system

Abstract

We provide the system. [Solution] A generation means that receives individual user information and generates hair improvement suggestions suitable for the user based on said information, A means of aggregating information that periodically collects hair-related information from the internet and stores the collected information in a database, A notification means for notifying the user of the hair improvement suggestion generated by the generation means, A regeneration means that receives feedback from the user and updates the proposal generated by the generation means based on the feedback, A system that includes this.

Description

Technical Field

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

Background Art

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

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] In modern society, many middle-aged and elderly people have concerns about hair health and hair loss. However, general hair improvement methods and commercially available products cannot provide solutions optimized for the specific needs and living habits of individual users. Therefore, it is an important issue to effectively generate and provide hair improvement proposals tailored to individual users.

Means for Solving the Problems

[0005] This invention provides a generation method for generating personalized hair improvement suggestions by collecting individual user information and integrating it with hair-related information obtained from the internet. Furthermore, by adding a means for notifying the user of these suggestions and a regeneration method for updating the generated suggestions based on continuous feedback, the invention provides an effective hair improvement solution that is tailored to the individual needs of the user.

[0006] "Generation means" refers to means that have the function of generating hair improvement suggestions that are optimal for each user by utilizing individual user information.

[0007] "Aggregation means" refers to a means that has the function of collecting hair-related information from multiple sources on the internet and storing it in a database.

[0008] "Notification means" refers to means that have the function of communicating the generated hair improvement suggestions to the user and presenting them visually or in other forms.

[0009] A "regeneration means" is a means that receives feedback from the user and has the function of updating and improving the proposal based on that feedback.

[0010] "User information" refers to the collective information collected from individual users regarding their hair condition, lifestyle, health status, and personal needs.

[0011] "Sensor data" includes data on the user's physical activity and environment, obtained from the user's mobile device or other means.

[0012] "Data from social networking services" refers to information related to hair and beauty obtained from users' online activities.

[0013] A "dashboard" is a visually organized interface designed to make it easy for users to understand and implement the hair improvement suggestions that have been generated. [Brief explanation of the drawing]

[0014] [Figure 1] This is a conceptual diagram showing an example of the configuration of a data processing system according to the first embodiment. [Figure 2] This is a conceptual diagram showing an example of the essential functions of a data processing device and a smart device according to the first embodiment. [Figure 3] This is a conceptual diagram showing an example of the configuration of a data processing system according to the second embodiment. [Figure 4] This is a conceptual diagram showing an example of the main functions of a data processing device and smart glasses according to the second embodiment. [Figure 5] This is a conceptual diagram showing an example of the configuration of a data processing system according to the third embodiment. [Figure 6] This is a conceptual diagram showing an example of the main functions of a data processing device and a headset-type terminal according to the third embodiment. [Figure 7] This is a conceptual diagram showing an example of the configuration of a data processing system according to the fourth embodiment. [Figure 8] This is a conceptual diagram showing an example of the main functions of a data processing device and a robot according to the fourth embodiment. [Figure 9] This shows an emotion map where multiple emotions are mapped. [Figure 10] This shows an emotion map where multiple emotions are mapped. [Figure 11] This is a sequence diagram showing the processing flow of the data processing system in Example 1. [Figure 12] This is a sequence diagram showing the processing flow of the data processing system in Application Example 1. [Figure 13] This is a sequence diagram showing the processing flow of the data processing system in Example 2, which incorporates an emotion engine. [Figure 14] This is a sequence diagram showing the processing flow of the data processing system in Application Example 2, which combines an emotion engine. [Modes for carrying out the invention]

[0015] Hereinafter, an example of an embodiment of the system according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0016] First, the terms used in the following description will be explained.

[0017] In the following embodiments, the numbered processor (hereinafter simply referred to as "processor") may be a single arithmetic unit or a combination of multiple arithmetic units. Also, the processor may be a single type of arithmetic unit or a combination of multiple types of arithmetic units. Examples of arithmetic units 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), and the like.

[0018] In the following embodiments, the numbered RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a work memory by the processor.

[0019] In the following embodiments, the numbered storage is one or more non-volatile storage devices that store various programs and various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), or magnetic tapes, and the like.

[0020] In the following embodiments, the signed communication interface (I / F) is an interface that includes a communication processor and an antenna, etc. The communication interface manages communication between multiple computers. Examples of communication standards applicable to the communication interface include wireless communication standards such as 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), or Bluetooth (registered trademark).

[0021] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." That is, "A and / or B" means that it may be A alone, or B alone, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" applies when expressing three or more things linked by "and / or."

[0022] [First Embodiment]

[0023] Figure 1 shows an example of the configuration of the data processing system 10 according to the first embodiment.

[0024] As shown in Figure 1, the data processing system 10 includes a data processing device 12 and a smart device 14. An example of the data processing device 12 is a server.

[0025] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0026] The smart device 14 comprises a computer 36, a reception device 38, an output device 40, a camera 42, and a communication interface 44. The computer 36 comprises a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The reception device 38, output device 40, and camera 42 are also connected to the bus 52.

[0027] The reception device 38 is equipped with a touch panel 38A and a microphone 38B, etc., and receives user input. The touch panel 38A receives user input by detecting contact with an object (e.g., a pen or finger). The microphone 38B receives user input by detecting the user's voice. The control unit 46A transmits data indicating the user input received by the touch panel 38A and microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the data indicating the user input.

[0028] The output device 40 includes a display 40A and a speaker 40B, and presents data to the user 20 by outputting the data in a form perceptible to the user 20 (e.g., audio and / or text). The display 40A displays visible information such as text and images according to instructions from the processor 46. The speaker 40B outputs audio according to instructions from the processor 46. The camera 42 is a small digital camera equipped with an optical system such as a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0029] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various types of information between processor 46 and processor 28 via network 54.

[0030] Figure 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0031] As shown in Figure 2, in the data processing device 12, a specific processing is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" related to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 according to the specific processing program 56 executed on the RAM 30.

[0032] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0033] In the smart device 14, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The reception output program 60 is used in conjunction with a specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0034] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0035] This invention is a system for providing hair improvement suggestions tailored to the user. This system collects individual user information and combines it with hair-related information from the internet to generate an optimal hair improvement program. Specific embodiments for carrying out this invention are described below.

[0036] First, users input information about their hair concerns and ideal hairstyle through a dedicated application. Furthermore, the application also acquires data from the user's smartphone sensors and information extracted from social networking services.

[0037] The terminal integrates this information and sends it to the server. The server then stores the collected user information in a database and gathers the latest hair-related information from the internet. This aggregation method ensures that user-related information is always up-to-date.

[0038] After the information is aggregated, the server uses a generation mechanism to generate hair improvement suggestions based on the individual user's information. Examples of suggestions include dietary improvements, exercise recommendations, and the use of specific hair care products.

[0039] The generated suggestions are notified to the user via their device. This notification method allows users to view specific improvement measures on a dashboard that is easy to understand visually.

[0040] The server also collects feedback from users and uses regeneration mechanisms to improve the suggestions. This allows the suggestions to adapt over time, increasing in accuracy and effectiveness.

[0041] For example, let's say a male user in his 40s uses this system. This user is concerned about thinning hair and has a habit of carrying a pedometer with him every day. When he logs into the application and enters his concerns about his hair, the server retrieves that information along with his step count data from his smartphone and saves it in the database.

[0042] The server then uses this information to generate a hair improvement program tailored to his lifestyle. The suggested improvements include increasing walking distance to improve blood flow and positively impact hair health, as well as actively consuming foods rich in specific vitamins.

[0043] As described above, the present invention provides hair improvement proposals optimized for individual users and offers solutions that meet the specific needs of users.

[0044] The following describes the processing flow.

[0045] Step 1:

[0046] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and desired hairstyle.

[0047] Step 2:

[0048] The device encrypts this input information and sends it to the server. Furthermore, with the user's permission, the device retrieves sensor data from the smartphone (e.g., steps, heart rate) and related data from social networking services.

[0049] Step 3:

[0050] The server integrates the received user information with sensor data and SNS data sent from the terminal and stores it in a database.

[0051] Step 4:

[0052] The server collects the latest information on hair in real time from various sources on the web and updates the database. This aggregation method ensures that the most up-to-date information is always available.

[0053] Step 5:

[0054] The server utilizes generation methods to automatically generate a hair improvement program optimized for each user, based on collected individual user information and hair-related information obtained from the web. The program includes nutritional guidance, exercise plans, and recommendations for hair care products.

[0055] Step 6:

[0056] The server sends the generated hair improvement program to the terminal in a visually easy-to-understand dashboard format and notifies the user.

[0057] Step 7:

[0058] Users review the provided dashboard and incorporate the suggested hair improvement program into their daily lives.

[0059] Step 8:

[0060] Users input the results of their program implementation and the effects they experienced into their device and send this feedback to the server.

[0061] Step 9:

[0062] Based on the feedback received, the server uses an AI model to further improve the program's accuracy through regeneration and updates the suggested content as needed.

[0063] Step 10:

[0064] The server resends the updated improvement program to the terminal, providing users with ongoing support.

[0065] (Example 1)

[0066] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0067] There is a need to address the diverse beauty challenges of various users and provide the latest, personalized beauty improvement suggestions. However, conventional technologies have made it difficult to efficiently generate suggestions tailored to users' lifestyles and specific needs and to incorporate feedback. Therefore, there is a need to develop a system that can provide more accurate suggestions to individual users.

[0068] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0069] In this invention, the server includes a generation means that receives individual user data and generates beauty improvement suggestions tailored to the user based on the data; an aggregation means that periodically collects beauty-related information from a communication network and stores the collected information in a data storage device; and a notification means that notifies the user of the beauty improvement suggestions generated by the generation means. This makes it possible to continuously provide the latest beauty improvement suggestions tailored to the individual needs of the user.

[0070] "User data" refers to information related to the beauty of individual users, and includes sensor information obtained from mobile devices and data from information sharing services.

[0071] "Beauty improvement suggestions" refer to information that provides specific guidance and recommendations to address users' beauty-related concerns.

[0072] A "generation method" is a system component that has the function of creating beauty improvement suggestions based on user data.

[0073] "Aggregation means" refers to a system component that has the function of storing beauty-related information collected via a communication network in a data storage device.

[0074] "Notification means" refers to a means of informing users of generated beauty improvement suggestions, and includes technologies for visually displaying information.

[0075] A "regeneration mechanism" is a system component that improves the suggestions generated by the generation mechanism based on user responses, and continuously provides more appropriate suggestions.

[0076] This invention is a system for providing users with personalized beauty improvement suggestions. This system receives individual user data, generates suggestions using a generative AI model, and periodically collects the latest information from the internet to provide information tailored to the user. A detailed description of how to implement this invention is provided below.

[0077] Users input information about their beauty concerns and goals using a dedicated application. This application can acquire sensor information about the user's current state using the smartphone's camera and location services. It also collects information about beauty-related interests and activities from social networking services.

[0078] The device aggregates information obtained from the user and transmits it to the server via a secure communication method. This process utilizes the mobile device's operating system and communication protocols.

[0079] The server stores received user data in a database. Furthermore, it uses a web crawler to collect reliable beauty-related information from the internet and stores it in the database. This allows a generative AI model to combine user data with the latest external information to generate suggestions. These suggestions include nutritional guidance, exercise advice, and recommended beauty products.

[0080] The generated beauty improvement suggestions are notified to the user via their device. The user can view the suggestions on a dashboard within the application and selectively provide feedback. This feedback is sent back to the server and used to improve the suggestions as a means of regeneration.

[0081] For example, by inputting a prompt such as, "Please suggest lifestyle habits for a woman in her 30s to achieve voluminous hair," into the AI ​​model, specific and user-specific improvement suggestions are provided. This allows users to receive practical and meaningful information to meet their individual beauty needs.

[0082] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0083] Step 1:

[0084] The user launches the application and enters their concerns and goals regarding hair and beauty. This input data also includes the user's preferences and daily activity data. For example, it might record image data of their hair condition and information about their recent diet and exercise. This information becomes the system's initial input data.

[0085] Step 2:

[0086] The terminal aggregates data entered by the user. Specifically, it integrates input data from the application with activity information acquired through sensors and formats it into a single data package. This package is encrypted using a communication protocol and securely transmitted to the server.

[0087] Step 3:

[0088] The server stores received user data in a database. The server uses this data to collect the latest beauty-related information from the internet. This collected data is periodically crawled from specific internet resources and stored in the database. The output here is a massive dataset integrating user data and internet information.

[0089] Step 4:

[0090] The server uses a generative AI model to generate personalized beauty improvement suggestions from an integrated dataset. It takes user activity data and recent information as input, and the AI ​​algorithm analyzes the relationships between the data. This results in improvement suggestions tailored to the user's needs. These suggestions include specific information such as dietary improvements, changes in exercise habits, and recommendations for beauty products.

[0091] Step 5:

[0092] The device receives generated beauty improvement suggestions sent from the server and notifies the user. The user can visually review these suggestions on a dashboard through the application. If feedback is needed, the user can easily provide a response using the interface.

[0093] Step 6:

[0094] The server receives feedback from the user and updates the suggestions using a regeneration mechanism. The feedback is treated as new input data, which the AI ​​analyzes again to improve the accuracy of the suggestions, and modifies the content of the suggestions as needed. This output is an optimized version of the improved suggestions.

[0095] (Application Example 1)

[0096] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0097] Modern consumers increasingly seek personalized advice regarding hair health and style. However, traditional methods have struggled to provide timely and appropriate suggestions tailored to individual consumer needs and circumstances. Furthermore, there has been a lack of means to improve the quality of service provided by store staff during customer visits. Therefore, a new system is needed that provides optimal hair improvement suggestions to users and enhances practicality in stores.

[0098] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0099] In this invention, the server includes a generation means for receiving individual user information and generating hair improvement suggestions suitable for the user based on that information; an aggregation means for periodically collecting hair-related information from the internet and storing the collected information in a database; and a means for acquiring customer attribute information using a visual display device and presenting appropriate hair improvement suggestions to staff based on the aggregated information. This makes it possible to provide personalized and immediate hair improvement suggestions to customers who visit the store, thereby improving the quality of customer service at the store.

[0100] "Individual user information" refers to data related to each individual user, including sensor data from mobile devices and various data obtained from communication network services.

[0101] "Generation means" refers to a component or method for automatically generating suggestions for hair improvement based on individual user information.

[0102] "Aggregation means" refers to a component or method used to periodically collect hair-related information from the internet and organize and store that information in a database.

[0103] "Notification means" refers to a method or technique for informing the user of the generated hair improvement suggestions, and which provides information visually.

[0104] A "regeneration means" is a component or method for receiving feedback from the user and recreating the suggestions generated based on that feedback.

[0105] A "visual display device" is a device used to present information visually, and is used to acquire and display attribute information of customers.

[0106] This invention is a system that generates optimized hair improvement suggestions based on individual user information and provides them to store staff. The system is implemented by combining a server, terminals, and a visual display device.

[0107] First, the server collects individual user information. It utilizes sensor data obtained through the user's mobile device and data from communication network services. Using this information, the server generates hair improvement suggestions tailored to the user's needs using a generation method.

[0108] The server then periodically collects the latest information related to hair from the internet through aggregation means and stores this information in a database. This information is used to keep the suggestions provided to users fresh and effective.

[0109] In store implementations, visual display devices play a crucial role. Customer attribute information is acquired and analyzed via these visual display devices. Staff members wear devices that display suggestions in real time, enabling immediate and personalized advice for each customer.

[0110] As a concrete example, when a female customer in her 40s visits the store and inputs her lifestyle and hair concerns, a store staff member wearing smart glasses can instantly suggest nutritional intake and appropriate care products. The generative AI model used in this process uses prompts such as, "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0111] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0112] Step 1:

[0113] Users input information about their hair concerns and ideal hairstyles at a terminal in the store. This information is collected along with sensor data from the user's mobile device and relevant information publicly available on social networks. This allows for the acquisition of personalized attribute information about the user.

[0114] Step 2:

[0115] The server uses a generative AI model to generate personalized hair improvement suggestions based on collected user information. Here, user information is used as input data, and suggestions tailored to the user's lifestyle and current situation are output. This process utilizes the prompt message to the generative model: "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0116] Step 3:

[0117] The server periodically collects hair-related information from the internet and stores it in a database. This aggregation method accumulates foundational data for making suggestions that take into account the latest trends and research information.

[0118] Step 4:

[0119] The server notifies store staff of the generated hair improvement suggestions via a visual display device. The displayed information is personalized to the user, allowing store staff to respond to customers in real time. This enables quick and appropriate advice even for first-time customers.

[0120] Step 5:

[0121] After a user receives a suggestion, they provide feedback. This feedback is sent back to the server and used as a means of regenerating the suggestion to improve its quality. Based on the feedback, the suggestion is fine-tuned to further enhance user satisfaction and convenience.

[0122] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0123] This invention relates to a system that provides hair improvement suggestions tailored to the user by utilizing individual user information and emotional data. By incorporating an emotional engine, this system enables the personalization of suggestions in response to the user's emotions.

[0124] First, users use a dedicated application to input information about their hair concerns and desired style. In this step, data from sensors on their smartphone or other devices, as well as data collected from their statements and actions on social media, are used.

[0125] Next, the device sends the input information, sensor data, and SNS data to the server. In particular, the emotion engine analyzes the user's voice, facial expressions, and text input to measure their current emotional state. This emotion data is sent to the server along with information about other users.

[0126] The server integrates all received information and stores it in a database, collecting the latest hair-related information from the internet. Based on this information, the generation system generates optimal hair improvement suggestions for the user. This process also takes into account data from the emotion engine, providing suggestions tailored to the user's emotional state.

[0127] The generated suggestions are processed by the server and sent to the device in the form of a visual dashboard. Through this dashboard, users can review the suggested improvement plans and incorporate them into their lives as needed.

[0128] For example, if the emotion engine detects that a female user in her 40s tends to experience stress on weekends, the server will add self-care methods to alleviate stress to its hair improvement suggestions. Specifically, this might include suggestions for scalp massage in a relaxing environment or the use of essential oils with relaxation effects.

[0129] To elaborate, user feedback and emotional changes during program execution are constantly transmitted from the device to the server. This allows the server to use a regeneration mechanism to update the program based on the passage of time and new emotional data, enabling more accurate hair improvement suggestions.

[0130] Thus, the present invention enables personalized hair care based on individual user information, including emotional data, and provides effective solutions tailored to the unique needs of each user.

[0131] The following describes the processing flow.

[0132] Step 1:

[0133] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and ideal hairstyle. The emotion engine then measures the user's emotional state from their voice, facial expressions, and entered text.

[0134] Step 2:

[0135] The device encrypts all information entered by the user, data acquired by sensors, data from social media, and emotional data recognized by the emotion engine, and sends them to the server.

[0136] Step 3:

[0137] The server integrates all transmitted data and stores it in a database. It also updates the database by retrieving the latest hair-related information from the internet.

[0138] Step 4:

[0139] The server uses all currently available information to create hair improvement suggestions optimized for the user's current situation through a generation mechanism. In doing so, it reflects the user's emotional state in the suggestions, generating suggestions that are considerate of the user's feelings.

[0140] Step 5:

[0141] The server converts the generated hair improvement suggestions into a dashboard format and sends it to the terminal. The terminal then notifies the user in an intuitively easy-to-understand format.

[0142] Step 6:

[0143] Users review the dashboard and incorporate the suggested hair improvement plan into their daily lives. The plan may include self-care methods and lifestyle improvements tailored to the user's stress level.

[0144] Step 7:

[0145] Users input feedback on the implementation status and effectiveness of improvement plans into their devices, and sentiment data is continuously updated.

[0146] Step 8:

[0147] The device then sends the collected feedback and sentiment data back to the server.

[0148] Step 9:

[0149] The server uses feedback and the latest sentiment data to improve the accuracy of suggestions through regeneration mechanisms. It updates the suggested improvements as needed and notifies the user again.

[0150] Through this series of steps, the system consistently provides optimal hair care based on individual needs and emotions.

[0151] (Example 2)

[0152] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart device 14 as the "terminal".

[0153] Conventional hair improvement recommendation systems do not adequately personalize the system by considering the emotional state of individual users, making it difficult to provide effective recommendations based on the user's current mental and physical condition.

[0154] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0155] In this invention, the server includes means for receiving individual user information and generating hair improvement suggestions suitable for the user based on said information; means for periodically collecting hair-related information from the internet and storing said information in a storage means; and means for analyzing the user's emotional state and reflecting the analysis results in the suggestions. This makes it possible to provide more effective and personalized hair improvement suggestions that are tailored to the user's emotional state.

[0156] "Individual user information" refers to a series of data related to a specific user, including their concerns, desires, and emotional state regarding hair.

[0157] A "hair improvement suggestion" is specific advice and methods provided based on the user's hair-related problems and desires, aimed at improving hair health and style.

[0158] "Generation method" refers to a mechanism or process for creating hair improvement suggestions tailored to the user based on the input information.

[0159] "Hair-related information from the internet" refers to data such as the latest research, products, and news related to hair that are publicly available online.

[0160] A "storage device" is a system or device for safely and efficiently storing collected data.

[0161] "Notification means" refers to an intermediary device or mechanism for informing the user of the generated proposal, and includes visual or auditory means.

[0162] "Emotional state" refers to the user's psychological situation or mood at any given time, as judged from their voice, facial expressions, text, etc.

[0163] "Display means" refers to a screen or device that presents generated information or suggestions in a way that is easy for users to understand.

[0164] "Regeneration methods" refer to the process of improving or updating existing proposals based on feedback and new information.

[0165] The system in this invention aims to provide users with personalized hair improvement suggestions using individual user information and emotional data. The following describes the implementation of this system.

[0166] First, users install a dedicated application on their mobile device and input information about their hair concerns and ideal style. This input utilizes sensors on the mobile device to measure environmental conditions (temperature, humidity, etc.) and physical condition. With permission, data obtained from social networking services can also be used.

[0167] The device collects input information from the user and then transmits the data to the server using a secure communication method. The device also uses speech recognition technology to analyze the tone and pitch of the user's voice and utilizes this as emotion data.

[0168] The server performs data integration and analysis based on the individual user information and sentiment data received. It further analyzes the user's emotional state using a sentiment engine. By regularly collecting cutting-edge hair-related data from the internet and storing it in memory, it provides users with always up-to-date suggestions.

[0169] The generative AI model creates personalized hair improvement suggestions based on the user's emotional data and hair-related information. These suggestions are generated by inputting prompts on the server, which are then executed by the generative AI model. For example, a possible prompt might be, "A woman in her 40s; based on the results of the emotional engine, stress levels increase on weekends. Please suggest relaxing hair care methods."

[0170] The generated suggestions are sent back to the device as a visually easy-to-understand dashboard, allowing users to review the suggestions through the application and incorporate them into their daily lives. In this way, the system can provide flexible and effective suggestions that comprehensively consider the user's individual information and emotional state.

[0171] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0172] Step 1:

[0173] Users launch a dedicated application and input information about their hair concerns and desired hairstyle. They also use sensors on their mobile device to measure environmental data such as temperature and humidity. This input data is stored on the device as individual user information.

[0174] Step 2:

[0175] Before sending the collected user information to the server, the terminal performs data preprocessing. Specifically, it converts the data format, imputes missing values, and converts it into a package ready for transmission. This output data is then ready to be received by the server.

[0176] Step 3:

[0177] The server receives user information transmitted from the terminal and analyzes the user's emotional state using an emotion engine. Voice tone and text data from social media are used as input data. The emotional data obtained through data analysis is processed as input for a generative AI model.

[0178] Step 4:

[0179] The server collects the latest hair-related information from the internet and stores it in its storage device. This information is used as reference data in generating hair improvement suggestions. Subsequently, the server integrates the user's emotional data with the latest information to create a prompt message for the AI ​​model. This prompt message takes the form of, "A woman in her 40s, based on the results of the emotional engine, experiences increased stress on weekends. Please suggest relaxing hair care methods."

[0180] Step 5:

[0181] The server uses a generative AI model to create hair improvement suggestions tailored to the user's needs. Based on the input prompt text, the model performs calculations and outputs personalized suggestions.

[0182] Step 6:

[0183] The server converts the generated suggestions into a dashboard format and sends it to the terminal. The dashboard contains visually clear information in a format that is easy for the user to understand.

[0184] Step 7:

[0185] Users can view a dashboard through the application and incorporate suggested improvement plans into their lives. The regeneration process begins when they input feedback and their emotional state after use. Feedback information is sent from the device to the server, and the program is updated accordingly.

[0186] (Application Example 2)

[0187] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart device 14 will be referred to as the "terminal."

[0188] In modern society, users seek personalized lifestyle suggestions that respond to stress and emotional fluctuations, but conventional systems lack solutions that take emotional data into account. Furthermore, they are unable to provide effective suggestions across all aspects of the user's life. In particular, it is difficult to receive suggestions regarding both hair care and diet simultaneously, and the lack of a consistent solution is a problem.

[0189] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0190] This invention includes a server that receives individual user information and emotional data and generates hair improvement suggestions suitable for the user based on the information and emotional data; an aggregation means that periodically collects hair-related information from the internet and stores the collected information in a storage device; and a food and beverage suggestion generation means that generates food suggestions suitable for the user based on the user's emotional data. This enables comprehensive, personalized suggestions for hair improvement and food and beverages to the user using emotional data.

[0191] "Individual user information" refers to data such as user-specific profiles and history, which is used to generate personalized suggestions.

[0192] "Emotional data" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice, facial expressions, and text input.

[0193] The "generation means" refers to the part that has the function of generating suggestions tailored to individual users based on user information and sentiment data.

[0194] The "aggregation means" refers to the part that has the function of periodically collecting information and storing it in a database.

[0195] "Notification means" refers to the part that has the function of communicating the generated suggestions to the user, and includes visual displays.

[0196] The "regeneration mechanism" refers to the part that receives user feedback and updates suggestions based on that feedback.

[0197] The "food and beverage suggestion generation means" refers to the part that has the function of generating food-related suggestions based on the user's emotional data.

[0198] The system for implementing the present invention provides hair improvement and dietary recommendations using emotional data and individual user information. The system mainly consists of a server, a user terminal, and related software.

[0199] Server Role

[0200] The server integrates individual user information and emotional data to generate hair improvement suggestions based on this data. Emotional data is analyzed from the user's voice, facial expressions, and text. This data is processed using AWS® machine learning services and emotion analysis APIs. The server periodically collects hair-related information from the internet and stores it in a database. It also generates food and drink suggestions based on the user's emotional data and provides these suggestions comprehensively.

[0201] The role of the user terminal

[0202] The user's mobile device, such as a smartphone or tablet, collects sensor data and transmits it to the server. The device visually displays the acquired suggestions on a dashboard and notifies the user. When the user reviews the suggestions and sends feedback to the server via the device, the suggestions are regenerated, resulting in more accurate suggestions.

[0203] Specific example

[0204] For example, if emotional data is analyzed indicating that a user is feeling stressed over the weekend, a scalp massage using relaxing essential oils and a meal accompanied by chamomile tea might be suggested. Another example of a prompt message is, "How are you feeling today? If you're feeling tired, we'd like to suggest some relaxing options." Using such interactive prompts improves the user experience.

[0205] This system will enable holistic and personalized hair care and food and beverage recommendations that utilize emotional data.

[0206] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0207] Step 1:

[0208] Users enter individual user information via their device. This includes information about their current hair concerns, desired hairstyle, and preferred foods. The entered information is then sent from the device to the server.

[0209] Step 2:

[0210] The server integrates the received user information and emotion data. The emotion data is analyzed using an emotion analysis API based on the user's voice and facial expression data to determine their emotional state. It receives user voice and facial expression data as input and generates data indicating their emotional state as output.

[0211] Step 3:

[0212] The server collects information related to hair and food from the internet. It aggregates the latest trends and health data and stores it in a database. This involves using crawlers for information gathering and structuring and storing the data.

[0213] Step 4:

[0214] The system generates hair improvement and dietary recommendations based on the user's individual information, emotional data, and collected information. A generation AI model analyzes the data to generate optimal recommendations. The output is data containing detailed recommendations.

[0215] Step 5:

[0216] The notification system visually displays the generated suggestions on the user's device via a dashboard. This includes providing an interface that allows the user to review the content of the suggestions and presents them in a visually appealing way.

[0217] Step 6:

[0218] The user reviews the notified suggestion and provides feedback as needed. The feedback is then sent back to the server via the device. The feedback includes evaluations and comments on the suggestion.

[0219] Step 7:

[0220] The server processes the received feedback using a regeneration mechanism and updates the proposal. The feedback data is analyzed again with the regeneration AI model to optimize the proposal. This regeneration makes the next proposal more personalized and improves its accuracy.

[0221] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0222] Data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of data generation model 58 is ChatGPT (registered trademark) (Internet search).<URL: https: / / openai.com / blog / chatgpt> ), Gemini (registered trademark) (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0223] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart device 14.

[0224] [Second Embodiment]

[0225] Figure 3 shows an example of the configuration of the data processing system 210 according to the second embodiment.

[0226] As shown in Figure 3, the data processing system 210 includes a data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0227] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0228] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication interface 44. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, and camera 42 are also connected to the bus 52.

[0229] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0230] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0231] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0232] Figure 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Figure 4, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0233] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0234] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0235] In the smart glasses 214, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0236] Next, the identification processing performed by the identification processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0237] This invention is a system for providing hair improvement suggestions tailored to the user. This system collects individual user information and combines it with hair-related information from the internet to generate an optimal hair improvement program. Specific embodiments for carrying out this invention are described below.

[0238] First, users input information about their hair concerns and ideal hairstyle through a dedicated application. Furthermore, the application also acquires data from the user's smartphone sensors and information extracted from social networking services.

[0239] The terminal integrates this information and sends it to the server. The server then stores the collected user information in a database and gathers the latest hair-related information from the internet. This aggregation method ensures that user-related information is always up-to-date.

[0240] After the information is aggregated, the server uses a generation mechanism to generate hair improvement suggestions based on the individual user's information. Examples of suggestions include dietary improvements, exercise recommendations, and the use of specific hair care products.

[0241] The generated suggestions are notified to the user via their device. This notification method allows users to view specific improvement measures on a dashboard that is easy to understand visually.

[0242] The server also collects feedback from users and uses regeneration mechanisms to improve the suggestions. This allows the suggestions to adapt over time, increasing in accuracy and effectiveness.

[0243] For example, let's say a male user in his 40s uses this system. This user is concerned about thinning hair and has a habit of carrying a pedometer with him every day. When he logs into the application and enters his concerns about his hair, the server retrieves that information along with his step count data from his smartphone and saves it in the database.

[0244] The server then uses this information to generate a hair improvement program tailored to his lifestyle. The suggested improvements include increasing walking distance to improve blood flow and positively impact hair health, as well as actively consuming foods rich in specific vitamins.

[0245] As described above, the present invention provides hair improvement proposals optimized for individual users and offers solutions that meet the specific needs of users.

[0246] The following describes the processing flow.

[0247] Step 1:

[0248] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and desired hairstyle.

[0249] Step 2:

[0250] The device encrypts this input information and sends it to the server. Furthermore, with the user's permission, the device retrieves sensor data from the smartphone (e.g., steps, heart rate) and related data from social networking services.

[0251] Step 3:

[0252] The server integrates the received user information with sensor data and SNS data sent from the terminal and stores it in a database.

[0253] Step 4:

[0254] The server collects the latest information on hair in real time from various sources on the web and updates the database. This aggregation method ensures that the most up-to-date information is always available.

[0255] Step 5:

[0256] The server utilizes generation methods to automatically generate a hair improvement program optimized for each user, based on collected individual user information and hair-related information obtained from the web. The program includes nutritional guidance, exercise plans, and recommendations for hair care products.

[0257] Step 6:

[0258] The server sends the generated hair improvement program to the terminal in a visually easy-to-understand dashboard format and notifies the user.

[0259] Step 7:

[0260] Users review the provided dashboard and incorporate the suggested hair improvement program into their daily lives.

[0261] Step 8:

[0262] Users input the results of their program implementation and the effects they experienced into their device and send this feedback to the server.

[0263] Step 9:

[0264] Based on the feedback received, the server uses an AI model to further improve the program's accuracy through regeneration and updates the suggested content as needed.

[0265] Step 10:

[0266] The server resends the updated improvement program to the terminal, providing users with ongoing support.

[0267] (Example 1)

[0268] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0269] There is a need to address the diverse beauty challenges of various users and provide the latest, personalized beauty improvement suggestions. However, conventional technologies have made it difficult to efficiently generate suggestions tailored to users' lifestyles and specific needs and to incorporate feedback. Therefore, there is a need to develop a system that can provide more accurate suggestions to individual users.

[0270] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0271] In this invention, the server includes a generation means that receives individual user data and generates beauty improvement suggestions tailored to the user based on the data; an aggregation means that periodically collects beauty-related information from a communication network and stores the collected information in a data storage device; and a notification means that notifies the user of the beauty improvement suggestions generated by the generation means. This makes it possible to continuously provide the latest beauty improvement suggestions tailored to the individual needs of the user.

[0272] "User data" refers to information related to the beauty of individual users, and includes sensor information obtained from mobile devices and data from information sharing services.

[0273] "Beauty improvement suggestions" refer to information that provides specific guidance and recommendations to address users' beauty-related concerns.

[0274] A "generation method" is a system component that has the function of creating beauty improvement suggestions based on user data.

[0275] "Aggregation means" refers to a system component that has the function of storing beauty-related information collected via a communication network in a data storage device.

[0276] "Notification means" refers to a means of informing users of generated beauty improvement suggestions, and includes technologies for visually displaying information.

[0277] A "regeneration mechanism" is a system component that improves the suggestions generated by the generation mechanism based on user responses, and continuously provides more appropriate suggestions.

[0278] This invention is a system for providing users with personalized beauty improvement suggestions. This system receives individual user data, generates suggestions using a generative AI model, and periodically collects the latest information from the internet to provide information tailored to the user. A detailed description of how to implement this invention is provided below.

[0279] The user uses a dedicated application to input information about their beauty concerns and goals. This application can utilize the smartphone's camera and location information service to obtain sensor information regarding the user's current state. Additionally, it collects interest and activity information related to beauty from social network services.

[0280] The terminal aggregates the information obtained from the user and transmits it to the server via secure communication means. In this process, the operating system and communication protocol of the mobile device are utilized.

[0281] The server stores the received user data in a database. Furthermore, it uses a web crawler to collect reliable beauty-related information on the Internet and accumulates it in the database. Thereby, an AI model generated by combining user data and the latest external information generates proposals. The content of the generated proposals includes nutritional guidance, exercise advice, recommended beauty products, etc.

[0282] The generated beauty improvement proposals are notified to the user through the terminal. The user can view the proposals on the dashboard within the application and selectively provide feedback. This feedback is sent back to the server and used to improve the proposals as a regeneration means.

[0283] For example, by inputting a prompt sentence such as "Please propose lifestyle habits for a 30-year-old woman to achieve voluminous hair." into the generated AI model, specific and user-specific improvement plans are provided. Thereby, the user can receive practical and meaningful information to meet their individual beauty needs.

[0284] The flow of the specific process in Example 1 will be described using FIG. 11.

[0285] Step 1:

[0286] The user launches the application and enters their concerns and goals regarding hair and beauty. The input data also includes the user's preferences and daily activity data. For example, image data of the hair condition is taken, and information on recent meals and exercise is recorded. This information becomes the initial input data for the system.

[0287] Step 2:

[0288] The terminal aggregates the data input by the user. Specifically, it integrates the input data within the application and the activity information obtained through sensors, and formats it as one data package. This package is encrypted using a communication protocol and securely sent to the server.

[0289] Step 3:

[0290] The server saves the received user data in the database. The server uses this data to collect the latest beauty-related information from the Internet. This collected data is regularly crawled from specific Internet resources and saved in the database. The output here is a huge dataset that integrates user data and Internet information.

[0291] Step 4:

[0292] The server uses a generative AI model to generate personalized beauty improvement suggestions from the integrated dataset. It takes the user's activity data and the latest information as inputs, and the AI algorithm analyzes the correlations between the data. As a result, improvement suggestions tailored to the user's needs are output. These suggestions include specific information regarding, for example, diet improvement, changes in exercise habits, and recommendations for beauty products.

[0293] Step 5:

[0294] The device receives generated beauty improvement suggestions sent from the server and notifies the user. The user can visually review these suggestions on a dashboard through the application. If feedback is needed, the user can easily provide a response using the interface.

[0295] Step 6:

[0296] The server receives feedback from the user and updates the suggestions using a regeneration mechanism. The feedback is treated as new input data, which the AI ​​analyzes again to improve the accuracy of the suggestions, and modifies the content of the suggestions as needed. This output is an optimized version of the improved suggestions.

[0297] (Application Example 1)

[0298] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the smart glasses 214 will be referred to as the "terminal."

[0299] Modern consumers increasingly seek personalized advice regarding hair health and style. However, traditional methods have struggled to provide timely and appropriate suggestions tailored to individual consumer needs and circumstances. Furthermore, there has been a lack of means to improve the quality of service provided by store staff during customer visits. Therefore, a new system is needed that provides optimal hair improvement suggestions to users and enhances practicality in stores.

[0300] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0301] In this invention, the server includes: a generating means for receiving individual user information and generating a hair improvement proposal suitable for the user based on the information; an aggregating means for periodically collecting hair-related information from the Internet and storing the collected information in a database; and a means for acquiring the attribute information of the visitors using a visual display device and presenting an appropriate hair improvement proposal to the staff based on the aggregated information. As a result, it becomes possible to provide a personal and immediate hair improvement proposal to the consumers who visit the store, and the quality of customer service at the store can be improved.

[0302] "Individual user information" refers to data related to each individual user, and includes information such as sensor data from a mobile device and various data obtained from a communication network service.

[0303] The "generating means" is a component or method for automatically generating a proposal for hair improvement based on individual user information.

[0304] The "aggregating means" is a component or method used to periodically collect hair-related information from the Internet and organize and store the information in a database.

[0305] The "notifying means" is a method or technology for notifying the user of the generated hair improvement proposal, and provides information visually.

[0306] The "regenerating means" is a component or method for receiving feedback from the user and re-creating the generated proposal based on the feedback.

[0307] The "visual display device" is a device for visually presenting information, and is used to acquire the attribute information of the visitors and display the information.

[0308] This invention is a system that generates optimized hair improvement suggestions based on individual user information and provides them to store staff. The system is implemented by combining a server, terminals, and a visual display device.

[0309] First, the server collects individual user information. It utilizes sensor data obtained through the user's mobile device and data from communication network services. Using this information, the server generates hair improvement suggestions tailored to the user's needs using a generation method.

[0310] The server then periodically collects the latest information related to hair from the internet through aggregation means and stores this information in a database. This information is used to keep the suggestions provided to users fresh and effective.

[0311] In store implementations, visual display devices play a crucial role. Customer attribute information is acquired and analyzed via these visual display devices. Staff members wear devices that display suggestions in real time, enabling immediate and personalized advice for each customer.

[0312] As a concrete example, when a female customer in her 40s visits the store and inputs her lifestyle and hair concerns, a store staff member wearing smart glasses can instantly suggest nutritional intake and appropriate care products. The generative AI model used in this process uses prompts such as, "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0313] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0314] Step 1:

[0315] Users input information about their hair concerns and ideal hairstyles at a terminal in the store. This information is collected along with sensor data from the user's mobile device and relevant information publicly available on social networks. This allows for the acquisition of personalized attribute information about the user.

[0316] Step 2:

[0317] The server uses a generative AI model to generate personalized hair improvement suggestions based on collected user information. Here, user information is used as input data, and suggestions tailored to the user's lifestyle and current situation are output. This process utilizes the prompt message to the generative model: "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0318] Step 3:

[0319] The server periodically collects hair-related information from the internet and stores it in a database. This aggregation method accumulates foundational data for making suggestions that take into account the latest trends and research information.

[0320] Step 4:

[0321] The server notifies store staff of the generated hair improvement suggestions via a visual display device. The displayed information is personalized to the user, allowing store staff to respond to customers in real time. This enables quick and appropriate advice even for first-time customers.

[0322] Step 5:

[0323] After a user receives a suggestion, they provide feedback. This feedback is sent back to the server and used as a means of regenerating the suggestion to improve its quality. Based on the feedback, the suggestion is fine-tuned to further enhance user satisfaction and convenience.

[0324] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0325] This invention relates to a system that provides hair improvement suggestions tailored to the user by utilizing individual user information and emotional data. By incorporating an emotional engine, this system enables the personalization of suggestions in response to the user's emotions.

[0326] First, users use a dedicated application to input information about their hair concerns and desired style. In this step, data from sensors on their smartphone or other devices, as well as data collected from their statements and actions on social media, are used.

[0327] Next, the device sends the input information, sensor data, and SNS data to the server. In particular, the emotion engine analyzes the user's voice, facial expressions, and text input to measure their current emotional state. This emotion data is sent to the server along with information about other users.

[0328] The server integrates all received information and stores it in a database, collecting the latest hair-related information from the internet. Based on this information, the generation system generates optimal hair improvement suggestions for the user. This process also takes into account data from the emotion engine, providing suggestions tailored to the user's emotional state.

[0329] The generated suggestions are processed by the server and sent to the device in the form of a visual dashboard. Through this dashboard, users can review the suggested improvement plans and incorporate them into their lives as needed.

[0330] For example, if the emotion engine detects that a female user in her 40s tends to experience stress on weekends, the server will add self-care methods to alleviate stress to its hair improvement suggestions. Specifically, this might include suggestions for scalp massage in a relaxing environment or the use of essential oils with relaxation effects.

[0331] To elaborate, user feedback and emotional changes during program execution are constantly transmitted from the device to the server. This allows the server to use a regeneration mechanism to update the program based on the passage of time and new emotional data, enabling more accurate hair improvement suggestions.

[0332] Thus, the present invention enables personalized hair care based on individual user information, including emotional data, and provides effective solutions tailored to the unique needs of each user.

[0333] The following describes the processing flow.

[0334] Step 1:

[0335] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and ideal hairstyle. The emotion engine then measures the user's emotional state from their voice, facial expressions, and entered text.

[0336] Step 2:

[0337] The device encrypts all information entered by the user, data acquired by sensors, data from social media, and emotional data recognized by the emotion engine, and sends them to the server.

[0338] Step 3:

[0339] The server integrates all transmitted data and stores it in a database. It also updates the database by retrieving the latest hair-related information from the internet.

[0340] Step 4:

[0341] The server uses all currently available information to create hair improvement suggestions optimized for the user's current situation through a generation mechanism. In doing so, it reflects the user's emotional state in the suggestions, generating suggestions that are considerate of the user's feelings.

[0342] Step 5:

[0343] The server converts the generated hair improvement suggestions into a dashboard format and sends it to the terminal. The terminal then notifies the user in an intuitively easy-to-understand format.

[0344] Step 6:

[0345] Users review the dashboard and incorporate the suggested hair improvement plan into their daily lives. The plan may include self-care methods and lifestyle improvements tailored to the user's stress level.

[0346] Step 7:

[0347] Users input feedback on the implementation status and effectiveness of improvement plans into their devices, and sentiment data is continuously updated.

[0348] Step 8:

[0349] The device then sends the collected feedback and sentiment data back to the server.

[0350] Step 9:

[0351] The server uses feedback and the latest sentiment data to improve the accuracy of suggestions through regeneration mechanisms. It updates the suggested improvements as needed and notifies the user again.

[0352] Through this series of steps, the system consistently provides optimal hair care based on individual needs and emotions.

[0353] (Example 2)

[0354] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal".

[0355] Conventional hair improvement recommendation systems do not adequately personalize the system by considering the emotional state of individual users, making it difficult to provide effective recommendations based on the user's current mental and physical condition.

[0356] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0357] In this invention, the server includes means for receiving individual user information and generating hair improvement suggestions suitable for the user based on said information; means for periodically collecting hair-related information from the internet and storing said information in a storage means; and means for analyzing the user's emotional state and reflecting the analysis results in the suggestions. This makes it possible to provide more effective and personalized hair improvement suggestions that are tailored to the user's emotional state.

[0358] "Individual user information" refers to a series of data related to a specific user, including their concerns, desires, and emotional state regarding hair.

[0359] A "hair improvement suggestion" is specific advice and methods provided based on the user's hair-related problems and desires, aimed at improving hair health and style.

[0360] "Generation method" refers to a mechanism or process for creating hair improvement suggestions tailored to the user based on the input information.

[0361] "Hair-related information from the internet" refers to data such as the latest research, products, and news related to hair that are publicly available online.

[0362] A "storage device" is a system or device for safely and efficiently storing collected data.

[0363] "Notification means" refers to an intermediary device or mechanism for informing the user of the generated proposal, and includes visual or auditory means.

[0364] "Emotional state" refers to the user's psychological situation or mood at any given time, as judged from their voice, facial expressions, text, etc.

[0365] "Display means" refers to a screen or device that presents generated information or suggestions in a way that is easy for users to understand.

[0366] "Regeneration methods" refer to the process of improving or updating existing proposals based on feedback and new information.

[0367] The system in this invention aims to provide users with personalized hair improvement suggestions using individual user information and emotional data. The following describes the implementation of this system.

[0368] First, users install a dedicated application on their mobile device and input information about their hair concerns and ideal style. This input utilizes sensors on the mobile device to measure environmental conditions (temperature, humidity, etc.) and physical condition. With permission, data obtained from social networking services can also be used.

[0369] The device collects input information from the user and then transmits the data to the server using a secure communication method. The device also uses speech recognition technology to analyze the tone and pitch of the user's voice and utilizes this as emotion data.

[0370] The server performs data integration and analysis based on the individual user information and sentiment data received. It further analyzes the user's emotional state using a sentiment engine. By regularly collecting cutting-edge hair-related data from the internet and storing it in memory, it provides users with always up-to-date suggestions.

[0371] The generative AI model creates personalized hair improvement suggestions based on the user's emotional data and hair-related information. These suggestions are generated by inputting prompts on the server, which are then executed by the generative AI model. For example, a possible prompt might be, "A woman in her 40s; based on the results of the emotional engine, stress levels increase on weekends. Please suggest relaxing hair care methods."

[0372] The generated suggestions are sent back to the device as a visually easy-to-understand dashboard, allowing users to review the suggestions through the application and incorporate them into their daily lives. In this way, the system can provide flexible and effective suggestions that comprehensively consider the user's individual information and emotional state.

[0373] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0374] Step 1:

[0375] Users launch a dedicated application and input information about their hair concerns and desired hairstyle. They also use sensors on their mobile device to measure environmental data such as temperature and humidity. This input data is stored on the device as individual user information.

[0376] Step 2:

[0377] Before sending the collected user information to the server, the terminal performs data preprocessing. Specifically, it converts the data format, imputes missing values, and converts it into a package ready for transmission. This output data is then ready to be received by the server.

[0378] Step 3:

[0379] The server receives user information transmitted from the terminal and analyzes the user's emotional state using an emotion engine. Voice tone and text data from social media are used as input data. The emotional data obtained through data analysis is processed as input for a generative AI model.

[0380] Step 4:

[0381] The server collects the latest hair-related information from the internet and stores it in its storage device. This information is used as reference data in generating hair improvement suggestions. Subsequently, the server integrates the user's emotional data with the latest information to create a prompt message for the AI ​​model. This prompt message takes the form of, "A woman in her 40s, based on the results of the emotional engine, experiences increased stress on weekends. Please suggest relaxing hair care methods."

[0382] Step 5:

[0383] The server uses a generative AI model to create hair improvement suggestions tailored to the user's needs. Based on the input prompt text, the model performs calculations and outputs personalized suggestions.

[0384] Step 6:

[0385] The server converts the generated suggestions into a dashboard format and sends it to the terminal. The dashboard contains visually clear information in a format that is easy for the user to understand.

[0386] Step 7:

[0387] Users can view a dashboard through the application and incorporate suggested improvement plans into their lives. The regeneration process begins when they input feedback and their emotional state after use. Feedback information is sent from the device to the server, and the program is updated accordingly.

[0388] (Application Example 2)

[0389] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the smart glasses 214 as the "terminal".

[0390] In modern society, users seek personalized lifestyle suggestions that respond to stress and emotional fluctuations, but conventional systems lack solutions that take emotional data into account. Furthermore, they are unable to provide effective suggestions across all aspects of the user's life. In particular, it is difficult to receive suggestions regarding both hair care and diet simultaneously, and the lack of a consistent solution is a problem.

[0391] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0392] This invention includes a server that receives individual user information and emotional data and generates hair improvement suggestions suitable for the user based on the information and emotional data; an aggregation means that periodically collects hair-related information from the internet and stores the collected information in a storage device; and a food and beverage suggestion generation means that generates food suggestions suitable for the user based on the user's emotional data. This enables comprehensive, personalized suggestions for hair improvement and food and beverages to the user using emotional data.

[0393] "Individual user information" refers to data such as user-specific profiles and history, which is used to generate personalized suggestions.

[0394] "Emotional data" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice, facial expressions, and text input.

[0395] The "generation means" refers to the part that has the function of generating suggestions tailored to individual users based on user information and sentiment data.

[0396] The "aggregation means" refers to the part that has the function of periodically collecting information and storing it in a database.

[0397] "Notification means" refers to the part that has the function of communicating the generated suggestions to the user, and includes visual displays.

[0398] The "regeneration mechanism" refers to the part that receives user feedback and updates suggestions based on that feedback.

[0399] The "food and beverage suggestion generation means" refers to the part that has the function of generating food-related suggestions based on the user's emotional data.

[0400] The system for implementing the present invention provides hair improvement and dietary recommendations using emotional data and individual user information. The system mainly consists of a server, a user terminal, and related software.

[0401] Server Role

[0402] The server integrates individual user information and emotional data to generate hair improvement suggestions based on this data. Emotional data is analyzed from the user's voice, facial expressions, and text. AWS machine learning services and emotion analysis APIs are used to process this data. The server periodically collects hair-related information from the internet and stores it in a database. It also generates food and drink suggestions based on the user's emotional data and provides these suggestions comprehensively.

[0403] The role of the user terminal

[0404] The user's mobile device, such as a smartphone or tablet, collects sensor data and transmits it to the server. The device visually displays the acquired suggestions on a dashboard and notifies the user. When the user reviews the suggestions and sends feedback to the server via the device, the suggestions are regenerated, resulting in more accurate suggestions.

[0405] Specific example

[0406] For example, if emotional data is analyzed indicating that a user is feeling stressed over the weekend, a scalp massage using relaxing essential oils and a meal accompanied by chamomile tea might be suggested. Another example of a prompt message is, "How are you feeling today? If you're feeling tired, we'd like to suggest some relaxing options." Using such interactive prompts improves the user experience.

[0407] This system will enable holistic and personalized hair care and food and beverage recommendations that utilize emotional data.

[0408] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0409] Step 1:

[0410] Users enter individual user information via their device. This includes information about their current hair concerns, desired hairstyle, and preferred foods. The entered information is then sent from the device to the server.

[0411] Step 2:

[0412] The server integrates the received user information and emotion data. The emotion data is analyzed using an emotion analysis API based on the user's voice and facial expression data to determine their emotional state. It receives user voice and facial expression data as input and generates data indicating their emotional state as output.

[0413] Step 3:

[0414] The server collects information related to hair and food from the internet. It aggregates the latest trends and health data and stores it in a database. This involves using crawlers for information gathering and structuring and storing the data.

[0415] Step 4:

[0416] The system generates hair improvement and dietary recommendations based on the user's individual information, emotional data, and collected information. A generation AI model analyzes the data to generate optimal recommendations. The output is data containing detailed recommendations.

[0417] Step 5:

[0418] The notification system visually displays the generated suggestions on the user's device via a dashboard. This includes providing an interface that allows the user to review the content of the suggestions and presents them in a visually appealing way.

[0419] Step 6:

[0420] The user reviews the notified suggestion and provides feedback as needed. The feedback is then sent back to the server via the device. The feedback includes evaluations and comments on the suggestion.

[0421] Step 7:

[0422] The server processes the received feedback using a regeneration mechanism and updates the proposal. The feedback data is analyzed again with the regeneration AI model to optimize the proposal. This regeneration makes the next proposal more personalized and improves its accuracy.

[0423] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0424] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0425] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the smart glasses 214.

[0426] [Third Embodiment]

[0427] Figure 5 shows an example of the configuration of the data processing system 310 according to the third embodiment.

[0428] As shown in Figure 5, the data processing system 310 includes a data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0429] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0430] The headset terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a display 343. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and display 343 are also connected to the bus 52.

[0431] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0432] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0433] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0434] Figure 6 shows an example of the main functions of the data processing device 12 and the headset terminal 314. As shown in Figure 6, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0435] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0436] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0437] In the headset terminal 314, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0438] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the headset terminal 314 will be referred to as the "terminal".

[0439] This invention is a system for providing hair improvement suggestions tailored to the user. This system collects individual user information and combines it with hair-related information from the internet to generate an optimal hair improvement program. Specific embodiments for carrying out this invention are described below.

[0440] First, users input information about their hair concerns and ideal hairstyle through a dedicated application. Furthermore, the application also acquires data from the user's smartphone sensors and information extracted from social networking services.

[0441] The terminal integrates this information and sends it to the server. The server then stores the collected user information in a database and gathers the latest hair-related information from the internet. This aggregation method ensures that user-related information is always up-to-date.

[0442] After the information is aggregated, the server uses a generation mechanism to generate hair improvement suggestions based on the individual user's information. Examples of suggestions include dietary improvements, exercise recommendations, and the use of specific hair care products.

[0443] The generated suggestions are notified to the user via their device. This notification method allows users to view specific improvement measures on a dashboard that is easy to understand visually.

[0444] The server also collects feedback from users and uses regeneration mechanisms to improve the suggestions. This allows the suggestions to adapt over time, increasing in accuracy and effectiveness.

[0445] For example, let's say a male user in his 40s uses this system. This user is concerned about thinning hair and has a habit of carrying a pedometer with him every day. When he logs into the application and enters his concerns about his hair, the server retrieves that information along with his step count data from his smartphone and saves it in the database.

[0446] The server then uses this information to generate a hair improvement program tailored to his lifestyle. The suggested improvements include increasing walking distance to improve blood flow and positively impact hair health, as well as actively consuming foods rich in specific vitamins.

[0447] As described above, the present invention provides hair improvement proposals optimized for individual users and offers solutions that meet the specific needs of users.

[0448] The following describes the processing flow.

[0449] Step 1:

[0450] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and desired hairstyle.

[0451] Step 2:

[0452] The device encrypts this input information and sends it to the server. Furthermore, with the user's permission, the device retrieves sensor data from the smartphone (e.g., steps, heart rate) and related data from social networking services.

[0453] Step 3:

[0454] The server integrates the received user information with sensor data and SNS data sent from the terminal and stores it in a database.

[0455] Step 4:

[0456] The server collects the latest information on hair in real time from various sources on the web and updates the database. This aggregation method ensures that the most up-to-date information is always available.

[0457] Step 5:

[0458] The server utilizes generation methods to automatically generate a hair improvement program optimized for each user, based on collected individual user information and hair-related information obtained from the web. The program includes nutritional guidance, exercise plans, and recommendations for hair care products.

[0459] Step 6:

[0460] The server sends the generated hair improvement program to the terminal in a visually easy-to-understand dashboard format and notifies the user.

[0461] Step 7:

[0462] Users review the provided dashboard and incorporate the suggested hair improvement program into their daily lives.

[0463] Step 8:

[0464] Users input the results of their program implementation and the effects they experienced into their device and send this feedback to the server.

[0465] Step 9:

[0466] Based on the feedback received, the server uses an AI model to further improve the program's accuracy through regeneration and updates the suggested content as needed.

[0467] Step 10:

[0468] The server resends the updated improvement program to the terminal, providing users with ongoing support.

[0469] (Example 1)

[0470] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0471] There is a need to address the diverse beauty challenges of various users and provide the latest, personalized beauty improvement suggestions. However, conventional technologies have made it difficult to efficiently generate suggestions tailored to users' lifestyles and specific needs and to incorporate feedback. Therefore, there is a need to develop a system that can provide more accurate suggestions to individual users.

[0472] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0473] In this invention, the server includes a generation means that receives individual user data and generates beauty improvement suggestions tailored to the user based on the data; an aggregation means that periodically collects beauty-related information from a communication network and stores the collected information in a data storage device; and a notification means that notifies the user of the beauty improvement suggestions generated by the generation means. This makes it possible to continuously provide the latest beauty improvement suggestions tailored to the individual needs of the user.

[0474] "User data" refers to information related to the beauty of individual users, and includes sensor information obtained from mobile devices and data from information sharing services.

[0475] "Beauty improvement suggestions" refer to information that provides specific guidance and recommendations to address users' beauty-related concerns.

[0476] A "generation method" is a system component that has the function of creating beauty improvement suggestions based on user data.

[0477] "Aggregation means" refers to a system component that has the function of storing beauty-related information collected via a communication network in a data storage device.

[0478] "Notification means" refers to a means of informing users of generated beauty improvement suggestions, and includes technologies for visually displaying information.

[0479] A "regeneration mechanism" is a system component that improves the suggestions generated by the generation mechanism based on user responses, and continuously provides more appropriate suggestions.

[0480] This invention is a system for providing users with personalized beauty improvement suggestions. This system receives individual user data, generates suggestions using a generative AI model, and periodically collects the latest information from the internet to provide information tailored to the user. A detailed description of how to implement this invention is provided below.

[0481] Users input information about their beauty concerns and goals using a dedicated application. This application can acquire sensor information about the user's current state using the smartphone's camera and location services. It also collects information about beauty-related interests and activities from social networking services.

[0482] The device aggregates information obtained from the user and transmits it to the server via a secure communication method. This process utilizes the mobile device's operating system and communication protocols.

[0483] The server stores received user data in a database. Furthermore, it uses a web crawler to collect reliable beauty-related information from the internet and stores it in the database. This allows a generative AI model to combine user data with the latest external information to generate suggestions. These suggestions include nutritional guidance, exercise advice, and recommended beauty products.

[0484] The generated beauty improvement suggestions are notified to the user via their device. The user can view the suggestions on a dashboard within the application and selectively provide feedback. This feedback is sent back to the server and used to improve the suggestions as a means of regeneration.

[0485] For example, by inputting a prompt such as, "Please suggest lifestyle habits for a woman in her 30s to achieve voluminous hair," into the AI ​​model, specific and user-specific improvement suggestions are provided. This allows users to receive practical and meaningful information to meet their individual beauty needs.

[0486] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0487] Step 1:

[0488] The user launches the application and enters their concerns and goals regarding hair and beauty. This input data also includes the user's preferences and daily activity data. For example, it might record image data of their hair condition and information about their recent diet and exercise. This information becomes the system's initial input data.

[0489] Step 2:

[0490] The terminal aggregates data entered by the user. Specifically, it integrates input data from the application with activity information acquired through sensors and formats it into a single data package. This package is encrypted using a communication protocol and securely transmitted to the server.

[0491] Step 3:

[0492] The server stores received user data in a database. The server uses this data to collect the latest beauty-related information from the internet. This collected data is periodically crawled from specific internet resources and stored in the database. The output here is a massive dataset integrating user data and internet information.

[0493] Step 4:

[0494] The server uses a generative AI model to generate personalized beauty improvement suggestions from an integrated dataset. It takes user activity data and recent information as input, and the AI ​​algorithm analyzes the relationships between the data. This results in improvement suggestions tailored to the user's needs. These suggestions include specific information such as dietary improvements, changes in exercise habits, and recommendations for beauty products.

[0495] Step 5:

[0496] The device receives generated beauty improvement suggestions sent from the server and notifies the user. The user can visually review these suggestions on a dashboard through the application. If feedback is needed, the user can easily provide a response using the interface.

[0497] Step 6:

[0498] The server receives feedback from the user and updates the suggestions using a regeneration mechanism. The feedback is treated as new input data, which the AI ​​analyzes again to improve the accuracy of the suggestions, and modifies the content of the suggestions as needed. This output is an optimized version of the improved suggestions.

[0499] (Application Example 1)

[0500] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0501] Modern consumers increasingly seek personalized advice regarding hair health and style. However, traditional methods have struggled to provide timely and appropriate suggestions tailored to individual consumer needs and circumstances. Furthermore, there has been a lack of means to improve the quality of service provided by store staff during customer visits. Therefore, a new system is needed that provides optimal hair improvement suggestions to users and enhances practicality in stores.

[0502] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0503] In this invention, the server includes a generation means for receiving individual user information and generating hair improvement suggestions suitable for the user based on that information; an aggregation means for periodically collecting hair-related information from the internet and storing the collected information in a database; and a means for acquiring customer attribute information using a visual display device and presenting appropriate hair improvement suggestions to staff based on the aggregated information. This makes it possible to provide personalized and immediate hair improvement suggestions to customers who visit the store, thereby improving the quality of customer service at the store.

[0504] "Individual user information" refers to data related to each individual user, including sensor data from mobile devices and various data obtained from communication network services.

[0505] "Generation means" refers to a component or method for automatically generating suggestions for hair improvement based on individual user information.

[0506] "Aggregation means" refers to a component or method used to periodically collect hair-related information from the internet and organize and store that information in a database.

[0507] "Notification means" refers to a method or technique for informing the user of the generated hair improvement suggestions, and which provides information visually.

[0508] A "regeneration means" is a component or method for receiving feedback from the user and recreating the suggestions generated based on that feedback.

[0509] A "visual display device" is a device used to present information visually, and is used to acquire and display attribute information of customers.

[0510] This invention is a system that generates optimized hair improvement suggestions based on individual user information and provides them to store staff. The system is implemented by combining a server, terminals, and a visual display device.

[0511] First, the server collects individual user information. It utilizes sensor data obtained through the user's mobile device and data from communication network services. Using this information, the server generates hair improvement suggestions tailored to the user's needs using a generation method.

[0512] The server then periodically collects the latest information related to hair from the internet through aggregation means and stores this information in a database. This information is used to keep the suggestions provided to users fresh and effective.

[0513] In store implementations, visual display devices play a crucial role. Customer attribute information is acquired and analyzed via these visual display devices. Staff members wear devices that display suggestions in real time, enabling immediate and personalized advice for each customer.

[0514] As a concrete example, when a female customer in her 40s visits the store and inputs her lifestyle and hair concerns, a store staff member wearing smart glasses can instantly suggest nutritional intake and appropriate care products. The generative AI model used in this process uses prompts such as, "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0515] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0516] Step 1:

[0517] Users input information about their hair concerns and ideal hairstyles at a terminal in the store. This information is collected along with sensor data from the user's mobile device and relevant information publicly available on social networks. This allows for the acquisition of personalized attribute information about the user.

[0518] Step 2:

[0519] The server uses a generative AI model to generate personalized hair improvement suggestions based on collected user information. Here, user information is used as input data, and suggestions tailored to the user's lifestyle and current situation are output. This process utilizes the prompt message to the generative model: "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0520] Step 3:

[0521] The server periodically collects hair-related information from the internet and stores it in a database. This aggregation method accumulates foundational data for making suggestions that take into account the latest trends and research information.

[0522] Step 4:

[0523] The server notifies store staff of the generated hair improvement suggestions via a visual display device. The displayed information is personalized to the user, allowing store staff to respond to customers in real time. This enables quick and appropriate advice even for first-time customers.

[0524] Step 5:

[0525] After a user receives a suggestion, they provide feedback. This feedback is sent back to the server and used as a means of regenerating the suggestion to improve its quality. Based on the feedback, the suggestion is fine-tuned to further enhance user satisfaction and convenience.

[0526] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0527] This invention relates to a system that provides hair improvement suggestions tailored to the user by utilizing individual user information and emotional data. By incorporating an emotional engine, this system enables the personalization of suggestions in response to the user's emotions.

[0528] First, users use a dedicated application to input information about their hair concerns and desired style. In this step, data from sensors on their smartphone or other devices, as well as data collected from their statements and actions on social media, are used.

[0529] Next, the device sends the input information, sensor data, and SNS data to the server. In particular, the emotion engine analyzes the user's voice, facial expressions, and text input to measure their current emotional state. This emotion data is sent to the server along with information about other users.

[0530] The server integrates all received information and stores it in a database, collecting the latest hair-related information from the internet. Based on this information, the generation system generates optimal hair improvement suggestions for the user. This process also takes into account data from the emotion engine, providing suggestions tailored to the user's emotional state.

[0531] The generated suggestions are processed by the server and sent to the device in the form of a visual dashboard. Through this dashboard, users can review the suggested improvement plans and incorporate them into their lives as needed.

[0532] For example, if the emotion engine detects that a female user in her 40s tends to experience stress on weekends, the server will add self-care methods to alleviate stress to its hair improvement suggestions. Specifically, this might include suggestions for scalp massage in a relaxing environment or the use of essential oils with relaxation effects.

[0533] To elaborate, user feedback and emotional changes during program execution are constantly transmitted from the device to the server. This allows the server to use a regeneration mechanism to update the program based on the passage of time and new emotional data, enabling more accurate hair improvement suggestions.

[0534] Thus, the present invention enables personalized hair care based on individual user information, including emotional data, and provides effective solutions tailored to the unique needs of each user.

[0535] The following describes the processing flow.

[0536] Step 1:

[0537] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and ideal hairstyle. The emotion engine then measures the user's emotional state from their voice, facial expressions, and entered text.

[0538] Step 2:

[0539] The device encrypts all information entered by the user, data acquired by sensors, data from social media, and emotional data recognized by the emotion engine, and sends them to the server.

[0540] Step 3:

[0541] The server integrates all transmitted data and stores it in a database. It also updates the database by retrieving the latest hair-related information from the internet.

[0542] Step 4:

[0543] The server uses all currently available information to create hair improvement suggestions optimized for the user's current situation through a generation mechanism. In doing so, it reflects the user's emotional state in the suggestions, generating suggestions that are considerate of the user's feelings.

[0544] Step 5:

[0545] The server converts the generated hair improvement suggestions into a dashboard format and sends it to the terminal. The terminal then notifies the user in an intuitively easy-to-understand format.

[0546] Step 6:

[0547] Users review the dashboard and incorporate the suggested hair improvement plan into their daily lives. The plan may include self-care methods and lifestyle improvements tailored to the user's stress level.

[0548] Step 7:

[0549] Users input feedback on the implementation status and effectiveness of improvement plans into their devices, and sentiment data is continuously updated.

[0550] Step 8:

[0551] The device then sends the collected feedback and sentiment data back to the server.

[0552] Step 9:

[0553] The server uses feedback and the latest sentiment data to improve the accuracy of suggestions through regeneration mechanisms. It updates the suggested improvements as needed and notifies the user again.

[0554] Through this series of steps, the system consistently provides optimal hair care based on individual needs and emotions.

[0555] (Example 2)

[0556] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0557] Conventional hair improvement recommendation systems do not adequately personalize the system by considering the emotional state of individual users, making it difficult to provide effective recommendations based on the user's current mental and physical condition.

[0558] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0559] In this invention, the server includes means for receiving individual user information and generating hair improvement suggestions suitable for the user based on said information; means for periodically collecting hair-related information from the internet and storing said information in a storage means; and means for analyzing the user's emotional state and reflecting the analysis results in the suggestions. This makes it possible to provide more effective and personalized hair improvement suggestions that are tailored to the user's emotional state.

[0560] "Individual user information" refers to a series of data related to a specific user, including their concerns, desires, and emotional state regarding hair.

[0561] A "hair improvement suggestion" is specific advice and methods provided based on the user's hair-related problems and desires, aimed at improving hair health and style.

[0562] "Generation method" refers to a mechanism or process for creating hair improvement suggestions tailored to the user based on the input information.

[0563] "Hair-related information from the internet" refers to data such as the latest research, products, and news related to hair that are publicly available online.

[0564] A "storage device" is a system or device for safely and efficiently storing collected data.

[0565] "Notification means" refers to an intermediary device or mechanism for informing the user of the generated proposal, and includes visual or auditory means.

[0566] "Emotional state" refers to the user's psychological situation or mood at any given time, as judged from their voice, facial expressions, text, etc.

[0567] "Display means" refers to a screen or device that presents generated information or suggestions in a way that is easy for users to understand.

[0568] "Regeneration methods" refer to the process of improving or updating existing proposals based on feedback and new information.

[0569] The system in this invention aims to provide users with personalized hair improvement suggestions using individual user information and emotional data. The following describes the implementation of this system.

[0570] First, users install a dedicated application on their mobile device and input information about their hair concerns and ideal style. This input utilizes sensors on the mobile device to measure environmental conditions (temperature, humidity, etc.) and physical condition. With permission, data obtained from social networking services can also be used.

[0571] The device collects input information from the user and then transmits the data to the server using a secure communication method. The device also uses speech recognition technology to analyze the tone and pitch of the user's voice and utilizes this as emotion data.

[0572] The server performs data integration and analysis based on the individual user information and sentiment data received. It further analyzes the user's emotional state using a sentiment engine. By regularly collecting cutting-edge hair-related data from the internet and storing it in memory, it provides users with always up-to-date suggestions.

[0573] The generative AI model creates personalized hair improvement suggestions based on the user's emotional data and hair-related information. These suggestions are generated by inputting prompts on the server, which are then executed by the generative AI model. For example, a possible prompt might be, "A woman in her 40s; based on the results of the emotional engine, stress levels increase on weekends. Please suggest relaxing hair care methods."

[0574] The generated suggestions are sent back to the device as a visually easy-to-understand dashboard, allowing users to review the suggestions through the application and incorporate them into their daily lives. In this way, the system can provide flexible and effective suggestions that comprehensively consider the user's individual information and emotional state.

[0575] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0576] Step 1:

[0577] Users launch a dedicated application and input information about their hair concerns and desired hairstyle. They also use sensors on their mobile device to measure environmental data such as temperature and humidity. This input data is stored on the device as individual user information.

[0578] Step 2:

[0579] Before sending the collected user information to the server, the terminal performs data preprocessing. Specifically, it converts the data format, imputes missing values, and converts it into a package ready for transmission. This output data is then ready to be received by the server.

[0580] Step 3:

[0581] The server receives user information transmitted from the terminal and analyzes the user's emotional state using an emotion engine. Voice tone and text data from social media are used as input data. The emotional data obtained through data analysis is processed as input for a generative AI model.

[0582] Step 4:

[0583] The server collects the latest hair-related information from the internet and stores it in its storage device. This information is used as reference data in generating hair improvement suggestions. Subsequently, the server integrates the user's emotional data with the latest information to create a prompt message for the AI ​​model. This prompt message takes the form of, "A woman in her 40s, based on the results of the emotional engine, experiences increased stress on weekends. Please suggest relaxing hair care methods."

[0584] Step 5:

[0585] The server uses a generative AI model to create hair improvement suggestions tailored to the user's needs. Based on the input prompt text, the model performs calculations and outputs personalized suggestions.

[0586] Step 6:

[0587] The server converts the generated suggestions into a dashboard format and sends it to the terminal. The dashboard contains visually clear information in a format that is easy for the user to understand.

[0588] Step 7:

[0589] Users can view a dashboard through the application and incorporate suggested improvement plans into their lives. The regeneration process begins when they input feedback and their emotional state after use. Feedback information is sent from the device to the server, and the program is updated accordingly.

[0590] (Application Example 2)

[0591] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server," and the headset-type terminal 314 will be referred to as the "terminal."

[0592] In modern society, users seek personalized lifestyle suggestions that respond to stress and emotional fluctuations, but conventional systems lack solutions that take emotional data into account. Furthermore, they are unable to provide effective suggestions across all aspects of the user's life. In particular, it is difficult to receive suggestions regarding both hair care and diet simultaneously, and the lack of a consistent solution is a problem.

[0593] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0594] This invention includes a server that receives individual user information and emotional data and generates hair improvement suggestions suitable for the user based on the information and emotional data; an aggregation means that periodically collects hair-related information from the internet and stores the collected information in a storage device; and a food and beverage suggestion generation means that generates food suggestions suitable for the user based on the user's emotional data. This enables comprehensive, personalized suggestions for hair improvement and food and beverages to the user using emotional data.

[0595] "Individual user information" refers to data such as user-specific profiles and history, which is used to generate personalized suggestions.

[0596] "Emotional data" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice, facial expressions, and text input.

[0597] The "generation means" refers to the part that has the function of generating suggestions tailored to individual users based on user information and sentiment data.

[0598] The "aggregation means" refers to the part that has the function of periodically collecting information and storing it in a database.

[0599] "Notification means" refers to the part that has the function of communicating the generated suggestions to the user, and includes visual displays.

[0600] The "regeneration mechanism" refers to the part that receives user feedback and updates suggestions based on that feedback.

[0601] The "food and beverage suggestion generation means" refers to the part that has the function of generating food-related suggestions based on the user's emotional data.

[0602] The system for implementing the present invention provides hair improvement and dietary recommendations using emotional data and individual user information. The system mainly consists of a server, a user terminal, and related software.

[0603] Server Role

[0604] The server integrates individual user information and emotional data to generate hair improvement suggestions based on this data. Emotional data is analyzed from the user's voice, facial expressions, and text. AWS machine learning services and emotion analysis APIs are used to process this data. The server periodically collects hair-related information from the internet and stores it in a database. It also generates food and drink suggestions based on the user's emotional data and provides these suggestions comprehensively.

[0605] The role of the user terminal

[0606] The user's mobile device, such as a smartphone or tablet, collects sensor data and transmits it to the server. The device visually displays the acquired suggestions on a dashboard and notifies the user. When the user reviews the suggestions and sends feedback to the server via the device, the suggestions are regenerated, resulting in more accurate suggestions.

[0607] Specific example

[0608] For example, if emotional data is analyzed indicating that a user is feeling stressed over the weekend, a scalp massage using relaxing essential oils and a meal accompanied by chamomile tea might be suggested. Another example of a prompt message is, "How are you feeling today? If you're feeling tired, we'd like to suggest some relaxing options." Using such interactive prompts improves the user experience.

[0609] This system will enable holistic and personalized hair care and food and beverage recommendations that utilize emotional data.

[0610] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0611] Step 1:

[0612] Users enter individual user information via their device. This includes information about their current hair concerns, desired hairstyle, and preferred foods. The entered information is then sent from the device to the server.

[0613] Step 2:

[0614] The server integrates the received user information and emotion data. The emotion data is analyzed using an emotion analysis API based on the user's voice and facial expression data to determine their emotional state. It receives user voice and facial expression data as input and generates data indicating their emotional state as output.

[0615] Step 3:

[0616] The server collects information related to hair and food from the internet. It aggregates the latest trends and health data and stores it in a database. This involves using crawlers for information gathering and structuring and storing the data.

[0617] Step 4:

[0618] The system generates hair improvement and dietary recommendations based on the user's individual information, emotional data, and collected information. A generation AI model analyzes the data to generate optimal recommendations. The output is data containing detailed recommendations.

[0619] Step 5:

[0620] The notification system visually displays the generated suggestions on the user's device via a dashboard. This includes providing an interface that allows the user to review the content of the suggestions and presents them in a visually appealing way.

[0621] Step 6:

[0622] The user reviews the notified suggestion and provides feedback as needed. The feedback is then sent back to the server via the device. The feedback includes evaluations and comments on the suggestion.

[0623] Step 7:

[0624] The server processes the received feedback using a regeneration mechanism and updates the proposal. The feedback data is analyzed again with the regeneration AI model to optimize the proposal. This regeneration makes the next proposal more personalized and improves its accuracy.

[0625] The specific processing unit 290 transmits the result of the specific processing to the headset terminal 314. In the headset terminal 314, the control unit 46A causes the speaker 240 and display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0626] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0627] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and specific processing may also be performed by the headset terminal 314.

[0628] [Fourth Embodiment]

[0629] Figure 7 shows an example of the configuration of the data processing system 410 according to the fourth embodiment.

[0630] As shown in Figure 7, the data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[0631] The data processing device 12 comprises a computer 22, a database 24, and a communication interface 26. The computer 22 is an example of a "computer" related to the technology of this disclosure. The computer 22 comprises a processor 28, RAM 30, and storage 32. The processor 28, RAM 30, and storage 32 are connected to a bus 34. The database 24 and the communication interface 26 are also connected to the bus 34. The communication interface 26 is connected to a network 54. An example of the network 54 is a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0632] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication interface 44, and a controlled object 443. The computer 36 includes a processor 46, RAM 48, and storage 50. The processor 46, RAM 48, and storage 50 are connected to a bus 52. The microphone 238, speaker 240, camera 42, and controlled object 443 are also connected to the bus 52.

[0633] The microphone 238 receives voice signals from the user 20 and receives instructions from the user 20. The microphone 238 captures the voice signals from the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio according to the instructions from the processor 46.

[0634] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an image sensor such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the area around the user 20 (for example, an imaging range defined by a field of view equivalent to the width of a typical healthy person's field of vision).

[0635] Communication interface 44 is connected to network 54. Communication interfaces 44 and 26 are responsible for the exchange of various information between processor 46 and processor 28 via network 54. The exchange of various information between processor 46 and processor 28 using communication interfaces 44 and 26 is performed in a secure manner.

[0636] The controlled object 443 includes a display device, LEDs in the eyes, and motors that drive the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the robot 414's emotions can be expressed by controlling these motors. Furthermore, the robot 414's facial expressions can also be expressed by controlling the illumination state of the LEDs in its eyes.

[0637] Figure 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Figure 8, the data processing device 12 performs specific processing using the processor 28. The storage 32 stores the specific processing program 56.

[0638] The specific processing program 56 is an example of a "program" relating to the technology of this disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0639] The storage 32 stores the data generation model 58 and the emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0640] In robot 414, the processor 46 performs the reception output processing. The storage 50 stores the reception output program 60. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as a control unit 46A according to the reception output program 60 executed on the RAM 48.

[0641] Next, the specific processing performed by the specific processing unit 290 of the data processing device 12 will be described. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0642] This invention is a system for providing hair improvement suggestions tailored to the user. This system collects individual user information and combines it with hair-related information from the internet to generate an optimal hair improvement program. Specific embodiments for carrying out this invention are described below.

[0643] First, users input information about their hair concerns and ideal hairstyle through a dedicated application. Furthermore, the application also acquires data from the user's smartphone sensors and information extracted from social networking services.

[0644] The terminal integrates this information and sends it to the server. The server then stores the collected user information in a database and gathers the latest hair-related information from the internet. This aggregation method ensures that user-related information is always up-to-date.

[0645] After the information is aggregated, the server uses a generation mechanism to generate hair improvement suggestions based on the individual user's information. Examples of suggestions include dietary improvements, exercise recommendations, and the use of specific hair care products.

[0646] The generated suggestions are notified to the user via their device. This notification method allows users to view specific improvement measures on a dashboard that is easy to understand visually.

[0647] The server also collects feedback from users and uses regeneration mechanisms to improve the suggestions. This allows the suggestions to adapt over time, increasing in accuracy and effectiveness.

[0648] For example, let's say a male user in his 40s uses this system. This user is concerned about thinning hair and has a habit of carrying a pedometer with him every day. When he logs into the application and enters his concerns about his hair, the server retrieves that information along with his step count data from his smartphone and saves it in the database.

[0649] The server then uses this information to generate a hair improvement program tailored to his lifestyle. The suggested improvements include increasing walking distance to improve blood flow and positively impact hair health, as well as actively consuming foods rich in specific vitamins.

[0650] As described above, the present invention provides hair improvement proposals optimized for individual users and offers solutions that meet the specific needs of users.

[0651] The following describes the processing flow.

[0652] Step 1:

[0653] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and desired hairstyle.

[0654] Step 2:

[0655] The device encrypts this input information and sends it to the server. Furthermore, with the user's permission, the device retrieves sensor data from the smartphone (e.g., steps, heart rate) and related data from social networking services.

[0656] Step 3:

[0657] The server integrates the received user information with sensor data and SNS data sent from the terminal and stores it in a database.

[0658] Step 4:

[0659] The server collects the latest information on hair in real time from various sources on the web and updates the database. This aggregation method ensures that the most up-to-date information is always available.

[0660] Step 5:

[0661] The server utilizes generation methods to automatically generate a hair improvement program optimized for each user, based on collected individual user information and hair-related information obtained from the web. The program includes nutritional guidance, exercise plans, and recommendations for hair care products.

[0662] Step 6:

[0663] The server sends the generated hair improvement program to the terminal in a visually easy-to-understand dashboard format and notifies the user.

[0664] Step 7:

[0665] Users review the provided dashboard and incorporate the suggested hair improvement program into their daily lives.

[0666] Step 8:

[0667] Users input the results of their program implementation and the effects they experienced into their device and send this feedback to the server.

[0668] Step 9:

[0669] Based on the feedback received, the server uses an AI model to further improve the program's accuracy through regeneration and updates the suggested content as needed.

[0670] Step 10:

[0671] The server resends the updated improvement program to the terminal, providing users with ongoing support.

[0672] (Example 1)

[0673] Next, we will describe Example 1. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0674] There is a need to address the diverse beauty challenges of various users and provide the latest, personalized beauty improvement suggestions. However, conventional technologies have made it difficult to efficiently generate suggestions tailored to users' lifestyles and specific needs and to incorporate feedback. Therefore, there is a need to develop a system that can provide more accurate suggestions to individual users.

[0675] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 1 is realized by the following means.

[0676] In this invention, the server includes a generation means that receives individual user data and generates beauty improvement suggestions tailored to the user based on the data; an aggregation means that periodically collects beauty-related information from a communication network and stores the collected information in a data storage device; and a notification means that notifies the user of the beauty improvement suggestions generated by the generation means. This makes it possible to continuously provide the latest beauty improvement suggestions tailored to the individual needs of the user.

[0677] "User data" refers to information related to the beauty of individual users, and includes sensor information obtained from mobile devices and data from information sharing services.

[0678] "Beauty improvement suggestions" refer to information that provides specific guidance and recommendations to address users' beauty-related concerns.

[0679] A "generation method" is a system component that has the function of creating beauty improvement suggestions based on user data.

[0680] "Aggregation means" refers to a system component that has the function of storing beauty-related information collected via a communication network in a data storage device.

[0681] "Notification means" refers to a means of informing users of generated beauty improvement suggestions, and includes technologies for visually displaying information.

[0682] A "regeneration mechanism" is a system component that improves the suggestions generated by the generation mechanism based on user responses, and continuously provides more appropriate suggestions.

[0683] This invention is a system for providing users with personalized beauty improvement suggestions. This system receives individual user data, generates suggestions using a generative AI model, and periodically collects the latest information from the internet to provide information tailored to the user. A detailed description of how to implement this invention is provided below.

[0684] Users input information about their beauty concerns and goals using a dedicated application. This application can acquire sensor information about the user's current state using the smartphone's camera and location services. It also collects information about beauty-related interests and activities from social networking services.

[0685] The device aggregates information obtained from the user and transmits it to the server via a secure communication method. This process utilizes the mobile device's operating system and communication protocols.

[0686] The server stores received user data in a database. Furthermore, it uses a web crawler to collect reliable beauty-related information from the internet and stores it in the database. This allows a generative AI model to combine user data with the latest external information to generate suggestions. These suggestions include nutritional guidance, exercise advice, and recommended beauty products.

[0687] The generated beauty improvement suggestions are notified to the user via their device. The user can view the suggestions on a dashboard within the application and selectively provide feedback. This feedback is sent back to the server and used to improve the suggestions as a means of regeneration.

[0688] For example, by inputting a prompt such as, "Please suggest lifestyle habits for a woman in her 30s to achieve voluminous hair," into the AI ​​model, specific and user-specific improvement suggestions are provided. This allows users to receive practical and meaningful information to meet their individual beauty needs.

[0689] The flow of the specific processing in Example 1 will be explained using Figure 11.

[0690] Step 1:

[0691] The user launches the application and enters their concerns and goals regarding hair and beauty. This input data also includes the user's preferences and daily activity data. For example, it might record image data of their hair condition and information about their recent diet and exercise. This information becomes the system's initial input data.

[0692] Step 2:

[0693] The terminal aggregates data entered by the user. Specifically, it integrates input data from the application with activity information acquired through sensors and formats it into a single data package. This package is encrypted using a communication protocol and securely transmitted to the server.

[0694] Step 3:

[0695] The server stores received user data in a database. The server uses this data to collect the latest beauty-related information from the internet. This collected data is periodically crawled from specific internet resources and stored in the database. The output here is a massive dataset integrating user data and internet information.

[0696] Step 4:

[0697] The server uses a generative AI model to generate personalized beauty improvement suggestions from an integrated dataset. It takes user activity data and recent information as input, and the AI ​​algorithm analyzes the relationships between the data. This results in improvement suggestions tailored to the user's needs. These suggestions include specific information such as dietary improvements, changes in exercise habits, and recommendations for beauty products.

[0698] Step 5:

[0699] The device receives generated beauty improvement suggestions sent from the server and notifies the user. The user can visually review these suggestions on a dashboard through the application. If feedback is needed, the user can easily provide a response using the interface.

[0700] Step 6:

[0701] The server receives feedback from the user and updates the suggestions using a regeneration mechanism. The feedback is treated as new input data, which the AI ​​analyzes again to improve the accuracy of the suggestions, and modifies the content of the suggestions as needed. This output is an optimized version of the improved suggestions.

[0702] (Application Example 1)

[0703] Next, we will explain Application Example 1. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0704] Modern consumers increasingly seek personalized advice regarding hair health and style. However, traditional methods have struggled to provide timely and appropriate suggestions tailored to individual consumer needs and circumstances. Furthermore, there has been a lack of means to improve the quality of service provided by store staff during customer visits. Therefore, a new system is needed that provides optimal hair improvement suggestions to users and enhances practicality in stores.

[0705] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 1 is realized by the following means.

[0706] In this invention, the server includes a generation means for receiving individual user information and generating hair improvement suggestions suitable for the user based on that information; an aggregation means for periodically collecting hair-related information from the internet and storing the collected information in a database; and a means for acquiring customer attribute information using a visual display device and presenting appropriate hair improvement suggestions to staff based on the aggregated information. This makes it possible to provide personalized and immediate hair improvement suggestions to customers who visit the store, thereby improving the quality of customer service at the store.

[0707] "Individual user information" refers to data related to each individual user, including sensor data from mobile devices and various data obtained from communication network services.

[0708] "Generation means" refers to a component or method for automatically generating suggestions for hair improvement based on individual user information.

[0709] "Aggregation means" refers to a component or method used to periodically collect hair-related information from the internet and organize and store that information in a database.

[0710] "Notification means" refers to a method or technique for informing the user of the generated hair improvement suggestions, and which provides information visually.

[0711] A "regeneration means" is a component or method for receiving feedback from the user and recreating the suggestions generated based on that feedback.

[0712] A "visual display device" is a device used to present information visually, and is used to acquire and display attribute information of customers.

[0713] This invention is a system that generates optimized hair improvement suggestions based on individual user information and provides them to store staff. The system is implemented by combining a server, terminals, and a visual display device.

[0714] First, the server collects individual user information. It utilizes sensor data obtained through the user's mobile device and data from communication network services. Using this information, the server generates hair improvement suggestions tailored to the user's needs using a generation method.

[0715] The server then periodically collects the latest information related to hair from the internet through aggregation means and stores this information in a database. This information is used to keep the suggestions provided to users fresh and effective.

[0716] In store implementations, visual display devices play a crucial role. Customer attribute information is acquired and analyzed via these visual display devices. Staff members wear devices that display suggestions in real time, enabling immediate and personalized advice for each customer.

[0717] As a concrete example, when a female customer in her 40s visits the store and inputs her lifestyle and hair concerns, a store staff member wearing smart glasses can instantly suggest nutritional intake and appropriate care products. The generative AI model used in this process uses prompts such as, "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0718] The flow of a specific process in Application Example 1 will be explained using Figure 12.

[0719] Step 1:

[0720] Users input information about their hair concerns and ideal hairstyles at a terminal in the store. This information is collected along with sensor data from the user's mobile device and relevant information publicly available on social networks. This allows for the acquisition of personalized attribute information about the user.

[0721] Step 2:

[0722] The server uses a generative AI model to generate personalized hair improvement suggestions based on collected user information. Here, user information is used as input data, and suggestions tailored to the user's lifestyle and current situation are output. This process utilizes the prompt message to the generative model: "A woman in her 40s, recently concerned about thinning hair. She exercises three times a week. Please generate suggestions for nutrients and hair care products suitable for her."

[0723] Step 3:

[0724] The server periodically collects hair-related information from the internet and stores it in a database. This aggregation method accumulates foundational data for making suggestions that take into account the latest trends and research information.

[0725] Step 4:

[0726] The server notifies store staff of the generated hair improvement suggestions via a visual display device. The displayed information is personalized to the user, allowing store staff to respond to customers in real time. This enables quick and appropriate advice even for first-time customers.

[0727] Step 5:

[0728] After a user receives a suggestion, they provide feedback. This feedback is sent back to the server and used as a means of regenerating the suggestion to improve its quality. Based on the feedback, the suggestion is fine-tuned to further enhance user satisfaction and convenience.

[0729] Furthermore, an emotion engine that estimates the user's emotions may be incorporated. That is, the identification processing unit 290 may use the emotion identification model 59 to estimate the user's emotions and perform identification processing using the user's emotions.

[0730] This invention relates to a system that provides hair improvement suggestions tailored to the user by utilizing individual user information and emotional data. By incorporating an emotional engine, this system enables the personalization of suggestions in response to the user's emotions.

[0731] First, users use a dedicated application to input information about their hair concerns and desired style. In this step, data from sensors on their smartphone or other devices, as well as data collected from their statements and actions on social media, are used.

[0732] Next, the device sends the input information, sensor data, and SNS data to the server. In particular, the emotion engine analyzes the user's voice, facial expressions, and text input to measure their current emotional state. This emotion data is sent to the server along with information about other users.

[0733] The server integrates all received information and stores it in a database, collecting the latest hair-related information from the internet. Based on this information, the generation system generates optimal hair improvement suggestions for the user. This process also takes into account data from the emotion engine, providing suggestions tailored to the user's emotional state.

[0734] The generated suggestions are processed by the server and sent to the device in the form of a visual dashboard. Through this dashboard, users can review the suggested improvement plans and incorporate them into their lives as needed.

[0735] For example, if the emotion engine detects that a female user in her 40s tends to experience stress on weekends, the server will add self-care methods to alleviate stress to its hair improvement suggestions. Specifically, this might include suggestions for scalp massage in a relaxing environment or the use of essential oils with relaxation effects.

[0736] To elaborate, user feedback and emotional changes during program execution are constantly transmitted from the device to the server. This allows the server to use a regeneration mechanism to update the program based on the passage of time and new emotional data, enabling more accurate hair improvement suggestions.

[0737] Thus, the present invention enables personalized hair care based on individual user information, including emotional data, and provides effective solutions tailored to the unique needs of each user.

[0738] The following describes the processing flow.

[0739] Step 1:

[0740] The user launches the application and enters basic information such as their name, age, gender, hair concerns, and ideal hairstyle. The emotion engine then measures the user's emotional state from their voice, facial expressions, and entered text.

[0741] Step 2:

[0742] The device encrypts all information entered by the user, data acquired by sensors, data from social media, and emotional data recognized by the emotion engine, and sends them to the server.

[0743] Step 3:

[0744] The server integrates all transmitted data and stores it in a database. It also updates the database by retrieving the latest hair-related information from the internet.

[0745] Step 4:

[0746] The server uses all currently available information to create hair improvement suggestions optimized for the user's current situation through a generation mechanism. In doing so, it reflects the user's emotional state in the suggestions, generating suggestions that are considerate of the user's feelings.

[0747] Step 5:

[0748] The server converts the generated hair improvement suggestions into a dashboard format and sends it to the terminal. The terminal then notifies the user in an intuitively easy-to-understand format.

[0749] Step 6:

[0750] Users review the dashboard and incorporate the suggested hair improvement plan into their daily lives. The plan may include self-care methods and lifestyle improvements tailored to the user's stress level.

[0751] Step 7:

[0752] Users input feedback on the implementation status and effectiveness of improvement plans into their devices, and sentiment data is continuously updated.

[0753] Step 8:

[0754] The device then sends the collected feedback and sentiment data back to the server.

[0755] Step 9:

[0756] The server uses feedback and the latest sentiment data to improve the accuracy of suggestions through regeneration mechanisms. It updates the suggested improvements as needed and notifies the user again.

[0757] Through this series of steps, the system consistently provides optimal hair care based on individual needs and emotions.

[0758] (Example 2)

[0759] Next, we will describe Example 2. In the following description, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0760] Conventional hair improvement recommendation systems do not adequately personalize the system by considering the emotional state of individual users, making it difficult to provide effective recommendations based on the user's current mental and physical condition.

[0761] The identification process performed by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means.

[0762] In this invention, the server includes means for receiving individual user information and generating hair improvement suggestions suitable for the user based on said information; means for periodically collecting hair-related information from the internet and storing said information in a storage means; and means for analyzing the user's emotional state and reflecting the analysis results in the suggestions. This makes it possible to provide more effective and personalized hair improvement suggestions that are tailored to the user's emotional state.

[0763] "Individual user information" refers to a series of data related to a specific user, including their concerns, desires, and emotional state regarding hair.

[0764] A "hair improvement suggestion" is specific advice and methods provided based on the user's hair-related problems and desires, aimed at improving hair health and style.

[0765] "Generation method" refers to a mechanism or process for creating hair improvement suggestions tailored to the user based on the input information.

[0766] "Hair-related information from the internet" refers to data such as the latest research, products, and news related to hair that are publicly available online.

[0767] A "storage device" is a system or device for safely and efficiently storing collected data.

[0768] "Notification means" refers to an intermediary device or mechanism for informing the user of the generated proposal, and includes visual or auditory means.

[0769] "Emotional state" refers to the user's psychological situation or mood at any given time, as judged from their voice, facial expressions, text, etc.

[0770] "Display means" refers to a screen or device that presents generated information or suggestions in a way that is easy for users to understand.

[0771] "Regeneration methods" refer to the process of improving or updating existing proposals based on feedback and new information.

[0772] The system in this invention aims to provide users with personalized hair improvement suggestions using individual user information and emotional data. The following describes the implementation of this system.

[0773] First, users install a dedicated application on their mobile device and input information about their hair concerns and ideal style. This input utilizes sensors on the mobile device to measure environmental conditions (temperature, humidity, etc.) and physical condition. With permission, data obtained from social networking services can also be used.

[0774] The device collects input information from the user and then transmits the data to the server using a secure communication method. The device also uses speech recognition technology to analyze the tone and pitch of the user's voice and utilizes this as emotion data.

[0775] The server performs data integration and analysis based on the individual user information and sentiment data received. It further analyzes the user's emotional state using a sentiment engine. By regularly collecting cutting-edge hair-related data from the internet and storing it in memory, it provides users with always up-to-date suggestions.

[0776] The generative AI model creates personalized hair improvement suggestions based on the user's emotional data and hair-related information. These suggestions are generated by inputting prompts on the server, which are then executed by the generative AI model. For example, a possible prompt might be, "A woman in her 40s; based on the results of the emotional engine, stress levels increase on weekends. Please suggest relaxing hair care methods."

[0777] The generated suggestions are sent back to the device as a visually easy-to-understand dashboard, allowing users to review the suggestions through the application and incorporate them into their daily lives. In this way, the system can provide flexible and effective suggestions that comprehensively consider the user's individual information and emotional state.

[0778] The flow of the specific processing in Example 2 will be explained using Figure 13.

[0779] Step 1:

[0780] Users launch a dedicated application and input information about their hair concerns and desired hairstyle. They also use sensors on their mobile device to measure environmental data such as temperature and humidity. This input data is stored on the device as individual user information.

[0781] Step 2:

[0782] Before sending the collected user information to the server, the terminal performs data preprocessing. Specifically, it converts the data format, imputes missing values, and converts it into a package ready for transmission. This output data is then ready to be received by the server.

[0783] Step 3:

[0784] The server receives user information transmitted from the terminal and analyzes the user's emotional state using an emotion engine. Voice tone and text data from social media are used as input data. The emotional data obtained through data analysis is processed as input for a generative AI model.

[0785] Step 4:

[0786] The server collects the latest hair-related information from the internet and stores it in its storage device. This information is used as reference data in generating hair improvement suggestions. Subsequently, the server integrates the user's emotional data with the latest information to create a prompt message for the AI ​​model. This prompt message takes the form of, "A woman in her 40s, based on the results of the emotional engine, experiences increased stress on weekends. Please suggest relaxing hair care methods."

[0787] Step 5:

[0788] The server uses a generative AI model to create hair improvement suggestions tailored to the user's needs. Based on the input prompt text, the model performs calculations and outputs personalized suggestions.

[0789] Step 6:

[0790] The server converts the generated suggestions into a dashboard format and sends it to the terminal. The dashboard contains visually clear information in a format that is easy for the user to understand.

[0791] Step 7:

[0792] Users can view a dashboard through the application and incorporate suggested improvement plans into their lives. The regeneration process begins when they input feedback and their emotional state after use. Feedback information is sent from the device to the server, and the program is updated accordingly.

[0793] (Application Example 2)

[0794] Next, we will explain application example 2. In the following explanation, the data processing device 12 will be referred to as the "server" and the robot 414 as the "terminal".

[0795] In modern society, users seek personalized lifestyle suggestions that respond to stress and emotional fluctuations, but conventional systems lack solutions that take emotional data into account. Furthermore, they are unable to provide effective suggestions across all aspects of the user's life. In particular, it is difficult to receive suggestions regarding both hair care and diet simultaneously, and the lack of a consistent solution is a problem.

[0796] The specific processing performed by the specific processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means.

[0797] This invention includes a server that receives individual user information and emotional data and generates hair improvement suggestions suitable for the user based on the information and emotional data; an aggregation means that periodically collects hair-related information from the internet and stores the collected information in a storage device; and a food and beverage suggestion generation means that generates food suggestions suitable for the user based on the user's emotional data. This enables comprehensive, personalized suggestions for hair improvement and food and beverages to the user using emotional data.

[0798] "Individual user information" refers to data such as user-specific profiles and history, which is used to generate personalized suggestions.

[0799] "Emotional data" refers to data that indicates the user's current emotional state, and is obtained from sources such as voice, facial expressions, and text input.

[0800] The "generation means" refers to the part that has the function of generating suggestions tailored to individual users based on user information and sentiment data.

[0801] The "aggregation means" refers to the part that has the function of periodically collecting information and storing it in a database.

[0802] "Notification means" refers to the part that has the function of communicating the generated suggestions to the user, and includes visual displays.

[0803] The "regeneration mechanism" refers to the part that receives user feedback and updates suggestions based on that feedback.

[0804] The "food and beverage suggestion generation means" refers to the part that has the function of generating food-related suggestions based on the user's emotional data.

[0805] The system for implementing the present invention provides hair improvement and dietary recommendations using emotional data and individual user information. The system mainly consists of a server, a user terminal, and related software.

[0806] Server Role

[0807] The server integrates individual user information and emotional data to generate hair improvement suggestions based on this data. Emotional data is analyzed from the user's voice, facial expressions, and text. AWS machine learning services and emotion analysis APIs are used to process this data. The server periodically collects hair-related information from the internet and stores it in a database. It also generates food and drink suggestions based on the user's emotional data and provides these suggestions comprehensively.

[0808] The role of the user terminal

[0809] The user's mobile device, such as a smartphone or tablet, collects sensor data and transmits it to the server. The device visually displays the acquired suggestions on a dashboard and notifies the user. When the user reviews the suggestions and sends feedback to the server via the device, the suggestions are regenerated, resulting in more accurate suggestions.

[0810] Specific example

[0811] For example, if emotional data is analyzed indicating that a user is feeling stressed over the weekend, a scalp massage using relaxing essential oils and a meal accompanied by chamomile tea might be suggested. Another example of a prompt message is, "How are you feeling today? If you're feeling tired, we'd like to suggest some relaxing options." Using such interactive prompts improves the user experience.

[0812] This system will enable holistic and personalized hair care and food and beverage recommendations that utilize emotional data.

[0813] The flow of a specific process in Application Example 2 will be explained using Figure 14.

[0814] Step 1:

[0815] Users enter individual user information via their device. This includes information about their current hair concerns, desired hairstyle, and preferred foods. The entered information is then sent from the device to the server.

[0816] Step 2:

[0817] The server integrates the received user information and emotion data. The emotion data is analyzed using an emotion analysis API based on the user's voice and facial expression data to determine their emotional state. It receives user voice and facial expression data as input and generates data indicating their emotional state as output.

[0818] Step 3:

[0819] The server collects information related to hair and food from the internet. It aggregates the latest trends and health data and stores it in a database. This involves using crawlers for information gathering and structuring and storing the data.

[0820] Step 4:

[0821] The system generates hair improvement and dietary recommendations based on the user's individual information, emotional data, and collected information. A generation AI model analyzes the data to generate optimal recommendations. The output is data containing detailed recommendations.

[0822] Step 5:

[0823] The notification system visually displays the generated suggestions on the user's device via a dashboard. This includes providing an interface that allows the user to review the content of the suggestions and presents them in a visually appealing way.

[0824] Step 6:

[0825] The user reviews the notified suggestion and provides feedback as needed. The feedback is then sent back to the server via the device. The feedback includes evaluations and comments on the suggestion.

[0826] Step 7:

[0827] The server processes the received feedback using a regeneration mechanism and updates the proposal. The feedback data is analyzed again with the regeneration AI model to optimize the proposal. This regeneration makes the next proposal more personalized and improves its accuracy.

[0828] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the controlled object 443 to output the result of the specific processing. The microphone 238 acquires audio indicating user input for the result of the specific processing. The control unit 46A transmits the audio data indicating user input acquired by the microphone 238 to the data processing unit 12. In the data processing unit 12, the specific processing unit 290 acquires the audio data.

[0829] Data generation model 58 is a type of so-called generative AI (Artificial Intelligence). One example of data generation model 58 is ChatGPT (Internet search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search) <url: https: gemini.google.com ?hl="ja">Examples of generative AI include the following. The data generation model 58 is obtained by performing deep learning on a neural network. The data generation model 58 is input with prompts containing instructions, and with inference data such as audio data representing speech, text data representing text, and image data representing images. The data generation model 58 infers from the input inference data according to the instructions indicated by the prompts, and outputs the inference results in data formats such as audio data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0830] In the above embodiment, an example was given in which specific processing is performed by the data processing device 12, but the technology of this disclosure is not limited thereto, and the specific processing may also be performed by the robot 414.

[0831] Furthermore, the emotion identification model 59, acting as an emotion engine, may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to a specific mapping, which is an emotion map (see Figure 9). Similarly, the emotion identification model 59 may also determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[0832] Figure 9 shows an emotion map 400 in which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. The closer to the center of the concentric circles, the more primitive the emotions are located. Further out of the concentric circles, emotions representing states and actions arising from mental states are located. Emotion is a concept that includes feelings and mental states. On the left side of the concentric circles, emotions that are generally generated from reactions occurring in the brain are located. On the right side of the concentric circles, emotions that are generally induced by situational judgment are located. Above and below the concentric circles, emotions that are generally generated from reactions occurring in the brain and induced by situational judgment are located. In addition, the emotion of "pleasure" is located on the upper side of the concentric circles, and the emotion of "displeasure" is located on the lower side. Thus, in the emotion map 400, multiple emotions are mapped based on the structure in which emotions arise, and emotions that are likely to occur simultaneously are mapped close together.

[0833] These emotions are distributed at the 3 o'clock position on the Emotion Map 400, and usually fluctuate between feelings of security and anxiety. In the right half of the Emotion Map 400, situational awareness takes precedence over internal feelings, resulting in a calm impression.

[0834] The inside of the Emotion Map 400 represents inner thoughts, while the outside represents actions. Therefore, the further you go from the outside of the Emotion Map 400, the more visible (expressed in actions) your emotions become.

[0835] Here, human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. Similarly, in robots, cars, motorcycles, etc., emotions can be created based on various balances, such as posture and battery level. When these balances deviate from the ideal, it results in discomfort, and when they approach the ideal, it results in pleasure. The emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on a system for analyzing brain physiological signals of speech emotion recognition and emotion, Tokushima University, doctoral dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map contains emotions belonging to a region called "response," where sensation is dominant. The right half of the emotion map contains emotions belonging to a region called "situation," where situational awareness is dominant.

[0836] The emotion map defines two emotions that promote learning. One is the emotion around the middle of the negative "repentance" and "reflection" on the situation side. In other words, it is when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is the emotion around the positive "desire" on the reaction side. In other words, it is when the robot has positive feelings such as "I want more" or "I want to know more."

[0837] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​representing each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple training data sets, which are combinations of user input and emotion values ​​representing each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions located close together have similar values, as shown in the emotion map 900 in Figure 10. Figure 10 shows an example where multiple emotions such as "reassured," "calm," and "confident" have similar emotion values.

[0838] The above description primarily focuses on the functions of the data processing device 12 in relation to this disclosure. However, the system related to this disclosure is not necessarily implemented on a server. The system related to this disclosure may be implemented as a general information processing system. This disclosure may be implemented, for example, as a software program that runs on a personal computer or as an application that runs on a smartphone. The method related to this disclosure may be provided to users in SaaS (Software as a Service) format.

[0839] In the above embodiment, an example was given in which a specific process is performed by a single computer 22. However, the technology of this disclosure is not limited thereto, and a distributed processing of the specific process may be performed by multiple computers, including computer 22. For example, a data generation model 58 may be provided in an external device of the data processing device 12, and the external device may generate data according to the input data.

[0840] In the above embodiment, an example was given in which the specific processing program 56 is stored in the storage 32, but the technology of this disclosure is not limited thereto. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-temporary storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-temporary storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes specific processing according to the specific processing program 56.

[0841] 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.

[0842] Furthermore, it is not necessary to store the entirety of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store the entirety of the specific processing program 56 in the storage 32; it is acceptable to store only a portion of the specific processing program 56.

[0843] The following types of processors can be used as hardware resources to perform specific processing. Examples of processors include a CPU, a general-purpose processor that functions as a hardware resource to perform specific processing by executing software, i.e., a program. Other examples of processors include dedicated electrical circuits, such as FPGAs (Field-Programmable Gate Arrays), PLDs (Programmable Logic Devices), or ASICs (Application Specific Integrated Circuits), which have circuit configurations specifically designed to perform specific processing. All of these processors have built-in or connected memory, and all of them perform specific processing by using memory.

[0844] The hardware resource that performs a specific process may consist of one of these various processors, or it may consist of a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Alternatively, the hardware resource that performs a specific process may consist of a single processor.

[0845] Examples of configurations using a single processor include, firstly, a configuration in which one or more CPUs and software are combined to form a single processor, and this processor functions as a hardware resource that performs a specific process. Secondly, there is a configuration using a processor that realizes the functions of the entire system, including multiple hardware resources that perform a specific process, on a single IC chip, as exemplified by SoCs (System-on-a-chip). In this way, a specific process is realized using one or more of the above types of processors as hardware resources.

[0846] Furthermore, the hardware structure of these various processors can more specifically utilize electrical circuits that combine circuit elements such as semiconductor devices. Also, the specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps can be deleted, new steps added, or the processing order rearranged, as long as it does not deviate from the main purpose.

[0847] The descriptions and illustrations presented above are detailed explanations of the technical aspects of this disclosure and are merely examples of the technical aspects. For example, the above descriptions of the structure, function, operation, and effect are examples of the structure, function, operation, and effect of the technical aspects of this disclosure. Therefore, it goes without saying that you may delete unnecessary parts, add new elements, or replace elements in the descriptions and illustrations presented above, as long as you do not deviate from the essence of the technical aspects of this disclosure. Furthermore, in order to avoid confusion and facilitate understanding of the technical aspects of this disclosure, explanations of common technical knowledge and the like that do not require special explanation to enable the implementation of the technical aspects of this disclosure have been omitted from the descriptions and illustrations presented above.

[0848] All documents, patent applications, and technical standards described herein are incorporated by reference to the same extent as if each individual document, patent application, and technical standard were specifically and individually noted as being incorporated by reference.

[0849] The following is further disclosed regarding the embodiments described above.

[0850] (Claim 1)

[0851] A generation means that receives individual user information and generates hair improvement suggestions suitable for the user based on said information,

[0852] A means of aggregating information that periodically collects hair-related information from the internet and stores the collected information in a database,

[0853] A notification means for notifying the user of the hair improvement suggestion generated by the generation means,

[0854] A regeneration means that receives feedback from the user and updates the proposal generated by the generation means based on the feedback,

[0855] A system that includes this.

[0856] (Claim 2)

[0857] The system according to claim 1, wherein the notification means includes means for generating a dashboard that visually displays the generated hair improvement suggestions.

[0858] (Claim 3)

[0859] The system according to claim 1, wherein the user information includes sensor data obtained from the user's mobile device and data from social networking services.

[0860] "Example 1"

[0861] (Claim 1)

[0862] A generation means that receives individual user data and generates beauty improvement suggestions suitable for the user based on said data,

[0863] A means for aggregating beauty-related information from a communication network and storing the collected information in a data storage device,

[0864] A notification means for notifying the user of the beauty improvement suggestions generated by the generation means,

[0865] A regeneration means that receives a response from the user and improves the proposal generated by the generation means based on the response,

[0866] A system that includes this.

[0867] (Claim 2)

[0868] The system according to claim 1, wherein the notification means includes means for generating an information display screen that visually displays the generated beauty improvement suggestions.

[0869] (Claim 3)

[0870] The system according to claim 1, wherein the user data includes sensor information obtained from the user's mobile device and data from an information sharing service.

[0871] "Application Example 1"

[0872] (Claim 1)

[0873] A generation means that receives individual user information and generates hair improvement suggestions suitable for the user based on said information,

[0874] A means of aggregating information that periodically collects hair-related information from the internet and stores the collected information in a database,

[0875] A notification means for notifying the user of the hair improvement suggestion generated by the generation means,

[0876] A regeneration means that receives feedback from the user and updates the proposal generated by the generation means based on the feedback,

[0877] A means of acquiring customer attribute information using a visual display device and presenting appropriate hair improvement suggestions to staff based on the aggregated information,

[0878] A system that includes this.

[0879] (Claim 2)

[0880] The system according to claim 1, comprising means for generating a visual display that visually displays the generated hair improvement suggestions in real time.

[0881] (Claim 3)

[0882] The system according to claim 1, wherein the user information includes various sensor data obtained from the user's portable terminal device and data from a communication network service.

[0883] "Example 2 of combining an emotion engine"

[0884] (Claim 1)

[0885] A means for receiving individual user information and generating hair improvement suggestions suitable for the user based on said information,

[0886] A means for periodically collecting hair-related information from the internet and storing the collected information in a storage means,

[0887] A means for notifying the user of the hair improvement suggestions generated by the generation means,

[0888] A means for receiving feedback from the aforementioned user and updating the proposal generated by the generation means based on said feedback,

[0889] A means for analyzing the emotional state of users and reflecting the results of the analysis in the proposal,

[0890] A system that includes this.

[0891] (Claim 2)

[0892] The system according to claim 1, wherein the notification means includes a display means for visually displaying the generated hair improvement suggestions.

[0893] (Claim 3)

[0894] The system according to claim 1, wherein the user information includes sensor data obtained from the user's mobile device and data from social network services.

[0895] "Application example 2 of combining emotional engines"

[0896] (Claim 1)

[0897] A generation means that receives individual user information and emotional data, and generates hair improvement suggestions suitable for the user based on said information and emotional data,

[0898] A means for aggregating hair-related information from the internet on a regular basis and storing the collected information in a storage device,

[0899] A notification means for notifying the user of the hair improvement suggestion generated by the generation means,

[0900] A regeneration means that receives feedback from the user and updates the proposal generated by the generation means based on the feedback,

[0901] A food and beverage suggestion generation method that generates food suggestions suitable for the user based on the user's emotional data,

[0902] A system that includes this.

[0903] (Claim 2)

[0904] The system according to claim 1, wherein the notification means includes means for generating a dashboard that visually displays the generated hair improvement suggestions and food suggestions.

[0905] (Claim 3)

[0906] The system according to claim 1, wherein the user information includes sensor data obtained from the user's portable device and data from lifestyle support services. [Explanation of Symbols]

[0907] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Devices 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robots< / url:> < / url:> < / url:> < / url:>

Claims

1. A generation means that receives individual user information and generates hair improvement suggestions suitable for the user based on said information, A means of aggregating information that periodically collects hair-related information from the internet and stores the collected information in a database, A notification means for notifying the user of the hair improvement suggestion generated by the generation means, A regeneration means that receives feedback from the user and updates the proposal generated by the generation means based on the feedback, A system that includes this.

2. The system according to claim 1, wherein the notification means includes means for generating a dashboard that visually displays the generated hair improvement suggestions.

3. The system according to claim 1, wherein the user information includes sensor data obtained from the user's mobile device and data from social networking services.

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