system

Abstract

We provide the system. [Solution] A means for receiving data entered by the user, A server including artificial intelligence for analyzing the input data, A means for generating appropriate medical information or recommended actions based on the aforementioned analysis results, Means for notifying the user of the generated information or recommended actions, Based on the aforementioned notification, a means to set up an online consultation with a doctor as needed, 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 persona chatbot control method performed by at least one processor, the method including 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 an aging society with a high proportion of elderly people, due to the thinning of the connection between people, there is a risk of an increase in problems such as isolation and solitary death. In addition, since it becomes difficult for elderly people to appropriately obtain medical information and life support, there is a risk of deterioration of health and quality of life. In order to solve these problems, there is a need for a mechanism that comprehensively provides medical care, life support, and mental care so that elderly people do not become isolated.

Means for Solving the Problems

[0005] The present invention is a system that includes means for receiving data entered by a user, a server including artificial intelligence for analyzing the entered data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, and means for setting up an online consultation with a doctor as necessary based on the notification. Furthermore, the present invention can alleviate difficulties in daily life by including means for analyzing the user's inputted lifestyle needs and providing appropriate lifestyle support, and means for coordinating the provided lifestyle support with supporters. In addition, the present invention can reduce isolation and feelings of loneliness and support mental health by including means for analyzing the user's inputted mental state and generating appropriate advice or mental care, and means for proposing communities among users. Thus, the present invention provides a system that comprehensively provides medical care, lifestyle support, and mental care in a super-aging society, and prevents users from becoming isolated.

[0006] "Entered data" refers to information provided to the system by the user, including medical conditions, symptoms, lifestyle needs, and mental state.

[0007] "Means of receiving" refers to the processing steps and devices that receive data input from the user on the system side.

[0008] A "server including artificial intelligence" refers to a server device equipped with algorithms and models for analyzing data.

[0009] "Means of analysis" refers to a function that uses artificial intelligence to understand the content of input data and generate appropriate analysis results.

[0010] "Generating means" refers to a function that processes data to output specific information or actions to the user based on the analysis results.

[0011] "Notification means" refers to communication and display means for informing users of generated information and recommended actions.

[0012] "Methods for setting up online consultations with doctors" refers to functions that allow doctors and users to coordinate online consultations, make reservations, and communicate as needed.

[0013] "Lifestyle needs" refers to the specific requests and problems that users face in their daily lives.

[0014] "Life support" refers to providing services and resources to support users according to their lifestyle needs.

[0015] "Supporters" refers to individuals and organizations that collaborate to provide actual support to users in their daily lives.

[0016] "State of mind" refers to the user's mental or emotional situation or worries.

[0017] "Advice or emotional support" refers to the process of providing appropriate advice or support regarding the user's emotional state.

[0018] "Means of suggesting communities" refers to features that recommend participation in online groups and networks to facilitate interaction among users in similar situations. [Brief explanation of the drawing]

[0019] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This 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

[0020] Hereinafter, an example of an embodiment of a system according to the technology of the present disclosure will be described according to the accompanying drawings.

[0021] First, the language used in the following description will be explained.

[0022] 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).

[0023] 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.

[0024] 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.

[0025] 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).

[0026] 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."

[0027] [First Embodiment]

[0028] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0029] 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.

[0030] 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).

[0031] 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.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0036] 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.

[0037] 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.

[0038] 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.

[0039] 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".

[0040] Modes for carrying out the invention

[0041] This invention relates to a system that utilizes generative AI to comprehensively provide medical care, lifestyle support, and mental health care in order to solve various problems in a super-aging society. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence, a terminal that generates and notifies appropriate information and actions based on the analysis results, and means for setting up online consultations as needed.

[0042] 1. Healthcare (connecting people with doctors)

[0043] Program processing:

[0044] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[0045] 2. The terminal sends the input information to the server.

[0046] 3. The server uses an AI module to analyze this information and generate the cause of the back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[0047] 4. The device notifies the user of the generated information.

[0048] 5. Users can choose to book an online doctor consultation as needed, and the server will coordinate the schedule with the doctor and confirm the online consultation booking.

[0049] 2. Life (Connecting people with supporters)

[0050] Program processing:

[0051] 1. The user enters into the application the difficulties they face in their daily life. For example, the user might enter, "It's difficult to go shopping."

[0052] 2. The device sends this information to the server.

[0053] 3. The server uses an AI module to analyze the user's needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[0054] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[0055] 3. Security (connecting people's hearts)

[0056] Program processing:

[0057] 1. The user enters their emotional state or worries into the application. For example, the user might enter "I'm lonely because I live alone."

[0058] 2. The device sends this information to the server.

[0059] 3. The server uses an AI module to analyze the user's mental state and generate appropriate advice and mental health care methods.

[0060] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0061] 5. The server further proposes communities for users with similar problems and supports interaction among users through their participation.

[0062] In this way, the system uses AI to analyze data based on information entered by users and proposes appropriate information and actions in medical care, daily living support, and mental health care. Furthermore, by arranging online consultations with doctors and collaboration with local supporters as needed, it provides an environment where users can lead fulfilling lives without feeling isolated.

[0063] The following describes the processing flow.

[0064] 1. Healthcare (connecting people with doctors)

[0065] Processing steps

[0066] Step 1:

[0067] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0068] Step 2:

[0069] The terminal sends the entered data about the patient's condition and symptoms to the server.

[0070] Step 3:

[0071] The server inputs the received information into the AI ​​module and begins analysis.

[0072] Step 4:

[0073] The server's AI analyzes the disease state and symptoms using natural language processing technology.

[0074] Step 5:

[0075] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, information on over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[0076] Step 6:

[0077] The server formats the generated information and creates a response message.

[0078] Step 7:

[0079] The terminal receives a response message and displays it to the user.

[0080] Step 8:

[0081] Users can choose to book an online doctor consultation as needed.

[0082] Step 9:

[0083] The server receives the user's appointment request and coordinates the schedule with the doctor.

[0084] Step 10:

[0085] The server confirms the reservation and sends a reservation confirmation notification to the user.

[0086] 2. Life (Connecting people with supporters)

[0087] Processing steps

[0088] Step 1:

[0089] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[0090] Step 2:

[0091] The device sends the entered data on lifestyle needs to the server.

[0092] Step 3:

[0093] The server inputs the received information into the AI ​​module and begins analysis.

[0094] Step 4:

[0095] The server's AI analyzes needs using natural language processing technology.

[0096] Step 5:

[0097] The server's AI identifies appropriate life support methods (e.g., volunteer work, delivery services) based on the analysis results.

[0098] Step 6:

[0099] The server formats the life support suggestions and creates a response message.

[0100] Step 7:

[0101] The terminal receives a response message and displays it to the user.

[0102] Step 8:

[0103] The user selects the most appropriate method from among the suggested life support options.

[0104] Step 9:

[0105] The terminal sends the user's selection to the server.

[0106] Step 10:

[0107] The server receives the user's selection and coordinates with supporters to arrange assistance.

[0108] 3. Security (connecting people's hearts)

[0109] Processing steps

[0110] Step 1:

[0111] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0112] Step 2:

[0113] The device sends the entered data about the mental state to the server.

[0114] Step 3:

[0115] The server inputs the received information into the AI ​​module and begins analysis.

[0116] Step 4:

[0117] The server's AI analyzes the user's emotional state and worries using natural language processing technology.

[0118] Step 5:

[0119] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[0120] Step 6:

[0121] The server formats advice and emotional support methods and creates response messages.

[0122] Step 7:

[0123] The terminal receives a response message and displays it to the user.

[0124] Step 8:

[0125] The server generates a message suggesting a community for users in similar situations.

[0126] Step 9:

[0127] The device receives the suggestion message and displays it to the user.

[0128] Step 10:

[0129] If a user wishes to join the community, the device sends a participation request to the server.

[0130] Step 11:

[0131] The server receives the participation request and provides the user with information on how to access the community.

[0132] The above outlines the specific processing steps in each system. In this way, systems utilizing generative AI can appropriately support users in medical care, daily living assistance, and mental health care.

[0133] (Example 1)

[0134] 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."

[0135] This invention aims to provide a comprehensive support system utilizing generative AI to solve problems related to medical care, daily living support, and mental health care in a super-aging society. Traditionally, users had to access these services individually, and the lack of coordination resulted in inefficient support. Furthermore, many elderly people are unable to fully utilize digital technology, creating a need for a user-friendly system.

[0136] 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.

[0137] In this invention, the server includes means for receiving data entered by a user, a data processing device including artificial intelligence for analyzing the entered data, and means for generating appropriate medical information or recommended actions based on the analysis results. This makes it possible for the AI ​​to analyze the data based on the information entered by the user and propose appropriate information and actions in medical care, life support, and mental health care.

[0138] A "user" refers to a person who uses this system to input information about their medical care, lifestyle support, and mental health care, and receives support based on that information.

[0139] A "data processing device" refers to a combination of hardware and software, including artificial intelligence, used to analyze data entered by users and generate appropriate information and actions based on that analysis.

[0140] A "server" is a computer system on a network that includes a data processing unit, and its role is to receive input data from users, analyze it, and provide the generated information.

[0141] "Medical information" refers to information including diagnostic results obtained by analyzing data on the user's health status and medical condition, recommended countermeasures and treatments, and the need for a doctor's consultation.

[0142] "Recommended actions" refer to specific actions or measures that users should take, generated based on the analysis of their input data.

[0143] "Online consultation" refers to a service that allows experts and users to communicate directly via the internet. In medical contexts, this includes consultations with doctors, and in lifestyle support, it includes communication with supporters and guidance on daily living.

[0144] "Life support" refers to support services aimed at resolving difficulties in users' daily lives, and includes, for example, grocery shopping assistance, household support, and introductions to local volunteers.

[0145] A "supporter" refers to an individual or organization that works in conjunction with a user to provide life support.

[0146] "Mental health care" refers to advice and measures to address the user's mental state, including, for example, counseling, instruction in relaxation techniques, and suggestions for community participation.

[0147] A "community" refers to a place where users with similar problems or needs can gather and help each other. Online forums and chat groups are examples of this.

[0148] This invention relates to a system for comprehensively solving problems related to medical care, daily living support, and mental health care in a super-aging society. This system utilizes a generative AI model to analyze data entered by the user and provide appropriate information and actions.

[0149] The system configuration consists of a terminal that receives user input data, a server that analyzes the data, a terminal that notifies users of information and recommended actions generated based on the analysis results, and means for setting up online consultations.

[0150] Specific hardware includes devices such as smartphones and tablets used by users, as well as servers with powerful data processing capabilities. The term "server" refers to a data processing device, and this definition assumes the use of cloud services.

[0151] The software used includes generative AI models installed on the server. For example, an AI model employing natural language processing (NLP) technology is used for analyzing medical information, while machine learning algorithms are used for analyzing lifestyle support data. Additionally, programs that communicate via APIs are included for setting up notifications and online consultations.

[0152] Specific example 1: Healthcare (connecting people with doctors)

[0153] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[0154] 2. The device sends this information to the server.

[0155] 3. The server uses NLP technology to analyze the information it receives and generates information about the cause of lower back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[0156] 4. The device notifies the user of the information it has generated.

[0157] 5. Users can book online doctor consultations as needed, and the server will coordinate schedules with appropriate doctors and confirm the online consultation booking.

[0158] Example 2: Daily Life (Connecting people with supporters)

[0159] 1. The user enters into the application the difficulties they face in their daily life. For example, they might enter, "It's difficult to go shopping."

[0160] 2. The device sends this information to the server.

[0161] 3. The server uses machine learning algorithms to analyze life needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[0162] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[0163] Specific example 3: Security (connecting people's hearts)

[0164] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0165] 2. The device sends this information to the server.

[0166] 3. The server uses NLP technology to analyze the user's mental state and generate appropriate advice and mental health care methods.

[0167] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0168] 5. The server proposes communities for users with similar problems and supports them in interacting with each other by encouraging participation.

[0169] Example of a prompt

[0170] "My lower back has been hurting lately, what should I do?"

[0171] "I'm having trouble going shopping. Please help me."

[0172] "I'm lonely living alone."

[0173] This system uses a generative AI model to analyze user input with high accuracy and provide various types of support quickly and appropriately. As a result, users can gain an environment where they can comprehensively resolve issues related to their health, lifestyle, and mental well-being.

[0174] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0175] Healthcare (connecting people with doctors)

[0176] Program processing steps

[0177] Step 1:

[0178] The user enters their medical condition and symptoms into the application.

[0179] Input: User-generated text (e.g., "My back has been hurting lately").

[0180] Output: Input data (text data).

[0181] Step 2:

[0182] The terminal sends the input information to the server.

[0183] Input: Text data entered by the user.

[0184] Data processing: The terminal encrypts the text data and sends it to the server using a secure communication method (e.g., HTTPS).

[0185] Output: Encrypted data packets.

[0186] Step 3:

[0187] The server analyzes the information using an AI module.

[0188] Input: Received encrypted data.

[0189] Data processing: The server decodes the data and analyzes the text using generative AI models and natural language processing (NLP) techniques. Specifically, it activates the model and matches it with patterns and datasets related to the user's symptoms.

[0190] Output: Analysis results (e.g., causes of lower back pain and recommended countermeasures).

[0191] Step 4:

[0192] The server generates the countermeasures.

[0193] Input: Analysis result data.

[0194] Data processing: Using an interactive AI engine, recommended actions (e.g., stretching, over-the-counter medication, consultation with a specialist) are generated.

[0195] Output: Recommended countermeasures list.

[0196] Step 5:

[0197] The device notifies the user of the necessary countermeasures.

[0198] Input: Recommended countermeasures list.

[0199] Data processing: Convert the generated recommended actions into a user-friendly format (e.g., pop-up notifications or in-app messages).

[0200] Output: Notifications displayed to the user.

[0201] Step 6:

[0202] The user books an online doctor consultation.

[0203] Input: User reservation information (e.g., desired date and time).

[0204] Data processing: Send reservation information to the server via the input form.

[0205] Output: Submitted reservation request.

[0206] Step 7:

[0207] The server adjusts the schedule and confirms the reservation.

[0208] Input: Reservation request.

[0209] Data processing: Check doctors' availability and finalize schedules using MICROSOFT® TEAMS® or other online meeting platforms.

[0210] Output: Notification of confirmed reservation information.

[0211] Life (Connecting people with supporters)

[0212] Program processing steps

[0213] Step 1:

[0214] Users input the difficulties they face in their daily lives into the application.

[0215] Input: User-generated text (e.g., "It's difficult to go shopping").

[0216] Output: Input data (text data).

[0217] Step 2:

[0218] The device sends this information to the server.

[0219] Input: Text data entered by the user.

[0220] Data processing: Encrypt text data and send it to the server using a secure communication method.

[0221] Output: Encrypted data packets.

[0222] Step 3:

[0223] The server analyzes lifestyle needs.

[0224] Input: Received encrypted data.

[0225] Data processing: The server decrypts the data and uses AWS® SageMaker's AI module to analyze lifestyle needs. It then matches the data against a dataset to identify the necessary support methods.

[0226] Output: Analysis results (e.g., appropriate support methods).

[0227] Step 4:

[0228] The server generates the appropriate support method.

[0229] Input: Analysis result data.

[0230] Data processing: Based on the analysis results, the AI ​​generates appropriate support methods (e.g., suggesting local volunteers or delivery services).

[0231] Output: List of supported methods.

[0232] Step 5:

[0233] The device will notify you of the support method.

[0234] Input: List of support methods.

[0235] Data processing: Notify users of the generated support methods in an easy-to-understand format.

[0236] Output: Notifications displayed to the user.

[0237] Step 6:

[0238] The user selects the support option.

[0239] Input: User selection information.

[0240] Data processing: The user selects their preferred support method and sends that selection information to the server.

[0241] Output: Sent selection information.

[0242] Step 7:

[0243] The server coordinates with supporters to arrange assistance.

[0244] Input: Submitted selection information.

[0245] Data processing: Use integration tools such as Slack to notify supporters of the support needed and make specific arrangements.

[0246] Output: Notification of the assistance arranged.

[0247] Security (connecting people's hearts)

[0248] Program processing steps

[0249] Step 1:

[0250] Users input their emotional state and worries into the application.

[0251] Input: User-generated text (e.g., "I'm lonely living alone").

[0252] Output: Input data (text data).

[0253] Step 2:

[0254] The device sends this information to the server.

[0255] Input: Text data entered by the user.

[0256] Data processing: Encrypt text data and send it to the server using a secure communication method.

[0257] Output: Encrypted data packets.

[0258] Step 3:

[0259] The server analyzes the state of mind.

[0260] Input: Received encrypted data.

[0261] Data processing: The server decodes the data and analyzes the mental state using Google Cloud AI modules. Natural language processing (NLP) techniques are used for the analysis.

[0262] Output: Analysis results (e.g., appropriate advice or methods for mental health care).

[0263] Step 4:

[0264] The server generates the care instructions.

[0265] Input: Analysis result data.

[0266] Data processing: Based on the analysis results, generate advice and mental health care methods (e.g., suggestions for yoga or meditation, suggestions for participating in community center events).

[0267] Output: List of care methods.

[0268] Step 5:

[0269] The device will notify you of care instructions.

[0270] Input: List of care methods.

[0271] Data processing: Notify users of the generated care methods in an easy-to-understand format.

[0272] Output: Notifications displayed to the user.

[0273] Step 6:

[0274] The server generates community suggestions.

[0275] Input: List of methods for mental health care.

[0276] Data processing: Based on the analysis results, generate suggestions for communities and online forums where users with similar problems can participate.

[0277] Output: Community suggestion list.

[0278] Step 7:

[0279] The server supports community participation.

[0280] Input: Community suggestion list.

[0281] Data processing: Provide users with information to participate in the proposed community and enable easy access to the community using platforms such as Discord.

[0282] Output: Notification regarding the participation procedure.

[0283] This realizes a system that enables users to easily manage information related to their health, life, and mental care and receive optimal support.

[0284] (Application Example 1)

[0285] Next, Application Example 1 will be described. In the following description, the data processing device 12 is referred to as a "server", and the smart device 14 is referred to as a "terminal".

[0286] In an aging society, it has become difficult for the elderly to maintain their daily lives on their own. In particular, in meal preparation and health management, the limited means of receiving appropriate support is a problem. Also, in order for the elderly to live a healthy and safe life without isolation, comprehensive support integrating medical care, life support, and mental care is necessary.

[0287] The specific processing by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0288] In this invention, the server includes means for receiving data input by a user, means including artificial intelligence for analyzing the input data, means for generating appropriate medical information or recommended actions based on the analysis result, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as needed based on the notification, means for generating a suitable meal plan and ingredient suggestions for the user based on the notification, and means for arranging the purchase and delivery of ingredients based on the suggestions. This enables comprehensive support for the elderly to maintain a healthy and safe life.

[0289] "Data entered by the user" refers to the information and requests provided by those who use the system.

[0290] "Means" refers to the methods, devices, or processes used to achieve a specific objective.

[0291] "Artificial intelligence for analysis" refers to AI technology that analyzes input data and derives relevant information and recommended actions.

[0292] A "server" refers to a computer system used for managing and processing data.

[0293] "Medical information" refers to information and knowledge related to health, treatment, and prevention.

[0294] "Recommended actions" refer to the appropriate actions or methods that should be taken, derived from the user's input data.

[0295] "Means of notification" refers to the methods or devices by which a system communicates information or alerts to a user.

[0296] "Methods for setting up online consultations" refers to the methods and devices used to schedule and prepare systems for users to communicate remotely with experts.

[0297] A "meal plan" refers to a set of meals planned based on the user's health condition and preferences.

[0298] "Food ingredient suggestions" refers to recommended foods and ingredients that users should purchase.

[0299] "Means of arranging purchase and delivery" refers to the procedures and systems for procuring the ingredients selected by the user and having them delivered to their home.

[0300] "Living needs" refers to the requirements and necessary support content related to the user's entire life.

[0301] "Living support" refers to various services and assistance provided to smoothly progress the user's daily life.

[0302] "Means of arranging in cooperation with supporters" refers to the methods and devices for carrying out the procedures in cooperation with volunteers and specialized services to provide the support required by the user.

[0303] "Mental state" refers to the user's mental health and emotional state.

[0304] "Advice" refers to the guidance and advice provided to the user.

[0305] "Mental care" refers to the support and activities for maintaining and improving the user's mental health.

[0306] "Means of proposing a community" refers to the methods and devices for guiding the user to a place for communication with other users having the same interests and concerns.

[0307] The system for implementing this invention receives the data input by the user, performs analysis, and makes appropriate proposals in various aspects of medical information, living support, and mental care, thereby providing support for the elderly to live a healthy and fulfilling life.

[0308] Hardware and software to be used

[0309] Smartphone, tablet: A terminal for the user to input data and receive proposed information.

[0310] Server: Performs data analysis and generation of proposals.

[0311] Artificial intelligence (AI) modules: Using TENSORFLOW® and Keras, the system analyzes user-input data and generates appropriate medical information, lifestyle support, and mental health care suggestions.

[0312] Communication API: Use Twilio to schedule online doctor and nutritionist consultations as needed.

[0313] System operation

[0314] 1. Data Input and Reception: Users input data into the application using their smartphones or tablets. For example, they might input symptoms, difficulties in daily life, or emotional worries such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone."

[0315] 2. Data Analysis: The server receives the input data and analyzes it using artificial intelligence modules (TensorFlow and Keras). Based on the analysis results, appropriate medical information (stretching methods, treatments), lifestyle support (suggestions for delivery services), and mental health care (suggestions for online consultations and community participation) are generated.

[0316] 3. Suggestion Generation and Notification: Information and suggestions generated on the server are notified to the user's terminal. Based on these notifications, users can arrange online doctor consultations or food delivery services.

[0317] 4. Setting up online consultations: Use communication APIs such as Twilio to schedule and confirm online consultations with doctors and nutritionists as needed.

[0318] Specific example

[0319] A 70-year-old elderly person living alone enters a request into the app for "healthy meals that take diabetes into consideration." The server analyzes this information and suggests low-sugar menus and preparation methods. The user can then order the ingredients for the suggested menus through a food delivery service, which will be delivered that evening. Furthermore, they can also book online consultations with a nutritionist if needed.

[0320] Example of a prompt

[0321] "Please suggest a healthy and delicious dinner."

[0322] "Please share some breakfast ideas that are suitable for people with diabetes."

[0323] "Please create a list of ingredients for this week."

[0324] In this way, this system provides comprehensive support for older adults to live safely and healthily.

[0325] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0326] Step 1:

[0327] User data entry

[0328] Users use smartphones or tablets to input data about their medical condition, lifestyle needs, and mental state into the application. For example, they might enter prompts such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone." This input data is recorded on the device and immediately sent to the server.

[0329] Step 2:

[0330] Data reception and preprocessing

[0331] The server receives user input data sent from the terminal. It then formats the received data and converts it into a parsable format. This preprocessing involves using natural language processing (NLP) tools to tokenize and grammatically analyze the text. For example, if the user inputs "My back has been hurting lately," the server generates an appropriate text format.

[0332] Step 3:

[0333] Data analysis and model application

[0334] The server inputs pre-processed data into a generative AI model (using TensorFlow or Keras). The AI ​​model analyzes the received data and generates appropriate medical information, lifestyle support, and mental health care suggestions. For example, it might analyze "lower back pain" and suggest stretching methods and treatments. The output includes a list of analysis results and suggestions.

[0335] Step 4:

[0336] Generation and transmission of proposal information

[0337] The server generates specific suggestion information based on the analysis results of the AI ​​model. This suggestion information includes medical information, lifestyle support, and mental health care methods that best suit the user's needs. The generated information is then formatted again in text format and sent to the user's device. For example, the device might receive notifications such as "Do some back stretches" or "Consider using a local delivery service."

[0338] Step 5:

[0339] User awareness and choice

[0340] The user reviews the suggested information displayed on their device. They can then select actions such as online doctor consultations, grocery ordering, or nutritionist consultations, as needed. Once the user selects an action, that information is sent back to the server.

[0341] Step 6:

[0342] Arrangement for the execution of the action

[0343] The server performs the necessary actions based on the user's selections. For example, it might use the Twilio API to set up an online doctor consultation appointment. It might also arrange for groceries to be ordered and delivered through a food delivery service based on the selected suggestions. Once all arrangements are complete, confirmation information is sent to the user's device.

[0344] This series of processing steps will result in a system that comprehensively supports the health management, daily living assistance, and mental health care of the elderly.

[0345] 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.

[0346] Modes for carrying out the invention

[0347] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society, and can provide more personalized support by combining generative AI and an emotion engine. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence (AI), a terminal that generates and notifies appropriate information and actions based on the analysis results, means for setting up online consultations as needed, and an emotion engine that recognizes the user's emotions.

[0348] 1. Providing medical information combined with emotion recognition.

[0349] Program processing:

[0350] 1. The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0351] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0352] 3. The server's AI analyzes the entered medical conditions and symptoms using natural language processing and combines them with emotional data to generate medical information and recommended actions. For example, if the user is feeling anxious, a reassuring message will be added.

[0353] 4. The device notifies the user of the medical information it has generated.

[0354] 5. The user selects the option to book an online doctor consultation as needed, and the server coordinates the schedule with the doctor and confirms the appointment.

[0355] 2. Providing life support that combines emotion recognition.

[0356] Program processing:

[0357] 1. The user inputs their daily life difficulties and needs into the application. For example, they might input, "It's difficult to go shopping."

[0358] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0359] 3. The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate appropriate lifestyle support methods (e.g., volunteering, delivery services). For example, if a user is feeling stressed, it will also suggest relaxation methods to reduce stress.

[0360] 4. The terminal identifies a specific life support method and notifies the user. If the user selects a method, the server coordinates with the supporter to arrange the assistance.

[0361] 3. Mental care combined with emotion recognition

[0362] Program processing:

[0363] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0364] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0365] 3. The server's AI analyzes the user's emotional state and concerns using natural language processing technology, and combines this with emotional data to generate appropriate advice and methods for emotional care. For example, if a user is feeling sad, it will suggest encouraging messages and activities to lift their spirits.

[0366] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0367] 5. The server further proposes communities for users in similar situations and supports users in interacting with each other by encouraging their participation.

[0368] This system can provide more personalized support by combining user input data with analysis results from an emotion engine. This allows it to comprehensively cover medical care, lifestyle support, and mental health care, thereby improving the user's quality of life.

[0369] The following describes the processing flow.

[0370] 1. Healthcare (connecting people with doctors)

[0371] Processing steps

[0372] Step 1:

[0373] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0374] Step 2:

[0375] The terminal sends the medical condition and symptoms entered, as well as emotional data (e.g., anxiety, pain) recognized by the emotion engine through user facial recognition and voice analysis, to the server.

[0376] Step 3:

[0377] The server passes the received data to the AI ​​module, which then begins analyzing the patient's condition and symptoms.

[0378] Step 4:

[0379] The server's AI uses natural language processing to analyze the patient's condition and symptoms, and combines this with emotional data to generate analysis results.

[0380] Step 5:

[0381] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, recommendations for over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[0382] Step 6:

[0383] The server formats the generated medical information and adds reassuring messages tailored to the user's emotions.

[0384] Step 7:

[0385] The terminal receives the generated response message and notifies the user.

[0386] Step 8:

[0387] Users can choose to book an online doctor consultation as needed.

[0388] Step 9:

[0389] The server receives the user's appointment request and coordinates the schedule with the doctor.

[0390] Step 10:

[0391] The server confirms the online consultation appointment and sends a reservation confirmation notification to the user.

[0392] 2. Life (Connecting people with supporters)

[0393] Processing steps

[0394] Step 1:

[0395] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[0396] Step 2:

[0397] The device sends the inputted lifestyle needs and emotional data recognized by the user's emotion engine (e.g., stress, fatigue) to the server.

[0398] Step 3:

[0399] The server passes the received data to the AI ​​module, which then begins analyzing lifestyle needs.

[0400] Step 4:

[0401] The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate analysis results.

[0402] Step 5:

[0403] The server's AI generates appropriate life support methods (e.g., volunteering, delivery services) based on the analysis results.

[0404] Step 6:

[0405] The server formats the generated life support information and adds stress reduction suggestions that take the user's emotions into consideration.

[0406] Step 7:

[0407] The terminal receives the generated response message and notifies the user.

[0408] Step 8:

[0409] The user selects the most appropriate method from among the suggested life support options.

[0410] Step 9:

[0411] The terminal sends the user's selection to the server.

[0412] Step 10:

[0413] The server coordinates with supporters based on the selected life support information and arranges assistance.

[0414] 3. Security (connecting people's hearts)

[0415] Processing steps

[0416] Step 1:

[0417] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0418] Step 2:

[0419] The device sends the entered mental state and emotional data recognized by the emotion engine (e.g., loneliness, fatigue) to the server.

[0420] Step 3:

[0421] The server passes the received data to the AI ​​module, which then begins analyzing the user's emotional state and concerns.

[0422] Step 4:

[0423] The server's AI analyzes the user's emotional state and worries using natural language processing technology, and combines this with emotional data to generate analysis results.

[0424] Step 5:

[0425] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[0426] Step 6:

[0427] The server formats the generated advice and emotional support methods, and also adds messages that empathize with the user's feelings.

[0428] Step 7:

[0429] The terminal receives the generated response message and notifies the user.

[0430] Step 8:

[0431] The server then generates a message suggesting communities for users in similar situations.

[0432] Step 9:

[0433] The device receives the suggestion message and notifies the user.

[0434] Step 10:

[0435] If a user wishes to join the community, the device sends a participation request to the server.

[0436] Step 11:

[0437] The server receives the participation request and provides the user with information on how to access the community.

[0438] The above outlines the specific processing steps in each system. This system combines generative AI and an emotion engine to provide medical care, lifestyle support, and mental health care while taking the user's emotions into consideration, thereby improving the user's quality of life.

[0439] (Example 2)

[0440] 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".

[0441] In a super-aging society, the problems faced by the elderly are diverse, encompassing healthcare, daily living support, and mental health care. Current systems lack comprehensive support for these needs, making it difficult to provide personalized assistance. Furthermore, support that takes into account the user's emotional state is not being provided, resulting in a lack of truly needed support.

[0442] The specific processing performed by the specific 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 receiving data input by a user, means including artificial intelligence for analyzing the input data, means for generating emotion data using an emotion analysis engine for analyzing the user's emotions, means for providing analysis results by combining the emotion data and input data, means for generating appropriate medical information, lifestyle support methods, or mental health care based on the analysis results, means for notifying the user of the generated information, recommended actions, or mental health care, and means for setting up an online consultation with a doctor or suggesting a community of users as necessary based on the notification. This makes it possible to provide personalized medical information, lifestyle support, and mental health care that takes the user's emotions into consideration.

[0443] A "user" refers to an individual who uses the system to receive medical information, lifestyle support, or mental health care.

[0444] "Input data" refers to information about medical conditions, lifestyle needs, and mental state entered into the application by the user.

[0445] A "server" refers to a computer system that analyzes data received from users and generates and notifies them of the results.

[0446] "Artificial intelligence" refers to machine learning models or natural language processing technologies that analyze input data and generate appropriate information or recommended actions.

[0447] A "sentiment analysis engine" refers to a software module that analyzes emotions from user input data and generates emotional data.

[0448] "Emotional data" refers to information that indicates the user's emotional state, generated by an emotion analysis engine.

[0449] "Analysis results" refer to the output generated by artificial intelligence and emotion analysis engines, based on user input data and emotion data.

[0450] "Medical information" refers to information including diagnoses, treatment methods, and recommended actions related to the user's medical condition.

[0451] "Life support methods" refer to specific support measures and services designed to meet the user's lifestyle needs.

[0452] "Mental health care" refers to advice, suggestions, and support methods for addressing the mental health issues that users are experiencing.

[0453] "Notification" refers to the process of communicating information or actions generated by a server to the user.

[0454] "Online consultation setup" refers to the process of booking and scheduling an online consultation with a medical professional or other expert.

[0455] A "community suggestion" refers to a suggestion made from the server to users to provide a space where users in similar situations can interact with each other.

[0456] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society. By combining generative artificial intelligence (AI) and an emotion analysis engine, the system can provide more personalized support.

[0457] Hardware and software to be used

[0458] Server: Receives data from users, performs data analysis, and provides information. For example, a high-performance cloud server (e.g., AWS, Google Cloud) can be used.

[0459] Terminal: A device used by users to input data and receive results. This includes smartphones, tablets, and personal computers.

[0460] Artificial intelligence (AI): A machine learning model used for data analysis. For example, OpenAI's GPT-4® is used as a generative AI model.

[0461] Emotion analysis engine: Software used to generate user emotion data. Examples include EmotionAI, Affectiva, and IBM Watson® Tone Analyzer.

[0462] Data processing and calculations

[0463] 1. Data entry

[0464] Users access the application on their device and input text about their medical condition, lifestyle needs, and mental state.

[0465] 2. Generation of emotion data

[0466] The device sends the input data to an emotion analysis engine, which then analyzes the user's emotions. For example, it generates emotion tags such as "anxiety," "stress," and "sadness."

[0467] 3. Sending data

[0468] The device sends the analyzed emotion data and input data to the server.

[0469] 4. Data Analysis and Generation

[0470] The server's AI analyzes the received data using natural language processing and combines it with emotional data to generate optimal information and recommended actions. For example, it can generate information such as "medical information," "life support methods," and "mental health care."

[0471] 5. Notification

[0472] The generated information and recommended actions are notified to the user via their device. The user then checks this information on their device.

[0473] 6. Online consultations and community proposals

[0474] If needed, users can choose the option to book an online doctor consultation, and the server will handle scheduling. The system also suggests and allows users to participate in user communities.

[0475] Examples of specific cases and prompt statements

[0476] For example, a user might input "My back has been hurting lately" into the application, expressing anxiety. In this case, the system would operate as follows:

[0477] User input: "My lower back has been hurting lately."

[0478] Example prompt: "If a user types 'My back hurts' and is feeling anxious, what reassuring message can you generate?"

[0479] Based on the "anxiety" tag generated by the emotion analysis engine and the user's medical condition data of "back pain," the server uses AI to generate the following message:

[0480] "Stretching is effective for lower back pain. If you are experiencing any concerns, we recommend consulting a doctor."

[0481] In this way, the system can provide optimal medical information and recommended actions while taking the user's emotions into consideration.

[0482] Similarly, for daily living support and mental health care, personalized support is provided that takes into account the user's emotional data. For example, if a user inputs "It's difficult to go shopping" and is feeling stressed, a message such as "We recommend using a delivery service for shopping and taking deep breaths to reduce stress" will be generated.

[0483] This system makes it possible to improve the quality of life for users by comprehensively covering medical care, daily living support, and mental health care.

[0484] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0485] Step 1:

[0486] The user accesses the application screen and enters their medical condition, lifestyle needs, and mental state. For example, they might enter, "My lower back has been hurting lately."

[0487] Input: Medical condition, lifestyle needs, mental state (text format)

[0488] Output: Input data (medical condition information, etc.)

[0489] Step 2:

[0490] The device sends the input data to an emotion analysis engine to analyze the user's emotions. For example, it uses EmotionAI or Affectiva to generate emotion tags such as "anxiety."

[0491] Input: Input data (medical condition, lifestyle needs, mental state)

[0492] Data processing: Emotional analysis using an emotion analysis engine.

[0493] Output: Sentiment data (sentiment tags)

[0494] Step 3:

[0495] The device sends the analyzed emotion data and input data to the server.

[0496] Input: Input data, sentiment data

[0497] Output: Integrated data sent to the server (input data + sentiment data)

[0498] Step 4:

[0499] The server uses AI (for example, OpenAI's GPT-4) to analyze the received data using natural language processing. For example, it might extract medical information related to "lower back pain."

[0500] Input: Integrated data (input data + sentiment data)

[0501] Data processing: Data analysis using natural language processing

[0502] Output: Analysis results (medical information, lifestyle support methods, mental health care methods)

[0503] Step 5:

[0504] The server combines emotional data to generate medical information and recommended actions. For example, it might generate a message such as, "Stretching is effective for back pain. If you are feeling anxious, we recommend consulting a doctor."

[0505] Input: Analysis results, sentiment data

[0506] Data processing: Information generation using generative AI models.

[0507] Output: Generated information (medical information, recommended actions, mental health care methods)

[0508] Step 6:

[0509] The device receives information generated from the server and notifies the user. The user's device displays the message, "Stretching is effective for lower back pain. If you are feeling anxious, we recommend consulting a doctor."

[0510] Input: Generated information

[0511] Output: Information displayed on the user screen

[0512] Step 7:

[0513] Users can select an online doctor consultation booking option from the application as needed. For example, a user might click the "Online Consultation" button.

[0514] Input: User reservation selection

[0515] Output: Reservation Request

[0516] Step 8:

[0517] The server receives the user's selection, coordinates the schedule with the doctor, and confirms the appointment. The server then notifies the user's device of the confirmed appointment information.

[0518] Input: Reservation Request

[0519] Data processing: Schedule adjustment and reservation confirmation.

[0520] Output: Reservation confirmation notification

[0521] Step 9:

[0522] If necessary, the server will suggest that the user join a community of users in similar situations. For example, it might generate a message such as, "Why not join a community of users who feel lonely?"

[0523] Input: Sentiment data, analysis results

[0524] Data processing: Community proposal generation using generative AI models

[0525] Output: Community suggestion notification

[0526] (Application Example 2)

[0527] 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".

[0528] With the advancement of a super-aging society, the conventional system is insufficient to adequately address the increasing demand for medical care, lifestyle support, and mental health care for the elderly, in terms of individualization and emergency response. Therefore, there is a need for more personalized food delivery services that incorporate emotional recognition, enabling the elderly to live with peace of mind.

[0529] 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. In this invention, the server includes means for receiving data input by the user, a server including artificial intelligence for analyzing the input data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for analyzing the user's emotions with an emotion engine and transmitting the emotion data to the server, and means for analyzing the combination of emotion data and user input data to generate personalized suggestions. This makes it possible to provide services according to the user's emotional state.

[0530] "Means for receiving user-entered data" refers to a function that collects text, voice, or other forms of data entered by the user and sends them to a server for analysis.

[0531] A "server that includes artificial intelligence" is a server that incorporates algorithms to analyze input data and generate appropriate information.

[0532] "Means for generating appropriate medical information or recommended actions based on analysis results" refers to a function that provides users with appropriate medical information and guidance on what to do next, based on the analyzed data.

[0533] "Means for notifying the user of generated information or recommended actions" refers to a function for notifying the user of generated information or recommended actions.

[0534] "Method for setting up online consultations with doctors" refers to a function for setting up online consultations between doctors and users as needed.

[0535] An "emotion engine" refers to software or algorithms used to analyze a user's emotions.

[0536] "Emotional data" refers to data that indicates a user's emotional state, analyzed using an emotion engine.

[0537] "Means of sending to the server" refers to the function of sending collected sentiment data and user input data to the server.

[0538] "A means of combining and analyzing emotional data and user input data to generate personalized suggestions" refers to a function that integrates and analyzes emotional data and input data to create and notify individual users of suggestions optimized for them.

[0539] "Lifestyle needs" refer to the basic requirements and problems that users face in their daily lives.

[0540] "Means of providing life support" refers to functions that provide appropriate support and services based on the user's life needs.

[0541] "Means of arranging life support in cooperation with supporters" refers to the function of arranging and coordinating the supporters and services necessary for life support.

[0542] "State of mind" refers to the user's psychological and emotional state.

[0543] "Means of generating advice or emotional support" refers to functions that provide appropriate advice or support methods based on the user's psychological state.

[0544] "Means of proposing user communities" refers to a function that proposes communities where users in similar situations can connect and help each other.

[0545] This invention is specifically designed for food delivery services in an aging society, combining generative AI and an emotion engine to provide a more personalized service that meets user needs. The system's implementation includes the following elements:

[0546] 1. Hardware and Software Configuration

[0547] Hardware:

[0548] Smartphone: A device for user input and notifications.

[0549] Server: A central device for data analysis and processing.

[0550] software:

[0551] Emotion engine: Uses Microsoft Azure® Emotion API.

[0552] Generative AI: OpenAI GPT-4 is used.

[0553] Food delivery related: Use a dedicated API (e.g., Uber Eats API).

[0554] 2. Program Processing

[0555] User input:

[0556] Users enter their desired dishes and recent preferences as text via a smartphone app. This data is sent to an emotion engine and then forwarded to a server for further analysis.

[0557] Emotion recognition:

[0558] The emotion engine (Microsoft Azure Emotion API) analyzes facial expressions from user input data and camera footage, and extracts emotion data. This data is also sent to the server.

[0559] Information analysis:

[0560] The server's AI (OpenAI GPT-4) analyzes emotional and text data, linking what the user wants with their emotional state. It then generates specific order suggestions and accompanying reassuring messages.

[0561] Suggestion generation:

[0562] The AI ​​generator might suggest, for example, "Japanese sushi," to the user, along with a message like "to help you relax." This suggestion is then communicated to the user via their device.

[0563] Order confirmation and notification:

[0564] Once the user agrees to the proposal, the order is confirmed. Notifications (such as food preparation status and estimated delivery time) are also integrated to provide reassurance, taking into account certain emotional states (such as anxiety).

[0565] Setting up an online consultation:

[0566] If necessary, an online nutritionist consultation regarding dietary habits will be set up. This process is also handled by the server, which manages scheduling and confirms reservations.

[0567] 3. Add specific examples

[0568] The following is an example of a prompt message.

[0569] Example 1: "I've been craving Japanese food lately." (User's judgment)

[0570] User input:

[0571] Text: Lately I've been craving Japanese food.

[0572] Camera footage: A smile and a little fatigue

[0573] Server processing:

[0574] 1. Input text analysis: → I want to eat Japanese food

[0575] 2. Emotional analysis: → Feeling fatigued

[0576] Suggestion generation:

[0577] Generation AI:

[0578] You seem tired. How about ordering some Japanese sushi to help you relax? There's a particular restaurant that's known for its excellent sushi.

[0579] Specific example 2: "It's cold, so I want to eat something warm." - User's anxiety

[0580] User input:

[0581] Text: It's cold, so I want to eat something warm.

[0582] Camera footage: A slightly anxious expression.

[0583] Server processing:

[0584] 1. Input text analysis: → I want some warm food.

[0585] 2. Emotion analysis: → Anxious

[0586] Suggestion generation:

[0587] Generation AI:

[0588] For a meal on a cold day, udon noodles with a soft-boiled egg are perfect. Let the warm soup soothe both your body and soul.

[0589] The delivery time is short, so you can enjoy it right away.

[0590] This system provides food delivery services that cater to the user's emotional state and specific requests.

[0591] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0592] Step 1:

[0593] The user enters text or voice input using a smartphone app. For example, they might input, "I've been craving Japanese food lately." This input data is received and passed on to the next process.

[0594] Step 2:

[0595] The device captures the user's facial expressions through the user's camera feed. The facial expression data is analyzed using an emotion engine (Microsoft Azure Emotion API) to generate emotion data. This emotion data, along with the text input data, is sent to the server.

[0596] Step 3:

[0597] The server receives user input data and sentiment data and performs analysis using AI (OpenAI GPT-4). Specifically, it analyzes the input text information using natural language processing techniques to determine the user's needs and emotional state. In this step, for example, the need "I want to eat Japanese food" and the emotion "I'm feeling tired" might be detected.

[0598] Step 4:

[0599] The server uses a generative AI model (GPT-4) to generate personalized suggestions based on the user's needs and emotional state. The generated suggestion might take the form of, for example, "You seem tired. How about ordering some Japanese sushi to help you relax?" This suggestion data is then passed on to the next step.

[0600] Step 5:

[0601] The terminal receives suggestion data from the server and notifies the user. The user reviews the notification and chooses whether or not to order the suggested dishes.

[0602] Step 6:

[0603] The user agrees to the offer and confirms the food order. The device sends the order information back to the server. The server works with food delivery-related APIs (e.g., Uber Eats API) to process the order. This results in the food being delivered from the specified restaurant to the specified delivery address.

[0604] Step 7:

[0605] After an order is confirmed, the server generates and sends notifications to the user's device regarding delivery status and food preparation status. These notifications include detailed information to provide reassurance, such as status and estimated delivery time.

[0606] Step 8:

[0607] If necessary, and the user requests advice on their diet, the device will offer an option to book an online consultation with a nutritionist. The server will process this booking request, schedule and confirm the appointment, and send a booking confirmation notification to the user.

[0608] The specific steps are as follows.

[0609] Example 1: "I've been craving Japanese food lately." (User's judgment)

[0610] Step 1:

[0611] User input: "Lately I've been craving Japanese food."

[0612] Input data: Text

[0613] Step 2:

[0614] Device analysis: Captures facial expression data.

[0615] Emotion Engine (Microsoft Azure Emotion API) Analysis

[0616] Emotional data generation: Feeling tired (emotional data)

[0617] Step 3:

[0618] Server analysis:

[0619] Input data + emotion data

[0620] Extracting information such as "I want to eat Japanese food" and "I'm feeling tired."

[0621] Step 4:

[0622] Server generation:

[0623] Generation AI (GPT-4)

[0624] Suggestion: You seem tired. How about ordering some Japanese sushi to help you relax?

[0625] Step 5:

[0626] notification:

[0627] Display suggestion message

[0628] Step 6:

[0629] User verification:

[0630] Confirm your order

[0631] Step 7:

[0632] Server processing:

[0633] Send order information to the food delivery API.

[0634] Step 8:

[0635] Delivery status notification:

[0636] Inform the user that their order is in transit and the estimated arrival time.

[0637] Step 9 (Optional):

[0638] Online consultation booking

[0639]

[0640] 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.

[0641] 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.

[0642] 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.

[0643] [Second Embodiment]

[0644] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0645] 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.

[0646] 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).

[0647] 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.

[0648] 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.

[0649] 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).

[0650] 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.

[0651] 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.

[0652] 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.

[0653] 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.

[0654] 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.

[0655] 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".

[0656] Modes for carrying out the invention

[0657] This invention relates to a system that utilizes generative AI to comprehensively provide medical care, lifestyle support, and mental health care in order to solve various problems in a super-aging society. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence, a terminal that generates and notifies appropriate information and actions based on the analysis results, and means for setting up online consultations as needed.

[0658] 1. Healthcare (connecting people with doctors)

[0659] Program processing:

[0660] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[0661] 2. The terminal sends the input information to the server.

[0662] 3. The server uses an AI module to analyze this information and generate the cause of the back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[0663] 4. The device notifies the user of the generated information.

[0664] 5. Users can choose to book an online doctor consultation as needed, and the server will coordinate the schedule with the doctor and confirm the online consultation booking.

[0665] 2. Life (Connecting people with supporters)

[0666] Program processing:

[0667] 1. The user enters into the application the difficulties they face in their daily life. For example, the user might enter, "It's difficult to go shopping."

[0668] 2. The device sends this information to the server.

[0669] 3. The server uses an AI module to analyze the user's needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[0670] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[0671] 3. Security (connecting people's hearts)

[0672] Program processing:

[0673] 1. The user enters their emotional state or worries into the application. For example, the user might enter "I'm lonely because I live alone."

[0674] 2. The device sends this information to the server.

[0675] 3. The server uses an AI module to analyze the user's mental state and generate appropriate advice and mental health care methods.

[0676] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0677] 5. The server further proposes communities for users with similar problems and supports interaction among users through their participation.

[0678] In this way, the system uses AI to analyze data based on information entered by users and proposes appropriate information and actions in medical care, daily living support, and mental health care. Furthermore, by arranging online consultations with doctors and collaboration with local supporters as needed, it provides an environment where users can lead fulfilling lives without feeling isolated.

[0679] The following describes the processing flow.

[0680] 1. Healthcare (connecting people with doctors)

[0681] Processing steps

[0682] Step 1:

[0683] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0684] Step 2:

[0685] The terminal sends the entered data about the patient's condition and symptoms to the server.

[0686] Step 3:

[0687] The server inputs the received information into the AI ​​module and begins analysis.

[0688] Step 4:

[0689] The server's AI analyzes the disease state and symptoms using natural language processing technology.

[0690] Step 5:

[0691] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, information on over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[0692] Step 6:

[0693] The server formats the generated information and creates a response message.

[0694] Step 7:

[0695] The terminal receives a response message and displays it to the user.

[0696] Step 8:

[0697] Users can choose to book an online doctor consultation as needed.

[0698] Step 9:

[0699] The server receives the user's appointment request and coordinates the schedule with the doctor.

[0700] Step 10:

[0701] The server confirms the reservation and sends a reservation confirmation notification to the user.

[0702] 2. Life (Connecting people with supporters)

[0703] Processing steps

[0704] Step 1:

[0705] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[0706] Step 2:

[0707] The device sends the entered data on lifestyle needs to the server.

[0708] Step 3:

[0709] The server inputs the received information into the AI ​​module and begins analysis.

[0710] Step 4:

[0711] The server's AI analyzes needs using natural language processing technology.

[0712] Step 5:

[0713] The server's AI identifies appropriate life support methods (e.g., volunteer work, delivery services) based on the analysis results.

[0714] Step 6:

[0715] The server formats the life support suggestions and creates a response message.

[0716] Step 7:

[0717] The terminal receives a response message and displays it to the user.

[0718] Step 8:

[0719] The user selects the most appropriate method from among the suggested life support options.

[0720] Step 9:

[0721] The terminal sends the user's selection to the server.

[0722] Step 10:

[0723] The server receives the user's selection and coordinates with supporters to arrange assistance.

[0724] 3. Security (connecting people's hearts)

[0725] Processing steps

[0726] Step 1:

[0727] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0728] Step 2:

[0729] The device sends the entered data about the mental state to the server.

[0730] Step 3:

[0731] The server inputs the received information into the AI ​​module and begins analysis.

[0732] Step 4:

[0733] The server's AI analyzes the user's emotional state and worries using natural language processing technology.

[0734] Step 5:

[0735] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[0736] Step 6:

[0737] The server formats advice and emotional support methods and creates response messages.

[0738] Step 7:

[0739] The terminal receives a response message and displays it to the user.

[0740] Step 8:

[0741] The server generates a message suggesting a community for users in similar situations.

[0742] Step 9:

[0743] The device receives the suggestion message and displays it to the user.

[0744] Step 10:

[0745] If a user wishes to join the community, the device sends a participation request to the server.

[0746] Step 11:

[0747] The server receives the participation request and provides the user with information on how to access the community.

[0748] The above outlines the specific processing steps in each system. In this way, systems utilizing generative AI can appropriately support users in medical care, daily living assistance, and mental health care.

[0749] (Example 1)

[0750] 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."

[0751] This invention aims to provide a comprehensive support system utilizing generative AI to solve problems related to medical care, daily living support, and mental health care in a super-aging society. Traditionally, users had to access these services individually, and the lack of coordination resulted in inefficient support. Furthermore, many elderly people are unable to fully utilize digital technology, creating a need for a user-friendly system.

[0752] 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.

[0753] In this invention, the server includes means for receiving data entered by a user, a data processing device including artificial intelligence for analyzing the entered data, and means for generating appropriate medical information or recommended actions based on the analysis results. This makes it possible for the AI ​​to analyze the data based on the information entered by the user and propose appropriate information and actions in medical care, life support, and mental health care.

[0754] A "user" refers to a person who uses this system to input information about their medical care, lifestyle support, and mental health care, and receives support based on that information.

[0755] A "data processing device" refers to a combination of hardware and software, including artificial intelligence, used to analyze data entered by users and generate appropriate information and actions based on that analysis.

[0756] A "server" is a computer system on a network that includes a data processing unit, and its role is to receive input data from users, analyze it, and provide the generated information.

[0757] "Medical information" refers to information including diagnostic results obtained by analyzing data on the user's health status and medical condition, recommended countermeasures and treatments, and the need for a doctor's consultation.

[0758] "Recommended actions" refer to specific actions or measures that users should take, generated based on the analysis of their input data.

[0759] "Online consultation" refers to a service that allows experts and users to communicate directly via the internet. In medical contexts, this includes consultations with doctors, and in lifestyle support, it includes communication with supporters and guidance on daily living.

[0760] "Life support" refers to support services aimed at resolving difficulties in users' daily lives, and includes, for example, grocery shopping assistance, household support, and introductions to local volunteers.

[0761] A "supporter" refers to an individual or organization that works in conjunction with a user to provide life support.

[0762] "Mental health care" refers to advice and measures to address the user's mental state, including, for example, counseling, instruction in relaxation techniques, and suggestions for community participation.

[0763] A "community" refers to a place where users with similar problems or needs can gather and help each other. Online forums and chat groups are examples of this.

[0764] This invention relates to a system for comprehensively solving problems related to medical care, daily living support, and mental health care in a super-aging society. This system utilizes a generative AI model to analyze data entered by the user and provide appropriate information and actions.

[0765] The system configuration consists of a terminal that receives user input data, a server that analyzes the data, a terminal that notifies users of information and recommended actions generated based on the analysis results, and means for setting up online consultations.

[0766] Specific hardware includes devices such as smartphones and tablets used by users, as well as servers with powerful data processing capabilities. The term "server" refers to a data processing device, and this definition assumes the use of cloud services.

[0767] The software used includes generative AI models installed on the server. For example, an AI model employing natural language processing (NLP) technology is used for analyzing medical information, while machine learning algorithms are used for analyzing lifestyle support data. Additionally, programs that communicate via APIs are included for setting up notifications and online consultations.

[0768] Specific example 1: Healthcare (connecting people with doctors)

[0769] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[0770] 2. The device sends this information to the server.

[0771] 3. The server uses NLP technology to analyze the information it receives and generates information about the cause of lower back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[0772] 4. The device notifies the user of the information it has generated.

[0773] 5. Users can book online doctor consultations as needed, and the server will coordinate schedules with appropriate doctors and confirm the online consultation booking.

[0774] Example 2: Daily Life (Connecting people with supporters)

[0775] 1. The user enters into the application the difficulties they face in their daily life. For example, they might enter, "It's difficult to go shopping."

[0776] 2. The device sends this information to the server.

[0777] 3. The server uses machine learning algorithms to analyze life needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[0778] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[0779] Specific example 3: Security (connecting people's hearts)

[0780] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0781] 2. The device sends this information to the server.

[0782] 3. The server uses NLP technology to analyze the user's mental state and generate appropriate advice and mental health care methods.

[0783] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0784] 5. The server proposes communities for users with similar problems and supports them in interacting with each other by encouraging participation.

[0785] Example of a prompt

[0786] "My lower back has been hurting lately, what should I do?"

[0787] "I'm having trouble going shopping. Please help me."

[0788] "I'm lonely living alone."

[0789] This system uses a generative AI model to analyze user input with high accuracy and provide various types of support quickly and appropriately. As a result, users can gain an environment where they can comprehensively resolve issues related to their health, lifestyle, and mental well-being.

[0790] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0791] Healthcare (connecting people with doctors)

[0792] Program processing steps

[0793] Step 1:

[0794] The user enters their medical condition and symptoms into the application.

[0795] Input: User-generated text (e.g., "My back has been hurting lately").

[0796] Output: Input data (text data).

[0797] Step 2:

[0798] The terminal sends the input information to the server.

[0799] Input: Text data entered by the user.

[0800] Data processing: The terminal encrypts the text data and sends it to the server using a secure communication method (e.g., HTTPS).

[0801] Output: Encrypted data packets.

[0802] Step 3:

[0803] The server analyzes the information using an AI module.

[0804] Input: Received encrypted data.

[0805] Data processing: The server decodes the data and analyzes the text using generative AI models and natural language processing (NLP) techniques. Specifically, it activates the model and matches it with patterns and datasets related to the user's symptoms.

[0806] Output: Analysis results (e.g., causes of lower back pain and recommended countermeasures).

[0807] Step 4:

[0808] The server generates the countermeasures.

[0809] Input: Analysis result data.

[0810] Data processing: Using an interactive AI engine, recommended actions (e.g., stretching, over-the-counter medication, consultation with a specialist) are generated.

[0811] Output: Recommended countermeasures list.

[0812] Step 5:

[0813] The device notifies the user of the necessary countermeasures.

[0814] Input: Recommended countermeasures list.

[0815] Data processing: Convert the generated recommended actions into a user-friendly format (e.g., pop-up notifications or in-app messages).

[0816] Output: Notifications displayed to the user.

[0817] Step 6:

[0818] The user books an online doctor consultation.

[0819] Input: User reservation information (e.g., desired date and time).

[0820] Data processing: Send reservation information to the server via the input form.

[0821] Output: Submitted reservation request.

[0822] Step 7:

[0823] The server adjusts the schedule and confirms the reservation.

[0824] Input: Reservation request.

[0825] Data processing: Check doctors' availability and confirm schedules using Microsoft Teams or other online meeting platforms.

[0826] Output: Notification of confirmed reservation information.

[0827] Life (Connecting people with supporters)

[0828] Program processing steps

[0829] Step 1:

[0830] Users input the difficulties they face in their daily lives into the application.

[0831] Input: User-generated text (e.g., "It's difficult to go shopping").

[0832] Output: Input data (text data).

[0833] Step 2:

[0834] The device sends this information to the server.

[0835] Input: Text data entered by the user.

[0836] Data processing: Encrypt text data and send it to the server using a secure communication method.

[0837] Output: Encrypted data packets.

[0838] Step 3:

[0839] The server analyzes lifestyle needs.

[0840] Input: Received encrypted data.

[0841] Data processing: The server decrypts the data and uses AWS SageMaker's AI module to analyze lifestyle needs. It then matches the data against a dataset to identify the necessary support methods.

[0842] Output: Analysis results (e.g., appropriate support methods).

[0843] Step 4:

[0844] The server generates the appropriate support method.

[0845] Input: Analysis result data.

[0846] Data processing: Based on the analysis results, the AI ​​generates appropriate support methods (e.g., suggesting local volunteers or delivery services).

[0847] Output: List of supported methods.

[0848] Step 5:

[0849] The device will notify you of the support method.

[0850] Input: List of support methods.

[0851] Data processing: Notify users of the generated support methods in an easy-to-understand format.

[0852] Output: Notifications displayed to the user.

[0853] Step 6:

[0854] The user selects the support option.

[0855] Input: User selection information.

[0856] Data processing: The user selects their preferred support method and sends that selection information to the server.

[0857] Output: Sent selection information.

[0858] Step 7:

[0859] The server coordinates with supporters to arrange assistance.

[0860] Input: Submitted selection information.

[0861] Data processing: Use integration tools such as Slack to notify supporters of the support needed and make specific arrangements.

[0862] Output: Notification of the assistance arranged.

[0863] Security (connecting people's hearts)

[0864] Program processing steps

[0865] Step 1:

[0866] Users input their emotional state and worries into the application.

[0867] Input: User-generated text (e.g., "I'm lonely living alone").

[0868] Output: Input data (text data).

[0869] Step 2:

[0870] The device sends this information to the server.

[0871] Input: Text data entered by the user.

[0872] Data processing: Encrypt text data and send it to the server using a secure communication method.

[0873] Output: Encrypted data packets.

[0874] Step 3:

[0875] The server analyzes the state of mind.

[0876] Input: Received encrypted data.

[0877] Data processing: The server decodes the data and analyzes the mental state using Google Cloud AI modules. Natural language processing (NLP) techniques are used for the analysis.

[0878] Output: Analysis results (e.g., appropriate advice or methods for mental health care).

[0879] Step 4:

[0880] The server generates the care instructions.

[0881] Input: Analysis result data.

[0882] Data processing: Based on the analysis results, generate advice and mental health care methods (e.g., suggestions for yoga or meditation, suggestions for participating in community center events).

[0883] Output: List of care methods.

[0884] Step 5:

[0885] The device will notify you of care instructions.

[0886] Input: List of care methods.

[0887] Data processing: Notify users of the generated care methods in an easy-to-understand format.

[0888] Output: Notifications displayed to the user.

[0889] Step 6:

[0890] The server generates community suggestions.

[0891] Input: List of methods for mental health care.

[0892] Data processing: Based on the analysis results, generate suggestions for communities and online forums where users with similar problems can participate.

[0893] Output: Community suggestion list.

[0894] Step 7:

[0895] The server supports community participation.

[0896] Input: Community suggestion list.

[0897] Data processing: Provide users with information to join the proposed community and make it easy to access the community using platforms such as Discord.

[0898] Output: Notification regarding participation procedures.

[0899] This will enable users to easily manage information related to their health, lifestyle, and mental well-being, and to receive optimal support.

[0900] (Application Example 1)

[0901] 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."

[0902] In a super-aging society, it is becoming increasingly difficult for the elderly to maintain their daily lives on their own. A particular problem is the limited availability of appropriate support, especially in areas such as meal preparation and health management. Furthermore, comprehensive support encompassing medical care, daily living assistance, and mental health care is necessary to ensure that the elderly can live healthy and safe lives without isolation.

[0903] 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.

[0904] In this invention, the server includes means for receiving data entered by a user, means including artificial intelligence for analyzing the entered data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for generating appropriate meal plans and food ingredient suggestions for the user based on the notification, and means for arranging the purchase and delivery of food ingredients based on the suggestions. This enables comprehensive support for elderly people to maintain a healthy and safe life.

[0905] "Data entered by the user" refers to the information and requests provided by those who use the system.

[0906] "Means" refers to the methods, devices, or processes used to achieve a specific objective.

[0907] "Artificial intelligence for analysis" refers to AI technology that analyzes input data and derives relevant information and recommended actions.

[0908] A "server" refers to a computer system used for managing and processing data.

[0909] "Medical information" refers to information and knowledge related to health, treatment, and prevention.

[0910] "Recommended actions" refer to the appropriate actions or methods that should be taken, derived from the user's input data.

[0911] "Means of notification" refers to the methods or devices by which a system communicates information or alerts to a user.

[0912] "Methods for setting up online consultations" refers to the methods and devices used to schedule and prepare systems for users to communicate remotely with experts.

[0913] A "meal plan" refers to a set of meals planned based on the user's health condition and preferences.

[0914] "Food ingredient suggestions" refers to recommended foods and ingredients that users should purchase.

[0915] "Means of arranging purchase and delivery" refers to the procedures and systems for procuring the ingredients selected by the user and having them delivered to their home.

[0916] "Lifestyle needs" refers to the user's demands and required support regarding all aspects of their daily life.

[0917] "Life support" refers to various services and assistance provided to facilitate the user's daily life.

[0918] "Means of coordinating with supporters" refers to methods and devices for coordinating with volunteers and professional services to provide the support that users need.

[0919] "State of mind" refers to the user's mental health and emotional state.

[0920] "Advice" refers to the guidance and suggestions provided to the user.

[0921] "Mental health care" refers to support and activities aimed at maintaining and improving the mental well-being of users.

[0922] "Means of proposing communities" refers to methods and devices that guide users to places where they can interact with other users who share similar interests or concerns.

[0923] The system for implementing this invention receives data input by the user, analyzes it, and provides appropriate suggestions in areas such as medical information, lifestyle support, and mental health care, thereby supporting elderly people in leading healthy and fulfilling lives.

[0924] Hardware and software to be used

[0925] Smartphones and tablets: These are devices used by users to input data and receive suggested information.

[0926] Server: Performs data analysis and generates suggestions.

[0927] Artificial Intelligence (AI) Module: Using TensorFlow and Keras, it analyzes user-input data and generates appropriate medical information, lifestyle support, and mental health care suggestions.

[0928] Communication API: Use Twilio to schedule online doctor and nutritionist consultations as needed.

[0929] System operation

[0930] 1. Data Input and Reception: Users input data into the application using their smartphones or tablets. For example, they might input symptoms, difficulties in daily life, or emotional worries such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone."

[0931] 2. Data Analysis: The server receives the input data and analyzes it using artificial intelligence modules (TensorFlow and Keras). Based on the analysis results, appropriate medical information (stretching methods, treatments), lifestyle support (suggestions for delivery services), and mental health care (suggestions for online consultations and community participation) are generated.

[0932] 3. Suggestion Generation and Notification: Information and suggestions generated on the server are notified to the user's terminal. Based on these notifications, users can arrange online doctor consultations or food delivery services.

[0933] 4. Setting up online consultations: Use communication APIs such as Twilio to schedule and confirm online consultations with doctors and nutritionists as needed.

[0934] Specific example

[0935] A 70-year-old elderly person living alone enters a request into the app for "healthy meals that take diabetes into consideration." The server analyzes this information and suggests low-sugar menus and preparation methods. The user can then order the ingredients for the suggested menus through a food delivery service, which will be delivered that evening. Furthermore, they can also book online consultations with a nutritionist if needed.

[0936] Example of a prompt

[0937] "Please suggest a healthy and delicious dinner."

[0938] "Please share some breakfast ideas that are suitable for people with diabetes."

[0939] "Please create a list of ingredients for this week."

[0940] In this way, this system provides comprehensive support for older adults to live safely and healthily.

[0941] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0942] Step 1:

[0943] User data entry

[0944] Users use smartphones or tablets to input data about their medical condition, lifestyle needs, and mental state into the application. For example, they might enter prompts such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone." This input data is recorded on the device and immediately sent to the server.

[0945] Step 2:

[0946] Data reception and preprocessing

[0947] The server receives user input data sent from the terminal. It then formats the received data and converts it into a parsable format. This preprocessing involves using natural language processing (NLP) tools to tokenize and grammatically analyze the text. For example, if the user inputs "My back has been hurting lately," the server generates an appropriate text format.

[0948] Step 3:

[0949] Data analysis and model application

[0950] The server inputs pre-processed data into a generative AI model (using TensorFlow or Keras). The AI ​​model analyzes the received data and generates appropriate medical information, lifestyle support, and mental health care suggestions. For example, it might analyze "lower back pain" and suggest stretching methods and treatments. The output includes a list of analysis results and suggestions.

[0951] Step 4:

[0952] Generation and transmission of proposal information

[0953] The server generates specific suggestion information based on the analysis results of the AI ​​model. This suggestion information includes medical information, lifestyle support, and mental health care methods that best suit the user's needs. The generated information is then formatted again in text format and sent to the user's device. For example, the device might receive notifications such as "Do some back stretches" or "Consider using a local delivery service."

[0954] Step 5:

[0955] User awareness and choice

[0956] The user reviews the suggested information displayed on their device. They can then select actions such as online doctor consultations, grocery ordering, or nutritionist consultations, as needed. Once the user selects an action, that information is sent back to the server.

[0957] Step 6:

[0958] Arrangement for the execution of the action

[0959] The server performs the necessary actions based on the user's selections. For example, it might use the Twilio API to set up an online doctor consultation appointment. It might also arrange for groceries to be ordered and delivered through a food delivery service based on the selected suggestions. Once all arrangements are complete, confirmation information is sent to the user's device.

[0960] This series of processing steps will result in a system that comprehensively supports the health management, daily living assistance, and mental health care of the elderly.

[0961] 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.

[0962] Modes for carrying out the invention

[0963] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society, and can provide more personalized support by combining generative AI and an emotion engine. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence (AI), a terminal that generates and notifies appropriate information and actions based on the analysis results, means for setting up online consultations as needed, and an emotion engine that recognizes the user's emotions.

[0964] 1. Providing medical information combined with emotion recognition.

[0965] Program processing:

[0966] 1. The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0967] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0968] 3. The server's AI analyzes the entered medical conditions and symptoms using natural language processing and combines them with emotional data to generate medical information and recommended actions. For example, if the user is feeling anxious, a reassuring message will be added.

[0969] 4. The device notifies the user of the medical information it has generated.

[0970] 5. The user selects the option to book an online doctor consultation as needed, and the server coordinates the schedule with the doctor and confirms the appointment.

[0971] 2. Providing life support that combines emotion recognition.

[0972] Program processing:

[0973] 1. The user inputs their daily life difficulties and needs into the application. For example, they might input, "It's difficult to go shopping."

[0974] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0975] 3. The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate appropriate lifestyle support methods (e.g., volunteering, delivery services). For example, if a user is feeling stressed, it will also suggest relaxation methods to reduce stress.

[0976] 4. The terminal identifies a specific life support method and notifies the user. If the user selects a method, the server coordinates with the supporter to arrange the assistance.

[0977] 3. Mental care combined with emotion recognition

[0978] Program processing:

[0979] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[0980] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[0981] 3. The server's AI analyzes the user's emotional state and concerns using natural language processing technology, and combines this with emotional data to generate appropriate advice and methods for emotional care. For example, if a user is feeling sad, it will suggest encouraging messages and activities to lift their spirits.

[0982] 4. The device notifies the user of any advice or mental health care methods it has generated.

[0983] 5. The server further proposes communities for users in similar situations and supports users in interacting with each other by encouraging their participation.

[0984] This system can provide more personalized support by combining user input data with analysis results from an emotion engine. This allows it to comprehensively cover medical care, lifestyle support, and mental health care, thereby improving the user's quality of life.

[0985] The following describes the processing flow.

[0986] 1. Healthcare (connecting people with doctors)

[0987] Processing steps

[0988] Step 1:

[0989] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[0990] Step 2:

[0991] The terminal sends the medical condition and symptoms entered, as well as emotional data (e.g., anxiety, pain) recognized by the emotion engine through user facial recognition and voice analysis, to the server.

[0992] Step 3:

[0993] The server passes the received data to the AI ​​module, which then begins analyzing the patient's condition and symptoms.

[0994] Step 4:

[0995] The server's AI uses natural language processing to analyze the patient's condition and symptoms, and combines this with emotional data to generate analysis results.

[0996] Step 5:

[0997] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, recommendations for over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[0998] Step 6:

[0999] The server formats the generated medical information and adds reassuring messages tailored to the user's emotions.

[1000] Step 7:

[1001] The terminal receives the generated response message and notifies the user.

[1002] Step 8:

[1003] Users can choose to book an online doctor consultation as needed.

[1004] Step 9:

[1005] The server receives the user's appointment request and coordinates the schedule with the doctor.

[1006] Step 10:

[1007] The server confirms the online consultation appointment and sends a reservation confirmation notification to the user.

[1008] 2. Life (Connecting people with supporters)

[1009] Processing steps

[1010] Step 1:

[1011] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[1012] Step 2:

[1013] The device sends the inputted lifestyle needs and emotional data recognized by the user's emotion engine (e.g., stress, fatigue) to the server.

[1014] Step 3:

[1015] The server passes the received data to the AI ​​module, which then begins analyzing lifestyle needs.

[1016] Step 4:

[1017] The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate analysis results.

[1018] Step 5:

[1019] The server's AI generates appropriate life support methods (e.g., volunteering, delivery services) based on the analysis results.

[1020] Step 6:

[1021] The server formats the generated life support information and adds stress reduction suggestions that take the user's emotions into consideration.

[1022] Step 7:

[1023] The terminal receives the generated response message and notifies the user.

[1024] Step 8:

[1025] The user selects the most appropriate method from among the suggested life support options.

[1026] Step 9:

[1027] The terminal sends the user's selection to the server.

[1028] Step 10:

[1029] The server coordinates with supporters based on the selected life support information and arranges assistance.

[1030] 3. Security (connecting people's hearts)

[1031] Processing steps

[1032] Step 1:

[1033] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1034] Step 2:

[1035] The device sends the entered mental state and emotional data recognized by the emotion engine (e.g., loneliness, fatigue) to the server.

[1036] Step 3:

[1037] The server passes the received data to the AI ​​module, which then begins analyzing the user's emotional state and concerns.

[1038] Step 4:

[1039] The server's AI analyzes the user's emotional state and worries using natural language processing technology, and combines this with emotional data to generate analysis results.

[1040] Step 5:

[1041] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[1042] Step 6:

[1043] The server formats the generated advice and emotional support methods, and also adds messages that empathize with the user's feelings.

[1044] Step 7:

[1045] The terminal receives the generated response message and notifies the user.

[1046] Step 8:

[1047] The server then generates a message suggesting communities for users in similar situations.

[1048] Step 9:

[1049] The device receives the suggestion message and notifies the user.

[1050] Step 10:

[1051] If a user wishes to join the community, the device sends a participation request to the server.

[1052] Step 11:

[1053] The server receives the participation request and provides the user with information on how to access the community.

[1054] The above outlines the specific processing steps in each system. This system combines generative AI and an emotion engine to provide medical care, lifestyle support, and mental health care while taking the user's emotions into consideration, thereby improving the user's quality of life.

[1055] (Example 2)

[1056] 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".

[1057] In a super-aging society, the problems faced by the elderly are diverse, encompassing healthcare, daily living support, and mental health care. Current systems lack comprehensive support for these needs, making it difficult to provide personalized assistance. Furthermore, support that takes into account the user's emotional state is not being provided, resulting in a lack of truly needed support.

[1058] The specific processing performed by the specific 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 receiving data input by a user, means including artificial intelligence for analyzing the input data, means for generating emotion data using an emotion analysis engine for analyzing the user's emotions, means for providing analysis results by combining the emotion data and input data, means for generating appropriate medical information, lifestyle support methods, or mental health care based on the analysis results, means for notifying the user of the generated information, recommended actions, or mental health care, and means for setting up an online consultation with a doctor or suggesting a community of users as necessary based on the notification. This makes it possible to provide personalized medical information, lifestyle support, and mental health care that takes the user's emotions into consideration.

[1059] A "user" refers to an individual who uses the system to receive medical information, lifestyle support, or mental health care.

[1060] "Input data" refers to information about medical conditions, lifestyle needs, and mental state entered into the application by the user.

[1061] A "server" refers to a computer system that analyzes data received from users and generates and notifies them of the results.

[1062] "Artificial intelligence" refers to machine learning models or natural language processing technologies that analyze input data and generate appropriate information or recommended actions.

[1063] A "sentiment analysis engine" refers to a software module that analyzes emotions from user input data and generates emotional data.

[1064] "Emotional data" refers to information that indicates the user's emotional state, generated by an emotion analysis engine.

[1065] "Analysis results" refer to the output generated by artificial intelligence and emotion analysis engines, based on user input data and emotion data.

[1066] "Medical information" refers to information including diagnoses, treatment methods, and recommended actions related to the user's medical condition.

[1067] "Life support methods" refer to specific support measures and services designed to meet the user's lifestyle needs.

[1068] "Mental health care" refers to advice, suggestions, and support methods for addressing the mental health issues that users are experiencing.

[1069] "Notification" refers to the process of communicating information or actions generated by a server to the user.

[1070] "Online consultation setup" refers to the process of booking and scheduling an online consultation with a medical professional or other expert.

[1071] A "community suggestion" refers to a suggestion made from the server to users to provide a space where users in similar situations can interact with each other.

[1072] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society. By combining generative artificial intelligence (AI) and an emotion analysis engine, the system can provide more personalized support.

[1073] Hardware and software to be used

[1074] Server: Receives data from users, performs data analysis, and provides information. For example, a high-performance cloud server (e.g., AWS, Google Cloud) can be used.

[1075] Terminal: A device used by users to input data and receive results. This includes smartphones, tablets, and personal computers.

[1076] Artificial intelligence (AI): Machine learning models used for data analysis. For example, OpenAI's GPT-4 is used as a generative AI model.

[1077] Emotion analysis engine: Software used to generate user emotion data. Examples include EmotionAI, Affectiva, and IBM Watson Tone Analyzer.

[1078] Data processing and calculations

[1079] 1. Data entry

[1080] Users access the application on their device and input text about their medical condition, lifestyle needs, and mental state.

[1081] 2. Generation of emotion data

[1082] The device sends the input data to an emotion analysis engine, which then analyzes the user's emotions. For example, it generates emotion tags such as "anxiety," "stress," and "sadness."

[1083] 3. Sending data

[1084] The device sends the analyzed emotion data and input data to the server.

[1085] 4. Data Analysis and Generation

[1086] The server's AI analyzes the received data using natural language processing and combines it with emotional data to generate optimal information and recommended actions. For example, it can generate information such as "medical information," "life support methods," and "mental health care."

[1087] 5. Notification

[1088] The generated information and recommended actions are notified to the user via their device. The user then checks this information on their device.

[1089] 6. Online consultations and community proposals

[1090] If needed, users can choose the option to book an online doctor consultation, and the server will handle scheduling. The system also suggests and allows users to participate in user communities.

[1091] Examples of specific cases and prompt statements

[1092] For example, a user might input "My back has been hurting lately" into the application, expressing anxiety. In this case, the system would operate as follows:

[1093] User input: "My lower back has been hurting lately."

[1094] Example prompt: "If a user types 'My back hurts' and is feeling anxious, what reassuring message can you generate?"

[1095] Based on the "anxiety" tag generated by the emotion analysis engine and the user's medical condition data of "back pain," the server uses AI to generate the following message:

[1096] "Stretching is effective for lower back pain. If you are experiencing any concerns, we recommend consulting a doctor."

[1097] In this way, the system can provide optimal medical information and recommended actions while taking the user's emotions into consideration.

[1098] Similarly, for daily living support and mental health care, personalized support is provided that takes into account the user's emotional data. For example, if a user inputs "It's difficult to go shopping" and is feeling stressed, a message such as "We recommend using a delivery service for shopping and taking deep breaths to reduce stress" will be generated.

[1099] This system makes it possible to improve the quality of life for users by comprehensively covering medical care, daily living support, and mental health care.

[1100] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1101] Step 1:

[1102] The user accesses the application screen and enters their medical condition, lifestyle needs, and mental state. For example, they might enter, "My lower back has been hurting lately."

[1103] Input: Medical condition, lifestyle needs, mental state (text format)

[1104] Output: Input data (medical condition information, etc.)

[1105] Step 2:

[1106] The device sends the input data to an emotion analysis engine to analyze the user's emotions. For example, it uses EmotionAI or Affectiva to generate emotion tags such as "anxiety."

[1107] Input: Input data (medical condition, lifestyle needs, mental state)

[1108] Data processing: Emotional analysis using an emotion analysis engine.

[1109] Output: Sentiment data (sentiment tags)

[1110] Step 3:

[1111] The device sends the analyzed emotion data and input data to the server.

[1112] Input: Input data, sentiment data

[1113] Output: Integrated data sent to the server (input data + sentiment data)

[1114] Step 4:

[1115] The server uses AI (for example, OpenAI's GPT-4) to analyze the received data using natural language processing. For example, it might extract medical information related to "lower back pain."

[1116] Input: Integrated data (input data + sentiment data)

[1117] Data processing: Data analysis using natural language processing

[1118] Output: Analysis results (medical information, lifestyle support methods, mental health care methods)

[1119] Step 5:

[1120] The server combines emotional data to generate medical information and recommended actions. For example, it might generate a message such as, "Stretching is effective for back pain. If you are feeling anxious, we recommend consulting a doctor."

[1121] Input: Analysis results, sentiment data

[1122] Data processing: Information generation using generative AI models.

[1123] Output: Generated information (medical information, recommended actions, mental health care methods)

[1124] Step 6:

[1125] The device receives information generated from the server and notifies the user. The user's device displays the message, "Stretching is effective for lower back pain. If you are feeling anxious, we recommend consulting a doctor."

[1126] Input: Generated information

[1127] Output: Information displayed on the user screen

[1128] Step 7:

[1129] Users can select an online doctor consultation booking option from the application as needed. For example, a user might click the "Online Consultation" button.

[1130] Input: User reservation selection

[1131] Output: Reservation Request

[1132] Step 8:

[1133] The server receives the user's selection, coordinates the schedule with the doctor, and confirms the appointment. The server then notifies the user's device of the confirmed appointment information.

[1134] Input: Reservation Request

[1135] Data processing: Schedule adjustment and reservation confirmation.

[1136] Output: Reservation confirmation notification

[1137] Step 9:

[1138] If necessary, the server will suggest that the user join a community of users in similar situations. For example, it might generate a message such as, "Why not join a community of users who feel lonely?"

[1139] Input: Sentiment data, analysis results

[1140] Data processing: Community proposal generation using generative AI models

[1141] Output: Community suggestion notification

[1142] (Application Example 2)

[1143] 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."

[1144] With the advancement of a super-aging society, the conventional system is insufficient to adequately address the increasing demand for medical care, lifestyle support, and mental health care for the elderly, in terms of individualization and emergency response. Therefore, there is a need for more personalized food delivery services that incorporate emotional recognition, enabling the elderly to live with peace of mind.

[1145] 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. In this invention, the server includes means for receiving data input by the user, a server including artificial intelligence for analyzing the input data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for analyzing the user's emotions with an emotion engine and transmitting the emotion data to the server, and means for analyzing the combination of emotion data and user input data to generate personalized suggestions. This makes it possible to provide services according to the user's emotional state.

[1146] "Means for receiving user-entered data" refers to a function that collects text, voice, or other forms of data entered by the user and sends them to a server for analysis.

[1147] A "server that includes artificial intelligence" is a server that incorporates algorithms to analyze input data and generate appropriate information.

[1148] "Means for generating appropriate medical information or recommended actions based on analysis results" refers to a function that provides users with appropriate medical information and guidance on what to do next, based on the analyzed data.

[1149] "Means for notifying the user of generated information or recommended actions" refers to a function for notifying the user of generated information or recommended actions.

[1150] "Method for setting up online consultations with doctors" refers to a function for setting up online consultations between doctors and users as needed.

[1151] An "emotion engine" refers to software or algorithms used to analyze a user's emotions.

[1152] "Emotional data" refers to data that indicates a user's emotional state, analyzed using an emotion engine.

[1153] "Means of sending to the server" refers to the function of sending collected sentiment data and user input data to the server.

[1154] "A means of combining and analyzing emotional data and user input data to generate personalized suggestions" refers to a function that integrates and analyzes emotional data and input data to create and notify individual users of suggestions optimized for them.

[1155] "Lifestyle needs" refer to the basic requirements and problems that users face in their daily lives.

[1156] "Means of providing life support" refers to functions that provide appropriate support and services based on the user's life needs.

[1157] "Means of arranging life support in cooperation with supporters" refers to the function of arranging and coordinating the supporters and services necessary for life support.

[1158] "State of mind" refers to the user's psychological and emotional state.

[1159] "Means of generating advice or emotional support" refers to functions that provide appropriate advice or support methods based on the user's psychological state.

[1160] "Means of proposing user communities" refers to a function that proposes communities where users in similar situations can connect and help each other.

[1161] This invention is specifically designed for food delivery services in an aging society, combining generative AI and an emotion engine to provide a more personalized service that meets user needs. The system's implementation includes the following elements:

[1162] 1. Hardware and Software Configuration

[1163] Hardware:

[1164] Smartphone: A device for user input and notifications.

[1165] Server: A central device for data analysis and processing.

[1166] software:

[1167] Emotion engine: Uses the Microsoft Azure Emotion API.

[1168] Generative AI: OpenAI GPT-4 is used.

[1169] Food delivery related: Use a dedicated API (e.g., Uber Eats API).

[1170] 2. Program Processing

[1171] User input:

[1172] Users enter their desired dishes and recent preferences as text via a smartphone app. This data is sent to an emotion engine and then forwarded to a server for further analysis.

[1173] Emotion recognition:

[1174] The emotion engine (Microsoft Azure Emotion API) analyzes facial expressions from user input data and camera footage, and extracts emotion data. This data is also sent to the server.

[1175] Information analysis:

[1176] The server's AI (OpenAI GPT-4) analyzes emotional and text data, linking what the user wants with their emotional state. It then generates specific order suggestions and accompanying reassuring messages.

[1177] Suggestion generation:

[1178] The AI ​​generator might suggest, for example, "Japanese sushi," to the user, along with a message like "to help you relax." This suggestion is then communicated to the user via their device.

[1179] Order confirmation and notification:

[1180] Once the user agrees to the proposal, the order is confirmed. Notifications (such as food preparation status and estimated delivery time) are also integrated to provide reassurance, taking into account certain emotional states (such as anxiety).

[1181] Setting up an online consultation:

[1182] If necessary, an online nutritionist consultation regarding dietary habits will be set up. This process is also handled by the server, which manages scheduling and confirms reservations.

[1183] 3. Add specific examples

[1184] The following is an example of a prompt message.

[1185] Example 1: "I've been craving Japanese food lately." (User's judgment)

[1186] User input:

[1187] Text: Lately I've been craving Japanese food.

[1188] Camera footage: A smile and a little fatigue

[1189] Server processing:

[1190] 1. Input text analysis: → I want to eat Japanese food

[1191] 2. Emotional analysis: → Feeling fatigued

[1192] Suggestion generation:

[1193] Generation AI:

[1194] You seem tired. How about ordering some Japanese sushi to help you relax? There's a particular restaurant that's known for its excellent sushi.

[1195] Specific example 2: "It's cold, so I want to eat something warm." - User's anxiety

[1196] User input:

[1197] Text: It's cold, so I want to eat something warm.

[1198] Camera footage: A slightly anxious expression.

[1199] Server processing:

[1200] 1. Input text analysis: → I want some warm food.

[1201] 2. Emotion analysis: → Anxious

[1202] Suggestion generation:

[1203] Generation AI:

[1204] For a meal on a cold day, udon noodles with a soft-boiled egg are perfect. Let the warm soup soothe both your body and soul.

[1205] The delivery time is short, so you can enjoy it right away.

[1206] This system provides food delivery services that cater to the user's emotional state and specific requests.

[1207] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1208] Step 1:

[1209] The user enters text or voice input using a smartphone app. For example, they might input, "I've been craving Japanese food lately." This input data is received and passed on to the next process.

[1210] Step 2:

[1211] The device captures the user's facial expressions through the user's camera feed. The facial expression data is analyzed using an emotion engine (Microsoft Azure Emotion API) to generate emotion data. This emotion data, along with the text input data, is sent to the server.

[1212] Step 3:

[1213] The server receives user input data and sentiment data and performs analysis using AI (OpenAI GPT-4). Specifically, it analyzes the input text information using natural language processing techniques to determine the user's needs and emotional state. In this step, for example, the need "I want to eat Japanese food" and the emotion "I'm feeling tired" might be detected.

[1214] Step 4:

[1215] The server uses a generative AI model (GPT-4) to generate personalized suggestions based on the user's needs and emotional state. The generated suggestion might take the form of, for example, "You seem tired. How about ordering some Japanese sushi to help you relax?" This suggestion data is then passed on to the next step.

[1216] Step 5:

[1217] The terminal receives suggestion data from the server and notifies the user. The user reviews the notification and chooses whether or not to order the suggested dishes.

[1218] Step 6:

[1219] The user agrees to the offer and confirms the food order. The device sends the order information back to the server. The server works with food delivery-related APIs (e.g., Uber Eats API) to process the order. This results in the food being delivered from the specified restaurant to the specified delivery address.

[1220] Step 7:

[1221] After an order is confirmed, the server generates and sends notifications to the user's device regarding delivery status and food preparation status. These notifications include detailed information to provide reassurance, such as status and estimated delivery time.

[1222] Step 8:

[1223] If necessary, and the user requests advice on their diet, the device will offer an option to book an online consultation with a nutritionist. The server will process this booking request, schedule and confirm the appointment, and send a booking confirmation notification to the user.

[1224] The specific steps are as follows.

[1225] Example 1: "I've been craving Japanese food lately." (User's judgment)

[1226] Step 1:

[1227] User input: "Lately I've been craving Japanese food."

[1228] Input data: Text

[1229] Step 2:

[1230] Device analysis: Captures facial expression data.

[1231] Emotion Engine (Microsoft Azure Emotion API) Analysis

[1232] Emotional data generation: Feeling tired (emotional data)

[1233] Step 3:

[1234] Server analysis:

[1235] Input data + emotion data

[1236] Extracting information such as "I want to eat Japanese food" and "I'm feeling tired."

[1237] Step 4:

[1238] Server generation:

[1239] Generation AI (GPT-4)

[1240] Suggestion: You seem tired. How about ordering some Japanese sushi to help you relax?

[1241] Step 5:

[1242] notification:

[1243] Display suggestion message

[1244] Step 6:

[1245] User verification:

[1246] Confirm your order

[1247] Step 7:

[1248] Server processing:

[1249] Send order information to the food delivery API.

[1250] Step 8:

[1251] Delivery status notification:

[1252] Inform the user that their order is in transit and the estimated arrival time.

[1253] Step 9 (Optional):

[1254] Online consultation booking

[1255]

[1256] 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.

[1257] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of 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.

[1258] 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.

[1259] [Third Embodiment]

[1260] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[1261] 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.

[1262] 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).

[1263] 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.

[1264] 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.

[1265] 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).

[1266] 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.

[1267] 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.

[1268] 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.

[1269] 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.

[1270] 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.

[1271] 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".

[1272] Modes for carrying out the invention

[1273] This invention relates to a system that utilizes generative AI to comprehensively provide medical care, lifestyle support, and mental health care in order to solve various problems in a super-aging society. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence, a terminal that generates and notifies appropriate information and actions based on the analysis results, and means for setting up online consultations as needed.

[1274] 1. Healthcare (connecting people with doctors)

[1275] Program processing:

[1276] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[1277] 2. The terminal sends the input information to the server.

[1278] 3. The server uses an AI module to analyze this information and generate the cause of the back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[1279] 4. The device notifies the user of the generated information.

[1280] 5. Users can choose to book an online doctor consultation as needed, and the server will coordinate the schedule with the doctor and confirm the online consultation booking.

[1281] 2. Life (Connecting people with supporters)

[1282] Program processing:

[1283] 1. The user enters into the application the difficulties they face in their daily life. For example, the user might enter, "It's difficult to go shopping."

[1284] 2. The device sends this information to the server.

[1285] 3. The server uses an AI module to analyze the user's needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[1286] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[1287] 3. Security (connecting people's hearts)

[1288] Program processing:

[1289] 1. The user enters their emotional state or worries into the application. For example, the user might enter "I'm lonely because I live alone."

[1290] 2. The device sends this information to the server.

[1291] 3. The server uses an AI module to analyze the user's mental state and generate appropriate advice and mental health care methods.

[1292] 4. The device notifies the user of any advice or mental health care methods it has generated.

[1293] 5. The server further proposes communities for users with similar problems and supports interaction among users through their participation.

[1294] In this way, the system uses AI to analyze data based on information entered by users and proposes appropriate information and actions in medical care, daily living support, and mental health care. Furthermore, by arranging online consultations with doctors and collaboration with local supporters as needed, it provides an environment where users can lead fulfilling lives without feeling isolated.

[1295] The following describes the processing flow.

[1296] 1. Healthcare (connecting people with doctors)

[1297] Processing steps

[1298] Step 1:

[1299] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[1300] Step 2:

[1301] The terminal sends the entered data about the patient's condition and symptoms to the server.

[1302] Step 3:

[1303] The server inputs the received information into the AI ​​module and begins analysis.

[1304] Step 4:

[1305] The server's AI analyzes the disease state and symptoms using natural language processing technology.

[1306] Step 5:

[1307] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, information on over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[1308] Step 6:

[1309] The server formats the generated information and creates a response message.

[1310] Step 7:

[1311] The terminal receives a response message and displays it to the user.

[1312] Step 8:

[1313] Users can choose to book an online doctor consultation as needed.

[1314] Step 9:

[1315] The server receives the user's appointment request and coordinates the schedule with the doctor.

[1316] Step 10:

[1317] The server confirms the reservation and sends a reservation confirmation notification to the user.

[1318] 2. Life (Connecting people with supporters)

[1319] Processing steps

[1320] Step 1:

[1321] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[1322] Step 2:

[1323] The device sends the entered data on lifestyle needs to the server.

[1324] Step 3:

[1325] The server inputs the received information into the AI ​​module and begins analysis.

[1326] Step 4:

[1327] The server's AI analyzes needs using natural language processing technology.

[1328] Step 5:

[1329] The server's AI identifies appropriate life support methods (e.g., volunteer work, delivery services) based on the analysis results.

[1330] Step 6:

[1331] The server formats the life support suggestions and creates a response message.

[1332] Step 7:

[1333] The terminal receives a response message and displays it to the user.

[1334] Step 8:

[1335] The user selects the most appropriate method from among the suggested life support options.

[1336] Step 9:

[1337] The terminal sends the user's selection to the server.

[1338] Step 10:

[1339] The server receives the user's selection and coordinates with supporters to arrange assistance.

[1340] 3. Security (connecting people's hearts)

[1341] Processing steps

[1342] Step 1:

[1343] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1344] Step 2:

[1345] The device sends the entered data about the mental state to the server.

[1346] Step 3:

[1347] The server inputs the received information into the AI ​​module and begins analysis.

[1348] Step 4:

[1349] The server's AI analyzes the user's emotional state and worries using natural language processing technology.

[1350] Step 5:

[1351] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[1352] Step 6:

[1353] The server formats advice and emotional support methods and creates response messages.

[1354] Step 7:

[1355] The terminal receives a response message and displays it to the user.

[1356] Step 8:

[1357] The server generates a message suggesting a community for users in similar situations.

[1358] Step 9:

[1359] The device receives the suggestion message and displays it to the user.

[1360] Step 10:

[1361] If a user wishes to join the community, the device sends a participation request to the server.

[1362] Step 11:

[1363] The server receives the participation request and provides the user with information on how to access the community.

[1364] The above outlines the specific processing steps in each system. In this way, systems utilizing generative AI can appropriately support users in medical care, daily living assistance, and mental health care.

[1365] (Example 1)

[1366] 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."

[1367] This invention aims to provide a comprehensive support system utilizing generative AI to solve problems related to medical care, daily living support, and mental health care in a super-aging society. Traditionally, users had to access these services individually, and the lack of coordination resulted in inefficient support. Furthermore, many elderly people are unable to fully utilize digital technology, creating a need for a user-friendly system.

[1368] 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.

[1369] In this invention, the server includes means for receiving data entered by a user, a data processing device including artificial intelligence for analyzing the entered data, and means for generating appropriate medical information or recommended actions based on the analysis results. This makes it possible for the AI ​​to analyze the data based on the information entered by the user and propose appropriate information and actions in medical care, life support, and mental health care.

[1370] A "user" refers to a person who uses this system to input information about their medical care, lifestyle support, and mental health care, and receives support based on that information.

[1371] A "data processing device" refers to a combination of hardware and software, including artificial intelligence, used to analyze data entered by users and generate appropriate information and actions based on that analysis.

[1372] A "server" is a computer system on a network that includes a data processing unit, and its role is to receive input data from users, analyze it, and provide the generated information.

[1373] "Medical information" refers to information including diagnostic results obtained by analyzing data on the user's health status and medical condition, recommended countermeasures and treatments, and the need for a doctor's consultation.

[1374] "Recommended actions" refer to specific actions or measures that users should take, generated based on the analysis of their input data.

[1375] "Online consultation" refers to a service that allows experts and users to communicate directly via the internet. In medical contexts, this includes consultations with doctors, and in lifestyle support, it includes communication with supporters and guidance on daily living.

[1376] "Life support" refers to support services aimed at resolving difficulties in users' daily lives, and includes, for example, grocery shopping assistance, household support, and introductions to local volunteers.

[1377] A "supporter" refers to an individual or organization that works in conjunction with a user to provide life support.

[1378] "Mental health care" refers to advice and measures to address the user's mental state, including, for example, counseling, instruction in relaxation techniques, and suggestions for community participation.

[1379] A "community" refers to a place where users with similar problems or needs can gather and help each other. Online forums and chat groups are examples of this.

[1380] This invention relates to a system for comprehensively solving problems related to medical care, daily living support, and mental health care in a super-aging society. This system utilizes a generative AI model to analyze data entered by the user and provide appropriate information and actions.

[1381] The system configuration consists of a terminal that receives user input data, a server that analyzes the data, a terminal that notifies users of information and recommended actions generated based on the analysis results, and means for setting up online consultations.

[1382] Specific hardware includes devices such as smartphones and tablets used by users, as well as servers with powerful data processing capabilities. The term "server" refers to a data processing device, and this definition assumes the use of cloud services.

[1383] The software used includes generative AI models installed on the server. For example, an AI model employing natural language processing (NLP) technology is used for analyzing medical information, while machine learning algorithms are used for analyzing lifestyle support data. Additionally, programs that communicate via APIs are included for setting up notifications and online consultations.

[1384] Specific example 1: Healthcare (connecting people with doctors)

[1385] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[1386] 2. The device sends this information to the server.

[1387] 3. The server uses NLP technology to analyze the information it receives and generates information about the cause of lower back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[1388] 4. The device notifies the user of the information it has generated.

[1389] 5. Users can book online doctor consultations as needed, and the server will coordinate schedules with appropriate doctors and confirm the online consultation booking.

[1390] Example 2: Daily Life (Connecting people with supporters)

[1391] 1. The user enters into the application the difficulties they face in their daily life. For example, they might enter, "It's difficult to go shopping."

[1392] 2. The device sends this information to the server.

[1393] 3. The server uses machine learning algorithms to analyze life needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[1394] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[1395] Specific example 3: Security (connecting people's hearts)

[1396] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1397] 2. The device sends this information to the server.

[1398] 3. The server uses NLP technology to analyze the user's mental state and generate appropriate advice and mental health care methods.

[1399] 4. The device notifies the user of any advice or mental health care methods it has generated.

[1400] 5. The server proposes communities for users with similar problems and supports them in interacting with each other by encouraging participation.

[1401] Example of a prompt

[1402] "My lower back has been hurting lately, what should I do?"

[1403] "I'm having trouble going shopping. Please help me."

[1404] "I'm lonely living alone."

[1405] This system uses a generative AI model to analyze user input with high accuracy and provide various types of support quickly and appropriately. As a result, users can gain an environment where they can comprehensively resolve issues related to their health, lifestyle, and mental well-being.

[1406] The flow of the specific processing in Example 1 will be explained using Figure 11.

[1407] Healthcare (connecting people with doctors)

[1408] Program processing steps

[1409] Step 1:

[1410] The user enters their medical condition and symptoms into the application.

[1411] Input: User-generated text (e.g., "My back has been hurting lately").

[1412] Output: Input data (text data).

[1413] Step 2:

[1414] The terminal sends the input information to the server.

[1415] Input: Text data entered by the user.

[1416] Data processing: The terminal encrypts the text data and sends it to the server using a secure communication method (e.g., HTTPS).

[1417] Output: Encrypted data packets.

[1418] Step 3:

[1419] The server analyzes the information using an AI module.

[1420] Input: Received encrypted data.

[1421] Data processing: The server decodes the data and analyzes the text using generative AI models and natural language processing (NLP) techniques. Specifically, it activates the model and matches it with patterns and datasets related to the user's symptoms.

[1422] Output: Analysis results (e.g., causes of lower back pain and recommended countermeasures).

[1423] Step 4:

[1424] The server generates the countermeasures.

[1425] Input: Analysis result data.

[1426] Data processing: Using an interactive AI engine, recommended actions (e.g., stretching, over-the-counter medication, consultation with a specialist) are generated.

[1427] Output: Recommended countermeasures list.

[1428] Step 5:

[1429] The device notifies the user of the necessary countermeasures.

[1430] Input: Recommended countermeasures list.

[1431] Data processing: Convert the generated recommended actions into a user-friendly format (e.g., pop-up notifications or in-app messages).

[1432] Output: Notifications displayed to the user.

[1433] Step 6:

[1434] The user books an online doctor consultation.

[1435] Input: User reservation information (e.g., desired date and time).

[1436] Data processing: Send reservation information to the server via the input form.

[1437] Output: Submitted reservation request.

[1438] Step 7:

[1439] The server adjusts the schedule and confirms the reservation.

[1440] Input: Reservation request.

[1441] Data processing: Check doctors' availability and confirm schedules using Microsoft Teams or other online meeting platforms.

[1442] Output: Notification of confirmed reservation information.

[1443] Life (Connecting people with supporters)

[1444] Program processing steps

[1445] Step 1:

[1446] Users input the difficulties they face in their daily lives into the application.

[1447] Input: User-generated text (e.g., "It's difficult to go shopping").

[1448] Output: Input data (text data).

[1449] Step 2:

[1450] The device sends this information to the server.

[1451] Input: Text data entered by the user.

[1452] Data processing: Encrypt text data and send it to the server using a secure communication method.

[1453] Output: Encrypted data packets.

[1454] Step 3:

[1455] The server analyzes lifestyle needs.

[1456] Input: Received encrypted data.

[1457] Data processing: The server decrypts the data and uses AWS SageMaker's AI module to analyze lifestyle needs. It then matches the data against a dataset to identify the necessary support methods.

[1458] Output: Analysis results (e.g., appropriate support methods).

[1459] Step 4:

[1460] The server generates the appropriate support method.

[1461] Input: Analysis result data.

[1462] Data processing: Based on the analysis results, the AI ​​generates appropriate support methods (e.g., suggesting local volunteers or delivery services).

[1463] Output: List of supported methods.

[1464] Step 5:

[1465] The device will notify you of the support method.

[1466] Input: List of support methods.

[1467] Data processing: Notify users of the generated support methods in an easy-to-understand format.

[1468] Output: Notifications displayed to the user.

[1469] Step 6:

[1470] The user selects the support option.

[1471] Input: User selection information.

[1472] Data processing: The user selects their preferred support method and sends that selection information to the server.

[1473] Output: Sent selection information.

[1474] Step 7:

[1475] The server coordinates with supporters to arrange assistance.

[1476] Input: Submitted selection information.

[1477] Data processing: Use integration tools such as Slack to notify supporters of the support needed and make specific arrangements.

[1478] Output: Notification of the assistance arranged.

[1479] Security (connecting people's hearts)

[1480] Program processing steps

[1481] Step 1:

[1482] Users input their emotional state and worries into the application.

[1483] Input: User-generated text (e.g., "I'm lonely living alone").

[1484] Output: Input data (text data).

[1485] Step 2:

[1486] The device sends this information to the server.

[1487] Input: Text data entered by the user.

[1488] Data processing: Encrypt text data and send it to the server using a secure communication method.

[1489] Output: Encrypted data packets.

[1490] Step 3:

[1491] The server analyzes the state of mind.

[1492] Input: Received encrypted data.

[1493] Data processing: The server decodes the data and analyzes the mental state using Google Cloud AI modules. Natural language processing (NLP) techniques are used for the analysis.

[1494] Output: Analysis results (e.g., appropriate advice or methods for mental health care).

[1495] Step 4:

[1496] The server generates the care instructions.

[1497] Input: Analysis result data.

[1498] Data processing: Based on the analysis results, generate advice and mental health care methods (e.g., suggestions for yoga or meditation, suggestions for participating in community center events).

[1499] Output: List of care methods.

[1500] Step 5:

[1501] The device will notify you of care instructions.

[1502] Input: List of care methods.

[1503] Data processing: Notify users of the generated care methods in an easy-to-understand format.

[1504] Output: Notifications displayed to the user.

[1505] Step 6:

[1506] The server generates community suggestions.

[1507] Input: List of methods for mental health care.

[1508] Data processing: Based on the analysis results, generate suggestions for communities and online forums where users with similar problems can participate.

[1509] Output: Community suggestion list.

[1510] Step 7:

[1511] The server supports community participation.

[1512] Input: Community suggestion list.

[1513] Data processing: Provide users with information to join the proposed community and make it easy to access the community using platforms such as Discord.

[1514] Output: Notification regarding participation procedures.

[1515] This will enable users to easily manage information related to their health, lifestyle, and mental well-being, and to receive optimal support.

[1516] (Application Example 1)

[1517] 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."

[1518] In a super-aging society, it is becoming increasingly difficult for the elderly to maintain their daily lives on their own. A particular problem is the limited availability of appropriate support, especially in areas such as meal preparation and health management. Furthermore, comprehensive support encompassing medical care, daily living assistance, and mental health care is necessary to ensure that the elderly can live healthy and safe lives without isolation.

[1519] 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.

[1520] In this invention, the server includes means for receiving data entered by a user, means including artificial intelligence for analyzing the entered data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for generating appropriate meal plans and food ingredient suggestions for the user based on the notification, and means for arranging the purchase and delivery of food ingredients based on the suggestions. This enables comprehensive support for elderly people to maintain a healthy and safe life.

[1521] "Data entered by the user" refers to the information and requests provided by those who use the system.

[1522] "Means" refers to the methods, devices, or processes used to achieve a specific objective.

[1523] "Artificial intelligence for analysis" refers to AI technology that analyzes input data and derives relevant information and recommended actions.

[1524] A "server" refers to a computer system used for managing and processing data.

[1525] "Medical information" refers to information and knowledge related to health, treatment, and prevention.

[1526] "Recommended actions" refer to the appropriate actions or methods that should be taken, derived from the user's input data.

[1527] "Means of notification" refers to the methods or devices by which a system communicates information or alerts to a user.

[1528] "Methods for setting up online consultations" refers to the methods and devices used to schedule and prepare systems for users to communicate remotely with experts.

[1529] A "meal plan" refers to a set of meals planned based on the user's health condition and preferences.

[1530] "Food ingredient suggestions" refers to recommended foods and ingredients that users should purchase.

[1531] "Means of arranging purchase and delivery" refers to the procedures and systems for procuring the ingredients selected by the user and having them delivered to their home.

[1532] "Lifestyle needs" refers to the user's demands and required support regarding all aspects of their daily life.

[1533] "Life support" refers to various services and assistance provided to facilitate the user's daily life.

[1534] "Means of coordinating with supporters" refers to methods and devices for coordinating with volunteers and professional services to provide the support that users need.

[1535] "State of mind" refers to the user's mental health and emotional state.

[1536] "Advice" refers to the guidance and suggestions provided to the user.

[1537] "Mental health care" refers to support and activities aimed at maintaining and improving the mental well-being of users.

[1538] "Means of proposing communities" refers to methods and devices that guide users to places where they can interact with other users who share similar interests or concerns.

[1539] The system for implementing this invention receives data input by the user, analyzes it, and provides appropriate suggestions in areas such as medical information, lifestyle support, and mental health care, thereby supporting elderly people in leading healthy and fulfilling lives.

[1540] Hardware and software to be used

[1541] Smartphones and tablets: These are devices used by users to input data and receive suggested information.

[1542] Server: Performs data analysis and generates suggestions.

[1543] Artificial Intelligence (AI) Module: Using TensorFlow and Keras, it analyzes user-input data and generates appropriate medical information, lifestyle support, and mental health care suggestions.

[1544] Communication API: Use Twilio to schedule online doctor and nutritionist consultations as needed.

[1545] System operation

[1546] 1. Data Input and Reception: Users input data into the application using their smartphones or tablets. For example, they might input symptoms, difficulties in daily life, or emotional worries such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone."

[1547] 2. Data Analysis: The server receives the input data and analyzes it using artificial intelligence modules (TensorFlow and Keras). Based on the analysis results, appropriate medical information (stretching methods, treatments), lifestyle support (suggestions for delivery services), and mental health care (suggestions for online consultations and community participation) are generated.

[1548] 3. Suggestion Generation and Notification: Information and suggestions generated on the server are notified to the user's terminal. Based on these notifications, users can arrange online doctor consultations or food delivery services.

[1549] 4. Setting up online consultations: Use communication APIs such as Twilio to schedule and confirm online consultations with doctors and nutritionists as needed.

[1550] Specific example

[1551] A 70-year-old elderly person living alone enters a request into the app for "healthy meals that take diabetes into consideration." The server analyzes this information and suggests low-sugar menus and preparation methods. The user can then order the ingredients for the suggested menus through a food delivery service, which will be delivered that evening. Furthermore, they can also book online consultations with a nutritionist if needed.

[1552] Example of a prompt

[1553] "Please suggest a healthy and delicious dinner."

[1554] "Please share some breakfast ideas that are suitable for people with diabetes."

[1555] "Please create a list of ingredients for this week."

[1556] In this way, this system provides comprehensive support for older adults to live safely and healthily.

[1557] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[1558] Step 1:

[1559] User data entry

[1560] Users use smartphones or tablets to input data about their medical condition, lifestyle needs, and mental state into the application. For example, they might enter prompts such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone." This input data is recorded on the device and immediately sent to the server.

[1561] Step 2:

[1562] Data reception and preprocessing

[1563] The server receives user input data sent from the terminal. It then formats the received data and converts it into a parsable format. This preprocessing involves using natural language processing (NLP) tools to tokenize and grammatically analyze the text. For example, if the user inputs "My back has been hurting lately," the server generates an appropriate text format.

[1564] Step 3:

[1565] Data analysis and model application

[1566] The server inputs pre-processed data into a generative AI model (using TensorFlow or Keras). The AI ​​model analyzes the received data and generates appropriate medical information, lifestyle support, and mental health care suggestions. For example, it might analyze "lower back pain" and suggest stretching methods and treatments. The output includes a list of analysis results and suggestions.

[1567] Step 4:

[1568] Generation and transmission of proposal information

[1569] The server generates specific suggestion information based on the analysis results of the AI ​​model. This suggestion information includes medical information, lifestyle support, and mental health care methods that best suit the user's needs. The generated information is then formatted again in text format and sent to the user's device. For example, the device might receive notifications such as "Do some back stretches" or "Consider using a local delivery service."

[1570] Step 5:

[1571] User awareness and choice

[1572] The user reviews the suggested information displayed on their device. They can then select actions such as online doctor consultations, grocery ordering, or nutritionist consultations, as needed. Once the user selects an action, that information is sent back to the server.

[1573] Step 6:

[1574] Arrangement for the execution of the action

[1575] The server performs the necessary actions based on the user's selections. For example, it might use the Twilio API to set up an online doctor consultation appointment. It might also arrange for groceries to be ordered and delivered through a food delivery service based on the selected suggestions. Once all arrangements are complete, confirmation information is sent to the user's device.

[1576] This series of processing steps will result in a system that comprehensively supports the health management, daily living assistance, and mental health care of the elderly.

[1577] 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.

[1578] Modes for carrying out the invention

[1579] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society, and can provide more personalized support by combining generative AI and an emotion engine. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence (AI), a terminal that generates and notifies appropriate information and actions based on the analysis results, means for setting up online consultations as needed, and an emotion engine that recognizes the user's emotions.

[1580] 1. Providing medical information combined with emotion recognition.

[1581] Program processing:

[1582] 1. The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[1583] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[1584] 3. The server's AI analyzes the entered medical conditions and symptoms using natural language processing and combines them with emotional data to generate medical information and recommended actions. For example, if the user is feeling anxious, a reassuring message will be added.

[1585] 4. The device notifies the user of the medical information it has generated.

[1586] 5. The user selects the option to book an online doctor consultation as needed, and the server coordinates the schedule with the doctor and confirms the appointment.

[1587] 2. Providing life support that combines emotion recognition.

[1588] Program processing:

[1589] 1. The user inputs their daily life difficulties and needs into the application. For example, they might input, "It's difficult to go shopping."

[1590] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[1591] 3. The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate appropriate lifestyle support methods (e.g., volunteering, delivery services). For example, if a user is feeling stressed, it will also suggest relaxation methods to reduce stress.

[1592] 4. The terminal identifies a specific life support method and notifies the user. If the user selects a method, the server coordinates with the supporter to arrange the assistance.

[1593] 3. Mental care combined with emotion recognition

[1594] Program processing:

[1595] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1596] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[1597] 3. The server's AI analyzes the user's emotional state and concerns using natural language processing technology, and combines this with emotional data to generate appropriate advice and methods for emotional care. For example, if a user is feeling sad, it will suggest encouraging messages and activities to lift their spirits.

[1598] 4. The device notifies the user of any advice or mental health care methods it has generated.

[1599] 5. The server further proposes communities for users in similar situations and supports users in interacting with each other by encouraging their participation.

[1600] This system can provide more personalized support by combining user input data with analysis results from an emotion engine. This allows it to comprehensively cover medical care, lifestyle support, and mental health care, thereby improving the user's quality of life.

[1601] The following describes the processing flow.

[1602] 1. Healthcare (connecting people with doctors)

[1603] Processing steps

[1604] Step 1:

[1605] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[1606] Step 2:

[1607] The terminal sends the medical condition and symptoms entered, as well as emotional data (e.g., anxiety, pain) recognized by the emotion engine through user facial recognition and voice analysis, to the server.

[1608] Step 3:

[1609] The server passes the received data to the AI ​​module, which then begins analyzing the patient's condition and symptoms.

[1610] Step 4:

[1611] The server's AI uses natural language processing to analyze the patient's condition and symptoms, and combines this with emotional data to generate analysis results.

[1612] Step 5:

[1613] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, recommendations for over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[1614] Step 6:

[1615] The server formats the generated medical information and adds reassuring messages tailored to the user's emotions.

[1616] Step 7:

[1617] The terminal receives the generated response message and notifies the user.

[1618] Step 8:

[1619] Users can choose to book an online doctor consultation as needed.

[1620] Step 9:

[1621] The server receives the user's appointment request and coordinates the schedule with the doctor.

[1622] Step 10:

[1623] The server confirms the online consultation appointment and sends a reservation confirmation notification to the user.

[1624] 2. Life (Connecting people with supporters)

[1625] Processing steps

[1626] Step 1:

[1627] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[1628] Step 2:

[1629] The device sends the inputted lifestyle needs and emotional data recognized by the user's emotion engine (e.g., stress, fatigue) to the server.

[1630] Step 3:

[1631] The server passes the received data to the AI ​​module, which then begins analyzing lifestyle needs.

[1632] Step 4:

[1633] The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate analysis results.

[1634] Step 5:

[1635] The server's AI generates appropriate life support methods (e.g., volunteering, delivery services) based on the analysis results.

[1636] Step 6:

[1637] The server formats the generated life support information and adds stress reduction suggestions that take the user's emotions into consideration.

[1638] Step 7:

[1639] The terminal receives the generated response message and notifies the user.

[1640] Step 8:

[1641] The user selects the most appropriate method from among the suggested life support options.

[1642] Step 9:

[1643] The terminal sends the user's selection to the server.

[1644] Step 10:

[1645] The server coordinates with supporters based on the selected life support information and arranges assistance.

[1646] 3. Security (connecting people's hearts)

[1647] Processing steps

[1648] Step 1:

[1649] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1650] Step 2:

[1651] The device sends the entered mental state and emotional data recognized by the emotion engine (e.g., loneliness, fatigue) to the server.

[1652] Step 3:

[1653] The server passes the received data to the AI ​​module, which then begins analyzing the user's emotional state and concerns.

[1654] Step 4:

[1655] The server's AI analyzes the user's emotional state and worries using natural language processing technology, and combines this with emotional data to generate analysis results.

[1656] Step 5:

[1657] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[1658] Step 6:

[1659] The server formats the generated advice and emotional support methods, and also adds messages that empathize with the user's feelings.

[1660] Step 7:

[1661] The terminal receives the generated response message and notifies the user.

[1662] Step 8:

[1663] The server then generates a message suggesting communities for users in similar situations.

[1664] Step 9:

[1665] The device receives the suggestion message and notifies the user.

[1666] Step 10:

[1667] If a user wishes to join the community, the device sends a participation request to the server.

[1668] Step 11:

[1669] The server receives the participation request and provides the user with information on how to access the community.

[1670] The above outlines the specific processing steps in each system. This system combines generative AI and an emotion engine to provide medical care, lifestyle support, and mental health care while taking the user's emotions into consideration, thereby improving the user's quality of life.

[1671] (Example 2)

[1672] 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."

[1673] In a super-aging society, the problems faced by the elderly are diverse, encompassing healthcare, daily living support, and mental health care. Current systems lack comprehensive support for these needs, making it difficult to provide personalized assistance. Furthermore, support that takes into account the user's emotional state is not being provided, resulting in a lack of truly needed support.

[1674] The specific processing performed by the specific 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 receiving data input by a user, means including artificial intelligence for analyzing the input data, means for generating emotion data using an emotion analysis engine for analyzing the user's emotions, means for providing analysis results by combining the emotion data and input data, means for generating appropriate medical information, lifestyle support methods, or mental health care based on the analysis results, means for notifying the user of the generated information, recommended actions, or mental health care, and means for setting up an online consultation with a doctor or suggesting a community of users as necessary based on the notification. This makes it possible to provide personalized medical information, lifestyle support, and mental health care that takes the user's emotions into consideration.

[1675] A "user" refers to an individual who uses the system to receive medical information, lifestyle support, or mental health care.

[1676] "Input data" refers to information about medical conditions, lifestyle needs, and mental state entered into the application by the user.

[1677] A "server" refers to a computer system that analyzes data received from users and generates and notifies them of the results.

[1678] "Artificial intelligence" refers to machine learning models or natural language processing technologies that analyze input data and generate appropriate information or recommended actions.

[1679] A "sentiment analysis engine" refers to a software module that analyzes emotions from user input data and generates emotional data.

[1680] "Emotional data" refers to information that indicates the user's emotional state, generated by an emotion analysis engine.

[1681] "Analysis results" refer to the output generated by artificial intelligence and emotion analysis engines, based on user input data and emotion data.

[1682] "Medical information" refers to information including diagnoses, treatment methods, and recommended actions related to the user's medical condition.

[1683] "Life support methods" refer to specific support measures and services designed to meet the user's lifestyle needs.

[1684] "Mental health care" refers to advice, suggestions, and support methods for addressing the mental health issues that users are experiencing.

[1685] "Notification" refers to the process of communicating information or actions generated by a server to the user.

[1686] "Online consultation setup" refers to the process of booking and scheduling an online consultation with a medical professional or other expert.

[1687] A "community suggestion" refers to a suggestion made from the server to users to provide a space where users in similar situations can interact with each other.

[1688] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society. By combining generative artificial intelligence (AI) and an emotion analysis engine, the system can provide more personalized support.

[1689] Hardware and software to be used

[1690] Server: Receives data from users, performs data analysis, and provides information. For example, a high-performance cloud server (e.g., AWS, Google Cloud) can be used.

[1691] Terminal: A device used by users to input data and receive results. This includes smartphones, tablets, and personal computers.

[1692] Artificial intelligence (AI): Machine learning models used for data analysis. For example, OpenAI's GPT-4 is used as a generative AI model.

[1693] Emotion analysis engine: Software used to generate user emotion data. Examples include EmotionAI, Affectiva, and IBM Watson Tone Analyzer.

[1694] Data processing and calculations

[1695] 1. Data entry

[1696] Users access the application on their device and input text about their medical condition, lifestyle needs, and mental state.

[1697] 2. Generation of emotion data

[1698] The device sends the input data to an emotion analysis engine, which then analyzes the user's emotions. For example, it generates emotion tags such as "anxiety," "stress," and "sadness."

[1699] 3. Sending data

[1700] The device sends the analyzed emotion data and input data to the server.

[1701] 4. Data Analysis and Generation

[1702] The server's AI analyzes the received data using natural language processing and combines it with emotional data to generate optimal information and recommended actions. For example, it can generate information such as "medical information," "life support methods," and "mental health care."

[1703] 5. Notification

[1704] The generated information and recommended actions are notified to the user via their device. The user then checks this information on their device.

[1705] 6. Online consultations and community proposals

[1706] If needed, users can choose the option to book an online doctor consultation, and the server will handle scheduling. The system also suggests and allows users to participate in user communities.

[1707] Examples of specific cases and prompt statements

[1708] For example, a user might input "My back has been hurting lately" into the application, expressing anxiety. In this case, the system would operate as follows:

[1709] User input: "My lower back has been hurting lately."

[1710] Example prompt: "If a user types 'My back hurts' and is feeling anxious, what reassuring message can you generate?"

[1711] Based on the "anxiety" tag generated by the emotion analysis engine and the user's medical condition data of "back pain," the server uses AI to generate the following message:

[1712] "Stretching is effective for lower back pain. If you are experiencing any concerns, we recommend consulting a doctor."

[1713] In this way, the system can provide optimal medical information and recommended actions while taking the user's emotions into consideration.

[1714] Similarly, for daily living support and mental health care, personalized support is provided that takes into account the user's emotional data. For example, if a user inputs "It's difficult to go shopping" and is feeling stressed, a message such as "We recommend using a delivery service for shopping and taking deep breaths to reduce stress" will be generated.

[1715] This system makes it possible to improve the quality of life for users by comprehensively covering medical care, daily living support, and mental health care.

[1716] The flow of the specific processing in Example 2 will be explained using Figure 13.

[1717] Step 1:

[1718] The user accesses the application screen and enters their medical condition, lifestyle needs, and mental state. For example, they might enter, "My lower back has been hurting lately."

[1719] Input: Medical condition, lifestyle needs, mental state (text format)

[1720] Output: Input data (medical condition information, etc.)

[1721] Step 2:

[1722] The device sends the input data to an emotion analysis engine to analyze the user's emotions. For example, it uses EmotionAI or Affectiva to generate emotion tags such as "anxiety."

[1723] Input: Input data (medical condition, lifestyle needs, mental state)

[1724] Data processing: Emotional analysis using an emotion analysis engine.

[1725] Output: Sentiment data (sentiment tags)

[1726] Step 3:

[1727] The device sends the analyzed emotion data and input data to the server.

[1728] Input: Input data, sentiment data

[1729] Output: Integrated data sent to the server (input data + sentiment data)

[1730] Step 4:

[1731] The server uses AI (for example, OpenAI's GPT-4) to analyze the received data using natural language processing. For example, it might extract medical information related to "lower back pain."

[1732] Input: Integrated data (input data + sentiment data)

[1733] Data processing: Data analysis using natural language processing

[1734] Output: Analysis results (medical information, lifestyle support methods, mental health care methods)

[1735] Step 5:

[1736] The server combines emotional data to generate medical information and recommended actions. For example, it might generate a message such as, "Stretching is effective for back pain. If you are feeling anxious, we recommend consulting a doctor."

[1737] Input: Analysis results, sentiment data

[1738] Data processing: Information generation using generative AI models.

[1739] Output: Generated information (medical information, recommended actions, mental health care methods)

[1740] Step 6:

[1741] The device receives information generated from the server and notifies the user. The user's device displays the message, "Stretching is effective for lower back pain. If you are feeling anxious, we recommend consulting a doctor."

[1742] Input: Generated information

[1743] Output: Information displayed on the user screen

[1744] Step 7:

[1745] Users can select an online doctor consultation booking option from the application as needed. For example, a user might click the "Online Consultation" button.

[1746] Input: User reservation selection

[1747] Output: Reservation Request

[1748] Step 8:

[1749] The server receives the user's selection, coordinates the schedule with the doctor, and confirms the appointment. The server then notifies the user's device of the confirmed appointment information.

[1750] Input: Reservation Request

[1751] Data processing: Schedule adjustment and reservation confirmation.

[1752] Output: Reservation confirmation notification

[1753] Step 9:

[1754] If necessary, the server will suggest that the user join a community of users in similar situations. For example, it might generate a message such as, "Why not join a community of users who feel lonely?"

[1755] Input: Sentiment data, analysis results

[1756] Data processing: Community proposal generation using generative AI models

[1757] Output: Community suggestion notification

[1758] (Application Example 2)

[1759] 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."

[1760] With the advancement of a super-aging society, the conventional system is insufficient to adequately address the increasing demand for medical care, lifestyle support, and mental health care for the elderly, in terms of individualization and emergency response. Therefore, there is a need for more personalized food delivery services that incorporate emotional recognition, enabling the elderly to live with peace of mind.

[1761] 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. In this invention, the server includes means for receiving data input by the user, a server including artificial intelligence for analyzing the input data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for analyzing the user's emotions with an emotion engine and transmitting the emotion data to the server, and means for analyzing the combination of emotion data and user input data to generate personalized suggestions. This makes it possible to provide services according to the user's emotional state.

[1762] "Means for receiving user-entered data" refers to a function that collects text, voice, or other forms of data entered by the user and sends them to a server for analysis.

[1763] A "server that includes artificial intelligence" is a server that incorporates algorithms to analyze input data and generate appropriate information.

[1764] "Means for generating appropriate medical information or recommended actions based on analysis results" refers to a function that provides users with appropriate medical information and guidance on what to do next, based on the analyzed data.

[1765] "Means for notifying the user of generated information or recommended actions" refers to a function for notifying the user of generated information or recommended actions.

[1766] "Method for setting up online consultations with doctors" refers to a function for setting up online consultations between doctors and users as needed.

[1767] An "emotion engine" refers to software or algorithms used to analyze a user's emotions.

[1768] "Emotional data" refers to data that indicates a user's emotional state, analyzed using an emotion engine.

[1769] "Means of sending to the server" refers to the function of sending collected sentiment data and user input data to the server.

[1770] "A means of combining and analyzing emotional data and user input data to generate personalized suggestions" refers to a function that integrates and analyzes emotional data and input data to create and notify individual users of suggestions optimized for them.

[1771] "Lifestyle needs" refer to the basic requirements and problems that users face in their daily lives.

[1772] "Means of providing life support" refers to functions that provide appropriate support and services based on the user's life needs.

[1773] "Means of arranging life support in cooperation with supporters" refers to the function of arranging and coordinating the supporters and services necessary for life support.

[1774] "State of mind" refers to the user's psychological and emotional state.

[1775] "Means of generating advice or emotional support" refers to functions that provide appropriate advice or support methods based on the user's psychological state.

[1776] "Means of proposing user communities" refers to a function that proposes communities where users in similar situations can connect and help each other.

[1777] This invention is specifically designed for food delivery services in an aging society, combining generative AI and an emotion engine to provide a more personalized service that meets user needs. The system's implementation includes the following elements:

[1778] 1. Hardware and Software Configuration

[1779] Hardware:

[1780] Smartphone: A device for user input and notifications.

[1781] Server: A central device for data analysis and processing.

[1782] software:

[1783] Emotion engine: Uses the Microsoft Azure Emotion API.

[1784] Generative AI: OpenAI GPT-4 is used.

[1785] Food delivery related: Use a dedicated API (e.g., Uber Eats API).

[1786] 2. Program Processing

[1787] User input:

[1788] Users enter their desired dishes and recent preferences as text via a smartphone app. This data is sent to an emotion engine and then forwarded to a server for further analysis.

[1789] Emotion recognition:

[1790] The emotion engine (Microsoft Azure Emotion API) analyzes facial expressions from user input data and camera footage, and extracts emotion data. This data is also sent to the server.

[1791] Information analysis:

[1792] The server's AI (OpenAI GPT-4) analyzes emotional and text data, linking what the user wants with their emotional state. It then generates specific order suggestions and accompanying reassuring messages.

[1793] Suggestion generation:

[1794] The AI ​​generator might suggest, for example, "Japanese sushi," to the user, along with a message like "to help you relax." This suggestion is then communicated to the user via their device.

[1795] Order confirmation and notification:

[1796] Once the user agrees to the proposal, the order is confirmed. Notifications (such as food preparation status and estimated delivery time) are also integrated to provide reassurance, taking into account certain emotional states (such as anxiety).

[1797] Setting up an online consultation:

[1798] If necessary, an online nutritionist consultation regarding dietary habits will be set up. This process is also handled by the server, which manages scheduling and confirms reservations.

[1799] 3. Add specific examples

[1800] The following is an example of a prompt message.

[1801] Example 1: "I've been craving Japanese food lately." (User's judgment)

[1802] User input:

[1803] Text: Lately I've been craving Japanese food.

[1804] Camera footage: A smile and a little fatigue

[1805] Server processing:

[1806] 1. Input text analysis: → I want to eat Japanese food

[1807] 2. Emotional analysis: → Feeling fatigued

[1808] Suggestion generation:

[1809] Generation AI:

[1810] You seem tired. How about ordering some Japanese sushi to help you relax? There's a particular restaurant that's known for its excellent sushi.

[1811] Specific example 2: "It's cold, so I want to eat something warm." - User's anxiety

[1812] User input:

[1813] Text: It's cold, so I want to eat something warm.

[1814] Camera footage: A slightly anxious expression.

[1815] Server processing:

[1816] 1. Input text analysis: → I want some warm food.

[1817] 2. Emotion analysis: → Anxious

[1818] Suggestion generation:

[1819] Generation AI:

[1820] For a meal on a cold day, udon noodles with a soft-boiled egg are perfect. Let the warm soup soothe both your body and soul.

[1821] The delivery time is short, so you can enjoy it right away.

[1822] This system provides food delivery services that cater to the user's emotional state and specific requests.

[1823] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[1824] Step 1:

[1825] The user enters text or voice input using a smartphone app. For example, they might input, "I've been craving Japanese food lately." This input data is received and passed on to the next process.

[1826] Step 2:

[1827] The device captures the user's facial expressions through the user's camera feed. The facial expression data is analyzed using an emotion engine (Microsoft Azure Emotion API) to generate emotion data. This emotion data, along with the text input data, is sent to the server.

[1828] Step 3:

[1829] The server receives user input data and sentiment data and performs analysis using AI (OpenAI GPT-4). Specifically, it analyzes the input text information using natural language processing techniques to determine the user's needs and emotional state. In this step, for example, the need "I want to eat Japanese food" and the emotion "I'm feeling tired" might be detected.

[1830] Step 4:

[1831] The server uses a generative AI model (GPT-4) to generate personalized suggestions based on the user's needs and emotional state. The generated suggestion might take the form of, for example, "You seem tired. How about ordering some Japanese sushi to help you relax?" This suggestion data is then passed on to the next step.

[1832] Step 5:

[1833] The terminal receives suggestion data from the server and notifies the user. The user reviews the notification and chooses whether or not to order the suggested dishes.

[1834] Step 6:

[1835] The user agrees to the offer and confirms the food order. The device sends the order information back to the server. The server works with food delivery-related APIs (e.g., Uber Eats API) to process the order. This results in the food being delivered from the specified restaurant to the specified delivery address.

[1836] Step 7:

[1837] After an order is confirmed, the server generates and sends notifications to the user's device regarding delivery status and food preparation status. These notifications include detailed information to provide reassurance, such as status and estimated delivery time.

[1838] Step 8:

[1839] If necessary, and the user requests advice on their diet, the device will offer an option to book an online consultation with a nutritionist. The server will process this booking request, schedule and confirm the appointment, and send a booking confirmation notification to the user.

[1840] The specific steps are as follows.

[1841] Example 1: "I've been craving Japanese food lately." (User's judgment)

[1842] Step 1:

[1843] User input: "Lately I've been craving Japanese food."

[1844] Input data: Text

[1845] Step 2:

[1846] Device analysis: Captures facial expression data.

[1847] Emotion Engine (Microsoft Azure Emotion API) Analysis

[1848] Emotional data generation: Feeling tired (emotional data)

[1849] Step 3:

[1850] Server analysis:

[1851] Input data + emotion data

[1852] Extracting information such as "I want to eat Japanese food" and "I'm feeling tired."

[1853] Step 4:

[1854] Server generation:

[1855] Generation AI (GPT-4)

[1856] Suggestion: You seem tired. How about ordering some Japanese sushi to help you relax?

[1857] Step 5:

[1858] notification:

[1859] Display suggestion message

[1860] Step 6:

[1861] User verification:

[1862] Confirm your order

[1863] Step 7:

[1864] Server processing:

[1865] Send order information to the food delivery API.

[1866] Step 8:

[1867] Delivery status notification:

[1868] Inform the user that their order is in transit and the estimated arrival time.

[1869] Step 9 (Optional):

[1870] Online consultation booking

[1871]

[1872] 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.

[1873] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of 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.

[1874] 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.

[1875] [Fourth Embodiment]

[1876] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[1877] 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.

[1878] 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).

[1879] 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.

[1880] 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.

[1881] 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).

[1882] 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.

[1883] 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.

[1884] 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.

[1885] 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.

[1886] 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.

[1887] 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.

[1888] 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".

[1889] Modes for carrying out the invention

[1890] This invention relates to a system that utilizes generative AI to comprehensively provide medical care, lifestyle support, and mental health care in order to solve various problems in a super-aging society. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence, a terminal that generates and notifies appropriate information and actions based on the analysis results, and means for setting up online consultations as needed.

[1891] 1. Healthcare (connecting people with doctors)

[1892] Program processing:

[1893] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[1894] 2. The terminal sends the input information to the server.

[1895] 3. The server uses an AI module to analyze this information and generate the cause of the back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[1896] 4. The device notifies the user of the generated information.

[1897] 5. Users can choose to book an online doctor consultation as needed, and the server will coordinate the schedule with the doctor and confirm the online consultation booking.

[1898] 2. Life (Connecting people with supporters)

[1899] Program processing:

[1900] 1. The user enters into the application the difficulties they face in their daily life. For example, the user might enter, "It's difficult to go shopping."

[1901] 2. The device sends this information to the server.

[1902] 3. The server uses an AI module to analyze the user's needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[1903] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[1904] 3. Security (connecting people's hearts)

[1905] Program processing:

[1906] 1. The user enters their emotional state or worries into the application. For example, the user might enter "I'm lonely because I live alone."

[1907] 2. The device sends this information to the server.

[1908] 3. The server uses an AI module to analyze the user's mental state and generate appropriate advice and mental health care methods.

[1909] 4. The device notifies the user of any advice or mental health care methods it has generated.

[1910] 5. The server further proposes communities for users with similar problems and supports interaction among users through their participation.

[1911] In this way, the system uses AI to analyze data based on information entered by users and proposes appropriate information and actions in medical care, daily living support, and mental health care. Furthermore, by arranging online consultations with doctors and collaboration with local supporters as needed, it provides an environment where users can lead fulfilling lives without feeling isolated.

[1912] The following describes the processing flow.

[1913] 1. Healthcare (connecting people with doctors)

[1914] Processing steps

[1915] Step 1:

[1916] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[1917] Step 2:

[1918] The terminal sends the entered data about the patient's condition and symptoms to the server.

[1919] Step 3:

[1920] The server inputs the received information into the AI ​​module and begins analysis.

[1921] Step 4:

[1922] The server's AI analyzes the disease state and symptoms using natural language processing technology.

[1923] Step 5:

[1924] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, information on over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[1925] Step 6:

[1926] The server formats the generated information and creates a response message.

[1927] Step 7:

[1928] The terminal receives a response message and displays it to the user.

[1929] Step 8:

[1930] Users can choose to book an online doctor consultation as needed.

[1931] Step 9:

[1932] The server receives the user's appointment request and coordinates the schedule with the doctor.

[1933] Step 10:

[1934] The server confirms the reservation and sends a reservation confirmation notification to the user.

[1935] 2. Life (Connecting people with supporters)

[1936] Processing steps

[1937] Step 1:

[1938] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[1939] Step 2:

[1940] The device sends the entered data on lifestyle needs to the server.

[1941] Step 3:

[1942] The server inputs the received information into the AI ​​module and begins analysis.

[1943] Step 4:

[1944] The server's AI analyzes needs using natural language processing technology.

[1945] Step 5:

[1946] The server's AI identifies appropriate life support methods (e.g., volunteer work, delivery services) based on the analysis results.

[1947] Step 6:

[1948] The server formats the life support suggestions and creates a response message.

[1949] Step 7:

[1950] The terminal receives a response message and displays it to the user.

[1951] Step 8:

[1952] The user selects the most appropriate method from among the suggested life support options.

[1953] Step 9:

[1954] The terminal sends the user's selection to the server.

[1955] Step 10:

[1956] The server receives the user's selection and coordinates with supporters to arrange assistance.

[1957] 3. Security (connecting people's hearts)

[1958] Processing steps

[1959] Step 1:

[1960] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[1961] Step 2:

[1962] The device sends the entered data about the mental state to the server.

[1963] Step 3:

[1964] The server inputs the received information into the AI ​​module and begins analysis.

[1965] Step 4:

[1966] The server's AI analyzes the user's emotional state and worries using natural language processing technology.

[1967] Step 5:

[1968] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[1969] Step 6:

[1970] The server formats advice and emotional support methods and creates response messages.

[1971] Step 7:

[1972] The terminal receives a response message and displays it to the user.

[1973] Step 8:

[1974] The server generates a message suggesting a community for users in similar situations.

[1975] Step 9:

[1976] The device receives the suggestion message and displays it to the user.

[1977] Step 10:

[1978] If a user wishes to join the community, the device sends a participation request to the server.

[1979] Step 11:

[1980] The server receives the participation request and provides the user with information on how to access the community.

[1981] The above outlines the specific processing steps in each system. In this way, systems utilizing generative AI can appropriately support users in medical care, daily living assistance, and mental health care.

[1982] (Example 1)

[1983] 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".

[1984] This invention aims to provide a comprehensive support system utilizing generative AI to solve problems related to medical care, daily living support, and mental health care in a super-aging society. Traditionally, users had to access these services individually, and the lack of coordination resulted in inefficient support. Furthermore, many elderly people are unable to fully utilize digital technology, creating a need for a user-friendly system.

[1985] 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.

[1986] In this invention, the server includes means for receiving data entered by a user, a data processing device including artificial intelligence for analyzing the entered data, and means for generating appropriate medical information or recommended actions based on the analysis results. This makes it possible for the AI ​​to analyze the data based on the information entered by the user and propose appropriate information and actions in medical care, life support, and mental health care.

[1987] A "user" refers to a person who uses this system to input information about their medical care, lifestyle support, and mental health care, and receives support based on that information.

[1988] A "data processing device" refers to a combination of hardware and software, including artificial intelligence, used to analyze data entered by users and generate appropriate information and actions based on that analysis.

[1989] A "server" is a computer system on a network that includes a data processing unit, and its role is to receive input data from users, analyze it, and provide the generated information.

[1990] "Medical information" refers to information including diagnostic results obtained by analyzing data on the user's health status and medical condition, recommended countermeasures and treatments, and the need for a doctor's consultation.

[1991] "Recommended actions" refer to specific actions or measures that users should take, generated based on the analysis of their input data.

[1992] "Online consultation" refers to a service that allows experts and users to communicate directly via the internet. In medical contexts, this includes consultations with doctors, and in lifestyle support, it includes communication with supporters and guidance on daily living.

[1993] "Life support" refers to support services aimed at resolving difficulties in users' daily lives, and includes, for example, grocery shopping assistance, household support, and introductions to local volunteers.

[1994] A "supporter" refers to an individual or organization that works in conjunction with a user to provide life support.

[1995] "Mental health care" refers to advice and measures to address the user's mental state, including, for example, counseling, instruction in relaxation techniques, and suggestions for community participation.

[1996] A "community" refers to a place where users with similar problems or needs can gather and help each other. Online forums and chat groups are examples of this.

[1997] This invention relates to a system for comprehensively solving problems related to medical care, daily living support, and mental health care in a super-aging society. This system utilizes a generative AI model to analyze data entered by the user and provide appropriate information and actions.

[1998] The system configuration consists of a terminal that receives user input data, a server that analyzes the data, a terminal that notifies users of information and recommended actions generated based on the analysis results, and means for setting up online consultations.

[1999] Specific hardware includes devices such as smartphones and tablets used by users, as well as servers with powerful data processing capabilities. The term "server" refers to a data processing device, and this definition assumes the use of cloud services.

[2000] The software used includes generative AI models installed on the server. For example, an AI model employing natural language processing (NLP) technology is used for analyzing medical information, while machine learning algorithms are used for analyzing lifestyle support data. Additionally, programs that communicate via APIs are included for setting up notifications and online consultations.

[2001] Specific example 1: Healthcare (connecting people with doctors)

[2002] 1. The user enters their medical condition or symptoms into the application. For example, the user enters "My lower back has been hurting lately."

[2003] 2. The device sends this information to the server.

[2004] 3. The server uses NLP technology to analyze the information it receives and generates information about the cause of lower back pain and recommended countermeasures (e.g., stretching, use of over-the-counter medication, consultation with a specialist).

[2005] 4. The device notifies the user of the information it has generated.

[2006] 5. Users can book online doctor consultations as needed, and the server will coordinate schedules with appropriate doctors and confirm the online consultation booking.

[2007] Example 2: Daily Life (Connecting people with supporters)

[2008] 1. The user enters into the application the difficulties they face in their daily life. For example, they might enter, "It's difficult to go shopping."

[2009] 2. The device sends this information to the server.

[2010] 3. The server uses machine learning algorithms to analyze life needs and identify appropriate support methods (e.g., local volunteers, delivery services).

[2011] 4. The user is notified of the support method for the identified device, and if the user selects one, the server coordinates with a supporter to arrange assistance.

[2012] Specific example 3: Security (connecting people's hearts)

[2013] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[2014] 2. The device sends this information to the server.

[2015] 3. The server uses NLP technology to analyze the user's mental state and generate appropriate advice and mental health care methods.

[2016] 4. The device notifies the user of any advice or mental health care methods it has generated.

[2017] 5. The server proposes communities for users with similar problems and supports them in interacting with each other by encouraging participation.

[2018] Example of a prompt

[2019] "My lower back has been hurting lately, what should I do?"

[2020] "I'm having trouble going shopping. Please help me."

[2021] "I'm lonely living alone."

[2022] This system uses a generative AI model to analyze user input with high accuracy and provide various types of support quickly and appropriately. As a result, users can gain an environment where they can comprehensively resolve issues related to their health, lifestyle, and mental well-being.

[2023] The flow of the specific processing in Example 1 will be explained using Figure 11.

[2024] Healthcare (connecting people with doctors)

[2025] Program processing steps

[2026] Step 1:

[2027] The user enters their medical condition and symptoms into the application.

[2028] Input: User-generated text (e.g., "My back has been hurting lately").

[2029] Output: Input data (text data).

[2030] Step 2:

[2031] The terminal sends the input information to the server.

[2032] Input: Text data entered by the user.

[2033] Data processing: The terminal encrypts the text data and sends it to the server using a secure communication method (e.g., HTTPS).

[2034] Output: Encrypted data packets.

[2035] Step 3:

[2036] The server analyzes the information using an AI module.

[2037] Input: Received encrypted data.

[2038] Data processing: The server decodes the data and analyzes the text using generative AI models and natural language processing (NLP) techniques. Specifically, it activates the model and matches it with patterns and datasets related to the user's symptoms.

[2039] Output: Analysis results (e.g., causes of lower back pain and recommended countermeasures).

[2040] Step 4:

[2041] The server generates the countermeasures.

[2042] Input: Analysis result data.

[2043] Data processing: Using an interactive AI engine, recommended actions (e.g., stretching, over-the-counter medication, consultation with a specialist) are generated.

[2044] Output: Recommended countermeasures list.

[2045] Step 5:

[2046] The device notifies the user of the necessary countermeasures.

[2047] Input: Recommended countermeasures list.

[2048] Data processing: Convert the generated recommended actions into a user-friendly format (e.g., pop-up notifications or in-app messages).

[2049] Output: Notifications displayed to the user.

[2050] Step 6:

[2051] The user books an online doctor consultation.

[2052] Input: User reservation information (e.g., desired date and time).

[2053] Data processing: Send reservation information to the server via the input form.

[2054] Output: Submitted reservation request.

[2055] Step 7:

[2056] The server adjusts the schedule and confirms the reservation.

[2057] Input: Reservation request.

[2058] Data processing: Check doctors' availability and confirm schedules using Microsoft Teams or other online meeting platforms.

[2059] Output: Notification of confirmed reservation information.

[2060] Life (Connecting people with supporters)

[2061] Program processing steps

[2062] Step 1:

[2063] Users input the difficulties they face in their daily lives into the application.

[2064] Input: User-generated text (e.g., "It's difficult to go shopping").

[2065] Output: Input data (text data).

[2066] Step 2:

[2067] The device sends this information to the server.

[2068] Input: Text data entered by the user.

[2069] Data processing: Encrypt text data and send it to the server using a secure communication method.

[2070] Output: Encrypted data packets.

[2071] Step 3:

[2072] The server analyzes lifestyle needs.

[2073] Input: Received encrypted data.

[2074] Data processing: The server decrypts the data and uses AWS SageMaker's AI module to analyze lifestyle needs. It then matches the data against a dataset to identify the necessary support methods.

[2075] Output: Analysis results (e.g., appropriate support methods).

[2076] Step 4:

[2077] The server generates the appropriate support method.

[2078] Input: Analysis result data.

[2079] Data processing: Based on the analysis results, the AI ​​generates appropriate support methods (e.g., suggesting local volunteers or delivery services).

[2080] Output: List of supported methods.

[2081] Step 5:

[2082] The device will notify you of the support method.

[2083] Input: List of support methods.

[2084] Data processing: Notify users of the generated support methods in an easy-to-understand format.

[2085] Output: Notifications displayed to the user.

[2086] Step 6:

[2087] The user selects the support option.

[2088] Input: User selection information.

[2089] Data processing: The user selects their preferred support method and sends that selection information to the server.

[2090] Output: Sent selection information.

[2091] Step 7:

[2092] The server coordinates with supporters to arrange assistance.

[2093] Input: Submitted selection information.

[2094] Data processing: Use integration tools such as Slack to notify supporters of the support needed and make specific arrangements.

[2095] Output: Notification of the assistance arranged.

[2096] Security (connecting people's hearts)

[2097] Program processing steps

[2098] Step 1:

[2099] Users input their emotional state and worries into the application.

[2100] Input: User-generated text (e.g., "I'm lonely living alone").

[2101] Output: Input data (text data).

[2102] Step 2:

[2103] The device sends this information to the server.

[2104] Input: Text data entered by the user.

[2105] Data processing: Encrypt text data and send it to the server using a secure communication method.

[2106] Output: Encrypted data packets.

[2107] Step 3:

[2108] The server analyzes the state of mind.

[2109] Input: Received encrypted data.

[2110] Data processing: The server decodes the data and analyzes the mental state using Google Cloud AI modules. Natural language processing (NLP) techniques are used for the analysis.

[2111] Output: Analysis results (e.g., appropriate advice or methods for mental health care).

[2112] Step 4:

[2113] The server generates the care instructions.

[2114] Input: Analysis result data.

[2115] Data processing: Based on the analysis results, generate advice and mental health care methods (e.g., suggestions for yoga or meditation, suggestions for participating in community center events).

[2116] Output: List of care methods.

[2117] Step 5:

[2118] The device will notify you of care instructions.

[2119] Input: List of care methods.

[2120] Data processing: Notify users of the generated care methods in an easy-to-understand format.

[2121] Output: Notifications displayed to the user.

[2122] Step 6:

[2123] The server generates community suggestions.

[2124] Input: List of methods for mental health care.

[2125] Data processing: Based on the analysis results, generate suggestions for communities and online forums where users with similar problems can participate.

[2126] Output: Community suggestion list.

[2127] Step 7:

[2128] The server supports community participation.

[2129] Input: Community suggestion list.

[2130] Data processing: Provide users with information to join the proposed community and make it easy to access the community using platforms such as Discord.

[2131] Output: Notification regarding participation procedures.

[2132] This will enable users to easily manage information related to their health, lifestyle, and mental well-being, and to receive optimal support.

[2133] (Application Example 1)

[2134] 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".

[2135] In a super-aging society, it is becoming increasingly difficult for the elderly to maintain their daily lives on their own. A particular problem is the limited availability of appropriate support, especially in areas such as meal preparation and health management. Furthermore, comprehensive support encompassing medical care, daily living assistance, and mental health care is necessary to ensure that the elderly can live healthy and safe lives without isolation.

[2136] 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.

[2137] In this invention, the server includes means for receiving data entered by a user, means including artificial intelligence for analyzing the entered data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for generating appropriate meal plans and food ingredient suggestions for the user based on the notification, and means for arranging the purchase and delivery of food ingredients based on the suggestions. This enables comprehensive support for elderly people to maintain a healthy and safe life.

[2138] "Data entered by the user" refers to the information and requests provided by those who use the system.

[2139] "Means" refers to the methods, devices, or processes used to achieve a specific objective.

[2140] "Artificial intelligence for analysis" refers to AI technology that analyzes input data and derives relevant information and recommended actions.

[2141] A "server" refers to a computer system used for managing and processing data.

[2142] "Medical information" refers to information and knowledge related to health, treatment, and prevention.

[2143] "Recommended actions" refer to the appropriate actions or methods that should be taken, derived from the user's input data.

[2144] "Means of notification" refers to the methods or devices by which a system communicates information or alerts to a user.

[2145] "Methods for setting up online consultations" refers to the methods and devices used to schedule and prepare systems for users to communicate remotely with experts.

[2146] A "meal plan" refers to a set of meals planned based on the user's health condition and preferences.

[2147] "Food ingredient suggestions" refers to recommended foods and ingredients that users should purchase.

[2148] "Means of arranging purchase and delivery" refers to the procedures and systems for procuring the ingredients selected by the user and having them delivered to their home.

[2149] "Lifestyle needs" refers to the user's demands and required support regarding all aspects of their daily life.

[2150] "Life support" refers to various services and assistance provided to facilitate the user's daily life.

[2151] "Means of coordinating with supporters" refers to methods and devices for coordinating with volunteers and professional services to provide the support that users need.

[2152] "State of mind" refers to the user's mental health and emotional state.

[2153] "Advice" refers to the guidance and suggestions provided to the user.

[2154] "Mental health care" refers to support and activities aimed at maintaining and improving the mental well-being of users.

[2155] "Means of proposing communities" refers to methods and devices that guide users to places where they can interact with other users who share similar interests or concerns.

[2156] The system for implementing this invention receives data input by the user, analyzes it, and provides appropriate suggestions in areas such as medical information, lifestyle support, and mental health care, thereby supporting elderly people in leading healthy and fulfilling lives.

[2157] Hardware and software to be used

[2158] Smartphones and tablets: These are devices used by users to input data and receive suggested information.

[2159] Server: Performs data analysis and generates suggestions.

[2160] Artificial Intelligence (AI) Module: Using TensorFlow and Keras, it analyzes user-input data and generates appropriate medical information, lifestyle support, and mental health care suggestions.

[2161] Communication API: Use Twilio to schedule online doctor and nutritionist consultations as needed.

[2162] System operation

[2163] 1. Data Input and Reception: Users input data into the application using their smartphones or tablets. For example, they might input symptoms, difficulties in daily life, or emotional worries such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone."

[2164] 2. Data Analysis: The server receives the input data and analyzes it using artificial intelligence modules (TensorFlow and Keras). Based on the analysis results, appropriate medical information (stretching methods, treatments), lifestyle support (suggestions for delivery services), and mental health care (suggestions for online consultations and community participation) are generated.

[2165] 3. Suggestion Generation and Notification: Information and suggestions generated on the server are notified to the user's terminal. Based on these notifications, users can arrange online doctor consultations or food delivery services.

[2166] 4. Setting up online consultations: Use communication APIs such as Twilio to schedule and confirm online consultations with doctors and nutritionists as needed.

[2167] Specific example

[2168] A 70-year-old elderly person living alone enters a request into the app for "healthy meals that take diabetes into consideration." The server analyzes this information and suggests low-sugar menus and preparation methods. The user can then order the ingredients for the suggested menus through a food delivery service, which will be delivered that evening. Furthermore, they can also book online consultations with a nutritionist if needed.

[2169] Example of a prompt

[2170] "Please suggest a healthy and delicious dinner."

[2171] "Please share some breakfast ideas that are suitable for people with diabetes."

[2172] "Please create a list of ingredients for this week."

[2173] In this way, this system provides comprehensive support for older adults to live safely and healthily.

[2174] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[2175] Step 1:

[2176] User data entry

[2177] Users use smartphones or tablets to input data about their medical condition, lifestyle needs, and mental state into the application. For example, they might enter prompts such as "My back has been hurting lately," "It's difficult to go shopping," or "I feel lonely living alone." This input data is recorded on the device and immediately sent to the server.

[2178] Step 2:

[2179] Data reception and preprocessing

[2180] The server receives user input data sent from the terminal. It then formats the received data and converts it into a parsable format. This preprocessing involves using natural language processing (NLP) tools to tokenize and grammatically analyze the text. For example, if the user inputs "My back has been hurting lately," the server generates an appropriate text format.

[2181] Step 3:

[2182] Data analysis and model application

[2183] The server inputs pre-processed data into a generative AI model (using TensorFlow or Keras). The AI ​​model analyzes the received data and generates appropriate medical information, lifestyle support, and mental health care suggestions. For example, it might analyze "lower back pain" and suggest stretching methods and treatments. The output includes a list of analysis results and suggestions.

[2184] Step 4:

[2185] Generation and transmission of proposal information

[2186] The server generates specific suggestion information based on the analysis results of the AI ​​model. This suggestion information includes medical information, lifestyle support, and mental health care methods that best suit the user's needs. The generated information is then formatted again in text format and sent to the user's device. For example, the device might receive notifications such as "Do some back stretches" or "Consider using a local delivery service."

[2187] Step 5:

[2188] User awareness and choice

[2189] The user reviews the suggested information displayed on their device. They can then select actions such as online doctor consultations, grocery ordering, or nutritionist consultations, as needed. Once the user selects an action, that information is sent back to the server.

[2190] Step 6:

[2191] Arrangement for the execution of the action

[2192] The server performs the necessary actions based on the user's selections. For example, it might use the Twilio API to set up an online doctor consultation appointment. It might also arrange for groceries to be ordered and delivered through a food delivery service based on the selected suggestions. Once all arrangements are complete, confirmation information is sent to the user's device.

[2193] This series of processing steps will result in a system that comprehensively supports the health management, daily living assistance, and mental health care of the elderly.

[2194] 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.

[2195] Modes for carrying out the invention

[2196] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society, and can provide more personalized support by combining generative AI and an emotion engine. The system includes a server that receives data entered by the user and analyzes it using artificial intelligence (AI), a terminal that generates and notifies appropriate information and actions based on the analysis results, means for setting up online consultations as needed, and an emotion engine that recognizes the user's emotions.

[2197] 1. Providing medical information combined with emotion recognition.

[2198] Program processing:

[2199] 1. The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[2200] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[2201] 3. The server's AI analyzes the entered medical conditions and symptoms using natural language processing and combines them with emotional data to generate medical information and recommended actions. For example, if the user is feeling anxious, a reassuring message will be added.

[2202] 4. The device notifies the user of the medical information it has generated.

[2203] 5. The user selects the option to book an online doctor consultation as needed, and the server coordinates the schedule with the doctor and confirms the appointment.

[2204] 2. Providing life support that combines emotion recognition.

[2205] Program processing:

[2206] 1. The user inputs their daily life difficulties and needs into the application. For example, they might input, "It's difficult to go shopping."

[2207] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[2208] 3. The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate appropriate lifestyle support methods (e.g., volunteering, delivery services). For example, if a user is feeling stressed, it will also suggest relaxation methods to reduce stress.

[2209] 4. The terminal identifies a specific life support method and notifies the user. If the user selects a method, the server coordinates with the supporter to arrange the assistance.

[2210] 3. Mental care combined with emotion recognition

[2211] Program processing:

[2212] 1. The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[2213] 2. The terminal analyzes the user's emotions along with the input data using an emotion engine and sends the emotion data to the server.

[2214] 3. The server's AI analyzes the user's emotional state and concerns using natural language processing technology, and combines this with emotional data to generate appropriate advice and methods for emotional care. For example, if a user is feeling sad, it will suggest encouraging messages and activities to lift their spirits.

[2215] 4. The device notifies the user of any advice or mental health care methods it has generated.

[2216] 5. The server further proposes communities for users in similar situations and supports users in interacting with each other by encouraging their participation.

[2217] This system can provide more personalized support by combining user input data with analysis results from an emotion engine. This allows it to comprehensively cover medical care, lifestyle support, and mental health care, thereby improving the user's quality of life.

[2218] The following describes the processing flow.

[2219] 1. Healthcare (connecting people with doctors)

[2220] Processing steps

[2221] Step 1:

[2222] The user enters their medical condition or symptoms into the application. For example, they might enter, "My lower back has been hurting lately."

[2223] Step 2:

[2224] The terminal sends the medical condition and symptoms entered, as well as emotional data (e.g., anxiety, pain) recognized by the emotion engine through user facial recognition and voice analysis, to the server.

[2225] Step 3:

[2226] The server passes the received data to the AI ​​module, which then begins analyzing the patient's condition and symptoms.

[2227] Step 4:

[2228] The server's AI uses natural language processing to analyze the patient's condition and symptoms, and combines this with emotional data to generate analysis results.

[2229] Step 5:

[2230] The server's AI generates appropriate medical information and recommended actions (e.g., stretching methods, recommendations for over-the-counter medications, the need for a specialist consultation, etc.) based on the analysis results.

[2231] Step 6:

[2232] The server formats the generated medical information and adds reassuring messages tailored to the user's emotions.

[2233] Step 7:

[2234] The terminal receives the generated response message and notifies the user.

[2235] Step 8:

[2236] Users can choose to book an online doctor consultation as needed.

[2237] Step 9:

[2238] The server receives the user's appointment request and coordinates the schedule with the doctor.

[2239] Step 10:

[2240] The server confirms the online consultation appointment and sends a reservation confirmation notification to the user.

[2241] 2. Life (Connecting people with supporters)

[2242] Processing steps

[2243] Step 1:

[2244] The user enters their difficulties and needs in daily life through the application. For example, they might enter, "It's difficult for me to go shopping."

[2245] Step 2:

[2246] The device sends the inputted lifestyle needs and emotional data recognized by the user's emotion engine (e.g., stress, fatigue) to the server.

[2247] Step 3:

[2248] The server passes the received data to the AI ​​module, which then begins analyzing lifestyle needs.

[2249] Step 4:

[2250] The server's AI analyzes lifestyle needs using natural language processing technology and combines them with emotional data to generate analysis results.

[2251] Step 5:

[2252] The server's AI generates appropriate life support methods (e.g., volunteering, delivery services) based on the analysis results.

[2253] Step 6:

[2254] The server formats the generated life support information and adds stress reduction suggestions that take the user's emotions into consideration.

[2255] Step 7:

[2256] The terminal receives the generated response message and notifies the user.

[2257] Step 8:

[2258] The user selects the most appropriate method from among the suggested life support options.

[2259] Step 9:

[2260] The terminal sends the user's selection to the server.

[2261] Step 10:

[2262] The server coordinates with supporters based on the selected life support information and arranges assistance.

[2263] 3. Security (connecting people's hearts)

[2264] Processing steps

[2265] Step 1:

[2266] The user enters their emotional state or worries into the application. For example, they might enter, "I'm lonely because I live alone."

[2267] Step 2:

[2268] The device sends the entered mental state and emotional data recognized by the emotion engine (e.g., loneliness, fatigue) to the server.

[2269] Step 3:

[2270] The server passes the received data to the AI ​​module, which then begins analyzing the user's emotional state and concerns.

[2271] Step 4:

[2272] The server's AI analyzes the user's emotional state and worries using natural language processing technology, and combines this with emotional data to generate analysis results.

[2273] Step 5:

[2274] The server's AI generates appropriate advice and mental health support methods based on the analysis results.

[2275] Step 6:

[2276] The server formats the generated advice and emotional support methods, and also adds messages that empathize with the user's feelings.

[2277] Step 7:

[2278] The terminal receives the generated response message and notifies the user.

[2279] Step 8:

[2280] The server then generates a message suggesting communities for users in similar situations.

[2281] Step 9:

[2282] The device receives the suggestion message and notifies the user.

[2283] Step 10:

[2284] If a user wishes to join the community, the device sends a participation request to the server.

[2285] Step 11:

[2286] The server receives the participation request and provides the user with information on how to access the community.

[2287] The above outlines the specific processing steps in each system. This system combines generative AI and an emotion engine to provide medical care, lifestyle support, and mental health care while taking the user's emotions into consideration, thereby improving the user's quality of life.

[2288] (Example 2)

[2289] 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".

[2290] In a super-aging society, the problems faced by the elderly are diverse, encompassing healthcare, daily living support, and mental health care. Current systems lack comprehensive support for these needs, making it difficult to provide personalized assistance. Furthermore, support that takes into account the user's emotional state is not being provided, resulting in a lack of truly needed support.

[2291] The specific processing performed by the specific 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 receiving data input by a user, means including artificial intelligence for analyzing the input data, means for generating emotion data using an emotion analysis engine for analyzing the user's emotions, means for providing analysis results by combining the emotion data and input data, means for generating appropriate medical information, lifestyle support methods, or mental health care based on the analysis results, means for notifying the user of the generated information, recommended actions, or mental health care, and means for setting up an online consultation with a doctor or suggesting a community of users as necessary based on the notification. This makes it possible to provide personalized medical information, lifestyle support, and mental health care that takes the user's emotions into consideration.

[2292] A "user" refers to an individual who uses the system to receive medical information, lifestyle support, or mental health care.

[2293] "Input data" refers to information about medical conditions, lifestyle needs, and mental state entered into the application by the user.

[2294] A "server" refers to a computer system that analyzes data received from users and generates and notifies them of the results.

[2295] "Artificial intelligence" refers to machine learning models or natural language processing technologies that analyze input data and generate appropriate information or recommended actions.

[2296] A "sentiment analysis engine" refers to a software module that analyzes emotions from user input data and generates emotional data.

[2297] "Emotional data" refers to information that indicates the user's emotional state, generated by an emotion analysis engine.

[2298] "Analysis results" refer to the output generated by artificial intelligence and emotion analysis engines, based on user input data and emotion data.

[2299] "Medical information" refers to information including diagnoses, treatment methods, and recommended actions related to the user's medical condition.

[2300] "Life support methods" refer to specific support measures and services designed to meet the user's lifestyle needs.

[2301] "Mental health care" refers to advice, suggestions, and support methods for addressing the mental health issues that users are experiencing.

[2302] "Notification" refers to the process of communicating information or actions generated by a server to the user.

[2303] "Online consultation setup" refers to the process of booking and scheduling an online consultation with a medical professional or other expert.

[2304] A "community suggestion" refers to a suggestion made from the server to users to provide a space where users in similar situations can interact with each other.

[2305] This invention relates to a system that comprehensively provides medical care, lifestyle support, and mental health care in a super-aging society. By combining generative artificial intelligence (AI) and an emotion analysis engine, the system can provide more personalized support.

[2306] Hardware and software to be used

[2307] Server: Receives data from users, performs data analysis, and provides information. For example, a high-performance cloud server (e.g., AWS, Google Cloud) can be used.

[2308] Terminal: A device used by users to input data and receive results. This includes smartphones, tablets, and personal computers.

[2309] Artificial intelligence (AI): Machine learning models used for data analysis. For example, OpenAI's GPT-4 is used as a generative AI model.

[2310] Emotion analysis engine: Software used to generate user emotion data. Examples include EmotionAI, Affectiva, and IBM Watson Tone Analyzer.

[2311] Data processing and calculations

[2312] 1. Data entry

[2313] Users access the application on their device and input text about their medical condition, lifestyle needs, and mental state.

[2314] 2. Generation of emotion data

[2315] The device sends the input data to an emotion analysis engine, which then analyzes the user's emotions. For example, it generates emotion tags such as "anxiety," "stress," and "sadness."

[2316] 3. Sending data

[2317] The device sends the analyzed emotion data and input data to the server.

[2318] 4. Data Analysis and Generation

[2319] The server's AI analyzes the received data using natural language processing and combines it with emotional data to generate optimal information and recommended actions. For example, it can generate information such as "medical information," "life support methods," and "mental health care."

[2320] 5. Notification

[2321] The generated information and recommended actions are notified to the user via their device. The user then checks this information on their device.

[2322] 6. Online consultations and community proposals

[2323] If needed, users can choose the option to book an online doctor consultation, and the server will handle scheduling. The system also suggests and allows users to participate in user communities.

[2324] Examples of specific cases and prompt statements

[2325] For example, a user might input "My back has been hurting lately" into the application, expressing anxiety. In this case, the system would operate as follows:

[2326] User input: "My lower back has been hurting lately."

[2327] Example prompt: "If a user types 'My back hurts' and is feeling anxious, what reassuring message can you generate?"

[2328] Based on the "anxiety" tag generated by the emotion analysis engine and the user's medical condition data of "back pain," the server uses AI to generate the following message:

[2329] "Stretching is effective for lower back pain. If you are experiencing any concerns, we recommend consulting a doctor."

[2330] In this way, the system can provide optimal medical information and recommended actions while taking the user's emotions into consideration.

[2331] Similarly, for daily living support and mental health care, personalized support is provided that takes into account the user's emotional data. For example, if a user inputs "It's difficult to go shopping" and is feeling stressed, a message such as "We recommend using a delivery service for shopping and taking deep breaths to reduce stress" will be generated.

[2332] This system makes it possible to improve the quality of life for users by comprehensively covering medical care, daily living support, and mental health care.

[2333] The flow of the specific processing in Example 2 will be explained using Figure 13.

[2334] Step 1:

[2335] The user accesses the application screen and enters their medical condition, lifestyle needs, and mental state. For example, they might enter, "My lower back has been hurting lately."

[2336] Input: Medical condition, lifestyle needs, mental state (text format)

[2337] Output: Input data (medical condition information, etc.)

[2338] Step 2:

[2339] The device sends the input data to an emotion analysis engine to analyze the user's emotions. For example, it uses EmotionAI or Affectiva to generate emotion tags such as "anxiety."

[2340] Input: Input data (medical condition, lifestyle needs, mental state)

[2341] Data processing: Emotional analysis using an emotion analysis engine.

[2342] Output: Sentiment data (sentiment tags)

[2343] Step 3:

[2344] The device sends the analyzed emotion data and input data to the server.

[2345] Input: Input data, sentiment data

[2346] Output: Integrated data sent to the server (input data + sentiment data)

[2347] Step 4:

[2348] The server uses AI (for example, OpenAI's GPT-4) to analyze the received data using natural language processing. For example, it might extract medical information related to "lower back pain."

[2349] Input: Integrated data (input data + sentiment data)

[2350] Data processing: Data analysis using natural language processing

[2351] Output: Analysis results (medical information, lifestyle support methods, mental health care methods)

[2352] Step 5:

[2353] The server combines emotional data to generate medical information and recommended actions. For example, it might generate a message such as, "Stretching is effective for back pain. If you are feeling anxious, we recommend consulting a doctor."

[2354] Input: Analysis results, sentiment data

[2355] Data processing: Information generation using generative AI models.

[2356] Output: Generated information (medical information, recommended actions, mental health care methods)

[2357] Step 6:

[2358] The device receives information generated from the server and notifies the user. The user's device displays the message, "Stretching is effective for lower back pain. If you are feeling anxious, we recommend consulting a doctor."

[2359] Input: Generated information

[2360] Output: Information displayed on the user screen

[2361] Step 7:

[2362] Users can select an online doctor consultation booking option from the application as needed. For example, a user might click the "Online Consultation" button.

[2363] Input: User reservation selection

[2364] Output: Reservation Request

[2365] Step 8:

[2366] The server receives the user's selection, coordinates the schedule with the doctor, and confirms the appointment. The server then notifies the user's device of the confirmed appointment information.

[2367] Input: Reservation Request

[2368] Data processing: Schedule adjustment and reservation confirmation.

[2369] Output: Reservation confirmation notification

[2370] Step 9:

[2371] If necessary, the server will suggest that the user join a community of users in similar situations. For example, it might generate a message such as, "Why not join a community of users who feel lonely?"

[2372] Input: Sentiment data, analysis results

[2373] Data processing: Community proposal generation using generative AI models

[2374] Output: Community suggestion notification

[2375] (Application Example 2)

[2376] 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".

[2377] With the advancement of a super-aging society, the conventional system is insufficient to adequately address the increasing demand for medical care, lifestyle support, and mental health care for the elderly, in terms of individualization and emergency response. Therefore, there is a need for more personalized food delivery services that incorporate emotional recognition, enabling the elderly to live with peace of mind.

[2378] 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. In this invention, the server includes means for receiving data input by the user, a server including artificial intelligence for analyzing the input data, means for generating appropriate medical information or recommended actions based on the analysis results, means for notifying the user of the generated information or recommended actions, means for setting up an online consultation with a doctor as necessary based on the notification, means for analyzing the user's emotions with an emotion engine and transmitting the emotion data to the server, and means for analyzing the combination of emotion data and user input data to generate personalized suggestions. This makes it possible to provide services according to the user's emotional state.

[2379] "Means for receiving user-entered data" refers to a function that collects text, voice, or other forms of data entered by the user and sends them to a server for analysis.

[2380] A "server that includes artificial intelligence" is a server that incorporates algorithms to analyze input data and generate appropriate information.

[2381] "Means for generating appropriate medical information or recommended actions based on analysis results" refers to a function that provides users with appropriate medical information and guidance on what to do next, based on the analyzed data.

[2382] "Means for notifying the user of generated information or recommended actions" refers to a function for notifying the user of generated information or recommended actions.

[2383] "Method for setting up online consultations with doctors" refers to a function for setting up online consultations between doctors and users as needed.

[2384] An "emotion engine" refers to software or algorithms used to analyze a user's emotions.

[2385] "Emotional data" refers to data that indicates a user's emotional state, analyzed using an emotion engine.

[2386] "Means of sending to the server" refers to the function of sending collected sentiment data and user input data to the server.

[2387] "A means of combining and analyzing emotional data and user input data to generate personalized suggestions" refers to a function that integrates and analyzes emotional data and input data to create and notify individual users of suggestions optimized for them.

[2388] "Lifestyle needs" refer to the basic requirements and problems that users face in their daily lives.

[2389] "Means of providing life support" refers to functions that provide appropriate support and services based on the user's life needs.

[2390] "Means of arranging life support in cooperation with supporters" refers to the function of arranging and coordinating the supporters and services necessary for life support.

[2391] "State of mind" refers to the user's psychological and emotional state.

[2392] "Means of generating advice or emotional support" refers to functions that provide appropriate advice or support methods based on the user's psychological state.

[2393] "Means of proposing user communities" refers to a function that proposes communities where users in similar situations can connect and help each other.

[2394] This invention is specifically designed for food delivery services in an aging society, combining generative AI and an emotion engine to provide a more personalized service that meets user needs. The system's implementation includes the following elements:

[2395] 1. Hardware and Software Configuration

[2396] Hardware:

[2397] Smartphone: A device for user input and notifications.

[2398] Server: A central device for data analysis and processing.

[2399] software:

[2400] Emotion engine: Uses the Microsoft Azure Emotion API.

[2401] Generative AI: OpenAI GPT-4 is used.

[2402] Food delivery related: Use a dedicated API (e.g., Uber Eats API).

[2403] 2. Program Processing

[2404] User input:

[2405] Users enter their desired dishes and recent preferences as text via a smartphone app. This data is sent to an emotion engine and then forwarded to a server for further analysis.

[2406] Emotion recognition:

[2407] The emotion engine (Microsoft Azure Emotion API) analyzes facial expressions from user input data and camera footage, and extracts emotion data. This data is also sent to the server.

[2408] Information analysis:

[2409] The server's AI (OpenAI GPT-4) analyzes emotional and text data, linking what the user wants with their emotional state. It then generates specific order suggestions and accompanying reassuring messages.

[2410] Suggestion generation:

[2411] The AI ​​generator might suggest, for example, "Japanese sushi," to the user, along with a message like "to help you relax." This suggestion is then communicated to the user via their device.

[2412] Order confirmation and notification:

[2413] Once the user agrees to the proposal, the order is confirmed. Notifications (such as food preparation status and estimated delivery time) are also integrated to provide reassurance, taking into account certain emotional states (such as anxiety).

[2414] Setting up an online consultation:

[2415] If necessary, an online nutritionist consultation regarding dietary habits will be set up. This process is also handled by the server, which manages scheduling and confirms reservations.

[2416] 3. Add specific examples

[2417] The following is an example of a prompt message.

[2418] Example 1: "I've been craving Japanese food lately." (User's judgment)

[2419] User input:

[2420] Text: Lately I've been craving Japanese food.

[2421] Camera footage: A smile and a little fatigue

[2422] Server processing:

[2423] 1. Input text analysis: → I want to eat Japanese food

[2424] 2. Emotional analysis: → Feeling fatigued

[2425] Suggestion generation:

[2426] Generation AI:

[2427] You seem tired. How about ordering some Japanese sushi to help you relax? There's a particular restaurant that's known for its excellent sushi.

[2428] Specific example 2: "It's cold, so I want to eat something warm." - User's anxiety

[2429] User input:

[2430] Text: It's cold, so I want to eat something warm.

[2431] Camera footage: A slightly anxious expression.

[2432] Server processing:

[2433] 1. Input text analysis: → I want some warm food.

[2434] 2. Emotion analysis: → Anxious

[2435] Suggestion generation:

[2436] Generation AI:

[2437] For a meal on a cold day, udon noodles with a soft-boiled egg are perfect. Let the warm soup soothe both your body and soul.

[2438] The delivery time is short, so you can enjoy it right away.

[2439] This system provides food delivery services that cater to the user's emotional state and specific requests.

[2440] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[2441] Step 1:

[2442] The user enters text or voice input using a smartphone app. For example, they might input, "I've been craving Japanese food lately." This input data is received and passed on to the next process.

[2443] Step 2:

[2444] The device captures the user's facial expressions through the user's camera feed. The facial expression data is analyzed using an emotion engine (Microsoft Azure Emotion API) to generate emotion data. This emotion data, along with the text input data, is sent to the server.

[2445] Step 3:

[2446] The server receives user input data and sentiment data and performs analysis using AI (OpenAI GPT-4). Specifically, it analyzes the input text information using natural language processing techniques to determine the user's needs and emotional state. In this step, for example, the need "I want to eat Japanese food" and the emotion "I'm feeling tired" might be detected.

[2447] Step 4:

[2448] The server uses a generative AI model (GPT-4) to generate personalized suggestions based on the user's needs and emotional state. The generated suggestion might take the form of, for example, "You seem tired. How about ordering some Japanese sushi to help you relax?" This suggestion data is then passed on to the next step.

[2449] Step 5:

[2450] The terminal receives suggestion data from the server and notifies the user. The user reviews the notification and chooses whether or not to order the suggested dishes.

[2451] Step 6:

[2452] The user agrees to the offer and confirms the food order. The device sends the order information back to the server. The server works with food delivery-related APIs (e.g., Uber Eats API) to process the order. This results in the food being delivered from the specified restaurant to the specified delivery address.

[2453] Step 7:

[2454] After an order is confirmed, the server generates and sends notifications to the user's device regarding delivery status and food preparation status. These notifications include detailed information to provide reassurance, such as status and estimated delivery time.

[2455] Step 8:

[2456] If necessary, and the user requests advice on their diet, the device will offer an option to book an online consultation with a nutritionist. The server will process this booking request, schedule and confirm the appointment, and send a booking confirmation notification to the user.

[2457] The specific steps are as follows.

[2458] Example 1: "I've been craving Japanese food lately." (User's judgment)

[2459] Step 1:

[2460] User input: "Lately I've been craving Japanese food."

[2461] Input data: Text

[2462] Step 2:

[2463] Device analysis: Captures facial expression data.

[2464] Emotion Engine (Microsoft Azure Emotion API) Analysis

[2465] Emotional data generation: Feeling tired (emotional data)

[2466] Step 3:

[2467] Server analysis:

[2468] Input data + emotion data

[2469] Extracting information such as "I want to eat Japanese food" and "I'm feeling tired."

[2470] Step 4:

[2471] Server generation:

[2472] Generation AI (GPT-4)

[2473] Suggestion: You seem tired. How about ordering some Japanese sushi to help you relax?

[2474] Step 5:

[2475] notification:

[2476] Display suggestion message

[2477] Step 6:

[2478] User verification:

[2479] Confirm your order

[2480] Step 7:

[2481] Server processing:

[2482] Send order information to the food delivery API.

[2483] Step 8:

[2484] Delivery status notification:

[2485] Inform the user that their order is in transit and the estimated arrival time.

[2486] Step 9 (Optional):

[2487] Online consultation booking

[2488]

[2489] 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.

[2490] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of 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.

[2491] 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 robot 414.

[2492] 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.

[2493] 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.

[2494] 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.

[2495] 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.

[2496] 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.

[2497] 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...

Claims

1. A means of receiving data entered by the user, A server including artificial intelligence for analyzing the input data, A means for generating appropriate medical information or recommended actions based on the aforementioned analysis results, Means for notifying the user of the generated information or recommended actions, Based on the aforementioned notification, a means to set up an online consultation with a doctor as needed, A system that includes this.

2. A means of receiving lifestyle needs entered by the user, A server including artificial intelligence for analyzing the input lifestyle needs, Means for providing appropriate life support based on the aforementioned analysis results, A means of arranging the aforementioned life support in cooperation with supporters, The system according to claim 1, including the following:

3. A means of receiving the mental state entered by the user, A server including artificial intelligence for analyzing the input mental state, A means for generating appropriate advice or mental health care based on the aforementioned analysis results, Means for notifying the user of the generated advice or emotional support, Based on the aforementioned notification, a means of proposing user communities, The system according to claim 1, including the following:

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