system

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving personal information and medical examination results input by a user; means for periodically collecting SNS posts and search histories of the user; means for analyzing a specific dangerous keyword from the collected data and detecting an abnormality; means for generating an appropriate support message and notifying the user when an abnormality is detected; and means for transmitting a notification to a professional counselor when it is difficult to respond or when the risk is high.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] The current increase in suicides among young people is largely due to the lack of people to talk to and the inability to obtain reliable advice. Current counseling services have difficulty providing 24-hour support due to physical constraints and a lack of specialists. A particular problem is the lack of a system for immediately detecting users in an abnormal psychological state and providing appropriate support. Another issue is the lack of a system that allows professional counselors to respond immediately when an abnormality is detected. [Means for solving the problem]

[0005] The system of the present invention includes a means for receiving personal information and health checkup results entered by the user. It also includes a means for periodically collecting the user's social media posts and search history, and a means for analyzing specific risk keywords from the collected data to detect abnormalities. Furthermore, it includes a means for generating an appropriate support message and notifying the user when an abnormality is detected, and a means for sending a notification to a professional counselor when the problem is difficult to resolve or the risk is high. This allows the psychological state of young people to be monitored 24 hours a day, and active and manned support can be provided immediately as needed.

[0006] "User" refers to a person who uses this system.

[0007] "Personal information" refers to information that can identify an individual, such as a user's name, age, gender, or address.

[0008] "Physical examination results" refers to the results of a medical examination that a user has undergone at a medical institution, and includes data related to mental health in particular.

[0009] "SNS posts" refers to content such as text, images, and videos posted by users on social networking services.

[0010] "Search history" refers to the keywords and search results that a user searches using an Internet search engine.

[0011] "Dangerous keywords" are words or phrases that are likely to indicate a particular psychological state or behavior. Examples include "I want to die," "Suicide," and "Pain."

[0012] "Detecting anomalies" refers to determining that there is an abnormality in the user's psychological state based on collected data.

[0013] A "support message" refers to a message containing advice or words of encouragement provided to a user when an abnormality is detected.

[0014] A "professional counselor" refers to a person who has specialized knowledge in psychology or psychiatry and is qualified to provide appropriate counseling to users.

[0015] "Generative artificial intelligence" refers to a system that uses natural language processing and machine learning to analyze data from users and automatically generate appropriate responses. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI (generative artificial intelligence). The system is mainly composed of three main components: a server, a terminal, and a user.

[0038] overview

[0039] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and, if it detects an abnormality, sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor, who will provide more specialized support.

[0040] Specific examples of processing

[0041] User registration and data acquisition

[0042] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0043] Anomaly detection

[0044] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, and the AI ​​analyzes specific dangerous keywords. For example, if a user posts on social media "School is hard" or "I feel like I want to die," the AI ​​analyzes these posts and detects anomalies.

[0045] Active Support Starts

[0046] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0047] Escalation and Human Support

[0048] If the AI ​​determines that the situation is difficult to address or that the risk is high, it will send an SOS notification to the server, which will then notify a professional counselor. For example, if the risk level is 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0049] This system uses generative AI to detect anomalies and provide support 24 hours a day, providing an environment where users can consult at any time. It also allows for on-site support by professional counselors, allowing for more appropriate support to be provided to users.

[0050] In this way, the present invention provides an effective counseling system aimed at preventing suicide among young people.

[0051] The processing flow will be explained below.

[0052] Step 1:

[0053] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0054] Step 2:

[0055] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0056] Step 3:

[0057] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0058] Step 4:

[0059] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0060] Step 5:

[0061] The generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0062] Step 6:

[0063] The server receives the "anomaly detected" flag from the generation AI and starts active support. The generation AI generates an appropriate support message (e.g., "Are you okay? We're here to help you."), and the server sends it to the user's device.

[0064] Step 7:

[0065] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0066] Step 8:

[0067] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0068] Step 9:

[0069] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0070] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0071] Example 1

[0072] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0073] In recent years, the suicide rate among young people has been increasing, making it an urgent task to detect abnormalities early and provide appropriate support. In particular, there is a need for a method to detect early signs of suicide from posts and search history on social networking services and provide professional support. However, existing systems are insufficient in collecting and analyzing data, making it difficult to respond in real time.

[0074] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0075] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for encrypting the collected data and transmitting it to the server, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for sending an appropriate prompt sentence to the generative AI model based on the analysis results, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when response is difficult or risk is high. This makes it possible to detect abnormalities in real time and provide appropriate support promptly while ensuring the safety of the collected data.

[0076] "Personal information" refers to information that can be used to individually identify a user, such as the user's name, age, gender, address, and contact details.

[0077] "Physical examination results" refers to data relating to the health condition of a user, such as blood pressure, body temperature, and blood test results, obtained when the user undergoes a medical examination.

[0078] A "social networking service" is an online platform that enables users to share information and communicate with other users.

[0079] "Search history" is a record of keywords or phrases that a user searches for on an Internet search engine.

[0080] "Data encryption" is a technology that codes transmitted data using a specific algorithm to protect it from unauthorized access.

[0081] A "generative AI model" is an artificial intelligence system that has been trained to perform a specific task using machine learning techniques.

[0082] A "prompt sentence" is a sentence that serves as input to a generative AI model, such as an instruction or question.

[0083] A "support message" is a message that is provided to the user and contains comforting words or a message that encourages action.

[0084] An "expert" is a professional with advanced knowledge and experience in the fields of psychology and counseling.

[0085] A "notification" is a message or alert that informs the recipient of important information or warnings.

[0086] MODE FOR CARRYING OUT THE INVENTION

[0087] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI models in particular. The system is primarily composed of three main components: a server, a terminal, and a user.

[0088] User registration and data acquisition

[0089] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to a server, which then stores the received information in a database. For example, if a user enters that they are a "20-year-old male with a mental health score of 5," this information is saved in the database.

[0090] Data collection

[0091] The device periodically monitors the user's social networking service posts and search history and sends this data to a server. The data is sent at specific time intervals during the collection process, for example, every hour. The server stores this data in temporary storage and prepares it for the necessary analysis. The hardware used is a typical smartphone (iPhone (registered trademark), ANDROID (registered trademark)), and the server uses a cloud service such as AWS (registered trademark) (Amazon Web Services) or Google (registered trademark).

[0092] Data analysis and anomaly detection

[0093] The server extracts the data from temporary storage and requests analysis from a generative AI model. The generative AI model analyzes the data using specific dangerous keywords (e.g., phrases like "school is hard" or "I want to die"). The generative AI model uses the latest machine learning models such as GPT-4 (registered trademark).

[0094] Send a support message

[0095] If the generative AI model detects an abnormality, the server sends a prompt to the model, which generates an appropriate support message. For example, a support message such as "Are you OK? We're here to help." The generated message is then sent to the user's smartphone via the server.

[0096] Risk Escalation and Specialized Support

[0097] If the generative AI model determines that the user is at high risk based on the analysis results, the server will send an SOS notification to a professional counselor. The counselor will receive this notification and contact the user directly to provide the necessary support. For example, if the risk level is high and the risk score is assessed as 8, the counselor will take appropriate action.

[0098] Specific examples

[0099] For example, a 20-year-old male user registers on a smartphone app with the name "Taro Yamada" and a mental health score of 5, and posts on social media that "school is tough." The device collects this information and sends it to a server. The server uses a generative AI model to analyze the post and determine that it is a dangerous situation. The prompt text is entered as "If you are feeling tough at school, what kind of support message would be appropriate?", and a message such as "Are you OK? We can talk to you" is generated. If the risk is high, a counselor is contacted and direct support is provided to the user.

[0100] Prompt Sentence Examples

[0101] "A 20-year-old man posted on social media that school is tough. What message of support should I send him?"

[0102] By utilizing generative AI models, this counseling system is able to detect anomalies and respond quickly 24 hours a day, providing effective support for suicide prevention.

[0103] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0104] Step 1:

[0105] A user downloads a smartphone app.

[0106] Users download and install apps from the app store by operating the smartphone interface, searching for the app, and pressing the download button.

[0107] Step 2:

[0108] The user inputs personal information and health check results.

[0109] Users launch the app and enter their personal information, such as their name, age, gender, and mental health score, which is then stored on their smartphone.

[0110] Step 3:

[0111] The terminal transmits the input data to the server.

[0112] The device encrypts the data using the SSL / TLS protocol and sends it to the server. The server stores the received data in a database. During this process, encryption is used to protect the security of the data. The input is the user's personal information, and the output is the data stored on the server.

[0113] Step 4:

[0114] The terminal periodically collects the user's social networking service postings and search history.

[0115] Data collection is performed automatically every hour. The device accesses the SNS API to obtain post content and search history. The input is SNS post and search history data, and the output is this data sent to the server.

[0116] Step 5:

[0117] The terminal transmits the collected data to the server.

[0118] The collected data is sent in real time to the server, which stores it in temporary storage and prepares it for later analysis. The input is the data collected by the device, and the output is the data stored in the server's temporary storage.

[0119] Step 6:

[0120] The server provides the collected data to a generative AI model that is responsible for data analysis.

[0121] The server extracts data from temporary storage and sends it to the generative AI model, which analyzes specific risk keywords and detects anomalies. The input is the data extracted from the server's storage, and the output is the analysis result of the generative AI model.

[0122] Step 7:

[0123] A generative AI model analyzes the data and detects anomalies.

[0124] The generative AI model analyzes data based on a list of dangerous keywords and detects abnormal patterns. For example, it detects keywords such as "I want to die" or "I want to disappear." The input is the collected data, and the output is the results of anomaly detection.

[0125] Step 8:

[0126] The server receives the analysis results from the generative AI model.

[0127] The server receives the analysis results from the generative AI model and prepares to execute the next action if an anomaly is detected. The input is the analysis results of the generative AI model, and the output is the anomaly analysis results stored on the server.

[0128] Step 9:

[0129] The server sends a prompt to the generative AI model based on the analysis results.

[0130] The server sends the prompt to the generative AI model, which then generates an appropriate support message. For example, the server sends the prompt, "A 20-year-old man posted on social media that 'school is tough.' What kind of support message should I send him?" The input is the anomaly detection result, and the output is the support message generated by the generative AI model.

[0131] Step 10:

[0132] A generative AI model generates support messages.

[0133] The generative AI model generates an appropriate support message based on the prompt sentence. For example, it generates a message like, "Are you okay? We're here to help you." The input is the prompt sentence, and the output is the support message.

[0134] Step 11:

[0135] The server sends the generated support message to the user's terminal.

[0136] The server sends the support message received from the generative AI model to the user's device. The input is the generated support message, and the output is the message displayed on the user's device.

[0137] Step 12:

[0138] The generative AI model assesses risk and takes action if it determines it is high risk.

[0139] The server receives the analysis results that the generative AI model judges to be high-risk and sends an SOS notification to a professional counselor. The input is the high-risk analysis result, and the output is a notification to the counselor.

[0140] Step 13:

[0141] Counsellors will contact users directly to provide professional support.

[0142] Based on the notification received from the server, the counselor contacts the user by phone or email and provides the necessary support. The input is the SOS notification, and the output is the professional support the user receives.

[0143] (Application example 1)

[0144] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0145] Suicide among young people is a serious social problem, and there is a need to detect psychological problems early and provide appropriate support. However, in many cases, these problems tend to be overlooked and progress without the individual or those around them noticing. Furthermore, there is a lack of means to monitor changes in their psychological state and behavior in real time and respond immediately. The present invention solves this problem.

[0146] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0147] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social media posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when the abnormality is difficult to resolve or the risk is high, means for collecting data via a device to monitor the user's behavior and comments in real time, means for analyzing the collected data in real time with artificial intelligence to detect abnormalities, and means for instantly generating and notifying prompt messages based on the collected and analyzed data. This makes it possible to monitor changes in the user's psychological state and behavior in real time and provide prompt and appropriate support when an abnormality is detected.

[0148] "User" refers to an individual using this system.

[0149] "Personal information" refers to information that can identify an individual, such as a user's name, age, or gender.

[0150] "Physical examination results" refers to the result data of a medical examination that the user has taken in the past.

[0151] "SNS posts" refer to messages or comments posted by users on social networking services.

[0152] "Search history" refers to a record of searches a user has conducted on the Internet.

[0153] "Specific risk keywords" refer to words or phrases that may indicate risk when monitoring a user's psychological state or behavior.

[0154] "Means for detecting anomalies" refers to technology that analyzes specific risk keywords from collected data and determines whether a user is at risk.

[0155] "Appropriate support messages" refer to messages of encouragement and support that the system generates depending on the user's condition.

[0156] An "expert" refers to a person, such as a psychological counselor or psychiatrist, who has specialized knowledge about the user's psychological state and behavior and can provide support.

[0157] "Real-time monitoring" refers to the immediate monitoring of user actions and comments.

[0158] "Device" refers to equipment that can collect user behavior and statements, such as smart glasses or smartphones.

[0159] "Generative AI" refers to algorithms that analyze collected data and automatically generate response messages, warnings, etc.

[0160] A "prompt sentence" refers to an instruction sentence or message generated to prompt a user to take an appropriate action.

[0161] MODE FOR CARRYING OUT THE INVENTION

[0162] This invention is a counseling system aimed at preventing suicide among young people, and in particular utilizes generative AI. This system is mainly composed of three main components: a server, a terminal, and a user. Specific embodiments of this system are described below.

[0163] User registration and data acquisition

[0164] Users access the system through devices such as smartphones or smart glasses and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which stores it in a database. For example, if a user registers as a 20-year-old male named "Taro Yamada" and enters that their mental health score is 5, this information will be saved in the database.

[0165] Data collection and real-time monitoring

[0166] The device periodically collects information about the user's daily activities, social media posts, search history, etc. It also uses devices such as smart glasses to monitor the user's facial expressions and comments in real time, making it possible to instantly detect changes in the user's psychological state and behavior.

[0167] Anomaly detection

[0168] The collected data is sent to a server where it is analyzed by the AI ​​generator. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the AI ​​generator will analyze it and detect certain dangerous keywords. Similarly, if a user mutters to themselves through the smart glasses, "I have no motivation to do anything anymore," the voice data will be instantly analyzed and deemed abnormal.

[0169] Support message generation and notification

[0170] If an abnormality is detected, the AI ​​generates an appropriate support message and sends it to the device via the server. For example, a prompt such as "Are you OK? Would you like to talk for a moment?" is displayed to the user, allowing the user to receive immediate support.

[0171] Escalation and Expert Notification

[0172] If it is difficult to respond or if the risk is deemed high, the generative AI will automatically notify experts (psychological counselors or psychiatrists) within the server. For example, if the risk level is high, the server will notify the experts in real time, and the experts will contact the user directly to provide support. This process enables a quick and accurate response.

[0173] Hardware and software used

[0174] Hardware:

[0175] Smart glasses (e.g., Google Glass (registered trademark), Vuzix)

[0176] Smartphone

[0177] Internet connection

[0178] software:

[0179] Generative AI (e.g., OpenAI (registered trademark) GPT-4, Google AI)

[0180] Voice recognition systems (e.g., Google Speech-to-Text)

[0181] Facial expression analysis software (e.g., Microsoft® Face API)

[0182] Examples of prompt statements

[0183] If the user says "Everything is painful", generate the following prompt:

[0184] A user says, "Everything is hard." Generate an appropriate support message for this statement.

[0185] In this way, the system monitors the user's psychological state and behavior in real time and provides support at the appropriate time, providing an effective counseling system aimed at preventing suicide among young people.

[0186] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0187] Step 1:

[0188] Users access the system using a smartphone or smart glasses and enter their personal information (name, age, gender, etc.) and health check results.

[0189] Input: Personal information, health check results

[0190] Output: Data sent to the server

[0191] Specific operation: The user launches the dedicated application on the device, follows the instructions to enter information into the form, and presses the submit button to send the information to the server.

[0192] Step 2:

[0193] The device periodically collects the user's SNS posts and search history and sends them to the server.

[0194] Input: Social media posts, search history

[0195] Output: Data sent to the server

[0196] Specific operation: A background program on the device checks the user's social media accounts and browser history every hour and automatically sends any new data to the server.

[0197] Step 3:

[0198] The server collects data from devices such as smart glasses to monitor users' actions and comments in real time.

[0199] Input: Real-time behavioral data, voice data

[0200] Output: Data sent to the server

[0201] Specific operation: The smart glasses' camera and microphone constantly capture data and stream it to the server.

[0202] Step 4:

[0203] The server analyzes the collected data using generative AI to detect specific dangerous keywords and abnormal behavior.

[0204] Input: Personal information, health check results, social media posts, search history, real-time behavioral data, voice data

[0205] Output: Analysis result (normal / abnormal)

[0206] Specific operation: The generative AI running on the server comprehensively analyzes all data, identifies dangerous keywords and abnormal patterns, and records the analysis results in a database.

[0207] Step 5:

[0208] If an abnormality is detected, the generation AI generates an appropriate support message and notifies the user's device via the server.

[0209] Input: Analysis result (abnormal)

[0210] Output: Support message to user terminal

[0211] Specific operation: The generative AI generates a prompt based on the analysis results and immediately notifies the user on their smart glasses or smartphone, displaying a pop-up message.

[0212] Step 6:

[0213] If the situation is difficult or the risk is high, the server will automatically notify experts and provide real-time support.

[0214] Input: Analysis results (high risk)

[0215] Output:Notify Expert

[0216] Specific operation: The server determines the risk level and automatically notifies a counselor or psychiatrist if necessary. The expert then contacts the user directly to provide support.

[0217] This enables the system to monitor the user's psychological state and behavior in real time and provide support at the appropriate time.

[0218] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0219] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: a server, a terminal, and a user.

[0220] overview

[0221] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor to provide more specialized support.

[0222] Specific examples of processing

[0223] User registration and data acquisition

[0224] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0225] Anomaly detection

[0226] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, where the generation AI analyzes specific dangerous keywords. The emotion engine also analyzes the user's posts, search history, and voice and facial expression data to recognize the user's emotional state. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects changes in emotion from the post content and provides that information to the generation AI.

[0227] Active Support Starts

[0228] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0229] Escalation and Human Support

[0230] If the situation is deemed difficult to deal with or the risk is high, the generating AI will send an SOS notification to the server, which will then notify a professional counselor. For example, if the emotion engine's analysis determines the risk level to be 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0231] How the Emotional Engine Works

[0232] The emotion engine analyzes the user's voice, facial expressions, and text data. For example, if a user says through the app, "I haven't been able to sleep lately," the emotion engine analyzes the tone of the voice and facial expressions to detect signs of stress or anxiety. Similarly, if a user frequently tweets negative phrases on social media, such as "I want to die" or "I'm so tired," the emotion engine can recognize their emotions from the text data.

[0233] By combining generative AI and an emotion engine, this system can more accurately grasp the user's psychological state, enabling 24-hour anomaly detection and support. When an anomaly is detected, appropriate messages and countermeasures are immediately displayed, and human support is also provided if necessary.

[0234] In this way, the present invention provides a more advanced and effective counseling system for preventing suicide among young people.

[0235] The processing flow will be explained below.

[0236] Step 1:

[0237] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0238] Step 2:

[0239] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0240] Step 3:

[0241] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0242] Step 4:

[0243] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0244] Step 5:

[0245] The server's generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0246] Step 6:

[0247] The device collects voice data from the user, and when the user speaks to the app, the device sends the voice data to the server.

[0248] Step 7:

[0249] The server receives the voice data and the emotion engine analyzes it to recognize the user's emotional state from the tone of the voice and the choice of words.

[0250] Step 8:

[0251] The emotion engine on the server uses facial recognition technology to analyze the user's facial expressions. If the user is using a camera, the device sends image data to the server, which then analyzes the facial expressions.

[0252] Step 9:

[0253] The emotion engine feeds back the results of its analysis to the generative AI, which then uses the feedback from the emotion engine to further detect anomalies.

[0254] Step 10:

[0255] The server's generation AI receives the "anomaly detected" flag and generates an appropriate support message as needed. The server then sends the message to the device.

[0256] Step 11:

[0257] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0258] Step 12:

[0259] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0260] Step 13:

[0261] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0262] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0263] Example 2

[0264] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0265] The problem that this invention aims to solve is to accurately grasp the user's psychological state and provide immediate and appropriate support in an advanced counseling system aimed at preventing suicide among young people. Current systems are unable to fully analyze the user's emotional state, and there is a risk that abnormalities will be overlooked. Another problem is the lack of a means to respond quickly when expert support is needed.

[0266] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for analyzing specific risky keywords from the collected data and analyzing the emotional state using an emotion engine to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when it is difficult to respond or the risk is high. This makes it possible to analyze the collected data and the analysis results of the emotion engine using a generative artificial intelligence model, and when an abnormality is detected, the generative artificial intelligence model can generate an appropriate support message and notify the user.

[0267] "Personal information" refers to information that can individually identify a user, such as the user's name, age, gender, address, and contact details.

[0268] "Medical checkup results" are data indicating the user's health condition, and include results obtained from a medical checkup conducted at a medical institution.

[0269] "Social networking service posts" are information such as text, images, and videos that users publish and share on social networking services (SNS).

[0270] "Search History" is the history of search queries made by a user using an internet search engine.

[0271] "Dangerous keywords" are specific words that are judged to indicate an abnormality in the user's psychological state or behavior, and include negative expressions such as "I want to die" and "It's painful."

[0272] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, and text data to recognize their emotional state (for example, joy, sadness, anger, etc.).

[0273] "Abnormal" refers to a situation that is different from the normal psychological state of the user, and particularly includes risky behavior and serious changes in mental state.

[0274] A "support message" is a message for assistance provided to a user when an abnormality is detected, and includes, for example, content such as "Are you OK? Please talk to us."

[0275] An "expert" is a professional who can respond to users' psychological and mental problems, such as a counselor or doctor with specialized knowledge and experience in psychology or psychiatry.

[0276] A "generative artificial intelligence model" is an artificial intelligence technology that analyzes collected data and performs specific tasks (such as detecting anomalies or generating support messages).

[0277] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: the user, the terminal, and the server.

[0278] Overall structure

[0279] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if it is deemed difficult to respond or high risk, the generative AI will notify an expert, who will provide more specialized support.

[0280] Hardware and Software Configuration

[0281] Device: The user's smartphone or computer, on which the smartphone application is installed.

[0282] Server: Use a cloud server or on-premise server to run a database management system (e.g. MySQL (registered trademark)), generative AI models (e.g. GPT series), and sentiment engines (e.g. Amazon Comprehend from AWS or Sentiment Analysis from Google Cloud).

[0283] Database: Stores users' personal information, health check results, collected SNS posts, and search history.

[0284] Program processing

[0285] The device sends personal information and health check results entered by the user to a server. The server receives this information and stores it in a database. The device then periodically collects the user's social media posts and search history and sends them to the server. Within the server, this data is analyzed by the generative AI and emotion engine. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects this change in emotion and provides that information to the generative AI.

[0286] The generating AI detects anomalies based on the analysis results, and if an anomaly is detected, it generates a support message such as "Are you OK? We can help you," and sends it to the user's device via the server. Furthermore, if the risk is deemed high, the generating AI sends an SOS notification to an expert via the server. The expert receives this notification and contacts the user directly to provide professional support.

[0287] Specific examples

[0288] If a user types "School has been tough lately and I can't sleep" into the app as "Kenji Suzuki," the emotion engine analyzes the text data and detects signs of stress or anxiety. As a result, the generative AI generates a message saying, "It seems like things are going to be tough at school. Why don't you try counseling?" and sends it to the user's device. The user can receive this message and receive support as needed.

[0289] Prompt Sentence Examples

[0290] "Analyze the text 'I feel like dying' posted by a user on social media and generate an appropriate support message."

[0291] "Analyze user voice data to detect signs of stress and anxiety."

[0292] "Save user registration information and health check results in a database."

[0293] This system combines generative AI and an emotion engine to accurately and quickly grasp the user's psychological state, and is capable of detecting anomalies and providing support 24 hours a day. When an anomaly is detected, appropriate messages and countermeasures are immediately presented, and expert support is also provided as needed, providing a more effective counseling system.

[0294] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0295] Step 1: User registration and data submission

[0296] Description: The user downloads a smartphone app and enters personal information (such as name, age, and gender) and health checkup results on the app's registration screen.

[0297] Specific behavior:

[0298] Input: The user enters their name, age, gender, and health check results into the app.

[0299] Data processing: The device converts the input information into an appropriate format.

[0300] Output: The device sends data to the server.

[0301] Server: Stores the received data in a database. For example, if a user enters "Taro Yamada," "20-year-old male," and "mental health score 5," this information will be saved in the database.

[0302] Step 2: Collect social media posts and search history

[0303] Description: The device periodically collects the user's social media posts and search history.

[0304] Specific behavior:

[0305] Input: The device retrieves the user's social media icon and search query.

[0306] Data collection: The device uses social media APIs to obtain post content and search history using search engine APIs.

[0307] Output: Send the collected data to the server.

[0308] Server: Stores received SNS posts and search history in an analytical database. This data collection is performed automatically in the background once a day.

[0309] Step 3: Data analysis and anomaly detection

[0310] Description: The server's generative AI model and emotion engine analyze the user's emotional state from collected data and detect anomalies.

[0311] Specific behavior:

[0312] Input: Collected social media posts, search history data, voice data, and facial expression data.

[0313] Data analysis: Generative AI detects dangerous keywords through text analysis, and the emotion engine analyzes psychological states from voice and facial expressions.

[0314] Output: Report anomaly detection. For example, if a user posts "I want to die" and the voice has a low tone, the generative AI and emotion engine will determine this as an anomaly.

[0315] Step 4: Send a support message

[0316] Description: If an abnormality is detected, the server's generation AI will generate an appropriate support message and notify the user.

[0317] Specific behavior:

[0318] Input: Data of abnormal presentation.

[0319] Message generation: The generation AI generates a support message for the user.

[0320] Output: The generated support message.

[0321] Server: Sends a message to the user's device. For example, generate a message saying "Are you okay? We're here to help you." and send it as a push notification to the device.

[0322] Step 5: Escalation and Specialized Support

[0323] Description: If the risk is deemed high, the server-generated AI will send an SOS notification to an expert.

[0324] Specific behavior:

[0325] Input: Sentiment engine analysis results and risk assessment.

[0326] Risk assessment: Generative AI assesses the risk level and quantifies the danger.

[0327] Output: SOS notification to the expert.

[0328] Server: If the risk level is high, a notification is sent to a counselor, who will contact the user and provide professional support. For example, if the risk level is determined to be 8, the server automatically notifies a counselor, who will provide support via phone or video chat.

[0329] (Application example 2)

[0330] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0331] Conventional counseling systems have difficulty accurately grasping a user's psychological state, making it difficult to detect abnormalities early and provide appropriate support. In particular, to prevent suicide among young people, advanced analytical technology that can detect subtle abnormalities that appear in social media posts and search history is needed. There is also a need for a system that can grasp a user's psychological state through the usage history of online sales systems and respond quickly.

[0332] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0333] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's SNS posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when it is difficult to respond or when the risk is high, means for collecting the usage history of the online sales system and analyzing the user's psychological state, and means for monitoring the user's psychological state in real time using an emotion engine. This makes it possible to more accurately grasp the user's psychological state, detect abnormalities early, and provide appropriate support.

[0334] "Personal information" refers to information that identifies an individual, such as name, age, and gender.

[0335] "Medical examination results" are medical information based on the medical examinations that the user has undergone, and are data that indicate the user's health condition.

[0336] "SNS posts" are content such as text, images, and videos that users post to social networking services.

[0337] "Search history" is a record of searches a user has conducted on an Internet search engine.

[0338] "Danger keywords" are specific words or phrases that indicate suicide or serious mental illness.

[0339] A "support message" is a message sent to support the user's psychological state.

[0340] An "expert" is a professional with advanced knowledge and experience in psychological counseling and mental health.

[0341] An "online sales system" is an electronic commerce system that sells products and services over the Internet.

[0342] "Usage history" is a record of purchases and browsing made by a user in the online sales system.

[0343] An "emotion engine" is software or a system for analyzing emotions from a user's text, voice, facial expressions, etc.

[0344] "Real-time monitoring" means constantly and instantly monitoring the user's psychological state.

[0345] This invention is an advanced counseling system that monitors the user's psychological state and provides support at the appropriate time. The system is mainly composed of three main components: a server, a terminal, and a user.

[0346] User registration and data acquisition

[0347] First, users install the smartphone app and create an account. Through the app, users enter personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This information is sent from the device to the server, which then stores it in a database.

[0348] Collection of social media posts and search history

[0349] The device periodically collects the user's social media posts and search history and sends them to a server. All collected data is stored in the server's database. The server uses this data to analyze the user's psychological state in real time.

[0350] Detecting anomalies and sending support messages

[0351] The server analyzes the collected data using a generation AI. The generation AI analyzes specific risky keywords, and an emotion engine evaluates the user's emotional state based on social media posts and search history. If an abnormality is detected, the generation AI generates an appropriate support message and sends it to the user's device via the server.

[0352] For example, if a user posts on social media, "I'm tired" or "Everything seems pointless," the emotion engine analyzes the post and detects negative emotions. The generative AI then generates a support message saying, "Are you okay? We're here to help," and sends it to the user.

[0353] Escalation and human support coordination

[0354] If an abnormality is detected and a high risk is deemed to exist, the generating AI will send an SOS notification to the server, which will then notify experts (psychological counselors and mental health professionals) who will then contact the user directly to provide support.

[0355] Hardware and Software Use

[0356] Hardware: smartphones, servers, databases

[0357] Software: Application frameworks (e.g., React Native), generative AI (e.g., OpenAI's GPT model), sentiment analysis engines (e.g., IBM Watson®)

[0358] The generative AI model operates by inputting a prompt sentence. An example of a prompt sentence is shown below.

[0359] Example prompt sentence:

[0360] "Analyze the user's recent emotional state from their social media posting history, detect negative keywords, and generate supportive messages."

[0361] This system will enable constant monitoring of the user's psychological state, detect abnormalities early, and provide support, which is expected to help prevent suicide and maintain psychological health among young people.

[0362] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0363] Step 1:

[0364] The user installs the smartphone app and creates an account. The user enters personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This data is sent from the device to the server, which stores it in a database. The input data is in text format and is saved as output in the database. Specifically, the information entered by the user, such as "Taro Yamada," "20 years old," and "male," is registered in the database.

[0365] Step 2:

[0366] The device periodically collects the user's SNS posts and search history and sends them to the server. The collected data is stored in the server's database. The input data is a text record of the user's SNS posts and search history, and is stored in the server's database as output. Specifically, the content of posts made by the user on SNS such as "School is hard" is periodically collected and sent to the server.

[0367] Step 3:

[0368] The server analyzes the collected data using a generative AI model. Input data includes the user's social media posts, search history, and health checkup results, and specific dangerous keywords are detected through text analysis using the generative AI model. The result of this analysis is the user's emotional state. Specifically, the analysis is performed by inputting the prompt statement "Analyze the user's recent emotional state from their social media posting history and detect negative keywords" into the generative AI.

[0369] Step 4:

[0370] If an abnormality is detected, an appropriate support message is generated using a generative AI model. The input data is the analyzed emotional state, and an automatically generated support message is output. This generated support message is sent from the server to the user's device. Specifically, if a negative emotion is detected, a message is generated saying, "Are you okay? We're here to help you," and sent to the user.

[0371] Step 5:

[0372] If the risk is high, the generative AI model sends an SOS notification to the server. The input data is the emotion analysis results and risk assessment results, and the output is an SOS notification sent to an expert. The server receives this notification and contacts a psychological counselor or mental health professional. Specifically, if the risk level is determined to be high, a notification is sent to the counselor saying, "Contact an expert for support."

[0373] As a result, it is possible to monitor the user's psychological state in real time and provide appropriate support promptly when an abnormality is detected.

[0374] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0375] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (registered trademark) (Internet search engine).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0376] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0377] [Second embodiment]

[0378] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0379] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0380] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0381] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0382] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0383] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0384] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0385] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0386] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0387] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0388] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0389] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0390] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI (generative artificial intelligence). The system is mainly composed of three main components: a server, a terminal, and a user.

[0391] overview

[0392] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and, if it detects an abnormality, sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor, who will provide more specialized support.

[0393] Specific examples of processing

[0394] User registration and data acquisition

[0395] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0396] Anomaly detection

[0397] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, and the AI ​​analyzes specific dangerous keywords. For example, if a user posts on social media "School is hard" or "I feel like I want to die," the AI ​​analyzes these posts and detects anomalies.

[0398] Active Support Starts

[0399] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0400] Escalation and Human Support

[0401] If the AI ​​determines that the situation is difficult to address or that the risk is high, it will send an SOS notification to the server, which will then notify a professional counselor. For example, if the risk level is 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0402] This system uses generative AI to detect anomalies and provide support 24 hours a day, providing an environment where users can consult at any time. It also allows for on-site support by professional counselors, allowing for more appropriate support to be provided to users.

[0403] In this way, the present invention provides an effective counseling system aimed at preventing suicide among young people.

[0404] The processing flow will be explained below.

[0405] Step 1:

[0406] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0407] Step 2:

[0408] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0409] Step 3:

[0410] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0411] Step 4:

[0412] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0413] Step 5:

[0414] The generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0415] Step 6:

[0416] The server receives the "anomaly detected" flag from the generation AI and starts active support. The generation AI generates an appropriate support message (e.g., "Are you okay? We're here to help you."), and the server sends it to the user's device.

[0417] Step 7:

[0418] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0419] Step 8:

[0420] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0421] Step 9:

[0422] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0423] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0424] Example 1

[0425] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0426] In recent years, the suicide rate among young people has been increasing, making it an urgent task to detect abnormalities early and provide appropriate support. In particular, there is a need for a method to detect early signs of suicide from posts and search history on social networking services and provide professional support. However, existing systems are insufficient in collecting and analyzing data, making it difficult to respond in real time.

[0427] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0428] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for encrypting the collected data and transmitting it to the server, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for sending an appropriate prompt sentence to the generative AI model based on the analysis results, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when response is difficult or risk is high. This makes it possible to detect abnormalities in real time and provide appropriate support promptly while ensuring the safety of the collected data.

[0429] "Personal information" refers to information that can be used to individually identify a user, such as the user's name, age, gender, address, and contact details.

[0430] "Physical examination results" refers to data relating to the health condition of a user, such as blood pressure, body temperature, and blood test results, obtained when the user undergoes a medical examination.

[0431] A "social networking service" is an online platform that enables users to share information and communicate with other users.

[0432] "Search history" is a record of keywords or phrases that a user searches for on an Internet search engine.

[0433] "Data encryption" is a technology that codes transmitted data using a specific algorithm to protect it from unauthorized access.

[0434] A "generative AI model" is an artificial intelligence system that has been trained to perform a specific task using machine learning techniques.

[0435] A "prompt sentence" is a sentence that serves as input to a generative AI model, such as an instruction or question.

[0436] A "support message" is a message that is provided to the user and contains comforting words or a message that encourages action.

[0437] An "expert" is a professional with advanced knowledge and experience in the fields of psychology and counseling.

[0438] A "notification" is a message or alert that informs the recipient of important information or warnings.

[0439] MODE FOR CARRYING OUT THE INVENTION

[0440] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI models in particular. The system is primarily composed of three main components: a server, a terminal, and a user.

[0441] User registration and data acquisition

[0442] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to a server, which then stores the received information in a database. For example, if a user enters that they are a "20-year-old male with a mental health score of 5," this information is saved in the database.

[0443] Data collection

[0444] The device periodically monitors the user's social networking service posts and search history, and sends this data to a server. The data is sent at specific time intervals during the collection process, for example, every hour. The server stores this data in temporary storage and prepares it for the necessary analysis. The hardware used is a standard smartphone (iPhone, Android), and the server uses cloud services such as AWS (Amazon Web Services) and Google Cloud.

[0445] Data analysis and anomaly detection

[0446] The server extracts the data from temporary storage and requests analysis from a generative AI model. The generative AI model analyzes the data using specific dangerous keywords (e.g., phrases like "school is hard" or "I want to die"). The generative AI model uses the latest machine learning models such as GPT-4.

[0447] Send a support message

[0448] If the generative AI model detects an abnormality, the server sends a prompt to the model, which generates an appropriate support message. For example, a support message such as "Are you OK? We're here to help." The generated message is then sent to the user's smartphone via the server.

[0449] Risk Escalation and Specialized Support

[0450] If the generative AI model determines that the user is at high risk based on the analysis results, the server will send an SOS notification to a professional counselor. The counselor will receive this notification and contact the user directly to provide the necessary support. For example, if the risk level is high and the risk score is assessed as 8, the counselor will take appropriate action.

[0451] Specific examples

[0452] For example, a 20-year-old male user registers on a smartphone app with the name "Taro Yamada" and a mental health score of 5, and posts on social media that "school is tough." The device collects this information and sends it to a server. The server uses a generative AI model to analyze the post and determine that it is a dangerous situation. The prompt text is entered as "If you are feeling tough at school, what kind of support message would be appropriate?", and a message such as "Are you OK? We can talk to you" is generated. If the risk is high, a counselor is contacted and direct support is provided to the user.

[0453] Prompt Sentence Examples

[0454] "A 20-year-old man posted on social media that school is tough. What message of support should I send him?"

[0455] By utilizing generative AI models, this counseling system is able to detect anomalies and respond quickly 24 hours a day, providing effective support for suicide prevention.

[0456] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0457] Step 1:

[0458] A user downloads a smartphone app.

[0459] Users download and install apps from the app store by operating the smartphone interface, searching for the app, and pressing the download button.

[0460] Step 2:

[0461] The user inputs personal information and health check results.

[0462] Users launch the app and enter their personal information, such as their name, age, gender, and mental health score, which is then stored on their smartphone.

[0463] Step 3:

[0464] The terminal transmits the input data to the server.

[0465] The device encrypts the data using the SSL / TLS protocol and sends it to the server. The server stores the received data in a database. During this process, encryption is used to protect the security of the data. The input is the user's personal information, and the output is the data stored on the server.

[0466] Step 4:

[0467] The terminal periodically collects the user's social networking service postings and search history.

[0468] Data collection is performed automatically every hour. The device accesses the SNS API to obtain post content and search history. The input is SNS post and search history data, and the output is this data sent to the server.

[0469] Step 5:

[0470] The terminal transmits the collected data to the server.

[0471] The collected data is sent in real time to the server, which stores it in temporary storage and prepares it for later analysis. The input is the data collected by the device, and the output is the data stored in the server's temporary storage.

[0472] Step 6:

[0473] The server provides the collected data to a generative AI model that is responsible for data analysis.

[0474] The server extracts data from temporary storage and sends it to the generative AI model, which analyzes specific risk keywords and detects anomalies. The input is the data extracted from the server's storage, and the output is the analysis result of the generative AI model.

[0475] Step 7:

[0476] A generative AI model analyzes the data and detects anomalies.

[0477] The generative AI model analyzes data based on a list of dangerous keywords and detects abnormal patterns. For example, it detects keywords such as "I want to die" or "I want to disappear." The input is the collected data, and the output is the results of anomaly detection.

[0478] Step 8:

[0479] The server receives the analysis results from the generative AI model.

[0480] The server receives the analysis results from the generative AI model and prepares to execute the next action if an anomaly is detected. The input is the analysis results of the generative AI model, and the output is the anomaly analysis results stored on the server.

[0481] Step 9:

[0482] The server sends a prompt to the generative AI model based on the analysis results.

[0483] The server sends the prompt to the generative AI model, which then generates an appropriate support message. For example, the server sends the prompt, "A 20-year-old man posted on social media that 'school is tough.' What kind of support message should I send him?" The input is the anomaly detection result, and the output is the support message generated by the generative AI model.

[0484] Step 10:

[0485] A generative AI model generates support messages.

[0486] The generative AI model generates an appropriate support message based on the prompt sentence. For example, it generates a message like, "Are you okay? We're here to help you." The input is the prompt sentence, and the output is the support message.

[0487] Step 11:

[0488] The server sends the generated support message to the user's terminal.

[0489] The server sends the support message received from the generative AI model to the user's device. The input is the generated support message, and the output is the message displayed on the user's device.

[0490] Step 12:

[0491] The generative AI model assesses risk and takes action if it determines it is high risk.

[0492] The server receives the analysis results that the generative AI model judges to be high-risk and sends an SOS notification to a professional counselor. The input is the high-risk analysis result, and the output is a notification to the counselor.

[0493] Step 13:

[0494] Counsellors will contact users directly to provide professional support.

[0495] Based on the notification received from the server, the counselor contacts the user by phone or email and provides the necessary support. The input is the SOS notification, and the output is the professional support the user receives.

[0496] (Application example 1)

[0497] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0498] Suicide among young people is a serious social problem, and there is a need to detect psychological problems early and provide appropriate support. However, in many cases, these problems tend to be overlooked and progress without the individual or those around them noticing. Furthermore, there is a lack of means to monitor changes in their psychological state and behavior in real time and respond immediately. The present invention solves this problem.

[0499] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0500] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social media posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when the abnormality is difficult to resolve or the risk is high, means for collecting data via a device to monitor the user's behavior and comments in real time, means for analyzing the collected data in real time with artificial intelligence to detect abnormalities, and means for instantly generating and notifying prompt messages based on the collected and analyzed data. This makes it possible to monitor changes in the user's psychological state and behavior in real time and provide prompt and appropriate support when an abnormality is detected.

[0501] "User" refers to an individual using this system.

[0502] "Personal information" refers to information that can identify an individual, such as a user's name, age, or gender.

[0503] "Physical examination results" refers to the result data of a medical examination that the user has taken in the past.

[0504] "SNS posts" refer to messages or comments posted by users on social networking services.

[0505] "Search history" refers to a record of searches a user has conducted on the Internet.

[0506] "Specific risk keywords" refer to words or phrases that may indicate risk when monitoring a user's psychological state or behavior.

[0507] "Means for detecting anomalies" refers to technology that analyzes specific risk keywords from collected data and determines whether a user is at risk.

[0508] "Appropriate support messages" refer to messages of encouragement and support that the system generates depending on the user's condition.

[0509] An "expert" refers to a person, such as a psychological counselor or psychiatrist, who has specialized knowledge about the user's psychological state and behavior and can provide support.

[0510] "Real-time monitoring" refers to the immediate monitoring of user actions and comments.

[0511] "Device" refers to equipment that can collect user behavior and statements, such as smart glasses or smartphones.

[0512] "Generative AI" refers to algorithms that analyze collected data and automatically generate response messages, warnings, etc.

[0513] A "prompt sentence" refers to an instruction sentence or message generated to prompt a user to take an appropriate action.

[0514] MODE FOR CARRYING OUT THE INVENTION

[0515] This invention is a counseling system aimed at preventing suicide among young people, and in particular utilizes generative AI. This system is mainly composed of three main components: a server, a terminal, and a user. Specific embodiments of this system are described below.

[0516] User registration and data acquisition

[0517] Users access the system through devices such as smartphones or smart glasses and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which stores it in a database. For example, if a user registers as a 20-year-old male named "Taro Yamada" and enters that their mental health score is 5, this information will be saved in the database.

[0518] Data collection and real-time monitoring

[0519] The device periodically collects information about the user's daily activities, social media posts, search history, etc. It also uses devices such as smart glasses to monitor the user's facial expressions and comments in real time, making it possible to instantly detect changes in the user's psychological state and behavior.

[0520] Anomaly detection

[0521] The collected data is sent to a server where it is analyzed by the AI ​​generator. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the AI ​​generator will analyze it and detect certain dangerous keywords. Similarly, if a user mutters to themselves through the smart glasses, "I have no motivation to do anything anymore," the voice data will be instantly analyzed and deemed abnormal.

[0522] Support message generation and notification

[0523] If an abnormality is detected, the AI ​​generates an appropriate support message and sends it to the device via the server. For example, a prompt such as "Are you OK? Would you like to talk for a moment?" is displayed to the user, allowing the user to receive immediate support.

[0524] Escalation and Expert Notification

[0525] If it is difficult to respond or if the risk is deemed high, the generative AI will automatically notify experts (psychological counselors or psychiatrists) within the server. For example, if the risk level is high, the server will notify the experts in real time, and the experts will contact the user directly to provide support. This process enables a quick and accurate response.

[0526] Hardware and software used

[0527] Hardware:

[0528] Smart glasses (e.g., Google Glass, Vuzix)

[0529] Smartphone

[0530] Internet connection

[0531] software:

[0532] Generative AI (e.g. OpenAI GPT-4, Google AI)

[0533] Voice recognition systems (e.g., Google Speech-to-Text)

[0534] Facial expression analysis software (e.g. Microsoft Face API)

[0535] Examples of prompt statements

[0536] If the user says "Everything is painful", generate the following prompt:

[0537] A user says, "Everything is hard." Generate an appropriate support message for this statement.

[0538] In this way, the system monitors the user's psychological state and behavior in real time and provides support at the appropriate time, providing an effective counseling system aimed at preventing suicide among young people.

[0539] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0540] Step 1:

[0541] Users access the system using a smartphone or smart glasses and enter their personal information (name, age, gender, etc.) and health check results.

[0542] Input: Personal information, health check results

[0543] Output: Data sent to the server

[0544] Specific operation: The user launches the dedicated application on the device, follows the instructions to enter information into the form, and presses the submit button to send the information to the server.

[0545] Step 2:

[0546] The device periodically collects the user's SNS posts and search history and sends them to the server.

[0547] Input: Social media posts, search history

[0548] Output: Data sent to the server

[0549] Specific operation: A background program on the device checks the user's social media accounts and browser history every hour and automatically sends any new data to the server.

[0550] Step 3:

[0551] The server collects data from devices such as smart glasses to monitor users' actions and comments in real time.

[0552] Input: Real-time behavioral data, voice data

[0553] Output: Data sent to the server

[0554] Specific operation: The smart glasses' camera and microphone constantly capture data and stream it to the server.

[0555] Step 4:

[0556] The server analyzes the collected data using generative AI to detect specific dangerous keywords and abnormal behavior.

[0557] Input: Personal information, health check results, social media posts, search history, real-time behavioral data, voice data

[0558] Output: Analysis result (normal / abnormal)

[0559] Specific operation: The generative AI running on the server comprehensively analyzes all data, identifies dangerous keywords and abnormal patterns, and records the analysis results in a database.

[0560] Step 5:

[0561] If an abnormality is detected, the generation AI generates an appropriate support message and notifies the user's device via the server.

[0562] Input: Analysis result (abnormal)

[0563] Output: Support message to user terminal

[0564] Specific operation: The generative AI generates a prompt based on the analysis results and immediately notifies the user on their smart glasses or smartphone, displaying a pop-up message.

[0565] Step 6:

[0566] If the situation is difficult or the risk is high, the server will automatically notify experts and provide real-time support.

[0567] Input: Analysis results (high risk)

[0568] Output:Notify Expert

[0569] Specific operation: The server determines the risk level and automatically notifies a counselor or psychiatrist if necessary. The expert then contacts the user directly to provide support.

[0570] This enables the system to monitor the user's psychological state and behavior in real time and provide support at the appropriate time.

[0571] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0572] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: a server, a terminal, and a user.

[0573] overview

[0574] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor to provide more specialized support.

[0575] Specific examples of processing

[0576] User registration and data acquisition

[0577] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0578] Anomaly detection

[0579] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, where the generation AI analyzes specific dangerous keywords. The emotion engine also analyzes the user's posts, search history, and voice and facial expression data to recognize the user's emotional state. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects changes in emotion from the post content and provides that information to the generation AI.

[0580] Active Support Starts

[0581] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0582] Escalation and Human Support

[0583] If the situation is deemed difficult to deal with or the risk is high, the generating AI will send an SOS notification to the server, which will then notify a professional counselor. For example, if the emotion engine's analysis determines the risk level to be 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0584] How the Emotional Engine Works

[0585] The emotion engine analyzes the user's voice, facial expressions, and text data. For example, if a user says through the app, "I haven't been able to sleep lately," the emotion engine analyzes the tone of the voice and facial expressions to detect signs of stress or anxiety. Similarly, if a user frequently tweets negative phrases on social media, such as "I want to die" or "I'm so tired," the emotion engine can recognize their emotions from the text data.

[0586] By combining generative AI and an emotion engine, this system can more accurately grasp the user's psychological state, enabling 24-hour anomaly detection and support. When an anomaly is detected, appropriate messages and countermeasures are immediately displayed, and human support is also provided if necessary.

[0587] In this way, the present invention provides a more advanced and effective counseling system for preventing suicide among young people.

[0588] The processing flow will be explained below.

[0589] Step 1:

[0590] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0591] Step 2:

[0592] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0593] Step 3:

[0594] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0595] Step 4:

[0596] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0597] Step 5:

[0598] The server's generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0599] Step 6:

[0600] The device collects voice data from the user, and when the user speaks to the app, the device sends the voice data to the server.

[0601] Step 7:

[0602] The server receives the voice data and the emotion engine analyzes it to recognize the user's emotional state from the tone of the voice and the choice of words.

[0603] Step 8:

[0604] The emotion engine on the server uses facial recognition technology to analyze the user's facial expressions. If the user is using a camera, the device sends image data to the server, which then analyzes the facial expressions.

[0605] Step 9:

[0606] The emotion engine feeds back the results of its analysis to the generative AI, which then uses the feedback from the emotion engine to further detect anomalies.

[0607] Step 10:

[0608] The server's generation AI receives the "anomaly detected" flag and generates an appropriate support message as needed. The server then sends the message to the device.

[0609] Step 11:

[0610] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0611] Step 12:

[0612] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0613] Step 13:

[0614] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0615] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0616] Example 2

[0617] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0618] The problem that this invention aims to solve is to accurately grasp the user's psychological state and provide immediate and appropriate support in an advanced counseling system aimed at preventing suicide among young people. Current systems are unable to fully analyze the user's emotional state, and there is a risk that abnormalities will be overlooked. Another problem is the lack of a means to respond quickly when expert support is needed.

[0619] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for analyzing specific risky keywords from the collected data and analyzing the emotional state using an emotion engine to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when it is difficult to respond or the risk is high. This makes it possible to analyze the collected data and the analysis results of the emotion engine using a generative artificial intelligence model, and when an abnormality is detected, the generative artificial intelligence model can generate an appropriate support message and notify the user.

[0620] "Personal information" refers to information that can individually identify a user, such as the user's name, age, gender, address, and contact details.

[0621] "Medical checkup results" are data indicating the user's health condition, and include results obtained from a medical checkup conducted at a medical institution.

[0622] "Social networking service posts" are information such as text, images, and videos that users publish and share on social networking services (SNS).

[0623] "Search History" is the history of search queries made by a user using an internet search engine.

[0624] "Dangerous keywords" are specific words that are judged to indicate an abnormality in the user's psychological state or behavior, and include negative expressions such as "I want to die" and "It's painful."

[0625] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, and text data to recognize their emotional state (for example, joy, sadness, anger, etc.).

[0626] "Abnormal" refers to a situation that is different from the normal psychological state of the user, and particularly includes risky behavior and serious changes in mental state.

[0627] A "support message" is a message for assistance provided to a user when an abnormality is detected, and includes, for example, content such as "Are you OK? Please talk to us."

[0628] An "expert" is a professional who can respond to users' psychological and mental problems, such as a counselor or doctor with specialized knowledge and experience in psychology or psychiatry.

[0629] A "generative artificial intelligence model" is an artificial intelligence technology that analyzes collected data and performs specific tasks (such as detecting anomalies or generating support messages).

[0630] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: the user, the terminal, and the server.

[0631] Overall structure

[0632] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if it is deemed difficult to respond or high risk, the generative AI will notify an expert, who will provide more specialized support.

[0633] Hardware and Software Configuration

[0634] Device: The user's smartphone or computer, on which the smartphone application is installed.

[0635] Server: Use a cloud or on-premise server to run a database management system (e.g. MySQL), generative AI models (e.g. GPT series), and sentiment engines (e.g. Amazon Comprehend on AWS or Sentiment Analysis on Google Cloud).

[0636] Database: Stores users' personal information, health check results, collected SNS posts, and search history.

[0637] Program processing

[0638] The device sends personal information and health check results entered by the user to a server. The server receives this information and stores it in a database. The device then periodically collects the user's social media posts and search history and sends them to the server. Within the server, this data is analyzed by the generative AI and emotion engine. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects this change in emotion and provides that information to the generative AI.

[0639] The generating AI detects anomalies based on the analysis results, and if an anomaly is detected, it generates a support message such as "Are you OK? We can help you," and sends it to the user's device via the server. Furthermore, if the risk is deemed high, the generating AI sends an SOS notification to an expert via the server. The expert receives this notification and contacts the user directly to provide professional support.

[0640] Specific examples

[0641] If a user types "School has been tough lately and I can't sleep" into the app as "Kenji Suzuki," the emotion engine analyzes the text data and detects signs of stress or anxiety. As a result, the generative AI generates a message saying, "It seems like things are going to be tough at school. Why don't you try counseling?" and sends it to the user's device. The user can receive this message and receive support as needed.

[0642] Prompt Sentence Examples

[0643] "Analyze the text 'I feel like dying' posted by a user on social media and generate an appropriate support message."

[0644] "Analyze user voice data to detect signs of stress and anxiety."

[0645] "Save user registration information and health check results in a database."

[0646] This system combines generative AI and an emotion engine to accurately and quickly grasp the user's psychological state, and is capable of detecting anomalies and providing support 24 hours a day. When an anomaly is detected, appropriate messages and countermeasures are immediately presented, and expert support is also provided as needed, providing a more effective counseling system.

[0647] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0648] Step 1: User registration and data submission

[0649] Description: The user downloads a smartphone app and enters personal information (such as name, age, and gender) and health checkup results on the app's registration screen.

[0650] Specific behavior:

[0651] Input: The user enters their name, age, gender, and health check results into the app.

[0652] Data processing: The device converts the input information into an appropriate format.

[0653] Output: The device sends data to the server.

[0654] Server: Stores the received data in a database. For example, if a user enters "Taro Yamada," "20-year-old male," and "mental health score 5," this information will be saved in the database.

[0655] Step 2: Collect social media posts and search history

[0656] Description: The device periodically collects the user's social media posts and search history.

[0657] Specific behavior:

[0658] Input: The device retrieves the user's social media icon and search query.

[0659] Data collection: The device uses social media APIs to obtain post content and search history using search engine APIs.

[0660] Output: Send the collected data to the server.

[0661] Server: Stores received SNS posts and search history in an analytical database. This data collection is performed automatically in the background once a day.

[0662] Step 3: Data analysis and anomaly detection

[0663] Description: The server's generative AI model and emotion engine analyze the user's emotional state from collected data and detect anomalies.

[0664] Specific behavior:

[0665] Input: Collected social media posts, search history data, voice data, and facial expression data.

[0666] Data analysis: Generative AI detects dangerous keywords through text analysis, and the emotion engine analyzes psychological states from voice and facial expressions.

[0667] Output: Report anomaly detection. For example, if a user posts "I want to die" and the voice has a low tone, the generative AI and emotion engine will determine this as an anomaly.

[0668] Step 4: Send a support message

[0669] Description: If an abnormality is detected, the server's generation AI will generate an appropriate support message and notify the user.

[0670] Specific behavior:

[0671] Input: Data of abnormal presentation.

[0672] Message generation: The generation AI generates a support message for the user.

[0673] Output: The generated support message.

[0674] Server: Sends a message to the user's device. For example, generate a message saying "Are you okay? We're here to help you." and send it as a push notification to the device.

[0675] Step 5: Escalation and Specialized Support

[0676] Description: If the risk is deemed high, the server-generated AI will send an SOS notification to an expert.

[0677] Specific behavior:

[0678] Input: Sentiment engine analysis results and risk assessment.

[0679] Risk assessment: Generative AI assesses the risk level and quantifies the danger.

[0680] Output: SOS notification to the expert.

[0681] Server: If the risk level is high, a notification is sent to a counselor, who will contact the user and provide professional support. For example, if the risk level is determined to be 8, the server automatically notifies a counselor, who will provide support via phone or video chat.

[0682] (Application example 2)

[0683] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0684] Conventional counseling systems have difficulty accurately grasping a user's psychological state, making it difficult to detect abnormalities early and provide appropriate support. In particular, to prevent suicide among young people, advanced analytical technology that can detect subtle abnormalities that appear in social media posts and search history is needed. There is also a need for a system that can grasp a user's psychological state through the usage history of online sales systems and respond quickly.

[0685] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0686] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's SNS posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when it is difficult to respond or when the risk is high, means for collecting the usage history of the online sales system and analyzing the user's psychological state, and means for monitoring the user's psychological state in real time using an emotion engine. This makes it possible to more accurately grasp the user's psychological state, detect abnormalities early, and provide appropriate support.

[0687] "Personal information" refers to information that identifies an individual, such as name, age, and gender.

[0688] "Medical examination results" are medical information based on the medical examinations that the user has undergone, and are data that indicate the user's health condition.

[0689] "SNS posts" are content such as text, images, and videos that users post to social networking services.

[0690] "Search history" is a record of searches a user has conducted on an Internet search engine.

[0691] "Danger keywords" are specific words or phrases that indicate suicide or serious mental illness.

[0692] A "support message" is a message sent to support the user's psychological state.

[0693] An "expert" is a professional with advanced knowledge and experience in psychological counseling and mental health.

[0694] An "online sales system" is an electronic commerce system that sells products and services over the Internet.

[0695] "Usage history" is a record of purchases and browsing made by a user in the online sales system.

[0696] An "emotion engine" is software or a system for analyzing emotions from a user's text, voice, facial expressions, etc.

[0697] "Real-time monitoring" means constantly and instantly monitoring the user's psychological state.

[0698] This invention is an advanced counseling system that monitors the user's psychological state and provides support at the appropriate time. The system is mainly composed of three main components: a server, a terminal, and a user.

[0699] User registration and data acquisition

[0700] First, users install the smartphone app and create an account. Through the app, users enter personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This information is sent from the device to the server, which then stores it in a database.

[0701] Collection of social media posts and search history

[0702] The device periodically collects the user's social media posts and search history and sends them to a server. All collected data is stored in the server's database. The server uses this data to analyze the user's psychological state in real time.

[0703] Detecting anomalies and sending support messages

[0704] The server analyzes the collected data using a generation AI. The generation AI analyzes specific risky keywords, and an emotion engine evaluates the user's emotional state based on social media posts and search history. If an abnormality is detected, the generation AI generates an appropriate support message and sends it to the user's device via the server.

[0705] For example, if a user posts on social media, "I'm tired" or "Everything seems pointless," the emotion engine analyzes the post and detects negative emotions. The generative AI then generates a support message saying, "Are you okay? We're here to help," and sends it to the user.

[0706] Escalation and human support coordination

[0707] If an abnormality is detected and a high risk is deemed to exist, the generating AI will send an SOS notification to the server, which will then notify experts (psychological counselors and mental health professionals) who will then contact the user directly to provide support.

[0708] Hardware and Software Use

[0709] Hardware: smartphones, servers, databases

[0710] Software: Application frameworks (e.g., React Native), generative AI (e.g., OpenAI's GPT model), sentiment analysis engines (e.g., IBM Watson)

[0711] The generative AI model operates by inputting a prompt sentence. An example of a prompt sentence is shown below.

[0712] Example prompt sentence:

[0713] "Analyze the user's recent emotional state from their social media posting history, detect negative keywords, and generate supportive messages."

[0714] This system will enable constant monitoring of the user's psychological state, detect abnormalities early, and provide support, which is expected to help prevent suicide and maintain psychological health among young people.

[0715] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0716] Step 1:

[0717] The user installs the smartphone app and creates an account. The user enters personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This data is sent from the device to the server, which stores it in a database. The input data is in text format and is saved as output in the database. Specifically, the information entered by the user, such as "Taro Yamada," "20 years old," and "male," is registered in the database.

[0718] Step 2:

[0719] The device periodically collects the user's SNS posts and search history and sends them to the server. The collected data is stored in the server's database. The input data is a text record of the user's SNS posts and search history, and is stored in the server's database as output. Specifically, the content of posts made by the user on SNS such as "School is hard" is periodically collected and sent to the server.

[0720] Step 3:

[0721] The server analyzes the collected data using a generative AI model. Input data includes the user's social media posts, search history, and health checkup results, and specific dangerous keywords are detected through text analysis using the generative AI model. The result of this analysis is the user's emotional state. Specifically, the analysis is performed by inputting the prompt statement "Analyze the user's recent emotional state from their social media posting history and detect negative keywords" into the generative AI.

[0722] Step 4:

[0723] If an abnormality is detected, an appropriate support message is generated using a generative AI model. The input data is the analyzed emotional state, and an automatically generated support message is output. This generated support message is sent from the server to the user's device. Specifically, if a negative emotion is detected, a message is generated saying, "Are you okay? We're here to help you," and sent to the user.

[0724] Step 5:

[0725] If the risk is high, the generative AI model sends an SOS notification to the server. The input data is the emotion analysis results and risk assessment results, and the output is an SOS notification sent to an expert. The server receives this notification and contacts a psychological counselor or mental health professional. Specifically, if the risk level is determined to be high, a notification is sent to the counselor saying, "Contact an expert for support."

[0726] As a result, it is possible to monitor the user's psychological state in real time and provide appropriate support promptly when an abnormality is detected.

[0727] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0728] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0729] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0730] [Third embodiment]

[0731] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0732] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0733] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0734] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0735] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0736] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0737] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0738] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0739] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0740] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0741] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0742] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0743] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI (generative artificial intelligence). The system is mainly composed of three main components: a server, a terminal, and a user.

[0744] overview

[0745] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and, if it detects an abnormality, sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor, who will provide more specialized support.

[0746] Specific examples of processing

[0747] User registration and data acquisition

[0748] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0749] Anomaly detection

[0750] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, and the AI ​​analyzes specific dangerous keywords. For example, if a user posts on social media "School is hard" or "I feel like I want to die," the AI ​​analyzes these posts and detects anomalies.

[0751] Active Support Starts

[0752] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0753] Escalation and Human Support

[0754] If the AI ​​determines that the situation is difficult to address or that the risk is high, it will send an SOS notification to the server, which will then notify a professional counselor. For example, if the risk level is 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0755] This system uses generative AI to detect anomalies and provide support 24 hours a day, providing an environment where users can consult at any time. It also allows for on-site support by professional counselors, allowing for more appropriate support to be provided to users.

[0756] In this way, the present invention provides an effective counseling system aimed at preventing suicide among young people.

[0757] The processing flow will be explained below.

[0758] Step 1:

[0759] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0760] Step 2:

[0761] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0762] Step 3:

[0763] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0764] Step 4:

[0765] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0766] Step 5:

[0767] The generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0768] Step 6:

[0769] The server receives the "anomaly detected" flag from the generation AI and starts active support. The generation AI generates an appropriate support message (e.g., "Are you okay? We're here to help you."), and the server sends it to the user's device.

[0770] Step 7:

[0771] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0772] Step 8:

[0773] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0774] Step 9:

[0775] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0776] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0777] Example 1

[0778] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0779] In recent years, the suicide rate among young people has been increasing, making it an urgent task to detect abnormalities early and provide appropriate support. In particular, there is a need for a method to detect early signs of suicide from posts and search history on social networking services and provide professional support. However, existing systems are insufficient in collecting and analyzing data, making it difficult to respond in real time.

[0780] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0781] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for encrypting the collected data and transmitting it to the server, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for sending an appropriate prompt sentence to the generative AI model based on the analysis results, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when response is difficult or risk is high. This makes it possible to detect abnormalities in real time and provide appropriate support promptly while ensuring the safety of the collected data.

[0782] "Personal information" refers to information that can be used to individually identify a user, such as the user's name, age, gender, address, and contact details.

[0783] "Physical examination results" refers to data relating to the health condition of a user, such as blood pressure, body temperature, and blood test results, obtained when the user undergoes a medical examination.

[0784] A "social networking service" is an online platform that enables users to share information and communicate with other users.

[0785] "Search history" is a record of keywords or phrases that a user searches for on an Internet search engine.

[0786] "Data encryption" is a technology that codes transmitted data using a specific algorithm to protect it from unauthorized access.

[0787] A "generative AI model" is an artificial intelligence system that has been trained to perform a specific task using machine learning techniques.

[0788] A "prompt sentence" is a sentence that serves as input to a generative AI model, such as an instruction or question.

[0789] A "support message" is a message that is provided to the user and contains comforting words or a message that encourages action.

[0790] An "expert" is a professional with advanced knowledge and experience in the fields of psychology and counseling.

[0791] A "notification" is a message or alert that informs the recipient of important information or warnings.

[0792] MODE FOR CARRYING OUT THE INVENTION

[0793] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI models in particular. The system is primarily composed of three main components: a server, a terminal, and a user.

[0794] User registration and data acquisition

[0795] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to a server, which then stores the received information in a database. For example, if a user enters that they are a "20-year-old male with a mental health score of 5," this information is saved in the database.

[0796] Data collection

[0797] The device periodically monitors the user's social networking service posts and search history, and sends this data to a server. The data is sent at specific time intervals during the collection process, for example, every hour. The server stores this data in temporary storage and prepares it for the necessary analysis. The hardware used is a standard smartphone (iPhone, Android), and the server uses cloud services such as AWS (Amazon Web Services) and Google Cloud.

[0798] Data analysis and anomaly detection

[0799] The server extracts the data from temporary storage and requests analysis from a generative AI model. The generative AI model analyzes the data using specific dangerous keywords (e.g., phrases like "school is hard" or "I want to die"). The generative AI model uses the latest machine learning models such as GPT-4.

[0800] Send a support message

[0801] If the generative AI model detects an abnormality, the server sends a prompt to the model, which generates an appropriate support message. For example, a support message such as "Are you OK? We're here to help." The generated message is then sent to the user's smartphone via the server.

[0802] Risk Escalation and Specialized Support

[0803] If the generative AI model determines that the user is at high risk based on the analysis results, the server will send an SOS notification to a professional counselor. The counselor will receive this notification and contact the user directly to provide the necessary support. For example, if the risk level is high and the risk score is assessed as 8, the counselor will take appropriate action.

[0804] Specific examples

[0805] For example, a 20-year-old male user registers on a smartphone app with the name "Taro Yamada" and a mental health score of 5, and posts on social media that "school is tough." The device collects this information and sends it to a server. The server uses a generative AI model to analyze the post and determine that it is a dangerous situation. The prompt text is entered as "If you are feeling tough at school, what kind of support message would be appropriate?", and a message such as "Are you OK? We can talk to you" is generated. If the risk is high, a counselor is contacted and direct support is provided to the user.

[0806] Prompt Sentence Examples

[0807] "A 20-year-old man posted on social media that school is tough. What message of support should I send him?"

[0808] By utilizing generative AI models, this counseling system is able to detect anomalies and respond quickly 24 hours a day, providing effective support for suicide prevention.

[0809] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0810] Step 1:

[0811] A user downloads a smartphone app.

[0812] Users download and install apps from the app store by operating the smartphone interface, searching for the app, and pressing the download button.

[0813] Step 2:

[0814] The user inputs personal information and health check results.

[0815] Users launch the app and enter their personal information, such as their name, age, gender, and mental health score, which is then stored on their smartphone.

[0816] Step 3:

[0817] The terminal transmits the input data to the server.

[0818] The device encrypts the data using the SSL / TLS protocol and sends it to the server. The server stores the received data in a database. During this process, encryption is used to protect the security of the data. The input is the user's personal information, and the output is the data stored on the server.

[0819] Step 4:

[0820] The terminal periodically collects the user's social networking service postings and search history.

[0821] Data collection is performed automatically every hour. The device accesses the SNS API to obtain post content and search history. The input is SNS post and search history data, and the output is this data sent to the server.

[0822] Step 5:

[0823] The terminal transmits the collected data to the server.

[0824] The collected data is sent in real time to the server, which stores it in temporary storage and prepares it for later analysis. The input is the data collected by the device, and the output is the data stored in the server's temporary storage.

[0825] Step 6:

[0826] The server provides the collected data to a generative AI model that is responsible for data analysis.

[0827] The server extracts data from temporary storage and sends it to the generative AI model, which analyzes specific risk keywords and detects anomalies. The input is the data extracted from the server's storage, and the output is the analysis result of the generative AI model.

[0828] Step 7:

[0829] A generative AI model analyzes the data and detects anomalies.

[0830] The generative AI model analyzes data based on a list of dangerous keywords and detects abnormal patterns. For example, it detects keywords such as "I want to die" or "I want to disappear." The input is the collected data, and the output is the results of anomaly detection.

[0831] Step 8:

[0832] The server receives the analysis results from the generative AI model.

[0833] The server receives the analysis results from the generative AI model and prepares to execute the next action if an anomaly is detected. The input is the analysis results of the generative AI model, and the output is the anomaly analysis results stored on the server.

[0834] Step 9:

[0835] The server sends a prompt to the generative AI model based on the analysis results.

[0836] The server sends the prompt to the generative AI model, which then generates an appropriate support message. For example, the server sends the prompt, "A 20-year-old man posted on social media that 'school is tough.' What kind of support message should I send him?" The input is the anomaly detection result, and the output is the support message generated by the generative AI model.

[0837] Step 10:

[0838] A generative AI model generates support messages.

[0839] The generative AI model generates an appropriate support message based on the prompt sentence. For example, it generates a message like, "Are you okay? We're here to help you." The input is the prompt sentence, and the output is the support message.

[0840] Step 11:

[0841] The server sends the generated support message to the user's terminal.

[0842] The server sends the support message received from the generative AI model to the user's device. The input is the generated support message, and the output is the message displayed on the user's device.

[0843] Step 12:

[0844] The generative AI model assesses risk and takes action if it determines it is high risk.

[0845] The server receives the analysis results that the generative AI model judges to be high-risk and sends an SOS notification to a professional counselor. The input is the high-risk analysis result, and the output is a notification to the counselor.

[0846] Step 13:

[0847] Counsellors will contact users directly to provide professional support.

[0848] Based on the notification received from the server, the counselor contacts the user by phone or email and provides the necessary support. The input is the SOS notification, and the output is the professional support the user receives.

[0849] (Application example 1)

[0850] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0851] Suicide among young people is a serious social problem, and there is a need to detect psychological problems early and provide appropriate support. However, in many cases, these problems tend to be overlooked and progress without the individual or those around them noticing. Furthermore, there is a lack of means to monitor changes in their psychological state and behavior in real time and respond immediately. The present invention solves this problem.

[0852] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0853] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social media posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when the abnormality is difficult to resolve or the risk is high, means for collecting data via a device to monitor the user's behavior and comments in real time, means for analyzing the collected data in real time with artificial intelligence to detect abnormalities, and means for instantly generating and notifying prompt messages based on the collected and analyzed data. This makes it possible to monitor changes in the user's psychological state and behavior in real time and provide prompt and appropriate support when an abnormality is detected.

[0854] "User" refers to an individual using this system.

[0855] "Personal information" refers to information that can identify an individual, such as a user's name, age, or gender.

[0856] "Physical examination results" refers to the result data of a medical examination that the user has taken in the past.

[0857] "SNS posts" refer to messages or comments posted by users on social networking services.

[0858] "Search history" refers to a record of searches a user has conducted on the Internet.

[0859] "Specific risk keywords" refer to words or phrases that may indicate risk when monitoring a user's psychological state or behavior.

[0860] "Means for detecting anomalies" refers to technology that analyzes specific risk keywords from collected data and determines whether a user is at risk.

[0861] "Appropriate support messages" refer to messages of encouragement and support that the system generates depending on the user's condition.

[0862] An "expert" refers to a person, such as a psychological counselor or psychiatrist, who has specialized knowledge about the user's psychological state and behavior and can provide support.

[0863] "Real-time monitoring" refers to the immediate monitoring of user actions and comments.

[0864] "Device" refers to equipment that can collect user behavior and statements, such as smart glasses or smartphones.

[0865] "Generative AI" refers to algorithms that analyze collected data and automatically generate response messages, warnings, etc.

[0866] A "prompt sentence" refers to an instruction sentence or message generated to prompt a user to take an appropriate action.

[0867] MODE FOR CARRYING OUT THE INVENTION

[0868] This invention is a counseling system aimed at preventing suicide among young people, and in particular utilizes generative AI. This system is mainly composed of three main components: a server, a terminal, and a user. Specific embodiments of this system are described below.

[0869] User registration and data acquisition

[0870] Users access the system through devices such as smartphones or smart glasses and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which stores it in a database. For example, if a user registers as a 20-year-old male named "Taro Yamada" and enters that their mental health score is 5, this information will be saved in the database.

[0871] Data collection and real-time monitoring

[0872] The device periodically collects information about the user's daily activities, social media posts, search history, etc. It also uses devices such as smart glasses to monitor the user's facial expressions and comments in real time, making it possible to instantly detect changes in the user's psychological state and behavior.

[0873] Anomaly detection

[0874] The collected data is sent to a server where it is analyzed by the AI ​​generator. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the AI ​​generator will analyze it and detect certain dangerous keywords. Similarly, if a user mutters to themselves through the smart glasses, "I have no motivation to do anything anymore," the voice data will be instantly analyzed and deemed abnormal.

[0875] Support message generation and notification

[0876] If an abnormality is detected, the AI ​​generates an appropriate support message and sends it to the device via the server. For example, a prompt such as "Are you OK? Would you like to talk for a moment?" is displayed to the user, allowing the user to receive immediate support.

[0877] Escalation and Expert Notification

[0878] If it is difficult to respond or if the risk is deemed high, the generative AI will automatically notify experts (psychological counselors or psychiatrists) within the server. For example, if the risk level is high, the server will notify the experts in real time, and the experts will contact the user directly to provide support. This process enables a quick and accurate response.

[0879] Hardware and software used

[0880] Hardware:

[0881] Smart glasses (e.g., Google Glass, Vuzix)

[0882] Smartphone

[0883] Internet connection

[0884] software:

[0885] Generative AI (e.g. OpenAI GPT-4, Google AI)

[0886] Voice recognition systems (e.g., Google Speech-to-Text)

[0887] Facial expression analysis software (e.g. Microsoft Face API)

[0888] Examples of prompt statements

[0889] If the user says "Everything is painful", generate the following prompt:

[0890] A user says, "Everything is hard." Generate an appropriate support message for this statement.

[0891] In this way, the system monitors the user's psychological state and behavior in real time and provides support at the appropriate time, providing an effective counseling system aimed at preventing suicide among young people.

[0892] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0893] Step 1:

[0894] Users access the system using a smartphone or smart glasses and enter their personal information (name, age, gender, etc.) and health check results.

[0895] Input: Personal information, health check results

[0896] Output: Data sent to the server

[0897] Specific operation: The user launches the dedicated application on the device, follows the instructions to enter information into the form, and presses the submit button to send the information to the server.

[0898] Step 2:

[0899] The device periodically collects the user's SNS posts and search history and sends them to the server.

[0900] Input: Social media posts, search history

[0901] Output: Data sent to the server

[0902] Specific operation: A background program on the device checks the user's social media accounts and browser history every hour and automatically sends any new data to the server.

[0903] Step 3:

[0904] The server collects data from devices such as smart glasses to monitor users' actions and comments in real time.

[0905] Input: Real-time behavioral data, voice data

[0906] Output: Data sent to the server

[0907] Specific operation: The smart glasses' camera and microphone constantly capture data and stream it to the server.

[0908] Step 4:

[0909] The server analyzes the collected data using generative AI to detect specific dangerous keywords and abnormal behavior.

[0910] Input: Personal information, health check results, social media posts, search history, real-time behavioral data, voice data

[0911] Output: Analysis result (normal / abnormal)

[0912] Specific operation: The generative AI running on the server comprehensively analyzes all data, identifies dangerous keywords and abnormal patterns, and records the analysis results in a database.

[0913] Step 5:

[0914] If an abnormality is detected, the generation AI generates an appropriate support message and notifies the user's device via the server.

[0915] Input: Analysis result (abnormal)

[0916] Output: Support message to user terminal

[0917] Specific operation: The generative AI generates a prompt based on the analysis results and immediately notifies the user on their smart glasses or smartphone, displaying a pop-up message.

[0918] Step 6:

[0919] If the situation is difficult or the risk is high, the server will automatically notify experts and provide real-time support.

[0920] Input: Analysis results (high risk)

[0921] Output:Notify Expert

[0922] Specific operation: The server determines the risk level and automatically notifies a counselor or psychiatrist if necessary. The expert then contacts the user directly to provide support.

[0923] This enables the system to monitor the user's psychological state and behavior in real time and provide support at the appropriate time.

[0924] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0925] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: a server, a terminal, and a user.

[0926] overview

[0927] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor to provide more specialized support.

[0928] Specific examples of processing

[0929] User registration and data acquisition

[0930] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[0931] Anomaly detection

[0932] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, where the generation AI analyzes specific dangerous keywords. The emotion engine also analyzes the user's posts, search history, and voice and facial expression data to recognize the user's emotional state. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects changes in emotion from the post content and provides that information to the generation AI.

[0933] Active Support Starts

[0934] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[0935] Escalation and Human Support

[0936] If the situation is deemed difficult to deal with or the risk is high, the generating AI will send an SOS notification to the server, which will then notify a professional counselor. For example, if the emotion engine's analysis determines the risk level to be 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[0937] How the Emotional Engine Works

[0938] The emotion engine analyzes the user's voice, facial expressions, and text data. For example, if a user says through the app, "I haven't been able to sleep lately," the emotion engine analyzes the tone of the voice and facial expressions to detect signs of stress or anxiety. Similarly, if a user frequently tweets negative phrases on social media, such as "I want to die" or "I'm so tired," the emotion engine can recognize their emotions from the text data.

[0939] By combining generative AI and an emotion engine, this system can more accurately grasp the user's psychological state, enabling 24-hour anomaly detection and support. When an anomaly is detected, appropriate messages and countermeasures are immediately displayed, and human support is also provided if necessary.

[0940] In this way, the present invention provides a more advanced and effective counseling system for preventing suicide among young people.

[0941] The processing flow will be explained below.

[0942] Step 1:

[0943] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[0944] Step 2:

[0945] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[0946] Step 3:

[0947] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[0948] Step 4:

[0949] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[0950] Step 5:

[0951] The server's generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[0952] Step 6:

[0953] The device collects voice data from the user, and when the user speaks to the app, the device sends the voice data to the server.

[0954] Step 7:

[0955] The server receives the voice data and the emotion engine analyzes it to recognize the user's emotional state from the tone of the voice and the choice of words.

[0956] Step 8:

[0957] The emotion engine on the server uses facial recognition technology to analyze the user's facial expressions. If the user is using a camera, the device sends image data to the server, which then analyzes the facial expressions.

[0958] Step 9:

[0959] The emotion engine feeds back the results of its analysis to the generative AI, which then uses the feedback from the emotion engine to further detect anomalies.

[0960] Step 10:

[0961] The server's generation AI receives the "anomaly detected" flag and generates an appropriate support message as needed. The server then sends the message to the device.

[0962] Step 11:

[0963] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[0964] Step 12:

[0965] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[0966] Step 13:

[0967] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[0968] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[0969] Example 2

[0970] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0971] The problem that this invention aims to solve is to accurately grasp the user's psychological state and provide immediate and appropriate support in an advanced counseling system aimed at preventing suicide among young people. Current systems are unable to fully analyze the user's emotional state, and there is a risk that abnormalities will be overlooked. Another problem is the lack of a means to respond quickly when expert support is needed.

[0972] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for analyzing specific risky keywords from the collected data and analyzing the emotional state using an emotion engine to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when it is difficult to respond or the risk is high. This makes it possible to analyze the collected data and the analysis results of the emotion engine using a generative artificial intelligence model, and when an abnormality is detected, the generative artificial intelligence model can generate an appropriate support message and notify the user.

[0973] "Personal information" refers to information that can individually identify a user, such as the user's name, age, gender, address, and contact details.

[0974] "Medical checkup results" are data indicating the user's health condition, and include results obtained from a medical checkup conducted at a medical institution.

[0975] "Social networking service posts" are information such as text, images, and videos that users publish and share on social networking services (SNS).

[0976] "Search History" is the history of search queries made by a user using an internet search engine.

[0977] "Dangerous keywords" are specific words that are judged to indicate an abnormality in the user's psychological state or behavior, and include negative expressions such as "I want to die" and "It's painful."

[0978] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, and text data to recognize their emotional state (for example, joy, sadness, anger, etc.).

[0979] "Abnormal" refers to a situation that is different from the normal psychological state of the user, and particularly includes risky behavior and serious changes in mental state.

[0980] A "support message" is a message for assistance provided to a user when an abnormality is detected, and includes, for example, content such as "Are you OK? Please talk to us."

[0981] An "expert" is a professional who can respond to users' psychological and mental problems, such as a counselor or doctor with specialized knowledge and experience in psychology or psychiatry.

[0982] A "generative artificial intelligence model" is an artificial intelligence technology that analyzes collected data and performs specific tasks (such as detecting anomalies or generating support messages).

[0983] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: the user, the terminal, and the server.

[0984] Overall structure

[0985] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if it is deemed difficult to respond or high risk, the generative AI will notify an expert, who will provide more specialized support.

[0986] Hardware and Software Configuration

[0987] Device: The user's smartphone or computer, on which the smartphone application is installed.

[0988] Server: Use a cloud or on-premise server to run a database management system (e.g. MySQL), generative AI models (e.g. GPT series), and sentiment engines (e.g. Amazon Comprehend on AWS or Sentiment Analysis on Google Cloud).

[0989] Database: Stores users' personal information, health check results, collected SNS posts, and search history.

[0990] Program processing

[0991] The device sends personal information and health check results entered by the user to a server. The server receives this information and stores it in a database. The device then periodically collects the user's social media posts and search history and sends them to the server. Within the server, this data is analyzed by the generative AI and emotion engine. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects this change in emotion and provides that information to the generative AI.

[0992] The generating AI detects anomalies based on the analysis results, and if an anomaly is detected, it generates a support message such as "Are you OK? We can help you," and sends it to the user's device via the server. Furthermore, if the risk is deemed high, the generating AI sends an SOS notification to an expert via the server. The expert receives this notification and contacts the user directly to provide professional support.

[0993] Specific examples

[0994] If a user types "School has been tough lately and I can't sleep" into the app as "Kenji Suzuki," the emotion engine analyzes the text data and detects signs of stress or anxiety. As a result, the generative AI generates a message saying, "It seems like things are going to be tough at school. Why don't you try counseling?" and sends it to the user's device. The user can receive this message and receive support as needed.

[0995] Prompt Sentence Examples

[0996] "Analyze the text 'I feel like dying' posted by a user on social media and generate an appropriate support message."

[0997] "Analyze user voice data to detect signs of stress and anxiety."

[0998] "Save user registration information and health check results in a database."

[0999] This system combines generative AI and an emotion engine to accurately and quickly grasp the user's psychological state, and is capable of detecting anomalies and providing support 24 hours a day. When an anomaly is detected, appropriate messages and countermeasures are immediately presented, and expert support is also provided as needed, providing a more effective counseling system.

[1000] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1001] Step 1: User registration and data submission

[1002] Description: The user downloads a smartphone app and enters personal information (such as name, age, and gender) and health checkup results on the app's registration screen.

[1003] Specific behavior:

[1004] Input: The user enters their name, age, gender, and health check results into the app.

[1005] Data processing: The device converts the input information into an appropriate format.

[1006] Output: The device sends data to the server.

[1007] Server: Stores the received data in a database. For example, if a user enters "Taro Yamada," "20-year-old male," and "mental health score 5," this information will be saved in the database.

[1008] Step 2: Collect social media posts and search history

[1009] Description: The device periodically collects the user's social media posts and search history.

[1010] Specific behavior:

[1011] Input: The device retrieves the user's social media icon and search query.

[1012] Data collection: The device uses social media APIs to obtain post content and search history using search engine APIs.

[1013] Output: Send the collected data to the server.

[1014] Server: Stores received SNS posts and search history in an analytical database. This data collection is performed automatically in the background once a day.

[1015] Step 3: Data analysis and anomaly detection

[1016] Description: The server's generative AI model and emotion engine analyze the user's emotional state from collected data and detect anomalies.

[1017] Specific behavior:

[1018] Input: Collected social media posts, search history data, voice data, and facial expression data.

[1019] Data analysis: Generative AI detects dangerous keywords through text analysis, and the emotion engine analyzes psychological states from voice and facial expressions.

[1020] Output: Report anomaly detection. For example, if a user posts "I want to die" and the voice has a low tone, the generative AI and emotion engine will determine this as an anomaly.

[1021] Step 4: Send a support message

[1022] Description: If an abnormality is detected, the server's generation AI will generate an appropriate support message and notify the user.

[1023] Specific behavior:

[1024] Input: Data of abnormal presentation.

[1025] Message generation: The generation AI generates a support message for the user.

[1026] Output: The generated support message.

[1027] Server: Sends a message to the user's device. For example, generate a message saying "Are you okay? We're here to help you." and send it as a push notification to the device.

[1028] Step 5: Escalation and Specialized Support

[1029] Description: If the risk is deemed high, the server-generated AI will send an SOS notification to an expert.

[1030] Specific behavior:

[1031] Input: Sentiment engine analysis results and risk assessment.

[1032] Risk assessment: Generative AI assesses the risk level and quantifies the danger.

[1033] Output: SOS notification to the expert.

[1034] Server: If the risk level is high, a notification is sent to a counselor, who will contact the user and provide professional support. For example, if the risk level is determined to be 8, the server automatically notifies a counselor, who will provide support via phone or video chat.

[1035] (Application example 2)

[1036] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1037] Conventional counseling systems have difficulty accurately grasping a user's psychological state, making it difficult to detect abnormalities early and provide appropriate support. In particular, to prevent suicide among young people, advanced analytical technology that can detect subtle abnormalities that appear in social media posts and search history is needed. There is also a need for a system that can grasp a user's psychological state through the usage history of online sales systems and respond quickly.

[1038] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1039] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's SNS posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when it is difficult to respond or when the risk is high, means for collecting the usage history of the online sales system and analyzing the user's psychological state, and means for monitoring the user's psychological state in real time using an emotion engine. This makes it possible to more accurately grasp the user's psychological state, detect abnormalities early, and provide appropriate support.

[1040] "Personal information" refers to information that identifies an individual, such as name, age, and gender.

[1041] "Medical examination results" are medical information based on the medical examinations that the user has undergone, and are data that indicate the user's health condition.

[1042] "SNS posts" are content such as text, images, and videos that users post to social networking services.

[1043] "Search history" is a record of searches a user has conducted on an Internet search engine.

[1044] "Danger keywords" are specific words or phrases that indicate suicide or serious mental illness.

[1045] A "support message" is a message sent to support the user's psychological state.

[1046] An "expert" is a professional with advanced knowledge and experience in psychological counseling and mental health.

[1047] An "online sales system" is an electronic commerce system that sells products and services over the Internet.

[1048] "Usage history" is a record of purchases and browsing made by a user in the online sales system.

[1049] An "emotion engine" is software or a system for analyzing emotions from a user's text, voice, facial expressions, etc.

[1050] "Real-time monitoring" means constantly and instantly monitoring the user's psychological state.

[1051] This invention is an advanced counseling system that monitors the user's psychological state and provides support at the appropriate time. The system is mainly composed of three main components: a server, a terminal, and a user.

[1052] User registration and data acquisition

[1053] First, users install the smartphone app and create an account. Through the app, users enter personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This information is sent from the device to the server, which then stores it in a database.

[1054] Collection of social media posts and search history

[1055] The device periodically collects the user's social media posts and search history and sends them to a server. All collected data is stored in the server's database. The server uses this data to analyze the user's psychological state in real time.

[1056] Detecting anomalies and sending support messages

[1057] The server analyzes the collected data using a generation AI. The generation AI analyzes specific risky keywords, and an emotion engine evaluates the user's emotional state based on social media posts and search history. If an abnormality is detected, the generation AI generates an appropriate support message and sends it to the user's device via the server.

[1058] For example, if a user posts on social media, "I'm tired" or "Everything seems pointless," the emotion engine analyzes the post and detects negative emotions. The generative AI then generates a support message saying, "Are you okay? We're here to help," and sends it to the user.

[1059] Escalation and human support coordination

[1060] If an abnormality is detected and a high risk is deemed to exist, the generating AI will send an SOS notification to the server, which will then notify experts (psychological counselors and mental health professionals) who will then contact the user directly to provide support.

[1061] Hardware and Software Use

[1062] Hardware: smartphones, servers, databases

[1063] Software: Application frameworks (e.g., React Native), generative AI (e.g., OpenAI's GPT model), sentiment analysis engines (e.g., IBM Watson)

[1064] The generative AI model operates by inputting a prompt sentence. An example of a prompt sentence is shown below.

[1065] Example prompt sentence:

[1066] "Analyze the user's recent emotional state from their social media posting history, detect negative keywords, and generate supportive messages."

[1067] This system will enable constant monitoring of the user's psychological state, detect abnormalities early, and provide support, which is expected to help prevent suicide and maintain psychological health among young people.

[1068] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1069] Step 1:

[1070] The user installs the smartphone app and creates an account. The user enters personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This data is sent from the device to the server, which stores it in a database. The input data is in text format and is saved as output in the database. Specifically, the information entered by the user, such as "Taro Yamada," "20 years old," and "male," is registered in the database.

[1071] Step 2:

[1072] The device periodically collects the user's SNS posts and search history and sends them to the server. The collected data is stored in the server's database. The input data is a text record of the user's SNS posts and search history, and is stored in the server's database as output. Specifically, the content of posts made by the user on SNS such as "School is hard" is periodically collected and sent to the server.

[1073] Step 3:

[1074] The server analyzes the collected data using a generative AI model. Input data includes the user's social media posts, search history, and health checkup results, and specific dangerous keywords are detected through text analysis using the generative AI model. The result of this analysis is the user's emotional state. Specifically, the analysis is performed by inputting the prompt statement "Analyze the user's recent emotional state from their social media posting history and detect negative keywords" into the generative AI.

[1075] Step 4:

[1076] If an abnormality is detected, an appropriate support message is generated using a generative AI model. The input data is the analyzed emotional state, and an automatically generated support message is output. This generated support message is sent from the server to the user's device. Specifically, if a negative emotion is detected, a message is generated saying, "Are you okay? We're here to help you," and sent to the user.

[1077] Step 5:

[1078] If the risk is high, the generative AI model sends an SOS notification to the server. The input data is the emotion analysis results and risk assessment results, and the output is an SOS notification sent to an expert. The server receives this notification and contacts a psychological counselor or mental health professional. Specifically, if the risk level is determined to be high, a notification is sent to the counselor saying, "Contact an expert for support."

[1079] As a result, it is possible to monitor the user's psychological state in real time and provide appropriate support promptly when an abnormality is detected.

[1080] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1081] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1082] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1083] [Fourth embodiment]

[1084] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1085] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1086] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1087] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1088] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1089] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1090] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1091] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1092] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1093] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1094] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1095] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1096] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1097] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI (generative artificial intelligence). The system is mainly composed of three main components: a server, a terminal, and a user.

[1098] overview

[1099] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and, if it detects an abnormality, sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor, who will provide more specialized support.

[1100] Specific examples of processing

[1101] User registration and data acquisition

[1102] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[1103] Anomaly detection

[1104] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, and the AI ​​analyzes specific dangerous keywords. For example, if a user posts on social media "School is hard" or "I feel like I want to die," the AI ​​analyzes these posts and detects anomalies.

[1105] Active Support Starts

[1106] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[1107] Escalation and Human Support

[1108] If the AI ​​determines that the situation is difficult to address or that the risk is high, it will send an SOS notification to the server, which will then notify a professional counselor. For example, if the risk level is 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[1109] This system uses generative AI to detect anomalies and provide support 24 hours a day, providing an environment where users can consult at any time. It also allows for on-site support by professional counselors, allowing for more appropriate support to be provided to users.

[1110] In this way, the present invention provides an effective counseling system aimed at preventing suicide among young people.

[1111] The processing flow will be explained below.

[1112] Step 1:

[1113] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[1114] Step 2:

[1115] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[1116] Step 3:

[1117] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[1118] Step 4:

[1119] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[1120] Step 5:

[1121] The generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[1122] Step 6:

[1123] The server receives the "anomaly detected" flag from the generation AI and starts active support. The generation AI generates an appropriate support message (e.g., "Are you okay? We're here to help you."), and the server sends it to the user's device.

[1124] Step 7:

[1125] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[1126] Step 8:

[1127] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[1128] Step 9:

[1129] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[1130] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[1131] Example 1

[1132] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1133] In recent years, the suicide rate among young people has been increasing, making it an urgent task to detect abnormalities early and provide appropriate support. In particular, there is a need for a method to detect early signs of suicide from posts and search history on social networking services and provide professional support. However, existing systems are insufficient in collecting and analyzing data, making it difficult to respond in real time.

[1134] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1135] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for encrypting the collected data and transmitting it to the server, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for sending an appropriate prompt sentence to the generative AI model based on the analysis results, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when response is difficult or risk is high. This makes it possible to detect abnormalities in real time and provide appropriate support promptly while ensuring the safety of the collected data.

[1136] "Personal information" refers to information that can be used to individually identify a user, such as the user's name, age, gender, address, and contact details.

[1137] "Physical examination results" refers to data relating to the health condition of a user, such as blood pressure, body temperature, and blood test results, obtained when the user undergoes a medical examination.

[1138] A "social networking service" is an online platform that enables users to share information and communicate with other users.

[1139] "Search history" is a record of keywords or phrases that a user searches for on an Internet search engine.

[1140] "Data encryption" is a technology that codes transmitted data using a specific algorithm to protect it from unauthorized access.

[1141] A "generative AI model" is an artificial intelligence system that has been trained to perform a specific task using machine learning techniques.

[1142] A "prompt sentence" is a sentence that serves as input to a generative AI model, such as an instruction or question.

[1143] A "support message" is a message that is provided to the user and contains comforting words or a message that encourages action.

[1144] An "expert" is a professional with advanced knowledge and experience in the fields of psychology and counseling.

[1145] A "notification" is a message or alert that informs the recipient of important information or warnings.

[1146] MODE FOR CARRYING OUT THE INVENTION

[1147] This invention is a counseling system aimed at preventing suicide among young people, and utilizes generative AI models in particular. The system is primarily composed of three main components: a server, a terminal, and a user.

[1148] User registration and data acquisition

[1149] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to a server, which then stores the received information in a database. For example, if a user enters that they are a "20-year-old male with a mental health score of 5," this information is saved in the database.

[1150] Data collection

[1151] The device periodically monitors the user's social networking service posts and search history, and sends this data to a server. The data is sent at specific time intervals during the collection process, for example, every hour. The server stores this data in temporary storage and prepares it for the necessary analysis. The hardware used is a standard smartphone (iPhone, Android), and the server uses cloud services such as AWS (Amazon Web Services) and Google Cloud.

[1152] Data analysis and anomaly detection

[1153] The server extracts the data from temporary storage and requests analysis from a generative AI model. The generative AI model analyzes the data using specific dangerous keywords (e.g., phrases like "school is hard" or "I want to die"). The generative AI model uses the latest machine learning models such as GPT-4.

[1154] Send a support message

[1155] If the generative AI model detects an abnormality, the server sends a prompt to the model, which generates an appropriate support message. For example, a support message such as "Are you OK? We're here to help." The generated message is then sent to the user's smartphone via the server.

[1156] Risk Escalation and Specialized Support

[1157] If the generative AI model determines that the user is at high risk based on the analysis results, the server will send an SOS notification to a professional counselor. The counselor will receive this notification and contact the user directly to provide the necessary support. For example, if the risk level is high and the risk score is assessed as 8, the counselor will take appropriate action.

[1158] Specific examples

[1159] For example, a 20-year-old male user registers on a smartphone app with the name "Taro Yamada" and a mental health score of 5, and posts on social media that "school is tough." The device collects this information and sends it to a server. The server uses a generative AI model to analyze the post and determine that it is a dangerous situation. The prompt text is entered as "If you are feeling tough at school, what kind of support message would be appropriate?", and a message such as "Are you OK? We can talk to you" is generated. If the risk is high, a counselor is contacted and direct support is provided to the user.

[1160] Prompt Sentence Examples

[1161] "A 20-year-old man posted on social media that school is tough. What message of support should I send him?"

[1162] By utilizing generative AI models, this counseling system is able to detect anomalies and respond quickly 24 hours a day, providing effective support for suicide prevention.

[1163] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1164] Step 1:

[1165] A user downloads a smartphone app.

[1166] Users download and install apps from the app store by operating the smartphone interface, searching for the app, and pressing the download button.

[1167] Step 2:

[1168] The user inputs personal information and health check results.

[1169] Users launch the app and enter their personal information, such as their name, age, gender, and mental health score, which is then stored on their smartphone.

[1170] Step 3:

[1171] The terminal transmits the input data to the server.

[1172] The device encrypts the data using the SSL / TLS protocol and sends it to the server. The server stores the received data in a database. During this process, encryption is used to protect the security of the data. The input is the user's personal information, and the output is the data stored on the server.

[1173] Step 4:

[1174] The terminal periodically collects the user's social networking service postings and search history.

[1175] Data collection is performed automatically every hour. The device accesses the SNS API to obtain post content and search history. The input is SNS post and search history data, and the output is this data sent to the server.

[1176] Step 5:

[1177] The terminal transmits the collected data to the server.

[1178] The collected data is sent in real time to the server, which stores it in temporary storage and prepares it for later analysis. The input is the data collected by the device, and the output is the data stored in the server's temporary storage.

[1179] Step 6:

[1180] The server provides the collected data to a generative AI model that is responsible for data analysis.

[1181] The server extracts data from temporary storage and sends it to the generative AI model, which analyzes specific risk keywords and detects anomalies. The input is the data extracted from the server's storage, and the output is the analysis result of the generative AI model.

[1182] Step 7:

[1183] A generative AI model analyzes the data and detects anomalies.

[1184] The generative AI model analyzes data based on a list of dangerous keywords and detects abnormal patterns. For example, it detects keywords such as "I want to die" or "I want to disappear." The input is the collected data, and the output is the results of anomaly detection.

[1185] Step 8:

[1186] The server receives the analysis results from the generative AI model.

[1187] The server receives the analysis results from the generative AI model and prepares to execute the next action if an anomaly is detected. The input is the analysis results of the generative AI model, and the output is the anomaly analysis results stored on the server.

[1188] Step 9:

[1189] The server sends a prompt to the generative AI model based on the analysis results.

[1190] The server sends the prompt to the generative AI model, which then generates an appropriate support message. For example, the server sends the prompt, "A 20-year-old man posted on social media that 'school is tough.' What kind of support message should I send him?" The input is the anomaly detection result, and the output is the support message generated by the generative AI model.

[1191] Step 10:

[1192] A generative AI model generates support messages.

[1193] The generative AI model generates an appropriate support message based on the prompt sentence. For example, it generates a message like, "Are you okay? We're here to help you." The input is the prompt sentence, and the output is the support message.

[1194] Step 11:

[1195] The server sends the generated support message to the user's terminal.

[1196] The server sends the support message received from the generative AI model to the user's device. The input is the generated support message, and the output is the message displayed on the user's device.

[1197] Step 12:

[1198] The generative AI model assesses risk and takes action if it determines it is high risk.

[1199] The server receives the analysis results that the generative AI model judges to be high-risk and sends an SOS notification to a professional counselor. The input is the high-risk analysis result, and the output is a notification to the counselor.

[1200] Step 13:

[1201] Counsellors will contact users directly to provide professional support.

[1202] Based on the notification received from the server, the counselor contacts the user by phone or email and provides the necessary support. The input is the SOS notification, and the output is the professional support the user receives.

[1203] (Application example 1)

[1204] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1205] Suicide among young people is a serious social problem, and there is a need to detect psychological problems early and provide appropriate support. However, in many cases, these problems tend to be overlooked and progress without the individual or those around them noticing. Furthermore, there is a lack of means to monitor changes in their psychological state and behavior in real time and respond immediately. The present invention solves this problem.

[1206] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1207] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social media posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when the abnormality is difficult to resolve or the risk is high, means for collecting data via a device to monitor the user's behavior and comments in real time, means for analyzing the collected data in real time with artificial intelligence to detect abnormalities, and means for instantly generating and notifying prompt messages based on the collected and analyzed data. This makes it possible to monitor changes in the user's psychological state and behavior in real time and provide prompt and appropriate support when an abnormality is detected.

[1208] "User" refers to an individual using this system.

[1209] "Personal information" refers to information that can identify an individual, such as a user's name, age, or gender.

[1210] "Physical examination results" refers to the result data of a medical examination that the user has taken in the past.

[1211] "SNS posts" refer to messages or comments posted by users on social networking services.

[1212] "Search history" refers to a record of searches a user has conducted on the Internet.

[1213] "Specific risk keywords" refer to words or phrases that may indicate risk when monitoring a user's psychological state or behavior.

[1214] "Means for detecting anomalies" refers to technology that analyzes specific risk keywords from collected data and determines whether a user is at risk.

[1215] "Appropriate support messages" refer to messages of encouragement and support that the system generates depending on the user's condition.

[1216] An "expert" refers to a person, such as a psychological counselor or psychiatrist, who has specialized knowledge about the user's psychological state and behavior and can provide support.

[1217] "Real-time monitoring" refers to the immediate monitoring of user actions and comments.

[1218] "Device" refers to equipment that can collect user behavior and statements, such as smart glasses or smartphones.

[1219] "Generative AI" refers to algorithms that analyze collected data and automatically generate response messages, warnings, etc.

[1220] A "prompt sentence" refers to an instruction sentence or message generated to prompt a user to take an appropriate action.

[1221] MODE FOR CARRYING OUT THE INVENTION

[1222] This invention is a counseling system aimed at preventing suicide among young people, and in particular utilizes generative AI. This system is mainly composed of three main components: a server, a terminal, and a user. Specific embodiments of this system are described below.

[1223] User registration and data acquisition

[1224] Users access the system through devices such as smartphones or smart glasses and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which stores it in a database. For example, if a user registers as a 20-year-old male named "Taro Yamada" and enters that their mental health score is 5, this information will be saved in the database.

[1225] Data collection and real-time monitoring

[1226] The device periodically collects information about the user's daily activities, social media posts, search history, etc. It also uses devices such as smart glasses to monitor the user's facial expressions and comments in real time, making it possible to instantly detect changes in the user's psychological state and behavior.

[1227] Anomaly detection

[1228] The collected data is sent to a server where it is analyzed by the AI ​​generator. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the AI ​​generator will analyze it and detect certain dangerous keywords. Similarly, if a user mutters to themselves through the smart glasses, "I have no motivation to do anything anymore," the voice data will be instantly analyzed and deemed abnormal.

[1229] Support message generation and notification

[1230] If an abnormality is detected, the AI ​​generates an appropriate support message and sends it to the device via the server. For example, a prompt such as "Are you OK? Would you like to talk for a moment?" is displayed to the user, allowing the user to receive immediate support.

[1231] Escalation and Expert Notification

[1232] If it is difficult to respond or if the risk is deemed high, the generative AI will automatically notify experts (psychological counselors or psychiatrists) within the server. For example, if the risk level is high, the server will notify the experts in real time, and the experts will contact the user directly to provide support. This process enables a quick and accurate response.

[1233] Hardware and software used

[1234] Hardware:

[1235] Smart glasses (e.g., Google Glass, Vuzix)

[1236] Smartphone

[1237] Internet connection

[1238] software:

[1239] Generative AI (e.g. OpenAI GPT-4, Google AI)

[1240] Voice recognition systems (e.g., Google Speech-to-Text)

[1241] Facial expression analysis software (e.g. Microsoft Face API)

[1242] Examples of prompt statements

[1243] If the user says "Everything is painful", generate the following prompt:

[1244] A user says, "Everything is hard." Generate an appropriate support message for this statement.

[1245] In this way, the system monitors the user's psychological state and behavior in real time and provides support at the appropriate time, providing an effective counseling system aimed at preventing suicide among young people.

[1246] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1247] Step 1:

[1248] Users access the system using a smartphone or smart glasses and enter their personal information (name, age, gender, etc.) and health check results.

[1249] Input: Personal information, health check results

[1250] Output: Data sent to the server

[1251] Specific operation: The user launches the dedicated application on the device, follows the instructions to enter information into the form, and presses the submit button to send the information to the server.

[1252] Step 2:

[1253] The device periodically collects the user's SNS posts and search history and sends them to the server.

[1254] Input: Social media posts, search history

[1255] Output: Data sent to the server

[1256] Specific operation: A background program on the device checks the user's social media accounts and browser history every hour and automatically sends any new data to the server.

[1257] Step 3:

[1258] The server collects data from devices such as smart glasses to monitor users' actions and comments in real time.

[1259] Input: Real-time behavioral data, voice data

[1260] Output: Data sent to the server

[1261] Specific operation: The smart glasses' camera and microphone constantly capture data and stream it to the server.

[1262] Step 4:

[1263] The server analyzes the collected data using generative AI to detect specific dangerous keywords and abnormal behavior.

[1264] Input: Personal information, health check results, social media posts, search history, real-time behavioral data, voice data

[1265] Output: Analysis result (normal / abnormal)

[1266] Specific operation: The generative AI running on the server comprehensively analyzes all data, identifies dangerous keywords and abnormal patterns, and records the analysis results in a database.

[1267] Step 5:

[1268] If an abnormality is detected, the generation AI generates an appropriate support message and notifies the user's device via the server.

[1269] Input: Analysis result (abnormal)

[1270] Output: Support message to user terminal

[1271] Specific operation: The generative AI generates a prompt based on the analysis results and immediately notifies the user on their smart glasses or smartphone, displaying a pop-up message.

[1272] Step 6:

[1273] If the situation is difficult or the risk is high, the server will automatically notify experts and provide real-time support.

[1274] Input: Analysis results (high risk)

[1275] Output:Notify Expert

[1276] Specific operation: The server determines the risk level and automatically notifies a counselor or psychiatrist if necessary. The expert then contacts the user directly to provide support.

[1277] This enables the system to monitor the user's psychological state and behavior in real time and provide support at the appropriate time.

[1278] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1279] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: a server, a terminal, and a user.

[1280] overview

[1281] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if the issue is deemed difficult to address or high risk, the generative AI will notify a professional counselor to provide more specialized support.

[1282] Specific examples of processing

[1283] User registration and data acquisition

[1284] Users download the smartphone app and enter their personal information (such as name, age, and gender) and health check results. This information is sent from the device to the server, which then stores the received information in a database. For example, if a user registers as "Taro Yamada," a 20-year-old male, and enters that their mental health score is 5, this information is saved in the database.

[1285] Anomaly detection

[1286] Next, the device periodically collects the user's social media posts and search history. This data is sent to a server, where the generation AI analyzes specific dangerous keywords. The emotion engine also analyzes the user's posts, search history, and voice and facial expression data to recognize the user's emotional state. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects changes in emotion from the post content and provides that information to the generation AI.

[1287] Active Support Starts

[1288] If an abnormality is detected, the AI ​​generates an appropriate support message such as "Are you OK? We can help you," and sends it to the user's device via the server. The user can receive this message and receive support.

[1289] Escalation and Human Support

[1290] If the situation is deemed difficult to deal with or the risk is high, the generating AI will send an SOS notification to the server, which will then notify a professional counselor. For example, if the emotion engine's analysis determines the risk level to be 8, the server will automatically notify a counselor, who will then contact the user directly to provide support.

[1291] How the Emotional Engine Works

[1292] The emotion engine analyzes the user's voice, facial expressions, and text data. For example, if a user says through the app, "I haven't been able to sleep lately," the emotion engine analyzes the tone of the voice and facial expressions to detect signs of stress or anxiety. Similarly, if a user frequently tweets negative phrases on social media, such as "I want to die" or "I'm so tired," the emotion engine can recognize their emotions from the text data.

[1293] By combining generative AI and an emotion engine, this system can more accurately grasp the user's psychological state, enabling 24-hour anomaly detection and support. When an anomaly is detected, appropriate messages and countermeasures are immediately displayed, and human support is also provided if necessary.

[1294] In this way, the present invention provides a more advanced and effective counseling system for preventing suicide among young people.

[1295] The processing flow will be explained below.

[1296] Step 1:

[1297] Users download a smartphone app and enter their personal information and health check results, including details such as name, age, gender, and health score.

[1298] Step 2:

[1299] The terminal sends the information entered by the user to the server, which stores the received information in a database and completes user registration.

[1300] Step 3:

[1301] The device periodically collects the user's social media posts and search history, including data from the social networking services and search engines that the user regularly uses.

[1302] Step 4:

[1303] The device sends the collected data to the server, which then passes it to the generation AI and begins data analysis.

[1304] Step 5:

[1305] The server's generation AI analyzes specific dangerous keywords (e.g., "I want to die," "suicide," "painful," etc.) and detects abnormalities. If an abnormality is detected, the generation AI sends an "anomaly detected" flag to the server.

[1306] Step 6:

[1307] The device collects voice data from the user, and when the user speaks to the app, the device sends the voice data to the server.

[1308] Step 7:

[1309] The server receives the voice data and the emotion engine analyzes it to recognize the user's emotional state from the tone of the voice and the choice of words.

[1310] Step 8:

[1311] The emotion engine on the server uses facial recognition technology to analyze the user's facial expressions. If the user is using a camera, the device sends image data to the server, which then analyzes the facial expressions.

[1312] Step 9:

[1313] The emotion engine feeds back the results of its analysis to the generative AI, which then uses the feedback from the emotion engine to further detect anomalies.

[1314] Step 10:

[1315] The server's generation AI receives the "anomaly detected" flag and generates an appropriate support message as needed. The server then sends the message to the device.

[1316] Step 11:

[1317] The device will notify the user of a support message from the generated AI, and the user can receive the message and take appropriate action according to the instructions.

[1318] Step 12:

[1319] If the AI ​​determines that a situation is difficult to resolve or that the risk is high, it will send an SOS notification to the server, which will then automatically send the SOS notification to a professional counselor.

[1320] Step 13:

[1321] A professional counselor receives the notification from the server and contacts the user directly to provide specific support. The counselor understands the user's situation and provides professional counseling as needed.

[1322] This is the specific processing flow of the system, which will provide 24-hour counseling support aimed at preventing suicide among young people.

[1323] Example 2

[1324] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1325] The problem that this invention aims to solve is to accurately grasp the user's psychological state and provide immediate and appropriate support in an advanced counseling system aimed at preventing suicide among young people. Current systems are unable to fully analyze the user's emotional state, and there is a risk that abnormalities will be overlooked. Another problem is the lack of a means to respond quickly when expert support is needed.

[1326] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's social networking service posts and search history, means for analyzing specific risky keywords from the collected data and analyzing the emotional state using an emotion engine to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, and means for sending a notification to an expert when it is difficult to respond or the risk is high. This makes it possible to analyze the collected data and the analysis results of the emotion engine using a generative artificial intelligence model, and when an abnormality is detected, the generative artificial intelligence model can generate an appropriate support message and notify the user.

[1327] "Personal information" refers to information that can individually identify a user, such as the user's name, age, gender, address, and contact details.

[1328] "Medical checkup results" are data indicating the user's health condition, and include results obtained from a medical checkup conducted at a medical institution.

[1329] "Social networking service posts" are information such as text, images, and videos that users publish and share on social networking services (SNS).

[1330] "Search History" is the history of search queries made by a user using an internet search engine.

[1331] "Dangerous keywords" are specific words that are judged to indicate an abnormality in the user's psychological state or behavior, and include negative expressions such as "I want to die" and "It's painful."

[1332] An "emotion engine" is a technology that analyzes a user's voice, facial expressions, and text data to recognize their emotional state (for example, joy, sadness, anger, etc.).

[1333] "Abnormal" refers to a situation that is different from the normal psychological state of the user, and particularly includes risky behavior and serious changes in mental state.

[1334] A "support message" is a message for assistance provided to a user when an abnormality is detected, and includes, for example, content such as "Are you OK? Please talk to us."

[1335] An "expert" is a professional who can respond to users' psychological and mental problems, such as a counselor or doctor with specialized knowledge and experience in psychology or psychiatry.

[1336] A "generative artificial intelligence model" is an artificial intelligence technology that analyzes collected data and performs specific tasks (such as detecting anomalies or generating support messages).

[1337] This invention is an advanced counseling system aimed at preventing suicide among young people, utilizing generative AI (generative artificial intelligence) and an emotion engine. The system is primarily composed of three main components: the user, the terminal, and the server.

[1338] Overall structure

[1339] Users access the system through a smartphone app and enter their personal information and health checkup results. The device sends this information to a server, which stores it in a database. The device also periodically collects the user's social media posts and search history and sends them to the server. Inside the server, the generative AI analyzes this data and the emotion analysis results from the emotion engine, and if it detects an abnormality, it sends a support message to the user. Furthermore, if it is deemed difficult to respond or high risk, the generative AI will notify an expert, who will provide more specialized support.

[1340] Hardware and Software Configuration

[1341] Device: The user's smartphone or computer, on which the smartphone application is installed.

[1342] Server: Use a cloud or on-premise server to run a database management system (e.g. MySQL), generative AI models (e.g. GPT series), and sentiment engines (e.g. Amazon Comprehend on AWS or Sentiment Analysis on Google Cloud).

[1343] Database: Stores users' personal information, health check results, collected SNS posts, and search history.

[1344] Program processing

[1345] The device sends personal information and health check results entered by the user to a server. The server receives this information and stores it in a database. The device then periodically collects the user's social media posts and search history and sends them to the server. Within the server, this data is analyzed by the generative AI and emotion engine. For example, if a user posts on social media that "school is hard" or "I feel like I want to die," the emotion engine detects this change in emotion and provides that information to the generative AI.

[1346] The generating AI detects anomalies based on the analysis results, and if an anomaly is detected, it generates a support message such as "Are you OK? We can help you," and sends it to the user's device via the server. Furthermore, if the risk is deemed high, the generating AI sends an SOS notification to an expert via the server. The expert receives this notification and contacts the user directly to provide professional support.

[1347] Specific examples

[1348] If a user types "School has been tough lately and I can't sleep" into the app as "Kenji Suzuki," the emotion engine analyzes the text data and detects signs of stress or anxiety. As a result, the generative AI generates a message saying, "It seems like things are going to be tough at school. Why don't you try counseling?" and sends it to the user's device. The user can receive this message and receive support as needed.

[1349] Prompt Sentence Examples

[1350] "Analyze the text 'I feel like dying' posted by a user on social media and generate an appropriate support message."

[1351] "Analyze user voice data to detect signs of stress and anxiety."

[1352] "Save user registration information and health check results in a database."

[1353] This system combines generative AI and an emotion engine to accurately and quickly grasp the user's psychological state, and is capable of detecting anomalies and providing support 24 hours a day. When an anomaly is detected, appropriate messages and countermeasures are immediately presented, and expert support is also provided as needed, providing a more effective counseling system.

[1354] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1355] Step 1: User registration and data submission

[1356] Description: The user downloads a smartphone app and enters personal information (such as name, age, and gender) and health checkup results on the app's registration screen.

[1357] Specific behavior:

[1358] Input: The user enters their name, age, gender, and health check results into the app.

[1359] Data processing: The device converts the input information into an appropriate format.

[1360] Output: The device sends data to the server.

[1361] Server: Stores the received data in a database. For example, if a user enters "Taro Yamada," "20-year-old male," and "mental health score 5," this information will be saved in the database.

[1362] Step 2: Collect social media posts and search history

[1363] Description: The device periodically collects the user's social media posts and search history.

[1364] Specific behavior:

[1365] Input: The device retrieves the user's social media icon and search query.

[1366] Data collection: The device uses social media APIs to obtain post content and search history using search engine APIs.

[1367] Output: Send the collected data to the server.

[1368] Server: Stores received SNS posts and search history in an analytical database. This data collection is performed automatically in the background once a day.

[1369] Step 3: Data analysis and anomaly detection

[1370] Description: The server's generative AI model and emotion engine analyze the user's emotional state from collected data and detect anomalies.

[1371] Specific behavior:

[1372] Input: Collected social media posts, search history data, voice data, and facial expression data.

[1373] Data analysis: Generative AI detects dangerous keywords through text analysis, and the emotion engine analyzes psychological states from voice and facial expressions.

[1374] Output: Report anomaly detection. For example, if a user posts "I want to die" and the voice has a low tone, the generative AI and emotion engine will determine this as an anomaly.

[1375] Step 4: Send a support message

[1376] Description: If an abnormality is detected, the server's generation AI will generate an appropriate support message and notify the user.

[1377] Specific behavior:

[1378] Input: Data of abnormal presentation.

[1379] Message generation: The generation AI generates a support message for the user.

[1380] Output: The generated support message.

[1381] Server: Sends a message to the user's device. For example, generate a message saying "Are you okay? We're here to help you." and send it as a push notification to the device.

[1382] Step 5: Escalation and Specialized Support

[1383] Description: If the risk is deemed high, the server-generated AI will send an SOS notification to an expert.

[1384] Specific behavior:

[1385] Input: Sentiment engine analysis results and risk assessment.

[1386] Risk assessment: Generative AI assesses the risk level and quantifies the danger.

[1387] Output: SOS notification to the expert.

[1388] Server: If the risk level is high, a notification is sent to a counselor, who will contact the user and provide professional support. For example, if the risk level is determined to be 8, the server automatically notifies a counselor, who will provide support via phone or video chat.

[1389] (Application example 2)

[1390] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1391] Conventional counseling systems have difficulty accurately grasping a user's psychological state, making it difficult to detect abnormalities early and provide appropriate support. In particular, to prevent suicide among young people, advanced analytical technology that can detect subtle abnormalities that appear in social media posts and search history is needed. There is also a need for a system that can grasp a user's psychological state through the usage history of online sales systems and respond quickly.

[1392] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1393] In this invention, the server includes means for receiving personal information and health checkup results entered by the user, means for periodically collecting the user's SNS posts and search history, means for analyzing specific risk keywords from the collected data to detect abnormalities, means for generating an appropriate support message and notifying the user when an abnormality is detected, means for sending a notification to an expert when it is difficult to respond or when the risk is high, means for collecting the usage history of the online sales system and analyzing the user's psychological state, and means for monitoring the user's psychological state in real time using an emotion engine. This makes it possible to more accurately grasp the user's psychological state, detect abnormalities early, and provide appropriate support.

[1394] "Personal information" refers to information that identifies an individual, such as name, age, and gender.

[1395] "Medical examination results" are medical information based on the medical examinations that the user has undergone, and are data that indicate the user's health condition.

[1396] "SNS posts" are content such as text, images, and videos that users post to social networking services.

[1397] "Search history" is a record of searches a user has conducted on an Internet search engine.

[1398] "Danger keywords" are specific words or phrases that indicate suicide or serious mental illness.

[1399] A "support message" is a message sent to support the user's psychological state.

[1400] An "expert" is a professional with advanced knowledge and experience in psychological counseling and mental health.

[1401] An "online sales system" is an electronic commerce system that sells products and services over the Internet.

[1402] "Usage history" is a record of purchases and browsing made by a user in the online sales system.

[1403] An "emotion engine" is software or a system for analyzing emotions from a user's text, voice, facial expressions, etc.

[1404] "Real-time monitoring" means constantly and instantly monitoring the user's psychological state.

[1405] This invention is an advanced counseling system that monitors the user's psychological state and provides support at the appropriate time. The system is mainly composed of three main components: a server, a terminal, and a user.

[1406] User registration and data acquisition

[1407] First, users install the smartphone app and create an account. Through the app, users enter personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This information is sent from the device to the server, which then stores it in a database.

[1408] Collection of social media posts and search history

[1409] The device periodically collects the user's social media posts and search history and sends them to a server. All collected data is stored in the server's database. The server uses this data to analyze the user's psychological state in real time.

[1410] Detecting anomalies and sending support messages

[1411] The server analyzes the collected data using a generation AI. The generation AI analyzes specific risky keywords, and an emotion engine evaluates the user's emotional state based on social media posts and search history. If an abnormality is detected, the generation AI generates an appropriate support message and sends it to the user's device via the server.

[1412] For example, if a user posts on social media, "I'm tired" or "Everything seems pointless," the emotion engine analyzes the post and detects negative emotions. The generative AI then generates a support message saying, "Are you okay? We're here to help," and sends it to the user.

[1413] Escalation and human support coordination

[1414] If an abnormality is detected and a high risk is deemed to exist, the generating AI will send an SOS notification to the server, which will then notify experts (psychological counselors and mental health professionals) who will then contact the user directly to provide support.

[1415] Hardware and Software Use

[1416] Hardware: smartphones, servers, databases

[1417] Software: Application frameworks (e.g., React Native), generative AI (e.g., OpenAI's GPT model), sentiment analysis engines (e.g., IBM Watson)

[1418] The generative AI model operates by inputting a prompt sentence. An example of a prompt sentence is shown below.

[1419] Example prompt sentence:

[1420] "Analyze the user's recent emotional state from their social media posting history, detect negative keywords, and generate supportive messages."

[1421] This system will enable constant monitoring of the user's psychological state, detect abnormalities early, and provide support, which is expected to help prevent suicide and maintain psychological health among young people.

[1422] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1423] Step 1:

[1424] The user installs the smartphone app and creates an account. The user enters personal information (such as name, age, and gender), health check results, and usage history of the online sales system. This data is sent from the device to the server, which stores it in a database. The input data is in text format and is saved as output in the database. Specifically, the information entered by the user, such as "Taro Yamada," "20 years old," and "male," is registered in the database.

[1425] Step 2:

[1426] The device periodically collects the user's SNS posts and search history and sends them to the server. The collected data is stored in the server's database. The input data is a text record of the user's SNS posts and search history, and is stored in the server's database as output. Specifically, the content of posts made by the user on SNS such as "School is hard" is periodically collected and sent to the server.

[1427] Step 3:

[1428] The server analyzes the collected data using a generative AI model. Input data includes the user's social media posts, search history, and health checkup results, and specific dangerous keywords are detected through text analysis using the generative AI model. The result of this analysis is the user's emotional state. Specifically, the analysis is performed by inputting the prompt statement "Analyze the user's recent emotional state from their social media posting history and detect negative keywords" into the generative AI.

[1429] Step 4:

[1430] If an abnormality is detected, an appropriate support message is generated using a generative AI model. The input data is the analyzed emotional state, and an automatically generated support message is output. This generated support message is sent from the server to the user's device. Specifically, if a negative emotion is detected, a message is generated saying, "Are you okay? We're here to help you," and sent to the user.

[1431] Step 5:

[1432] If the risk is high, the generative AI model sends an SOS notification to the server. The input data is the emotion analysis results and risk assessment results, and the output is an SOS notification sent to an expert. The server receives this notification and contacts a psychological counselor or mental health professional. Specifically, if the risk level is determined to be high, a notification is sent to the counselor saying, "Contact an expert for support."

[1433] As a result, it is possible to monitor the user's psychological state in real time and provide appropriate support promptly when an abnormality is detected.

[1434] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1435] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1436] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1437] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1438] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1439] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1440] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1441] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1442] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1443] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1444] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1445] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1446] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1447] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[1448] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1449] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1450] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1451] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1452] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1453] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1454] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1455] The following is further disclosed regarding the above embodiment.

[1456] (Claim 1)

[1457] A means for receiving personal information and health examination results input by a user;

[1458] A means of periodically collecting users' SNS posts and search history;

[1459] A method for detecting abnormalities by analyzing specific risk keywords from collected data;

[1460] means for generating an appropriate support message and notifying the user when an abnormality is detected;

[1461] a means of notifying professional counselors in difficult or high-risk situations;

[1462] A system including:

[1463] (Claim 2)

[1464] The system of claim 1, wherein generative artificial intelligence is used to analyze the collected data.

[1465] (Claim 3)

[1466] 2. The system according to claim 1, further comprising a means for receiving consultation content from a user, the generating artificial intelligence analyzing the content and providing appropriate advice.

[1467] "Example 1"

[1468] (Claim 1)

[1469] A means for receiving personal information and health examination results input by a user;

[1470] A means for periodically collecting users' social networking service posting and search history;

[1471] A method for detecting abnormalities by analyzing specific risk keywords from collected data;

[1472] means for generating an appropriate support message and notifying the user when an abnormality is detected;

[1473] A means to notify experts when a situation is difficult or high risk;

[1474] A means for encrypting the collected data and transmitting it to a server; and

[1475] The system includes means for sending appropriate prompt sentences to the generative AI model based on the analysis results.

[1476] (Claim 2)

[1477] The system of claim 1, wherein generative artificial intelligence is used to analyze the collected data.

[1478] (Claim 3)

[1479] 2. The system according to claim 1, further comprising a means for receiving consultation content from a user, the generating artificial intelligence analyzing the content and providing appropriate advice.

[1480] "Application Example 1"

[1481] (Claim 1)

[1482] A means for receiving personal information and health examination results input by a user;

[1483] A means of periodically collecting users' SNS posts and search history;

[1484] A method for detecting abnormalities by analyzing specific risk keywords from collected data;

[1485] means for generating an appropriate support message and notifying the user when an abnormality is detected;

[1486] A means to notify experts when a situation is difficult or high risk;

[1487] A means of collecting data via devices to monitor user actions and statements in real time;

[1488] A method to analyze data collected in real time using artificial intelligence to detect abnormalities,

[1489] A means for instantly generating and notifying prompt sentences based on the collected and analyzed data;

[1490] A system including:

[1491] (Claim 2)

[1492] The system of claim 1, wherein generative artificial intelligence is used to analyze the collected data.

[1493] (Claim 3)

[1494] 2. The system according to claim 1, further comprising a means for receiving consultation content from a user, the generating artificial intelligence analyzing the content and providing appropriate advice.

[1495] "Example 2: Combining Emotion Engines"

[1496] (Claim 1)

[1497] A means for receiving personal information and health examination results input by a user;

[1498] A means for periodically collecting users' social networking service posting and search history;

[1499] A means for analyzing specific dangerous keywords from the collected data and analyzing the emotional state using an emotion engine to detect abnormalities;

[1500] means for generating an appropriate support message and notifying the user when an abnormality is detected;

[1501] A means to notify experts when a situation is difficult or high risk;

[1502] A system including:

[1503] (Claim 2)

[1504] 10. The system of claim 1, wherein the collected data and the emotion engine's analysis results are analyzed using a generative artificial intelligence model.

[1505] (Claim 3)

[1506] 2. The system of claim 1, further comprising means for the generative artificial intelligence model to generate an appropriate support message and notify the user when an anomaly is detected.

[1507] "Application example 2 when combining emotion engines"

[1508] (Claim 1)

[1509] A means for receiving personal information and health examination results input by a user;

[1510] A means of periodically collecting users' SNS posts and search history;

[1511] A method for detecting abnormalities by analyzing specific risk keywords from collected data;

[1512] means for generating an appropriate support message and notifying the user when an abnormality is detected;

[1513] A means to notify experts when a situation is difficult or high risk;

[1514] A means for collecting usage history of an online sales system and analyzing psychological states;

[1515] A means of monitoring the user's psychological state in real time using an emotion engine;

[1516] A system including:

[1517] (Claim 2)

[1518] The system of claim 1, wherein generative artificial intelligence is used to analyze the collected data.

[1519] (Claim 3)

[1520] 2. The system according to claim 1, further comprising a means for receiving consultation content from a user, the generating artificial intelligence analyzing the content and providing appropriate advice. [Explanation of symbols]

[1521] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. A means for receiving personal information and health examination results input by a user; A means of periodically collecting users' SNS posts and search history; A method for detecting abnormalities by analyzing specific risk keywords from collected data; means for generating an appropriate support message and notifying the user when an abnormality is detected; a means of notifying professional counselors in difficult or high-risk situations; A system including:

2. 10. The system of claim 1, wherein generative artificial intelligence is used to analyze the collected data.

3. 2. The system according to claim 1, further comprising means for receiving consultation content from a user, the generating artificial intelligence analyzing the content and providing appropriate advice.

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