System

Abstract

A system is provided.SOLUTION: A system, comprising: means for receiving input data and collecting information about a desired orthopaedic surgery of a user; means for analyzing the received input data and generating an optimal candidate orthopaedic surgery; means for generating a specific suggestion based on the generated candidate orthopaedic surgery; and means for presenting the generated suggestion to the user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Many people interested in cosmetic surgery must gather and understand a large amount of information to find the procedure that is best for them. However, the abundance of information makes it difficult to select the procedure that is best for them. Furthermore, a lack of basic knowledge makes it difficult to make the right choice. Furthermore, anxiety increases because people cannot easily discuss information about cosmetic surgery with those around them. Technological solutions to address this issue are needed. [Means for solving the problem]

[0005] The present invention is a system for collecting information about cosmetic procedures desired by a user and proposing the most suitable cosmetic procedure. The system includes a means for allowing the user to provide input data and a means for converting the data into a standard format. The system also includes a generation means for analyzing the received input data and generating the most suitable cosmetic procedure candidates based on the user's preferences and conditions. The system also includes a proposal generation means for generating specific proposals based on the generated cosmetic procedure candidates. Finally, the system includes a display means for presenting the generated proposals to the user. This makes it easier for users to find the most suitable cosmetic procedure from a large amount of information, reducing anxiety and helping them make an appropriate choice.

[0006] "Input data" refers to information provided by users regarding their desired image and desired cosmetic procedures.

[0007] "Means for receiving" refers to the function by which the system receives input data from the user.

[0008] "Means for analyzing" refers to the function for analyzing received input data and extracting the user's wishes and conditions.

[0009] The "means for generating" refers to a function for generating optimal cosmetic surgery candidates based on the analyzed data.

[0010] The "proposal generation means" refers to a function for generating specific proposals as text or images from the generated cosmetic surgery candidates.

[0011] The "display means" refers to a function for visualizing and providing the generated proposal content to the user.

[0012] "Standard format" refers to a unified format that enhances data compatibility.

[0013] "Plastic surgery" refers to any surgical or non-surgical medical procedure performed for cosmetic purposes.

[0014] "Candidates" refers to multiple cosmetic surgery options that are suggested based on the analyzed data.

[0015] "Specific proposal details" refers to a proposal that includes detailed information such as the type of cosmetic surgery, benefits, risks, downtime, and costs. [Brief explanation of the drawings]

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

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

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

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

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

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

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

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

[0024] [First embodiment]

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

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

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

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

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

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

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

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

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

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

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

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

[0037] This invention is a generative AI system that helps users select the cosmetic surgery they desire. The system generates and provides optimal cosmetic surgery suggestions based on user input information.

[0038] System Overview and Operation

[0039] This system is broadly composed of the following four main components:

[0040] 1. User Interface (Terminal)

[0041] 2. Data Processing Server (Server)

[0042] 3. Generative AI module (server)

[0043] 4. Result display widget (terminal)

[0044] User Interface (Terminal)

[0045] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[0046] Data Processing Server (Server)

[0047] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0048] Generative AI module (server)

[0049] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0050] Result display widget (terminal)

[0051] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0052] Explanation of program processing

[0053] The program of this system performs processing in the following procedure.

[0054] 1. Enter your user information

[0055] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[0056] 2. Receiving and converting input data

[0057] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[0058] 3. Data analysis and surgical procedure selection

[0059] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[0060] 4. Proposal generation using generative AI

[0061] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and costs.

[0062] 5. Displaying the results

[0063] The device displays the suggestions received from the server to the user, who can then review the suggestions and choose the cosmetic surgery that best suits their needs.

[0064] Specific examples

[0065] Example of input data

[0066] The user enters the following information:

[0067] Desired image: Pure and gentle

[0068] Celebrity: Mr. A

[0069] Favorite clothing and style: Casual

[0070] Skeleton:Slender

[0071] Facial shape: Round face

[0072] Body type: Standard

[0073] Hair color: Black, Skin color: Fair, Eye color: Brown

[0074] Budget: 500,000 yen

[0075] Downtime: 1 week

[0076] Minor cosmetic surgery: Hope

[0077] Past plastic surgery history: None

[0078] Examples of proposals

[0079] The generative AI generates the following proposal:

[0080] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases, this can be covered with makeup.

[0081] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[0082] The processing flow will be explained below.

[0083] Step 1:

[0084] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[0085] Step 2:

[0086] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[0087] Step 3:

[0088] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[0089] Step 4:

[0090] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[0091] Step 5:

[0092] The server's data analysis module analyzes the data received from the user, extracting the user's preferences and conditions based on, for example, the "image they want to achieve," "budget," and "past plastic surgery history."

[0093] Step 6:

[0094] The server's generation AI module selects candidate cosmetic procedures based on the analysis results, extracting from the database the procedures that best fit the user's budget, downtime, and preferences.

[0095] Step 7:

[0096] The server generates specific recommendations from the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, and costs.

[0097] Step 8:

[0098] The server formats the generated suggestions into text for the user and sends it to the terminal.

[0099] Step 9:

[0100] The device receives the proposal from the server and displays it in a format that is easy for the user to understand, such as an image or a detailed explanation.

[0101] Step 10:

[0102] The user reviews the displayed information and decides which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[0103] Through the above steps, the system will suggest the most suitable cosmetic surgery to the user and help them make a choice with confidence.

[0104] Example 1

[0105] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0106] In today's world, the demand for cosmetic surgery is on the rise, making it important for users to select the most suitable cosmetic surgery that suits their needs. However, it is not easy for users to find the most suitable cosmetic surgery from the vast amount of information available. In addition, there is a lack of systems that can generate effective suggestions based on users' wishes and conditions. Therefore, there is a need for a system that allows users to easily and accurately receive suggestions for the most suitable cosmetic surgery.

[0107] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0108] In this invention, the server includes means for a user to input data using a terminal and collect information, means for converting the received input data into a format that the server can analyze, means for the server to analyze the input data and select optimal cosmetic surgery candidates based on the user's wishes and conditions, means for a generation AI module to generate detailed recommendations for optimal cosmetic surgery, and means for the terminal to display the generated recommendations to the user, thereby enabling the user to easily and accurately receive recommendations for the optimal cosmetic surgery.

[0109] "User" refers to an individual who utilizes the System to input information about their desired cosmetic procedure and receive the best possible recommendations.

[0110] "Device" means a computer device, smartphone, tablet, or other device through which a user enters information and / or reviews generated cosmetic surgery recommendations.

[0111] "Server" refers to the central processing unit that analyzes the data received from the User and generates optimal cosmetic surgery recommendations using the generative AI module.

[0112] "Input data" refers to information that users enter into the system, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial shape, body type, hair, skin and eye color, budget, desired downtime, desired minor cosmetic surgery, and past cosmetic surgery history.

[0113] "Parsable format" refers to a standard data format (e.g., JSON) required for the server to process and parse the data correctly.

[0114] "Generative AI module" refers to an artificial intelligence software component that automatically generates detailed recommendations for optimal cosmetic surgery based on input data and the server's analysis results.

[0115] "Recommendations" means the cosmetic surgery recommendations generated by the Generative AI Module, including details such as the type of cosmetic surgery that best suits the User's preferences and requirements, benefits, risks, required downtime, and costs.

[0116] The "display means" is a system component for visually presenting the generated proposal content to the user, and mainly refers to a user interface that operates on a terminal.

[0117] The present invention is a generative AI system that helps users select the cosmetic surgery they desire. The system aims to generate and provide optimal cosmetic surgery suggestions based on user input information.

[0118] System Overview and Operation

[0119] The system consists of four main components:

[0120] 1. User Interface (Terminal)

[0121] 2. Data Processing Server (Server)

[0122] 3. Generative AI module (server)

[0123] 4. Result display widget (terminal)

[0124] User Interface (Terminal)

[0125] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After entering this information and submitting it, the data is transferred to the server.

[0126] Data Processing Server (Server)

[0127] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0128] Specifically, it uses a web framework such as Python's Flask to receive data sent as an HTTP request, and then analyzes the data using libraries such as Pandas and Scikit-learn.

[0129] Generative AI module (server)

[0130] The generative AI module generates optimal plastic surgery candidates based on the results of data analysis. This module uses a large database to suggest the plastic surgery that best suits the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific type of plastic surgery, its benefits, risks, required downtime, and costs. Generative AI models such as GPT-3 are used.

[0131] Example prompt sentence:

[0132] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[0133] Result display widget (terminal)

[0134] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0135] For example, the user enters the following information:

[0136] Desired image: Pure and gentle

[0137] Celebrities: Famous people

[0138] Favorite clothing and style: Casual

[0139] Skeleton:Slender

[0140] Facial shape: Round face

[0141] Body type: Standard

[0142] Hair color: Black, Skin color: Fair, Eye color: Brown

[0143] Budget: 500,000 yen

[0144] Downtime: 1 week

[0145] Minor cosmetic surgery: Hope

[0146] Past plastic surgery history: None

[0147] An example of the generated suggestions:

[0148] "I recommend the 'mini-double eyelid surgery' to achieve a neat and gentle look. The downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup."

[0149] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[0150] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0151] Step 1:

[0152] Using the device interface, users enter details about the cosmetic surgery they wish to undergo, including the image they want to achieve, celebrities, preferred clothing and style, bone structure, facial features, body type, hair, skin, and eye color, budget, desired downtime, desired minor cosmetic surgery, and previous cosmetic surgery history. When the user clicks the "Submit" button, the entered data is sent from the device to the server.

[0153] Input: User-entered details about the plastic surgery

[0154] Output: Detailed information about the surgery sent (terminal → server)

[0155] Step 2:

[0156] The terminal receives input data from the user and converts it into a standard format (e.g., JSON format). The converted data is then transferred to the server. By converting the data into the appropriate format, the server can more easily analyze it.

[0157] Specifically, the device structures the user's input data, parses it into JSON format, and sends it to the server as an HTTP request.

[0158] Input: Raw data from the user

[0159] Output: Data converted to JSON format (terminal → server)

[0160] Step 3:

[0161] The server receives the JSON data sent from the device and converts it into a format that can be parsed. An analysis module on the server then analyzes the data and selects the most suitable plastic surgery candidates based on the user's preferences and conditions.

[0162] Specifically, the server receives HTTP requests using a framework such as Python's Flask and analyzes the data using libraries such as Pandas and Scikit-learn.

[0163] Input: Input data in JSON format

[0164] Output: Data converted into a parsable format and optimal cosmetic surgery candidates

[0165] Step 4:

[0166] The generative AI module generates detailed recommendations for the most suitable cosmetic surgery based on the data analyzed on the server. This module uses a large database and a generative AI model (e.g., GPT-3) to generate the recommendations. Based on the prompt, the module automatically generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0167] Specifically, a prompt sentence is input into the generation AI module, and a sentence suggesting the optimal plastic surgery is generated as a response to the prompt.

[0168] Example prompt sentence:

[0169] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[0170] Input: Parsed data and prompt statements

[0171] Output: Detailed plastic surgery proposals generated

[0172] Step 5:

[0173] The device receives the recommendations generated by the server and displays them to the user, allowing the user to review the specific recommendations and make the best choice for themselves. The recommendations include detailed information such as the most suitable type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0174] Specifically, the device visually displays the received information using HTML and CSS. By providing information in an easy-to-understand format for users, decision-making becomes smoother.

[0175] Input: Generated plastic surgery proposal

[0176] Output: Display the suggestion to the user

[0177] (Application example 1)

[0178] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0179] Conventional cosmetic surgery and fashion recommendation systems have struggled to provide optimal recommendations in real time based on a user's detailed wishes and requirements. They also lacked an interactive system that allowed users to efficiently find the items and procedures that best suit them. This meant that users had to spend a great deal of time and effort trying to find their ideal style and procedure.

[0180] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0181] In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery or fashion desired by the user, means for analyzing the received input data and generating optimal cosmetic surgery candidates or fashion items, and means for generating specific proposals based on the generated cosmetic surgery candidates or fashion items, thereby making it possible to propose optimal cosmetic surgery or fashion items based on the user's detailed wishes and conditions.

[0182] "Input data" refers to data that indicates information about cosmetic surgery or fashion desired by the user.

[0183] "Receiving" refers to the process by which input data is taken in by the system.

[0184] "User" means an individual who utilizes the System to seek cosmetic or fashion item recommendations.

[0185] The "generation means" refers to a processing function that analyzes received input data and generates optimal cosmetic surgery candidates or fashion items.

[0186] The "proposal generation means" refers to a processing function that generates specific proposal content based on the generated cosmetic surgery candidates or fashion items.

[0187] The "display means" refers to a device or function that visually presents the generated proposal content to the user.

[0188] "Standard format" means a format that provides a consistent structure or format for data and allows input data from a user to be sent to a server in a parsable form.

[0189] "Analysis" refers to the process of analyzing the received input data in detail to extract the user's wishes and conditions.

[0190] "Candidate" refers to each of the multiple cosmetic or fashion items selected by the generating means.

[0191] "Information" refers to specific data based on the user's wishes and conditions.

[0192] The term "server" refers to a device or system that performs a series of processes including receiving, analyzing, generating, and displaying input data.

[0193] System program generation

[0194] The system includes a program for recommending optimal cosmetic surgery or fashion items based on the user's preferences and conditions. This program is composed of multiple components, each of which functions in conjunction with the others.

[0195] Hardware and Software

[0196] The system is implemented using the following main hardware and software:

[0197] 1. User terminal (smartphone, smart glasses): A device that allows users to input information and check the results.

[0198] 2. Data Processing Server: A server for receiving input data, converting it into a standard format, and analyzing the data.

[0199] 3. Generative AI module (server): This module contains an AI model for generating specific proposals based on the generated candidates.

[0200] 4. Result display widget (terminal): This is a component for visually displaying the generated suggestions to the user.

[0201] Specific explanation of program processing

[0202] Receiving input data

[0203] Using the interface of a smartphone or smart glasses, a user inputs information about their desired cosmetic surgery or fashion, such as "I like casual style" or "I like the color blue," and this information is sent from the device to a data processing server.

[0204] Receiving data and converting it to a standard format

[0205] The server receives input data sent by the user, converts it into a standard format such as JSON, and makes it ready for analysis.

[0206] Data analysis and generation

[0207] The generative AI module analyzes the data converted into a standard format and generates optimal cosmetic surgery candidates and fashion items based on the user's preferences and conditions, using a pre-trained generative AI model.

[0208] Proposal generation and display

[0209] The generative AI module creates specific recommendations based on the generated candidates, including details of plastic surgery, descriptions of fashion items, benefits, risks, prices, etc. The generated recommendations are sent to the user's device via the data processing server and displayed to the user via the result display widget.

[0210] Examples and prompts

[0211] For example, a user enters the following information:

[0212] Image: Casual

[0213] Favorite color: Blue

[0214] Skeleton:Slender

[0215] Height: 160cm

[0216] Body type: Standard

[0217] Hair color: Black, Eye color: Brown

[0218] Budget: 30,000 yen

[0219] An example prompt is:

[0220] "Please suggest the best fashion items and outfits for a casual image, someone who likes the color blue, is 160cm tall with a slim build, average build, black hair, brown eyes, and a budget of 30,000 yen or less."

[0221] This allows the system to provide optimal proposals in real time based on the user's detailed wishes and conditions.

[0222] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0223] Step 1:

[0224] Users use the interface of their smartphone or smart glasses to input information about their desired cosmetic surgery or fashion. Users input specific preferences and conditions, such as "I like casual styles" or "I like the color blue." This generates input data.

[0225] Step 2:

[0226] The terminal receives data entered by the user and converts it into a standard format such as JSON. The converted data is ready for analysis. The input here is information including the user's wishes and requirements, and the output is data in a standard format that can be analyzed.

[0227] Step 3:

[0228] The server receives input data converted into a standard format, analyzes the received data, and prepares data to generate optimal cosmetic surgery candidates or fashion items based on the user's preferences and conditions. The input is data in a standard format, and the output is the analysis results.

[0229] Step 4:

[0230] The generative AI module uses data provided by the server to generate optimal plastic surgery candidates or fashion items based on a generative AI model. The generated candidates include details of the procedure or item, as well as benefits, risks, and price. The input is the analysis results, and the output is the generated candidate list.

[0231] Step 5:

[0232] The generative AI module generates specific recommendations based on the generated candidate list, including the type of cosmetic surgery, details of fashion items, benefits, risks, required downtime, costs, etc. The input is the generated candidate list, and the output is the specific recommendations.

[0233] Step 6:

[0234] The server sends the specific proposal provided by the generation AI module to the user terminal. The input is the proposal content, and the output is the transmission of the proposal data to the user terminal.

[0235] Step 7:

[0236] The terminal displays the proposals received from the server to the user. The user can then select the cosmetic surgery or fashion item that best suits their needs based on the information obtained. The input is the proposal data from the server, and the output is the proposal displayed to the user.

[0237] This allows users to receive real-time recommendations for the best cosmetic surgery or fashion items based on their detailed wishes and requirements.

[0238] Furthermore, an emotion engine that estimates the user's emotion may be combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59 and perform identification processing using the user's emotion.

[0239] This invention is a generative AI system that takes into account the user's emotional state when selecting the cosmetic surgery they desire and proposes the most suitable cosmetic surgery. The system generates and provides optimal cosmetic surgery proposals based on the user's input information.

[0240] System Overview and Operation

[0241] This system is broadly composed of the following five main components:

[0242] 1. User Interface (Terminal)

[0243] 2. Data Processing Server (Server)

[0244] 3. Generative AI module (server)

[0245] 4. Emotion engine (server)

[0246] 5. Result display widget (terminal)

[0247] User Interface (Terminal)

[0248] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[0249] Data Processing Server (Server)

[0250] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences and conditions.

[0251] Generative AI module (server)

[0252] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0253] Emotion engine (server)

[0254] The emotion engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the cosmetic surgery options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[0255] Result display widget (terminal)

[0256] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0257] Explanation of program processing

[0258] The program of this system performs processing in the following procedure.

[0259] 1. Enter your user information

[0260] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[0261] 2. Receiving and converting input data

[0262] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[0263] 3. Data analysis and surgical procedure selection

[0264] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[0265] 4. Emotion Recognition with Emotion Engine

[0266] The emotion engine analyzes the user's emotional state based on input data and past data, recognizing emotions such as anxiety, anticipation, and hope.

[0267] 5. Proposal generation using generative AI

[0268] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and cost, and adjusts the recommendations based on information from the emotion engine.

[0269] 6. Displaying the results

[0270] The terminal displays the proposal received from the server to the user, for example, by displaying an image or a specific explanation.

[0271] Specific examples

[0272] Example of input data

[0273] The user enters the following information:

[0274] Desired image: Pure and gentle

[0275] Celebrity: Mr. A

[0276] Favorite clothing and style: Casual

[0277] Skeleton:Slender

[0278] Facial shape: Round face

[0279] Body type: Standard

[0280] Hair color: Black, Skin color: Fair, Eye color: Brown

[0281] Budget: 500,000 yen

[0282] Downtime: 1 week

[0283] Minor cosmetic surgery: Hope

[0284] Past plastic surgery history: None

[0285] Examples of proposals

[0286] If the emotion engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[0287] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is approximately one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[0288] In this way, the system takes into account the user's emotional state and suggests the most appropriate cosmetic surgery, helping the user make a choice with confidence.

[0289] The processing flow will be explained below.

[0290] Step 1:

[0291] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[0292] Step 2:

[0293] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[0294] Step 3:

[0295] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[0296] Step 4:

[0297] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[0298] Step 5:

[0299] The server's data analysis module analyzes the data received from the user and extracts the user's wishes and requirements. For example, the user's wishes are identified based on the "image they want to achieve," "budget," and "past plastic surgery history."

[0300] Step 6:

[0301] The server's emotion engine analyzes emotions (e.g., anxiety, anticipation, relief, etc.) from the user's input data. This emotion information influences subsequent suggestion generation.

[0302] Step 7:

[0303] The server's generative AI module selects the most suitable plastic surgery candidates based on the analysis results and the output of the emotion engine. For example, if the user is feeling anxious, suggestions including ways to mitigate risks and detailed procedure procedures will be selected.

[0304] Step 8:

[0305] The server generates specific recommendations based on the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, costs, and care information. Based on information from the emotion engine, the recommendation also includes explanations and advice based on the user's emotions.

[0306] Step 9:

[0307] The server formats the generated suggestions into text for the user and sends it to the terminal.

[0308] Step 10:

[0309] The device receives the suggestions from the server and displays them in a user-friendly format, including images and detailed explanations.

[0310] Step 11:

[0311] The user can review the displayed information and decide which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[0312] Through these steps, the system proposes the most appropriate cosmetic surgery procedure while taking into account the user's emotional state, helping the user to make an appropriate choice with peace of mind.

[0313] Example 2

[0314] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0315] Currently, when users select a plastic surgery, it is difficult to obtain optimal suggestions that take into account their emotional state and detailed desired conditions. In particular, if the user has emotional states such as anxiety or anticipation, suggestions that do not take these emotions into account may reduce user satisfaction. Therefore, there is a need for a system that can properly recognize the user's emotional state and suggest the optimal plastic surgery that suits each individual situation.

[0316] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0317] In this invention, the server includes means for receiving input data and collecting information on the treatment desired by the user, means for analyzing the received input data and generating optimal treatment candidates, means for recognizing the emotional state of the user based on the input data, and means for generating specific proposals based on the generated treatment candidates and the emotional state, thereby making it possible to propose optimal treatments while taking the emotional state of the user into consideration.

[0318] "Input data" refers to data that includes information and conditions regarding the treatment desired by the user.

[0319] "Means for receiving" refers to a device or program that has the function of incorporating input data sent by a user into the system.

[0320] The "analyzing means" refers to a device or program that has the function of analyzing information based on received input data and selecting the most suitable treatment options.

[0321] The "generation means" is a device or program that has the function of automatically generating specific treatment candidates that meet the user's wishes based on the analysis results.

[0322] "Emotion recognition means" refers to a device or program that has the function of analyzing user input data and other information to identify the user's emotional state.

[0323] The "proposal generation means" is a device or program that has the function of creating specific proposal content based on the generated treatment candidates and the results of the emotion recognition means.

[0324] The "display means" refers to a device or program that has the function of visually presenting the generated proposal content to the user.

[0325] A "standard format" is a consistent data format required for systems to analyze and process data.

[0326] This invention is a generative AI system that takes into account the emotional state of the user when selecting the desired treatment and makes optimal suggestions. The system analyzes information provided by the user and suggests the optimal treatment for the user.

[0327] System Configuration

[0328] This system is broadly composed of the following five main components:

[0329] 1. User Interface (Terminal)

[0330] 2. Data Processing Server (Server)

[0331] 3. Generative AI module (server)

[0332] 4. Emotion Recognition Engine (Server)

[0333] 5. Result display widget (terminal)

[0334] User Interface (Terminal)

[0335] Users use a terminal to enter their information, including the image they want to resemble, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, downtime, whether they want simple treatment, and past treatment history. After entering this information and clicking the "Submit" button, the data is transferred to the server.

[0336] Data Processing Server (Server)

[0337] The server receives input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects candidate actions based on the user's wishes and conditions.

[0338] Generative AI module (server)

[0339] The generative AI module generates optimal treatment options based on the results of data analysis. This module uses a large database to suggest the best treatment for the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific treatment type, benefits, risks, required downtime, and costs.

[0340] Emotion recognition engine (server)

[0341] The emotion recognition engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the treatment options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[0342] Result display widget (terminal)

[0343] The device receives the recommendations sent from the server and displays them on the user's screen, allowing the user to check detailed information about specific treatments and make the best choice for themselves.

[0344] Specific examples

[0345] Example of input data

[0346] The user enters the following information:

[0347] Desired image: Pure and gentle

[0348] Celebrity: Mr. A

[0349] Favorite clothing and style: Casual

[0350] Skeleton:Slender

[0351] Facial shape: Round face

[0352] Body type: Standard

[0353] Hair color: Black, Skin color: Fair, Eye color: Brown

[0354] Budget: 500,000 yen

[0355] Downtime: 1 week

[0356] Simple Treatment: Hope

[0357] Past treatment history: None

[0358] Examples of proposals

[0359] If the emotion recognition engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[0360] Recommendation: We recommend the "simple double eyelid surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[0361] This system allows users to make choices with confidence, as it suggests the most appropriate treatment that takes into account their emotional state.

[0362] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0363] Step 1: Enter your user information

[0364] The user enters their information using the device's user interface. Specifically, they enter details in fields such as "desired image," "budget," "desired downtime," and "past treatment history," and click the "Submit" button. This action sends the user's input data (in JSON format) from the device to the server.

[0365] Input: User information (desired image, budget, desired downtime, etc.)

[0366] Output: Send input data (JSON format)

[0367] Step 2: Receiving and converting input data

[0368] The device receives the data sent by the user. After receiving the data, the device converts it into the correct format (e.g., JSON format) and forwards it to the server. The server converts the received data into a parsable format and prepares it for data processing.

[0369] Input: User input data (JSON format)

[0370] Output: Data converted into a parsable format

[0371] Step 3: Data analysis and treatment selection

[0372] The server analyzes the received data using the data processing server's analysis module. Based on the user's preferences and conditions (e.g., "round face," "black hair," "budget of 500,000 yen," etc.), it selects the most suitable treatment options. This analysis process uses a large database of past data and treatments to make the best recommendations.

[0373] Input: Data converted into a parsable format

[0374] Output: Candidates for optimal treatment

[0375] Step 4: Recognizing emotions with the emotion recognition engine

[0376] The server uses an emotion recognition engine to analyze the user's emotional state. Specifically, it recognizes emotions such as "anxiety" or "expectation" based on the user's input data and past data. This emotional information is reflected in subsequent suggestions.

[0377] Input: User-entered and historical data

[0378] Output: Information about the user's emotional state

[0379] Step 5: Generative AI generates proposals

[0380] The generative AI module generates specific treatment recommendations based on the server's analysis results and information from the emotion recognition engine. Specifically, it makes detailed recommendations such as "simple double eyelid surgery," "one week of downtime," and "cost: 300,000 yen." If the user is feeling anxious, it makes adjustments based on the user's emotional information, such as adding detailed information about risks and care.

[0381] Input: Optimal treatment options and emotional information

[0382] Output: Specific proposals

[0383] Step 6: View the results

[0384] The terminal displays the proposal received from the server to the user. Specifically, the generated treatment details, benefits, risks, downtime, costs, etc. are displayed on the user interface, allowing the user to review the information and make the best choice for themselves.

[0385] Input: Specific proposal

[0386] Output: Display of proposal

[0387] Through this series of processes, the user is presented with the optimal course of action that takes into account their emotional state, allowing them to make a choice with confidence.

[0388] (Application example 2)

[0389] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart device 14 will be referred to as a "terminal."

[0390] Conventional security services have the problem that it is difficult for security guards to quickly decide on the appropriate response on the scene, and there is a high possibility that they will make incorrect decisions, especially when psychological factors such as emotions and stress are influential.In addition, because uniform response measures are provided without considering the emotional state of the security guards themselves, there is a need for flexible responses that are appropriate for the situation.

[0391] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery desired by the user, generation means for analyzing the received input data and generating optimal cosmetic surgery candidates, proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates, means for analyzing the emotional states of the security target and security guards using a generation AI and proposing optimal countermeasures, and display means for presenting the generated proposals to the user. This allows optimal countermeasures to be provided in real time based on the situation and emotional state of the scene, enabling security guards to take prompt and appropriate action.

[0392] "Input Data" refers to information about your preferences and circumstances submitted by you.

[0393] "Generation means" refers to the part of the system that analyzes the received input data and generates optimal cosmetic surgery or treatment options based on the user's preferences.

[0394] The "proposal generation means" refers to a part of the system that creates specific proposals based on the candidate cosmetic procedures and countermeasures generated by the generation means.

[0395] "Generative AI" refers to artificial intelligence technology that analyzes large amounts of data to understand a user's wishes and emotional state and make optimal suggestions.

[0396] "Emotional state" refers to the psychological state (e.g., anxiety, stress, relief, etc.) of the user, the person being guarded, and the security guard.

[0397] The "generated proposal content" refers to detailed information about specific cosmetic procedures and countermeasures created by the proposal generation means.

[0398] "Display means" refers to the part of the system that allows the user to visually confirm the generated suggestions.

[0399] System Overview and Operation

[0400] 1. System Components

[0401] The system of the present invention consists of the following major components:

[0402] User Interface (Terminal)

[0403] Data Processing Server

[0404] Generative AI Module

[0405] Emotion Engine

[0406] Result Display Widget

[0407] 2. Hardware and Software Used

[0408] The system uses devices such as smartphones and smart glasses, various servers, analysis libraries, and generative AI models. The specific hardware and software used includes the following:

[0409] Hardware: Smartphones (iOS / Android), smart glasses (Google Glass, Microsoft HoloLens)

[0410] Software: AWS, Google Cloud, Microsoft Azure (data processing servers), MySQL, MongoDB (databases), IBM Watson Emotion Analysis, Microsoft Text Analytics (sentiment analysis library), OpenAI GPT-4, Google BERT (generative AI module)

[0411] 3. Natural Language Description

[0412] User Interface (Terminal)

[0413] Users use their smartphones or smart glasses to input their personal information, the situation at the scene, the condition of the person being guarded, and the guard's own emotions. This information is sent to the server in JSON format through the application.

[0414] Data Processing Server

[0415] The server receives input data in a standard format (JSON) and converts it into a format that can be parsed. Cloud services such as AWS, Google Cloud, and Microsoft Azure are used for data processing. Information is stored in the database using MySQL or MongoDB.

[0416] Generative AI Module

[0417] The generative AI module analyzes the received data and generates optimal countermeasures based on the user's preferences and on-site conditions, using AI models such as OpenAI GPT-4 and Google BERT. This generates recommendations that include details such as the type of specific cosmetic or security countermeasure, its benefits, risks, costs, and required time.

[0418] Emotion Engine

[0419] The emotion engine uses emotion analysis libraries like IBM Watson Emotion Analysis and Microsoft Text Analytics to analyze the user's emotional state from their input data. Based on this analysis, the generative AI module optimizes the suggestions it generates. For example, if a security guard is feeling anxious, the suggestions will take that into account.

[0420] Result Display Widget

[0421] The result display widget displays the generated suggestions on the user's smartphone or smart glasses, allowing the user to review the suggestions and select the appropriate response.

[0422] 4. Examples and prompts

[0423] As a concrete example, suppose the user enters the following information:

[0424] Example of input data

[0425] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[0426] Condition of the guarded person: "Face red and appears very angry."

[0427] Security guard's feelings: "I feel unsafe."

[0428] Specific examples of proposals

[0429] The system receives the above information, and if the emotion engine detects "anxiety," the generative AI makes the following suggestions:

[0430] "We will continue to monitor the situation on site and instruct people to maintain distance from each other to stay safe. If you feel unsafe, please contact security headquarters and report the situation. We will also provide advice on how to stay calm, for example, by taking deep breaths to calm yourself down."

[0431] Example prompts for generative AI models

[0432] Generate optimal responses based on the user's emotional state and on-site conditions.

[0433] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[0434] Condition of the guarded person: "Face red and appears very angry."

[0435] Security guard's feelings: "I feel unsafe."

[0436] In this way, the system helps security guards take prompt and appropriate action by making appropriate suggestions in real time that take into account their emotional state.

[0437] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0438] Step 1:

[0439] The user uses the terminal to input the situation at the scene, the state of the person being guarded, and their own emotions. The input data includes the situation at the scene (e.g., "crowded"), the state of the person being guarded (e.g., "his face is red and he looks very angry"), and the emotions of the security guard (e.g., "he feels anxious"). The user clicks the "Send" button to send the input data to the server.

[0440] Step 2:

[0441] The terminal receives input data sent by the user and converts it into JSON format. The converted data is then transferred to the server. The input data (the situation at the scene, the state of the person being guarded, and the security guard's emotions) is converted into JSON format and sent.

[0442] Step 3:

[0443] The server converts the received JSON formatted input data into a parsable format. Specifically, it processes it so that it can be stored in a database (MySQL, MongoDB). Through this processing, the server obtains a format that can be stored in the database (for example, a structured table format).

[0444] Step 4:

[0445] The server performs data analysis based on the converted input data. The analysis uses the computational resources of cloud services (AWS, Google Cloud, Microsoft Azure), and a generative AI model (OpenAI GPT-4, Google BERT) generates optimal candidate solutions. Based on the input data, solutions are proposed that match the user's wishes and the situation on-site.

[0446] Step 5:

[0447] The emotion engine analyzes the user's emotional state from the input data. This process uses emotion analysis libraries (IBM Watson Emotion Analysis, Microsoft Text Analytics). The emotion engine analyzes the user's input data and obtains the emotional state (e.g., "anxiety").

[0448] Step 6:

[0449] The generative AI module adjusts its suggestions based on the emotional state information obtained from the emotion engine. For example, if a security guard feels "anxious," it will suggest countermeasures with specific instructions to mitigate risk. The generative AI model is used to generate detailed instructions and advice to reassure the user.

[0450] Step 7:

[0451] The server sends the generated proposal to the device, which then displays it on the user's screen. For example, details of appropriate countermeasures and necessary steps are displayed, allowing the user to act accordingly.

[0452] This series of processes allows users to receive optimal countermeasures in real time based on the situation at the scene and their own emotional state.

[0453] The specific processing unit 290 transmits the result of the specific processing to the smart device 14. In the smart device 14, the control unit 46A causes the output device 40 to output the result of the specific processing. The microphone 38B acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 38B to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0454] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0455] In the above embodiment, an example in which the specific process is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific process may be performed by the smart device 14.

[0456] [Second embodiment]

[0457] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0458] 3, the data processing system 210 includes the data processing device 12 and smart glasses 214. An example of the data processing device 12 is a server.

[0459] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0460] The smart glasses 214 include a computer 36, a microphone 238, a speaker 240, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, and the camera 42 are also connected to the bus 52.

[0461] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0462] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0463] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0464] Fig. 4 shows an example of the main functions of the data processing device 12 and the smart glasses 214. As shown in Fig. 4, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0465] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0466] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0467] In the smart glasses 214, the reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0468] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the smart glasses 214 will be referred to as the "terminal."

[0469] This invention is a generative AI system that helps users select the cosmetic surgery they desire. The system generates and provides optimal cosmetic surgery suggestions based on user input information.

[0470] System Overview and Operation

[0471] This system is broadly composed of the following four main components:

[0472] 1. User Interface (Terminal)

[0473] 2. Data Processing Server (Server)

[0474] 3. Generative AI module (server)

[0475] 4. Result display widget (terminal)

[0476] User Interface (Terminal)

[0477] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[0478] Data Processing Server (Server)

[0479] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0480] Generative AI module (server)

[0481] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0482] Result display widget (terminal)

[0483] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0484] Explanation of program processing

[0485] The program of this system performs processing in the following procedure.

[0486] 1. Enter your user information

[0487] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[0488] 2. Receiving and converting input data

[0489] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[0490] 3. Data analysis and surgical procedure selection

[0491] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[0492] 4. Proposal generation using generative AI

[0493] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and costs.

[0494] 5. Displaying the results

[0495] The device displays the suggestions received from the server to the user, who can then review the suggestions and choose the cosmetic surgery that best suits their needs.

[0496] Specific examples

[0497] Example of input data

[0498] The user enters the following information:

[0499] Desired image: Pure and gentle

[0500] Celebrity: Mr. A

[0501] Favorite clothing and style: Casual

[0502] Skeleton:Slender

[0503] Facial shape: Round face

[0504] Body type: Standard

[0505] Hair color: Black, Skin color: Fair, Eye color: Brown

[0506] Budget: 500,000 yen

[0507] Downtime: 1 week

[0508] Minor cosmetic surgery: Hope

[0509] Past plastic surgery history: None

[0510] Examples of proposals

[0511] The generative AI generates the following proposal:

[0512] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases, this can be covered with makeup.

[0513] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[0514] The processing flow will be explained below.

[0515] Step 1:

[0516] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[0517] Step 2:

[0518] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[0519] Step 3:

[0520] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[0521] Step 4:

[0522] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[0523] Step 5:

[0524] The server's data analysis module analyzes the data received from the user, extracting the user's preferences and conditions based on, for example, the "image they want to achieve," "budget," and "past plastic surgery history."

[0525] Step 6:

[0526] The server's generation AI module selects candidate cosmetic procedures based on the analysis results, extracting from the database the procedures that best fit the user's budget, downtime, and preferences.

[0527] Step 7:

[0528] The server generates specific recommendations from the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, and costs.

[0529] Step 8:

[0530] The server formats the generated suggestions into text for the user and sends it to the terminal.

[0531] Step 9:

[0532] The device receives the proposal from the server and displays it in a format that is easy for the user to understand, such as an image or a detailed explanation.

[0533] Step 10:

[0534] The user reviews the displayed information and decides which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[0535] Through the above steps, the system will suggest the most suitable cosmetic surgery to the user and help them make a choice with confidence.

[0536] Example 1

[0537] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0538] In today's world, the demand for cosmetic surgery is on the rise, making it important for users to select the most suitable cosmetic surgery that suits their needs. However, it is not easy for users to find the most suitable cosmetic surgery from the vast amount of information available. In addition, there is a lack of systems that can generate effective suggestions based on users' wishes and conditions. Therefore, there is a need for a system that allows users to easily and accurately receive suggestions for the most suitable cosmetic surgery.

[0539] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0540] In this invention, the server includes means for a user to input data using a terminal and collect information, means for converting the received input data into a format that the server can analyze, means for the server to analyze the input data and select optimal cosmetic surgery candidates based on the user's wishes and conditions, means for a generation AI module to generate detailed recommendations for optimal cosmetic surgery, and means for the terminal to display the generated recommendations to the user, thereby enabling the user to easily and accurately receive recommendations for the optimal cosmetic surgery.

[0541] "User" refers to an individual who utilizes the System to input information about their desired cosmetic procedure and receive the best possible recommendations.

[0542] "Device" means a computer device, smartphone, tablet, or other device through which a user enters information and / or reviews generated cosmetic surgery recommendations.

[0543] "Server" refers to the central processing unit that analyzes the data received from the User and generates optimal cosmetic surgery recommendations using the generative AI module.

[0544] "Input data" refers to information that users enter into the system, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial shape, body type, hair, skin and eye color, budget, desired downtime, desired minor cosmetic surgery, and past cosmetic surgery history.

[0545] "Parsable format" refers to a standard data format (e.g., JSON) required for the server to process and parse the data correctly.

[0546] "Generative AI module" refers to an artificial intelligence software component that automatically generates detailed recommendations for optimal cosmetic surgery based on input data and the server's analysis results.

[0547] "Recommendations" means the cosmetic surgery recommendations generated by the Generative AI Module, including details such as the type of cosmetic surgery that best suits the User's preferences and requirements, benefits, risks, required downtime, and costs.

[0548] The "display means" is a system component for visually presenting the generated proposal content to the user, and mainly refers to a user interface that operates on a terminal.

[0549] The present invention is a generative AI system that helps users select the cosmetic surgery they desire. The system aims to generate and provide optimal cosmetic surgery suggestions based on user input information.

[0550] System Overview and Operation

[0551] The system consists of four main components:

[0552] 1. User Interface (Terminal)

[0553] 2. Data Processing Server (Server)

[0554] 3. Generative AI module (server)

[0555] 4. Result display widget (terminal)

[0556] User Interface (Terminal)

[0557] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After entering this information and submitting it, the data is transferred to the server.

[0558] Data Processing Server (Server)

[0559] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0560] Specifically, it uses a web framework such as Python's Flask to receive data sent as an HTTP request, and then analyzes the data using libraries such as Pandas and Scikit-learn.

[0561] Generative AI module (server)

[0562] The generative AI module generates optimal plastic surgery candidates based on the results of data analysis. This module uses a large database to suggest the plastic surgery that best suits the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific type of plastic surgery, its benefits, risks, required downtime, and costs. Generative AI models such as GPT-3 are used.

[0563] Example prompt sentence:

[0564] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[0565] Result display widget (terminal)

[0566] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0567] For example, the user enters the following information:

[0568] Desired image: Pure and gentle

[0569] Celebrities: Famous people

[0570] Favorite clothing and style: Casual

[0571] Skeleton:Slender

[0572] Facial shape: Round face

[0573] Body type: Standard

[0574] Hair color: Black, Skin color: Fair, Eye color: Brown

[0575] Budget: 500,000 yen

[0576] Downtime: 1 week

[0577] Minor cosmetic surgery: Hope

[0578] Past plastic surgery history: None

[0579] An example of the generated suggestions:

[0580] "I recommend the 'mini-double eyelid surgery' to achieve a neat and gentle look. The downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup."

[0581] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[0582] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0583] Step 1:

[0584] Using the device interface, users enter details about the cosmetic surgery they wish to undergo, including the image they want to achieve, celebrities, preferred clothing and style, bone structure, facial features, body type, hair, skin, and eye color, budget, desired downtime, desired minor cosmetic surgery, and previous cosmetic surgery history. When the user clicks the "Submit" button, the entered data is sent from the device to the server.

[0585] Input: User-entered details about the plastic surgery

[0586] Output: Detailed information about the surgery sent (terminal → server)

[0587] Step 2:

[0588] The terminal receives input data from the user and converts it into a standard format (e.g., JSON format). The converted data is then transferred to the server. By converting the data into the appropriate format, the server can more easily analyze it.

[0589] Specifically, the device structures the user's input data, parses it into JSON format, and sends it to the server as an HTTP request.

[0590] Input: Raw data from the user

[0591] Output: Data converted to JSON format (terminal → server)

[0592] Step 3:

[0593] The server receives the JSON data sent from the device and converts it into a format that can be parsed. An analysis module on the server then analyzes the data and selects the most suitable plastic surgery candidates based on the user's preferences and conditions.

[0594] Specifically, the server receives HTTP requests using a framework such as Python's Flask and analyzes the data using libraries such as Pandas and Scikit-learn.

[0595] Input: Input data in JSON format

[0596] Output: Data converted into a parsable format and optimal cosmetic surgery candidates

[0597] Step 4:

[0598] The generative AI module generates detailed recommendations for the most suitable cosmetic surgery based on the data analyzed on the server. This module uses a large database and a generative AI model (e.g., GPT-3) to generate the recommendations. Based on the prompt, the module automatically generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0599] Specifically, a prompt sentence is input into the generation AI module, and a sentence suggesting the optimal plastic surgery is generated as a response to the prompt.

[0600] Example prompt sentence:

[0601] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[0602] Input: Parsed data and prompt statements

[0603] Output: Detailed plastic surgery proposals generated

[0604] Step 5:

[0605] The device receives the recommendations generated by the server and displays them to the user, allowing the user to review the specific recommendations and make the best choice for themselves. The recommendations include detailed information such as the most suitable type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0606] Specifically, the device visually displays the received information using HTML and CSS. By providing information in an easy-to-understand format for users, decision-making becomes smoother.

[0607] Input: Generated plastic surgery proposal

[0608] Output: Display the suggestion to the user

[0609] (Application example 1)

[0610] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0611] Conventional cosmetic surgery and fashion recommendation systems have struggled to provide optimal recommendations in real time based on a user's detailed wishes and requirements. They also lacked an interactive system that allowed users to efficiently find the items and procedures that best suit them. This meant that users had to spend a great deal of time and effort trying to find their ideal style and procedure.

[0612] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[0613] In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery or fashion desired by the user, means for analyzing the received input data and generating optimal cosmetic surgery candidates or fashion items, and means for generating specific proposals based on the generated cosmetic surgery candidates or fashion items, thereby making it possible to propose optimal cosmetic surgery or fashion items based on the user's detailed wishes and conditions.

[0614] "Input data" refers to data that indicates information about cosmetic surgery or fashion desired by the user.

[0615] "Receiving" refers to the process by which input data is taken in by the system.

[0616] "User" means an individual who utilizes the System to seek cosmetic or fashion item recommendations.

[0617] The "generation means" refers to a processing function that analyzes received input data and generates optimal cosmetic surgery candidates or fashion items.

[0618] The "proposal generation means" refers to a processing function that generates specific proposal content based on the generated cosmetic surgery candidates or fashion items.

[0619] The "display means" refers to a device or function that visually presents the generated proposal content to the user.

[0620] "Standard format" means a format that provides a consistent structure or format for data and allows input data from a user to be sent to a server in a parsable form.

[0621] "Analysis" refers to the process of analyzing the received input data in detail to extract the user's wishes and conditions.

[0622] "Candidate" refers to each of the multiple cosmetic or fashion items selected by the generating means.

[0623] "Information" refers to specific data based on the user's wishes and conditions.

[0624] The term "server" refers to a device or system that performs a series of processes including receiving, analyzing, generating, and displaying input data.

[0625] System program generation

[0626] The system includes a program for recommending optimal cosmetic surgery or fashion items based on the user's preferences and conditions. This program is composed of multiple components, each of which functions in conjunction with the others.

[0627] Hardware and Software

[0628] The system is implemented using the following main hardware and software:

[0629] 1. User terminal (smartphone, smart glasses): A device that allows users to input information and check the results.

[0630] 2. Data Processing Server: A server for receiving input data, converting it into a standard format, and analyzing the data.

[0631] 3. Generative AI module (server): This module contains an AI model for generating specific proposals based on the generated candidates.

[0632] 4. Result display widget (terminal): This is a component for visually displaying the generated suggestions to the user.

[0633] Specific explanation of program processing

[0634] Receiving input data

[0635] Using the interface of a smartphone or smart glasses, a user inputs information about their desired cosmetic surgery or fashion, such as "I like casual style" or "I like the color blue," and this information is sent from the device to a data processing server.

[0636] Receiving data and converting it to a standard format

[0637] The server receives input data sent by the user, converts it into a standard format such as JSON, and makes it ready for analysis.

[0638] Data analysis and generation

[0639] The generative AI module analyzes the data converted into a standard format and generates optimal cosmetic surgery candidates and fashion items based on the user's preferences and conditions, using a pre-trained generative AI model.

[0640] Proposal generation and display

[0641] The generative AI module creates specific recommendations based on the generated candidates, including details of plastic surgery, descriptions of fashion items, benefits, risks, prices, etc. The generated recommendations are sent to the user's device via the data processing server and displayed to the user via the result display widget.

[0642] Examples and prompts

[0643] For example, a user enters the following information:

[0644] Image: Casual

[0645] Favorite color: Blue

[0646] Skeleton:Slender

[0647] Height: 160cm

[0648] Body type: Standard

[0649] Hair color: Black, Eye color: Brown

[0650] Budget: 30,000 yen

[0651] An example prompt is:

[0652] "Please suggest the best fashion items and outfits for a casual image, someone who likes the color blue, is 160cm tall with a slim build, average build, black hair, brown eyes, and a budget of 30,000 yen or less."

[0653] This allows the system to provide optimal proposals in real time based on the user's detailed wishes and conditions.

[0654] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0655] Step 1:

[0656] Users use the interface of their smartphone or smart glasses to input information about their desired cosmetic surgery or fashion. Users input specific preferences and conditions, such as "I like casual styles" or "I like the color blue." This generates input data.

[0657] Step 2:

[0658] The terminal receives data entered by the user and converts it into a standard format such as JSON. The converted data is ready for analysis. The input here is information including the user's wishes and requirements, and the output is data in a standard format that can be analyzed.

[0659] Step 3:

[0660] The server receives input data converted into a standard format, analyzes the received data, and prepares data to generate optimal cosmetic surgery candidates or fashion items based on the user's preferences and conditions. The input is data in a standard format, and the output is the analysis results.

[0661] Step 4:

[0662] The generative AI module uses data provided by the server to generate optimal plastic surgery candidates or fashion items based on a generative AI model. The generated candidates include details of the procedure or item, as well as benefits, risks, and price. The input is the analysis results, and the output is the generated candidate list.

[0663] Step 5:

[0664] The generative AI module generates specific recommendations based on the generated candidate list, including the type of cosmetic surgery, details of fashion items, benefits, risks, required downtime, costs, etc. The input is the generated candidate list, and the output is the specific recommendations.

[0665] Step 6:

[0666] The server sends the specific proposal provided by the generation AI module to the user terminal. The input is the proposal content, and the output is the transmission of the proposal data to the user terminal.

[0667] Step 7:

[0668] The terminal displays the proposals received from the server to the user. The user can then select the cosmetic surgery or fashion item that best suits their needs based on the information obtained. The input is the proposal data from the server, and the output is the proposal displayed to the user.

[0669] This allows users to receive real-time recommendations for the best cosmetic surgery or fashion items based on their detailed wishes and requirements.

[0670] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[0671] This invention is a generative AI system that takes into account the user's emotional state when selecting the cosmetic surgery they desire and proposes the most suitable cosmetic surgery. The system generates and provides optimal cosmetic surgery proposals based on the user's input information.

[0672] System Overview and Operation

[0673] This system is broadly composed of the following five main components:

[0674] 1. User Interface (Terminal)

[0675] 2. Data Processing Server (Server)

[0676] 3. Generative AI module (server)

[0677] 4. Emotion engine (server)

[0678] 5. Result display widget (terminal)

[0679] User Interface (Terminal)

[0680] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[0681] Data Processing Server (Server)

[0682] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences and conditions.

[0683] Generative AI module (server)

[0684] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0685] Emotion engine (server)

[0686] The emotion engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the cosmetic surgery options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[0687] Result display widget (terminal)

[0688] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0689] Explanation of program processing

[0690] The program of this system performs processing in the following procedure.

[0691] 1. Enter your user information

[0692] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[0693] 2. Receiving and converting input data

[0694] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[0695] 3. Data analysis and surgical procedure selection

[0696] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[0697] 4. Emotion Recognition with Emotion Engine

[0698] The emotion engine analyzes the user's emotional state based on input data and past data, recognizing emotions such as anxiety, anticipation, and hope.

[0699] 5. Proposal generation using generative AI

[0700] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and cost, and adjusts the recommendations based on information from the emotion engine.

[0701] 6. Displaying the results

[0702] The terminal displays the proposal received from the server to the user, for example, by displaying an image or a specific explanation.

[0703] Specific examples

[0704] Example of input data

[0705] The user enters the following information:

[0706] Desired image: Pure and gentle

[0707] Celebrity: Mr. A

[0708] Favorite clothing and style: Casual

[0709] Skeleton:Slender

[0710] Facial shape: Round face

[0711] Body type: Standard

[0712] Hair color: Black, Skin color: Fair, Eye color: Brown

[0713] Budget: 500,000 yen

[0714] Downtime: 1 week

[0715] Minor cosmetic surgery: Hope

[0716] Past plastic surgery history: None

[0717] Examples of proposals

[0718] If the emotion engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[0719] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is approximately one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[0720] In this way, the system takes into account the user's emotional state and suggests the most appropriate cosmetic surgery, helping the user make a choice with confidence.

[0721] The processing flow will be explained below.

[0722] Step 1:

[0723] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[0724] Step 2:

[0725] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[0726] Step 3:

[0727] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[0728] Step 4:

[0729] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[0730] Step 5:

[0731] The server's data analysis module analyzes the data received from the user and extracts the user's wishes and requirements. For example, the user's wishes are identified based on the "image they want to achieve," "budget," and "past plastic surgery history."

[0732] Step 6:

[0733] The server's emotion engine analyzes emotions (e.g., anxiety, anticipation, relief, etc.) from the user's input data. This emotion information influences subsequent suggestion generation.

[0734] Step 7:

[0735] The server's generative AI module selects the most suitable plastic surgery candidates based on the analysis results and the output of the emotion engine. For example, if the user is feeling anxious, suggestions including ways to mitigate risks and detailed procedure procedures will be selected.

[0736] Step 8:

[0737] The server generates specific recommendations based on the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, costs, and care information. Based on information from the emotion engine, the recommendation also includes explanations and advice based on the user's emotions.

[0738] Step 9:

[0739] The server formats the generated suggestions into text for the user and sends it to the terminal.

[0740] Step 10:

[0741] The device receives the suggestions from the server and displays them in a user-friendly format, including images and detailed explanations.

[0742] Step 11:

[0743] The user can review the displayed information and decide which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[0744] Through these steps, the system proposes the most appropriate cosmetic surgery procedure while taking into account the user's emotional state, helping the user to make an appropriate choice with peace of mind.

[0745] Example 2

[0746] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0747] Currently, when users select a plastic surgery, it is difficult to obtain optimal suggestions that take into account their emotional state and detailed desired conditions. In particular, if the user has emotional states such as anxiety or anticipation, suggestions that do not take these emotions into account may reduce user satisfaction. Therefore, there is a need for a system that can properly recognize the user's emotional state and suggest the optimal plastic surgery that suits each individual situation.

[0748] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0749] In this invention, the server includes means for receiving input data and collecting information on the treatment desired by the user, means for analyzing the received input data and generating optimal treatment candidates, means for recognizing the emotional state of the user based on the input data, and means for generating specific proposals based on the generated treatment candidates and the emotional state, thereby making it possible to propose optimal treatments while taking the emotional state of the user into consideration.

[0750] "Input data" refers to data that includes information and conditions regarding the treatment desired by the user.

[0751] "Means for receiving" refers to a device or program that has the function of incorporating input data sent by a user into the system.

[0752] The "analyzing means" refers to a device or program that has the function of analyzing information based on received input data and selecting the most suitable treatment options.

[0753] The "generation means" is a device or program that has the function of automatically generating specific treatment candidates that meet the user's wishes based on the analysis results.

[0754] "Emotion recognition means" refers to a device or program that has the function of analyzing user input data and other information to identify the user's emotional state.

[0755] The "proposal generation means" is a device or program that has the function of creating specific proposal content based on the generated treatment candidates and the results of the emotion recognition means.

[0756] The "display means" refers to a device or program that has the function of visually presenting the generated proposal content to the user.

[0757] A "standard format" is a consistent data format required for systems to analyze and process data.

[0758] This invention is a generative AI system that takes into account the emotional state of the user when selecting the desired treatment and makes optimal suggestions. The system analyzes information provided by the user and suggests the optimal treatment for the user.

[0759] System Configuration

[0760] This system is broadly composed of the following five main components:

[0761] 1. User Interface (Terminal)

[0762] 2. Data Processing Server (Server)

[0763] 3. Generative AI module (server)

[0764] 4. Emotion Recognition Engine (Server)

[0765] 5. Result display widget (terminal)

[0766] User Interface (Terminal)

[0767] Users use a terminal to enter their information, including the image they want to resemble, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, downtime, whether they want simple treatment, and past treatment history. After entering this information and clicking the "Submit" button, the data is transferred to the server.

[0768] Data Processing Server (Server)

[0769] The server receives input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects candidate actions based on the user's wishes and conditions.

[0770] Generative AI module (server)

[0771] The generative AI module generates optimal treatment options based on the results of data analysis. This module uses a large database to suggest the best treatment for the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific treatment type, benefits, risks, required downtime, and costs.

[0772] Emotion recognition engine (server)

[0773] The emotion recognition engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the treatment options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[0774] Result display widget (terminal)

[0775] The device receives the recommendations sent from the server and displays them on the user's screen, allowing the user to check detailed information about specific treatments and make the best choice for themselves.

[0776] Specific examples

[0777] Example of input data

[0778] The user enters the following information:

[0779] Desired image: Pure and gentle

[0780] Celebrity: Mr. A

[0781] Favorite clothing and style: Casual

[0782] Skeleton:Slender

[0783] Facial shape: Round face

[0784] Body type: Standard

[0785] Hair color: Black, Skin color: Fair, Eye color: Brown

[0786] Budget: 500,000 yen

[0787] Downtime: 1 week

[0788] Simple Treatment: Hope

[0789] Past treatment history: None

[0790] Examples of proposals

[0791] If the emotion recognition engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[0792] Recommendation: We recommend the "simple double eyelid surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[0793] This system allows users to make choices with confidence, as it suggests the most appropriate treatment that takes into account their emotional state.

[0794] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0795] Step 1: Enter your user information

[0796] The user enters their information using the device's user interface. Specifically, they enter details in fields such as "desired image," "budget," "desired downtime," and "past treatment history," and click the "Submit" button. This action sends the user's input data (in JSON format) from the device to the server.

[0797] Input: User information (desired image, budget, desired downtime, etc.)

[0798] Output: Send input data (JSON format)

[0799] Step 2: Receiving and converting input data

[0800] The device receives the data sent by the user. After receiving the data, the device converts it into the correct format (e.g., JSON format) and forwards it to the server. The server converts the received data into a parsable format and prepares it for data processing.

[0801] Input: User input data (JSON format)

[0802] Output: Data converted into a parsable format

[0803] Step 3: Data analysis and treatment selection

[0804] The server analyzes the received data using the data processing server's analysis module. Based on the user's preferences and conditions (e.g., "round face," "black hair," "budget of 500,000 yen," etc.), it selects the most suitable treatment options. This analysis process uses a large database of past data and treatments to make the best recommendations.

[0805] Input: Data converted into a parsable format

[0806] Output: Candidates for optimal treatment

[0807] Step 4: Recognizing emotions with the emotion recognition engine

[0808] The server uses an emotion recognition engine to analyze the user's emotional state. Specifically, it recognizes emotions such as "anxiety" or "expectation" based on the user's input data and past data. This emotional information is reflected in subsequent suggestions.

[0809] Input: User-entered and historical data

[0810] Output: Information about the user's emotional state

[0811] Step 5: Generative AI generates proposals

[0812] The generative AI module generates specific treatment recommendations based on the server's analysis results and information from the emotion recognition engine. Specifically, it makes detailed recommendations such as "simple double eyelid surgery," "one week of downtime," and "cost: 300,000 yen." If the user is feeling anxious, it makes adjustments based on the user's emotional information, such as adding detailed information about risks and care.

[0813] Input: Optimal treatment options and emotional information

[0814] Output: Specific proposals

[0815] Step 6: View the results

[0816] The terminal displays the proposal received from the server to the user. Specifically, the generated treatment details, benefits, risks, downtime, costs, etc. are displayed on the user interface, allowing the user to review the information and make the best choice for themselves.

[0817] Input: Specific proposal

[0818] Output: Display of proposal

[0819] Through this series of processes, the user is presented with the optimal course of action that takes into account their emotional state, allowing them to make a choice with confidence.

[0820] (Application example 2)

[0821] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the smart glasses 214 will be referred to as a "terminal."

[0822] Conventional security services have the problem that it is difficult for security guards to quickly decide on the appropriate response on the scene, and there is a high possibility that they will make incorrect decisions, especially when psychological factors such as emotions and stress are influential.In addition, because uniform response measures are provided without considering the emotional state of the security guards themselves, there is a need for flexible responses that are appropriate for the situation.

[0823] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery desired by the user, generation means for analyzing the received input data and generating optimal cosmetic surgery candidates, proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates, means for analyzing the emotional states of the security target and security guards using a generation AI and proposing optimal countermeasures, and display means for presenting the generated proposals to the user. This allows optimal countermeasures to be provided in real time based on the situation and emotional state of the scene, enabling security guards to take prompt and appropriate action.

[0824] "Input Data" refers to information about your preferences and circumstances submitted by you.

[0825] "Generation means" refers to the part of the system that analyzes the received input data and generates optimal cosmetic surgery or treatment options based on the user's preferences.

[0826] The "proposal generation means" refers to a part of the system that creates specific proposals based on the candidate cosmetic procedures and countermeasures generated by the generation means.

[0827] "Generative AI" refers to artificial intelligence technology that analyzes large amounts of data to understand a user's wishes and emotional state and make optimal suggestions.

[0828] "Emotional state" refers to the psychological state (e.g., anxiety, stress, relief, etc.) of the user, the person being guarded, and the security guard.

[0829] The "generated proposal content" refers to detailed information about specific cosmetic procedures and countermeasures created by the proposal generation means.

[0830] "Display means" refers to the part of the system that allows the user to visually confirm the generated suggestions.

[0831] System Overview and Operation

[0832] 1. System Components

[0833] The system of the present invention consists of the following major components:

[0834] User Interface (Terminal)

[0835] Data Processing Server

[0836] Generative AI Module

[0837] Emotion Engine

[0838] Result Display Widget

[0839] 2. Hardware and Software Used

[0840] The system uses devices such as smartphones and smart glasses, various servers, analysis libraries, and generative AI models. The specific hardware and software used includes the following:

[0841] Hardware: Smartphones (iOS / Android), smart glasses (Google Glass, Microsoft HoloLens)

[0842] Software: AWS, Google Cloud, Microsoft Azure (data processing servers), MySQL, MongoDB (databases), IBM Watson Emotion Analysis, Microsoft Text Analytics (sentiment analysis library), OpenAI GPT-4, Google BERT (generative AI module)

[0843] 3. Natural Language Description

[0844] User Interface (Terminal)

[0845] Users use their smartphones or smart glasses to input their personal information, the situation at the scene, the condition of the person being guarded, and the guard's own emotions. This information is sent to the server in JSON format through the application.

[0846] Data Processing Server

[0847] The server receives input data in a standard format (JSON) and converts it into a format that can be parsed. Cloud services such as AWS, Google Cloud, and Microsoft Azure are used for data processing. Information is stored in the database using MySQL or MongoDB.

[0848] Generative AI Module

[0849] The generative AI module analyzes the received data and generates optimal countermeasures based on the user's preferences and on-site conditions, using AI models such as OpenAI GPT-4 and Google BERT. This generates recommendations that include details such as the type of specific cosmetic or security countermeasure, its benefits, risks, costs, and required time.

[0850] Emotion Engine

[0851] The emotion engine uses emotion analysis libraries like IBM Watson Emotion Analysis and Microsoft Text Analytics to analyze the user's emotional state from their input data. Based on this analysis, the generative AI module optimizes the suggestions it generates. For example, if a security guard is feeling anxious, the suggestions will take that into account.

[0852] Result Display Widget

[0853] The result display widget displays the generated suggestions on the user's smartphone or smart glasses, allowing the user to review the suggestions and select the appropriate response.

[0854] 4. Examples and prompts

[0855] As a concrete example, suppose the user enters the following information:

[0856] Example of input data

[0857] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[0858] Condition of the guarded person: "Face red and appears very angry."

[0859] Security guard's feelings: "I feel unsafe."

[0860] Specific examples of proposals

[0861] The system receives the above information, and if the emotion engine detects "anxiety," the generative AI makes the following suggestions:

[0862] "We will continue to monitor the situation on site and instruct people to maintain distance from each other to stay safe. If you feel unsafe, please contact security headquarters and report the situation. We will also provide advice on how to stay calm, for example, by taking deep breaths to calm yourself down."

[0863] Example prompts for generative AI models

[0864] Generate optimal responses based on the user's emotional state and on-site conditions.

[0865] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[0866] Condition of the guarded person: "Face red and appears very angry."

[0867] Security guard's feelings: "I feel unsafe."

[0868] In this way, the system helps security guards take prompt and appropriate action by making appropriate suggestions in real time that take into account their emotional state.

[0869] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0870] Step 1:

[0871] The user uses the terminal to input the situation at the scene, the state of the person being guarded, and their own emotions. The input data includes the situation at the scene (e.g., "crowded"), the state of the person being guarded (e.g., "his face is red and he looks very angry"), and the emotions of the security guard (e.g., "he feels anxious"). The user clicks the "Send" button to send the input data to the server.

[0872] Step 2:

[0873] The terminal receives input data sent by the user and converts it into JSON format. The converted data is then transferred to the server. The input data (the situation at the scene, the state of the person being guarded, and the security guard's emotions) is converted into JSON format and sent.

[0874] Step 3:

[0875] The server converts the received JSON formatted input data into a parsable format. Specifically, it processes it so that it can be stored in a database (MySQL, MongoDB). Through this processing, the server obtains a format that can be stored in the database (for example, a structured table format).

[0876] Step 4:

[0877] The server performs data analysis based on the converted input data. The analysis uses the computational resources of cloud services (AWS, Google Cloud, Microsoft Azure), and a generative AI model (OpenAI GPT-4, Google BERT) generates optimal candidate solutions. Based on the input data, solutions are proposed that match the user's wishes and the situation on-site.

[0878] Step 5:

[0879] The emotion engine analyzes the user's emotional state from the input data. This process uses emotion analysis libraries (IBM Watson Emotion Analysis, Microsoft Text Analytics). The emotion engine analyzes the user's input data and obtains the emotional state (e.g., "anxiety").

[0880] Step 6:

[0881] The generative AI module adjusts its suggestions based on the emotional state information obtained from the emotion engine. For example, if a security guard feels "anxious," it will suggest countermeasures with specific instructions to mitigate risk. The generative AI model is used to generate detailed instructions and advice to reassure the user.

[0882] Step 7:

[0883] The server sends the generated proposal to the device, which then displays it on the user's screen. For example, details of appropriate countermeasures and necessary steps are displayed, allowing the user to act accordingly.

[0884] This series of processes allows users to receive optimal countermeasures in real time based on the situation at the scene and their own emotional state.

[0885] The specific processing unit 290 transmits the result of the specific processing to the smart glasses 214. In the smart glasses 214, the control unit 46A causes the speaker 240 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[0886] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[0887] In the above embodiment, an example in which the specific processing is performed by the data processing device 12 has been given, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the smart glasses 214.

[0888] [Third embodiment]

[0889] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[0890] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[0891] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0892] The headset type terminal 314 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a display 343. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the display 343 are also connected to the bus 52.

[0893] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[0894] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[0895] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[0896] Fig. 6 shows an example of the main functions of the data processing device 12 and the headset type terminal 314. As shown in Fig. 6, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[0897] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0898] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[0899] In the headset type terminal 314, a reception output process is performed by the processor 46. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0900] Next, a description will be given of the identification process performed by the identification processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as the "server" and the headset type terminal 314 will be referred to as the "terminal."

[0901] This invention is a generative AI system that helps users select the cosmetic surgery they desire. The system generates and provides optimal cosmetic surgery suggestions based on user input information.

[0902] System Overview and Operation

[0903] This system is broadly composed of the following four main components:

[0904] 1. User Interface (Terminal)

[0905] 2. Data Processing Server (Server)

[0906] 3. Generative AI module (server)

[0907] 4. Result display widget (terminal)

[0908] User Interface (Terminal)

[0909] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[0910] Data Processing Server (Server)

[0911] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0912] Generative AI module (server)

[0913] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[0914] Result display widget (terminal)

[0915] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0916] Explanation of program processing

[0917] The program of this system performs processing in the following procedure.

[0918] 1. Enter your user information

[0919] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[0920] 2. Receiving and converting input data

[0921] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[0922] 3. Data analysis and surgical procedure selection

[0923] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[0924] 4. Proposal generation using generative AI

[0925] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and costs.

[0926] 5. Displaying the results

[0927] The device displays the suggestions received from the server to the user, who can then review the suggestions and choose the cosmetic surgery that best suits their needs.

[0928] Specific examples

[0929] Example of input data

[0930] The user enters the following information:

[0931] Desired image: Pure and gentle

[0932] Celebrity: Mr. A

[0933] Favorite clothing and style: Casual

[0934] Skeleton:Slender

[0935] Facial shape: Round face

[0936] Body type: Standard

[0937] Hair color: Black, Skin color: Fair, Eye color: Brown

[0938] Budget: 500,000 yen

[0939] Downtime: 1 week

[0940] Minor cosmetic surgery: Hope

[0941] Past plastic surgery history: None

[0942] Examples of proposals

[0943] The generative AI generates the following proposal:

[0944] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases, this can be covered with makeup.

[0945] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[0946] The processing flow will be explained below.

[0947] Step 1:

[0948] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[0949] Step 2:

[0950] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[0951] Step 3:

[0952] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[0953] Step 4:

[0954] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[0955] Step 5:

[0956] The server's data analysis module analyzes the data received from the user, extracting the user's preferences and conditions based on, for example, the "image they want to achieve," "budget," and "past plastic surgery history."

[0957] Step 6:

[0958] The server's generation AI module selects candidate cosmetic procedures based on the analysis results, extracting from the database the procedures that best fit the user's budget, downtime, and preferences.

[0959] Step 7:

[0960] The server generates specific recommendations from the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, and costs.

[0961] Step 8:

[0962] The server formats the generated suggestions into text for the user and sends it to the terminal.

[0963] Step 9:

[0964] The device receives the proposal from the server and displays it in a format that is easy for the user to understand, such as an image or a detailed explanation.

[0965] Step 10:

[0966] The user reviews the displayed information and decides which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[0967] Through the above steps, the system will suggest the most suitable cosmetic surgery to the user and help them make a choice with confidence.

[0968] Example 1

[0969] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[0970] In today's world, the demand for cosmetic surgery is on the rise, making it important for users to select the most suitable cosmetic surgery that suits their needs. However, it is not easy for users to find the most suitable cosmetic surgery from the vast amount of information available. In addition, there is a lack of systems that can generate effective suggestions based on users' wishes and conditions. Therefore, there is a need for a system that allows users to easily and accurately receive suggestions for the most suitable cosmetic surgery.

[0971] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[0972] In this invention, the server includes means for a user to input data using a terminal and collect information, means for converting the received input data into a format that the server can analyze, means for the server to analyze the input data and select optimal cosmetic surgery candidates based on the user's wishes and conditions, means for a generation AI module to generate detailed recommendations for optimal cosmetic surgery, and means for the terminal to display the generated recommendations to the user, thereby enabling the user to easily and accurately receive recommendations for the optimal cosmetic surgery.

[0973] "User" refers to an individual who utilizes the System to input information about their desired cosmetic procedure and receive the best possible recommendations.

[0974] "Device" means a computer device, smartphone, tablet, or other device through which a user enters information and / or reviews generated cosmetic surgery recommendations.

[0975] "Server" refers to the central processing unit that analyzes the data received from the User and generates optimal cosmetic surgery recommendations using the generative AI module.

[0976] "Input data" refers to information that users enter into the system, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial shape, body type, hair, skin and eye color, budget, desired downtime, desired minor cosmetic surgery, and past cosmetic surgery history.

[0977] "Parsable format" refers to a standard data format (e.g., JSON) required for the server to process and parse the data correctly.

[0978] "Generative AI module" refers to an artificial intelligence software component that automatically generates detailed recommendations for optimal cosmetic surgery based on input data and the server's analysis results.

[0979] "Recommendations" means the cosmetic surgery recommendations generated by the Generative AI Module, including details such as the type of cosmetic surgery that best suits the User's preferences and requirements, benefits, risks, required downtime, and costs.

[0980] The "display means" is a system component for visually presenting the generated proposal content to the user, and mainly refers to a user interface that operates on a terminal.

[0981] The present invention is a generative AI system that helps users select the cosmetic surgery they desire. The system aims to generate and provide optimal cosmetic surgery suggestions based on user input information.

[0982] System Overview and Operation

[0983] The system consists of four main components:

[0984] 1. User Interface (Terminal)

[0985] 2. Data Processing Server (Server)

[0986] 3. Generative AI module (server)

[0987] 4. Result display widget (terminal)

[0988] User Interface (Terminal)

[0989] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After entering this information and submitting it, the data is transferred to the server.

[0990] Data Processing Server (Server)

[0991] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[0992] Specifically, it uses a web framework such as Python's Flask to receive data sent as an HTTP request, and then analyzes the data using libraries such as Pandas and Scikit-learn.

[0993] Generative AI module (server)

[0994] The generative AI module generates optimal plastic surgery candidates based on the results of data analysis. This module uses a large database to suggest the plastic surgery that best suits the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific type of plastic surgery, its benefits, risks, required downtime, and costs. Generative AI models such as GPT-3 are used.

[0995] Example prompt sentence:

[0996] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[0997] Result display widget (terminal)

[0998] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[0999] For example, the user enters the following information:

[1000] Desired image: Pure and gentle

[1001] Celebrities: Famous people

[1002] Favorite clothing and style: Casual

[1003] Skeleton:Slender

[1004] Facial shape: Round face

[1005] Body type: Standard

[1006] Hair color: Black, Skin color: Fair, Eye color: Brown

[1007] Budget: 500,000 yen

[1008] Downtime: 1 week

[1009] Minor cosmetic surgery: Hope

[1010] Past plastic surgery history: None

[1011] An example of the generated suggestions:

[1012] "I recommend the 'mini-double eyelid surgery' to achieve a neat and gentle look. The downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup."

[1013] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[1014] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1015] Step 1:

[1016] Using the device interface, users enter details about the cosmetic surgery they wish to undergo, including the image they want to achieve, celebrities, preferred clothing and style, bone structure, facial features, body type, hair, skin, and eye color, budget, desired downtime, desired minor cosmetic surgery, and previous cosmetic surgery history. When the user clicks the "Submit" button, the entered data is sent from the device to the server.

[1017] Input: User-entered details about the plastic surgery

[1018] Output: Detailed information about the surgery sent (terminal → server)

[1019] Step 2:

[1020] The terminal receives input data from the user and converts it into a standard format (e.g., JSON format). The converted data is then transferred to the server. By converting the data into the appropriate format, the server can more easily analyze it.

[1021] Specifically, the device structures the user's input data, parses it into JSON format, and sends it to the server as an HTTP request.

[1022] Input: Raw data from the user

[1023] Output: Data converted to JSON format (terminal → server)

[1024] Step 3:

[1025] The server receives the JSON data sent from the device and converts it into a format that can be parsed. An analysis module on the server then analyzes the data and selects the most suitable plastic surgery candidates based on the user's preferences and conditions.

[1026] Specifically, the server receives HTTP requests using a framework such as Python's Flask and analyzes the data using libraries such as Pandas and Scikit-learn.

[1027] Input: Input data in JSON format

[1028] Output: Data converted into a parsable format and optimal cosmetic surgery candidates

[1029] Step 4:

[1030] The generative AI module generates detailed recommendations for the most suitable cosmetic surgery based on the data analyzed on the server. This module uses a large database and a generative AI model (e.g., GPT-3) to generate the recommendations. Based on the prompt, the module automatically generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1031] Specifically, a prompt sentence is input into the generation AI module, and a sentence suggesting the optimal plastic surgery is generated as a response to the prompt.

[1032] Example prompt sentence:

[1033] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[1034] Input: Parsed data and prompt statements

[1035] Output: Detailed plastic surgery proposals generated

[1036] Step 5:

[1037] The device receives the recommendations generated by the server and displays them to the user, allowing the user to review the specific recommendations and make the best choice for themselves. The recommendations include detailed information such as the most suitable type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1038] Specifically, the device visually displays the received information using HTML and CSS. By providing information in an easy-to-understand format for users, decision-making becomes smoother.

[1039] Input: Generated plastic surgery proposal

[1040] Output: Display the suggestion to the user

[1041] (Application example 1)

[1042] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1043] Conventional cosmetic surgery and fashion recommendation systems have struggled to provide optimal recommendations in real time based on a user's detailed wishes and requirements. They also lacked an interactive system that allowed users to efficiently find the items and procedures that best suit them. This meant that users had to spend a great deal of time and effort trying to find their ideal style and procedure.

[1044] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1045] In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery or fashion desired by the user, means for analyzing the received input data and generating optimal cosmetic surgery candidates or fashion items, and means for generating specific proposals based on the generated cosmetic surgery candidates or fashion items, thereby making it possible to propose optimal cosmetic surgery or fashion items based on the user's detailed wishes and conditions.

[1046] "Input data" refers to data that indicates information about cosmetic surgery or fashion desired by the user.

[1047] "Receiving" refers to the process by which input data is taken in by the system.

[1048] "User" means an individual who utilizes the System to seek cosmetic or fashion item recommendations.

[1049] The "generation means" refers to a processing function that analyzes received input data and generates optimal cosmetic surgery candidates or fashion items.

[1050] The "proposal generation means" refers to a processing function that generates specific proposal content based on the generated cosmetic surgery candidates or fashion items.

[1051] The "display means" refers to a device or function that visually presents the generated proposal content to the user.

[1052] "Standard format" means a format that provides a consistent structure or format for data and allows input data from a user to be sent to a server in a parsable form.

[1053] "Analysis" refers to the process of analyzing the received input data in detail to extract the user's wishes and conditions.

[1054] "Candidate" refers to each of the multiple cosmetic or fashion items selected by the generating means.

[1055] "Information" refers to specific data based on the user's wishes and conditions.

[1056] The term "server" refers to a device or system that performs a series of processes including receiving, analyzing, generating, and displaying input data.

[1057] System program generation

[1058] The system includes a program for recommending optimal cosmetic surgery or fashion items based on the user's preferences and conditions. This program is composed of multiple components, each of which functions in conjunction with the others.

[1059] Hardware and Software

[1060] The system is implemented using the following main hardware and software:

[1061] 1. User terminal (smartphone, smart glasses): A device that allows users to input information and check the results.

[1062] 2. Data Processing Server: A server for receiving input data, converting it into a standard format, and analyzing the data.

[1063] 3. Generative AI module (server): This module contains an AI model for generating specific proposals based on the generated candidates.

[1064] 4. Result display widget (terminal): This is a component for visually displaying the generated suggestions to the user.

[1065] Specific explanation of program processing

[1066] Receiving input data

[1067] Using the interface of a smartphone or smart glasses, a user inputs information about their desired cosmetic surgery or fashion, such as "I like casual style" or "I like the color blue," and this information is sent from the device to a data processing server.

[1068] Receiving data and converting it to a standard format

[1069] The server receives input data sent by the user, converts it into a standard format such as JSON, and makes it ready for analysis.

[1070] Data analysis and generation

[1071] The generative AI module analyzes the data converted into a standard format and generates optimal cosmetic surgery candidates and fashion items based on the user's preferences and conditions, using a pre-trained generative AI model.

[1072] Proposal generation and display

[1073] The generative AI module creates specific recommendations based on the generated candidates, including details of plastic surgery, descriptions of fashion items, benefits, risks, prices, etc. The generated recommendations are sent to the user's device via the data processing server and displayed to the user via the result display widget.

[1074] Examples and prompts

[1075] For example, a user enters the following information:

[1076] Image: Casual

[1077] Favorite color: Blue

[1078] Skeleton:Slender

[1079] Height: 160cm

[1080] Body type: Standard

[1081] Hair color: Black, Eye color: Brown

[1082] Budget: 30,000 yen

[1083] An example prompt is:

[1084] "Please suggest the best fashion items and outfits for a casual image, someone who likes the color blue, is 160cm tall with a slim build, average build, black hair, brown eyes, and a budget of 30,000 yen or less."

[1085] This allows the system to provide optimal proposals in real time based on the user's detailed wishes and conditions.

[1086] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1087] Step 1:

[1088] Users use the interface of their smartphone or smart glasses to input information about their desired cosmetic surgery or fashion. Users input specific preferences and conditions, such as "I like casual styles" or "I like the color blue." This generates input data.

[1089] Step 2:

[1090] The terminal receives data entered by the user and converts it into a standard format such as JSON. The converted data is ready for analysis. The input here is information including the user's wishes and requirements, and the output is data in a standard format that can be analyzed.

[1091] Step 3:

[1092] The server receives input data converted into a standard format, analyzes the received data, and prepares data to generate optimal cosmetic surgery candidates or fashion items based on the user's preferences and conditions. The input is data in a standard format, and the output is the analysis results.

[1093] Step 4:

[1094] The generative AI module uses data provided by the server to generate optimal plastic surgery candidates or fashion items based on a generative AI model. The generated candidates include details of the procedure or item, as well as benefits, risks, and price. The input is the analysis results, and the output is the generated candidate list.

[1095] Step 5:

[1096] The generative AI module generates specific recommendations based on the generated candidate list, including the type of cosmetic surgery, details of fashion items, benefits, risks, required downtime, costs, etc. The input is the generated candidate list, and the output is the specific recommendations.

[1097] Step 6:

[1098] The server sends the specific proposal provided by the generation AI module to the user terminal. The input is the proposal content, and the output is the transmission of the proposal data to the user terminal.

[1099] Step 7:

[1100] The terminal displays the proposals received from the server to the user. The user can then select the cosmetic surgery or fashion item that best suits their needs based on the information obtained. The input is the proposal data from the server, and the output is the proposal displayed to the user.

[1101] This allows users to receive real-time recommendations for the best cosmetic surgery or fashion items based on their detailed wishes and requirements.

[1102] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1103] This invention is a generative AI system that takes into account the user's emotional state when selecting the cosmetic surgery they desire and proposes the most suitable cosmetic surgery. The system generates and provides optimal cosmetic surgery proposals based on the user's input information.

[1104] System Overview and Operation

[1105] This system is broadly composed of the following five main components:

[1106] 1. User Interface (Terminal)

[1107] 2. Data Processing Server (Server)

[1108] 3. Generative AI module (server)

[1109] 4. Emotion engine (server)

[1110] 5. Result display widget (terminal)

[1111] User Interface (Terminal)

[1112] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[1113] Data Processing Server (Server)

[1114] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences and conditions.

[1115] Generative AI module (server)

[1116] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1117] Emotion engine (server)

[1118] The emotion engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the cosmetic surgery options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[1119] Result display widget (terminal)

[1120] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[1121] Explanation of program processing

[1122] The program of this system performs processing in the following procedure.

[1123] 1. Enter your user information

[1124] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[1125] 2. Receiving and converting input data

[1126] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[1127] 3. Data analysis and surgical procedure selection

[1128] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[1129] 4. Emotion Recognition with Emotion Engine

[1130] The emotion engine analyzes the user's emotional state based on input data and past data, recognizing emotions such as anxiety, anticipation, and hope.

[1131] 5. Proposal generation using generative AI

[1132] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and cost, and adjusts the recommendations based on information from the emotion engine.

[1133] 6. Displaying the results

[1134] The terminal displays the proposal received from the server to the user, for example, by displaying an image or a specific explanation.

[1135] Specific examples

[1136] Example of input data

[1137] The user enters the following information:

[1138] Desired image: Pure and gentle

[1139] Celebrity: Mr. A

[1140] Favorite clothing and style: Casual

[1141] Skeleton:Slender

[1142] Facial shape: Round face

[1143] Body type: Standard

[1144] Hair color: Black, Skin color: Fair, Eye color: Brown

[1145] Budget: 500,000 yen

[1146] Downtime: 1 week

[1147] Minor cosmetic surgery: Hope

[1148] Past plastic surgery history: None

[1149] Examples of proposals

[1150] If the emotion engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[1151] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is approximately one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[1152] In this way, the system takes into account the user's emotional state and suggests the most appropriate cosmetic surgery, helping the user make a choice with confidence.

[1153] The processing flow will be explained below.

[1154] Step 1:

[1155] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[1156] Step 2:

[1157] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[1158] Step 3:

[1159] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[1160] Step 4:

[1161] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[1162] Step 5:

[1163] The server's data analysis module analyzes the data received from the user and extracts the user's wishes and requirements. For example, the user's wishes are identified based on the "image they want to achieve," "budget," and "past plastic surgery history."

[1164] Step 6:

[1165] The server's emotion engine analyzes emotions (e.g., anxiety, anticipation, relief, etc.) from the user's input data. This emotion information influences subsequent suggestion generation.

[1166] Step 7:

[1167] The server's generative AI module selects the most suitable plastic surgery candidates based on the analysis results and the output of the emotion engine. For example, if the user is feeling anxious, suggestions including ways to mitigate risks and detailed procedure procedures will be selected.

[1168] Step 8:

[1169] The server generates specific recommendations based on the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, costs, and care information. Based on information from the emotion engine, the recommendation also includes explanations and advice based on the user's emotions.

[1170] Step 9:

[1171] The server formats the generated suggestions into text for the user and sends it to the terminal.

[1172] Step 10:

[1173] The device receives the suggestions from the server and displays them in a user-friendly format, including images and detailed explanations.

[1174] Step 11:

[1175] The user can review the displayed information and decide which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[1176] Through these steps, the system proposes the most appropriate cosmetic surgery procedure while taking into account the user's emotional state, helping the user to make an appropriate choice with peace of mind.

[1177] Example 2

[1178] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1179] Currently, when users select a plastic surgery, it is difficult to obtain optimal suggestions that take into account their emotional state and detailed desired conditions. In particular, if the user has emotional states such as anxiety or anticipation, suggestions that do not take these emotions into account may reduce user satisfaction. Therefore, there is a need for a system that can properly recognize the user's emotional state and suggest the optimal plastic surgery that suits each individual situation.

[1180] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1181] In this invention, the server includes means for receiving input data and collecting information on the treatment desired by the user, means for analyzing the received input data and generating optimal treatment candidates, means for recognizing the emotional state of the user based on the input data, and means for generating specific proposals based on the generated treatment candidates and the emotional state, thereby making it possible to propose optimal treatments while taking the emotional state of the user into consideration.

[1182] "Input data" refers to data that includes information and conditions regarding the treatment desired by the user.

[1183] "Means for receiving" refers to a device or program that has the function of incorporating input data sent by a user into the system.

[1184] The "analyzing means" refers to a device or program that has the function of analyzing information based on received input data and selecting the most suitable treatment options.

[1185] The "generation means" is a device or program that has the function of automatically generating specific treatment candidates that meet the user's wishes based on the analysis results.

[1186] "Emotion recognition means" refers to a device or program that has the function of analyzing user input data and other information to identify the user's emotional state.

[1187] The "proposal generation means" is a device or program that has the function of creating specific proposal content based on the generated treatment candidates and the results of the emotion recognition means.

[1188] The "display means" refers to a device or program that has the function of visually presenting the generated proposal content to the user.

[1189] A "standard format" is a consistent data format required for systems to analyze and process data.

[1190] This invention is a generative AI system that takes into account the emotional state of the user when selecting the desired treatment and makes optimal suggestions. The system analyzes information provided by the user and suggests the optimal treatment for the user.

[1191] System Configuration

[1192] This system is broadly composed of the following five main components:

[1193] 1. User Interface (Terminal)

[1194] 2. Data Processing Server (Server)

[1195] 3. Generative AI module (server)

[1196] 4. Emotion Recognition Engine (Server)

[1197] 5. Result display widget (terminal)

[1198] User Interface (Terminal)

[1199] Users use a terminal to enter their information, including the image they want to resemble, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, downtime, whether they want simple treatment, and past treatment history. After entering this information and clicking the "Submit" button, the data is transferred to the server.

[1200] Data Processing Server (Server)

[1201] The server receives input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects candidate actions based on the user's wishes and conditions.

[1202] Generative AI module (server)

[1203] The generative AI module generates optimal treatment options based on the results of data analysis. This module uses a large database to suggest the best treatment for the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific treatment type, benefits, risks, required downtime, and costs.

[1204] Emotion recognition engine (server)

[1205] The emotion recognition engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the treatment options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[1206] Result display widget (terminal)

[1207] The device receives the recommendations sent from the server and displays them on the user's screen, allowing the user to check detailed information about specific treatments and make the best choice for themselves.

[1208] Specific examples

[1209] Example of input data

[1210] The user enters the following information:

[1211] Desired image: Pure and gentle

[1212] Celebrity: Mr. A

[1213] Favorite clothing and style: Casual

[1214] Skeleton:Slender

[1215] Facial shape: Round face

[1216] Body type: Standard

[1217] Hair color: Black, Skin color: Fair, Eye color: Brown

[1218] Budget: 500,000 yen

[1219] Downtime: 1 week

[1220] Simple Treatment: Hope

[1221] Past treatment history: None

[1222] Examples of proposals

[1223] If the emotion recognition engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[1224] Recommendation: We recommend the "simple double eyelid surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[1225] This system allows users to make choices with confidence, as it suggests the most appropriate treatment that takes into account their emotional state.

[1226] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1227] Step 1: Enter your user information

[1228] The user enters their information using the device's user interface. Specifically, they enter details in fields such as "desired image," "budget," "desired downtime," and "past treatment history," and click the "Submit" button. This action sends the user's input data (in JSON format) from the device to the server.

[1229] Input: User information (desired image, budget, desired downtime, etc.)

[1230] Output: Send input data (JSON format)

[1231] Step 2: Receiving and converting input data

[1232] The device receives the data sent by the user. After receiving the data, the device converts it into the correct format (e.g., JSON format) and forwards it to the server. The server converts the received data into a parsable format and prepares it for data processing.

[1233] Input: User input data (JSON format)

[1234] Output: Data converted into a parsable format

[1235] Step 3: Data analysis and treatment selection

[1236] The server analyzes the received data using the data processing server's analysis module. Based on the user's preferences and conditions (e.g., "round face," "black hair," "budget of 500,000 yen," etc.), it selects the most suitable treatment options. This analysis process uses a large database of past data and treatments to make the best recommendations.

[1237] Input: Data converted into a parsable format

[1238] Output: Candidates for optimal treatment

[1239] Step 4: Recognizing emotions with the emotion recognition engine

[1240] The server uses an emotion recognition engine to analyze the user's emotional state. Specifically, it recognizes emotions such as "anxiety" or "expectation" based on the user's input data and past data. This emotional information is reflected in subsequent suggestions.

[1241] Input: User-entered and historical data

[1242] Output: Information about the user's emotional state

[1243] Step 5: Generative AI generates proposals

[1244] The generative AI module generates specific treatment recommendations based on the server's analysis results and information from the emotion recognition engine. Specifically, it makes detailed recommendations such as "simple double eyelid surgery," "one week of downtime," and "cost: 300,000 yen." If the user is feeling anxious, it makes adjustments based on the user's emotional information, such as adding detailed information about risks and care.

[1245] Input: Optimal treatment options and emotional information

[1246] Output: Specific proposals

[1247] Step 6: View the results

[1248] The terminal displays the proposal received from the server to the user. Specifically, the generated treatment details, benefits, risks, downtime, costs, etc. are displayed on the user interface, allowing the user to review the information and make the best choice for themselves.

[1249] Input: Specific proposal

[1250] Output: Display of proposal

[1251] Through this series of processes, the user is presented with the optimal course of action that takes into account their emotional state, allowing them to make a choice with confidence.

[1252] (Application example 2)

[1253] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the headset type terminal 314 will be referred to as a "terminal."

[1254] Conventional security services have the problem that it is difficult for security guards to quickly decide on the appropriate response on the scene, and there is a high possibility that they will make incorrect decisions, especially when psychological factors such as emotions and stress are influential.In addition, because uniform response measures are provided without considering the emotional state of the security guards themselves, there is a need for flexible responses that are appropriate for the situation.

[1255] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery desired by the user, generation means for analyzing the received input data and generating optimal cosmetic surgery candidates, proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates, means for analyzing the emotional states of the security target and security guards using a generation AI and proposing optimal countermeasures, and display means for presenting the generated proposals to the user. This allows optimal countermeasures to be provided in real time based on the situation and emotional state of the scene, enabling security guards to take prompt and appropriate action.

[1256] "Input Data" refers to information about your preferences and circumstances submitted by you.

[1257] "Generation means" refers to the part of the system that analyzes the received input data and generates optimal cosmetic surgery or treatment options based on the user's preferences.

[1258] The "proposal generation means" refers to a part of the system that creates specific proposals based on the candidate cosmetic procedures and countermeasures generated by the generation means.

[1259] "Generative AI" refers to artificial intelligence technology that analyzes large amounts of data to understand a user's wishes and emotional state and make optimal suggestions.

[1260] "Emotional state" refers to the psychological state (e.g., anxiety, stress, relief, etc.) of the user, the person being guarded, and the security guard.

[1261] The "generated proposal content" refers to detailed information about specific cosmetic procedures and countermeasures created by the proposal generation means.

[1262] "Display means" refers to the part of the system that allows the user to visually confirm the generated suggestions.

[1263] System Overview and Operation

[1264] 1. System Components

[1265] The system of the present invention consists of the following major components:

[1266] User Interface (Terminal)

[1267] Data Processing Server

[1268] Generative AI Module

[1269] Emotion Engine

[1270] Result Display Widget

[1271] 2. Hardware and Software Used

[1272] The system uses devices such as smartphones and smart glasses, various servers, analysis libraries, and generative AI models. The specific hardware and software used includes the following:

[1273] Hardware: Smartphones (iOS / Android), smart glasses (Google Glass, Microsoft HoloLens)

[1274] Software: AWS, Google Cloud, Microsoft Azure (data processing servers), MySQL, MongoDB (databases), IBM Watson Emotion Analysis, Microsoft Text Analytics (sentiment analysis library), OpenAI GPT-4, Google BERT (generative AI module)

[1275] 3. Natural Language Description

[1276] User Interface (Terminal)

[1277] Users use their smartphones or smart glasses to input their personal information, the situation at the scene, the condition of the person being guarded, and the guard's own emotions. This information is sent to the server in JSON format through the application.

[1278] Data Processing Server

[1279] The server receives input data in a standard format (JSON) and converts it into a format that can be parsed. Cloud services such as AWS, Google Cloud, and Microsoft Azure are used for data processing. Information is stored in the database using MySQL or MongoDB.

[1280] Generative AI Module

[1281] The generative AI module analyzes the received data and generates optimal countermeasures based on the user's preferences and on-site conditions, using AI models such as OpenAI GPT-4 and Google BERT. This generates recommendations that include details such as the type of specific cosmetic or security countermeasure, its benefits, risks, costs, and required time.

[1282] Emotion Engine

[1283] The emotion engine uses emotion analysis libraries like IBM Watson Emotion Analysis and Microsoft Text Analytics to analyze the user's emotional state from their input data. Based on this analysis, the generative AI module optimizes the suggestions it generates. For example, if a security guard is feeling anxious, the suggestions will take that into account.

[1284] Result Display Widget

[1285] The result display widget displays the generated suggestions on the user's smartphone or smart glasses, allowing the user to review the suggestions and select the appropriate response.

[1286] 4. Examples and prompts

[1287] As a concrete example, suppose the user enters the following information:

[1288] Example of input data

[1289] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[1290] Condition of the guarded person: "Face red and appears very angry."

[1291] Security guard's feelings: "I feel unsafe."

[1292] Specific examples of proposals

[1293] The system receives the above information, and if the emotion engine detects "anxiety," the generative AI makes the following suggestions:

[1294] "We will continue to monitor the situation on site and instruct people to maintain distance from each other to stay safe. If you feel unsafe, please contact security headquarters and report the situation. We will also provide advice on how to stay calm, for example, by taking deep breaths to calm yourself down."

[1295] Example prompts for generative AI models

[1296] Generate optimal responses based on the user's emotional state and on-site conditions.

[1297] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[1298] Condition of the guarded person: "Face red and appears very angry."

[1299] Security guard's feelings: "I feel unsafe."

[1300] In this way, the system helps security guards take prompt and appropriate action by making appropriate suggestions in real time that take into account their emotional state.

[1301] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1302] Step 1:

[1303] The user uses the terminal to input the situation at the scene, the state of the person being guarded, and their own emotions. The input data includes the situation at the scene (e.g., "crowded"), the state of the person being guarded (e.g., "his face is red and he looks very angry"), and the emotions of the security guard (e.g., "he feels anxious"). The user clicks the "Send" button to send the input data to the server.

[1304] Step 2:

[1305] The terminal receives input data sent by the user and converts it into JSON format. The converted data is then transferred to the server. The input data (the situation at the scene, the state of the person being guarded, and the security guard's emotions) is converted into JSON format and sent.

[1306] Step 3:

[1307] The server converts the received JSON formatted input data into a parsable format. Specifically, it processes it so that it can be stored in a database (MySQL, MongoDB). Through this processing, the server obtains a format that can be stored in the database (for example, a structured table format).

[1308] Step 4:

[1309] The server performs data analysis based on the converted input data. The analysis uses the computational resources of cloud services (AWS, Google Cloud, Microsoft Azure), and a generative AI model (OpenAI GPT-4, Google BERT) generates optimal candidate solutions. Based on the input data, solutions are proposed that match the user's wishes and the situation on-site.

[1310] Step 5:

[1311] The emotion engine analyzes the user's emotional state from the input data. This process uses emotion analysis libraries (IBM Watson Emotion Analysis, Microsoft Text Analytics). The emotion engine analyzes the user's input data and obtains the emotional state (e.g., "anxiety").

[1312] Step 6:

[1313] The generative AI module adjusts its suggestions based on the emotional state information obtained from the emotion engine. For example, if a security guard feels "anxious," it will suggest countermeasures with specific instructions to mitigate risk. The generative AI model is used to generate detailed instructions and advice to reassure the user.

[1314] Step 7:

[1315] The server sends the generated proposal to the device, which then displays it on the user's screen. For example, details of appropriate countermeasures and necessary steps are displayed, allowing the user to act accordingly.

[1316] This series of processes allows users to receive optimal countermeasures in real time based on the situation at the scene and their own emotional state.

[1317] The specific processing unit 290 transmits the result of the specific processing to the headset type terminal 314. In the headset type terminal 314, the control unit 46A causes the speaker 240 and the display 343 to output the result of the specific processing. The microphone 238 acquires audio indicating a user input regarding the result of the specific processing. The control unit 46A transmits audio data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the audio data.

[1318] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1319] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the headset type terminal 314.

[1320] [Fourth embodiment]

[1321] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1322] 7, a data processing system 410 includes a data processing device 12 and a robot 414. An example of the data processing device 12 is a server.

[1323] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[1324] The robot 414 includes a computer 36, a microphone 238, a speaker 240, a camera 42, a communication I / F 44, and a control target 443. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The microphone 238, the speaker 240, the camera 42, and the control target 443 are also connected to the bus 52.

[1325] The microphone 238 receives instructions and the like from the user 20 by receiving voice uttered by the user 20. The microphone 238 captures the voice uttered by the user 20, converts the captured voice into audio data, and outputs it to the processor 46. The speaker 240 outputs audio in accordance with instructions from the processor 46.

[1326] Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor, and captures images of the surroundings of user 20 (for example, an imaging range defined by an angle of view equivalent to the field of vision of a typical healthy person).

[1327] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 are responsible for the exchange of various information between the processor 46 and the processor 28 via the network 54. The exchange of various information between the processor 46 and the processor 28 using the communication I / Fs 44 and 26 is carried out in a secure state.

[1328] The control object 443 includes a display device, LEDs in the eyes, and motors for driving the arms, hands, and feet. The posture and gestures of the robot 414 are controlled by controlling the motors of the arms, hands, and feet. Some of the emotions of the robot 414 can be expressed by controlling these motors. In addition, the facial expressions of the robot 414 can also be expressed by controlling the light emission state of the LEDs in the eyes of the robot 414.

[1329] Fig. 8 shows an example of the main functions of the data processing device 12 and the robot 414. As shown in Fig. 8, in the data processing device 12, a specific process is performed by the processor 28. A specific process program 56 is stored in the storage 32.

[1330] The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific processing is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[1331] The storage 32 stores a data generation model 58 and an emotion identification model 59. The data generation model 58 and the emotion identification model 59 are used by the identification processing unit 290.

[1332] In the robot 414, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[1333] Next, a description will be given of the specific processing performed by the specific processing unit 290 of the data processing device 12. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1334] This invention is a generative AI system that helps users select the cosmetic surgery they desire. The system generates and provides optimal cosmetic surgery suggestions based on user input information.

[1335] System Overview and Operation

[1336] This system is broadly composed of the following four main components:

[1337] 1. User Interface (Terminal)

[1338] 2. Data Processing Server (Server)

[1339] 3. Generative AI module (server)

[1340] 4. Result display widget (terminal)

[1341] User Interface (Terminal)

[1342] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[1343] Data Processing Server (Server)

[1344] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[1345] Generative AI module (server)

[1346] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1347] Result display widget (terminal)

[1348] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[1349] Explanation of program processing

[1350] The program of this system performs processing in the following procedure.

[1351] 1. Enter your user information

[1352] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[1353] 2. Receiving and converting input data

[1354] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[1355] 3. Data analysis and surgical procedure selection

[1356] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[1357] 4. Proposal generation using generative AI

[1358] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and costs.

[1359] 5. Displaying the results

[1360] The device displays the suggestions received from the server to the user, who can then review the suggestions and choose the cosmetic surgery that best suits their needs.

[1361] Specific examples

[1362] Example of input data

[1363] The user enters the following information:

[1364] Desired image: Pure and gentle

[1365] Celebrity: Mr. A

[1366] Favorite clothing and style: Casual

[1367] Skeleton:Slender

[1368] Facial shape: Round face

[1369] Body type: Standard

[1370] Hair color: Black, Skin color: Fair, Eye color: Brown

[1371] Budget: 500,000 yen

[1372] Downtime: 1 week

[1373] Minor cosmetic surgery: Hope

[1374] Past plastic surgery history: None

[1375] Examples of proposals

[1376] The generative AI generates the following proposal:

[1377] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases, this can be covered with makeup.

[1378] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[1379] The processing flow will be explained below.

[1380] Step 1:

[1381] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[1382] Step 2:

[1383] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[1384] Step 3:

[1385] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[1386] Step 4:

[1387] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[1388] Step 5:

[1389] The server's data analysis module analyzes the data received from the user, extracting the user's preferences and conditions based on, for example, the "image they want to achieve," "budget," and "past plastic surgery history."

[1390] Step 6:

[1391] The server's generation AI module selects candidate cosmetic procedures based on the analysis results, extracting from the database the procedures that best fit the user's budget, downtime, and preferences.

[1392] Step 7:

[1393] The server generates specific recommendations from the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, and costs.

[1394] Step 8:

[1395] The server formats the generated suggestions into text for the user and sends it to the terminal.

[1396] Step 9:

[1397] The device receives the proposal from the server and displays it in a format that is easy for the user to understand, such as an image or a detailed explanation.

[1398] Step 10:

[1399] The user reviews the displayed information and decides which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[1400] Through the above steps, the system will suggest the most suitable cosmetic surgery to the user and help them make a choice with confidence.

[1401] Example 1

[1402] Next, a description will be given of Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1403] In today's world, the demand for cosmetic surgery is on the rise, making it important for users to select the most suitable cosmetic surgery that suits their needs. However, it is not easy for users to find the most suitable cosmetic surgery from the vast amount of information available. In addition, there is a lack of systems that can generate effective suggestions based on users' wishes and conditions. Therefore, there is a need for a system that allows users to easily and accurately receive suggestions for the most suitable cosmetic surgery.

[1404] The specific processing by the specific processing unit 290 of the data processing device 12 in the first embodiment is realized by the following means.

[1405] In this invention, the server includes means for a user to input data using a terminal and collect information, means for converting the received input data into a format that the server can analyze, means for the server to analyze the input data and select optimal cosmetic surgery candidates based on the user's wishes and conditions, means for a generation AI module to generate detailed recommendations for optimal cosmetic surgery, and means for the terminal to display the generated recommendations to the user, thereby enabling the user to easily and accurately receive recommendations for the optimal cosmetic surgery.

[1406] "User" refers to an individual who utilizes the System to input information about their desired cosmetic procedure and receive the best possible recommendations.

[1407] "Device" means a computer device, smartphone, tablet, or other device through which a user enters information and / or reviews generated cosmetic surgery recommendations.

[1408] "Server" refers to the central processing unit that analyzes the data received from the User and generates optimal cosmetic surgery recommendations using the generative AI module.

[1409] "Input data" refers to information that users enter into the system, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial shape, body type, hair, skin and eye color, budget, desired downtime, desired minor cosmetic surgery, and past cosmetic surgery history.

[1410] "Parsable format" refers to a standard data format (e.g., JSON) required for the server to process and parse the data correctly.

[1411] "Generative AI module" refers to an artificial intelligence software component that automatically generates detailed recommendations for optimal cosmetic surgery based on input data and the server's analysis results.

[1412] "Recommendations" means the cosmetic surgery recommendations generated by the Generative AI Module, including details such as the type of cosmetic surgery that best suits the User's preferences and requirements, benefits, risks, required downtime, and costs.

[1413] The "display means" is a system component for visually presenting the generated proposal content to the user, and mainly refers to a user interface that operates on a terminal.

[1414] The present invention is a generative AI system that helps users select the cosmetic surgery they desire. The system aims to generate and provide optimal cosmetic surgery suggestions based on user input information.

[1415] System Overview and Operation

[1416] The system consists of four main components:

[1417] 1. User Interface (Terminal)

[1418] 2. Data Processing Server (Server)

[1419] 3. Generative AI module (server)

[1420] 4. Result display widget (terminal)

[1421] User Interface (Terminal)

[1422] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After entering this information and submitting it, the data is transferred to the server.

[1423] Data Processing Server (Server)

[1424] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences.

[1425] Specifically, it uses a web framework such as Python's Flask to receive data sent as an HTTP request, and then analyzes the data using libraries such as Pandas and Scikit-learn.

[1426] Generative AI module (server)

[1427] The generative AI module generates optimal plastic surgery candidates based on the results of data analysis. This module uses a large database to suggest the plastic surgery that best suits the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific type of plastic surgery, its benefits, risks, required downtime, and costs. Generative AI models such as GPT-3 are used.

[1428] Example prompt sentence:

[1429] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[1430] Result display widget (terminal)

[1431] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[1432] For example, the user enters the following information:

[1433] Desired image: Pure and gentle

[1434] Celebrities: Famous people

[1435] Favorite clothing and style: Casual

[1436] Skeleton:Slender

[1437] Facial shape: Round face

[1438] Body type: Standard

[1439] Hair color: Black, Skin color: Fair, Eye color: Brown

[1440] Budget: 500,000 yen

[1441] Downtime: 1 week

[1442] Minor cosmetic surgery: Hope

[1443] Past plastic surgery history: None

[1444] An example of the generated suggestions:

[1445] "I recommend the 'mini-double eyelid surgery' to achieve a neat and gentle look. The downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup."

[1446] In this way, the system can optimally suggest the cosmetic surgery desired by the user and assist the user in making a selection.

[1447] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1448] Step 1:

[1449] Using the device interface, users enter details about the cosmetic surgery they wish to undergo, including the image they want to achieve, celebrities, preferred clothing and style, bone structure, facial features, body type, hair, skin, and eye color, budget, desired downtime, desired minor cosmetic surgery, and previous cosmetic surgery history. When the user clicks the "Submit" button, the entered data is sent from the device to the server.

[1450] Input: User-entered details about the plastic surgery

[1451] Output: Detailed information about the surgery sent (terminal → server)

[1452] Step 2:

[1453] The terminal receives input data from the user and converts it into a standard format (e.g., JSON format). The converted data is then transferred to the server. By converting the data into the appropriate format, the server can more easily analyze it.

[1454] Specifically, the device structures the user's input data, parses it into JSON format, and sends it to the server as an HTTP request.

[1455] Input: Raw data from the user

[1456] Output: Data converted to JSON format (terminal → server)

[1457] Step 3:

[1458] The server receives the JSON data sent from the device and converts it into a format that can be parsed. An analysis module on the server then analyzes the data and selects the most suitable plastic surgery candidates based on the user's preferences and conditions.

[1459] Specifically, the server receives HTTP requests using a framework such as Python's Flask and analyzes the data using libraries such as Pandas and Scikit-learn.

[1460] Input: Input data in JSON format

[1461] Output: Data converted into a parsable format and optimal cosmetic surgery candidates

[1462] Step 4:

[1463] The generative AI module generates detailed recommendations for the most suitable cosmetic surgery based on the data analyzed on the server. This module uses a large database and a generative AI model (e.g., GPT-3) to generate the recommendations. Based on the prompt, the module automatically generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1464] Specifically, a prompt sentence is input into the generation AI module, and a sentence suggesting the optimal plastic surgery is generated as a response to the prompt.

[1465] Example prompt sentence:

[1466] "If the user wants a clean and gentle image, please suggest the best plastic surgery."

[1467] Input: Parsed data and prompt statements

[1468] Output: Detailed plastic surgery proposals generated

[1469] Step 5:

[1470] The device receives the recommendations generated by the server and displays them to the user, allowing the user to review the specific recommendations and make the best choice for themselves. The recommendations include detailed information such as the most suitable type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1471] Specifically, the device visually displays the received information using HTML and CSS. By providing information in an easy-to-understand format for users, decision-making becomes smoother.

[1472] Input: Generated plastic surgery proposal

[1473] Output: Display the suggestion to the user

[1474] (Application example 1)

[1475] Next, a description will be given of Application Example 1. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1476] Conventional cosmetic surgery and fashion recommendation systems have struggled to provide optimal recommendations in real time based on a user's detailed wishes and requirements. They also lacked an interactive system that allowed users to efficiently find the items and procedures that best suit them. This meant that users had to spend a great deal of time and effort trying to find their ideal style and procedure.

[1477] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 1 is realized by the following means.

[1478] In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery or fashion desired by the user, means for analyzing the received input data and generating optimal cosmetic surgery candidates or fashion items, and means for generating specific proposals based on the generated cosmetic surgery candidates or fashion items, thereby making it possible to propose optimal cosmetic surgery or fashion items based on the user's detailed wishes and conditions.

[1479] "Input data" refers to data that indicates information about cosmetic surgery or fashion desired by the user.

[1480] "Receiving" refers to the process by which input data is taken in by the system.

[1481] "User" means an individual who utilizes the System to seek cosmetic or fashion item recommendations.

[1482] The "generation means" refers to a processing function that analyzes received input data and generates optimal cosmetic surgery candidates or fashion items.

[1483] The "proposal generation means" refers to a processing function that generates specific proposal content based on the generated cosmetic surgery candidates or fashion items.

[1484] The "display means" refers to a device or function that visually presents the generated proposal content to the user.

[1485] "Standard format" means a format that provides a consistent structure or format for data and allows input data from a user to be sent to a server in a parsable form.

[1486] "Analysis" refers to the process of analyzing the received input data in detail to extract the user's wishes and conditions.

[1487] "Candidate" refers to each of the multiple cosmetic or fashion items selected by the generating means.

[1488] "Information" refers to specific data based on the user's wishes and conditions.

[1489] The term "server" refers to a device or system that performs a series of processes including receiving, analyzing, generating, and displaying input data.

[1490] System program generation

[1491] The system includes a program for recommending optimal cosmetic surgery or fashion items based on the user's preferences and conditions. This program is composed of multiple components, each of which functions in conjunction with the others.

[1492] Hardware and Software

[1493] The system is implemented using the following main hardware and software:

[1494] 1. User terminal (smartphone, smart glasses): A device that allows users to input information and check the results.

[1495] 2. Data Processing Server: A server for receiving input data, converting it into a standard format, and analyzing the data.

[1496] 3. Generative AI module (server): This module contains an AI model for generating specific proposals based on the generated candidates.

[1497] 4. Result display widget (terminal): This is a component for visually displaying the generated suggestions to the user.

[1498] Specific explanation of program processing

[1499] Receiving input data

[1500] Using the interface of a smartphone or smart glasses, a user inputs information about their desired cosmetic surgery or fashion, such as "I like casual style" or "I like the color blue," and this information is sent from the device to a data processing server.

[1501] Receiving data and converting it to a standard format

[1502] The server receives input data sent by the user, converts it into a standard format such as JSON, and makes it ready for analysis.

[1503] Data analysis and generation

[1504] The generative AI module analyzes the data converted into a standard format and generates optimal cosmetic surgery candidates and fashion items based on the user's preferences and conditions, using a pre-trained generative AI model.

[1505] Proposal generation and display

[1506] The generative AI module creates specific recommendations based on the generated candidates, including details of plastic surgery, descriptions of fashion items, benefits, risks, prices, etc. The generated recommendations are sent to the user's device via the data processing server and displayed to the user via the result display widget.

[1507] Examples and prompts

[1508] For example, a user enters the following information:

[1509] Image: Casual

[1510] Favorite color: Blue

[1511] Skeleton:Slender

[1512] Height: 160cm

[1513] Body type: Standard

[1514] Hair color: Black, Eye color: Brown

[1515] Budget: 30,000 yen

[1516] An example prompt is:

[1517] "Please suggest the best fashion items and outfits for a casual image, someone who likes the color blue, is 160cm tall with a slim build, average build, black hair, brown eyes, and a budget of 30,000 yen or less."

[1518] This allows the system to provide optimal proposals in real time based on the user's detailed wishes and conditions.

[1519] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1520] Step 1:

[1521] Users use the interface of their smartphone or smart glasses to input information about their desired cosmetic surgery or fashion. Users input specific preferences and conditions, such as "I like casual styles" or "I like the color blue." This generates input data.

[1522] Step 2:

[1523] The terminal receives data entered by the user and converts it into a standard format such as JSON. The converted data is ready for analysis. The input here is information including the user's wishes and requirements, and the output is data in a standard format that can be analyzed.

[1524] Step 3:

[1525] The server receives input data converted into a standard format, analyzes the received data, and prepares data to generate optimal cosmetic surgery candidates or fashion items based on the user's preferences and conditions. The input is data in a standard format, and the output is the analysis results.

[1526] Step 4:

[1527] The generative AI module uses data provided by the server to generate optimal plastic surgery candidates or fashion items based on a generative AI model. The generated candidates include details of the procedure or item, as well as benefits, risks, and price. The input is the analysis results, and the output is the generated candidate list.

[1528] Step 5:

[1529] The generative AI module generates specific recommendations based on the generated candidate list, including the type of cosmetic surgery, details of fashion items, benefits, risks, required downtime, costs, etc. The input is the generated candidate list, and the output is the specific recommendations.

[1530] Step 6:

[1531] The server sends the specific proposal provided by the generation AI module to the user terminal. The input is the proposal content, and the output is the transmission of the proposal data to the user terminal.

[1532] Step 7:

[1533] The terminal displays the proposals received from the server to the user. The user can then select the cosmetic surgery or fashion item that best suits their needs based on the information obtained. The input is the proposal data from the server, and the output is the proposal displayed to the user.

[1534] This allows users to receive real-time recommendations for the best cosmetic surgery or fashion items based on their detailed wishes and requirements.

[1535] Furthermore, an emotion engine that estimates the user's emotion may be further combined. That is, the identification processing unit 290 may estimate the user's emotion using the emotion identification model 59, and perform identification processing using the user's emotion.

[1536] This invention is a generative AI system that takes into account the user's emotional state when selecting the cosmetic surgery they desire and proposes the most suitable cosmetic surgery. The system generates and provides optimal cosmetic surgery proposals based on the user's input information.

[1537] System Overview and Operation

[1538] This system is broadly composed of the following five main components:

[1539] 1. User Interface (Terminal)

[1540] 2. Data Processing Server (Server)

[1541] 3. Generative AI module (server)

[1542] 4. Emotion engine (server)

[1543] 5. Result display widget (terminal)

[1544] User Interface (Terminal)

[1545] Users use a terminal to input their information, including the image they want to achieve, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history. After inputting this information, the data is sent and transferred to the server.

[1546] Data Processing Server (Server)

[1547] The server receives the input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects plastic surgery candidates based on the user's preferences and conditions.

[1548] Generative AI module (server)

[1549] The Generative AI module generates optimal cosmetic surgery candidates based on the results of data analysis. This module uses a large database to suggest the most suitable cosmetic surgery for the user's desired conditions. The Generative AI generates recommendations that include detailed information such as the specific type of cosmetic surgery, its benefits, risks, required downtime, and costs.

[1550] Emotion engine (server)

[1551] The emotion engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the cosmetic surgery options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[1552] Result display widget (terminal)

[1553] The device receives the suggestions sent from the server and displays them on the user's screen, allowing the user to view detailed information about specific cosmetic procedures and make the best choice for themselves.

[1554] Explanation of program processing

[1555] The program of this system performs processing in the following procedure.

[1556] 1. Enter your user information

[1557] Using the device interface, users enter information, including their name and details of the cosmetic procedure they wish to undergo. When the user clicks the "Submit" button, the data is sent to the server.

[1558] 2. Receiving and converting input data

[1559] The device receives input data in the correct format (e.g. JSON) and forwards it to the server, which receives the data and converts it into a parseable format.

[1560] 3. Data analysis and surgical procedure selection

[1561] The server analyzes the received data and selects the most suitable plastic surgery based on the user's information, taking into account factors such as the user's facial shape, desired style, and budget.

[1562] 4. Emotion Recognition with Emotion Engine

[1563] The emotion engine analyzes the user's emotional state based on input data and past data, recognizing emotions such as anxiety, anticipation, and hope.

[1564] 5. Proposal generation using generative AI

[1565] The generative AI module generates detailed recommendations for the selected cosmetic procedure, including the type of procedure, benefits, risks, required downtime, and cost, and adjusts the recommendations based on information from the emotion engine.

[1566] 6. Displaying the results

[1567] The terminal displays the proposal received from the server to the user, for example, by displaying an image or a specific explanation.

[1568] Specific examples

[1569] Example of input data

[1570] The user enters the following information:

[1571] Desired image: Pure and gentle

[1572] Celebrity: Mr. A

[1573] Favorite clothing and style: Casual

[1574] Skeleton:Slender

[1575] Facial shape: Round face

[1576] Body type: Standard

[1577] Hair color: Black, Skin color: Fair, Eye color: Brown

[1578] Budget: 500,000 yen

[1579] Downtime: 1 week

[1580] Minor cosmetic surgery: Hope

[1581] Past plastic surgery history: None

[1582] Examples of proposals

[1583] If the emotion engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[1584] Recommendation: We recommend the "Mini Double Eyelid Surgery" to achieve a neat and gentle look. Downtime is approximately one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[1585] In this way, the system takes into account the user's emotional state and suggests the most appropriate cosmetic surgery, helping the user make a choice with confidence.

[1586] The processing flow will be explained below.

[1587] Step 1:

[1588] Users enter their information into an input form on the device, including the image they want to achieve, celebrity, favorite clothing and style, bone structure, facial shape, body type, hair, skin, and eye color, budget, required downtime, whether they wish to have minor cosmetic surgery, and past cosmetic surgery history.

[1589] Step 2:

[1590] The user clicks the "Submit" button and the input data is sent from the terminal to the server.

[1591] Step 3:

[1592] The device converts the received user input data into the correct format (e.g., JSON format) and forwards it to the server.

[1593] Step 4:

[1594] The server receives the input data and prepares it for passing to the data analysis module, where data integrity checks and formatting checks are performed.

[1595] Step 5:

[1596] The server's data analysis module analyzes the data received from the user and extracts the user's wishes and requirements. For example, the user's wishes are identified based on the "image they want to achieve," "budget," and "past plastic surgery history."

[1597] Step 6:

[1598] The server's emotion engine analyzes emotions (e.g., anxiety, anticipation, relief, etc.) from the user's input data. This emotion information influences subsequent suggestion generation.

[1599] Step 7:

[1600] The server's generative AI module selects the most suitable plastic surgery candidates based on the analysis results and the output of the emotion engine. For example, if the user is feeling anxious, suggestions including ways to mitigate risks and detailed procedure procedures will be selected.

[1601] Step 8:

[1602] The server generates specific recommendations based on the selected cosmetic procedures, including the type of procedure, benefits, risks, required downtime, costs, and care information. Based on information from the emotion engine, the recommendation also includes explanations and advice based on the user's emotions.

[1603] Step 9:

[1604] The server formats the generated suggestions into text for the user and sends it to the terminal.

[1605] Step 10:

[1606] The device receives the suggestions from the server and displays them in a user-friendly format, including images and detailed explanations.

[1607] Step 11:

[1608] The user can review the displayed information and decide which plastic surgery is best for them. If necessary, the user can make an appointment or get more information.

[1609] Through these steps, the system proposes the most appropriate cosmetic surgery procedure while taking into account the user's emotional state, helping the user to make an appropriate choice with peace of mind.

[1610] Example 2

[1611] Next, a description will be given of Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1612] Currently, when users select a plastic surgery, it is difficult to obtain optimal suggestions that take into account their emotional state and detailed desired conditions. In particular, if the user has emotional states such as anxiety or anticipation, suggestions that do not take these emotions into account may reduce user satisfaction. Therefore, there is a need for a system that can properly recognize the user's emotional state and suggest the optimal plastic surgery that suits each individual situation.

[1613] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1614] In this invention, the server includes means for receiving input data and collecting information on the treatment desired by the user, means for analyzing the received input data and generating optimal treatment candidates, means for recognizing the emotional state of the user based on the input data, and means for generating specific proposals based on the generated treatment candidates and the emotional state, thereby making it possible to propose optimal treatments while taking the emotional state of the user into consideration.

[1615] "Input data" refers to data that includes information and conditions regarding the treatment desired by the user.

[1616] "Means for receiving" refers to a device or program that has the function of incorporating input data sent by a user into the system.

[1617] The "analyzing means" refers to a device or program that has the function of analyzing information based on received input data and selecting the most suitable treatment options.

[1618] The "generation means" is a device or program that has the function of automatically generating specific treatment candidates that meet the user's wishes based on the analysis results.

[1619] "Emotion recognition means" refers to a device or program that has the function of analyzing user input data and other information to identify the user's emotional state.

[1620] The "proposal generation means" is a device or program that has the function of creating specific proposal content based on the generated treatment candidates and the results of the emotion recognition means.

[1621] The "display means" refers to a device or program that has the function of visually presenting the generated proposal content to the user.

[1622] A "standard format" is a consistent data format required for systems to analyze and process data.

[1623] This invention is a generative AI system that takes into account the emotional state of the user when selecting the desired treatment and makes optimal suggestions. The system analyzes information provided by the user and suggests the optimal treatment for the user.

[1624] System Configuration

[1625] This system is broadly composed of the following five main components:

[1626] 1. User Interface (Terminal)

[1627] 2. Data Processing Server (Server)

[1628] 3. Generative AI module (server)

[1629] 4. Emotion Recognition Engine (Server)

[1630] 5. Result display widget (terminal)

[1631] User Interface (Terminal)

[1632] Users use a terminal to enter their information, including the image they want to resemble, celebrities, favorite clothing and style, bone structure, facial structure, body type, hair, skin, and eye color, budget, downtime, whether they want simple treatment, and past treatment history. After entering this information and clicking the "Submit" button, the data is transferred to the server.

[1633] Data Processing Server (Server)

[1634] The server receives input data sent by the user. The received data is converted into a standard format (e.g., JSON format) and made parseable. The server's analysis module then analyzes the data and selects candidate actions based on the user's wishes and conditions.

[1635] Generative AI module (server)

[1636] The generative AI module generates optimal treatment options based on the results of data analysis. This module uses a large database to suggest the best treatment for the user's desired conditions. The generative AI generates recommendations that include detailed information such as the specific treatment type, benefits, risks, required downtime, and costs.

[1637] Emotion recognition engine (server)

[1638] The emotion recognition engine recognizes the user's emotional state based on their input data. This emotional state information is used to tailor the treatment options and recommendations generated by the generative AI module. For example, if the user is feeling anxious, the engine will provide reassuring recommendations with detailed information about risks and care.

[1639] Result display widget (terminal)

[1640] The device receives the recommendations sent from the server and displays them on the user's screen, allowing the user to check detailed information about specific treatments and make the best choice for themselves.

[1641] Specific examples

[1642] Example of input data

[1643] The user enters the following information:

[1644] Desired image: Pure and gentle

[1645] Celebrity: Mr. A

[1646] Favorite clothing and style: Casual

[1647] Skeleton:Slender

[1648] Facial shape: Round face

[1649] Body type: Standard

[1650] Hair color: Black, Skin color: Fair, Eye color: Brown

[1651] Budget: 500,000 yen

[1652] Downtime: 1 week

[1653] Simple Treatment: Hope

[1654] Past treatment history: None

[1655] Examples of proposals

[1656] If the emotion recognition engine recognizes "anxiety" from the user's input data, the generative AI will generate the following suggestions:

[1657] Recommendation: We recommend the "simple double eyelid surgery" to achieve a neat and gentle look. Downtime is about one week, and the cost is 300,000 yen. You may experience swelling and bruising for a few days after the procedure, but in most cases this can be covered with makeup. We will also provide detailed instructions on post-procedure care and precautions.

[1658] This system allows users to make choices with confidence, as it suggests the most appropriate treatment that takes into account their emotional state.

[1659] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1660] Step 1: Enter your user information

[1661] The user enters their information using the device's user interface. Specifically, they enter details in fields such as "desired image," "budget," "desired downtime," and "past treatment history," and click the "Submit" button. This action sends the user's input data (in JSON format) from the device to the server.

[1662] Input: User information (desired image, budget, desired downtime, etc.)

[1663] Output: Send input data (JSON format)

[1664] Step 2: Receiving and converting input data

[1665] The device receives the data sent by the user. After receiving the data, the device converts it into the correct format (e.g., JSON format) and forwards it to the server. The server converts the received data into a parsable format and prepares it for data processing.

[1666] Input: User input data (JSON format)

[1667] Output: Data converted into a parsable format

[1668] Step 3: Data analysis and treatment selection

[1669] The server analyzes the received data using the data processing server's analysis module. Based on the user's preferences and conditions (e.g., "round face," "black hair," "budget of 500,000 yen," etc.), it selects the most suitable treatment options. This analysis process uses a large database of past data and treatments to make the best recommendations.

[1670] Input: Data converted into a parsable format

[1671] Output: Candidates for optimal treatment

[1672] Step 4: Recognizing emotions with the emotion recognition engine

[1673] The server uses an emotion recognition engine to analyze the user's emotional state. Specifically, it recognizes emotions such as "anxiety" or "expectation" based on the user's input data and past data. This emotional information is reflected in subsequent suggestions.

[1674] Input: User-entered and historical data

[1675] Output: Information about the user's emotional state

[1676] Step 5: Generative AI generates proposals

[1677] The generative AI module generates specific treatment recommendations based on the server's analysis results and information from the emotion recognition engine. Specifically, it makes detailed recommendations such as "simple double eyelid surgery," "one week of downtime," and "cost: 300,000 yen." If the user is feeling anxious, it makes adjustments based on the user's emotional information, such as adding detailed information about risks and care.

[1678] Input: Optimal treatment options and emotional information

[1679] Output: Specific proposals

[1680] Step 6: View the results

[1681] The terminal displays the proposal received from the server to the user. Specifically, the generated treatment details, benefits, risks, downtime, costs, etc. are displayed on the user interface, allowing the user to review the information and make the best choice for themselves.

[1682] Input: Specific proposal

[1683] Output: Display of proposal

[1684] Through this series of processes, the user is presented with the optimal course of action that takes into account their emotional state, allowing them to make a choice with confidence.

[1685] (Application example 2)

[1686] Next, a description will be given of Application Example 2. In the following description, the data processing device 12 will be referred to as a "server" and the robot 414 will be referred to as a "terminal."

[1687] Conventional security services have the problem that it is difficult for security guards to quickly decide on the appropriate response on the scene, and there is a high possibility that they will make incorrect decisions, especially when psychological factors such as emotions and stress are influential.In addition, because uniform response measures are provided without considering the emotional state of the security guards themselves, there is a need for flexible responses that are appropriate for the situation.

[1688] The identification process by the identification processing unit 290 of the data processing device 12 in Application Example 2 is realized by the following means. In this invention, the server includes means for receiving input data and collecting information on the cosmetic surgery desired by the user, generation means for analyzing the received input data and generating optimal cosmetic surgery candidates, proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates, means for analyzing the emotional states of the security target and security guards using a generation AI and proposing optimal countermeasures, and display means for presenting the generated proposals to the user. This allows optimal countermeasures to be provided in real time based on the situation and emotional state of the scene, enabling security guards to take prompt and appropriate action.

[1689] "Input Data" refers to information about your preferences and circumstances submitted by you.

[1690] "Generation means" refers to the part of the system that analyzes the received input data and generates optimal cosmetic surgery or treatment options based on the user's preferences.

[1691] The "proposal generation means" refers to a part of the system that creates specific proposals based on the candidate cosmetic procedures and countermeasures generated by the generation means.

[1692] "Generative AI" refers to artificial intelligence technology that analyzes large amounts of data to understand a user's wishes and emotional state and make optimal suggestions.

[1693] "Emotional state" refers to the psychological state (e.g., anxiety, stress, relief, etc.) of the user, the person being guarded, and the security guard.

[1694] The "generated proposal content" refers to detailed information about specific cosmetic procedures and countermeasures created by the proposal generation means.

[1695] "Display means" refers to the part of the system that allows the user to visually confirm the generated suggestions.

[1696] System Overview and Operation

[1697] 1. System Components

[1698] The system of the present invention consists of the following major components:

[1699] User Interface (Terminal)

[1700] Data Processing Server

[1701] Generative AI Module

[1702] Emotion Engine

[1703] Result Display Widget

[1704] 2. Hardware and Software Used

[1705] The system uses devices such as smartphones and smart glasses, various servers, analysis libraries, and generative AI models. The specific hardware and software used includes the following:

[1706] Hardware: Smartphones (iOS / Android), smart glasses (Google Glass, Microsoft HoloLens)

[1707] Software: AWS, Google Cloud, Microsoft Azure (data processing servers), MySQL, MongoDB (databases), IBM Watson Emotion Analysis, Microsoft Text Analytics (sentiment analysis library), OpenAI GPT-4, Google BERT (generative AI module)

[1708] 3. Natural Language Description

[1709] User Interface (Terminal)

[1710] Users use their smartphones or smart glasses to input their personal information, the situation at the scene, the condition of the person being guarded, and the guard's own emotions. This information is sent to the server in JSON format through the application.

[1711] Data Processing Server

[1712] The server receives input data in a standard format (JSON) and converts it into a format that can be parsed. Cloud services such as AWS, Google Cloud, and Microsoft Azure are used for data processing. Information is stored in the database using MySQL or MongoDB.

[1713] Generative AI Module

[1714] The generative AI module analyzes the received data and generates optimal countermeasures based on the user's preferences and on-site conditions, using AI models such as OpenAI GPT-4 and Google BERT. This generates recommendations that include details such as the type of specific cosmetic or security countermeasure, its benefits, risks, costs, and required time.

[1715] Emotion Engine

[1716] The emotion engine uses emotion analysis libraries like IBM Watson Emotion Analysis and Microsoft Text Analytics to analyze the user's emotional state from their input data. Based on this analysis, the generative AI module optimizes the suggestions it generates. For example, if a security guard is feeling anxious, the suggestions will take that into account.

[1717] Result Display Widget

[1718] The result display widget displays the generated suggestions on the user's smartphone or smart glasses, allowing the user to review the suggestions and select the appropriate response.

[1719] 4. Examples and prompts

[1720] As a concrete example, suppose the user enters the following information:

[1721] Example of input data

[1722] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[1723] Condition of the guarded person: "Face red and appears very angry."

[1724] Security guard's feelings: "I feel unsafe."

[1725] Specific examples of proposals

[1726] The system receives the above information, and if the emotion engine detects "anxiety," the generative AI makes the following suggestions:

[1727] "We will continue to monitor the situation on site and instruct people to maintain distance from each other to stay safe. If you feel unsafe, please contact security headquarters and report the situation. We will also provide advice on how to stay calm, for example, by taking deep breaths to calm yourself down."

[1728] Example prompts for generative AI models

[1729] Generate optimal responses based on the user's emotional state and on-site conditions.

[1730] Scene: "Crowded area. Multiple people talking loudly. No suspicious items found."

[1731] Condition of the guarded person: "Face red and appears very angry."

[1732] Security guard's feelings: "I feel unsafe."

[1733] In this way, the system helps security guards take prompt and appropriate action by making appropriate suggestions in real time that take into account their emotional state.

[1734] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1735] Step 1:

[1736] The user uses the terminal to input the situation at the scene, the state of the person being guarded, and their own emotions. The input data includes the situation at the scene (e.g., "crowded"), the state of the person being guarded (e.g., "his face is red and he looks very angry"), and the emotions of the security guard (e.g., "he feels anxious"). The user clicks the "Send" button to send the input data to the server.

[1737] Step 2:

[1738] The terminal receives input data sent by the user and converts it into JSON format. The converted data is then transferred to the server. The input data (the situation at the scene, the state of the person being guarded, and the security guard's emotions) is converted into JSON format and sent.

[1739] Step 3:

[1740] The server converts the received JSON formatted input data into a parsable format. Specifically, it processes it so that it can be stored in a database (MySQL, MongoDB). Through this processing, the server obtains a format that can be stored in the database (for example, a structured table format).

[1741] Step 4:

[1742] The server performs data analysis based on the converted input data. The analysis uses the computational resources of cloud services (AWS, Google Cloud, Microsoft Azure), and a generative AI model (OpenAI GPT-4, Google BERT) generates optimal candidate solutions. Based on the input data, solutions are proposed that match the user's wishes and the situation on-site.

[1743] Step 5:

[1744] The emotion engine analyzes the user's emotional state from the input data. This process uses emotion analysis libraries (IBM Watson Emotion Analysis, Microsoft Text Analytics). The emotion engine analyzes the user's input data and obtains the emotional state (e.g., "anxiety").

[1745] Step 6:

[1746] The generative AI module adjusts its suggestions based on the emotional state information obtained from the emotion engine. For example, if a security guard feels "anxious," it will suggest countermeasures with specific instructions to mitigate risk. The generative AI model is used to generate detailed instructions and advice to reassure the user.

[1747] Step 7:

[1748] The server sends the generated proposal to the device, which then displays it on the user's screen. For example, details of appropriate countermeasures and necessary steps are displayed, allowing the user to act accordingly.

[1749] This series of processes allows users to receive optimal countermeasures in real time based on the situation at the scene and their own emotional state.

[1750] The specific processing unit 290 transmits the result of the specific processing to the robot 414. In the robot 414, the control unit 46A causes the speaker 240 and the control target 443 to output the result of the specific processing. The microphone 238 acquires voice indicating a user input regarding the result of the specific processing. The control unit 46A transmits voice data indicating the user input acquired by the microphone 238 to the data processing device 12. In the data processing device 12, the specific processing unit 290 acquires the voice data.

[1751] The data generation model 58 is a so-called generative AI (Artificial Intelligence). An example of the data generation model 58 is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> ), Gemini (Internet search <url: https: gemini.google.com ?hl="ja">) and other generation AIs. The data generation model 58 is obtained by performing deep learning on a neural network. A prompt including an instruction is input to the data generation model 58, and inference data such as voice data indicating voice, text data indicating text, and image data indicating an image is also input. The data generation model 58 performs inference on the input inference data in accordance with the instruction indicated by the prompt, and outputs the inference result in a data format such as voice data and text data. Here, inference refers to, for example, analysis, classification, prediction, and / or summarization.

[1752] In the above embodiment, an example was given in which the specific processing is performed by the data processing device 12, but the technology of the present disclosure is not limited to this, and the specific processing may be performed by the robot 414.

[1753] The emotion identification model 59 as an emotion engine may determine the user's emotion according to a specific mapping. Specifically, the emotion identification model 59 may determine the user's emotion according to an emotion map (see FIG. 9), which is a specific mapping. Similarly, the emotion identification model 59 may determine the robot's emotion, and the identification processing unit 290 may perform identification processing using the robot's emotion.

[1754] FIG. 9 is a diagram illustrating an emotion map 400 on which multiple emotions are mapped. In the emotion map 400, emotions are arranged in concentric circles radiating from the center. Emotions closer to the center of the concentric circles are more primitive. Emotions representing states and actions arising from a state of mind are arranged on the outer edges of the concentric circles. The concept of emotion includes both affect and mental states. Emotions generally generated from reactions occurring in the brain are arranged on the left side of the concentric circles. Emotions generally induced by situational judgment are arranged on the right side of the concentric circles. Emotions generally generated from reactions occurring in the brain and induced by situational judgment are arranged on the upper and lower sides of the concentric circles. Furthermore, the emotion of "pleasure" is arranged on the upper side of the concentric circles, and the emotion of "discomfort" is arranged on the lower side. In this way, in the emotion map 400, multiple emotions are mapped based on the structure by which emotions are generated, and emotions that tend to occur simultaneously are mapped close to each other.

[1755] These emotions are distributed in the 3 o'clock direction on emotion map 400, and typically fluctuate between relief and anxiety. In the right half of emotion map 400, situational awareness dominates over internal sensations, resulting in a sense of calm.

[1756] The inside of emotion map 400 represents what is going on in the mind, and the outside of emotion map 400 represents behavior, so the further you go outside emotion map 400, the more visible the emotions become (the more they are expressed in behavior).

[1757] Human emotions are based on various balances, such as posture and blood sugar levels. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. Emotions can also be created for robots, automobiles, and motorcycles, based on various balances, such as posture and remaining battery life. When these balances deviate from the ideal, a state of discomfort is indicated, and when they approach the ideal, a state of pleasure is indicated. An emotion map can be generated, for example, based on Dr. Mitsuyoshi's emotion map (Research on Voice Emotion Recognition and Emotional Brain Physiological Signal Analysis Systems, Tokushima University, Doctoral Dissertation: https: / / ci.nii.ac.jp / naid / 500000375379). The left half of the emotion map lists emotions belonging to the "reaction" domain, where sensation is dominant. The right half of the emotion map lists emotions belonging to the "situation" domain, where situational awareness is dominant.

[1758] The emotion map defines two emotions that promote learning. One is a negative emotion on the situation side, around the middle of "repentance" or "reflection." In other words, this occurs when the robot experiences negative emotions such as "I never want to feel this way again" or "I don't want to be scolded again." The other is a positive emotion on the response side, around "desire." In other words, this occurs when the robot experiences positive feelings such as "I want more" or "I want to know more."

[1759] The emotion identification model 59 inputs user input into a pre-trained neural network, obtains emotion values ​​indicating each emotion shown in the emotion map 400, and determines the user's emotion. This neural network is pre-trained based on multiple pieces of training data that are combinations of user input and emotion values ​​indicating each emotion shown in the emotion map 400. Furthermore, this neural network is trained so that emotions that are located close to each other have similar values, as in the emotion map 900 shown in FIG. 10. FIG. 10 shows an example in which multiple emotions, "relieved," "calm," and "reassuring," have similar emotion values.

[1760] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[1761] In the above embodiment, an example was given in which the specific processing is performed by one computer 22, but the technology of the present disclosure is not limited to this, and the specific processing may be distributed and performed by a plurality of computers including the computer 22. For example, the data generation model 58 may be provided in an external device of the data processing device 12, and data may be generated in the external device in accordance with input data.

[1762] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[1763] 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.

[1764] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[1765] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[1766] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[1767] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[1768] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[1769] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[1770] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference.

[1771] The following is further disclosed regarding the above embodiment.

[1772] (Claim 1)

[1773] means for receiving input data and collecting information regarding the cosmetic procedure desired by the user;

[1774] generating means for analyzing the received input data and generating optimal cosmetic surgery candidates;

[1775] a proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates;

[1776] a display means for displaying the generated proposal to the user;

[1777] A system including:

[1778] (Claim 2)

[1779] 10. The system of claim 1, further comprising means for converting input data from a user into a standard format.

[1780] (Claim 3)

[1781] 10. The system of claim 1, further comprising means for analyzing the received input data and suggesting the most suitable cosmetic procedure based on the user's wishes and conditions.

[1782] "Example 1"

[1783] (Claim 1)

[1784] a means by which a user uses the terminal to enter input data and collect information;

[1785] means for converting received input data into a format that can be parsed by the server;

[1786] The server analyzes the input data and selects the most suitable cosmetic surgery candidates based on the user's wishes and conditions.

[1787] A means for the generative AI module to generate detailed recommendations for optimal cosmetic surgery;

[1788] means for the terminal to display the generated suggestions to the user;

[1789] A system including:

[1790] (Claim 2)

[1791] The system of claim 1, further comprising means for converting input data into a standard format (e.g., JSON format).

[1792] (Claim 3)

[1793] 10. The system of claim 1, further comprising means for generating detailed optimal cosmetic procedure recommendations using the generative AI model.

[1794] "Application Example 1"

[1795] (Claim 1)

[1796] a means for receiving input data and collecting information regarding cosmetic procedures or fashion desired by the user;

[1797] generating means for analyzing the received input data and generating optimal cosmetic surgery candidates or fashion items;

[1798] a proposal generation means for generating specific proposal content based on the generated cosmetic surgery candidates or fashion items;

[1799] a display means for displaying the generated proposal to the user;

[1800] A system including:

[1801] (Claim 2)

[1802] 10. The system of claim 1, further comprising means for converting input data from a user into a standard format.

[1803] (Claim 3)

[1804] 10. The system according to claim 1, further comprising means for analyzing the received input data and suggesting the most suitable cosmetic surgery or fashion item based on the user's wishes and conditions.

[1805] "Example 2: Combining Emotion Engines"

[1806] (Claim 1)

[1807] means for receiving input data and collecting information regarding the user's desired action;

[1808] generating means for analyzing received input data and generating optimal treatment candidates;

[1809] emotion recognition means for recognizing an emotional state based on user input data;

[1810] a proposal generation means for generating specific proposal content based on the generated treatment candidates and the emotional state;

[1811] a display means for displaying the generated proposal to the user;

[1812] A system including:

[1813] (Claim 2)

[1814] 10. The system of claim 1, further comprising means for converting input data from a user into a standard format.

[1815] (Claim 3)

[1816] 10. The system of claim 1, further comprising means for analyzing the received input data and proposing optimal treatment based on the user's wishes and conditions.

[1817] "Application example 2 when combining emotion engines"

[1818] (Claim 1)

[1819] means for receiving input data and collecting information regarding the cosmetic procedure desired by the user;

[1820] generating means for analyzing the received input data and generating optimal cosmetic surgery candidates;

[1821] a proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates;

[1822] Using generative AI, we will analyze the emotional state of the security personnel and security guards and propose optimal countermeasures.

[1823] a display means for displaying the generated proposal to the user;

[1824] A system including:

[1825] (Claim 2)

[1826] 10. The system of claim 1, further comprising means for converting input data from a user into a standard format.

[1827] (Claim 3)

[1828] 10. The system of claim 1, further comprising means for analyzing the received input data and suggesting the most suitable cosmetic procedure based on the user's wishes and conditions. [Explanation of symbols]

[1829] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. means for receiving input data and collecting information regarding the cosmetic procedure desired by the user; generating means for analyzing the received input data and generating optimal cosmetic surgery candidates; a proposal generation means for generating specific proposals based on the generated cosmetic surgery candidates; a display means for displaying the generated proposal to the user; A system including:

2. 10. The system of claim 1, further comprising means for converting input data from a user into a standard format.

3. The system of claim 1 further comprising means for analyzing the received input data and proposing the most suitable cosmetic surgery based on the user's wishes and conditions.

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