System

Abstract

An object of a system according to an embodiment is to analyze a skin condition and a mental health condition of a user and provide appropriate support.SOLUTION: A system includes an analysis unit, an interaction unit, an advice providing unit, a tracking unit, and a community promotion unit. The analysis unit analyzes a skin condition and a mental health condition of the user using the generated AI. The interaction unit provides an environment in which the user can anonymously interact on the basis of the result analyzed by the analysis unit. The advice providing unit provides the custom advice and the resource on the basis of the information collected by the interaction unit. The tracking unit tracks the user's emotion and state on the basis of the advice provided by the advice providing unit. The community promotion part promotes the unification of the communities of the users based on the data tracked by the tracking part.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] Conventional technology has had the problem of not being able to comprehensively analyze a user's skin condition and mental health and provide appropriate support.

[0005] The system according to the embodiment aims to analyze the skin condition and mental health condition of the user and provide appropriate support. [Means for solving the problem]

[0006] The system according to the embodiment includes an analysis unit, a dialogue unit, an advice providing unit, a tracking unit, and a community promotion unit. The analysis unit uses generative AI to analyze a user's skin condition and mental health state. The dialogue unit provides an environment in which users can interact anonymously based on the results of the analysis by the analysis unit. The advice providing unit provides custom advice and resources based on the information collected by the dialogue unit. The tracking unit tracks the user's emotions and state based on the advice provided by the advice providing unit. The community promotion unit promotes community cohesion among users based on the data tracked by the tracking unit. [Effects of the Invention]

[0007] The system according to the embodiment can analyze the skin condition and mental health of the user and provide appropriate support. [Brief explanation of the drawings]

[0008] [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. DETAILED DESCRIPTION OF THE INVENTION

[0009] 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.

[0010] First, the terms used in the following description will be explained.

[0011] 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, the 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), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0012] 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.

[0013] 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.

[0014] 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), and Bluetooth (registered trademark).

[0015] 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."

[0016] [First embodiment] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0017] 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.

[0018] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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).

[0019] 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.

[0020] The reception device 38 includes a touch panel 38A and a microphone 38B, and receives user input. The touch panel 38A detects contact with a pointer (for example, a pen or a finger) to receive user input by the touch of the pointer. 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 (see FIG. 2) acquires the data indicating the user input.

[0021] Output device 40 includes a display 40A and a speaker 40B, and presents data to a user by outputting the data in a form of expression that the user can perceive (e.g., audio and / or text). Display 40A displays visible information such as text and images in accordance with instructions from processor 46. Speaker 40B outputs audio in accordance with instructions from processor 46. 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.

[0022] 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.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0024] 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.

[0025] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0026] In the smart device 14, the specific processing is performed by the processor 46. The storage 50 stores a specific processing program 60. The specific processing program 60 is used together with the specific processing program 56 by the data processing system 10. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the smart device 14 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0027] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device (e.g., a generation server) may have the data generation model 58. In this case, the data processing device 12 obtains a processing result (prediction result, etc.) using the data generation model 58 by communicating with the server device having the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device owned by a user (e.g., a mobile phone, a robot, a home appliance, etc.). Next, an example of processing by the data processing system 10 according to the first embodiment will be described.

[0028] (Example 1) The support system according to the embodiment of the present invention is a system that links skin condition and mental health and effectively conveys user feedback. As a result, the support system comprehensively manages the user's skin condition and mental health, allowing the user to receive support with peace of mind.

[0029] A support system according to an embodiment includes an analysis unit, a dialogue unit, an advice provision unit, a tracking unit, and a community promotion unit. The analysis unit uses a generation AI to analyze a user's skin condition and mental health. For example, if the user's dry skin or inflammation is related to stress or anxiety, the generation AI analyzes the relationship and provides feedback to the user. The generation AI also performs analysis based on prompts containing data on the user's skin condition and information on their mental health. The dialogue unit provides an environment in which users can anonymously converse based on the results of the analysis by the analysis unit. For example, when a user talks about mental worries or skin problems, the generation AI generates appropriate responses, giving the user a sense of security. The generation AI also generates responses based on prompts containing the user's worries and questions. The advice provision unit provides custom advice and resources based on the information collected by the dialogue unit. For example, the generation AI suggests appropriate skin care products and relaxation methods based on the user's skin condition and mental health. The generation AI also generates advice based on prompts containing information on the user's skin condition and mental health. The tracking unit tracks the user's emotions and condition based on the advice provided by the advice providing unit. For example, the generation AI analyzes the data by having the user record their daily emotions and skin condition, and tracks changes in the user. The generation AI also performs analysis based on prompts containing data related to the user's emotions and skin condition. The community promotion unit promotes community cohesion among users based on the data tracked by the tracking unit. For example, the generation AI matches users with the same concerns and provides a forum for information exchange and support. The generation AI also performs matching based on prompts containing information related to the user's concerns and interests. As a result, the support system according to the embodiment comprehensively manages the user's skin condition and mental health, allowing them to receive support with peace of mind. For example, the system can understand the impact of skin problems on mental health and take appropriate measures. Furthermore, through anonymous conversations and customized advice, users can find skin care methods that suit them.Additionally, emotion and state tracking allows users to understand their own changes and share information with other users through community bonding.

[0030] When analyzing a user's skin condition and mental health, the analysis unit can take seasonal and weather changes into account to perform a more precise analysis. For example, when using generation AI to analyze a user's skin condition and mental health, the analysis unit incorporates seasonal and weather changes as data and reflects them in the analysis results. For example, it analyzes the effects of dry winter weather and humidity in summer on skin and mental health. In addition, to perform analysis that takes seasonal and weather changes into account, weather data is acquired in real time and input into the generation AI. For example, it analyzes the relationship between skin and mental health based on data such as temperature, humidity, and UV levels. Furthermore, based on the analysis results that take seasonal and weather changes into account, it provides the user with seasonal skin care and mental care advice. For example, it recommends moisturizing care in winter and UV protection in summer. This allows for analysis that takes seasonal and weather changes into account to provide more precise analysis results.

[0031] The analysis unit can analyze the relationship with the user's lifestyle habits (diet, exercise, sleep) and provide comprehensive health advice. For example, the analysis unit uses a generation AI to analyze the user's skin condition and mental health state, and then analyzes the relationship with lifestyle habits such as diet, exercise, and sleep based on that data. For example, it analyzes the impact of dietary content on skin condition and mental health. In addition, by collecting the user's lifestyle data and inputting it into the generation AI, it analyzes the relationship between skin and mental health. For example, it analyzes the impact of exercise frequency and sleep duration on skin condition and mental health. In addition, based on the results of analyzing the relationship with lifestyle habits, it provides the user with comprehensive health advice. For example, it recommends a balanced diet, moderate exercise, and sufficient sleep. In this way, comprehensive health advice can be provided by analyzing the relationship with lifestyle habits.

[0032] The analysis unit can link the pet's health condition with the user's mental health condition to provide a support system that integrates pet care and mental care. For example, the analysis unit uses a generation AI to analyze the pet's health condition and the user's mental health condition, and provides a support system that integrates pet care and mental care based on that data. For example, the analysis unit analyzes the impact of the pet's health condition on the user's mental health. Furthermore, by collecting pet health data and user mental health data and inputting them into the generation AI, the analysis unit analyzes the relationship between the two. For example, the analysis unit analyzes the impact of pet illness and stress on the user's mental health. Furthermore, to provide a support system that integrates pet care and mental care, the analysis unit generates advice for the user based on the pet's health condition. For example, the analysis unit recommends methods for managing the pet's health and methods for reducing the user's stress. This allows the provision of a support system that integrates pet care and mental care to support the health of both the user and the pet.

[0033] When analyzing a user's skin condition and mental health, the analysis unit can also incorporate at least one of emotional data from music or art to analyze the relationship between emotion and health. For example, the analysis unit incorporates emotional data from music, art, etc. when analyzing a user's skin condition and mental health using a generative AI. For example, it analyzes the impact of the rhythm of music or the colors of art on skin and mental health. Furthermore, by collecting emotional data and inputting it into the generative AI, it analyzes the relationship between skin and mental health. For example, it analyzes the impact of the music a user listens to or the art a user views on skin condition and mental health. Furthermore, based on the results of the analysis of the relationship between emotion and health, it provides the user with health advice utilizing the emotional data. For example, it recommends relaxing music or soothing art. In this way, incorporating emotional data enables more comprehensive health analysis.

[0034] The dialogue unit can analyze the content of the user's dialogue and generate a more appropriate response based on the tone and wording of the dialogue. The dialogue unit, for example, uses a generation AI to analyze the content of the user's dialogue and generate an appropriate response based on the tone and wording of the dialogue. For example, a relaxed response is generated for a dialogue in a gentle tone. In addition, to analyze the content of the user's dialogue, text data is collected and input into the generation AI. For example, the tone and wording of the dialogue is analyzed and an appropriate response is generated based on the results. In addition, to generate a response based on the tone and wording of the dialogue, the generation AI provides a customized response based on the analysis results. For example, a response that shows empathy is generated for an emotional dialogue. In this way, more appropriate support can be provided to the user by generating a response based on the tone and wording of the dialogue.

[0035] The dialogue unit can provide a consistent response by taking into account the user's past dialogue history. For example, when analyzing the content of a user's dialogue using a generation AI, the dialogue unit can also take into account the past dialogue history and provide a consistent response. For example, the dialogue unit generates a response related to the current dialogue by referring to the content of the past dialogue. In addition, a consistent response can be provided by collecting the user's past dialogue history and inputting it into the generation AI. For example, a response appropriate for the current dialogue is generated based on the content of the past dialogue. In addition, in order to provide a response that takes into account the past dialogue history, the generation AI provides a customized response based on the analysis results. For example, specific advice for the user's concerns is provided based on the content of the past dialogue. In this way, a consistent response can be provided by taking into account the past dialogue history.

[0036] The dialogue unit, when providing an environment where users can converse anonymously, can also support dialogue between different languages, thereby promoting international communication. For example, the dialogue unit uses a generation AI to support dialogue between different languages ​​when providing an environment where users can converse anonymously. For example, it translates dialogue between English and Japanese in real time. In addition, to support dialogue between different languages, the generation AI is equipped with a multilingual translation function. For example, it automatically translates text entered by the user and conveys it to the other person. In addition, to promote international communication, the generation AI enables smooth dialogue between different languages. For example, it provides translations that take cultural nuances into account. This supports dialogue between different languages, thereby promoting international communication.

[0037] When providing an environment in which users can converse anonymously, the dialogue unit can visualize the content of the dialogue and provide responses that are visually easy to understand. When providing an environment in which users can converse anonymously, the dialogue unit, for example, uses a generation AI to visualize the content of the dialogue. For example, the main points of the dialogue are displayed in diagrams or graphs. In addition, to visualize the content of the dialogue, the generation AI is equipped with a visualization function. For example, the flow of the dialogue is displayed in a flowchart. In addition, in order to provide responses that are visually easy to understand, the generation AI generates visualized responses based on the analysis results. For example, the content of the dialogue is represented using illustrations or icons. In this way, by visualizing the content of the dialogue, it is possible to provide responses that are visually easy to understand.

[0038] The advice providing unit can propose individual meal plans and exercise plans based on the user's skin condition and mental health condition. The advice providing unit, for example, uses a generation AI to propose individual meal plans based on the user's skin condition and mental health condition. For example, a meal plan including nutrients to prevent dry skin is proposed. The advice providing unit also analyzes the user's skin condition and mental health condition and proposes an individual exercise plan based on that data. For example, an exercise plan including yoga and meditation for stress reduction is proposed. In addition, to propose individual meal plans and exercise plans, the generation AI provides customized advice based on the analysis results. For example, it suggests meals and exercises that are tailored to the user's lifestyle habits. This allows the system to comprehensively support the user's health by proposing individual meal plans and exercise plans.

[0039] The advice providing unit can provide more personalized advice by taking into account the user's genetic information. The advice providing unit, for example, uses a generation AI to provide custom advice that takes into account the user's genetic information. For example, appropriate skin care products are suggested for a user who is genetically prone to sensitive skin. In addition, more personalized advice is provided by collecting the user's genetic information and inputting it into the generation AI. For example, stress management methods are suggested for a user who is genetically prone to stress. In addition, in order to provide custom advice that takes into account genetic information, the generation AI provides customized advice based on the analysis results. For example, diet and exercise suggestions are made based on genetic factors. In this way, more personalized advice can be provided by taking genetic information into account.

[0040] The advice providing unit can provide customized pet care advice based on the health condition of the user's pet. The advice providing unit uses, for example, a generation AI to provide customized pet care advice based on the health condition of the user's pet. For example, it may propose a diet and exercise plan for the pet. In addition, the customized pet care advice is provided by collecting health data of the pet and inputting it into the generation AI. For example, it may propose disease prevention and health management methods for the pet. In addition, to provide the customized pet care advice, the generation AI provides customized advice based on the analysis results. For example, it may suggest diet and exercise plans tailored to the pet's health condition. This makes it possible to support pet care by providing customized advice based on the pet's health condition.

[0041] The advice providing unit can suggest appropriate travel destinations and activities based on the user's skin condition and mental health state. The advice providing unit, for example, uses a generation AI to suggest appropriate travel destinations based on the user's skin condition and mental health state. For example, it may recommend relaxing hot spring resorts or places rich in nature. It may also analyze the user's skin condition and mental health state and suggest appropriate activities based on that data. For example, it may recommend a yoga retreat or meditation workshop to reduce stress. In addition, to suggest travel destinations and activities, the generation AI provides customized advice based on the analysis results. For example, it may suggest travel plans and activities tailored to the user's health state. This can help the user feel refreshed by suggesting travel destinations and activities based on the user's skin condition and mental health state.

[0042] When tracking a user's emotions and state, the tracking unit also analyzes the user's voice data and facial expression data, enabling more precise tracking. For example, when using a generation AI to track a user's emotions and state, the tracking unit analyzes voice data and facial expression data. For example, it analyzes changes in the user's voice tone and facial expression to track their emotional state. It also tracks emotions and states by collecting the user's voice data and facial expression data and inputting it into the generation AI. For example, it analyzes subtle changes in voice intonation and facial expressions to understand their emotional state. It also provides the user with advice on emotional and health management based on the results of analyzing the voice data and facial expression data. For example, it suggests relaxation methods if stress is increasing. This enables more precise tracking by analyzing voice data and facial expression data.

[0043] The tracking unit can analyze the user's long-term health trends based on the tracked data and provide preventative advice. The tracking unit, for example, uses a generation AI to track the user's emotions and condition and analyze long-term health trends based on that data. For example, it analyzes emotional fluctuations and changes in skin condition over a long period of time. It also collects tracking data and inputs it into the generation AI to analyze the user's long-term health trends. For example, it predicts future health risks based on past data. It also provides preventative advice to the user based on the results of analyzing long-term health trends. For example, it suggests taking appropriate measures before health risks increase. In this way, it is possible to provide preventative advice by analyzing long-term health trends.

[0044] The tracking unit can track the emotions and health of the user's pet and provide pet care advice. For example, the tracking unit uses a generation AI to track the emotions and health of the user's pet and provide pet care advice based on that data. For example, it analyzes the pet's stress and health and suggests appropriate care methods. In addition, to track the pet's emotions and health, the tracking unit collects pet behavioral data and health data and inputs it into the generation AI. For example, it analyzes the pet's activity level and dietary data to understand its health. In addition, based on the results of tracking the pet's emotions and health, it provides pet care advice to the user. For example, it suggests methods for reducing stress and managing the pet's health. In this way, the tracking unit can support the pet's health by tracking the pet's emotions and health and providing pet care advice.

[0045] When tracking the user's emotions and state, the tracking unit can also analyze the user's living environment (temperature, humidity, noise) and provide advice on improving the environment. For example, the tracking unit uses a generation AI to analyze living environment data when tracking the user's emotions and state. For example, it analyzes the impact of temperature, humidity, and noise levels on emotions and health. It also tracks emotions and states by collecting the user's living environment data and inputting it into the generation AI. For example, it monitors temperature, humidity, and noise levels in real time to understand emotions and health states. It also provides the user with advice on improving the environment based on the results of analyzing the living environment data. For example, it suggests appropriate temperature and humidity settings and noise control measures. In this way, it is possible to provide advice on improving the environment by analyzing the living environment.

[0046] The community promotion unit can match users with common hobbies and interests when promoting community cohesion between users. The community promotion unit, for example, uses a generation AI to match users with common hobbies and interests when promoting community cohesion between users. For example, it groups users with the same hobbies. Furthermore, by collecting data on users' hobbies and interests and inputting it into the generation AI, users with common hobbies and interests are matched. For example, groups are created based on hobbies and interests. Furthermore, to match users with common hobbies and interests, the generation AI provides customized matching based on the analysis results. For example, it suggests events and activities based on hobbies and interests. This makes it possible to promote community cohesion by matching users with common hobbies and interests.

[0047] The community promotion unit can analyze the content of the conversation between matched users and provide feedback to improve the quality of the conversation. The community promotion unit, for example, uses a generation AI to analyze the content of the conversation between matched users and provide feedback to improve the quality of the conversation. For example, it analyzes the tone and language of the conversation and suggests areas for improvement. In addition, the content of the conversation between users is collected and input into the generation AI to provide feedback to improve the quality of the conversation. For example, it analyzes the content of the conversation and provides advice to deepen empathy and understanding. In addition, in order to provide feedback to improve the quality of the conversation, the generation AI provides customized advice based on the analysis results. For example, it makes suggestions to make the flow of the conversation smoother. In this way, feedback that improves the quality of the conversation is provided, thereby smoothing communication between users.

[0048] The community promotion unit can match users with different cultural backgrounds and promote intercultural exchange. The community promotion unit, for example, uses a generation AI to match users with different cultural backgrounds and promote intercultural exchange. For example, it groups users from different countries or regions. It also matches users with different cultural backgrounds by collecting data on the users' cultural backgrounds and inputting it into the generation AI. For example, it creates groups based on cultural interests and experiences. In addition, to promote intercultural exchange, the generation AI provides customized matching based on the analysis results. For example, it suggests dialogues and activities between users with different cultural backgrounds. This makes it possible to promote intercultural exchange by matching users with different cultural backgrounds.

[0049] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0050] When analyzing a user's skin condition and mental health, the analysis unit can take the user's diet into account, allowing for more precise analysis. For example, the generation AI can be used to analyze the impact of the user's diet on their skin condition and mental health. In addition, by collecting the user's dietary data and inputting it into the generation AI, the relationship between skin and mental health can be analyzed. For example, if a specific nutrient is lacking, the impact can be analyzed and feedback provided to the user. Furthermore, based on the analysis results that take dietary content into account, advice on dietary improvement can be provided to the user. For example, the intake of vitamins and minerals can be recommended. This allows for more precise analysis results to be provided by taking dietary content into account.

[0051] When analyzing a user's skin condition and mental health, the analysis unit can take the user's exercise habits into account to perform a more precise analysis. For example, it uses a generation AI to analyze the impact of a user's exercise habits on their skin condition and mental health. It also collects the user's exercise data and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of lack of exercise on skin problems and mental disorders and provides feedback to the user. It also provides advice to the user on how to improve their exercise based on the analysis results that take exercise habits into account. For example, it recommends moderate exercise. This allows for more precise analysis results to be provided by taking exercise habits into account.

[0052] When analyzing a user's skin condition and mental health, the analysis unit can take the user's sleep patterns into account, allowing for more precise analysis. For example, the analysis unit uses a generation AI to analyze the impact of a user's sleep patterns on their skin condition and mental health. In addition, by collecting the user's sleep data and inputting it into the generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, it can analyze the impact of lack of sleep on skin problems and mental disorders and provide feedback to the user. In addition, based on the analysis results that take sleep patterns into account, it can provide the user with advice on improving their sleep. For example, it can recommend getting enough sleep. This allows for more precise analysis results to be provided by taking sleep patterns into account in the analysis.

[0053] When analyzing a user's skin condition and mental health, the analysis unit can take the user's living environment into account to perform a more precise analysis. For example, it uses a generation AI to analyze the impact of the user's living environment on their skin condition and mental health. It also collects data on the user's living environment and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of the temperature and humidity of the living environment on skin problems and mental disorders and provides feedback to the user. It also provides the user with advice on improving their environment based on the analysis results that take the living environment into account. For example, it recommends appropriate temperature and humidity settings. This allows for more precise analysis results to be provided by taking the living environment into account in the analysis.

[0054] When analyzing a user's skin condition and mental health, the analysis unit can take the user's social relationships into account, allowing for more precise analysis. For example, it uses a generation AI to analyze the impact of a user's social relationships on their skin condition and mental health. It also collects the user's social relationship data and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of loneliness and social stress on skin problems and mental disorders, and provides feedback to the user. It also provides the user with advice on improving their social relationships based on the analysis results that take social relationships into account. For example, it recommends participation in community activities. This allows for more precise analysis results to be provided by analysis that takes social relationships into account.

[0055] When analyzing a user's skin condition and mental health, the analysis unit can take the user's hobbies and interests into account, allowing for more precise analysis. For example, the analysis unit uses generation AI to analyze the impact of a user's hobbies and interests on their skin condition and mental health. In addition, by collecting the user's hobby and interest data and inputting it into generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, the analysis unit can analyze the impact of hobbies and interests on stress reduction and relaxation, and provide feedback to the user. In addition, based on the analysis results that take hobbies and interests into account, the analysis unit can provide advice to the user on how to utilize their hobbies and interests. For example, it can recommend hobbies that have a relaxing effect. This allows for analysis that takes hobbies and interests into account, allowing for more precise analysis results.

[0056] When analyzing a user's skin condition and mental health, the analysis unit can take the health condition of the user's pet into account, allowing for more precise analysis. For example, the analysis unit uses a generation AI to analyze the impact of the user's pet's health condition on the user's skin condition and mental health. In addition, by collecting the user's pet's health data and inputting it into the generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, the analysis unit can analyze the impact of the pet's illness or stress on the user's mental health and provide feedback to the user. In addition, based on the analysis results that take the pet's health condition into account, the analysis unit can provide the user with pet care advice. For example, the analysis unit can recommend health care methods for the pet. This allows for more precise analysis results to be provided by taking the pet's health condition into account.

[0057] The processing flow of the first embodiment will be briefly explained below.

[0058] Step 1: The analysis unit uses the generation AI to analyze the user's skin condition and mental health. For example, if the user's dryness or inflammation of the skin is related to stress or anxiety, the generation AI analyzes the relationship and provides feedback to the user. The generation AI also performs its analysis based on prompts containing data about the user's skin condition and information about their mental health. Step 2: The dialogue unit provides an environment where users can anonymously converse based on the results of the analysis by the analysis unit. For example, when a user talks about their mental worries or skin problems, the generation AI generates an appropriate response, giving the user a sense of security. The generation AI also generates a response based on prompts that include the user's worries and questions. Step 3: The advice provider provides custom advice and resources based on the information collected by the dialogue component. For example, the generator AI suggests appropriate skin care products and relaxation methods based on the user's skin condition and mental health. The generator AI also generates advice based on prompts containing information about the user's skin condition and mental health. Step 4: The tracking unit tracks the user's emotions and condition based on the advice provided by the advice providing unit. For example, the generation AI analyzes the data by having the user record their daily emotions and skin condition, and tracks changes in the user. The generation AI also performs analysis based on prompts containing data on the user's emotions and skin condition. Step 5: The community promotion unit promotes community cohesion among users based on the data tracked by the tracking unit. For example, the generation AI matches users with the same concerns and provides a place for them to exchange information and receive support. The generation AI also matches users based on prompts containing information about their concerns and interests.

[0059] (Example 2) The support system according to the embodiment of the present invention is a system that links skin condition and mental health and effectively conveys user feedback. As a result, the support system comprehensively manages the user's skin condition and mental health, allowing the user to receive support with peace of mind.

[0060] A support system according to an embodiment includes an analysis unit, a dialogue unit, an advice provision unit, a tracking unit, and a community promotion unit. The analysis unit uses a generation AI to analyze a user's skin condition and mental health. For example, if the user's dry skin or inflammation is related to stress or anxiety, the generation AI analyzes the relationship and provides feedback to the user. The generation AI also performs analysis based on prompts containing data on the user's skin condition and information on their mental health. The dialogue unit provides an environment in which users can anonymously converse based on the results of the analysis by the analysis unit. For example, when a user talks about mental worries or skin problems, the generation AI generates appropriate responses, giving the user a sense of security. The generation AI also generates responses based on prompts containing the user's worries and questions. The advice provision unit provides custom advice and resources based on the information collected by the dialogue unit. For example, the generation AI suggests appropriate skin care products and relaxation methods based on the user's skin condition and mental health. The generation AI also generates advice based on prompts containing information on the user's skin condition and mental health. The tracking unit tracks the user's emotions and condition based on the advice provided by the advice providing unit. For example, the generation AI analyzes the data by having the user record their daily emotions and skin condition, and tracks changes in the user. The generation AI also performs analysis based on prompts containing data related to the user's emotions and skin condition. The community promotion unit promotes community cohesion among users based on the data tracked by the tracking unit. For example, the generation AI matches users with the same concerns and provides a forum for information exchange and support. The generation AI also performs matching based on prompts containing information related to the user's concerns and interests. As a result, the support system according to the embodiment comprehensively manages the user's skin condition and mental health, allowing them to receive support with peace of mind. For example, the system can understand the impact of skin problems on mental health and take appropriate measures. Furthermore, through anonymous conversations and customized advice, users can find skin care methods that suit them.Additionally, emotion and state tracking allows users to understand their own changes and share information with other users through community bonding.

[0061] When analyzing a user's skin condition and mental health, the analysis unit can take seasonal and weather changes into account to perform a more precise analysis. For example, when using generation AI to analyze a user's skin condition and mental health, the analysis unit incorporates seasonal and weather changes as data and reflects them in the analysis results. For example, it analyzes the effects of dry winter weather and humidity in summer on skin and mental health. In addition, to perform analysis that takes seasonal and weather changes into account, weather data is acquired in real time and input into the generation AI. For example, it analyzes the relationship between skin and mental health based on data such as temperature, humidity, and UV levels. Furthermore, based on the analysis results that take seasonal and weather changes into account, it provides the user with seasonal skin care and mental care advice. For example, it recommends moisturizing care in winter and UV protection in summer. This allows for analysis that takes seasonal and weather changes into account to provide more precise analysis results.

[0062] The analysis unit can analyze the relationship with the user's lifestyle habits (diet, exercise, sleep) and provide comprehensive health advice. For example, the analysis unit uses a generation AI to analyze the user's skin condition and mental health state, and then analyzes the relationship with lifestyle habits such as diet, exercise, and sleep based on that data. For example, it analyzes the impact of dietary content on skin condition and mental health. In addition, by collecting the user's lifestyle data and inputting it into the generation AI, it analyzes the relationship between skin and mental health. For example, it analyzes the impact of exercise frequency and sleep duration on skin condition and mental health. In addition, based on the results of analyzing the relationship with lifestyle habits, it provides the user with comprehensive health advice. For example, it recommends a balanced diet, moderate exercise, and sufficient sleep. In this way, comprehensive health advice can be provided by analyzing the relationship with lifestyle habits.

[0063] The analysis unit can use the emotion estimation function to analyze the user's emotional state in real time and clarify the correlation with skin condition. For example, the analysis unit uses the emotion estimation function to analyze the user's emotional state in real time and clarify the correlation with skin condition based on the data. For example, it analyzes the effects of stress and anxiety on dry skin and inflammation. In addition, to analyze the user's emotional state in real time, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and the correlation with skin condition is analyzed. Furthermore, based on the results of analyzing the correlation between the emotional state and skin condition, advice on emotion management and skin care is provided to the user. For example, relaxation methods and skin care products to reduce stress are recommended. In this way, by clarifying the correlation between the emotional state and skin condition, more appropriate care can be provided.

[0064] The analysis unit can link the pet's health condition with the user's mental health condition to provide a support system that integrates pet care and mental care. For example, the analysis unit uses a generation AI to analyze the pet's health condition and the user's mental health condition, and provides a support system that integrates pet care and mental care based on that data. For example, the analysis unit analyzes the impact of the pet's health condition on the user's mental health. Furthermore, by collecting pet health data and user mental health data and inputting them into the generation AI, the analysis unit analyzes the relationship between the two. For example, the analysis unit analyzes the impact of pet illness and stress on the user's mental health. Furthermore, to provide a support system that integrates pet care and mental care, the analysis unit generates advice for the user based on the pet's health condition. For example, the analysis unit recommends methods for managing the pet's health and methods for reducing the user's stress. This allows the provision of a support system that integrates pet care and mental care to support the health of both the user and the pet.

[0065] When analyzing a user's skin condition and mental health, the analysis unit can also incorporate at least one of emotional data from music or art to analyze the relationship between emotion and health. For example, the analysis unit incorporates emotional data from music, art, etc. when analyzing a user's skin condition and mental health using a generative AI. For example, it analyzes the impact of the rhythm of music or the colors of art on skin and mental health. Furthermore, by collecting emotional data and inputting it into the generative AI, it analyzes the relationship between skin and mental health. For example, it analyzes the impact of the music a user listens to or the art a user views on skin condition and mental health. Furthermore, based on the results of the analysis of the relationship between emotion and health, it provides the user with health advice utilizing the emotional data. For example, it recommends relaxing music or soothing art. In this way, incorporating emotional data enables more comprehensive health analysis.

[0066] The analysis unit can use the emotion estimation function to analyze the user's emotional state and suggest skin care products and relaxation methods according to the emotion. For example, the analysis unit can use the emotion estimation function to analyze the user's emotional state and, based on that data, suggest skin care products and relaxation methods according to the emotion. For example, if the user is highly stressed, it can recommend skin care products with a relaxing effect. To analyze the user's emotional state, facial expression and voice data can be collected and input into the generation AI. For example, an emotion score can be calculated and appropriate skin care products and relaxation methods can be suggested based on the results. To suggest skin care products and relaxation methods according to the emotional state, the generation AI can provide customized advice based on the analysis results. For example, it can recommend aromatherapy or massage methods according to the emotional state. This can support the user's physical and mental health by suggesting skin care products and relaxation methods according to the user's emotional state.

[0067] The dialogue unit can analyze the content of the user's dialogue and generate a more appropriate response based on the tone and wording of the dialogue. The dialogue unit, for example, uses a generation AI to analyze the content of the user's dialogue and generate an appropriate response based on the tone and wording of the dialogue. For example, a relaxed response is generated for a dialogue in a gentle tone. In addition, to analyze the content of the user's dialogue, text data is collected and input into the generation AI. For example, the tone and wording of the dialogue is analyzed and an appropriate response is generated based on the results. In addition, to generate a response based on the tone and wording of the dialogue, the generation AI provides a customized response based on the analysis results. For example, a response that shows empathy is generated for an emotional dialogue. In this way, more appropriate support can be provided to the user by generating a response based on the tone and wording of the dialogue.

[0068] The dialogue unit can provide a consistent response by taking into account the user's past dialogue history. For example, when analyzing the content of a user's dialogue using a generation AI, the dialogue unit can also take into account the past dialogue history and provide a consistent response. For example, the dialogue unit generates a response related to the current dialogue by referring to the content of the past dialogue. In addition, a consistent response can be provided by collecting the user's past dialogue history and inputting it into the generation AI. For example, a response appropriate for the current dialogue is generated based on the content of the past dialogue. In addition, in order to provide a response that takes into account the past dialogue history, the generation AI provides a customized response based on the analysis results. For example, specific advice for the user's concerns is provided based on the content of the past dialogue. In this way, a consistent response can be provided by taking into account the past dialogue history.

[0069] The dialogue unit can use the emotion estimation function to analyze the user's emotional state and generate a response that corresponds to the emotion. For example, the dialogue unit uses the emotion estimation function to analyze the user's emotional state and generate a response that corresponds to the emotion based on that data. For example, if the user is sad, it generates words of comfort. In addition, to analyze the user's emotional state, facial expressions and voice data are collected and input into the generation AI. For example, an emotion score is calculated and an appropriate response is generated based on the result. In addition, to generate a response that corresponds to the emotional state, the generation AI provides a customized response based on the analysis result. For example, if the user is feeling stressed, it suggests ways to relax. In this way, by generating a response that corresponds to the emotional state, more appropriate support can be provided to the user.

[0070] The dialogue unit, when providing an environment where users can converse anonymously, can also support dialogue between different languages, thereby promoting international communication. For example, the dialogue unit uses a generation AI to support dialogue between different languages ​​when providing an environment where users can converse anonymously. For example, it translates dialogue between English and Japanese in real time. In addition, to support dialogue between different languages, the generation AI is equipped with a multilingual translation function. For example, it automatically translates text entered by the user and conveys it to the other person. In addition, to promote international communication, the generation AI enables smooth dialogue between different languages. For example, it provides translations that take cultural nuances into account. This supports dialogue between different languages, thereby promoting international communication.

[0071] When providing an environment in which users can converse anonymously, the dialogue unit can visualize the content of the dialogue and provide responses that are visually easy to understand. When providing an environment in which users can converse anonymously, the dialogue unit, for example, uses a generation AI to visualize the content of the dialogue. For example, the main points of the dialogue are displayed in diagrams or graphs. In addition, to visualize the content of the dialogue, the generation AI is equipped with a visualization function. For example, the flow of the dialogue is displayed in a flowchart. In addition, in order to provide responses that are visually easy to understand, the generation AI generates visualized responses based on the analysis results. For example, the content of the dialogue is represented using illustrations or icons. In this way, by visualizing the content of the dialogue, it is possible to provide responses that are visually easy to understand.

[0072] The dialogue unit can use the emotion estimation function to analyze the user's emotional state and provide relaxation music or meditation guides that correspond to the emotion. For example, the dialogue unit can use the emotion estimation function to analyze the user's emotional state and provide relaxation music or meditation guides that correspond to the emotion based on the data. For example, if the user is feeling stressed, music with a relaxing effect can be provided. In addition, to analyze the user's emotional state, facial expression and voice data can be collected and input into the generation AI. For example, an emotion score can be calculated and appropriate relaxation music or meditation guides can be provided based on the result. In addition, to provide relaxation music or meditation guides that correspond to the emotional state, the generation AI provides customized content based on the analysis results. For example, a meditation guide that matches the user's emotional state can be generated. In this way, the user's physical and mental health can be supported by providing relaxation music or meditation guides that correspond to the user's emotional state.

[0073] The advice providing unit can propose individual meal plans and exercise plans based on the user's skin condition and mental health condition. The advice providing unit, for example, uses a generation AI to propose individual meal plans based on the user's skin condition and mental health condition. For example, a meal plan including nutrients to prevent dry skin is proposed. The advice providing unit also analyzes the user's skin condition and mental health condition and proposes an individual exercise plan based on that data. For example, an exercise plan including yoga and meditation for stress reduction is proposed. In addition, to propose individual meal plans and exercise plans, the generation AI provides customized advice based on the analysis results. For example, it suggests meals and exercises that are tailored to the user's lifestyle habits. This allows the system to comprehensively support the user's health by proposing individual meal plans and exercise plans.

[0074] The advice providing unit can provide more personalized advice by taking into account the user's genetic information. The advice providing unit, for example, uses a generation AI to provide custom advice that takes into account the user's genetic information. For example, appropriate skin care products are suggested for a user who is genetically prone to sensitive skin. In addition, more personalized advice is provided by collecting the user's genetic information and inputting it into the generation AI. For example, stress management methods are suggested for a user who is genetically prone to stress. In addition, in order to provide custom advice that takes into account genetic information, the generation AI provides customized advice based on the analysis results. For example, diet and exercise suggestions are made based on genetic factors. In this way, more personalized advice can be provided by taking genetic information into account.

[0075] The advice providing unit can use the emotion estimation function to analyze the user's emotional state and provide custom advice according to the emotion. For example, the advice providing unit uses the emotion estimation function to analyze the user's emotional state and provides custom advice according to the emotion based on that data. For example, if the user is feeling anxious, it suggests a relaxation method. In addition, to analyze the user's emotional state, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate custom advice is provided based on the result. In addition, to provide custom advice according to the emotional state, the generation AI provides customized advice based on the analysis results. For example, it suggests skin care products or relaxation methods tailored to the emotional state. In this way, custom advice according to the emotional state can be provided to support the user's physical and mental health.

[0076] The advice providing unit can provide customized pet care advice based on the health condition of the user's pet. The advice providing unit uses, for example, a generation AI to provide customized pet care advice based on the health condition of the user's pet. For example, it may propose a diet and exercise plan for the pet. In addition, the customized pet care advice is provided by collecting health data of the pet and inputting it into the generation AI. For example, it may propose disease prevention and health management methods for the pet. In addition, to provide the customized pet care advice, the generation AI provides customized advice based on the analysis results. For example, it may suggest diet and exercise plans tailored to the pet's health condition. This makes it possible to support pet care by providing customized advice based on the pet's health condition.

[0077] The advice providing unit can suggest appropriate travel destinations and activities based on the user's skin condition and mental health state. The advice providing unit, for example, uses a generation AI to suggest appropriate travel destinations based on the user's skin condition and mental health state. For example, it may recommend relaxing hot spring resorts or places rich in nature. It may also analyze the user's skin condition and mental health state and suggest appropriate activities based on that data. For example, it may recommend a yoga retreat or meditation workshop to reduce stress. In addition, to suggest travel destinations and activities, the generation AI provides customized advice based on the analysis results. For example, it may suggest travel plans and activities tailored to the user's health state. This can help the user feel refreshed by suggesting travel destinations and activities based on the user's skin condition and mental health state.

[0078] The advice providing unit can use the emotion estimation function to analyze the user's emotional state and suggest hobbies and leisure activities according to the emotion. For example, the advice providing unit uses the emotion estimation function to analyze the user's emotional state and, based on that data, suggests hobbies and leisure activities according to the emotion. For example, if the user wants to relax, it suggests art therapy. In addition, to analyze the user's emotional state, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate hobbies and leisure activities are suggested based on the result. In addition, to suggest hobbies and leisure activities according to the emotional state, the generation AI provides customized advice based on the analysis results. For example, outdoor activities or creative hobbies that match the emotional state are suggested. In this way, the advice providing unit can support the user's physical and mental health by suggesting hobbies and leisure activities according to the emotional state.

[0079] When tracking a user's emotions and state, the tracking unit also analyzes the user's voice data and facial expression data, enabling more precise tracking. For example, when using a generation AI to track a user's emotions and state, the tracking unit analyzes voice data and facial expression data. For example, it analyzes changes in the user's voice tone and facial expression to track their emotional state. It also tracks emotions and states by collecting the user's voice data and facial expression data and inputting it into the generation AI. For example, it analyzes subtle changes in voice intonation and facial expressions to understand their emotional state. It also provides the user with advice on emotional and health management based on the results of analyzing the voice data and facial expression data. For example, it suggests relaxation methods if stress is increasing. This enables more precise tracking by analyzing voice data and facial expression data.

[0080] The tracking unit can analyze the user's long-term health trends based on the tracked data and provide preventative advice. The tracking unit, for example, uses a generation AI to track the user's emotions and condition and analyze long-term health trends based on that data. For example, it analyzes emotional fluctuations and changes in skin condition over a long period of time. It also collects tracking data and inputs it into the generation AI to analyze the user's long-term health trends. For example, it predicts future health risks based on past data. It also provides preventative advice to the user based on the results of analyzing long-term health trends. For example, it suggests taking appropriate measures before health risks increase. In this way, it is possible to provide preventative advice by analyzing long-term health trends.

[0081] The tracking unit can use the emotion estimation function to track the user's emotional state in real time and provide feedback according to changes in emotion. For example, the tracking unit uses the emotion estimation function to track the user's emotional state in real time and provide feedback according to changes in emotion based on that data. For example, if the user is feeling stressed, it can suggest relaxation methods. In addition, to track the user's emotional state in real time, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate feedback is provided based on the result. In addition, to provide feedback according to changes in emotion, the generation AI provides customized advice based on the analysis results. For example, it can suggest stress management methods or relaxation methods tailored to the emotional state. In this way, the tracking unit can support the user's physical and mental health by tracking the emotional state in real time and providing feedback according to changes.

[0082] The tracking unit can track the emotions and health of the user's pet and provide pet care advice. For example, the tracking unit uses a generation AI to track the emotions and health of the user's pet and provide pet care advice based on that data. For example, it analyzes the pet's stress and health and suggests appropriate care methods. In addition, to track the pet's emotions and health, the tracking unit collects pet behavioral data and health data and inputs it into the generation AI. For example, it analyzes the pet's activity level and dietary data to understand its health. In addition, based on the results of tracking the pet's emotions and health, it provides pet care advice to the user. For example, it suggests methods for reducing stress and managing the pet's health. In this way, the tracking unit can support the pet's health by tracking the pet's emotions and health and providing pet care advice.

[0083] When tracking the user's emotions and state, the tracking unit can also analyze the user's living environment (temperature, humidity, noise) and provide advice on improving the environment. For example, the tracking unit uses a generation AI to analyze living environment data when tracking the user's emotions and state. For example, it analyzes the impact of temperature, humidity, and noise levels on emotions and health. It also tracks emotions and states by collecting the user's living environment data and inputting it into the generation AI. For example, it monitors temperature, humidity, and noise levels in real time to understand emotions and health states. It also provides the user with advice on improving the environment based on the results of analyzing the living environment data. For example, it suggests appropriate temperature and humidity settings and noise control measures. In this way, it is possible to provide advice on improving the environment by analyzing the living environment.

[0084] The tracking unit can use the emotion estimation function to track the user's emotional state and suggest entertainment content that matches the emotion. For example, the tracking unit uses the emotion estimation function to track the user's emotional state and suggest entertainment content that matches the emotion based on that data. For example, if the user wants to relax, it suggests relaxation music. In addition, to track the user's emotional state, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate entertainment content is suggested based on the result. In addition, to suggest entertainment content that matches the emotional state, the generation AI provides customized content based on the analysis results. For example, movies and games that match the emotional state are suggested. In this way, the user's physical and mental health can be supported by suggesting entertainment content that matches the emotional state.

[0085] The community promotion unit can match users with common hobbies and interests when promoting community cohesion between users. The community promotion unit, for example, uses a generation AI to match users with common hobbies and interests when promoting community cohesion between users. For example, it groups users with the same hobbies. Furthermore, by collecting data on users' hobbies and interests and inputting it into the generation AI, users with common hobbies and interests are matched. For example, groups are created based on hobbies and interests. Furthermore, to match users with common hobbies and interests, the generation AI provides customized matching based on the analysis results. For example, it suggests events and activities based on hobbies and interests. This makes it possible to promote community cohesion by matching users with common hobbies and interests.

[0086] The community promotion unit can analyze the content of the conversation between matched users and provide feedback to improve the quality of the conversation. The community promotion unit, for example, uses a generation AI to analyze the content of the conversation between matched users and provide feedback to improve the quality of the conversation. For example, it analyzes the tone and language of the conversation and suggests areas for improvement. In addition, the content of the conversation between users is collected and input into the generation AI to provide feedback to improve the quality of the conversation. For example, it analyzes the content of the conversation and provides advice to deepen empathy and understanding. In addition, in order to provide feedback to improve the quality of the conversation, the generation AI provides customized advice based on the analysis results. For example, it makes suggestions to make the flow of the conversation smoother. In this way, feedback that improves the quality of the conversation is provided, thereby smoothing communication between users.

[0087] The community promotion unit can use the emotion estimation function to analyze the user's emotional state and suggest community activities that correspond to the emotion. For example, the community promotion unit uses the emotion estimation function to analyze the user's emotional state and suggest community activities that correspond to the emotion based on that data. For example, if the user wants to relax, it suggests relaxation activities. In addition, to analyze the user's emotional state, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate community activities are suggested based on the result. In addition, to suggest community activities that correspond to the emotional state, the generation AI provides customized advice based on the analysis results. For example, hobbies and leisure activities that match the emotional state are suggested. In this way, by suggesting community activities that correspond to the emotional state, it is possible to support the user's physical and mental health.

[0088] The community promotion unit can match users with different cultural backgrounds and promote intercultural exchange. The community promotion unit, for example, uses a generation AI to match users with different cultural backgrounds and promote intercultural exchange. For example, it groups users from different countries or regions. It also matches users with different cultural backgrounds by collecting data on the users' cultural backgrounds and inputting it into the generation AI. For example, it creates groups based on cultural interests and experiences. In addition, to promote intercultural exchange, the generation AI provides customized matching based on the analysis results. For example, it suggests dialogues and activities between users with different cultural backgrounds. This makes it possible to promote intercultural exchange by matching users with different cultural backgrounds.

[0089] The community promotion unit can use the emotion estimation function to analyze the user's emotional state and suggest volunteer activities or social contribution activities that correspond to the emotion. For example, the community promotion unit uses the emotion estimation function to analyze the user's emotional state and, based on that data, suggests volunteer activities or social contribution activities that correspond to the emotion. For example, if the user has positive emotions, it suggests volunteer activities. In addition, to analyze the user's emotional state, facial expression and voice data are collected and input into the generation AI. For example, an emotion score is calculated and appropriate volunteer activities or social contribution activities are suggested based on the result. In addition, to suggest volunteer activities or social contribution activities that correspond to the emotional state, the generation AI provides customized advice based on the analysis results. For example, it suggests activities that match the emotional state. In this way, it is possible to support the user's physical and mental health by suggesting volunteer activities or social contribution activities that correspond to the emotional state.

[0090] The system according to the embodiment is not limited to the above-described example, and various modifications are possible, for example, as follows.

[0091] When analyzing a user's skin condition and mental health, the analysis unit can take the user's diet into account, allowing for more precise analysis. For example, the generation AI can be used to analyze the impact of the user's diet on their skin condition and mental health. In addition, by collecting the user's dietary data and inputting it into the generation AI, the relationship between skin and mental health can be analyzed. For example, if a specific nutrient is lacking, the impact can be analyzed and feedback provided to the user. Furthermore, based on the analysis results that take dietary content into account, advice on dietary improvement can be provided to the user. For example, the intake of vitamins and minerals can be recommended. This allows for more precise analysis results to be provided by taking dietary content into account.

[0092] When analyzing a user's skin condition and mental health, the analysis unit can take the user's exercise habits into account to perform a more precise analysis. For example, it uses a generation AI to analyze the impact of a user's exercise habits on their skin condition and mental health. It also collects the user's exercise data and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of lack of exercise on skin problems and mental disorders and provides feedback to the user. It also provides advice to the user on how to improve their exercise based on the analysis results that take exercise habits into account. For example, it recommends moderate exercise. This allows for more precise analysis results to be provided by taking exercise habits into account.

[0093] When analyzing a user's skin condition and mental health, the analysis unit can take the user's sleep patterns into account, allowing for more precise analysis. For example, the analysis unit uses a generation AI to analyze the impact of a user's sleep patterns on their skin condition and mental health. In addition, by collecting the user's sleep data and inputting it into the generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, it can analyze the impact of lack of sleep on skin problems and mental disorders and provide feedback to the user. In addition, based on the analysis results that take sleep patterns into account, it can provide the user with advice on improving their sleep. For example, it can recommend getting enough sleep. This allows for more precise analysis results to be provided by taking sleep patterns into account in the analysis.

[0094] When analyzing a user's skin condition and mental health, the analysis unit can take the user's stress level into account, allowing for a more precise analysis. For example, the generation AI can be used to analyze the impact of the user's stress level on their skin condition and mental health. In addition, by collecting the user's stress data and inputting it into the generation AI, the relationship between skin and mental health can be analyzed. For example, the impact of stress on skin problems and mental disorders can be analyzed and feedback provided to the user. In addition, based on the analysis results that take stress level into account, advice on stress management can be provided to the user. For example, relaxation methods can be recommended. This allows for more precise analysis results to be provided by taking stress level into account.

[0095] When analyzing a user's skin condition and mental health, the analysis unit can take the user's emotional state into account, allowing for more precise analysis. For example, it uses a generation AI to analyze the impact of the user's emotional state on their skin condition and mental health. It also collects the user's emotional data and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of emotional fluctuations on skin problems and mental disorders and provides feedback to the user. It also provides the user with emotional management advice based on the analysis results that take the user's emotional state into account. For example, it recommends methods to stabilize emotions. This allows for more precise analysis results to be provided by taking the user's emotional state into account.

[0096] When analyzing a user's skin condition and mental health, the analysis unit can take the user's living environment into account to perform a more precise analysis. For example, it uses a generation AI to analyze the impact of the user's living environment on their skin condition and mental health. It also collects data on the user's living environment and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of the temperature and humidity of the living environment on skin problems and mental disorders and provides feedback to the user. It also provides the user with advice on improving their environment based on the analysis results that take the living environment into account. For example, it recommends appropriate temperature and humidity settings. This allows for more precise analysis results to be provided by taking the living environment into account in the analysis.

[0097] When analyzing a user's skin condition and mental health, the analysis unit can take the user's social relationships into account, allowing for more precise analysis. For example, it uses a generation AI to analyze the impact of a user's social relationships on their skin condition and mental health. It also collects the user's social relationship data and inputs it into the generation AI to analyze the relationship between skin and mental health. For example, it analyzes the impact of loneliness and social stress on skin problems and mental disorders, and provides feedback to the user. It also provides the user with advice on improving their social relationships based on the analysis results that take social relationships into account. For example, it recommends participation in community activities. This allows for more precise analysis results to be provided by analysis that takes social relationships into account.

[0098] When analyzing a user's skin condition and mental health, the analysis unit can take the user's hobbies and interests into account, allowing for more precise analysis. For example, the analysis unit uses generation AI to analyze the impact of a user's hobbies and interests on their skin condition and mental health. In addition, by collecting the user's hobby and interest data and inputting it into generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, the analysis unit can analyze the impact of hobbies and interests on stress reduction and relaxation, and provide feedback to the user. In addition, based on the analysis results that take hobbies and interests into account, the analysis unit can provide advice to the user on how to utilize their hobbies and interests. For example, it can recommend hobbies that have a relaxing effect. This allows for analysis that takes hobbies and interests into account, allowing for more precise analysis results.

[0099] When analyzing a user's skin condition and mental health, the analysis unit can take the health condition of the user's pet into account, allowing for more precise analysis. For example, the analysis unit uses a generation AI to analyze the impact of the user's pet's health condition on the user's skin condition and mental health. In addition, by collecting the user's pet's health data and inputting it into the generation AI, the analysis unit can analyze the relationship between skin and mental health. For example, the analysis unit can analyze the impact of the pet's illness or stress on the user's mental health and provide feedback to the user. In addition, based on the analysis results that take the pet's health condition into account, the analysis unit can provide the user with pet care advice. For example, the analysis unit can recommend health care methods for the pet. This allows for more precise analysis results to be provided by taking the pet's health condition into account.

[0100] When analyzing the user's skin condition and mental health, the analysis unit can also analyze the user's emotional state in real time and suggest skin care products and relaxation methods according to their emotions. For example, the emotion estimation function can be used to analyze the user's emotional state in real time and, based on that data, suggest skin care products and relaxation methods according to their emotions. For example, if the user is highly stressed, skin care products with a relaxing effect can be recommended. Furthermore, to analyze the user's emotional state, facial expression and voice data can be collected and input into the generation AI. For example, an emotional score can be calculated and appropriate skin care products and relaxation methods can be suggested based on the results. Furthermore, to suggest skin care products and relaxation methods according to the user's emotional state, the generation AI provides customized advice based on the analysis results. For example, aromatherapy or massage methods can be recommended according to the user's emotional state. This allows the system to support the user's physical and mental health by suggesting skin care products and relaxation methods according to the user's emotional state.

[0101] The processing flow of the second embodiment will be briefly explained below.

[0102] Step 1: The analysis unit uses the generation AI to analyze the user's skin condition and mental health. For example, if the user's dryness or inflammation of the skin is related to stress or anxiety, the generation AI analyzes the relationship and provides feedback to the user. The generation AI also performs its analysis based on prompts containing data about the user's skin condition and information about their mental health. Step 2: The dialogue unit provides an environment where users can anonymously converse based on the results of the analysis by the analysis unit. For example, when a user talks about their mental worries or skin problems, the generation AI generates an appropriate response, giving the user a sense of security. The generation AI also generates a response based on prompts that include the user's worries and questions. Step 3: The advice provider provides custom advice and resources based on the information collected by the dialogue component. For example, the generator AI suggests appropriate skin care products and relaxation methods based on the user's skin condition and mental health. The generator AI also generates advice based on prompts containing information about the user's skin condition and mental health. Step 4: The tracking unit tracks the user's emotions and condition based on the advice provided by the advice providing unit. For example, the generation AI analyzes the data by having the user record their daily emotions and skin condition, and tracks changes in the user. The generation AI also performs analysis based on prompts containing data on the user's emotions and skin condition. Step 5: The community promotion unit promotes community cohesion among users based on the data tracked by the tracking unit. For example, the generation AI matches users with the same concerns and provides a place for them to exchange information and receive support. The generation AI also matches users based on prompts containing information about their concerns and interests.

[0103] 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.

[0104] 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> Examples of generative AIs include the data generation model 58, such as a neural network model (e.g., a neural network model), and a neural network model (e.g., a neural network model). 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 speech, text data indicating text, and image data indicating an image is also input to the data generation model 58. 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. The specification processing unit 290 performs the above-mentioned specification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0105] Furthermore, the processing by the data processing system 10 described above is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart device 14, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart device 14. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information necessary for processing from the smart device 14 or an external device, and the smart device 14 acquires or collects information necessary for processing from the data processing device 12 or an external device.

[0106] [Second embodiment] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0107] 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.

[0108] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0109] 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.

[0110] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0111] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0112] 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.

[0113] 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.

[0114] 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.

[0115] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0116] In the smart glasses 214, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The smart glasses 214 also have a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can perform processing similar to that of the specific processing unit 290 using these models.

[0117] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0118] 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.

[0119] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0120] The data processing system 210 according to the second embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 210 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the smart glasses 214, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the smart glasses 214. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the smart glasses 214 or an external device, etc., and the smart glasses 214 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0121] [Third embodiment] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0122] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[0123] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0124] 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.

[0125] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0126] 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 user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0127] 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.

[0128] 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.

[0129] 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.

[0130] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0131] In the headset type terminal 314, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. Note that the headset type terminal 314 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0132] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0133] 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.

[0134] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0135] The data processing system 310 according to the third embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 310 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the headset type terminal 314, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the headset type terminal 314. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the headset type terminal 314 or an external device, etc., and the headset type terminal 314 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0136] [Fourth embodiment] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[0137] 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0138] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, RAM 30, and 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 and / or a LAN.

[0139] 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.

[0140] The microphone 238 receives instructions and the like from the user by receiving voice uttered by the user. The microphone 238 captures the voice uttered by the user, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to instructions from the processor 46.

[0141] 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 image sensor or a CCD image sensor, and captures images of the user's surroundings (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0142] 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.

[0143] The control object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the 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.

[0144] 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.

[0145] 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.

[0146] 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. The identification processing unit 290 can estimate a user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion. The emotion estimation function (emotion identification function) using the emotion identification model 59 performs various estimations and predictions regarding the user's emotion, including estimation and prediction of the user's emotion, but is not limited to these examples. Furthermore, the estimation and prediction of emotion also includes, for example, emotion analysis.

[0147] In the robot 414, the specific processing is performed by the processor 46. A specific processing program 60 is stored in the storage 50. The processor 46 reads the specific processing program 60 from the storage 50 and executes the read specific processing program 60 on the RAM 48. The specific processing is realized by the processor 46 operating as the control unit 46A in accordance with the specific processing program 60 executed on the RAM 48. The robot 414 has a data generation model and an emotion identification model similar to the data generation model 58 and the emotion identification model 59, and can also perform processing similar to that of the specific processing unit 290 using these models.

[0148] Note that a device other than the data processing device 12 may have the data generation model 58. For example, a server device may have the data generation model 58. In this case, the data processing device 12 communicates with the server device having the data generation model 58 to obtain a processing result (such as a prediction result) using the data generation model 58. Furthermore, the data processing device 12 may be a server device, or may be a terminal device (for example, a mobile phone, a robot, a home appliance, etc.) owned by a user.

[0149] 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.

[0150] The data generation model 58 is a so-called generative AI. An example of the data generation model 58 is a generative AI such as ChatGPT. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 receives a prompt containing an instruction, as well as inference data such as voice data representing speech, text data representing text, and image data representing an image. 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. The identification processing unit 290 performs the above-mentioned identification processing using the data generation model 58. The data generation model 58 may be a fine-tuned model so as to output an inference result from a prompt that does not include an instruction. In this case, the data generation model 58 can output an inference result from a prompt that does not include an instruction. The data processing device 12 and the like include multiple types of data generation models 58, and the data generation model 58 includes AIs other than the generative AI. The AI ​​other than the generative AI may be, for example, linear regression, logistic regression, decision tree, random forest, support vector machine (SVM), k-means clustering, convolutional neural network (CNN), recurrent neural network (RNN), generative adversarial network (GAN), or naive Bayes, and can perform various processes, but is not limited to these examples. The AI ​​may also be an AI agent. When the processes of each of the above-mentioned parts are performed by AI, the processes may be performed in part or entirely by AI, but are not limited to these examples. The processes performed by AI, including the generative AI, may be replaced with rule-based processes.

[0151] The data processing system 410 according to the fourth embodiment performs the same processing as the data processing system 10 according to the first embodiment. The processing by the data processing system 410 is executed by the specific processing unit 290 of the data processing device 12 or the control unit 46A of the robot 414, but may also be executed by the specific processing unit 290 of the data processing device 12 and the control unit 46A of the robot 414. Furthermore, the specific processing unit 290 of the data processing device 12 acquires or collects information required for processing from the robot 414 or an external device, etc., and the robot 414 acquires or collects information required for processing from the data processing device 12 or an external device, etc.

[0152] 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.

[0153] FIG. 9 illustrates 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 behaviors arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion encompasses both emotions 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.

[0154] 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.

[0155] 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).

[0156] 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 expressed, and when they approach the ideal, a state of pleasure is expressed. Emotions can also be created for robots, cars, 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 expressed, and when they approach the ideal, a state of pleasure is expressed. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on speech emotion recognition and brain physiological signal analysis systems for emotions, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the area called "reaction," where sensation is dominant. The right half of the emotion map lists emotions belonging to the area called "situation," where situational awareness is dominant.

[0157] 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."

[0158] 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.

[0159] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0160] 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.

[0161] 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.

[0162] 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.

[0163] The hardware resource for executing a specific process can be any of the following types of processors: A processor, for example, 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. A processor also includes 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.

[0164] The hardware resource that executes the specific process 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 process may be a single processor.

[0165] 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.

[0166] 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.

[0167] In the above example, the first to fourth embodiments have been described separately, but some or all of these embodiments may be combined. The smart device 14, smart glasses 214, headset terminal 314, and robot 414 are merely examples, and they may be combined, or other devices may be used. In the above example, the first and second embodiments have been described separately, but they may be combined.

[0168] 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.

[0169] 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. [Explanation of symbols]

[0170] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot

Claims

1. An analysis unit that uses generative AI to analyze the user's skin condition and mental health status; a dialogue unit that provides an environment in which users can have anonymous dialogue based on the results of the analysis by the analysis unit; an advice providing unit that provides custom advice and resources based on the information collected by the dialogue unit; a tracking unit that tracks the user's emotions and state based on the advice provided by the advice providing unit; a community promotion unit that promotes community bonding among users based on the data tracked by the tracking unit. A system characterized by:

2. The analysis unit When analyzing the user's skin condition and mental health, the analysis will be more precise, taking into account seasonal and weather changes.

2. The system of claim 1.

3. The analysis unit Analyze the relationship with the user's lifestyle habits (diet, exercise, sleep) and provide comprehensive health advice 2. The system of claim 1.

4. The analysis unit Analyzing the emotional state of the user in real time and identifying correlations with the skin condition 2. The system of claim 1.

5. The analysis unit By linking the health status of the pet with the mental health status of the user, we provide a support system that integrates pet care and mental care.

2. The system of claim 1.

6. The analysis unit When analyzing the user's skin condition and mental health condition, emotional data of at least one of music and art is also incorporated to analyze the relationship between the emotional state and health.

2. The system of claim 1.

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