of meals.

[0506] Step 1:

[0507] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[0508] Step 2:

[0509] The terminal verifies the meal menu data entered by the user, checking for any missing or inappropriate information.

[0510] Step 3:

[0511] The terminal sends the verified meal menu data to the server.

[0512] Step 4:

[0513] The server analyzes the data of the received meal menu.

[0514] Step 5:

[0515] The server uses its built-in nutritional database to identify the nutrients in each food item.

[0516] Step 6:

[0517] The server calculates the total daily nutrient intake based on the analysis results and compares it to the recommended daily intake standards.

[0518] Step 7:

[0519] The server identifies deficient nutrients based on comparisons with nutritional intake standards.

[0520] Step 8:

[0521] The server generates meal plans to supplement any missing nutrients.

[0522] Step 9:

[0523] The server sends the generated meal menu to the terminal.

[0524] Step 10:

[0525] The device searches for nearby supermarkets and restaurants based on the user's location information.

[0526] Step 11:

[0527] The device sends the search results to the server for filtering and optimization.

[0528] Step 12:

[0529] The server returns a list of the best places to shop to the device.

[0530] Step 13:

[0531] The device displays a list of optimal shopping destinations to the user.

[0532] 2. Procedures related to the initial consultation before hospital visit

[0533] Step 1:

[0534] The user enters their symptoms of illness (headache, sore throat, fever, etc.) into the terminal.

[0535] Step 2:

[0536] The terminal verifies the symptom data entered by the user and asks for additional information as needed.

[0537] Step 3:

[0538] The device sends complete symptom data to the server.

[0539] Step 4:

[0540] The server analyzes the received symptom data.

[0541] Step 5:

[0542] The server cross-references the data with its built-in medical database and generates a list of possible illnesses.

[0543] Step 6:

[0544] The server sends the generated disease list and initial countermeasures corresponding to the symptoms to the terminal.

[0545] Step 7:

[0546] The device displays a list of diseases and initial countermeasures to the user.

[0547] Step 8:

[0548] If a user wishes to receive a hospital consultation, they enter that information into the terminal.

[0549] Step 9:

[0550] The terminal sends the user's consultation request information and location information to the server.

[0551] Step 10:

[0552] The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for cases.

[0553] Step 11:

[0554] The server sends the generated list of hospitals to the terminal.

[0555] Step 12:

[0556] The terminal displays a list of the most suitable hospitals to the user.

[0557] (Example 1)

[0558] Next, we will describe Example 1. 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."

[0559] In today's busy lifestyle, proper nutritional management and appropriate responses to health problems are difficult. In particular, there is a lack of means for users to efficiently manage their diet and health status and quickly obtain necessary information. Furthermore, supplementing with appropriate nutrients, providing initial responses to health problems, and selecting the most suitable medical institution require specialized knowledge, making these tasks difficult for the average user. Therefore, there is a need for a system that allows users to easily and quickly manage their diet and health.

[0560] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0561] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting a store or restaurant based on the user's location information, means for the user to input any symptoms of poor health, means for the server to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable treatment facility based on the user's wishes and evaluations, and means for verifying the meal menu and symptom information entered by the user to check for any incomplete or inappropriate data. This enables the user to efficiently and effectively manage their diet and health.

[0562] A "user" refers to an individual or group that uses the system.

[0563] A "meal menu" refers to information that lists the types and quantities of food and beverages a user consumes.

[0564] "Means" refers to a method, device, or software used to perform a specific function or action.

[0565] A "server" refers to a computer system that receives requests from clients via a network, processes the necessary information, and responds.

[0566] "Nutrients" refer to components such as vitamins, minerals, proteins, fats, and carbohydrates that are necessary to maintain human health.

[0567] A "sales outlet" refers to a store where users can purchase the food ingredients and products they need.

[0568] "Dining places" refer to facilities such as restaurants and cafes where users can eat meals.

[0569] "Location information" refers to data that indicates the user's current geographical location.

[0570] "Symptoms" refer to the specific physical or psychological abnormalities that a user experiences when feeling unwell.

[0571] "Disease" refers to a condition in which health deteriorates due to abnormalities in bodily functions or organs.

[0572] A "treatment facility" refers to a place that provides medical care, such as a hospital, clinic, or medical office.

[0573] "Data" refers to a collection of numbers, characters, symbols, and other elements used to represent information.

[0574] This invention is a system that allows users to manage and analyze their meal menus and symptoms of poor health, and provides appropriate dietary suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[0575] Hardware and software configuration

[0576] In this system, users input their daily meal menus and symptoms of illness using devices such as smartphones and personal computers. The data entered by users is sent via the internet to a cloud-based server. On the server side, data analysis and suggestion generation are performed using specific software.

[0577] Device configuration

[0578] The user's device has a dedicated application installed for entering data on meals and symptoms. This application has fields for entering the food name, quantity, time of intake, and the severity and time of symptom onset.

[0579] Server Configuration

[0580] On the server side, the following software and databases are used to analyze the received data:

[0581] Nutritional databases (e.g., USDA National Nutrient Database): Used to analyze the nutritional content of meal menus.

[0582] Medical databases (e.g., MedlinePlus): Used to identify possible illnesses based on symptoms of illness.

[0583] Location databases (e.g., Google Maps API): Used to suggest nearby shops, restaurants, and medical facilities based on the user's location.

[0584] System operation

[0585] The operation of this system is outlined below:

[0586] 1. Data Entry: Users enter meal menus and symptoms of illness using their smartphones or computers. Meal menus include food names, quantities, and times of consumption, while symptoms include specific details of illnesses and the time they occurred.

[0587] 2. Data Transmission: The device transmits the entered data to the server via the internet. The transmitted data includes the user ID, input data, and location information.

[0588] 3. Data Analysis: The server analyzes the received data. In the case of meal menus, it uses a nutrition database to analyze nutrients and identify any nutrient deficiencies. In the case of illness, it uses a medical database to identify possible diseases.

[0589] 4. Suggestion Generation: Based on the analysis results, the server generates meal menus to supplement any deficient nutrients. If the user is unwell, it also suggests initial countermeasures tailored to their symptoms. Furthermore, based on location information, it suggests nearby shops, restaurants, and medical facilities.

[0590] 5. Provision to the user: The generated suggestions are provided to the user via their device. This allows the user to efficiently manage their diet and health.

[0591] Specific example

[0592] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that data to the server. The server uses a nutritional database to identify a deficiency in vitamin D and calcium and suggests "eating salmon steak and broccoli salad for dinner." At the same time, information about nearby stores is also displayed.

[0593] Furthermore, if a user enters "headache, sore throat, and 38-degree fever," the server uses its medical database to identify the possibility of a cold, influenza, or pharyngitis and suggests "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, the server will also suggest nearby hospitals with good reputations based on their location.

[0594] Example of a prompt

[0595] Meal menu management

[0596] Prompt: "I had one slice of toast and coffee for breakfast. Please analyze its nutrients and suggest a complementary dinner menu."

[0597] Measures to take when you are feeling unwell

[0598] Prompt: "I currently have a headache, sore throat, and a fever of 38 degrees Celsius. Please tell me what the possible illnesses are and what initial treatments I should take. Also, please recommend a nearby hospital with a good reputation."

[0599] In this way, the system enables users to efficiently manage and analyze information about their diet and health problems, and to provide optimal suggestions.

[0600] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0601] Step 1:

[0602] Users input their daily meal menus and symptoms of illness into a dedicated application using their smartphones or computers. The input data includes the name of the food, the quantity, the time of consumption, and the symptoms and the time of their onset.

[0603] Input: Information on meal menus and symptoms of illness

[0604] Output: Data entered into the terminal

[0605] Step 2:

[0606] The terminal packages the data entered by the user and sends it to the server via the internet. The transmitted data includes the user ID, information about meals or symptoms, and location information.

[0607] Input: Data entered by the user on the device.

[0608] Output: Packaged data sent to the server

[0609] Step 3:

[0610] The server receives the data and stores it in the database. The stored data is then retrieved for analysis.

[0611] Input: Data sent from the device

[0612] Output: Data stored on the server

[0613] Step 4:

[0614] For food data, the server uses an internal nutrition database to analyze the nutrients in each food item and calculate the total daily nutrient intake. For data related to poor health, it uses a medical database to identify possible illnesses.

[0615] Input: Meal data or symptom data stored on the server

[0616] Data processing / calculation: Analysis by cross-referencing with nutritional or medical databases.

[0617] Output: List of deficient nutrients or possible diseases

[0618] Step 5:

[0619] The server generates meal plans to supplement any nutritional deficiencies based on the analysis results. If the user is unwell, it generates initial countermeasures tailored to their symptoms.

[0620] Input: List of deficient nutrients or diseases

[0621] Data processing / data calculation: Generation of meal suggestions or initial countermeasures

[0622] Output: Meal suggestion menu or initial countermeasures

[0623] Step 6:

[0624] The server searches for shops, restaurants, and medical facilities based on the user's location information and provides this information to the user along with the analysis results.

[0625] Input: Location information, generated suggestion information

[0626] Data processing / data calculation: Location-based search and integration of suggestion information

[0627] Output: Location-based suggestion information

[0628] Step 7:

[0629] The terminal displays suggested information received from the server to the user. For meal suggestions, it displays specific menus and purchase locations; for health issues, it displays initial countermeasures and hospital information.

[0630] Input: Suggestion information sent from the server

[0631] Output: Displayed suggestion information

[0632] Step 8:

[0633] Users take action based on information suggested through their device. For example, if a meal is suggested, they prepare a meal based on the suggested menu; if they feel unwell, they take initial measures and visit a hospital if necessary.

[0634] Input: Suggested information

[0635] Output: User behavior

[0636] (Application Example 1)

[0637] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0638] In modern society, users need to manage their daily diets and symptoms of illness themselves for health management. However, it is not easy for them to find appropriate dietary suggestions or early countermeasures for symptoms on their own. Furthermore, there is a lack of systems that efficiently provide information on foods to supplement necessary nutrients and appropriate medical facilities. As a result, it is difficult for users to effectively maintain their health and take preventative measures against illness.

[0639] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0640] In this invention, the server includes means for analyzing the user's meal menu and identifying deficient nutrients, means for generating meal menus to supplement the deficient nutrients, and means for providing health supplements and medical information based on the analysis results. This enables the user to efficiently manage their daily diet and physical condition and to perform appropriate health management.

[0641] "Means for inputting meal menus" refers to devices or application functions that allow users to record or input their daily meal contents.

[0642] "Means for sending meal menus to the server" refers to a communication function for sending meal information entered by the user to a central server.

[0643] "Means for identifying deficient nutrients" refers to a function where the server analyzes the received meal information and identifies nutrients that the user is not consuming or is deficient in.

[0644] "Method for generating meal menus" refers to a function where the server creates new meal suggestions to supplement any missing nutrients.

[0645] "Means of providing meal menus to users" refers to a function for notifying or displaying generated meal suggestions to users.

[0646] The "means of searching for and suggesting places where ingredients can be purchased" refers to a function that uses the user's location information to search for and suggest places where the ingredients needed for the generated meal menu can be purchased.

[0647] "Means for inputting symptoms of poor health" refers to devices or application functions that allow users to record or input health problems related to their own or their family's physical condition.

[0648] "Means for sending symptoms to the server" refers to a communication function for sending health information entered by the user to a central server.

[0649] "Means of presenting possible illnesses" refers to a function that, based on the symptom information received by the server, lists possible illnesses and health problems and notifies the user.

[0650] "Means for searching for and suggesting medical institutions" refers to a function that searches for and provides appropriate hospitals and clinics to users based on their health condition and preferences.

[0651] "Means of providing health supplements and medical information" refers to a function that recommends appropriate supplements and medical institutions to address users' health conditions and nutritional deficiencies.

[0652] To realize this invention, a system is needed in which users manage and input their daily health information, and a server analyzes and makes suggestions based on that information. The system mainly consists of a terminal used by the user (such as a smartphone or computer) and a server that processes the data.

[0653] Hardware and software

[0654] 1. Hardware:

[0655] Smartphone: Used by users to record and transmit input data.

[0656] Server: A central processing unit for data analysis and proposal generation.

[0657] 2. Software:

[0658] Python: Used for data processing and API requests.

[0659] Requests library: Used for communication with APIs.

[0660] Geopy library: Used to obtain the user's location information.

[0661] Data processing and calculation flow

[0662] 1. User input:

[0663] Users input their daily meal menus and symptoms of illness into a smartphone app.

[0664] Regarding dietary information, details such as food names, quantities, and timing of consumption are included.

[0665] Information about feeling unwell includes symptoms such as headache, sore throat, and fever.

[0666] 2. Data transmission:

[0667] The user enters information and sends it from their smartphone to the server.

[0668] 3. Server analysis:

[0669] The server analyzes the received meal data and identifies any nutritional deficiencies.

[0670] The system utilizes a built-in nutrition database to extract nutrient information for each meal. Next, it calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0671] The server automatically generates meal plans to supplement any missing nutrients. The generated suggested menus include specific food names and their corresponding nutrients.

[0672] Furthermore, based on the symptom information entered by the user, the system cross-references it with a built-in medical database to generate a list of possible illnesses. It also provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0673] 4. Providing suggestions:

[0674] The created suggested menus, health supplements, and medical institution information are sent back from the server to the user's terminal and displayed.

[0675] At the same time, based on the user's location information, it provides information on stores where the suggested food items can be purchased and information on appropriate hospitals.

[0676] Specific example

[0677] For example, if a user enters, "I had one slice of toast and coffee for breakfast. Recently, I've had a headache, sore throat, and a fever of 38 degrees Celsius," the server will identify a deficiency in "vitamin D and calcium" and suggest "salmon steak and broccoli salad for dinner." At the same time, it will suggest the possibility of "a cold, the flu, or pharyngitis" and advise "drink plenty of fluids and rest." Based on the user's location, a list of the nearest supermarkets and highly-rated hospitals will also be provided.

[0678] Example of a generated AI prompt

[0679] Write code for a program that provides personalized suggestions based on the user's health status.

[0680] It has a function to input user dietary data and symptoms of illness.

[0681] Send data to the server for analysis and recommendations.

[0682] Based on the results, we will provide appropriate nutritional supplements and information on medical facilities.

[0683] Use location information to display nearby hospitals

[0684] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0685] Step 1:

[0686] The user inputs their meal menu. The user enters details of their daily meals (food name, quantity, time of consumption, etc.) into a device (smartphone, computer, etc.). This input data is formatted by the application.

[0687] Step 2:

[0688] The device sends meal data to the server. The meal information entered by the user is sent from the device to the server. In this process, the device often converts the input data into JSON format and sends it via an HTTP request.

[0689] Step 3:

[0690] The server analyzes the meal data. The server analyzes the received meal data and identifies any deficient nutrients. It extracts nutrient information for each meal using its built-in nutrition database. It calculates the total daily nutrient intake and identifies any deficiencies by comparing it to recommended nutritional intake standards.

[0691] Step 4:

[0692] The server generates meal plans that supplement any missing nutrients. The server creates new meal suggestions to address any nutritional deficiencies. This generation process automatically generates menus that include specific food names and corresponding nutrients, referencing a built-in recipe database.

[0693] Step 5:

[0694] The server generates a meal menu and provides it to the user. The generated meal menu is sent back from the server to the terminal and notified or displayed to the user. The user can review the suggested menu through the application.

[0695] Step 6:

[0696] The user enters their symptoms of illness. The user enters detailed information about their or their family member's illness (e.g., headache, sore throat, fever, etc.) into the device. This input data is also formatted by the application.

[0697] Step 7:

[0698] The terminal sends symptom data to the server. The symptom information entered by the user is sent from the terminal to the server. During this process, the terminal converts the input data into JSON format and sends it via an HTTP request.

[0699] Step 8:

[0700] The server analyzes the symptom data. Based on the received symptom information, the server compares it with its built-in medical database and generates a list of possible illnesses. Furthermore, it provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0701] Step 9:

[0702] The server searches for and suggests the most suitable medical institutions. Based on the user's health condition and preferences, the server searches for appropriate medical institutions and generates a list to provide to the user. This list is compiled considering factors such as hospital reputation and the success rate of cases.

[0703] Step 10:

[0704] The server generates a list of medical institutions and provides it to the user. The generated list of medical institutions is then sent back from the server to the terminal and notified or displayed to the user. The user can then review the suggested medical institutions through the application.

[0705] Step 11:

[0706] Based on the user's location information, the server suggests places where the product can be purchased and medical facilities. Using the user's location information, the server provides information on stores where the suggested food product can be purchased and appropriate medical facilities. This information is generated through database lookup and location data analysis.

[0707] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0708] This invention combines a system that manages and analyzes a user's meal menu and minor health symptoms, providing appropriate meal suggestions and useful information before hospital visits, with an emotion engine that recognizes the user's emotions. This system mainly consists of a terminal used by the user, a server that processes data, and an emotion engine that acquires and analyzes emotional data.

[0709] 1. Overall System Overview

[0710] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user. An emotion engine analyzes the user's emotional state and provides appropriate responses accordingly.

[0711] 2. Inputting meal menus and managing nutrition

[0712] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[0713] The server analyzes the received meal data and extracts nutrient information for each food item using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0714] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[0715] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[0716] 3. Support for initial medical consultation when feeling unwell

[0717] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[0718] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0719] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[0720] 4. Emotion recognition by an emotion engine

[0721] When a user enters meal menus or symptom information, the emotion engine activates and analyzes the user's emotional state from their voice tone and input content. The emotion engine recognizes emotions such as joy, sadness, stress, and anger.

[0722] The acquired emotional data is sent to a server, which adjusts the suggestions based on the user's emotional state. For example, if a user is feeling stressed, they will be offered advice on stress-reducing foods and relaxation techniques. Suggestions for when the user is feeling unwell will also take their emotional state into consideration.

[0723] Specific example

[0724] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides this menu to the user through the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0725] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[0726] Furthermore, if the emotion engine detects that the user is experiencing stress during input, it will simultaneously provide advice on foods and behaviors that are effective in reducing stress. In this way, utilizing emotion recognition enables more personalized care.

[0727] The following describes the processing flow.

[0728] 1. Processing related to nutritional management of meals.

[0729] Step 1:

[0730] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[0731] Step 2:

[0732] The terminal verifies the data entered by the user to check for incomplete or incorrect information.

[0733] Step 3:

[0734] The terminal sends the verified meal menu data to the server.

[0735] Step 4:

[0736] The server analyzes the data of the received meal menu.

[0737] Step 5:

[0738] The server uses a nutrition database to identify the nutritional information of each food item.

[0739] Step 6:

[0740] The server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to standard nutritional intakes.

[0741] Step 7:

[0742] The server generates meal plans to supplement any missing nutrients.

[0743] Step 8:

[0744] The server sends the generated meal menu to the terminal.

[0745] Step 9:

[0746] The terminal displays the generated meal menu to the user.

[0747] Step 10:

[0748] The device sends data to a server based on the user's location information to search for nearby supermarkets and restaurants.

[0749] Step 11:

[0750] The server searches for the best supermarkets and restaurants and sends that information back to the terminal.

[0751] Step 12:

[0752] The device displays search results to the user and suggests places where recommended foods can be purchased.

[0753] 2. Procedures for initial medical examination in case of illness

[0754] Step 1:

[0755] The user enters detailed information about their symptoms (e.g., headache, sore throat, fever, etc.) into the device.

[0756] Step 2:

[0757] The terminal verifies the symptoms entered by the user and asks for additional information as needed.

[0758] Step 3:

[0759] The device sends complete symptom data to the server.

[0760] Step 4:

[0761] The server analyzes the received symptom data.

[0762] Step 5:

[0763] The server cross-references the information with a medical database and generates a list of possible illnesses.

[0764] Step 6:

[0765] The server sends the generated disease list and initial response information to the terminal.

[0766] Step 7:

[0767] The device displays a list of diseases and initial countermeasures to the user.

[0768] Step 8:

[0769] If a user wishes to schedule a hospital appointment, they enter that information into the terminal.

[0770] Step 9:

[0771] The terminal transmits the user's consultation request information and location information to the server.

[0772] Step 10:

[0773] The server generates a list of optimal hospitals, taking into account the user's desired treatment, hospital reputation, and the cure rate for cases.

[0774] Step 11:

[0775] The server sends the generated hospital list to the terminal.

[0776] Step 12:

[0777] The terminal displays a list of suitable hospitals to the user and assists with the appointment booking process.

[0778] 3. Processing related to emotion recognition by the emotion engine

[0779] Step 1:

[0780] When a user enters meal menus or symptom information into the terminal, the emotion engine automatically activates to analyze the user's emotional state while they are entering the information.

[0781] Step 2:

[0782] The emotion engine acquires emotion data from the user's voice tone and input content.

[0783] Step 3:

[0784] The device sends the acquired emotion data to the server.

[0785] Step 4:

[0786] The server analyzes emotional data and adjusts the content of its meal menu and disease predictions based on the user's emotional state.

[0787] Step 5:

[0788] The server generates optimal menus and advice based on sentiment data.

[0789] Step 6:

[0790] The server sends the generated suggestions to the terminal.

[0791] Step 7:

[0792] The device displays meal menus and advice tailored to the user's emotional state.

[0793] Specific example

[0794] For example, if a user inputs "I had one slice of toast and coffee for breakfast," the device sends this information to the server, which analyzes it and identifies a deficiency in "vitamin D" and "calcium." The server then suggests "salmon steak and broccoli salad for dinner" and provides this menu to the user via the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0795] On another day, if a user enters "headache, sore throat, and 38-degree fever," the server suggests the possibility of "cold, flu, or pharyngitis" and recommends "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases is provided.

[0796] Furthermore, if the emotion engine is activated and recognizes that the user is experiencing stress during input, it will also provide advice on foods that are effective in reducing stress and relaxation techniques. In this way, utilizing emotion recognition enables more personalized care.

[0797] (Example 2)

[0798] Next, we will describe Example 2. 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".

[0799] Current meal and health management systems are insufficient in managing nutrients and analyzing symptoms, and they fail to provide individualized support that takes into account the user's emotional state. As a result, users often do not receive appropriate nutritional support or timely, appropriate medical care. Furthermore, there is a need for systems that can address not only nutrient deficiencies and potential illnesses, but also the stress and other emotions that users are experiencing.

[0800] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server with the generated meal menu to the user, means for searching for and suggesting sales facilities or restaurants based on the user's location information, means for the user to input symptoms of poor health, means for the user to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable medical facility based on the user's preferences and reputation, means for the emotion engine to recognize the emotional state when the user inputs meal menu and symptom information, means for the emotion engine to transmit the analyzed emotional data to the server, and means for the server to adjust the suggested content based on the emotional state. This will not only enable users to properly replenish the nutrients they need for diet and health management, but also allow them to receive prompt and appropriate medical care when they are unwell, and furthermore, enable personalized support tailored to their emotional state.

[0801] A "user" refers to an individual who uses this system to manage their diet and health.

[0802] A "terminal" refers to a device used by a user to input data and communicate with a server. Examples include smartphones and personal computers.

[0803] A "server" refers to a computer system that receives data sent by a user, analyzes and processes it, and provides the results.

[0804] "Meal menu" refers to the detailed information about meals entered by the user. Specifically, this includes the name of the food, the quantity, and the time of consumption.

[0805] "Nutrients" refer to components found in food that are necessary for maintaining bodily functions. Examples include vitamins, calcium, and protein.

[0806] "Symptoms" refer to physical abnormalities or discomforts that a user experiences when feeling unwell. Examples include headaches, sore throats, and fever.

[0807] An "emotion engine" refers to a technology that analyzes a user's emotional state from their input or voice.

[0808] A "sales facility" refers to a place where you can buy ingredients and food products. Examples include supermarkets and grocery stores.

[0809] A "food and beverage establishment" refers to a place where users can eat. This includes, for example, restaurants and cafes.

[0810] A "medical facility" refers to a place that provides diagnosis and treatment for illnesses and health problems. Examples include hospitals and clinics.

[0811] "Generative AI models" refer to artificial intelligence technologies that provide appropriate suggestions and analyses based on user requests.

[0812] A "prompt sentence" refers to an instruction or question that is input into a generative AI model. Examples include sentences requesting meal menu suggestions or sentences requesting symptom analysis.

[0813] This invention relates to a system that manages and analyzes a user's meal menu and symptoms of poor health, and provides appropriate meal suggestions and medical information. This system further achieves more personalized care by incorporating an emotion engine that recognizes the user's emotions.

[0814] This system primarily consists of a user terminal, a server that processes data, and an emotion engine that acquires and analyzes emotional data. The overall system flow begins with the user entering their meal menu or symptoms of illness into the terminal and sending that data to the server. The server analyzes this data, generates appropriate suggestions, and finally delivers them to the user through the terminal.

[0815] The terminal uses common devices such as smartphones and personal computers. Users input meal menus and symptom information into the terminal, and the terminal sends this information to the server. Examples of software used include web browsers and dedicated applications.

[0816] The server incorporates various databases (nutrition database, medical database, sentiment analysis database) and uses them for data analysis and processing. For example, FoodData Central is commonly used for the nutrition database, and general medical information is stored in the medical database. Furthermore, Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding are used for the sentiment engine. The server uses Python's pandas library and the NLP library spaCy to analyze data received from users.

[0817] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that information to the server. The server analyzes the data and identifies a deficiency in "vitamin D" and "calcium," and based on that, suggests "salmon steak and broccoli salad for dinner." It also uses the user's location information to show where these ingredients can be purchased at the nearest supermarket.

[0818] If a user is feeling unwell and enters "headache, sore throat, and 38-degree fever," the server will suggest possibilities such as "cold," "flu," or "pharyngitis," and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, the server will list nearby medical facilities with good reputations based on the user's location and preferences, and provide this information to the user via their device.

[0819] As an example of analysis by the emotion engine, if a user enters "I've been really busy with work lately and feeling stressed" when inputting meal menus or symptom information, the emotion engine analyzes the text and recognizes that the user is feeling stressed. Based on this, the server provides stress-reducing foods (for example, chamomile tea) and relaxation advice.

[0820] Examples of prompts generated using a generative AI model include the following:

[0821] mark down

[0822] Please analyze the following dietary information and suggest a daily meal plan to identify any nutritional deficiencies and supplement them.

[0823] Meal information: Had one slice of toast and coffee for breakfast.

[0824] mark down

[0825] Please analyze the following symptom information, provide a list of possible illnesses, and suggest initial countermeasures.

[0826] Symptoms: Headache and sore throat, fever of 38 degrees Celsius.

[0827] mark down

[0828] The user made the following request: "Please use an emotion engine to analyze my emotional state (joy, sadness, stress, anger, etc.) and suggest appropriate countermeasures."

[0829] Statement: Lately, I feel like I'm stressed because work has been so busy.

[0830] Thus, this system not only manages nutrition and health based on the meal menus and symptom information entered by the user, but also enables personalized responses that take into account the user's emotional state.

[0831] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0832] Step 1: Enter and submit your meal menu.

[0833] Users input meal menus using their smartphones or PCs. Specifically, they input information such as, "I had one slice of toast and coffee for breakfast." The device sends this input information to the server. The output is the server receiving the meal menu entered by the user.

[0834] Step 2: Analysis of meal plans and identification of nutritional deficiencies

[0835] The server analyzes the received meal menu. First, it reads the received data into a DataFrame using the pandas library and extracts nutrient information for each food item from a nutrition database (e.g., FoodData Central). Next, it calculates the total daily nutrient intake and compares it to the recommended daily intake. Based on this comparison, it identifies any deficient nutrients. The input is the meal menu entered and submitted by the user, and the output is a list of identified deficient nutrients.

[0836] Step 3: Generating complementary meal menus

[0837] The server generates meal plans to supplement identified nutrient deficiencies. Specifically, it uses Python's scikit-learn to build a machine learning model for recipe suggestions and generates specific food suggestions to supplement the missing nutrients (e.g., "Salmon steak and broccoli salad for dinner"). The input is a list of the missing nutrients, and the output is the generated supplementary meal plan.

[0838] Step 4: Suggesting places to buy groceries

[0839] The server uses the user's location information based on the generated meal menu to search for nearby retail and dining establishments. Specifically, it uses the Google Places API to list stores where the necessary ingredients can be purchased. This information is then provided to the user via their device. The input is the generated meal menu and the user's location information, and the output is a list of suggested places to buy.

[0840] Step 5: Enter and submit your symptoms.

[0841] The user enters their symptoms into the terminal. Specifically, they enter detailed symptom information such as "headache, sore throat, and a fever of 38 degrees Celsius." The terminal sends this symptom information to the server. The output is the user's entered symptom information sent to the server.

[0842] Step 6: Analysis of symptom information and presentation of possibilities

[0843] The server analyzes the received symptoms. Using an NLP library (e.g., spaCy), it analyzes the symptom information and compares it with a medical database. It generates a list of possible illnesses and suggests appropriate initial countermeasures (e.g., "Drink plenty of fluids and rest"). The input is the symptom information entered and submitted by the user, and the output is the likelihood of possible illnesses and initial countermeasures.

[0844] Step 7: Propose hospital information

[0845] When a user requests a medical consultation, the device sends their request information and location to the server. The server uses the Google Maps API to search for nearby medical facilities and generates a list of the best hospitals based on reputation and success rates. This list is then provided to the user via the device. The input is the user's consultation request information and location, and the output is a list of suggested hospitals.

[0846] Step 8: Input and analysis of emotional data

[0847] When a user enters meal menus or symptom information, the emotion engine activates and analyzes their emotional state from the input content and tone of voice. It uses Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding to generate emotion data. The server receives this emotion data and adjusts the suggestions based on the estimated emotional state. The input is the user's emotional state, and the output is the analyzed emotional state.

[0848] Step 9: Adjusting proposals based on emotional state

[0849] The server adjusts the suggested meal menus and medical information based on the user's emotional state, using the results of the emotion engine's analysis. For example, if the user is feeling stressed, it will provide stress-reducing foods and relaxation advice. This enables more personalized care. The input is the analysis results from the emotion engine, and the output is the adjusted suggestions.

[0850] Through the processing steps described above, this system comprehensively supports the user's dietary and health management, and provides personalized support tailored to their emotional state.

[0851] (Application Example 2)

[0852] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0853] In today's busy lifestyle, it is difficult for individuals to properly manage their own nutritional balance and health. Furthermore, receiving personalized advice on diet and health is time-consuming and requires direct support from a specialist. Moreover, few health management systems take into account the user's emotional state, and personalized suggestions tailored to those emotions are needed. Therefore, there is a need for a system that allows users to efficiently manage their diet and health and receive detailed advice that reflects their emotional state.

[0854] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0855] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting supermarkets or restaurants based on the user's location information, means for the user to input and view information within a virtual store through a virtual reality device, means for analyzing the user's emotional state using an emotion recognition engine, and means for adjusting the suggested meal menu and advice based on the emotional state. As a result, the user can more efficiently manage their health and eating habits and receive personalized advice tailored to their emotional state.

[0856] "Methods for inputting meal menus" refers to interfaces that allow users to directly input details of their meals into a device, and this includes text input and voice input.

[0857] "Means of sending to a server" refers to infrastructure that has the function of sending data entered by a user to a remote server via the internet.

[0858] "Methods for analyzing meal menus" refers to software or hardware that analyzes the nutrient content and composition based on meal data received by a server, and identifies any deficient nutrients.

[0859] "Method for generating meal menus" refers to an algorithm and software that enables a server to automatically generate appropriate meal menus to supplement identified nutritional deficiencies.

[0860] "Means of providing to the user" refers to means of presenting the generated meal menu and related information to the user's device, and this includes display and audio notifications.

[0861] The "means for searching for and suggesting supermarkets or restaurants" refers to a system that uses the user's location information to search the internet for information on stores and restaurants where suggested food items or dishes can be purchased, and then notifies the user.

[0862] A "virtual reality device" is a device, such as a head-mounted display or VR goggles, that allows users to enter a virtual space and realistically recreates the experience of being in a virtual store.

[0863] An "emotion recognition engine" is a software system that uses artificial intelligence to analyze a user's voice and input data and determine the emotional state contained within it.

[0864] A "means for analyzing emotional states" refers to a system that analyzes a user's emotional state from their input data and behavior, and transmits that information to a server.

[0865] "Means for adjusting suggested meal menus and advice" refers to a system that customizes the content of meal menus and health advice to best suit the user based on their analyzed emotional state.

[0866] This invention is a system that allows users to input meal menus and symptoms of illness, and then provides nutritional management and health advice based on that input. Furthermore, it can analyze the user's emotional state and make suggestions accordingly. This system can be implemented using a smartphone, personal computer, or virtual reality device (such as VR goggles or a head-mounted display).

[0867] System Overview

[0868] 1. The user enters their meal menu and symptoms of illness into the device.

[0869] 2. The entered data is sent to the server via the internet.

[0870] 3. The server analyzes the data to identify potential nutrient deficiencies or health problems.

[0871] 4. Generate dietary suggestions to supplement necessary nutrients and create appropriate initial countermeasures.

[0872] 5. Provide users with suggestions and information on supermarkets, restaurants, or hospitals.

[0873] 6. The emotion recognition engine analyzes the user's emotional state and adjusts the suggested content accordingly.

[0874] Hardware and software to be used

[0875] Virtual reality devices: Oculus Rift, HTC Vive, Sony PlayStation VR, etc.

[0876] Speech-to-Text API: Google Speech-to-Text

[0877] Emotion recognition engine: Azure Cognitive Services Emotion API

[0878] Server-side frameworks: Django, Flask

[0879] Data analysis and management: Dedicated nutritional and medical databases

[0880] Language processing solutions: Google Cloud Natural Language API

[0881] Program Processing Overview

[0882] User input

[0883] The user puts on VR goggles, logs into a virtual store, and uses a voice recognition API to input their meal order and health status. For example, they might say, "I had toast and coffee for breakfast today."

[0884] Data transmission

[0885] The input data is transmitted to the server in real time via the internet. The server receives the transmitted data and proceeds to the next analysis step.

[0886] Data Analysis

[0887] The server analyzes the received dietary and symptom data. Here, it uses dedicated nutritional and medical databases to identify nutrient content and possible diseases.

[0888] Proposal generation

[0889] To supplement any missing nutrients, the server automatically generates appropriate meal plans. Furthermore, if you feel unwell, it will suggest possible illnesses and provide initial treatment options.

[0890] Presentation to the user

[0891] The generated meal menus and health information are presented to the user within the virtual store. Furthermore, information on nearby supermarkets, restaurants, and hospitals is included.

[0892] Emotional analysis and proposal adjustment

[0893] The emotion recognition engine analyzes the user's voice data and input to determine their emotional state. For example, if the system detects that the user is stressed, it adds suggestions for stress-reducing meals and activities.

[0894] Specific example

[0895] If user A enters "I had a café au lait and a croissant for lunch today," the server identifies a vitamin B deficiency. Simultaneously, the emotion recognition engine recognizes the user's stress level from their voice data. Based on this information, the server suggests "grilled chicken and avocado salad" and also notifies the user of nearby supermarkets.

[0896] Examples of prompts for a generative AI model:

[0897] "The user entered their meal plan and it was identified that they are deficient in B vitamins. Since the user is under stress, please suggest meal options that would help reduce stress."

[0898] Expected output:

[0899] "Grilled chicken and avocado salad would be good. Vitamin B complex and potassium are effective for stress reduction. You can buy these ingredients at your local supermarket."

[0900] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0901] Step 1:

[0902] The user puts on VR goggles and logs into the virtual store. They enter their user ID and password as login information. This allows the user to access the system, and the system obtains the user's identification information.

[0903] Step 2:

[0904] The user enters their meal menu and symptoms of illness. A speech recognition API (e.g., Google Speech-to-Text) is used to convert the voice data into text, inputting the meal menu and health status. The input data includes food names, time of consumption, and detailed symptoms. This input data is then sent to the server.

[0905] Step 3:

[0906] The server analyzes the received data. First, it extracts the nutritional components of the food using a dedicated nutrition database. Next, it uses a medical database to extract possible diseases based on the entered symptoms. The identified nutrient deficiencies and disease possibilities are the output of this step.

[0907] Step 4:

[0908] The server identifies deficient nutrients and generates meal plans to compensate for them. Using a generation AI model, it automatically generates menus to optimize the user's nutritional balance. The input here is the analyzed information on deficient nutrients, and the output is the recommended meal plan.

[0909] Step 5:

[0910] The server analyzes the user's emotional state. Using an emotion recognition engine (e.g., Azure Cognitive Services Emotion API), it analyzes the user's voice tone and input data to determine their emotional state. The input data can be voice or text, and the output is the user's emotional level (e.g., stress, joy, anger).

[0911] Step 6:

[0912] The server adjusts suggestions based on the user's emotional state. Based on the generated emotional analysis data, it optimizes meal menus and health advice to match the user's emotional state. For example, if a user is feeling stressed, it adds stress-reducing foods and relaxation methods to the menu.

[0913] Step 7:

[0914] This service searches for information on supermarkets, restaurants, and hospitals recommended by the server. Based on the user's location, it searches the internet for nearby stores and hospitals and provides the most suitable options for the user. The input is the user's location and suggested menus, and the output is a list of stores and hospitals.

[0915] Step 8:

[0916] The system provides users with generated meal menus and advice. The suggestions are displayed to the user within the virtual store, and notifications are also sent to other devices. This step utilizes a user-friendly interface, providing information in an intuitive and easily accessible manner.

[0917] Step 9:

[0918] The feedback function allows users to input feedback on their emotional state and physical condition after implementing the suggested actions. This enables the system to update the data, allowing for more accurate and personalized future suggestions. The input data is feedback information, and the output represents improvements in the system's analysis accuracy.

[0919] 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 user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0920] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0921] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0922] [Third Embodiment]

[0923] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0924] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0925] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0926] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0927] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0928] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0929] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0930] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0931] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[0932] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0933] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0934] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0935] This invention is a system for users to manage and analyze their meal menus and minor health symptoms, and to provide appropriate meal suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[0936] 1. Overall System Overview

[0937] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user.

[0938] 2. Inputting meal menus and managing nutrition

[0939] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[0940] The server analyzes the received meal data and extracts nutrient information for each meal using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[0941] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[0942] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[0943] 3. Support for initial medical consultation when feeling unwell

[0944] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[0945] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[0946] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[0947] Specific example

[0948] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides the user with that menu. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[0949] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[0950] Thus, a system that efficiently manages and analyzes users' dietary information and health status, and provides appropriate suggestions, is extremely useful in the advanced lifestyles of modern society.

[0951] The following describes the processing flow.

[0952] 1. Processing related to nutritional management of meals.

[0953] Step 1:

[0954] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[0955] Step 2:

[0956] The terminal verifies the meal menu data entered by the user, checking for any missing or inappropriate information.

[0957] Step 3:

[0958] The terminal sends the verified meal menu data to the server.

[0959] Step 4:

[0960] The server analyzes the data of the received meal menu.

[0961] Step 5:

[0962] The server uses its built-in nutritional database to identify the nutrients in each food item.

[0963] Step 6:

[0964] The server calculates the total daily nutrient intake based on the analysis results and compares it to the recommended daily intake standards.

[0965] Step 7:

[0966] The server identifies deficient nutrients based on comparisons with nutritional intake standards.

[0967] Step 8:

[0968] The server generates meal plans to supplement any missing nutrients.

[0969] Step 9:

[0970] The server sends the generated meal menu to the terminal.

[0971] Step 10:

[0972] The device searches for nearby supermarkets and restaurants based on the user's location information.

[0973] Step 11:

[0974] The device sends the search results to the server for filtering and optimization.

[0975] Step 12:

[0976] The server returns a list of the best places to shop to the device.

[0977] Step 13:

[0978] The device displays a list of optimal shopping destinations to the user.

[0979] 2. Procedures related to the initial consultation before hospital visit

[0980] Step 1:

[0981] The user enters their symptoms of illness (headache, sore throat, fever, etc.) into the terminal.

[0982] Step 2:

[0983] The terminal verifies the symptom data entered by the user and asks for additional information as needed.

[0984] Step 3:

[0985] The device sends complete symptom data to the server.

[0986] Step 4:

[0987] The server analyzes the received symptom data.

[0988] Step 5:

[0989] The server cross-references the data with its built-in medical database and generates a list of possible illnesses.

[0990] Step 6:

[0991] The server sends the generated disease list and initial countermeasures corresponding to the symptoms to the terminal.

[0992] Step 7:

[0993] The device displays a list of diseases and initial countermeasures to the user.

[0994] Step 8:

[0995] If a user wishes to receive a hospital consultation, they enter that information into the terminal.

[0996] Step 9:

[0997] The terminal sends the user's consultation request information and location information to the server.

[0998] Step 10:

[0999] The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for cases.

[1000] Step 11:

[1001] The server sends the generated list of hospitals to the terminal.

[1002] Step 12:

[1003] The terminal displays a list of the most suitable hospitals to the user.

[1004] (Example 1)

[1005] Next, we will describe Example 1. 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."

[1006] In today's busy lifestyle, proper nutritional management and appropriate responses to health problems are difficult. In particular, there is a lack of means for users to efficiently manage their diet and health status and quickly obtain necessary information. Furthermore, supplementing with appropriate nutrients, providing initial responses to health problems, and selecting the most suitable medical institution require specialized knowledge, making these tasks difficult for the average user. Therefore, there is a need for a system that allows users to easily and quickly manage their diet and health.

[1007] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1008] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting a store or restaurant based on the user's location information, means for the user to input any symptoms of poor health, means for the server to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable treatment facility based on the user's wishes and evaluations, and means for verifying the meal menu and symptom information entered by the user to check for any incomplete or inappropriate data. This enables the user to efficiently and effectively manage their diet and health.

[1009] A "user" refers to an individual or group that uses the system.

[1010] A "meal menu" refers to information that lists the types and quantities of food and beverages a user consumes.

[1011] "Means" refers to a method, device, or software used to perform a specific function or action.

[1012] A "server" refers to a computer system that receives requests from clients via a network, processes the necessary information, and responds.

[1013] "Nutrients" refer to components such as vitamins, minerals, proteins, fats, and carbohydrates that are necessary to maintain human health.

[1014] A "sales outlet" refers to a store where users can purchase the food ingredients and products they need.

[1015] "Dining places" refer to facilities such as restaurants and cafes where users can eat meals.

[1016] "Location information" refers to data that indicates the user's current geographical location.

[1017] "Symptoms" refer to the specific physical or psychological abnormalities that a user experiences when feeling unwell.

[1018] "Disease" refers to a condition in which health deteriorates due to abnormalities in bodily functions or organs.

[1019] A "treatment facility" refers to a place that provides medical care, such as a hospital, clinic, or medical office.

[1020] "Data" refers to a collection of numbers, characters, symbols, and other elements used to represent information.

[1021] This invention is a system that allows users to manage and analyze their meal menus and symptoms of poor health, and provides appropriate dietary suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[1022] Hardware and software configuration

[1023] In this system, users input their daily meal menus and symptoms of illness using devices such as smartphones and personal computers. The data entered by users is sent via the internet to a cloud-based server. On the server side, data analysis and suggestion generation are performed using specific software.

[1024] Device configuration

[1025] The user's device has a dedicated application installed for entering data on meals and symptoms. This application has fields for entering the food name, quantity, time of intake, and the severity and time of symptom onset.

[1026] Server Configuration

[1027] On the server side, the following software and databases are used to analyze the received data:

[1028] Nutritional databases (e.g., USDA National Nutrient Database): Used to analyze the nutritional content of meal menus.

[1029] Medical databases (e.g., MedlinePlus): Used to identify possible illnesses based on symptoms of illness.

[1030] Location databases (e.g., Google Maps API): Used to suggest nearby shops, restaurants, and medical facilities based on the user's location.

[1031] System operation

[1032] The operation of this system is outlined below:

[1033] 1. Data Entry: Users enter meal menus and symptoms of illness using their smartphones or computers. Meal menus include food names, quantities, and times of consumption, while symptoms include specific details of illnesses and the time they occurred.

[1034] 2. Data Transmission: The device transmits the entered data to the server via the internet. The transmitted data includes the user ID, input data, and location information.

[1035] 3. Data Analysis: The server analyzes the received data. In the case of meal menus, it uses a nutrition database to analyze nutrients and identify any nutrient deficiencies. In the case of illness, it uses a medical database to identify possible diseases.

[1036] 4. Suggestion Generation: Based on the analysis results, the server generates meal menus to supplement any deficient nutrients. If the user is unwell, it also suggests initial countermeasures tailored to their symptoms. Furthermore, based on location information, it suggests nearby shops, restaurants, and medical facilities.

[1037] 5. Provision to the user: The generated suggestions are provided to the user via their device. This allows the user to efficiently manage their diet and health.

[1038] Specific example

[1039] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that data to the server. The server uses a nutritional database to identify a deficiency in vitamin D and calcium and suggests "eating salmon steak and broccoli salad for dinner." At the same time, information about nearby stores is also displayed.

[1040] Furthermore, if a user enters "headache, sore throat, and 38-degree fever," the server uses its medical database to identify the possibility of a cold, influenza, or pharyngitis and suggests "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, the server will also suggest nearby hospitals with good reputations based on their location.

[1041] Example of a prompt

[1042] Meal menu management

[1043] Prompt: "I had one slice of toast and coffee for breakfast. Please analyze its nutrients and suggest a complementary dinner menu."

[1044] Measures to take when you are feeling unwell

[1045] Prompt: "I currently have a headache, sore throat, and a fever of 38 degrees Celsius. Please tell me what the possible illnesses are and what initial treatments I should take. Also, please recommend a nearby hospital with a good reputation."

[1046] In this way, the system enables users to efficiently manage and analyze information about their diet and health problems, and to provide optimal suggestions.

[1047] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1048] Step 1:

[1049] Users input their daily meal menus and symptoms of illness into a dedicated application using their smartphones or computers. The input data includes the name of the food, the quantity, the time of consumption, and the symptoms and the time of their onset.

[1050] Input: Information on meal menus and symptoms of illness

[1051] Output: Data entered into the terminal

[1052] Step 2:

[1053] The terminal packages the data entered by the user and sends it to the server via the internet. The transmitted data includes the user ID, information about meals or symptoms, and location information.

[1054] Input: Data entered by the user on the device.

[1055] Output: Packaged data sent to the server

[1056] Step 3:

[1057] The server receives the data and stores it in the database. The stored data is then retrieved for analysis.

[1058] Input: Data sent from the device

[1059] Output: Data stored on the server

[1060] Step 4:

[1061] For food data, the server uses an internal nutrition database to analyze the nutrients in each food item and calculate the total daily nutrient intake. For data related to poor health, it uses a medical database to identify possible illnesses.

[1062] Input: Meal data or symptom data stored on the server

[1063] Data processing / calculation: Analysis by cross-referencing with nutritional or medical databases.

[1064] Output: List of deficient nutrients or possible diseases

[1065] Step 5:

[1066] The server generates meal plans to supplement any nutritional deficiencies based on the analysis results. If the user is unwell, it generates initial countermeasures tailored to their symptoms.

[1067] Input: List of deficient nutrients or diseases

[1068] Data processing / data calculation: Generation of meal suggestions or initial countermeasures

[1069] Output: Meal suggestion menu or initial countermeasures

[1070] Step 6:

[1071] The server searches for shops, restaurants, and medical facilities based on the user's location information and provides this information to the user along with the analysis results.

[1072] Input: Location information, generated suggestion information

[1073] Data processing / data calculation: Location-based search and integration of suggestion information

[1074] Output: Location-based suggestion information

[1075] Step 7:

[1076] The terminal displays suggested information received from the server to the user. For meal suggestions, it displays specific menus and purchase locations; for health issues, it displays initial countermeasures and hospital information.

[1077] Input: Suggestion information sent from the server

[1078] Output: Displayed suggestion information

[1079] Step 8:

[1080] Users take action based on information suggested through their device. For example, if a meal is suggested, they prepare a meal based on the suggested menu; if they feel unwell, they take initial measures and visit a hospital if necessary.

[1081] Input: Suggested information

[1082] Output: User behavior

[1083] (Application Example 1)

[1084] Next, we will explain Application Example 1. In the following explanation, 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."

[1085] In modern society, users need to manage their daily diets and symptoms of illness themselves for health management. However, it is not easy for them to find appropriate dietary suggestions or early countermeasures for symptoms on their own. Furthermore, there is a lack of systems that efficiently provide information on foods to supplement necessary nutrients and appropriate medical facilities. As a result, it is difficult for users to effectively maintain their health and take preventative measures against illness.

[1086] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1087] In this invention, the server includes means for analyzing the user's meal menu and identifying deficient nutrients, means for generating meal menus to supplement the deficient nutrients, and means for providing health supplements and medical information based on the analysis results. This enables the user to efficiently manage their daily diet and physical condition and to perform appropriate health management.

[1088] "Means for inputting meal menus" refers to devices or application functions that allow users to record or input their daily meal contents.

[1089] "Means for sending meal menus to the server" refers to a communication function for sending meal information entered by the user to a central server.

[1090] "Means for identifying deficient nutrients" refers to a function where the server analyzes the received meal information and identifies nutrients that the user is not consuming or is deficient in.

[1091] "Method for generating meal menus" refers to a function where the server creates new meal suggestions to supplement any missing nutrients.

[1092] "Means of providing meal menus to users" refers to a function for notifying or displaying generated meal suggestions to users.

[1093] The "means of searching for and suggesting places where ingredients can be purchased" refers to a function that uses the user's location information to search for and suggest places where the ingredients needed for the generated meal menu can be purchased.

[1094] "Means for inputting symptoms of poor health" refers to devices or application functions that allow users to record or input health problems related to their own or their family's physical condition.

[1095] "Means for sending symptoms to the server" refers to a communication function for sending health information entered by the user to a central server.

[1096] "Means of presenting possible illnesses" refers to a function that, based on the symptom information received by the server, lists possible illnesses and health problems and notifies the user.

[1097] "Means for searching for and suggesting medical institutions" refers to a function that searches for and provides appropriate hospitals and clinics to users based on their health condition and preferences.

[1098] "Means of providing health supplements and medical information" refers to a function that recommends appropriate supplements and medical institutions to address users' health conditions and nutritional deficiencies.

[1099] To realize this invention, a system is needed in which users manage and input their daily health information, and a server analyzes and makes suggestions based on that information. The system mainly consists of a terminal used by the user (such as a smartphone or computer) and a server that processes the data.

[1100] Hardware and software

[1101] 1. Hardware:

[1102] Smartphone: Used by users to record and transmit input data.

[1103] Server: A central processing unit for data analysis and proposal generation.

[1104] 2. Software:

[1105] Python: Used for data processing and API requests.

[1106] Requests library: Used for communication with APIs.

[1107] Geopy library: Used to obtain the user's location information.

[1108] Data processing and calculation flow

[1109] 1. User input:

[1110] Users input their daily meal menus and symptoms of illness into a smartphone app.

[1111] Regarding dietary information, details such as food names, quantities, and timing of consumption are included.

[1112] Information about feeling unwell includes symptoms such as headache, sore throat, and fever.

[1113] 2. Data transmission:

[1114] The user enters information and sends it from their smartphone to the server.

[1115] 3. Server analysis:

[1116] The server analyzes the received meal data and identifies any nutritional deficiencies.

[1117] The system utilizes a built-in nutrition database to extract nutrient information for each meal. Next, it calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[1118] The server automatically generates meal plans to supplement any missing nutrients. The generated suggested menus include specific food names and their corresponding nutrients.

[1119] Furthermore, based on the symptom information entered by the user, the system cross-references it with a built-in medical database to generate a list of possible illnesses. It also provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1120] 4. Providing suggestions:

[1121] The created suggested menus, health supplements, and medical institution information are sent back from the server to the user's terminal and displayed.

[1122] At the same time, based on the user's location information, it provides information on stores where the suggested food items can be purchased and information on appropriate hospitals.

[1123] Specific example

[1124] For example, if a user enters, "I had one slice of toast and coffee for breakfast. Recently, I've had a headache, sore throat, and a fever of 38 degrees Celsius," the server will identify a deficiency in "vitamin D and calcium" and suggest "salmon steak and broccoli salad for dinner." At the same time, it will suggest the possibility of "a cold, the flu, or pharyngitis" and advise "drink plenty of fluids and rest." Based on the user's location, a list of the nearest supermarkets and highly-rated hospitals will also be provided.

[1125] Example of a generated AI prompt

[1126] Write code for a program that provides personalized suggestions based on the user's health status.

[1127] It has a function to input user dietary data and symptoms of illness.

[1128] Send data to the server for analysis and recommendations.

[1129] Based on the results, we will provide appropriate nutritional supplements and information on medical facilities.

[1130] Use location information to display nearby hospitals

[1131] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1132] Step 1:

[1133] The user inputs their meal menu. The user enters details of their daily meals (food name, quantity, time of consumption, etc.) into a device (smartphone, computer, etc.). This input data is formatted by the application.

[1134] Step 2:

[1135] The device sends meal data to the server. The meal information entered by the user is sent from the device to the server. In this process, the device often converts the input data into JSON format and sends it via an HTTP request.

[1136] Step 3:

[1137] The server analyzes the meal data. The server analyzes the received meal data and identifies any deficient nutrients. It extracts nutrient information for each meal using its built-in nutrition database. It calculates the total daily nutrient intake and identifies any deficiencies by comparing it to recommended nutritional intake standards.

[1138] Step 4:

[1139] The server generates meal plans that supplement any missing nutrients. The server creates new meal suggestions to address any nutritional deficiencies. This generation process automatically generates menus that include specific food names and corresponding nutrients, referencing a built-in recipe database.

[1140] Step 5:

[1141] The server generates a meal menu and provides it to the user. The generated meal menu is sent back from the server to the terminal and notified or displayed to the user. The user can review the suggested menu through the application.

[1142] Step 6:

[1143] The user enters their symptoms of illness. The user enters detailed information about their or their family member's illness (e.g., headache, sore throat, fever, etc.) into the device. This input data is also formatted by the application.

[1144] Step 7:

[1145] The terminal sends symptom data to the server. The symptom information entered by the user is sent from the terminal to the server. During this process, the terminal converts the input data into JSON format and sends it via an HTTP request.

[1146] Step 8:

[1147] The server analyzes the symptom data. Based on the received symptom information, the server compares it with its built-in medical database and generates a list of possible illnesses. Furthermore, it provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1148] Step 9:

[1149] The server searches for and suggests the most suitable medical institutions. Based on the user's health condition and preferences, the server searches for appropriate medical institutions and generates a list to provide to the user. This list is compiled considering factors such as hospital reputation and the success rate of cases.

[1150] Step 10:

[1151] The server generates a list of medical institutions and provides it to the user. The generated list of medical institutions is then sent back from the server to the terminal and notified or displayed to the user. The user can then review the suggested medical institutions through the application.

[1152] Step 11:

[1153] Based on the user's location information, the server suggests places where the product can be purchased and medical facilities. Using the user's location information, the server provides information on stores where the suggested food product can be purchased and appropriate medical facilities. This information is generated through database lookup and location data analysis.

[1154] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1155] This invention combines a system that manages and analyzes a user's meal menu and minor health symptoms, providing appropriate meal suggestions and useful information before hospital visits, with an emotion engine that recognizes the user's emotions. This system mainly consists of a terminal used by the user, a server that processes data, and an emotion engine that acquires and analyzes emotional data.

[1156] 1. Overall System Overview

[1157] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user. An emotion engine analyzes the user's emotional state and provides appropriate responses accordingly.

[1158] 2. Inputting meal menus and managing nutrition

[1159] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[1160] The server analyzes the received meal data and extracts nutrient information for each food item using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[1161] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[1162] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[1163] 3. Support for initial medical consultation when feeling unwell

[1164] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[1165] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1166] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[1167] 4. Emotion recognition by an emotion engine

[1168] When a user enters meal menus or symptom information, the emotion engine activates and analyzes the user's emotional state from their voice tone and input content. The emotion engine recognizes emotions such as joy, sadness, stress, and anger.

[1169] The acquired emotional data is sent to a server, which adjusts the suggestions based on the user's emotional state. For example, if a user is feeling stressed, they will be offered advice on stress-reducing foods and relaxation techniques. Suggestions for when the user is feeling unwell will also take their emotional state into consideration.

[1170] Specific example

[1171] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides this menu to the user through the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[1172] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[1173] Furthermore, if the emotion engine detects that the user is experiencing stress during input, it will simultaneously provide advice on foods and behaviors that are effective in reducing stress. In this way, utilizing emotion recognition enables more personalized care.

[1174] The following describes the processing flow.

[1175] 1. Processing related to nutritional management of meals.

[1176] Step 1:

[1177] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[1178] Step 2:

[1179] The terminal verifies the data entered by the user to check for incomplete or incorrect information.

[1180] Step 3:

[1181] The terminal sends the verified meal menu data to the server.

[1182] Step 4:

[1183] The server analyzes the data of the received meal menu.

[1184] Step 5:

[1185] The server uses a nutrition database to identify the nutritional information of each food item.

[1186] Step 6:

[1187] The server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to standard nutritional intakes.

[1188] Step 7:

[1189] The server generates meal plans to supplement any missing nutrients.

[1190] Step 8:

[1191] The server sends the generated meal menu to the terminal.

[1192] Step 9:

[1193] The terminal displays the generated meal menu to the user.

[1194] Step 10:

[1195] The device sends data to a server based on the user's location information to search for nearby supermarkets and restaurants.

[1196] Step 11:

[1197] The server searches for the best supermarkets and restaurants and sends that information back to the terminal.

[1198] Step 12:

[1199] The device displays search results to the user and suggests places where recommended foods can be purchased.

[1200] 2. Procedures for initial medical examination in case of illness

[1201] Step 1:

[1202] The user enters detailed information about their symptoms (e.g., headache, sore throat, fever, etc.) into the device.

[1203] Step 2:

[1204] The terminal verifies the symptoms entered by the user and asks for additional information as needed.

[1205] Step 3:

[1206] The device sends complete symptom data to the server.

[1207] Step 4:

[1208] The server analyzes the received symptom data.

[1209] Step 5:

[1210] The server cross-references the information with a medical database and generates a list of possible illnesses.

[1211] Step 6:

[1212] The server sends the generated disease list and initial response information to the terminal.

[1213] Step 7:

[1214] The device displays a list of diseases and initial countermeasures to the user.

[1215] Step 8:

[1216] If a user wishes to schedule a hospital appointment, they enter that information into the terminal.

[1217] Step 9:

[1218] The terminal transmits the user's consultation request information and location information to the server.

[1219] Step 10:

[1220] The server generates a list of optimal hospitals, taking into account the user's desired treatment, hospital reputation, and the cure rate for cases.

[1221] Step 11:

[1222] The server sends the generated hospital list to the terminal.

[1223] Step 12:

[1224] The terminal displays a list of suitable hospitals to the user and assists with the appointment booking process.

[1225] 3. Processing related to emotion recognition by the emotion engine

[1226] Step 1:

[1227] When a user enters meal menus or symptom information into the terminal, the emotion engine automatically activates to analyze the user's emotional state while they are entering the information.

[1228] Step 2:

[1229] The emotion engine acquires emotion data from the user's voice tone and input content.

[1230] Step 3:

[1231] The device sends the acquired emotion data to the server.

[1232] Step 4:

[1233] The server analyzes emotional data and adjusts the content of its meal menu and disease predictions based on the user's emotional state.

[1234] Step 5:

[1235] The server generates optimal menus and advice based on sentiment data.

[1236] Step 6:

[1237] The server sends the generated suggestions to the terminal.

[1238] Step 7:

[1239] The device displays meal menus and advice tailored to the user's emotional state.

[1240] Specific example

[1241] For example, if a user inputs "I had one slice of toast and coffee for breakfast," the device sends this information to the server, which analyzes it and identifies a deficiency in "vitamin D" and "calcium." The server then suggests "salmon steak and broccoli salad for dinner" and provides this menu to the user via the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[1242] On another day, if a user enters "headache, sore throat, and 38-degree fever," the server suggests the possibility of "cold, flu, or pharyngitis" and recommends "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases is provided.

[1243] Furthermore, if the emotion engine is activated and recognizes that the user is experiencing stress during input, it will also provide advice on foods that are effective in reducing stress and relaxation techniques. In this way, utilizing emotion recognition enables more personalized care.

[1244] (Example 2)

[1245] Next, we will describe Example 2. 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."

[1246] Current meal and health management systems are insufficient in managing nutrients and analyzing symptoms, and they fail to provide individualized support that takes into account the user's emotional state. As a result, users often do not receive appropriate nutritional support or timely, appropriate medical care. Furthermore, there is a need for systems that can address not only nutrient deficiencies and potential illnesses, but also the stress and other emotions that users are experiencing.

[1247] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server with the generated meal menu to the user, means for searching for and suggesting sales facilities or restaurants based on the user's location information, means for the user to input symptoms of poor health, means for the user to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable medical facility based on the user's preferences and reputation, means for the emotion engine to recognize the emotional state when the user inputs meal menu and symptom information, means for the emotion engine to transmit the analyzed emotional data to the server, and means for the server to adjust the suggested content based on the emotional state. This will not only enable users to properly replenish the nutrients they need for diet and health management, but also allow them to receive prompt and appropriate medical care when they are unwell, and furthermore, enable personalized support tailored to their emotional state.

[1248] A "user" refers to an individual who uses this system to manage their diet and health.

[1249] A "terminal" refers to a device used by a user to input data and communicate with a server. Examples include smartphones and personal computers.

[1250] A "server" refers to a computer system that receives data sent by a user, analyzes and processes it, and provides the results.

[1251] "Meal menu" refers to the detailed information about meals entered by the user. Specifically, this includes the name of the food, the quantity, and the time of consumption.

[1252] "Nutrients" refer to components found in food that are necessary for maintaining bodily functions. Examples include vitamins, calcium, and protein.

[1253] "Symptoms" refer to physical abnormalities or discomforts that a user experiences when feeling unwell. Examples include headaches, sore throats, and fever.

[1254] An "emotion engine" refers to a technology that analyzes a user's emotional state from their input or voice.

[1255] A "sales facility" refers to a place where you can buy ingredients and food products. Examples include supermarkets and grocery stores.

[1256] A "food and beverage establishment" refers to a place where users can eat. This includes, for example, restaurants and cafes.

[1257] A "medical facility" refers to a place that provides diagnosis and treatment for illnesses and health problems. Examples include hospitals and clinics.

[1258] "Generative AI models" refer to artificial intelligence technologies that provide appropriate suggestions and analyses based on user requests.

[1259] A "prompt sentence" refers to an instruction or question that is input into a generative AI model. Examples include sentences requesting meal menu suggestions or sentences requesting symptom analysis.

[1260] This invention relates to a system that manages and analyzes a user's meal menu and symptoms of poor health, and provides appropriate meal suggestions and medical information. This system further achieves more personalized care by incorporating an emotion engine that recognizes the user's emotions.

[1261] This system primarily consists of a user terminal, a server that processes data, and an emotion engine that acquires and analyzes emotional data. The overall system flow begins with the user entering their meal menu or symptoms of illness into the terminal and sending that data to the server. The server analyzes this data, generates appropriate suggestions, and finally delivers them to the user through the terminal.

[1262] The terminal uses common devices such as smartphones and personal computers. Users input meal menus and symptom information into the terminal, and the terminal sends this information to the server. Examples of software used include web browsers and dedicated applications.

[1263] The server incorporates various databases (nutrition database, medical database, sentiment analysis database) and uses them for data analysis and processing. For example, FoodData Central is commonly used for the nutrition database, and general medical information is stored in the medical database. Furthermore, Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding are used for the sentiment engine. The server uses Python's pandas library and the NLP library spaCy to analyze data received from users.

[1264] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that information to the server. The server analyzes the data and identifies a deficiency in "vitamin D" and "calcium," and based on that, suggests "salmon steak and broccoli salad for dinner." It also uses the user's location information to show where these ingredients can be purchased at the nearest supermarket.

[1265] If a user is feeling unwell and enters "headache, sore throat, and 38-degree fever," the server will suggest possibilities such as "cold," "flu," or "pharyngitis," and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, the server will list nearby medical facilities with good reputations based on the user's location and preferences, and provide this information to the user via their device.

[1266] As an example of analysis by the emotion engine, if a user enters "I've been really busy with work lately and feeling stressed" when inputting meal menus or symptom information, the emotion engine analyzes the text and recognizes that the user is feeling stressed. Based on this, the server provides stress-reducing foods (for example, chamomile tea) and relaxation advice.

[1267] Examples of prompts generated using a generative AI model include the following:

[1268] mark down

[1269] Please analyze the following dietary information and suggest a daily meal plan to identify any nutritional deficiencies and supplement them.

[1270] Meal information: Had one slice of toast and coffee for breakfast.

[1271] mark down

[1272] Please analyze the following symptom information, provide a list of possible illnesses, and suggest initial countermeasures.

[1273] Symptoms: Headache and sore throat, fever of 38 degrees Celsius.

[1274] mark down

[1275] The user made the following request: "Please use an emotion engine to analyze my emotional state (joy, sadness, stress, anger, etc.) and suggest appropriate countermeasures."

[1276] Statement: Lately, I feel like I'm stressed because work has been so busy.

[1277] Thus, this system not only manages nutrition and health based on the meal menus and symptom information entered by the user, but also enables personalized responses that take into account the user's emotional state.

[1278] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1279] Step 1: Enter and submit your meal menu.

[1280] Users input meal menus using their smartphones or PCs. Specifically, they input information such as, "I had one slice of toast and coffee for breakfast." The device sends this input information to the server. The output is the server receiving the meal menu entered by the user.

[1281] Step 2: Analysis of meal plans and identification of nutritional deficiencies

[1282] The server analyzes the received meal menu. First, it reads the received data into a DataFrame using the pandas library and extracts nutrient information for each food item from a nutrition database (e.g., FoodData Central). Next, it calculates the total daily nutrient intake and compares it to the recommended daily intake. Based on this comparison, it identifies any deficient nutrients. The input is the meal menu entered and submitted by the user, and the output is a list of identified deficient nutrients.

[1283] Step 3: Generating complementary meal menus

[1284] The server generates meal plans to supplement identified nutrient deficiencies. Specifically, it uses Python's scikit-learn to build a machine learning model for recipe suggestions and generates specific food suggestions to supplement the missing nutrients (e.g., "Salmon steak and broccoli salad for dinner"). The input is a list of the missing nutrients, and the output is the generated supplementary meal plan.

[1285] Step 4: Suggesting places to buy groceries

[1286] The server uses the user's location information based on the generated meal menu to search for nearby retail and dining establishments. Specifically, it uses the Google Places API to list stores where the necessary ingredients can be purchased. This information is then provided to the user via their device. The input is the generated meal menu and the user's location information, and the output is a list of suggested places to buy.

[1287] Step 5: Enter and submit your symptoms.

[1288] The user enters their symptoms into the terminal. Specifically, they enter detailed symptom information such as "headache, sore throat, and a fever of 38 degrees Celsius." The terminal sends this symptom information to the server. The output is the user's entered symptom information sent to the server.

[1289] Step 6: Analysis of symptom information and presentation of possibilities

[1290] The server analyzes the received symptoms. Using an NLP library (e.g., spaCy), it analyzes the symptom information and compares it with a medical database. It generates a list of possible illnesses and suggests appropriate initial countermeasures (e.g., "Drink plenty of fluids and rest"). The input is the symptom information entered and submitted by the user, and the output is the likelihood of possible illnesses and initial countermeasures.

[1291] Step 7: Propose hospital information

[1292] When a user requests a medical consultation, the device sends their request information and location to the server. The server uses the Google Maps API to search for nearby medical facilities and generates a list of the best hospitals based on reputation and success rates. This list is then provided to the user via the device. The input is the user's consultation request information and location, and the output is a list of suggested hospitals.

[1293] Step 8: Input and analysis of emotional data

[1294] When a user enters meal menus or symptom information, the emotion engine activates and analyzes their emotional state from the input content and tone of voice. It uses Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding to generate emotion data. The server receives this emotion data and adjusts the suggestions based on the estimated emotional state. The input is the user's emotional state, and the output is the analyzed emotional state.

[1295] Step 9: Adjusting proposals based on emotional state

[1296] The server adjusts the suggested meal menus and medical information based on the user's emotional state, using the results of the emotion engine's analysis. For example, if the user is feeling stressed, it will provide stress-reducing foods and relaxation advice. This enables more personalized care. The input is the analysis results from the emotion engine, and the output is the adjusted suggestions.

[1297] Through the processing steps described above, this system comprehensively supports the user's dietary and health management, and provides personalized support tailored to their emotional state.

[1298] (Application Example 2)

[1299] Next, we will explain application example 2. In the following explanation, 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."

[1300] In today's busy lifestyle, it is difficult for individuals to properly manage their own nutritional balance and health. Furthermore, receiving personalized advice on diet and health is time-consuming and requires direct support from a specialist. Moreover, few health management systems take into account the user's emotional state, and personalized suggestions tailored to those emotions are needed. Therefore, there is a need for a system that allows users to efficiently manage their diet and health and receive detailed advice that reflects their emotional state.

[1301] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1302] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting supermarkets or restaurants based on the user's location information, means for the user to input and view information within a virtual store through a virtual reality device, means for analyzing the user's emotional state using an emotion recognition engine, and means for adjusting the suggested meal menu and advice based on the emotional state. As a result, the user can more efficiently manage their health and eating habits and receive personalized advice tailored to their emotional state.

[1303] "Methods for inputting meal menus" refers to interfaces that allow users to directly input details of their meals into a device, and this includes text input and voice input.

[1304] "Means of sending to a server" refers to infrastructure that has the function of sending data entered by a user to a remote server via the internet.

[1305] "Methods for analyzing meal menus" refers to software or hardware that analyzes the nutrient content and composition based on meal data received by a server, and identifies any deficient nutrients.

[1306] "Method for generating meal menus" refers to an algorithm and software that enables a server to automatically generate appropriate meal menus to supplement identified nutritional deficiencies.

[1307] "Means of providing to the user" refers to means of presenting the generated meal menu and related information to the user's device, and this includes display and audio notifications.

[1308] The "means for searching for and suggesting supermarkets or restaurants" refers to a system that uses the user's location information to search the internet for information on stores and restaurants where suggested food items or dishes can be purchased, and then notifies the user.

[1309] A "virtual reality device" is a device, such as a head-mounted display or VR goggles, that allows users to enter a virtual space and realistically recreates the experience of being in a virtual store.

[1310] An "emotion recognition engine" is a software system that uses artificial intelligence to analyze a user's voice and input data and determine the emotional state contained within it.

[1311] A "means for analyzing emotional states" refers to a system that analyzes a user's emotional state from their input data and behavior, and transmits that information to a server.

[1312] "Means for adjusting suggested meal menus and advice" refers to a system that customizes the content of meal menus and health advice to best suit the user based on their analyzed emotional state.

[1313] This invention is a system that allows users to input meal menus and symptoms of illness, and then provides nutritional management and health advice based on that input. Furthermore, it can analyze the user's emotional state and make suggestions accordingly. This system can be implemented using a smartphone, personal computer, or virtual reality device (such as VR goggles or a head-mounted display).

[1314] System Overview

[1315] 1. The user enters their meal menu and symptoms of illness into the device.

[1316] 2. The entered data is sent to the server via the internet.

[1317] 3. The server analyzes the data to identify potential nutrient deficiencies or health problems.

[1318] 4. Generate dietary suggestions to supplement necessary nutrients and create appropriate initial countermeasures.

[1319] 5. Provide users with suggestions and information on supermarkets, restaurants, or hospitals.

[1320] 6. The emotion recognition engine analyzes the user's emotional state and adjusts the suggested content accordingly.

[1321] Hardware and software to be used

[1322] Virtual reality devices: Oculus Rift, HTC Vive, Sony PlayStation VR, etc.

[1323] Speech-to-Text API: Google Speech-to-Text

[1324] Emotion recognition engine: Azure Cognitive Services Emotion API

[1325] Server-side frameworks: Django, Flask

[1326] Data analysis and management: Dedicated nutritional and medical databases

[1327] Language processing solutions: Google Cloud Natural Language API

[1328] Program Processing Overview

[1329] User input

[1330] The user puts on VR goggles, logs into a virtual store, and uses a voice recognition API to input their meal order and health status. For example, they might say, "I had toast and coffee for breakfast today."

[1331] Data transmission

[1332] The input data is transmitted to the server in real time via the internet. The server receives the transmitted data and proceeds to the next analysis step.

[1333] Data Analysis

[1334] The server analyzes the received dietary and symptom data. Here, it uses dedicated nutritional and medical databases to identify nutrient content and possible diseases.

[1335] Proposal generation

[1336] To supplement any missing nutrients, the server automatically generates appropriate meal plans. Furthermore, if you feel unwell, it will suggest possible illnesses and provide initial treatment options.

[1337] Presentation to the user

[1338] The generated meal menus and health information are presented to the user within the virtual store. Furthermore, information on nearby supermarkets, restaurants, and hospitals is included.

[1339] Emotional analysis and proposal adjustment

[1340] The emotion recognition engine analyzes the user's voice data and input to determine their emotional state. For example, if the system detects that the user is stressed, it adds suggestions for stress-reducing meals and activities.

[1341] Specific example

[1342] If user A enters "I had a café au lait and a croissant for lunch today," the server identifies a vitamin B deficiency. Simultaneously, the emotion recognition engine recognizes the user's stress level from their voice data. Based on this information, the server suggests "grilled chicken and avocado salad" and also notifies the user of nearby supermarkets.

[1343] Examples of prompts for a generative AI model:

[1344] "The user entered their meal plan and it was identified that they are deficient in B vitamins. Since the user is under stress, please suggest meal options that would help reduce stress."

[1345] Expected output:

[1346] "Grilled chicken and avocado salad would be good. Vitamin B complex and potassium are effective for stress reduction. You can buy these ingredients at your local supermarket."

[1347] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1348] Step 1:

[1349] The user puts on VR goggles and logs into the virtual store. They enter their user ID and password as login information. This allows the user to access the system, and the system obtains the user's identification information.

[1350] Step 2:

[1351] The user enters their meal menu and symptoms of illness. A speech recognition API (e.g., Google Speech-to-Text) is used to convert the voice data into text, inputting the meal menu and health status. The input data includes food names, time of consumption, and detailed symptoms. This input data is then sent to the server.

[1352] Step 3:

[1353] The server analyzes the received data. First, it extracts the nutritional components of the food using a dedicated nutrition database. Next, it uses a medical database to extract possible diseases based on the entered symptoms. The identified nutrient deficiencies and disease possibilities are the output of this step.

[1354] Step 4:

[1355] The server identifies deficient nutrients and generates meal plans to compensate for them. Using a generation AI model, it automatically generates menus to optimize the user's nutritional balance. The input here is the analyzed information on deficient nutrients, and the output is the recommended meal plan.

[1356] Step 5:

[1357] The server analyzes the user's emotional state. Using an emotion recognition engine (e.g., Azure Cognitive Services Emotion API), it analyzes the user's voice tone and input data to determine their emotional state. The input data can be voice or text, and the output is the user's emotional level (e.g., stress, joy, anger).

[1358] Step 6:

[1359] The server adjusts suggestions based on the user's emotional state. Based on the generated emotional analysis data, it optimizes meal menus and health advice to match the user's emotional state. For example, if a user is feeling stressed, it adds stress-reducing foods and relaxation methods to the menu.

[1360] Step 7:

[1361] This service searches for information on supermarkets, restaurants, and hospitals recommended by the server. Based on the user's location, it searches the internet for nearby stores and hospitals and provides the most suitable options for the user. The input is the user's location and suggested menus, and the output is a list of stores and hospitals.

[1362] Step 8:

[1363] The system provides users with generated meal menus and advice. The suggestions are displayed to the user within the virtual store, and notifications are also sent to other devices. This step utilizes a user-friendly interface, providing information in an intuitive and easily accessible manner.

[1364] Step 9:

[1365] The feedback function allows users to input feedback on their emotional state and physical condition after implementing the suggested actions. This enables the system to update the data, allowing for more accurate and personalized future suggestions. The input data is feedback information, and the output represents improvements in the system's analysis accuracy.

[1366] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1367] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1368] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[1369] [Fourth Embodiment]

[1370] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1371] As shown in Figure 7, the 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.

[1372] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1373] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[1374] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[1375] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[1376] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[1377] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive 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 robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[1378] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[1379] The specific processing program 56 is an example of a "program" relating to the technology of this 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.

[1380] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1381] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. 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 processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[1382] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1383] This invention is a system for users to manage and analyze their meal menus and minor health symptoms, and to provide appropriate meal suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[1384] 1. Overall System Overview

[1385] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user.

[1386] 2. Inputting meal menus and managing nutrition

[1387] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[1388] The server analyzes the received meal data and extracts nutrient information for each meal using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[1389] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[1390] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[1391] 3. Support for initial medical consultation when feeling unwell

[1392] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[1393] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1394] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[1395] Specific example

[1396] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides the user with that menu. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[1397] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[1398] Thus, a system that efficiently manages and analyzes users' dietary information and health status, and provides appropriate suggestions, is extremely useful in the advanced lifestyles of modern society.

[1399] The following describes the processing flow.

[1400] 1. Processing related to nutritional management of meals.

[1401] Step 1:

[1402] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[1403] Step 2:

[1404] The terminal verifies the meal menu data entered by the user, checking for any missing or inappropriate information.

[1405] Step 3:

[1406] The terminal sends the verified meal menu data to the server.

[1407] Step 4:

[1408] The server analyzes the data of the received meal menu.

[1409] Step 5:

[1410] The server uses its built-in nutritional database to identify the nutrients in each food item.

[1411] Step 6:

[1412] The server calculates the total daily nutrient intake based on the analysis results and compares it to the recommended daily intake standards.

[1413] Step 7:

[1414] The server identifies deficient nutrients based on comparisons with nutritional intake standards.

[1415] Step 8:

[1416] The server generates meal plans to supplement any missing nutrients.

[1417] Step 9:

[1418] The server sends the generated meal menu to the terminal.

[1419] Step 10:

[1420] The device searches for nearby supermarkets and restaurants based on the user's location information.

[1421] Step 11:

[1422] The device sends the search results to the server for filtering and optimization.

[1423] Step 12:

[1424] The server returns a list of the best places to shop to the device.

[1425] Step 13:

[1426] The device displays a list of optimal shopping destinations to the user.

[1427] 2. Procedures related to the initial consultation before hospital visit

[1428] Step 1:

[1429] The user enters their symptoms of illness (headache, sore throat, fever, etc.) into the terminal.

[1430] Step 2:

[1431] The terminal verifies the symptom data entered by the user and asks for additional information as needed.

[1432] Step 3:

[1433] The device sends complete symptom data to the server.

[1434] Step 4:

[1435] The server analyzes the received symptom data.

[1436] Step 5:

[1437] The server cross-references the data with its built-in medical database and generates a list of possible illnesses.

[1438] Step 6:

[1439] The server sends the generated disease list and initial countermeasures corresponding to the symptoms to the terminal.

[1440] Step 7:

[1441] The device displays a list of diseases and initial countermeasures to the user.

[1442] Step 8:

[1443] If a user wishes to receive a hospital consultation, they enter that information into the terminal.

[1444] Step 9:

[1445] The terminal sends the user's consultation request information and location information to the server.

[1446] Step 10:

[1447] The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for cases.

[1448] Step 11:

[1449] The server sends the generated list of hospitals to the terminal.

[1450] Step 12:

[1451] The terminal displays a list of the most suitable hospitals to the user.

[1452] (Example 1)

[1453] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1454] In today's busy lifestyle, proper nutritional management and appropriate responses to health problems are difficult. In particular, there is a lack of means for users to efficiently manage their diet and health status and quickly obtain necessary information. Furthermore, supplementing with appropriate nutrients, providing initial responses to health problems, and selecting the most suitable medical institution require specialized knowledge, making these tasks difficult for the average user. Therefore, there is a need for a system that allows users to easily and quickly manage their diet and health.

[1455] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[1456] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting a store or restaurant based on the user's location information, means for the user to input any symptoms of poor health, means for the server to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable treatment facility based on the user's wishes and evaluations, and means for verifying the meal menu and symptom information entered by the user to check for any incomplete or inappropriate data. This enables the user to efficiently and effectively manage their diet and health.

[1457] A "user" refers to an individual or group that uses the system.

[1458] A "meal menu" refers to information that lists the types and quantities of food and beverages a user consumes.

[1459] "Means" refers to a method, device, or software used to perform a specific function or action.

[1460] A "server" refers to a computer system that receives requests from clients via a network, processes the necessary information, and responds.

[1461] "Nutrients" refer to components such as vitamins, minerals, proteins, fats, and carbohydrates that are necessary to maintain human health.

[1462] A "sales outlet" refers to a store where users can purchase the food ingredients and products they need.

[1463] "Dining places" refer to facilities such as restaurants and cafes where users can eat meals.

[1464] "Location information" refers to data that indicates the user's current geographical location.

[1465] "Symptoms" refer to the specific physical or psychological abnormalities that a user experiences when feeling unwell.

[1466] "Disease" refers to a condition in which health deteriorates due to abnormalities in bodily functions or organs.

[1467] A "treatment facility" refers to a place that provides medical care, such as a hospital, clinic, or medical office.

[1468] "Data" refers to a collection of numbers, characters, symbols, and other elements used to represent information.

[1469] This invention is a system that allows users to manage and analyze their meal menus and symptoms of poor health, and provides appropriate dietary suggestions and useful information before hospital visits. This system mainly consists of a terminal used by the user and a server that processes the data.

[1470] Hardware and software configuration

[1471] In this system, users input their daily meal menus and symptoms of illness using devices such as smartphones and personal computers. The data entered by users is sent via the internet to a cloud-based server. On the server side, data analysis and suggestion generation are performed using specific software.

[1472] Device configuration

[1473] The user's device has a dedicated application installed for entering data on meals and symptoms. This application has fields for entering the food name, quantity, time of intake, and the severity and time of symptom onset.

[1474] Server Configuration

[1475] On the server side, the following software and databases are used to analyze the received data:

[1476] Nutritional databases (e.g., USDA National Nutrient Database): Used to analyze the nutritional content of meal menus.

[1477] Medical databases (e.g., MedlinePlus): Used to identify possible illnesses based on symptoms of illness.

[1478] Location databases (e.g., Google Maps API): Used to suggest nearby shops, restaurants, and medical facilities based on the user's location.

[1479] System operation

[1480] The operation of this system is outlined below:

[1481] 1. Data Entry: Users enter meal menus and symptoms of illness using their smartphones or computers. Meal menus include food names, quantities, and times of consumption, while symptoms include specific details of illnesses and the time they occurred.

[1482] 2. Data Transmission: The device transmits the entered data to the server via the internet. The transmitted data includes the user ID, input data, and location information.

[1483] 3. Data Analysis: The server analyzes the received data. In the case of meal menus, it uses a nutrition database to analyze nutrients and identify any nutrient deficiencies. In the case of illness, it uses a medical database to identify possible diseases.

[1484] 4. Suggestion Generation: Based on the analysis results, the server generates meal menus to supplement any deficient nutrients. If the user is unwell, it also suggests initial countermeasures tailored to their symptoms. Furthermore, based on location information, it suggests nearby shops, restaurants, and medical facilities.

[1485] 5. Provision to the user: The generated suggestions are provided to the user via their device. This allows the user to efficiently manage their diet and health.

[1486] Specific example

[1487] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that data to the server. The server uses a nutritional database to identify a deficiency in vitamin D and calcium and suggests "eating salmon steak and broccoli salad for dinner." At the same time, information about nearby stores is also displayed.

[1488] Furthermore, if a user enters "headache, sore throat, and 38-degree fever," the server uses its medical database to identify the possibility of a cold, influenza, or pharyngitis and suggests "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, the server will also suggest nearby hospitals with good reputations based on their location.

[1489] Example of a prompt

[1490] Meal menu management

[1491] Prompt: "I had one slice of toast and coffee for breakfast. Please analyze its nutrients and suggest a complementary dinner menu."

[1492] Measures to take when you are feeling unwell

[1493] Prompt: "I currently have a headache, sore throat, and a fever of 38 degrees Celsius. Please tell me what the possible illnesses are and what initial treatments I should take. Also, please recommend a nearby hospital with a good reputation."

[1494] In this way, the system enables users to efficiently manage and analyze information about their diet and health problems, and to provide optimal suggestions.

[1495] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1496] Step 1:

[1497] Users input their daily meal menus and symptoms of illness into a dedicated application using their smartphones or computers. The input data includes the name of the food, the quantity, the time of consumption, and the symptoms and the time of their onset.

[1498] Input: Information on meal menus and symptoms of illness

[1499] Output: Data entered into the terminal

[1500] Step 2:

[1501] The terminal packages the data entered by the user and sends it to the server via the internet. The transmitted data includes the user ID, information about meals or symptoms, and location information.

[1502] Input: Data entered by the user on the device.

[1503] Output: Packaged data sent to the server

[1504] Step 3:

[1505] The server receives the data and stores it in the database. The stored data is then retrieved for analysis.

[1506] Input: Data sent from the device

[1507] Output: Data stored on the server

[1508] Step 4:

[1509] For food data, the server uses an internal nutrition database to analyze the nutrients in each food item and calculate the total daily nutrient intake. For data related to poor health, it uses a medical database to identify possible illnesses.

[1510] Input: Meal data or symptom data stored on the server

[1511] Data processing / calculation: Analysis by cross-referencing with nutritional or medical databases.

[1512] Output: List of deficient nutrients or possible diseases

[1513] Step 5:

[1514] The server generates meal plans to supplement any nutritional deficiencies based on the analysis results. If the user is unwell, it generates initial countermeasures tailored to their symptoms.

[1515] Input: List of deficient nutrients or diseases

[1516] Data processing / data calculation: Generation of meal suggestions or initial countermeasures

[1517] Output: Meal suggestion menu or initial countermeasures

[1518] Step 6:

[1519] The server searches for shops, restaurants, and medical facilities based on the user's location information and provides this information to the user along with the analysis results.

[1520] Input: Location information, generated suggestion information

[1521] Data processing / data calculation: Location-based search and integration of suggestion information

[1522] Output: Location-based suggestion information

[1523] Step 7:

[1524] The terminal displays suggested information received from the server to the user. For meal suggestions, it displays specific menus and purchase locations; for health issues, it displays initial countermeasures and hospital information.

[1525] Input: Suggestion information sent from the server

[1526] Output: Displayed suggestion information

[1527] Step 8:

[1528] Users take action based on information suggested through their device. For example, if a meal is suggested, they prepare a meal based on the suggested menu; if they feel unwell, they take initial measures and visit a hospital if necessary.

[1529] Input: Suggested information

[1530] Output: User behavior

[1531] (Application Example 1)

[1532] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1533] In modern society, users need to manage their daily diets and symptoms of illness themselves for health management. However, it is not easy for them to find appropriate dietary suggestions or early countermeasures for symptoms on their own. Furthermore, there is a lack of systems that efficiently provide information on foods to supplement necessary nutrients and appropriate medical facilities. As a result, it is difficult for users to effectively maintain their health and take preventative measures against illness.

[1534] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[1535] In this invention, the server includes means for analyzing the user's meal menu and identifying deficient nutrients, means for generating meal menus to supplement the deficient nutrients, and means for providing health supplements and medical information based on the analysis results. This enables the user to efficiently manage their daily diet and physical condition and to perform appropriate health management.

[1536] "Means for inputting meal menus" refers to devices or application functions that allow users to record or input their daily meal contents.

[1537] "Means for sending meal menus to the server" refers to a communication function for sending meal information entered by the user to a central server.

[1538] "Means for identifying deficient nutrients" refers to a function where the server analyzes the received meal information and identifies nutrients that the user is not consuming or is deficient in.

[1539] "Method for generating meal menus" refers to a function where the server creates new meal suggestions to supplement any missing nutrients.

[1540] "Means of providing meal menus to users" refers to a function for notifying or displaying generated meal suggestions to users.

[1541] The "means of searching for and suggesting places where ingredients can be purchased" refers to a function that uses the user's location information to search for and suggest places where the ingredients needed for the generated meal menu can be purchased.

[1542] "Means for inputting symptoms of poor health" refers to devices or application functions that allow users to record or input health problems related to their own or their family's physical condition.

[1543] "Means for sending symptoms to the server" refers to a communication function for sending health information entered by the user to a central server.

[1544] "Means of presenting possible illnesses" refers to a function that, based on the symptom information received by the server, lists possible illnesses and health problems and notifies the user.

[1545] "Means for searching for and suggesting medical institutions" refers to a function that searches for and provides appropriate hospitals and clinics to users based on their health condition and preferences.

[1546] "Means of providing health supplements and medical information" refers to a function that recommends appropriate supplements and medical institutions to address users' health conditions and nutritional deficiencies.

[1547] To realize this invention, a system is needed in which users manage and input their daily health information, and a server analyzes and makes suggestions based on that information. The system mainly consists of a terminal used by the user (such as a smartphone or computer) and a server that processes the data.

[1548] Hardware and software

[1549] 1. Hardware:

[1550] Smartphone: Used by users to record and transmit input data.

[1551] Server: A central processing unit for data analysis and proposal generation.

[1552] 2. Software:

[1553] Python: Used for data processing and API requests.

[1554] Requests library: Used for communication with APIs.

[1555] Geopy library: Used to obtain the user's location information.

[1556] Data processing and calculation flow

[1557] 1. User input:

[1558] Users input their daily meal menus and symptoms of illness into a smartphone app.

[1559] Regarding dietary information, details such as food names, quantities, and timing of consumption are included.

[1560] Information about feeling unwell includes symptoms such as headache, sore throat, and fever.

[1561] 2. Data transmission:

[1562] The user enters information and sends it from their smartphone to the server.

[1563] 3. Server analysis:

[1564] The server analyzes the received meal data and identifies any nutritional deficiencies.

[1565] The system utilizes a built-in nutrition database to extract nutrient information for each meal. Next, it calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[1566] The server automatically generates meal plans to supplement any missing nutrients. The generated suggested menus include specific food names and their corresponding nutrients.

[1567] Furthermore, based on the symptom information entered by the user, the system cross-references it with a built-in medical database to generate a list of possible illnesses. It also provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1568] 4. Providing suggestions:

[1569] The created suggested menus, health supplements, and medical institution information are sent back from the server to the user's terminal and displayed.

[1570] At the same time, based on the user's location information, it provides information on stores where the suggested food items can be purchased and information on appropriate hospitals.

[1571] Specific example

[1572] For example, if a user enters, "I had one slice of toast and coffee for breakfast. Recently, I've had a headache, sore throat, and a fever of 38 degrees Celsius," the server will identify a deficiency in "vitamin D and calcium" and suggest "salmon steak and broccoli salad for dinner." At the same time, it will suggest the possibility of "a cold, the flu, or pharyngitis" and advise "drink plenty of fluids and rest." Based on the user's location, a list of the nearest supermarkets and highly-rated hospitals will also be provided.

[1573] Example of a generated AI prompt

[1574] Write code for a program that provides personalized suggestions based on the user's health status.

[1575] It has a function to input user dietary data and symptoms of illness.

[1576] Send data to the server for analysis and recommendations.

[1577] Based on the results, we will provide appropriate nutritional supplements and information on medical facilities.

[1578] Use location information to display nearby hospitals

[1579] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1580] Step 1:

[1581] The user inputs their meal menu. The user enters details of their daily meals (food name, quantity, time of consumption, etc.) into a device (smartphone, computer, etc.). This input data is formatted by the application.

[1582] Step 2:

[1583] The device sends meal data to the server. The meal information entered by the user is sent from the device to the server. In this process, the device often converts the input data into JSON format and sends it via an HTTP request.

[1584] Step 3:

[1585] The server analyzes the meal data. The server analyzes the received meal data and identifies any deficient nutrients. It extracts nutrient information for each meal using its built-in nutrition database. It calculates the total daily nutrient intake and identifies any deficiencies by comparing it to recommended nutritional intake standards.

[1586] Step 4:

[1587] The server generates meal plans that supplement any missing nutrients. The server creates new meal suggestions to address any nutritional deficiencies. This generation process automatically generates menus that include specific food names and corresponding nutrients, referencing a built-in recipe database.

[1588] Step 5:

[1589] The server generates a meal menu and provides it to the user. The generated meal menu is sent back from the server to the terminal and notified or displayed to the user. The user can review the suggested menu through the application.

[1590] Step 6:

[1591] The user enters their symptoms of illness. The user enters detailed information about their or their family member's illness (e.g., headache, sore throat, fever, etc.) into the device. This input data is also formatted by the application.

[1592] Step 7:

[1593] The terminal sends symptom data to the server. The symptom information entered by the user is sent from the terminal to the server. During this process, the terminal converts the input data into JSON format and sends it via an HTTP request.

[1594] Step 8:

[1595] The server analyzes the symptom data. Based on the received symptom information, the server compares it with its built-in medical database and generates a list of possible illnesses. Furthermore, it provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1596] Step 9:

[1597] The server searches for and suggests the most suitable medical institutions. Based on the user's health condition and preferences, the server searches for appropriate medical institutions and generates a list to provide to the user. This list is compiled considering factors such as hospital reputation and the success rate of cases.

[1598] Step 10:

[1599] The server generates a list of medical institutions and provides it to the user. The generated list of medical institutions is then sent back from the server to the terminal and notified or displayed to the user. The user can then review the suggested medical institutions through the application.

[1600] Step 11:

[1601] Based on the user's location information, the server suggests places where the product can be purchased and medical facilities. Using the user's location information, the server provides information on stores where the suggested food product can be purchased and appropriate medical facilities. This information is generated through database lookup and location data analysis.

[1602] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[1603] This invention combines a system that manages and analyzes a user's meal menu and minor health symptoms, providing appropriate meal suggestions and useful information before hospital visits, with an emotion engine that recognizes the user's emotions. This system mainly consists of a terminal used by the user, a server that processes data, and an emotion engine that acquires and analyzes emotional data.

[1604] 1. Overall System Overview

[1605] This system allows users to input meal plans and symptoms of illness into a terminal, and then sends this data to a server for various analyses and suggestions. The server then sends back and displays information about meal plans, potential illnesses, and suitable supermarkets, restaurants, and hospitals to the user. An emotion engine analyzes the user's emotional state and provides appropriate responses accordingly.

[1606] 2. Inputting meal menus and managing nutrition

[1607] Users input their daily meal menus using devices such as smartphones or computers. The entered data includes details such as food names, quantities, and times of consumption. The device then sends this data to the server.

[1608] The server analyzes the received meal data and extracts nutrient information for each food item using its built-in nutrition database. Next, the server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to recommended nutritional intake standards.

[1609] Once the deficient nutrients are identified, the server automatically generates meal plans to supplement those nutrients. The generated suggested menus include specific food names and corresponding nutrients, such as "salmon steak" or "spinach salad."

[1610] The created suggested menu is provided to the user via the terminal. Simultaneously, based on the user's location information, the system searches for nearby supermarkets and restaurants and displays information on stores where the suggested food items can be purchased.

[1611] 3. Support for initial medical consultation when feeling unwell

[1612] The user enters detailed information about their own or their family's health symptoms into the device. This information includes specific examples such as headache, sore throat, and fever. The device then sends this data to the server.

[1613] The server, based on the received symptom information, compares it with its built-in medical database and generates a list of possible illnesses. For example, "cold," "flu," and "pharyngitis" are considered. Furthermore, the server provides initial countermeasures tailored to the symptoms (e.g., fluid intake, rest).

[1614] If a user requests a hospital consultation, the device sends this request information along with the user's location to the server. The server generates a list of optimal hospitals, taking into account the user's desired treatment, the hospital's reputation, and the cure rate for similar cases. This list is then presented to the user via the device.

[1615] 4. Emotion recognition by an emotion engine

[1616] When a user enters meal menus or symptom information, the emotion engine activates and analyzes the user's emotional state from their voice tone and input content. The emotion engine recognizes emotions such as joy, sadness, stress, and anger.

[1617] The acquired emotional data is sent to a server, which adjusts the suggestions based on the user's emotional state. For example, if a user is feeling stressed, they will be offered advice on stress-reducing foods and relaxation techniques. Suggestions for when the user is feeling unwell will also take their emotional state into consideration.

[1618] Specific example

[1619] For example, suppose a user inputs, "I had one slice of toast and coffee for breakfast." The device sends this information to the server, which analyzes it and identifies a deficiency in "Vitamin D" and "Calcium." Based on this, the server suggests "Salmon steak and broccoli salad for dinner" and provides this menu to the user through the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[1620] Furthermore, if a user enters "headache, sore throat, and 38-degree fever" on another day, the server will suggest the possibility of "a cold, influenza, or pharyngitis" and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases will be provided.

[1621] Furthermore, if the emotion engine detects that the user is experiencing stress during input, it will simultaneously provide advice on foods and behaviors that are effective in reducing stress. In this way, utilizing emotion recognition enables more personalized care.

[1622] The following describes the processing flow.

[1623] 1. Processing related to nutritional management of meals.

[1624] Step 1:

[1625] The user enters their current meal menu (food name, quantity, time of consumption, etc.) into the terminal.

[1626] Step 2:

[1627] The terminal verifies the data entered by the user to check for incomplete or incorrect information.

[1628] Step 3:

[1629] The terminal sends the verified meal menu data to the server.

[1630] Step 4:

[1631] The server analyzes the data of the received meal menu.

[1632] Step 5:

[1633] The server uses a nutrition database to identify the nutritional information of each food item.

[1634] Step 6:

[1635] The server calculates the total daily nutrient intake and identifies any nutrient deficiencies by comparing it to standard nutritional intakes.

[1636] Step 7:

[1637] The server generates meal plans to supplement any missing nutrients.

[1638] Step 8:

[1639] The server sends the generated meal menu to the terminal.

[1640] Step 9:

[1641] The terminal displays the generated meal menu to the user.

[1642] Step 10:

[1643] The device sends data to a server based on the user's location information to search for nearby supermarkets and restaurants.

[1644] Step 11:

[1645] The server searches for the best supermarkets and restaurants and sends that information back to the terminal.

[1646] Step 12:

[1647] The device displays search results to the user and suggests places where recommended foods can be purchased.

[1648] 2. Procedures for initial medical examination in case of illness

[1649] Step 1:

[1650] The user enters detailed information about their symptoms (e.g., headache, sore throat, fever, etc.) into the device.

[1651] Step 2:

[1652] The terminal verifies the symptoms entered by the user and asks for additional information as needed.

[1653] Step 3:

[1654] The device sends complete symptom data to the server.

[1655] Step 4:

[1656] The server analyzes the received symptom data.

[1657] Step 5:

[1658] The server cross-references the information with a medical database and generates a list of possible illnesses.

[1659] Step 6:

[1660] The server sends the generated disease list and initial response information to the terminal.

[1661] Step 7:

[1662] The device displays a list of diseases and initial countermeasures to the user.

[1663] Step 8:

[1664] If a user wishes to schedule a hospital appointment, they enter that information into the terminal.

[1665] Step 9:

[1666] The terminal transmits the user's consultation request information and location information to the server.

[1667] Step 10:

[1668] The server generates a list of optimal hospitals, taking into account the user's desired treatment, hospital reputation, and the cure rate for cases.

[1669] Step 11:

[1670] The server sends the generated hospital list to the terminal.

[1671] Step 12:

[1672] The terminal displays a list of suitable hospitals to the user and assists with the appointment booking process.

[1673] 3. Processing related to emotion recognition by the emotion engine

[1674] Step 1:

[1675] When a user enters meal menus or symptom information into the terminal, the emotion engine automatically activates to analyze the user's emotional state while they are entering the information.

[1676] Step 2:

[1677] The emotion engine acquires emotion data from the user's voice tone and input content.

[1678] Step 3:

[1679] The device sends the acquired emotion data to the server.

[1680] Step 4:

[1681] The server analyzes emotional data and adjusts the content of its meal menu and disease predictions based on the user's emotional state.

[1682] Step 5:

[1683] The server generates optimal menus and advice based on sentiment data.

[1684] Step 6:

[1685] The server sends the generated suggestions to the terminal.

[1686] Step 7:

[1687] The device displays meal menus and advice tailored to the user's emotional state.

[1688] Specific example

[1689] For example, if a user inputs "I had one slice of toast and coffee for breakfast," the device sends this information to the server, which analyzes it and identifies a deficiency in "vitamin D" and "calcium." The server then suggests "salmon steak and broccoli salad for dinner" and provides this menu to the user via the device. Furthermore, based on the user's location, information about the nearest supermarket is also provided.

[1690] On another day, if a user enters "headache, sore throat, and 38-degree fever," the server suggests the possibility of "cold, flu, or pharyngitis" and recommends "drink plenty of fluids and rest" as initial countermeasures. If the user wishes to see a doctor, a list of nearby hospitals with good reputations and high recovery rates for similar cases is provided.

[1691] Furthermore, if the emotion engine is activated and recognizes that the user is experiencing stress during input, it will also provide advice on foods that are effective in reducing stress and relaxation techniques. In this way, utilizing emotion recognition enables more personalized care.

[1692] (Example 2)

[1693] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1694] Current meal and health management systems are insufficient in managing nutrients and analyzing symptoms, and they fail to provide individualized support that takes into account the user's emotional state. As a result, users often do not receive appropriate nutritional support or timely, appropriate medical care. Furthermore, there is a need for systems that can address not only nutrient deficiencies and potential illnesses, but also the stress and other emotions that users are experiencing.

[1695] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server with the generated meal menu to the user, means for searching for and suggesting sales facilities or restaurants based on the user's location information, means for the user to input symptoms of poor health, means for the user to transmit the symptoms entered by the user to the server, means for the server to analyze the symptoms and suggest possible illnesses, means for the server to search for and suggest the most suitable medical facility based on the user's preferences and reputation, means for the emotion engine to recognize the emotional state when the user inputs meal menu and symptom information, means for the emotion engine to transmit the analyzed emotional data to the server, and means for the server to adjust the suggested content based on the emotional state. This will not only enable users to properly replenish the nutrients they need for diet and health management, but also allow them to receive prompt and appropriate medical care when they are unwell, and furthermore, enable personalized support tailored to their emotional state.

[1696] A "user" refers to an individual who uses this system to manage their diet and health.

[1697] A "terminal" refers to a device used by a user to input data and communicate with a server. Examples include smartphones and personal computers.

[1698] A "server" refers to a computer system that receives data sent by a user, analyzes and processes it, and provides the results.

[1699] "Meal menu" refers to the detailed information about meals entered by the user. Specifically, this includes the name of the food, the quantity, and the time of consumption.

[1700] "Nutrients" refer to components found in food that are necessary for maintaining bodily functions. Examples include vitamins, calcium, and protein.

[1701] "Symptoms" refer to physical abnormalities or discomforts that a user experiences when feeling unwell. Examples include headaches, sore throats, and fever.

[1702] An "emotion engine" refers to a technology that analyzes a user's emotional state from their input or voice.

[1703] A "sales facility" refers to a place where you can buy ingredients and food products. Examples include supermarkets and grocery stores.

[1704] A "food and beverage establishment" refers to a place where users can eat. This includes, for example, restaurants and cafes.

[1705] A "medical facility" refers to a place that provides diagnosis and treatment for illnesses and health problems. Examples include hospitals and clinics.

[1706] "Generative AI models" refer to artificial intelligence technologies that provide appropriate suggestions and analyses based on user requests.

[1707] A "prompt sentence" refers to an instruction or question that is input into a generative AI model. Examples include sentences requesting meal menu suggestions or sentences requesting symptom analysis.

[1708] This invention relates to a system that manages and analyzes a user's meal menu and symptoms of poor health, and provides appropriate meal suggestions and medical information. This system further achieves more personalized care by incorporating an emotion engine that recognizes the user's emotions.

[1709] This system primarily consists of a user terminal, a server that processes data, and an emotion engine that acquires and analyzes emotional data. The overall system flow begins with the user entering their meal menu or symptoms of illness into the terminal and sending that data to the server. The server analyzes this data, generates appropriate suggestions, and finally delivers them to the user through the terminal.

[1710] The terminal uses common devices such as smartphones and personal computers. Users input meal menus and symptom information into the terminal, and the terminal sends this information to the server. Examples of software used include web browsers and dedicated applications.

[1711] The server incorporates various databases (nutrition database, medical database, sentiment analysis database) and uses them for data analysis and processing. For example, FoodData Central is commonly used for the nutrition database, and general medical information is stored in the medical database. Furthermore, Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding are used for the sentiment engine. The server uses Python's pandas library and the NLP library spaCy to analyze data received from users.

[1712] For example, if a user enters "I had one slice of toast and coffee for breakfast," the device sends that information to the server. The server analyzes the data and identifies a deficiency in "vitamin D" and "calcium," and based on that, suggests "salmon steak and broccoli salad for dinner." It also uses the user's location information to show where these ingredients can be purchased at the nearest supermarket.

[1713] If a user is feeling unwell and enters "headache, sore throat, and 38-degree fever," the server will suggest possibilities such as "cold," "flu," or "pharyngitis," and propose initial measures such as "drink plenty of fluids and rest." If the user wishes to see a doctor, the server will list nearby medical facilities with good reputations based on the user's location and preferences, and provide this information to the user via their device.

[1714] As an example of analysis by the emotion engine, if a user enters "I've been really busy with work lately and feeling stressed" when inputting meal menus or symptom information, the emotion engine analyzes the text and recognizes that the user is feeling stressed. Based on this, the server provides stress-reducing foods (for example, chamomile tea) and relaxation advice.

[1715] Examples of prompts generated using a generative AI model include the following:

[1716] mark down

[1717] Please analyze the following dietary information and suggest a daily meal plan to identify any nutritional deficiencies and supplement them.

[1718] Meal information: Had one slice of toast and coffee for breakfast.

[1719] mark down

[1720] Please analyze the following symptom information, provide a list of possible illnesses, and suggest initial countermeasures.

[1721] Symptoms: Headache and sore throat, fever of 38 degrees Celsius.

[1722] mark down

[1723] The user made the following request: "Please use an emotion engine to analyze my emotional state (joy, sadness, stress, anger, etc.) and suggest appropriate countermeasures."

[1724] Statement: Lately, I feel like I'm stressed because work has been so busy.

[1725] Thus, this system not only manages nutrition and health based on the meal menus and symptom information entered by the user, but also enables personalized responses that take into account the user's emotional state.

[1726] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1727] Step 1: Enter and submit your meal menu.

[1728] Users input meal menus using their smartphones or PCs. Specifically, they input information such as, "I had one slice of toast and coffee for breakfast." The device sends this input information to the server. The output is the server receiving the meal menu entered by the user.

[1729] Step 2: Analysis of meal plans and identification of nutritional deficiencies

[1730] The server analyzes the received meal menu. First, it reads the received data into a DataFrame using the pandas library and extracts nutrient information for each food item from a nutrition database (e.g., FoodData Central). Next, it calculates the total daily nutrient intake and compares it to the recommended daily intake. Based on this comparison, it identifies any deficient nutrients. The input is the meal menu entered and submitted by the user, and the output is a list of identified deficient nutrients.

[1731] Step 3: Generating complementary meal menus

[1732] The server generates meal plans to supplement identified nutrient deficiencies. Specifically, it uses Python's scikit-learn to build a machine learning model for recipe suggestions and generates specific food suggestions to supplement the missing nutrients (e.g., "Salmon steak and broccoli salad for dinner"). The input is a list of the missing nutrients, and the output is the generated supplementary meal plan.

[1733] Step 4: Suggesting places to buy groceries

[1734] The server uses the user's location information based on the generated meal menu to search for nearby retail and dining establishments. Specifically, it uses the Google Places API to list stores where the necessary ingredients can be purchased. This information is then provided to the user via their device. The input is the generated meal menu and the user's location information, and the output is a list of suggested places to buy.

[1735] Step 5: Enter and submit your symptoms.

[1736] The user enters their symptoms into the terminal. Specifically, they enter detailed symptom information such as "headache, sore throat, and a fever of 38 degrees Celsius." The terminal sends this symptom information to the server. The output is the user's entered symptom information sent to the server.

[1737] Step 6: Analysis of symptom information and presentation of possibilities

[1738] The server analyzes the received symptoms. Using an NLP library (e.g., spaCy), it analyzes the symptom information and compares it with a medical database. It generates a list of possible illnesses and suggests appropriate initial countermeasures (e.g., "Drink plenty of fluids and rest"). The input is the symptom information entered and submitted by the user, and the output is the likelihood of possible illnesses and initial countermeasures.

[1739] Step 7: Propose hospital information

[1740] When a user requests a medical consultation, the device sends their request information and location to the server. The server uses the Google Maps API to search for nearby medical facilities and generates a list of the best hospitals based on reputation and success rates. This list is then provided to the user via the device. The input is the user's consultation request information and location, and the output is a list of suggested hospitals.

[1741] Step 8: Input and analysis of emotional data

[1742] When a user enters meal menus or symptom information, the emotion engine activates and analyzes their emotional state from the input content and tone of voice. It uses Google Cloud Speech-to-Text API and IBM Watson Natural Language Understanding to generate emotion data. The server receives this emotion data and adjusts the suggestions based on the estimated emotional state. The input is the user's emotional state, and the output is the analyzed emotional state.

[1743] Step 9: Adjusting proposals based on emotional state

[1744] The server adjusts the suggested meal menus and medical information based on the user's emotional state, using the results of the emotion engine's analysis. For example, if the user is feeling stressed, it will provide stress-reducing foods and relaxation advice. This enables more personalized care. The input is the analysis results from the emotion engine, and the output is the adjusted suggestions.

[1745] Through the processing steps described above, this system comprehensively supports the user's dietary and health management, and provides personalized support tailored to their emotional state.

[1746] (Application Example 2)

[1747] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[1748] In today's busy lifestyle, it is difficult for individuals to properly manage their own nutritional balance and health. Furthermore, receiving personalized advice on diet and health is time-consuming and requires direct support from a specialist. Moreover, few health management systems take into account the user's emotional state, and personalized suggestions tailored to those emotions are needed. Therefore, there is a need for a system that allows users to efficiently manage their diet and health and receive detailed advice that reflects their emotional state.

[1749] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[1750] In this invention, the server includes means for the user to input a meal menu, means for transmitting the meal menu entered by the user to the server, means for the server to analyze the received meal menu and identify any deficient nutrients, means for the server to generate a meal menu to supplement the identified deficient nutrients, means for providing the server-generated meal menu to the user, means for searching for and suggesting supermarkets or restaurants based on the user's location information, means for the user to input and view information within a virtual store through a virtual reality device, means for analyzing the user's emotional state using an emotion recognition engine, and means for adjusting the suggested meal menu and advice based on the emotional state. As a result, the user can more efficiently manage their health and eating habits and receive personalized advice tailored to their emotional state.

[1751] "Methods for inputting meal menus" refers to interfaces that allow users to directly input details of their meals into a device, and this includes text input and voice input.

[1752] "Means of sending to a server" refers to infrastructure that has the function of sending data entered by a user to a remote server via the internet.

[1753] "Methods for analyzing meal menus" refers to software or hardware that analyzes the nutrient content and composition based on meal data received by a server, and identifies any deficient nutrients.

[1754] "Method for generating meal menus" refers to an algorithm and software that enables a server to automatically generate appropriate meal menus to supplement identified nutritional deficiencies.

[1755] "Means of providing to the user" refers to means of presenting the generated meal menu and related information to the user's device, and this includes display and audio notifications.

[1756] The "means for searching for and suggesting supermarkets or restaurants" refers to a system that uses the user's location information to search the internet for information on stores and restaurants where suggested food items or dishes can be purchased, and then notifies the user.

[1757] A "virtual reality device" is a device, such as a head-mounted display or VR goggles, that allows users to enter a virtual space and realistically recreates the experience of being in a virtual store.

[1758] An "emotion recognition engine" is a software system that uses artificial intelligence to analyze a user's voice and input data and determine the emotional state contained within it.

[1759] A "means for analyzing emotional states" refers to a system that analyzes a user's emotional state from their input data and behavior, and transmits that information to a server.

[1760] "Means for adjusting suggested meal menus and advice" refers to a system that customizes the content of meal menus and health advice to best suit the user based on their analyzed emotional state.

[1761] This invention is a system that allows users to input meal menus and symptoms of illness, and then provides nutritional management and health advice based on that input. Furthermore, it can analyze the user's emotional state and make suggestions accordingly. This system can be implemented using a smartphone, personal computer, or virtual reality device (such as VR goggles or a head-mounted display).

[1762] System Overview

[1763] 1. The user enters their meal menu and symptoms of illness into the device.

[1764] 2. The entered data is sent to the server via the internet.

[1765] 3. The server analyzes the data to identify potential nutrient deficiencies or health problems.

[1766] 4. Generate dietary suggestions to supplement necessary nutrients and create appropriate initial countermeasures.

[1767] 5. Provide users with suggestions and information on supermarkets, restaurants, or hospitals.

[1768] 6. The emotion recognition engine analyzes the user's emotional state and adjusts the suggested content accordingly.

[1769] Hardware and software to be used

[1770] Virtual reality devices: Oculus Rift, HTC Vive, Sony PlayStation VR, etc.

[1771] Speech-to-Text API: Google Speech-to-Text

[1772] Emotion recognition engine: Azure Cognitive Services Emotion API

[1773] Server-side frameworks: Django, Flask

[1774] Data analysis and management: Dedicated nutritional and medical databases

[1775] Language processing solutions: Google Cloud Natural Language API

[1776] Program Processing Overview

[1777] User input

[1778] The user puts on VR goggles, logs into a virtual store, and uses a voice recognition API to input their meal order and health status. For example, they might say, "I had toast and coffee for breakfast today."

[1779] Data transmission

[1780] The input data is transmitted to the server in real time via the internet. The server receives the transmitted data and proceeds to the next analysis step.

[1781] Data Analysis

[1782] The server analyzes the received dietary and symptom data. Here, it uses dedicated nutritional and medical databases to identify nutrient content and possible diseases.

[1783] Proposal generation

[1784] To supplement any missing nutrients, the server automatically generates appropriate meal plans. Furthermore, if you feel unwell, it will suggest possible illnesses and provide initial treatment options.

[1785] Presentation to the user

[1786] The generated meal menus and health information are presented to the user within the virtual store. Furthermore, information on nearby supermarkets, restaurants, and hospitals is included.

[1787] Emotional analysis and proposal adjustment

[1788] The emotion recognition engine analyzes the user's voice data and input to determine their emotional state. For example, if the system detects that the user is stressed, it adds suggestions for stress-reducing meals and activities.

[1789] Specific example

[1790] If user A enters "I had a café au lait and a croissant for lunch today," the server identifies a vitamin B deficiency. Simultaneously, the emotion recognition engine recognizes the user's stress level from their voice data. Based on this information, the server suggests "grilled chicken and avocado salad" and also notifies the user of nearby supermarkets.

[1791] Examples of prompts for a generative AI model:

[1792] "The user entered their meal plan and it was identified that they are deficient in B vitamins. Since the user is under stress, please suggest meal options that would help reduce stress."

[1793] Expected output:

[1794] "Grilled chicken and avocado salad would be good. Vitamin B complex and potassium are effective for stress reduction. You can buy these ingredients at your local supermarket."

[1795] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1796] Step 1:

[1797] The user puts on VR goggles and logs into the virtual store. They enter their user ID and password as login information. This allows the user to access the system, and the system obtains the user's identification information.

[1798] Step 2:

[1799] The user enters their meal menu and symptoms of illness. A speech recognition API (e.g., Google Speech-to-Text) is used to convert the voice data into text, inputting the meal menu and health status. The input data includes food names, time of consumption, and detailed symptoms. This input data is then sent to the server.

[1800] Step 3:

[1801] The server analyzes the received data. First, it extracts the nutritional components of the food using a dedicated nutrition database. Next, it uses a medical database to extract possible diseases based on the entered symptoms. The identified nutrient deficiencies and disease possibilities are the output of this step.

[1802] Step 4:

[1803] The server identifies deficient nutrients and generates meal plans to compensate for them. Using a generation AI model, it automatically generates menus to optimize the user's nutritional balance. The input here is the analyzed information on deficient nutrients, and the output is the recommended meal plan.

[1804] Step 5:

[1805] The server analyzes the user's emotional state. Using an emotion recognition engine (e.g., Azure Cognitive Services Emotion API), it analyzes the user's voice tone and input data to determine their emotional state. The input data can be voice or text, and the output is the user's emotional level (e.g., stress, joy, anger).

[1806] Step 6:

[1807] The server adjusts suggestions based on the user's emotional state. Based on the generated emotional analysis data, it optimizes meal menus and health advice to match the user's emotional state. For example, if a user is feeling stressed, it adds stress-reducing foods and relaxation methods to the menu.

[1808] Step 7:

[1809] This service searches for information on supermarkets, restaurants, and hospitals recommended by the server. Based on the user's location, it searches the internet for nearby stores and hospitals and provides the most suitable options for the user. The input is the user's location and suggested menus, and the output is a list of stores and hospitals.

[1810] Step 8:

[1811] The system provides users with generated meal menus and advice. The suggestions are displayed to the user within the virtual store, and notifications are also sent to other devices. This step utilizes a user-friendly interface, providing information in an intuitive and easily accessible manner.

[1812] Step 9:

[1813] The feedback function allows users to input feedback on their emotional state and physical condition after implementing the suggested actions. This enables the system to update the data, allowing for more accurate and personalized future suggestions. The input data is feedback information, and the output represents improvements in the system's analysis accuracy.

[1814] 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 controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[1815] The data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One 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">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1816] 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 this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[1817] Furthermore, the emotion identification model 59, acting 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 a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1818] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[1819] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[1820] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[1821] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[1822] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is 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 the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[1823] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[1824] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[1825] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[1826] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[1827] 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.

[1828] Furthermore, it is not necessary to store the entirety 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 the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[1829] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[1830] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of 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). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[1831] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[1832] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[1833] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and e...

Claims

1. A means for users to input their meal order, A means of sending the meal menu entered by the user to the server, A method for the server to analyze the received meal menu and identify deficient nutrients, A means for generating a meal plan to supplement the nutrient deficiencies identified by the server, A means of providing the user with a meal menu generated by the server, A method for searching for and suggesting supermarkets or restaurants based on the user's location information, A system that includes this.

2. A means for users to input symptoms of illness, A means of sending the symptoms entered by the user to the server, The server analyzes the symptoms and presents possible diseases, A server that searches for and suggests the most suitable hospital based on user preferences and reviews, The system according to claim 1, including the following:

3. The system according to claim 1, further comprising means for verifying meal menus and symptom information entered by the user and confirming that there is no incomplete or inappropriate data.

Images