System

Abstract

A system is provided.SOLUTION: A system comprising: means for receiving basic information from a user; means for generating a dedicated generation-based artificial intelligence chatbot based on the received basic information; means for receiving an image of palmistry or a face from the user; means for analyzing the received image and specifying a partner suitable for the user; means for automatically applying for matching to the specified partner; and means for notifying the user of a matching result and details of a schedule.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

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

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

[0004] Conventional matching systems require users to create detailed profiles, search for a suitable partner, and apply for a match, which requires a lot of time and effort. It is also difficult to provide customized responses for individual users, which can lead to a poor user experience. Furthermore, no systems exist that integrate a method for diagnosing compatibility based on palmistry and physiognomy and selecting a suitable partner based on that diagnosis. The present invention aims to solve these problems and provide a system that allows users to more easily and effectively match with their ideal partner. [Means for solving the problem]

[0005] The present invention provides a means for receiving basic information from a user and generating a dedicated generative AI chatbot based on that information. It also includes a means for receiving palm or facial images from the user and analyzing them to identify a suitable match for the user. The analysis is based on palm and facial features, and includes a means for automatically requesting a match with the identified match. It also includes a means for notifying the user of the match results and detailed schedules, such as dates. The system accesses an external service platform via a communications network and automatically performs the necessary operations, reducing the user's workload and achieving efficient matching.

[0006] "User information" refers to basic personal information such as name, age, and hobbies that a user enters into the app.

[0007] A "generative AI chatbot" is an AI that is generated specifically for a user and engages in conversation based on input user information.

[0008] Palmistry refers to the lines and shapes engraved on the palm of the hand, and is used as a means of divining an individual's personality and destiny.

[0009] Physiognomy is a method used to predict an individual's character and destiny based on facial features and shape.

[0010] An "image analysis system" is a system that takes an image as input for palm reading or facial analysis, analyzes it, and generates results.

[0011] A "matching application" is a procedure in which a user proposes a mutual match to a person selected by the user through the system.

[0012] "Communications network" refers to the electronics communications infrastructure over which digital data is transmitted, and includes various networks, including the Internet.

[0013] "Service platform" means a system or website that provides external services and is used for automated operations and information exchange.

[0014] A "schedule" is a timetable that allows a user to manage their plans, and includes details of dates and events. [Brief explanation of the drawings]

[0015] [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

[0016] 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.

[0017] First, the terms used in the following description will be explained.

[0018] 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).

[0019] 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.

[0020] 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.

[0021] 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.

[0022] 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."

[0023] [First embodiment]

[0024] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0025] 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.

[0026] 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).

[0027] 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.

[0028] 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.

[0029] 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.

[0030] 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.

[0031] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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."

[0036] The system of the present invention receives basic information from a user and generates a dedicated generative AI chatbot based on that information. It then analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also automatically requests a match with the identified partner and notifies the user of the match results and schedule details.

[0037] 1. Entering user information and creating a chatbot

[0038] Users enter their basic information (name, age, hobbies, etc.) into the app.

[0039] The terminal sends this information to the server.

[0040] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[0041] Once the setup is complete, the server will notify the user that the setup is complete.

[0042] 2. Upload palm / face photo and analyze the image

[0043] Users take a photo of their palm or face and upload it to the app.

[0044] The terminal sends the uploaded image to the server.

[0045] The server uses an image analysis system to analyze palm lines and facial features.

[0046] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[0047] 3. Matching application and notification of results

[0048] The user selects the desired partner from the notified candidate list.

[0049] The terminal transmits the selection information to the server.

[0050] The server accesses an external service platform and automatically applies for a match.

[0051] The server checks the matching results, and if successful, generates date details (date, time, location, details, etc.) and adds them to the user's schedule.

[0052] The results and schedule details are notified to the user via the terminal.

[0053] 4. Specific Examples

[0054] For example, User A uses the app to perform the following process:

[0055] User A enters and uploads basic information and a photo of their palm into the app.

[0056] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0057] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0058] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0059] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0060] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0061] By linking the server, terminals, and users, the system is designed to allow users to easily and quickly match with their ideal partner. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[0062] The processing flow will be explained below.

[0063] Step 1:

[0064] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[0065] Step 2:

[0066] The terminal converts the input user information into a data format and transmits it to the server.

[0067] Step 3:

[0068] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[0069] Step 4:

[0070] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[0071] Step 5:

[0072] Users take a photo of their palm or face and upload it to the app.

[0073] Step 6:

[0074] The terminal transmits the uploaded image data to the server.

[0075] Step 7:

[0076] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[0077] Step 8:

[0078] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[0079] Step 9:

[0080] The terminal displays the candidate list to the user.

[0081] Step 10:

[0082] The user checks the list of candidates and selects the person with whom they wish to be matched.

[0083] Step 11:

[0084] The terminal transmits the information of the selected party to the server.

[0085] Step 12:

[0086] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0087] Step 13:

[0088] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0089] Step 14:

[0090] The server sends the matching results and schedule details to the terminal.

[0091] Step 15:

[0092] The terminal notifies and displays the matching results and schedule information to the user.

[0093] This series of processing flows allows users to efficiently match with the most suitable partner with minimal effort.

[0094] Example 1

[0095] 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."

[0096] Conventional matching systems have the problem that users must manually enter their own information to search for a suitable partner, which is a complicated process that takes time and effort. In addition, methods for searching for partners based on palm lines or facial features are not widely used, and their effectiveness is not fully utilized. Another issue is the difficulty of building a system that automatically connects with external service platforms and matches partners.

[0097] 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.

[0098] In this invention, the server includes: means for receiving basic information from a user; means for generating a dedicated generative AI chatbot based on the received basic information; means for receiving palm or facial images from the user; image analysis means for analyzing the received images; means for identifying a suitable partner for the user based on the analyzed characteristics; means for accessing an external service platform via a communication network and automatically applying for a match with the identified partner; and means for notifying the user of the match results and schedule details. This allows users to easily input information and quickly find a suitable partner. Furthermore, analyzing palm and facial features can achieve more accurate matching. Furthermore, automatic collaboration with external services can improve matching efficiency and significantly reduce user effort.

[0099] "User" refers to an individual who uses the system to enter their basic information and upload images of their palm or face to search for a match.

[0100] A "generative AI chatbot" refers to an AI that is generated specifically for a user based on their basic information and provides support through dialogue with the user.

[0101] "Basic information" refers to personal information entered by the user, such as their name, age, hobbies, etc.

[0102] "Palm or face image" refers to a photograph of the palm of the hand or face that a user uploads to the system.

[0103] "Image Analysis Means" refers to the technical means for analyzing the uploaded palm or face image to extract features.

[0104] "Identified partner" refers to a suitable candidate for the user, selected by the system based on the image analysis results and the user's basic information.

[0105] "Communications Network" refers to the Internet and other digital communications means used to send and receive information.

[0106] "External Service Platform" refers to a third-party platform that provides matching or dating services.

[0107] "Matching proposal" refers to the system automatically proposing dates or interactions to suitable partners for the user.

[0108] "Matching result" refers to the other party's response to the matching request.

[0109] "Schedule details" refers to information such as the date, time, location, and content of the date that will be set if the match is successful.

[0110] The present invention is a system that receives basic information from a user, generates a dedicated generative AI chatbot based on that information, and identifies the user's best match by analyzing palm reading or facial images uploaded by the user. Furthermore, the system automatically requests a match with the identified match and notifies the user of the match results and schedule details. Specific hardware and software are used to efficiently implement this process.

[0111] This system mainly consists of the following elements:

[0112] 1. Enter your user information

[0113] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[0114] The device receives this input information and sends it to the server. The basic information is used to generate a generative AI chatbot based on the user's hobbies and interests.

[0115] 2. Chatbot Creation

[0116] Based on the received user information, the server uses generative artificial intelligence (e.g., OpenAI's GPT-4) to generate a chatbot specifically for the user. This chatbot is customized for the user and provides support through dialogue with the user.

[0117] 3. Upload your palm / face photo

[0118] Users take a photo of their palm or face and upload it to the application.

[0119] The device receives the uploaded images and automatically sends them to the server.

[0120] 4. Image Analysis

[0121] The server uses an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze the received palm or face image. Based on the analyzed features, it applies an algorithm to match the user with the best possible partner.

[0122] 5. Identifying and notifying potential matches

[0123] Based on the analysis results, the server identifies the most suitable partner for the user and generates a list of candidates. This list is then notified to the user, allowing the user to select the partner they desire.

[0124] 6. Automatic matching application

[0125] Based on the user's selection, the server accesses an external service platform via a communication network and automatically sends a matching request to the identified person.

[0126] The server checks the match results and, if successful, generates the date details (date, time, location, details, etc.).

[0127] 7. Adding results and schedules

[0128] The server sends the date details to the device and notifies the user, and the date schedule is automatically added to the user's calendar.

[0129] Specific examples of operation

[0130] For example, consider the case where a user enters basic information such as "Taro Tanaka, 35 years old, hobby: reading" and uploads a photo of his palm.

[0131] The device formats this information into JSON format and sends it to the server.

[0132] The server uses OpenAI's GPT-4 to generate a chatbot specifically for Tanaka Taro.

[0133] The server uses the Google Cloud Vision API to analyze the characteristics of the palm lines and select the most suitable partner.

[0134] Next, based on the analysis results, a candidate list (for example, "Candidate A: Yamada Hanako, age 30, hobby: listening to music") is generated and notified to Tanaka Taro.

[0135] When Taro Tanaka selects Hanako Yamada, the server accesses an external dating platform and automatically requests a match.

[0136] If the match is successful, the details of the date (for example, "Date and time: July 10th, Location: Tokyo cafe, Content: Lunchtime") are generated, notified to Taro Tanaka via his device, and the date is automatically added to his calendar.

[0137] Example prompt sentence:

[0138] "You enter some basic information into the app, upload a photo of your palm, and it will then automatically find your ideal match and notify you of date details if a match is made."

[0139] This system is designed to enable users to easily and quickly find the perfect match through collaboration between users, devices, and servers. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[0140] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0141] Step 1:

[0142] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[0143] Input: User's basic information (name, age, hobbies, etc.)

[0144] Output: The terminal checks the input, formats it into JSON format, and sends it to the server.

[0145] Specific operation: For example, enter "Yamada Taro, 30 years old, hobby: cycling" and the device will convert this information into JSON format as shown below.

[0146] json

[0147] {

[0148] "name": "Yamada Taro",

[0149] "age": 30,

[0150] "hobbies": ["cycling"]

[0151] }

[0152] This JSON data is sent to the server.

[0153] Step 2:

[0154] The server generates a dedicated chatbot using generative artificial intelligence (e.g., OpenAI's GPT-4) based on the received user information.

[0155] Input: User basic information (JSON format)

[0156] Output: Chatbot generation result (user-specific bot)

[0157] Specific operation: The server analyzes the received JSON data and calls a generative AI API based on it to generate a chatbot for the user. The chatbot reflects the user's preferences and interests.

[0158] Step 3:

[0159] The server sends a notification of completion of the generated chatbot configuration to the terminal, and the terminal notifies the user of the same.

[0160] Input: Chatbot generation result (user-specific bot)

[0161] Output: Notification of successful setup

[0162] Specific operation: The server notifies the device that the chatbot configuration is complete, and the device displays a message to the user such as "Chatbot configuration is complete."

[0163] Step 4:

[0164] Users take a photo of their palm or face and upload it to the application.

[0165] Input: Palm or face photo (image file)

[0166] Output: Image file uploaded to the device

[0167] What happens: A user takes a photo of their palm using their smartphone camera and uploads it through the application.

[0168] Step 5:

[0169] The terminal sends the uploaded image to the server.

[0170] Input: Uploaded image file

[0171] Output: Image data sent to the server

[0172] Specific operation: The device receives the image file, encodes it as binary data, and sends it to the server.

[0173] Step 6:

[0174] The server sends the received images to an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze palm lines and facial features.

[0175] Input: Image data (binary)

[0176] Output: Image analysis results (palm reading and facial feature data)

[0177] Specific operation: The server calls the image analysis API, analyzes the received image data, and obtains information such as the length and position of the palm lines, facial feature points, etc. The analysis results are saved in JSON format.

[0178] Step 7:

[0179] Based on the analysis results, the server applies an algorithm to select the most suitable partner to provide to the user and generates a list of candidates.

[0180] Input: Image analysis results (palm reading and facial feature data)

[0181] Output: Candidate list

[0182] Specific operation: The server analyzes the analysis results and selects suitable candidates according to an algorithm. For example, it generates a list containing information such as "Candidate B: Hanako Sato, 28 years old, hobby: trekking."

[0183] Step 8:

[0184] The server sends the candidate list to the terminal and notifies the user.

[0185] Input: Candidate list

[0186] Output: Notification of candidate list to terminal

[0187] Specific operation: The server sends the generated candidate list to the terminal, and the terminal displays it to the user in the form of "A list of the best possible candidates has been generated."

[0188] Step 9:

[0189] The user selects the desired partner from the notified candidate list.

[0190] Input: Candidate list

[0191] Output: Selected contact information

[0192] Specific operation: The user selects the desired partner from the displayed list of candidates, for example, selecting "Hanako Sato."

[0193] Step 10:

[0194] The terminal transmits the selection information to the server.

[0195] Input: User selection information

[0196] Output: Sends the selection to the server

[0197] Specific operation: The device converts the information selected by the user into JSON format and sends it to the server.

[0198] Step 11:

[0199] The server accesses an external service platform and automatically applies for a match.

[0200] Input: User selection information

[0201] Output: Matching application results

[0202] Specific operation: The server uses an external API to request a match with the selected partner and obtains the result of success or failure.

[0203] Step 12:

[0204] The server checks the match results and generates the date details if successful.

[0205] Input: Matching application results

[0206] Output: Date details (date, time, location, details, etc.)

[0207] Specific operation: If the match is successful, the server generates date details such as "Date and time: August 15th, Location: Tokyo cafe, Content: Lunchtime."

[0208] Step 13:

[0209] The server sends the date details to the terminal, which notifies the user and automatically adds them to the schedule.

[0210] Input: Date details (date, time, location, details, etc.)

[0211] Output: Notification to device and addition to user's calendar

[0212] Specific operation: The server sends the date details to the device, and the device sends a notification to the user saying "The date has been confirmed." The date information is also automatically added to the user's calendar.

[0213] (Application example 1)

[0214] 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."

[0215] Conventional AI chatbot systems based on user information are limited to simply sending messages to users, making it difficult to provide services optimized to individual users' needs and preferences. Even with the introduction of image analysis functions, advanced customization based on users' lifestyles and specific situations remains a challenge. In particular, there is no system that can individually optimize the riding experience inside an autonomous vehicle, making it necessary to address these challenges.

[0216] 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.

[0217] In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving palm or facial images from the user, means for analyzing the received images to identify a suitable partner for the user, means for automatically requesting a match with the identified partner, means for notifying the user of the match results and schedule details, and means for receiving the user's basic information and facial image, generating a driverbot equipped with a dedicated generative AI, and providing entertainment and relaxation support based on the user's preferences and facial data, thereby enabling users to individually optimize their riding experience in an autonomous vehicle and receive personalized entertainment and relaxation support.

[0218] "User basic information" refers to personal data such as the user's name, age, hobbies, and preferences.

[0219] A "generative AI chatbot" is an interactive AI system that is automatically generated based on basic information received from the user and communicates with the user.

[0220] "Palm or face image" refers to image data such as a photo of the user's palm or face.

[0221] "Image analysis" refers to the process of analyzing received palm or facial images to extract features and patterns to derive specific information.

[0222] "Identifying suitable partners" refers to the process of finding the most suitable partner for a user based on image analysis and basic information.

[0223] A "matching request" refers to a request to contact an automatically identified person and build a certain relationship.

[0224] "Notification" refers to the act of informing users of important information such as matching results and schedule details.

[0225] "DriverBot" is a dedicated AI driver that is generated based on the user's basic information and facial image, and provides entertainment and relaxation support according to the user's hobbies and preferences.

[0226] "Entertainment" refers to entertainment such as music, videos, and games provided in the autonomous vehicle.

[0227] "Relaxation support" refers to services and functions that allow users to relax inside an autonomous vehicle.

[0228] The system of the present invention generates an interactive AI chatbot and a driverbot that are optimal for a user based on the user's basic information and facial image. Detailed embodiments of this system are described below.

[0229] First, a user accesses the application using a device (e.g., a smartphone). The application obtains basic information from the user, such as name, age, hobbies, and favorite music, and then asks the user to upload an image of their palm or face. The hardware used in this case includes a smartphone with a camera, and the software used includes an application and an image processing library (e.g., OpenCV).

[0230] The device sends the acquired basic information and facial image to a server, which then creates a generative AI chatbot based on the information received. The software used includes AI models (e.g., TensorFlow) and image analysis algorithms.

[0231] The server analyzes the facial image and performs image analysis to identify the user's facial features and expressions. This process extracts features based on the user's facial data. Based on the analysis results, a driver bot is generated that best suits the user's preferences and needs.

[0232] The generated driver bot will individually optimize the user's riding experience based on user information and facial data. For example, it can play music that matches the user's preferences and provide entertainment tailored to the user's hobbies. The driver bot also has a relaxation support function, providing relaxing music and guidance.

[0233] Furthermore, the generated driver bot will suggest entertainment and relaxation support to the user and carry out them upon request. This process includes customization based on the user's basic information and facial data, allowing the user to maximize their riding experience in the autonomous vehicle.

[0234] (Example)

[0235] For example, a user can use an application to input their name, age, hobbies, and favorite music, and upload a facial image. This information is sent from the device to a server. The server then creates a generative AI chatbot and driver bot specifically for the user based on the received basic information and facial image. This driver bot then plays music and provides relaxation support according to the user's preferences. As a specific example, if the user likes classical music, the application can be set to play classical music in the car.

[0236] (Example of a prompt)

[0237] Use the following prompt sentence to perform processing based on an artificial intelligence model.

[0238] "We want a personal driver AI driver bot to be generated based on the basic information and facial photo provided by the user, and provide optimal car entertainment and relaxation support."

[0239] In this way, the system can utilize the user's basic information and facial image to generate a dedicated generative AI driverbot that can provide individually optimized entertainment and relaxation support.

[0240] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0241] Step 1: Enter your user information

[0242] A user uses a device to input their basic information (such as name, age, hobbies, and favorite music) into the application. The user also takes a picture of their face using a camera-equipped device and uploads it. The input information and face image are sent to the server via the device. The input here is the user's basic information and face image, and the output is user data sent to the server.

[0243] Step 2: Receiving user information and generating an AI chatbot

[0244] The server receives the user's basic information and facial image sent from the device. Based on the received information, the server uses a generative AI model to generate a generative AI chatbot dedicated to the user. The data processing in this process involves analyzing the user data and generating a chatbot based on the AI ​​model. The output is the generated chatbot.

[0245] Step 3: Analyze the facial image

[0246] The server analyzes the received facial image using an image analysis algorithm (e.g., OpenCV). Specifically, it uses facial recognition technology to extract facial features in the image and use them to identify the user's individual characteristics. The input to this process is the facial image, and the output is the analyzed facial feature data.

[0247] Step 4: Create a Driver Bot

[0248] The server generates a dedicated generative AI driver bot based on the user's basic information and facial feature data. The generative AI model used is input with a prompt statement: "Based on the basic information and facial photo provided by the user, I would like a personal driver AI driver bot to provide optimal car entertainment and relaxation support." The driver bot is constructed based on this statement. The input in this process is basic information and facial feature data, and the output is the generated driver bot.

[0249] Step 5: Providing customized entertainment and relaxation support

[0250] The generated driver bot provides optimal entertainment and relaxation support based on the user's basic information and facial features. Specific actions include playing the user's favorite music, providing relaxation music, and providing guidance. The input to this process is the driver bot and its configuration data, and the output is the provision of customized services.

[0251] Step 6: Get user feedback and update the system

[0252] Users provide feedback on the entertainment and relaxation support provided. This feedback is sent from the device to the server, which then uses this information to update the driver bot's settings and generative AI model. The input to this process is the user's feedback data, and the output is an improved driver bot and model.

[0253] Through the above steps, the system of the present invention uses the user's basic information and facial image to generate an interactive AI chatbot and driverbot that are optimal for the user, and is able to provide individually optimized entertainment and relaxation support.

[0254] 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.

[0255] The system of the present invention receives basic information from the user and generates a dedicated generative AI chatbot based on that information. It also analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also combines an emotion engine that recognizes the user's emotions to improve matching accuracy and user experience. It automatically applies for a match with the most suitable partner and notifies the user of the matching results and schedule details.

[0256] 1. Entering user information and creating a chatbot

[0257] Users enter their basic information (name, age, hobbies, etc.) into the app.

[0258] The terminal sends this information to the server.

[0259] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[0260] Once the setup is complete, the server will notify the user that the setup is complete.

[0261] 2. Upload palm / face photo and analyze the image

[0262] Users take a photo of their palm or face and upload it to the app.

[0263] The terminal sends the uploaded image to the server.

[0264] The server uses an image analysis system to analyze palm lines and facial features.

[0265] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[0266] 3. Emotion recognition and response adjustment using an emotion engine

[0267] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text.

[0268] The server adjusts the chatbot's responses based on the emotion recognition results of the emotion engine. For example, if the user is nervous, the server will respond in a way that helps them relax.

[0269] 4. Adjusting match selection criteria using an emotion engine

[0270] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine. For example, if the user is excited, it will select a partner with a calmer personality, achieving optimal matching according to the user's emotional state.

[0271] 5. Matching application and result notification

[0272] The user selects the desired partner from the notified candidate list.

[0273] The terminal transmits the selection information to the server.

[0274] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0275] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0276] The results and schedule details are notified and displayed to the user via the terminal.

[0277] 6. Specific Examples

[0278] For example, User A uses the app to perform the following process:

[0279] User A enters and uploads basic information and a photo of their palm into the app.

[0280] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0281] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0282] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0283] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[0284] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0285] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0286] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0287] By linking the server, terminal, user, and emotion engine, this system can appropriately adjust dialogue and matching criteria according to the user's emotional state, efficiently matching the optimal partner with minimal effort.

[0288] The processing flow will be explained below.

[0289] Step 1:

[0290] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[0291] Step 2:

[0292] The terminal converts the input user information into a data format and transmits it to the server.

[0293] Step 3:

[0294] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[0295] Step 4:

[0296] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[0297] Step 5:

[0298] Users take a photo of their palm or face and upload it to the app.

[0299] Step 6:

[0300] The terminal transmits the uploaded image data to the server.

[0301] Step 7:

[0302] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[0303] Step 8:

[0304] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[0305] Step 9:

[0306] The terminal displays the candidate list to the user.

[0307] Step 10:

[0308] The user checks the list of candidates and selects the person with whom they wish to be matched.

[0309] Step 11:

[0310] The terminal transmits the information of the selected party to the server.

[0311] Step 12:

[0312] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0313] Step 13:

[0314] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0315] Step 14:

[0316] The server sends the matching results and schedule details to the terminal.

[0317] Step 15:

[0318] The terminal notifies and displays the matching results and schedule information to the user.

[0319] Step 16:

[0320] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text, thereby understanding the user's psychological state.

[0321] Step 17:

[0322] The server adjusts the chatbot's responses based on the results of the emotion engine. For example, if the user is nervous, the server will respond in a way that relaxes them.

[0323] Step 18:

[0324] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine, and creates a list of the most suitable partners according to the user's emotional state.

[0325] Step 19:

[0326] The server selects a partner based on the newly adjusted criteria, regenerates the candidate list, and sends this list to the terminal.

[0327] Step 20:

[0328] The terminal displays the regenerated candidate list to the user.

[0329] This series of processes allows for more accurate and satisfying matching by reflecting the user's emotional state.

[0330] Example 2

[0331] 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."

[0332] Conventional matching systems only identify potential partners based on basic user information and image analysis, and do not consider the user's emotional state. This results in problems such as insufficient matching accuracy and user experience with partners who are suited to the user's emotions.

[0333] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving images from a user, means for analyzing the received images to identify a partner suitable for the user, means for recognizing emotions from the user's facial expressions and text, means for adjusting the chatbot's response content based on the emotion recognition result, means for adjusting the match selection criteria based on the emotion recognition result, means for automatically applying for matching with the identified partner, and means for notifying the user of the matching result and schedule details. This makes it possible to identify the most suitable partner according to the user's emotional state, improving matching accuracy and user experience.

[0334] A "user" is an individual who uses the system to input and upload their own basic information and images.

[0335] "Basic information" refers to profile data such as the user's name, age, hobbies, etc.

[0336] A "generative AI chatbot" is an AI program that is customized based on the user's basic information and engages in conversation.

[0337] "Image" refers to a photograph of your palm or face uploaded by you.

[0338] "Image analysis" is the process of processing uploaded image data to identify palm lines and facial features.

[0339] "Partner" refers to a potential match identified by the system.

[0340] "Emotion recognition" is the process of determining a user's emotional state from their facial expressions and text.

[0341] "Adjusting response content" refers to dynamically changing the chatbot's statements and actions based on the emotion recognition results.

[0342] "Matching selection criteria" refers to the criteria for selecting the most suitable partner based on the user's emotional state.

[0343] "Matching application" is the process by which the system automatically proposes a date or interaction to a identified person.

[0344] "Schedule details" refers to information such as the date, time, location, and content of a date or event that is generated if a match is successful.

[0345] "External Platform" refers to other services on a communications network that the system accesses.

[0346] MODE FOR CARRYING OUT THE INVENTION

[0347] The system of the present invention receives basic information and images from users, generates a generative AI chatbot, recognizes the user's emotions, and matches them with the most suitable partner. The main roles of this system are played by the user, the terminal, and the server.

[0348] Hardware and software used

[0349] User device: A device used by a user, such as a smartphone, tablet, or PC.

[0350] Server: A central server handles data processing, generative artificial intelligence, image analysis, and emotion recognition.

[0351] Generative artificial intelligence (AI) model: An AI model that generates a chatbot based on basic user information.

[0352] Image analysis system: Uses image processing libraries such as OpenCV to analyze palm lines and facial features.

[0353] Emotion recognition engine: Uses emotion analysis APIs such as IBM Watson to recognize emotions from user facial expressions and text.

[0354] Entering user information and generating a chatbot

[0355] 1. The user enters their basic information (name, age, hobbies, etc.) into the app on their device.

[0356] 2. The terminal checks the entered information in real time and sends it to the server in the appropriate format.

[0357] 3. The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user, which reflects the user's interests and hobbies.

[0358] 4. Once the setup is complete, the server sends a "Setup Complete" message to the terminal, which is displayed to the user.

[0359] Upload palm / face photo and analyze the image

[0360] 1. The user uses the camera function in the app to take a photo of their palm or face and presses the upload button.

[0361] 2. The device converts the uploaded image into a pre-specified format and sends it to the server.

[0362] 3. The server analyzes the image using an image analysis system (libraries such as OpenCV) to identify palm lines and facial features.

[0363] 4. The server creates a list of suitable potential partners based on the analysis results and notifies the user of the list via the terminal.

[0364] Emotion recognition and response adjustment with emotion engine

[0365] 1. When users enter basic information and images, their facial expressions and voice are captured through the built-in camera and microphone.

[0366] 2. The device transmits this data to the server in real time.

[0367] 3. The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (joy, sadness, anger, etc.).

[0368] 4. The server dynamically adjusts the responses of the generated chatbot based on the results of emotion recognition. For example, if the user is nervous, it will display a message such as "Relax."

[0369] Adjusting match selection criteria using an emotion engine

[0370] 1. The server continuously monitors the results of the emotion engine and records the user's emotional state.

[0371] 2. The server uses this emotional data to dynamically adjust the matching algorithm, for example, if the user is excited, it will choose a partner with a calmer personality.

[0372] 3. The server generates a new candidate list based on the adjusted selection criteria and notifies the user via the terminal.

[0373] Matching application and result notification

[0374] 1. The user selects the person of interest from the notified candidate list.

[0375] 2. The device sends the information of the selected person to the server.

[0376] 3. The server accesses the external platform and automatically applies for a match, for example, by sending data using an API.

[0377] 4. The server obtains the matching results and, if successful, automatically generates the date details (date, time, location, content, etc.).

[0378] 5. The server notifies the user of the generated date details through the terminal and automatically adds them to the user's schedule.

[0379] Specific examples

[0380] For example, User A uses the app to perform the following process:

[0381] User A enters and uploads basic information and a photo of their palm into the app.

[0382] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0383] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0384] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0385] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[0386] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0387] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0388] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0389] Prompt Sentence Examples

[0390] Below are some example prompts to input to a generative AI model:

[0391] Describe how users can upload their basic information and a photo of their palm, and how the chatbot will tailor its responses using an emotion engine. Include specific use cases.

[0392] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0393] Step 1:

[0394] The user logs in to the app and enters their basic information (name, age, hobbies, etc.). The input data is entered in a text field. The device checks the entered information in real time and sends it to the server in an appropriate format (e.g., JSON format).

[0395] Input: Basic information such as name, age, hobbies, etc.

[0396] Data processing: Check the input information and convert the format (JSON format)

[0397] Output: Basic information formatted to the server

[0398] Step 2:

[0399] The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user. This chatbot reflects the user's interests and hobbies. Once setup is complete, a "Setup Complete" message is generated.

[0400] Input: Basic formatted information

[0401] Data Computation: Chatbot Generation with Generative AI Models Based on Basic Information

[0402] Output: The generated chatbot, and a "You're all set" message

[0403] Step 3:

[0404] The server sends the generated chatbot information to the device, and the device notifies the user of the "Settings complete" message. The user receives the notification.

[0405] Input: "Settings complete" message, generated chatbot

[0406] Data processing: Sending messages and chatbot information

[0407] Output: Notification with "Setup complete" message

[0408] Step 4:

[0409] Users can use the app's camera to take and upload a photo of their palm or face. The device then converts the image file into a pre-specified format (e.g., PNG, JPEG) and sends it to the server.

[0410] Input: Palm or face photo

[0411] Data processing: Image file format conversion

[0412] Output: Converted image file

[0413] Step 5:

[0414] The server uses an image analysis system (libraries such as OpenCV) to analyze the received image. As a result of the analysis, palm lines and facial features are extracted. Based on this, a list of potential partners suitable for the user is generated.

[0415] Input: Converted image file

[0416] Data calculation: Image analysis (palm lines and facial feature extraction)

[0417] Output: List of potential partners

[0418] Step 6:

[0419] The server sends the generated list of potential partners to the terminal, which notifies the user of the list and displays it.

[0420] Input: candidate list

[0421] Data processing: Sending list information

[0422] Output: Notification and display of candidate list

[0423] Step 7:

[0424] When users enter basic information and images, facial expressions and voices are captured through the built-in camera and microphone, and the device transmits the captured data to a server in real time.

[0425] Input: facial expression and voice data

[0426] Data processing: Real-time data transmission

[0427] Output: Captured data

[0428] Step 8:

[0429] The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (happiness, sadness, anger, etc.) and dynamically adjusts the responses of the generated chatbot based on the analysis results.

[0430] Input: Captured facial and voice data

[0431] Data Computing: Sentiment Analysis

[0432] Output: Tailored chatbot response

[0433] Step 9:

[0434] The server continuously monitors the results of the emotion engine and records the user's emotional state. This emotional data is used to dynamically adjust the matching algorithm.

[0435] Input: Sentiment analysis results

[0436] Data calculation: Adjusting the matching algorithm

[0437] Output: Adjusted match selection criteria

[0438] Step 10:

[0439] The server generates a new list of potential partners based on the adjusted matching selection criteria and notifies the user via the terminal.

[0440] Input: Adjusted match selection criteria

[0441] Data calculation: generating a new list of potential partners

[0442] Output: Notification of new match candidate list

[0443] Step 11:

[0444] The user selects the desired partner from the notified candidate list, and the selection information is sent from the terminal to the server.

[0445] Input: User selects a partner

[0446] Data processing: Sending selected information

[0447] Output: Selection information

[0448] Step 12:

[0449] The server accesses the external platform and automatically applies for a match. Once the application is complete, the matching results are obtained.

[0450] Input: Selection information

[0451] Data calculation: Application to external platform

[0452] Output: Matching results

[0453] Step 13:

[0454] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information in the user's schedule.

[0455] Input: Matching results

[0456] Data Calculation: Generating Date Details

[0457] Output: Date details

[0458] Step 14:

[0459] The server notifies the terminal of the generated date details, which are then displayed to the user, who receives the notification and confirms the details added to the schedule.

[0460] Input: Date Details

[0461] Data processing: Sending detailed information

[0462] Output: Notifications and schedule additions

[0463] (Application example 2)

[0464] 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."

[0465] The problem to be solved by this invention is a system that uses basic information from a user and an image of the palm or face to identify a suitable partner for the user and automatically performs matching. This system can notify the user of details of the date schedule with the identified partner and the matching results. It is also required to provide a more personalized customer service experience by suggesting products and services based on the user's emotional state.

[0466] 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 basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving an image of a palm or face from the user, means for analyzing the received image to identify a suitable partner for the user, means for automatically applying for a match, means for notifying the user of the match result and schedule details, means for proposing products and services based on the image analysis result and emotion recognition result, and means for notifying the user of information on the proposed products and services. This provides a personalized customer service experience based on the user's emotions and basic information, thereby improving user satisfaction.

[0467] "User" refers to any individual or organization that uses this system.

[0468] "Basic information" refers to information including personal data such as the user's name, age, and hobbies.

[0469] A "generative AI chatbot" refers to a dedicated conversational agent that is generated based on basic information about the user.

[0470] "Palm or face image" refers to a digital image of a user's palm or face.

[0471] "Image analysis" refers to the process of extracting features from a received palm or face image and analyzing those features.

[0472] "Emotion recognition" refers to the process of determining a user's emotions from facial expressions and text information.

[0473] "Matching" refers to the process of identifying the most suitable partner for a user based on analyzed information and connecting the user with that partner.

[0474] "Schedule" refers to detailed information such as the date, time, and location of a date that is generated as a result of matching.

[0475] "Product and service proposal" refers to the process of providing optimal products and services to users based on the results of image analysis and emotion recognition.

[0476] "Notification" refers to the action of communicating information to a user.

[0477] An embodiment of the present invention will be described.

[0478] First, the user enters basic information using a device such as a smartphone. This basic information includes personal data such as name, age, and hobbies. The device then sends this basic information to a server. The server uses the received information to create a generative AI chatbot and configures the chatbot specifically for the user. Once configuration is complete, the server sends a completion notification to the user.

[0479] Next, the user takes an image of their palm or face and uploads it to the app. The device then sends the uploaded image to the server, which uses an image analysis system to analyze the palm or facial features, applying algorithms to identify palm lines and facial features. Based on the analysis results, the server identifies suitable partners for the user and generates a list of candidates, which the user is notified of.

[0480] Additionally, when a user enters basic information and an image, the device uses sensors such as a camera to capture the user's facial expressions in real time, and the emotion engine recognizes the emotion from the image. The server flexibly adjusts the chatbot's responses based on the emotion engine's results. For example, if the user is nervous, the chatbot will engage in a conversation designed to relax the user. The emotion engine's results can also be used to adjust the matching selection criteria and identify more suitable partners.

[0481] Furthermore, once the user selects a suggested partner based on the results of image analysis and emotion recognition, the device sends the selection information to the server. The server then accesses an external service platform via the communications network and automatically requests a match. If the request is successful, date details (date, time, location, content, etc.) are generated and set as the user's schedule. This information is then notified to the user via the device.

[0482] In addition, the server will suggest optimal products and services to users based on the results of image analysis and emotion recognition, providing a personalized customer service experience based on the user's emotions and basic information, improving user satisfaction.

[0483] As a concrete example, let's take an example where User A uses the app to perform the following process:

[0484] User A enters and uploads basic information and a photo of their palm into the app.

[0485] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0486] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0487] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0488] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0489] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0490] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0491] An example prompt is:

[0492] "Please enter the following information:

[0493] 1. Name

[0494] 2. Age

[0495] 3. Hobbies

[0496] 4. Palm reading image or face image

[0497] The above is an embodiment of the present invention.

[0498] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0499] Processing steps of the system that realizes the application example

[0500] Step 1:

[0501] A user accesses an application using a device such as a smartphone and enters basic information such as name, age, hobbies, etc. The entered basic information is sent to the server by the device. This is the input data.

[0502] Step 2:

[0503] The server generates a generative AI chatbot based on the received basic information. Specifically, a system analyzes the received data and creates a dialogue agent specifically for the user based on that information. The generated chatbot is stored on the server, and a dialogue model optimized for the user becomes the output data.

[0504] Step 3:

[0505] The user takes a picture of their palm or face using their device and uploads it to the application. The uploaded image data is sent to the server by the device. This image is the input data.

[0506] Step 4:

[0507] The server analyzes the uploaded image. Specifically, it uses an image analysis system (e.g., OpenCV or other image processing libraries) to extract palm or facial features. The results of this feature analysis are output data.

[0508] Step 5:

[0509] The server then applies an algorithm to identify potential partners based on the image analysis results. For example, it can use palm lines and facial features to determine the user's personality and potential compatible partners. The results are then output as a list of potential partners.

[0510] Step 6:

[0511] When a user inputs basic information and images, the device's camera and sensors capture the user's facial expressions in real time and send them to the server. This facial expression data is the input data.

[0512] Step 7:

[0513] The server uses an emotion engine to analyze the user's facial expression data and identify their emotions. The identification results are output data and used to adjust the chatbot's responses.

[0514] Step 8:

[0515] When a user selects a partner from the candidate list, the selection information is sent to the server by the terminal. This selection information is the input data.

[0516] Step 9:

[0517] Based on the selection information, the server accesses an external service platform via a communication network and automatically applies for matching. The matching results are output data.

[0518] Step 10:

[0519] If the matching result is successful, the server automatically generates date details (date, time, location, content, etc.) and saves them as schedule data. This date details information is the output data.

[0520] Step 11:

[0521] The server sends the date details to the user's terminal for notification, which becomes output data and is displayed in the user's application.

[0522] Step 12:

[0523] Finally, the server proposes optimal products and services to the user based on the results of image analysis and emotion recognition. The proposal information is sent to the user's device. This becomes the final output data.

[0524] 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.

[0525] 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.

[0526] 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.

[0527] [Second embodiment]

[0528] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0529] 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.

[0530] 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).

[0531] 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.

[0532] 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.

[0533] 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).

[0534] 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.

[0535] 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.

[0536] 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.

[0537] 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.

[0538] 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.

[0539] 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."

[0540] The system of the present invention receives basic information from a user and generates a dedicated generative AI chatbot based on that information. It then analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also automatically requests a match with the identified partner and notifies the user of the match results and schedule details.

[0541] 1. Entering user information and creating a chatbot

[0542] Users enter their basic information (name, age, hobbies, etc.) into the app.

[0543] The terminal sends this information to the server.

[0544] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[0545] Once the setup is complete, the server will notify the user that the setup is complete.

[0546] 2. Upload palm / face photo and analyze the image

[0547] Users take a photo of their palm or face and upload it to the app.

[0548] The terminal sends the uploaded image to the server.

[0549] The server uses an image analysis system to analyze palm lines and facial features.

[0550] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[0551] 3. Matching application and notification of results

[0552] The user selects the desired partner from the notified candidate list.

[0553] The terminal transmits the selection information to the server.

[0554] The server accesses an external service platform and automatically applies for a match.

[0555] The server checks the matching results, and if successful, generates date details (date, time, location, details, etc.) and adds them to the user's schedule.

[0556] The results and schedule details are notified to the user via the terminal.

[0557] 4. Specific Examples

[0558] For example, User A uses the app to perform the following process:

[0559] User A enters and uploads basic information and a photo of their palm into the app.

[0560] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0561] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0562] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0563] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0564] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0565] By linking the server, terminals, and users, the system is designed to allow users to easily and quickly match with their ideal partner. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[0566] The processing flow will be explained below.

[0567] Step 1:

[0568] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[0569] Step 2:

[0570] The terminal converts the input user information into a data format and transmits it to the server.

[0571] Step 3:

[0572] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[0573] Step 4:

[0574] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[0575] Step 5:

[0576] Users take a photo of their palm or face and upload it to the app.

[0577] Step 6:

[0578] The terminal transmits the uploaded image data to the server.

[0579] Step 7:

[0580] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[0581] Step 8:

[0582] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[0583] Step 9:

[0584] The terminal displays the candidate list to the user.

[0585] Step 10:

[0586] The user checks the list of candidates and selects the person with whom they wish to be matched.

[0587] Step 11:

[0588] The terminal transmits the information of the selected party to the server.

[0589] Step 12:

[0590] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0591] Step 13:

[0592] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0593] Step 14:

[0594] The server sends the matching results and schedule details to the terminal.

[0595] Step 15:

[0596] The terminal notifies and displays the matching results and schedule information to the user.

[0597] This series of processing flows allows users to efficiently match with the most suitable partner with minimal effort.

[0598] Example 1

[0599] 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."

[0600] Conventional matching systems have the problem that users must manually enter their own information to search for a suitable partner, which is a complicated process that takes time and effort. In addition, methods for searching for partners based on palm lines or facial features are not widely used, and their effectiveness is not fully utilized. Another issue is the difficulty of building a system that automatically connects with external service platforms and matches partners.

[0601] 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.

[0602] In this invention, the server includes: means for receiving basic information from a user; means for generating a dedicated generative AI chatbot based on the received basic information; means for receiving palm or facial images from the user; image analysis means for analyzing the received images; means for identifying a suitable partner for the user based on the analyzed characteristics; means for accessing an external service platform via a communication network and automatically applying for a match with the identified partner; and means for notifying the user of the match results and schedule details. This allows users to easily input information and quickly find a suitable partner. Furthermore, analyzing palm and facial features can achieve more accurate matching. Furthermore, automatic collaboration with external services can improve matching efficiency and significantly reduce user effort.

[0603] "User" refers to an individual who uses the system to enter their basic information and upload images of their palm or face to search for a match.

[0604] A "generative AI chatbot" refers to an AI that is generated specifically for a user based on their basic information and provides support through dialogue with the user.

[0605] "Basic information" refers to personal information entered by the user, such as their name, age, hobbies, etc.

[0606] "Palm or face image" refers to a photograph of the palm of the hand or face that a user uploads to the system.

[0607] "Image Analysis Means" refers to the technical means for analyzing the uploaded palm or face image to extract features.

[0608] "Identified partner" refers to a suitable candidate for the user, selected by the system based on the image analysis results and the user's basic information.

[0609] "Communications Network" refers to the Internet and other digital communications means used to send and receive information.

[0610] "External Service Platform" refers to a third-party platform that provides matching or dating services.

[0611] "Matching proposal" refers to the system automatically proposing dates or interactions to suitable partners for the user.

[0612] "Matching result" refers to the other party's response to the matching request.

[0613] "Schedule details" refers to information such as the date, time, location, and content of the date that will be set if the match is successful.

[0614] The present invention is a system that receives basic information from a user, generates a dedicated generative AI chatbot based on that information, and identifies the user's best match by analyzing palm reading or facial images uploaded by the user. Furthermore, the system automatically requests a match with the identified match and notifies the user of the match results and schedule details. Specific hardware and software are used to efficiently implement this process.

[0615] This system mainly consists of the following elements:

[0616] 1. Enter your user information

[0617] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[0618] The device receives this input information and sends it to the server. The basic information is used to generate a generative AI chatbot based on the user's hobbies and interests.

[0619] 2. Chatbot Creation

[0620] Based on the received user information, the server uses generative artificial intelligence (e.g., OpenAI's GPT-4) to generate a chatbot specifically for the user. This chatbot is customized for the user and provides support through dialogue with the user.

[0621] 3. Upload your palm / face photo

[0622] Users take a photo of their palm or face and upload it to the application.

[0623] The device receives the uploaded images and automatically sends them to the server.

[0624] 4. Image Analysis

[0625] The server uses an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze the received palm or face image. Based on the analyzed features, it applies an algorithm to match the user with the best possible partner.

[0626] 5. Identifying and notifying potential matches

[0627] Based on the analysis results, the server identifies the most suitable partner for the user and generates a list of candidates. This list is then notified to the user, allowing the user to select the partner they desire.

[0628] 6. Automatic matching application

[0629] Based on the user's selection, the server accesses an external service platform via a communication network and automatically sends a matching request to the identified person.

[0630] The server checks the match results and, if successful, generates the date details (date, time, location, details, etc.).

[0631] 7. Adding results and schedules

[0632] The server sends the date details to the device and notifies the user, and the date schedule is automatically added to the user's calendar.

[0633] Specific examples of operation

[0634] For example, consider the case where a user enters basic information such as "Taro Tanaka, 35 years old, hobby: reading" and uploads a photo of his palm.

[0635] The device formats this information into JSON format and sends it to the server.

[0636] The server uses OpenAI's GPT-4 to generate a chatbot specifically for Tanaka Taro.

[0637] The server uses the Google Cloud Vision API to analyze the characteristics of the palm lines and select the most suitable partner.

[0638] Next, based on the analysis results, a candidate list (for example, "Candidate A: Yamada Hanako, age 30, hobby: listening to music") is generated and notified to Tanaka Taro.

[0639] When Taro Tanaka selects Hanako Yamada, the server accesses an external dating platform and automatically requests a match.

[0640] If the match is successful, the details of the date (for example, "Date and time: July 10th, Location: Tokyo cafe, Content: Lunchtime") are generated, notified to Taro Tanaka via his device, and the date is automatically added to his calendar.

[0641] Example prompt sentence:

[0642] "You enter some basic information into the app, upload a photo of your palm, and it will then automatically find your ideal match and notify you of date details if a match is made."

[0643] This system is designed to enable users to easily and quickly find the perfect match through collaboration between users, devices, and servers. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[0644] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0645] Step 1:

[0646] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[0647] Input: User's basic information (name, age, hobbies, etc.)

[0648] Output: The terminal checks the input, formats it into JSON format, and sends it to the server.

[0649] Specific operation: For example, enter "Yamada Taro, 30 years old, hobby: cycling" and the device will convert this information into JSON format as shown below.

[0650] json

[0651] {

[0652] "name": "Yamada Taro",

[0653] "age": 30,

[0654] "hobbies": ["cycling"]

[0655] }

[0656] This JSON data is sent to the server.

[0657] Step 2:

[0658] The server generates a dedicated chatbot using generative artificial intelligence (e.g., OpenAI's GPT-4) based on the received user information.

[0659] Input: User basic information (JSON format)

[0660] Output: Chatbot generation result (user-specific bot)

[0661] Specific operation: The server analyzes the received JSON data and calls a generative AI API based on it to generate a chatbot for the user. The chatbot reflects the user's preferences and interests.

[0662] Step 3:

[0663] The server sends a notification of completion of the generated chatbot configuration to the terminal, and the terminal notifies the user of the same.

[0664] Input: Chatbot generation result (user-specific bot)

[0665] Output: Notification of successful setup

[0666] Specific operation: The server notifies the device that the chatbot configuration is complete, and the device displays a message to the user such as "Chatbot configuration is complete."

[0667] Step 4:

[0668] Users take a photo of their palm or face and upload it to the application.

[0669] Input: Palm or face photo (image file)

[0670] Output: Image file uploaded to the device

[0671] What happens: A user takes a photo of their palm using their smartphone camera and uploads it through the application.

[0672] Step 5:

[0673] The terminal sends the uploaded image to the server.

[0674] Input: Uploaded image file

[0675] Output: Image data sent to the server

[0676] Specific operation: The device receives the image file, encodes it as binary data, and sends it to the server.

[0677] Step 6:

[0678] The server sends the received images to an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze palm lines and facial features.

[0679] Input: Image data (binary)

[0680] Output: Image analysis results (palm reading and facial feature data)

[0681] Specific operation: The server calls the image analysis API, analyzes the received image data, and obtains information such as the length and position of the palm lines, facial feature points, etc. The analysis results are saved in JSON format.

[0682] Step 7:

[0683] Based on the analysis results, the server applies an algorithm to select the most suitable partner to provide to the user and generates a list of candidates.

[0684] Input: Image analysis results (palm reading and facial feature data)

[0685] Output: Candidate list

[0686] Specific operation: The server analyzes the analysis results and selects suitable candidates according to an algorithm. For example, it generates a list containing information such as "Candidate B: Hanako Sato, 28 years old, hobby: trekking."

[0687] Step 8:

[0688] The server sends the candidate list to the terminal and notifies the user.

[0689] Input: Candidate list

[0690] Output: Notification of candidate list to terminal

[0691] Specific operation: The server sends the generated candidate list to the terminal, and the terminal displays it to the user in the form of "A list of the best possible candidates has been generated."

[0692] Step 9:

[0693] The user selects the desired partner from the notified candidate list.

[0694] Input: Candidate list

[0695] Output: Selected contact information

[0696] Specific operation: The user selects the desired partner from the displayed list of candidates, for example, selecting "Hanako Sato."

[0697] Step 10:

[0698] The terminal transmits the selection information to the server.

[0699] Input: User selection information

[0700] Output: Sends the selection to the server

[0701] Specific operation: The device converts the information selected by the user into JSON format and sends it to the server.

[0702] Step 11:

[0703] The server accesses an external service platform and automatically applies for a match.

[0704] Input: User selection information

[0705] Output: Matching application results

[0706] Specific operation: The server uses an external API to request a match with the selected partner and obtains the result of success or failure.

[0707] Step 12:

[0708] The server checks the match results and generates the date details if successful.

[0709] Input: Matching application results

[0710] Output: Date details (date, time, location, details, etc.)

[0711] Specific operation: If the match is successful, the server generates date details such as "Date and time: August 15th, Location: Tokyo cafe, Content: Lunchtime."

[0712] Step 13:

[0713] The server sends the date details to the terminal, which notifies the user and automatically adds them to the schedule.

[0714] Input: Date details (date, time, location, details, etc.)

[0715] Output: Notification to device and addition to user's calendar

[0716] Specific operation: The server sends the date details to the device, and the device sends a notification to the user saying "The date has been confirmed." The date information is also automatically added to the user's calendar.

[0717] (Application example 1)

[0718] 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."

[0719] Conventional AI chatbot systems based on user information are limited to simply sending messages to users, making it difficult to provide services optimized to individual users' needs and preferences. Even with the introduction of image analysis functions, advanced customization based on users' lifestyles and specific situations remains a challenge. In particular, there is no system that can individually optimize the riding experience inside an autonomous vehicle, making it necessary to address these challenges.

[0720] 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.

[0721] In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving palm or facial images from the user, means for analyzing the received images to identify a suitable partner for the user, means for automatically requesting a match with the identified partner, means for notifying the user of the match results and schedule details, and means for receiving the user's basic information and facial image, generating a driverbot equipped with a dedicated generative AI, and providing entertainment and relaxation support based on the user's preferences and facial data, thereby enabling users to individually optimize their riding experience in an autonomous vehicle and receive personalized entertainment and relaxation support.

[0722] "User basic information" refers to personal data such as the user's name, age, hobbies, and preferences.

[0723] A "generative AI chatbot" is an interactive AI system that is automatically generated based on basic information received from the user and communicates with the user.

[0724] "Palm or face image" refers to image data such as a photo of the user's palm or face.

[0725] "Image analysis" refers to the process of analyzing received palm or facial images to extract features and patterns to derive specific information.

[0726] "Identifying suitable partners" refers to the process of finding the most suitable partner for a user based on image analysis and basic information.

[0727] A "matching request" refers to a request to contact an automatically identified person and build a certain relationship.

[0728] "Notification" refers to the act of informing users of important information such as matching results and schedule details.

[0729] "DriverBot" is a dedicated AI driver that is generated based on the user's basic information and facial image, and provides entertainment and relaxation support according to the user's hobbies and preferences.

[0730] "Entertainment" refers to entertainment such as music, videos, and games provided in the autonomous vehicle.

[0731] "Relaxation support" refers to services and functions that allow users to relax inside an autonomous vehicle.

[0732] The system of the present invention generates an interactive AI chatbot and a driverbot that are optimal for a user based on the user's basic information and facial image. Detailed embodiments of this system are described below.

[0733] First, a user accesses the application using a device (e.g., a smartphone). The application obtains basic information from the user, such as name, age, hobbies, and favorite music, and then asks the user to upload an image of their palm or face. The hardware used in this case includes a smartphone with a camera, and the software used includes an application and an image processing library (e.g., OpenCV).

[0734] The device sends the acquired basic information and facial image to a server, which then creates a generative AI chatbot based on the information received. The software used includes AI models (e.g., TensorFlow) and image analysis algorithms.

[0735] The server analyzes the facial image and performs image analysis to identify the user's facial features and expressions. This process extracts features based on the user's facial data. Based on the analysis results, a driver bot is generated that best suits the user's preferences and needs.

[0736] The generated driver bot will individually optimize the user's riding experience based on user information and facial data. For example, it can play music that matches the user's preferences and provide entertainment tailored to the user's hobbies. The driver bot also has a relaxation support function, providing relaxing music and guidance.

[0737] Furthermore, the generated driver bot will suggest entertainment and relaxation support to the user and carry out them upon request. This process includes customization based on the user's basic information and facial data, allowing the user to maximize their riding experience in the autonomous vehicle.

[0738] (Example)

[0739] For example, a user can use an application to input their name, age, hobbies, and favorite music, and upload a facial image. This information is sent from the device to a server. The server then creates a generative AI chatbot and driver bot specifically for the user based on the received basic information and facial image. This driver bot then plays music and provides relaxation support according to the user's preferences. As a specific example, if the user likes classical music, the application can be set to play classical music in the car.

[0740] (Example of a prompt)

[0741] Use the following prompt sentence to perform processing based on an artificial intelligence model.

[0742] "We want a personal driver AI driver bot to be generated based on the basic information and facial photo provided by the user, and provide optimal car entertainment and relaxation support."

[0743] In this way, the system can utilize the user's basic information and facial image to generate a dedicated generative AI driverbot that can provide individually optimized entertainment and relaxation support.

[0744] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0745] Step 1: Enter your user information

[0746] A user uses a device to input their basic information (such as name, age, hobbies, and favorite music) into the application. The user also takes a picture of their face using a camera-equipped device and uploads it. The input information and face image are sent to the server via the device. The input here is the user's basic information and face image, and the output is user data sent to the server.

[0747] Step 2: Receiving user information and generating an AI chatbot

[0748] The server receives the user's basic information and facial image sent from the device. Based on the received information, the server uses a generative AI model to generate a generative AI chatbot dedicated to the user. The data processing in this process involves analyzing the user data and generating a chatbot based on the AI ​​model. The output is the generated chatbot.

[0749] Step 3: Analyze the facial image

[0750] The server analyzes the received facial image using an image analysis algorithm (e.g., OpenCV). Specifically, it uses facial recognition technology to extract facial features in the image and use them to identify the user's individual characteristics. The input to this process is the facial image, and the output is the analyzed facial feature data.

[0751] Step 4: Create a Driver Bot

[0752] The server generates a dedicated generative AI driver bot based on the user's basic information and facial feature data. The generative AI model used is input with a prompt statement: "Based on the basic information and facial photo provided by the user, I would like a personal driver AI driver bot to provide optimal car entertainment and relaxation support." The driver bot is constructed based on this statement. The input in this process is basic information and facial feature data, and the output is the generated driver bot.

[0753] Step 5: Providing customized entertainment and relaxation support

[0754] The generated driver bot provides optimal entertainment and relaxation support based on the user's basic information and facial features. Specific actions include playing the user's favorite music, providing relaxation music, and providing guidance. The input to this process is the driver bot and its configuration data, and the output is the provision of customized services.

[0755] Step 6: Get user feedback and update the system

[0756] Users provide feedback on the entertainment and relaxation support provided. This feedback is sent from the device to the server, which then uses this information to update the driver bot's settings and generative AI model. The input to this process is the user's feedback data, and the output is an improved driver bot and model.

[0757] Through the above steps, the system of the present invention uses the user's basic information and facial image to generate an interactive AI chatbot and driverbot that are optimal for the user, and is able to provide individually optimized entertainment and relaxation support.

[0758] 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.

[0759] The system of the present invention receives basic information from the user and generates a dedicated generative AI chatbot based on that information. It also analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also combines an emotion engine that recognizes the user's emotions to improve matching accuracy and user experience. It automatically applies for a match with the most suitable partner and notifies the user of the matching results and schedule details.

[0760] 1. Entering user information and creating a chatbot

[0761] Users enter their basic information (name, age, hobbies, etc.) into the app.

[0762] The terminal sends this information to the server.

[0763] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[0764] Once the setup is complete, the server will notify the user that the setup is complete.

[0765] 2. Upload palm / face photo and analyze the image

[0766] Users take a photo of their palm or face and upload it to the app.

[0767] The terminal sends the uploaded image to the server.

[0768] The server uses an image analysis system to analyze palm lines and facial features.

[0769] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[0770] 3. Emotion recognition and response adjustment using an emotion engine

[0771] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text.

[0772] The server adjusts the chatbot's responses based on the emotion recognition results of the emotion engine. For example, if the user is nervous, the server will respond in a way that helps them relax.

[0773] 4. Adjusting match selection criteria using an emotion engine

[0774] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine. For example, if the user is excited, it will select a partner with a calmer personality, achieving optimal matching according to the user's emotional state.

[0775] 5. Matching application and result notification

[0776] The user selects the desired partner from the notified candidate list.

[0777] The terminal transmits the selection information to the server.

[0778] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0779] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0780] The results and schedule details are notified and displayed to the user via the terminal.

[0781] 6. Specific Examples

[0782] For example, User A uses the app to perform the following process:

[0783] User A enters and uploads basic information and a photo of their palm into the app.

[0784] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0785] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0786] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0787] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[0788] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0789] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0790] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0791] By linking the server, terminal, user, and emotion engine, this system can appropriately adjust dialogue and matching criteria according to the user's emotional state, efficiently matching the optimal partner with minimal effort.

[0792] The processing flow will be explained below.

[0793] Step 1:

[0794] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[0795] Step 2:

[0796] The terminal converts the input user information into a data format and transmits it to the server.

[0797] Step 3:

[0798] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[0799] Step 4:

[0800] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[0801] Step 5:

[0802] Users take a photo of their palm or face and upload it to the app.

[0803] Step 6:

[0804] The terminal transmits the uploaded image data to the server.

[0805] Step 7:

[0806] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[0807] Step 8:

[0808] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[0809] Step 9:

[0810] The terminal displays the candidate list to the user.

[0811] Step 10:

[0812] The user checks the list of candidates and selects the person with whom they wish to be matched.

[0813] Step 11:

[0814] The terminal transmits the information of the selected party to the server.

[0815] Step 12:

[0816] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[0817] Step 13:

[0818] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[0819] Step 14:

[0820] The server sends the matching results and schedule details to the terminal.

[0821] Step 15:

[0822] The terminal notifies and displays the matching results and schedule information to the user.

[0823] Step 16:

[0824] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text, thereby understanding the user's psychological state.

[0825] Step 17:

[0826] The server adjusts the chatbot's responses based on the results of the emotion engine. For example, if the user is nervous, the server will respond in a way that relaxes them.

[0827] Step 18:

[0828] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine, and creates a list of the most suitable partners according to the user's emotional state.

[0829] Step 19:

[0830] The server selects a partner based on the newly adjusted criteria, regenerates the candidate list, and sends this list to the terminal.

[0831] Step 20:

[0832] The terminal displays the regenerated candidate list to the user.

[0833] This series of processes allows for more accurate and satisfying matching by reflecting the user's emotional state.

[0834] Example 2

[0835] 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."

[0836] Conventional matching systems only identify potential partners based on basic user information and image analysis, and do not consider the user's emotional state. This results in problems such as insufficient matching accuracy and user experience with partners who are suited to the user's emotions.

[0837] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving images from a user, means for analyzing the received images to identify a partner suitable for the user, means for recognizing emotions from the user's facial expressions and text, means for adjusting the chatbot's response content based on the emotion recognition result, means for adjusting the match selection criteria based on the emotion recognition result, means for automatically applying for matching with the identified partner, and means for notifying the user of the matching result and schedule details. This makes it possible to identify the most suitable partner according to the user's emotional state, improving matching accuracy and user experience.

[0838] A "user" is an individual who uses the system to input and upload their own basic information and images.

[0839] "Basic information" refers to profile data such as the user's name, age, hobbies, etc.

[0840] A "generative AI chatbot" is an AI program that is customized based on the user's basic information and engages in conversation.

[0841] "Image" refers to a photograph of your palm or face uploaded by you.

[0842] "Image analysis" is the process of processing uploaded image data to identify palm lines and facial features.

[0843] "Partner" refers to a potential match identified by the system.

[0844] "Emotion recognition" is the process of determining a user's emotional state from their facial expressions and text.

[0845] "Adjusting response content" refers to dynamically changing the chatbot's statements and actions based on the emotion recognition results.

[0846] "Matching selection criteria" refers to the criteria for selecting the most suitable partner based on the user's emotional state.

[0847] "Matching application" is the process by which the system automatically proposes a date or interaction to a identified person.

[0848] "Schedule details" refers to information such as the date, time, location, and content of a date or event that is generated if a match is successful.

[0849] "External Platform" refers to other services on a communications network that the system accesses.

[0850] MODE FOR CARRYING OUT THE INVENTION

[0851] The system of the present invention receives basic information and images from users, generates a generative AI chatbot, recognizes the user's emotions, and matches them with the most suitable partner. The main roles of this system are played by the user, the terminal, and the server.

[0852] Hardware and software used

[0853] User device: A device used by a user, such as a smartphone, tablet, or PC.

[0854] Server: A central server handles data processing, generative artificial intelligence, image analysis, and emotion recognition.

[0855] Generative artificial intelligence (AI) model: An AI model that generates a chatbot based on basic user information.

[0856] Image analysis system: Uses image processing libraries such as OpenCV to analyze palm lines and facial features.

[0857] Emotion recognition engine: Uses emotion analysis APIs such as IBM Watson to recognize emotions from user facial expressions and text.

[0858] Entering user information and generating a chatbot

[0859] 1. The user enters their basic information (name, age, hobbies, etc.) into the app on their device.

[0860] 2. The terminal checks the entered information in real time and sends it to the server in the appropriate format.

[0861] 3. The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user, which reflects the user's interests and hobbies.

[0862] 4. Once the setup is complete, the server sends a "Setup Complete" message to the terminal, which is displayed to the user.

[0863] Upload palm / face photo and analyze the image

[0864] 1. The user uses the camera function in the app to take a photo of their palm or face and presses the upload button.

[0865] 2. The device converts the uploaded image into a pre-specified format and sends it to the server.

[0866] 3. The server analyzes the image using an image analysis system (libraries such as OpenCV) to identify palm lines and facial features.

[0867] 4. The server creates a list of suitable potential partners based on the analysis results and notifies the user of the list via the terminal.

[0868] Emotion recognition and response adjustment with emotion engine

[0869] 1. When users enter basic information and images, their facial expressions and voice are captured through the built-in camera and microphone.

[0870] 2. The device transmits this data to the server in real time.

[0871] 3. The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (joy, sadness, anger, etc.).

[0872] 4. The server dynamically adjusts the responses of the generated chatbot based on the results of emotion recognition. For example, if the user is nervous, it will display a message such as "Relax."

[0873] Adjusting match selection criteria using an emotion engine

[0874] 1. The server continuously monitors the results of the emotion engine and records the user's emotional state.

[0875] 2. The server uses this emotional data to dynamically adjust the matching algorithm, for example, if the user is excited, it will choose a partner with a calmer personality.

[0876] 3. The server generates a new candidate list based on the adjusted selection criteria and notifies the user via the terminal.

[0877] Matching application and result notification

[0878] 1. The user selects the person of interest from the notified candidate list.

[0879] 2. The device sends the information of the selected person to the server.

[0880] 3. The server accesses the external platform and automatically applies for a match, for example, by sending data using an API.

[0881] 4. The server obtains the matching results and, if successful, automatically generates the date details (date, time, location, content, etc.).

[0882] 5. The server notifies the user of the generated date details through the terminal and automatically adds them to the user's schedule.

[0883] Specific examples

[0884] For example, User A uses the app to perform the following process:

[0885] User A enters and uploads basic information and a photo of their palm into the app.

[0886] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0887] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0888] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0889] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[0890] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0891] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0892] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0893] Prompt Sentence Examples

[0894] Below are some example prompts to input to a generative AI model:

[0895] Describe how users can upload their basic information and a photo of their palm, and how the chatbot will tailor its responses using an emotion engine. Include specific use cases.

[0896] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0897] Step 1:

[0898] The user logs in to the app and enters their basic information (name, age, hobbies, etc.). The input data is entered in a text field. The device checks the entered information in real time and sends it to the server in an appropriate format (e.g., JSON format).

[0899] Input: Basic information such as name, age, hobbies, etc.

[0900] Data processing: Check the input information and convert the format (JSON format)

[0901] Output: Basic information formatted to the server

[0902] Step 2:

[0903] The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user. This chatbot reflects the user's interests and hobbies. Once setup is complete, a "Setup Complete" message is generated.

[0904] Input: Basic formatted information

[0905] Data Computation: Chatbot Generation with Generative AI Models Based on Basic Information

[0906] Output: The generated chatbot, and a "You're all set" message

[0907] Step 3:

[0908] The server sends the generated chatbot information to the device, and the device notifies the user of the "Settings complete" message. The user receives the notification.

[0909] Input: "Settings complete" message, generated chatbot

[0910] Data processing: Sending messages and chatbot information

[0911] Output: Notification with "Setup complete" message

[0912] Step 4:

[0913] Users can use the app's camera to take and upload a photo of their palm or face. The device then converts the image file into a pre-specified format (e.g., PNG, JPEG) and sends it to the server.

[0914] Input: Palm or face photo

[0915] Data processing: Image file format conversion

[0916] Output: Converted image file

[0917] Step 5:

[0918] The server uses an image analysis system (libraries such as OpenCV) to analyze the received image. As a result of the analysis, palm lines and facial features are extracted. Based on this, a list of potential partners suitable for the user is generated.

[0919] Input: Converted image file

[0920] Data calculation: Image analysis (palm lines and facial feature extraction)

[0921] Output: List of potential partners

[0922] Step 6:

[0923] The server sends the generated list of potential partners to the terminal, which notifies the user of the list and displays it.

[0924] Input: candidate list

[0925] Data processing: Sending list information

[0926] Output: Notification and display of candidate list

[0927] Step 7:

[0928] When users enter basic information and images, facial expressions and voices are captured through the built-in camera and microphone, and the device transmits the captured data to a server in real time.

[0929] Input: facial expression and voice data

[0930] Data processing: Real-time data transmission

[0931] Output: Captured data

[0932] Step 8:

[0933] The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (happiness, sadness, anger, etc.) and dynamically adjusts the responses of the generated chatbot based on the analysis results.

[0934] Input: Captured facial and voice data

[0935] Data Computing: Sentiment Analysis

[0936] Output: Tailored chatbot response

[0937] Step 9:

[0938] The server continuously monitors the results of the emotion engine and records the user's emotional state. This emotional data is used to dynamically adjust the matching algorithm.

[0939] Input: Sentiment analysis results

[0940] Data calculation: Adjusting the matching algorithm

[0941] Output: Adjusted match selection criteria

[0942] Step 10:

[0943] The server generates a new list of potential partners based on the adjusted matching selection criteria and notifies the user via the terminal.

[0944] Input: Adjusted match selection criteria

[0945] Data calculation: generating a new list of potential partners

[0946] Output: Notification of new match candidate list

[0947] Step 11:

[0948] The user selects the desired partner from the notified candidate list, and the selection information is sent from the terminal to the server.

[0949] Input: User selects a partner

[0950] Data processing: Sending selected information

[0951] Output: Selection information

[0952] Step 12:

[0953] The server accesses the external platform and automatically applies for a match. Once the application is complete, the matching results are obtained.

[0954] Input: Selection information

[0955] Data calculation: Application to external platform

[0956] Output: Matching results

[0957] Step 13:

[0958] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information in the user's schedule.

[0959] Input: Matching results

[0960] Data Calculation: Generating Date Details

[0961] Output: Date details

[0962] Step 14:

[0963] The server notifies the terminal of the generated date details, which are then displayed to the user, who receives the notification and confirms the details added to the schedule.

[0964] Input: Date Details

[0965] Data processing: Sending detailed information

[0966] Output: Notifications and schedule additions

[0967] (Application example 2)

[0968] 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."

[0969] The problem to be solved by this invention is a system that uses basic information from a user and an image of the palm or face to identify a suitable partner for the user and automatically performs matching. This system can notify the user of details of the date schedule with the identified partner and the matching results. It is also required to provide a more personalized customer service experience by suggesting products and services based on the user's emotional state.

[0970] 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 basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving an image of a palm or face from the user, means for analyzing the received image to identify a suitable partner for the user, means for automatically applying for a match, means for notifying the user of the match result and schedule details, means for proposing products and services based on the image analysis result and emotion recognition result, and means for notifying the user of information on the proposed products and services. This provides a personalized customer service experience based on the user's emotions and basic information, thereby improving user satisfaction.

[0971] "User" refers to any individual or organization that uses this system.

[0972] "Basic information" refers to information including personal data such as the user's name, age, and hobbies.

[0973] A "generative AI chatbot" refers to a dedicated conversational agent that is generated based on basic information about the user.

[0974] "Palm or face image" refers to a digital image of a user's palm or face.

[0975] "Image analysis" refers to the process of extracting features from a received palm or face image and analyzing those features.

[0976] "Emotion recognition" refers to the process of determining a user's emotions from facial expressions and text information.

[0977] "Matching" refers to the process of identifying the most suitable partner for a user based on analyzed information and connecting the user with that partner.

[0978] "Schedule" refers to detailed information such as the date, time, and location of a date that is generated as a result of matching.

[0979] "Product and service proposal" refers to the process of providing optimal products and services to users based on the results of image analysis and emotion recognition.

[0980] "Notification" refers to the action of communicating information to a user.

[0981] An embodiment of the present invention will be described.

[0982] First, the user enters basic information using a device such as a smartphone. This basic information includes personal data such as name, age, and hobbies. The device then sends this basic information to a server. The server uses the received information to create a generative AI chatbot and configures the chatbot specifically for the user. Once configuration is complete, the server sends a completion notification to the user.

[0983] Next, the user takes an image of their palm or face and uploads it to the app. The device then sends the uploaded image to the server, which uses an image analysis system to analyze the palm or facial features, applying algorithms to identify palm lines and facial features. Based on the analysis results, the server identifies suitable partners for the user and generates a list of candidates, which the user is notified of.

[0984] Additionally, when a user enters basic information and an image, the device uses sensors such as a camera to capture the user's facial expressions in real time, and the emotion engine recognizes the emotion from the image. The server flexibly adjusts the chatbot's responses based on the emotion engine's results. For example, if the user is nervous, the chatbot will engage in a conversation designed to relax the user. The emotion engine's results can also be used to adjust the matching selection criteria and identify more suitable partners.

[0985] Furthermore, once the user selects a suggested partner based on the results of image analysis and emotion recognition, the device sends the selection information to the server. The server then accesses an external service platform via the communications network and automatically requests a match. If the request is successful, date details (date, time, location, content, etc.) are generated and set as the user's schedule. This information is then notified to the user via the device.

[0986] In addition, the server will suggest optimal products and services to users based on the results of image analysis and emotion recognition, providing a personalized customer service experience based on the user's emotions and basic information, improving user satisfaction.

[0987] As a concrete example, let's take an example where User A uses the app to perform the following process:

[0988] User A enters and uploads basic information and a photo of their palm into the app.

[0989] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[0990] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[0991] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[0992] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[0993] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[0994] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[0995] An example prompt is:

[0996] "Please enter the following information:

[0997] 1. Name

[0998] 2. Age

[0999] 3. Hobbies

[1000] 4. Palm reading image or face image

[1001] The above is an embodiment of the present invention.

[1002] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1003] Processing steps of the system that realizes the application example

[1004] Step 1:

[1005] A user accesses an application using a device such as a smartphone and enters basic information such as name, age, hobbies, etc. The entered basic information is sent to the server by the device. This is the input data.

[1006] Step 2:

[1007] The server generates a generative AI chatbot based on the received basic information. Specifically, a system analyzes the received data and creates a dialogue agent specifically for the user based on that information. The generated chatbot is stored on the server, and a dialogue model optimized for the user becomes the output data.

[1008] Step 3:

[1009] The user takes a picture of their palm or face using their device and uploads it to the application. The uploaded image data is sent to the server by the device. This image is the input data.

[1010] Step 4:

[1011] The server analyzes the uploaded image. Specifically, it uses an image analysis system (e.g., OpenCV or other image processing libraries) to extract palm or facial features. The results of this feature analysis are output data.

[1012] Step 5:

[1013] The server then applies an algorithm to identify potential partners based on the image analysis results. For example, it can use palm lines and facial features to determine the user's personality and potential compatible partners. The results are then output as a list of potential partners.

[1014] Step 6:

[1015] When a user inputs basic information and images, the device's camera and sensors capture the user's facial expressions in real time and send them to the server. This facial expression data is the input data.

[1016] Step 7:

[1017] The server uses an emotion engine to analyze the user's facial expression data and identify their emotions. The identification results are output data and used to adjust the chatbot's responses.

[1018] Step 8:

[1019] When a user selects a partner from the candidate list, the selection information is sent to the server by the terminal. This selection information is the input data.

[1020] Step 9:

[1021] Based on the selection information, the server accesses an external service platform via a communication network and automatically applies for matching. The matching results are output data.

[1022] Step 10:

[1023] If the matching result is successful, the server automatically generates date details (date, time, location, content, etc.) and saves them as schedule data. This date details information is the output data.

[1024] Step 11:

[1025] The server sends the date details to the user's terminal for notification, which becomes output data and is displayed in the user's application.

[1026] Step 12:

[1027] Finally, the server proposes optimal products and services to the user based on the results of image analysis and emotion recognition. The proposal information is sent to the user's device. This becomes the final output data.

[1028] 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.

[1029] 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.

[1030] 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.

[1031] [Third embodiment]

[1032] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1033] 5, the data processing system 310 includes the data processing device 12 and a headset type terminal 314. An example of the data processing device 12 is a server.

[1034] 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).

[1035] 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.

[1036] 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.

[1037] 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).

[1038] 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.

[1039] 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.

[1040] 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.

[1041] 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.

[1042] 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.

[1043] 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."

[1044] The system of the present invention receives basic information from a user and generates a dedicated generative AI chatbot based on that information. It then analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also automatically requests a match with the identified partner and notifies the user of the match results and schedule details.

[1045] 1. Entering user information and creating a chatbot

[1046] Users enter their basic information (name, age, hobbies, etc.) into the app.

[1047] The terminal sends this information to the server.

[1048] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[1049] Once the setup is complete, the server will notify the user that the setup is complete.

[1050] 2. Upload palm / face photo and analyze the image

[1051] Users take a photo of their palm or face and upload it to the app.

[1052] The terminal sends the uploaded image to the server.

[1053] The server uses an image analysis system to analyze palm lines and facial features.

[1054] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[1055] 3. Matching application and notification of results

[1056] The user selects the desired partner from the notified candidate list.

[1057] The terminal transmits the selection information to the server.

[1058] The server accesses an external service platform and automatically applies for a match.

[1059] The server checks the matching results, and if successful, generates date details (date, time, location, details, etc.) and adds them to the user's schedule.

[1060] The results and schedule details are notified to the user via the terminal.

[1061] 4. Specific Examples

[1062] For example, User A uses the app to perform the following process:

[1063] User A enters and uploads basic information and a photo of their palm into the app.

[1064] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1065] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1066] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1067] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1068] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1069] By linking the server, terminals, and users, the system is designed to allow users to easily and quickly match with their ideal partner. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[1070] The processing flow will be explained below.

[1071] Step 1:

[1072] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[1073] Step 2:

[1074] The terminal converts the input user information into a data format and transmits it to the server.

[1075] Step 3:

[1076] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[1077] Step 4:

[1078] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[1079] Step 5:

[1080] Users take a photo of their palm or face and upload it to the app.

[1081] Step 6:

[1082] The terminal transmits the uploaded image data to the server.

[1083] Step 7:

[1084] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[1085] Step 8:

[1086] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[1087] Step 9:

[1088] The terminal displays the candidate list to the user.

[1089] Step 10:

[1090] The user checks the list of candidates and selects the person with whom they wish to be matched.

[1091] Step 11:

[1092] The terminal transmits the information of the selected party to the server.

[1093] Step 12:

[1094] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1095] Step 13:

[1096] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1097] Step 14:

[1098] The server sends the matching results and schedule details to the terminal.

[1099] Step 15:

[1100] The terminal notifies and displays the matching results and schedule information to the user.

[1101] This series of processing flows allows users to efficiently match with the most suitable partner with minimal effort.

[1102] Example 1

[1103] 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."

[1104] Conventional matching systems have the problem that users must manually enter their own information to search for a suitable partner, which is a complicated process that takes time and effort. In addition, methods for searching for partners based on palm lines or facial features are not widely used, and their effectiveness is not fully utilized. Another issue is the difficulty of building a system that automatically connects with external service platforms and matches partners.

[1105] 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.

[1106] In this invention, the server includes: means for receiving basic information from a user; means for generating a dedicated generative AI chatbot based on the received basic information; means for receiving palm or facial images from the user; image analysis means for analyzing the received images; means for identifying a suitable partner for the user based on the analyzed characteristics; means for accessing an external service platform via a communication network and automatically applying for a match with the identified partner; and means for notifying the user of the match results and schedule details. This allows users to easily input information and quickly find a suitable partner. Furthermore, analyzing palm and facial features can achieve more accurate matching. Furthermore, automatic collaboration with external services can improve matching efficiency and significantly reduce user effort.

[1107] "User" refers to an individual who uses the system to enter their basic information and upload images of their palm or face to search for a match.

[1108] A "generative AI chatbot" refers to an AI that is generated specifically for a user based on their basic information and provides support through dialogue with the user.

[1109] "Basic information" refers to personal information entered by the user, such as their name, age, hobbies, etc.

[1110] "Palm or face image" refers to a photograph of the palm of the hand or face that a user uploads to the system.

[1111] "Image Analysis Means" refers to the technical means for analyzing the uploaded palm or face image to extract features.

[1112] "Identified partner" refers to a suitable candidate for the user, selected by the system based on the image analysis results and the user's basic information.

[1113] "Communications Network" refers to the Internet and other digital communications means used to send and receive information.

[1114] "External Service Platform" refers to a third-party platform that provides matching or dating services.

[1115] "Matching proposal" refers to the system automatically proposing dates or interactions to suitable partners for the user.

[1116] "Matching result" refers to the other party's response to the matching request.

[1117] "Schedule details" refers to information such as the date, time, location, and content of the date that will be set if the match is successful.

[1118] The present invention is a system that receives basic information from a user, generates a dedicated generative AI chatbot based on that information, and identifies the user's best match by analyzing palm reading or facial images uploaded by the user. Furthermore, the system automatically requests a match with the identified match and notifies the user of the match results and schedule details. Specific hardware and software are used to efficiently implement this process.

[1119] This system mainly consists of the following elements:

[1120] 1. Enter your user information

[1121] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[1122] The device receives this input information and sends it to the server. The basic information is used to generate a generative AI chatbot based on the user's hobbies and interests.

[1123] 2. Chatbot Creation

[1124] Based on the received user information, the server uses generative artificial intelligence (e.g., OpenAI's GPT-4) to generate a chatbot specifically for the user. This chatbot is customized for the user and provides support through dialogue with the user.

[1125] 3. Upload your palm / face photo

[1126] Users take a photo of their palm or face and upload it to the application.

[1127] The device receives the uploaded images and automatically sends them to the server.

[1128] 4. Image Analysis

[1129] The server uses an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze the received palm or face image. Based on the analyzed features, it applies an algorithm to match the user with the best possible partner.

[1130] 5. Identifying and notifying potential matches

[1131] Based on the analysis results, the server identifies the most suitable partner for the user and generates a list of candidates. This list is then notified to the user, allowing the user to select the partner they desire.

[1132] 6. Automatic matching application

[1133] Based on the user's selection, the server accesses an external service platform via a communication network and automatically sends a matching request to the identified person.

[1134] The server checks the match results and, if successful, generates the date details (date, time, location, details, etc.).

[1135] 7. Adding results and schedules

[1136] The server sends the date details to the device and notifies the user, and the date schedule is automatically added to the user's calendar.

[1137] Specific examples of operation

[1138] For example, consider the case where a user enters basic information such as "Taro Tanaka, 35 years old, hobby: reading" and uploads a photo of his palm.

[1139] The device formats this information into JSON format and sends it to the server.

[1140] The server uses OpenAI's GPT-4 to generate a chatbot specifically for Tanaka Taro.

[1141] The server uses the Google Cloud Vision API to analyze the characteristics of the palm lines and select the most suitable partner.

[1142] Next, based on the analysis results, a candidate list (for example, "Candidate A: Yamada Hanako, age 30, hobby: listening to music") is generated and notified to Tanaka Taro.

[1143] When Taro Tanaka selects Hanako Yamada, the server accesses an external dating platform and automatically requests a match.

[1144] If the match is successful, the details of the date (for example, "Date and time: July 10th, Location: Tokyo cafe, Content: Lunchtime") are generated, notified to Taro Tanaka via his device, and the date is automatically added to his calendar.

[1145] Example prompt sentence:

[1146] "You enter some basic information into the app, upload a photo of your palm, and it will then automatically find your ideal match and notify you of date details if a match is made."

[1147] This system is designed to enable users to easily and quickly find the perfect match through collaboration between users, devices, and servers. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[1148] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1149] Step 1:

[1150] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[1151] Input: User's basic information (name, age, hobbies, etc.)

[1152] Output: The terminal checks the input, formats it into JSON format, and sends it to the server.

[1153] Specific operation: For example, enter "Yamada Taro, 30 years old, hobby: cycling" and the device will convert this information into JSON format as shown below.

[1154] json

[1155] {

[1156] "name": "Yamada Taro",

[1157] "age": 30,

[1158] "hobbies": ["cycling"]

[1159] }

[1160] This JSON data is sent to the server.

[1161] Step 2:

[1162] The server generates a dedicated chatbot using generative artificial intelligence (e.g., OpenAI's GPT-4) based on the received user information.

[1163] Input: User basic information (JSON format)

[1164] Output: Chatbot generation result (user-specific bot)

[1165] Specific operation: The server analyzes the received JSON data and calls a generative AI API based on it to generate a chatbot for the user. The chatbot reflects the user's preferences and interests.

[1166] Step 3:

[1167] The server sends a notification of completion of the generated chatbot configuration to the terminal, and the terminal notifies the user of the same.

[1168] Input: Chatbot generation result (user-specific bot)

[1169] Output: Notification of successful setup

[1170] Specific operation: The server notifies the device that the chatbot configuration is complete, and the device displays a message to the user such as "Chatbot configuration is complete."

[1171] Step 4:

[1172] Users take a photo of their palm or face and upload it to the application.

[1173] Input: Palm or face photo (image file)

[1174] Output: Image file uploaded to the device

[1175] What happens: A user takes a photo of their palm using their smartphone camera and uploads it through the application.

[1176] Step 5:

[1177] The terminal sends the uploaded image to the server.

[1178] Input: Uploaded image file

[1179] Output: Image data sent to the server

[1180] Specific operation: The device receives the image file, encodes it as binary data, and sends it to the server.

[1181] Step 6:

[1182] The server sends the received images to an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze palm lines and facial features.

[1183] Input: Image data (binary)

[1184] Output: Image analysis results (palm reading and facial feature data)

[1185] Specific operation: The server calls the image analysis API, analyzes the received image data, and obtains information such as the length and position of the palm lines, facial feature points, etc. The analysis results are saved in JSON format.

[1186] Step 7:

[1187] Based on the analysis results, the server applies an algorithm to select the most suitable partner to provide to the user and generates a list of candidates.

[1188] Input: Image analysis results (palm reading and facial feature data)

[1189] Output: Candidate list

[1190] Specific operation: The server analyzes the analysis results and selects suitable candidates according to an algorithm. For example, it generates a list containing information such as "Candidate B: Hanako Sato, 28 years old, hobby: trekking."

[1191] Step 8:

[1192] The server sends the candidate list to the terminal and notifies the user.

[1193] Input: Candidate list

[1194] Output: Notification of candidate list to terminal

[1195] Specific operation: The server sends the generated candidate list to the terminal, and the terminal displays it to the user in the form of "A list of the best possible candidates has been generated."

[1196] Step 9:

[1197] The user selects the desired partner from the notified candidate list.

[1198] Input: Candidate list

[1199] Output: Selected contact information

[1200] Specific operation: The user selects the desired partner from the displayed list of candidates, for example, selecting "Hanako Sato."

[1201] Step 10:

[1202] The terminal transmits the selection information to the server.

[1203] Input: User selection information

[1204] Output: Sends the selection to the server

[1205] Specific operation: The device converts the information selected by the user into JSON format and sends it to the server.

[1206] Step 11:

[1207] The server accesses an external service platform and automatically applies for a match.

[1208] Input: User selection information

[1209] Output: Matching application results

[1210] Specific operation: The server uses an external API to request a match with the selected partner and obtains the result of success or failure.

[1211] Step 12:

[1212] The server checks the match results and generates the date details if successful.

[1213] Input: Matching application results

[1214] Output: Date details (date, time, location, details, etc.)

[1215] Specific operation: If the match is successful, the server generates date details such as "Date and time: August 15th, Location: Tokyo cafe, Content: Lunchtime."

[1216] Step 13:

[1217] The server sends the date details to the terminal, which notifies the user and automatically adds them to the schedule.

[1218] Input: Date details (date, time, location, details, etc.)

[1219] Output: Notification to device and addition to user's calendar

[1220] Specific operation: The server sends the date details to the device, and the device sends a notification to the user saying "The date has been confirmed." The date information is also automatically added to the user's calendar.

[1221] (Application example 1)

[1222] 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."

[1223] Conventional AI chatbot systems based on user information are limited to simply sending messages to users, making it difficult to provide services optimized to individual users' needs and preferences. Even with the introduction of image analysis functions, advanced customization based on users' lifestyles and specific situations remains a challenge. In particular, there is no system that can individually optimize the riding experience inside an autonomous vehicle, making it necessary to address these challenges.

[1224] 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.

[1225] In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving palm or facial images from the user, means for analyzing the received images to identify a suitable partner for the user, means for automatically requesting a match with the identified partner, means for notifying the user of the match results and schedule details, and means for receiving the user's basic information and facial image, generating a driverbot equipped with a dedicated generative AI, and providing entertainment and relaxation support based on the user's preferences and facial data, thereby enabling users to individually optimize their riding experience in an autonomous vehicle and receive personalized entertainment and relaxation support.

[1226] "User basic information" refers to personal data such as the user's name, age, hobbies, and preferences.

[1227] A "generative AI chatbot" is an interactive AI system that is automatically generated based on basic information received from the user and communicates with the user.

[1228] "Palm or face image" refers to image data such as a photo of the user's palm or face.

[1229] "Image analysis" refers to the process of analyzing received palm or facial images to extract features and patterns to derive specific information.

[1230] "Identifying suitable partners" refers to the process of finding the most suitable partner for a user based on image analysis and basic information.

[1231] A "matching request" refers to a request to contact an automatically identified person and build a certain relationship.

[1232] "Notification" refers to the act of informing users of important information such as matching results and schedule details.

[1233] "DriverBot" is a dedicated AI driver that is generated based on the user's basic information and facial image, and provides entertainment and relaxation support according to the user's hobbies and preferences.

[1234] "Entertainment" refers to entertainment such as music, videos, and games provided in the autonomous vehicle.

[1235] "Relaxation support" refers to services and functions that allow users to relax inside an autonomous vehicle.

[1236] The system of the present invention generates an interactive AI chatbot and a driverbot that are optimal for a user based on the user's basic information and facial image. Detailed embodiments of this system are described below.

[1237] First, a user accesses the application using a device (e.g., a smartphone). The application obtains basic information from the user, such as name, age, hobbies, and favorite music, and then asks the user to upload an image of their palm or face. The hardware used in this case includes a smartphone with a camera, and the software used includes an application and an image processing library (e.g., OpenCV).

[1238] The device sends the acquired basic information and facial image to a server, which then creates a generative AI chatbot based on the information received. The software used includes AI models (e.g., TensorFlow) and image analysis algorithms.

[1239] The server analyzes the facial image and performs image analysis to identify the user's facial features and expressions. This process extracts features based on the user's facial data. Based on the analysis results, a driver bot is generated that best suits the user's preferences and needs.

[1240] The generated driver bot will individually optimize the user's riding experience based on user information and facial data. For example, it can play music that matches the user's preferences and provide entertainment tailored to the user's hobbies. The driver bot also has a relaxation support function, providing relaxing music and guidance.

[1241] Furthermore, the generated driver bot will suggest entertainment and relaxation support to the user and carry out them upon request. This process includes customization based on the user's basic information and facial data, allowing the user to maximize their riding experience in the autonomous vehicle.

[1242] (Example)

[1243] For example, a user can use an application to input their name, age, hobbies, and favorite music, and upload a facial image. This information is sent from the device to a server. The server then creates a generative AI chatbot and driver bot specifically for the user based on the received basic information and facial image. This driver bot then plays music and provides relaxation support according to the user's preferences. As a specific example, if the user likes classical music, the application can be set to play classical music in the car.

[1244] (Example of a prompt)

[1245] Use the following prompt sentence to perform processing based on an artificial intelligence model.

[1246] "We want a personal driver AI driver bot to be generated based on the basic information and facial photo provided by the user, and provide optimal car entertainment and relaxation support."

[1247] In this way, the system can utilize the user's basic information and facial image to generate a dedicated generative AI driverbot that can provide individually optimized entertainment and relaxation support.

[1248] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1249] Step 1: Enter your user information

[1250] A user uses a device to input their basic information (such as name, age, hobbies, and favorite music) into the application. The user also takes a picture of their face using a camera-equipped device and uploads it. The input information and face image are sent to the server via the device. The input here is the user's basic information and face image, and the output is user data sent to the server.

[1251] Step 2: Receiving user information and generating an AI chatbot

[1252] The server receives the user's basic information and facial image sent from the device. Based on the received information, the server uses a generative AI model to generate a generative AI chatbot dedicated to the user. The data processing in this process involves analyzing the user data and generating a chatbot based on the AI ​​model. The output is the generated chatbot.

[1253] Step 3: Analyze the facial image

[1254] The server analyzes the received facial image using an image analysis algorithm (e.g., OpenCV). Specifically, it uses facial recognition technology to extract facial features in the image and use them to identify the user's individual characteristics. The input to this process is the facial image, and the output is the analyzed facial feature data.

[1255] Step 4: Create a Driver Bot

[1256] The server generates a dedicated generative AI driver bot based on the user's basic information and facial feature data. The generative AI model used is input with a prompt statement: "Based on the basic information and facial photo provided by the user, I would like a personal driver AI driver bot to provide optimal car entertainment and relaxation support." The driver bot is constructed based on this statement. The input in this process is basic information and facial feature data, and the output is the generated driver bot.

[1257] Step 5: Providing customized entertainment and relaxation support

[1258] The generated driver bot provides optimal entertainment and relaxation support based on the user's basic information and facial features. Specific actions include playing the user's favorite music, providing relaxation music, and providing guidance. The input to this process is the driver bot and its configuration data, and the output is the provision of customized services.

[1259] Step 6: Get user feedback and update the system

[1260] Users provide feedback on the entertainment and relaxation support provided. This feedback is sent from the device to the server, which then uses this information to update the driver bot's settings and generative AI model. The input to this process is the user's feedback data, and the output is an improved driver bot and model.

[1261] Through the above steps, the system of the present invention uses the user's basic information and facial image to generate an interactive AI chatbot and driverbot that are optimal for the user, and is able to provide individually optimized entertainment and relaxation support.

[1262] 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.

[1263] The system of the present invention receives basic information from the user and generates a dedicated generative AI chatbot based on that information. It also analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also combines an emotion engine that recognizes the user's emotions to improve matching accuracy and user experience. It automatically applies for a match with the most suitable partner and notifies the user of the matching results and schedule details.

[1264] 1. Entering user information and creating a chatbot

[1265] Users enter their basic information (name, age, hobbies, etc.) into the app.

[1266] The terminal sends this information to the server.

[1267] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[1268] Once the setup is complete, the server will notify the user that the setup is complete.

[1269] 2. Upload palm / face photo and analyze the image

[1270] Users take a photo of their palm or face and upload it to the app.

[1271] The terminal sends the uploaded image to the server.

[1272] The server uses an image analysis system to analyze palm lines and facial features.

[1273] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[1274] 3. Emotion recognition and response adjustment using an emotion engine

[1275] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text.

[1276] The server adjusts the chatbot's responses based on the emotion recognition results of the emotion engine. For example, if the user is nervous, the server will respond in a way that helps them relax.

[1277] 4. Adjusting match selection criteria using an emotion engine

[1278] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine. For example, if the user is excited, it will select a partner with a calmer personality, achieving optimal matching according to the user's emotional state.

[1279] 5. Matching application and result notification

[1280] The user selects the desired partner from the notified candidate list.

[1281] The terminal transmits the selection information to the server.

[1282] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1283] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1284] The results and schedule details are notified and displayed to the user via the terminal.

[1285] 6. Specific Examples

[1286] For example, User A uses the app to perform the following process:

[1287] User A enters and uploads basic information and a photo of their palm into the app.

[1288] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1289] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1290] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[1291] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[1292] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1293] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1294] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1295] By linking the server, terminal, user, and emotion engine, this system can appropriately adjust dialogue and matching criteria according to the user's emotional state, efficiently matching the optimal partner with minimal effort.

[1296] The processing flow will be explained below.

[1297] Step 1:

[1298] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[1299] Step 2:

[1300] The terminal converts the input user information into a data format and transmits it to the server.

[1301] Step 3:

[1302] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[1303] Step 4:

[1304] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[1305] Step 5:

[1306] Users take a photo of their palm or face and upload it to the app.

[1307] Step 6:

[1308] The terminal transmits the uploaded image data to the server.

[1309] Step 7:

[1310] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[1311] Step 8:

[1312] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[1313] Step 9:

[1314] The terminal displays the candidate list to the user.

[1315] Step 10:

[1316] The user checks the list of candidates and selects the person with whom they wish to be matched.

[1317] Step 11:

[1318] The terminal transmits the information of the selected party to the server.

[1319] Step 12:

[1320] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1321] Step 13:

[1322] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1323] Step 14:

[1324] The server sends the matching results and schedule details to the terminal.

[1325] Step 15:

[1326] The terminal notifies and displays the matching results and schedule information to the user.

[1327] Step 16:

[1328] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text, thereby understanding the user's psychological state.

[1329] Step 17:

[1330] The server adjusts the chatbot's responses based on the results of the emotion engine. For example, if the user is nervous, the server will respond in a way that relaxes them.

[1331] Step 18:

[1332] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine, and creates a list of the most suitable partners according to the user's emotional state.

[1333] Step 19:

[1334] The server selects a partner based on the newly adjusted criteria, regenerates the candidate list, and sends this list to the terminal.

[1335] Step 20:

[1336] The terminal displays the regenerated candidate list to the user.

[1337] This series of processes allows for more accurate and satisfying matching by reflecting the user's emotional state.

[1338] Example 2

[1339] 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."

[1340] Conventional matching systems only identify potential partners based on basic user information and image analysis, and do not consider the user's emotional state. This results in problems such as insufficient matching accuracy and user experience with partners who are suited to the user's emotions.

[1341] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving images from a user, means for analyzing the received images to identify a partner suitable for the user, means for recognizing emotions from the user's facial expressions and text, means for adjusting the chatbot's response content based on the emotion recognition result, means for adjusting the match selection criteria based on the emotion recognition result, means for automatically applying for matching with the identified partner, and means for notifying the user of the matching result and schedule details. This makes it possible to identify the most suitable partner according to the user's emotional state, improving matching accuracy and user experience.

[1342] A "user" is an individual who uses the system to input and upload their own basic information and images.

[1343] "Basic information" refers to profile data such as the user's name, age, hobbies, etc.

[1344] A "generative AI chatbot" is an AI program that is customized based on the user's basic information and engages in conversation.

[1345] "Image" refers to a photograph of your palm or face uploaded by you.

[1346] "Image analysis" is the process of processing uploaded image data to identify palm lines and facial features.

[1347] "Partner" refers to a potential match identified by the system.

[1348] "Emotion recognition" is the process of determining a user's emotional state from their facial expressions and text.

[1349] "Adjusting response content" refers to dynamically changing the chatbot's statements and actions based on the emotion recognition results.

[1350] "Matching selection criteria" refers to the criteria for selecting the most suitable partner based on the user's emotional state.

[1351] "Matching application" is the process by which the system automatically proposes a date or interaction to a identified person.

[1352] "Schedule details" refers to information such as the date, time, location, and content of a date or event that is generated if a match is successful.

[1353] "External Platform" refers to other services on a communications network that the system accesses.

[1354] MODE FOR CARRYING OUT THE INVENTION

[1355] The system of the present invention receives basic information and images from users, generates a generative AI chatbot, recognizes the user's emotions, and matches them with the most suitable partner. The main roles of this system are played by the user, the terminal, and the server.

[1356] Hardware and software used

[1357] User device: A device used by a user, such as a smartphone, tablet, or PC.

[1358] Server: A central server handles data processing, generative artificial intelligence, image analysis, and emotion recognition.

[1359] Generative artificial intelligence (AI) model: An AI model that generates a chatbot based on basic user information.

[1360] Image analysis system: Uses image processing libraries such as OpenCV to analyze palm lines and facial features.

[1361] Emotion recognition engine: Uses emotion analysis APIs such as IBM Watson to recognize emotions from user facial expressions and text.

[1362] Entering user information and generating a chatbot

[1363] 1. The user enters their basic information (name, age, hobbies, etc.) into the app on their device.

[1364] 2. The terminal checks the entered information in real time and sends it to the server in the appropriate format.

[1365] 3. The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user, which reflects the user's interests and hobbies.

[1366] 4. Once the setup is complete, the server sends a "Setup Complete" message to the terminal, which is displayed to the user.

[1367] Upload palm / face photo and analyze the image

[1368] 1. The user uses the camera function in the app to take a photo of their palm or face and presses the upload button.

[1369] 2. The device converts the uploaded image into a pre-specified format and sends it to the server.

[1370] 3. The server analyzes the image using an image analysis system (libraries such as OpenCV) to identify palm lines and facial features.

[1371] 4. The server creates a list of suitable potential partners based on the analysis results and notifies the user of the list via the terminal.

[1372] Emotion recognition and response adjustment with emotion engine

[1373] 1. When users enter basic information and images, their facial expressions and voice are captured through the built-in camera and microphone.

[1374] 2. The device transmits this data to the server in real time.

[1375] 3. The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (joy, sadness, anger, etc.).

[1376] 4. The server dynamically adjusts the responses of the generated chatbot based on the results of emotion recognition. For example, if the user is nervous, it will display a message such as "Relax."

[1377] Adjusting match selection criteria using an emotion engine

[1378] 1. The server continuously monitors the results of the emotion engine and records the user's emotional state.

[1379] 2. The server uses this emotional data to dynamically adjust the matching algorithm, for example, if the user is excited, it will choose a partner with a calmer personality.

[1380] 3. The server generates a new candidate list based on the adjusted selection criteria and notifies the user via the terminal.

[1381] Matching application and result notification

[1382] 1. The user selects the person of interest from the notified candidate list.

[1383] 2. The device sends the information of the selected person to the server.

[1384] 3. The server accesses the external platform and automatically applies for a match, for example, by sending data using an API.

[1385] 4. The server obtains the matching results and, if successful, automatically generates the date details (date, time, location, content, etc.).

[1386] 5. The server notifies the user of the generated date details through the terminal and automatically adds them to the user's schedule.

[1387] Specific examples

[1388] For example, User A uses the app to perform the following process:

[1389] User A enters and uploads basic information and a photo of their palm into the app.

[1390] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1391] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1392] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[1393] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[1394] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1395] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1396] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1397] Prompt Sentence Examples

[1398] Below are some example prompts to input to a generative AI model:

[1399] Describe how users can upload their basic information and a photo of their palm, and how the chatbot will tailor its responses using an emotion engine. Include specific use cases.

[1400] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1401] Step 1:

[1402] The user logs in to the app and enters their basic information (name, age, hobbies, etc.). The input data is entered in a text field. The device checks the entered information in real time and sends it to the server in an appropriate format (e.g., JSON format).

[1403] Input: Basic information such as name, age, hobbies, etc.

[1404] Data processing: Check the input information and convert the format (JSON format)

[1405] Output: Basic information formatted to the server

[1406] Step 2:

[1407] The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user. This chatbot reflects the user's interests and hobbies. Once setup is complete, a "Setup Complete" message is generated.

[1408] Input: Basic formatted information

[1409] Data Computation: Chatbot Generation with Generative AI Models Based on Basic Information

[1410] Output: The generated chatbot, and a "You're all set" message

[1411] Step 3:

[1412] The server sends the generated chatbot information to the device, and the device notifies the user of the "Settings complete" message. The user receives the notification.

[1413] Input: "Settings complete" message, generated chatbot

[1414] Data processing: Sending messages and chatbot information

[1415] Output: Notification with "Setup complete" message

[1416] Step 4:

[1417] Users can use the app's camera to take and upload a photo of their palm or face. The device then converts the image file into a pre-specified format (e.g., PNG, JPEG) and sends it to the server.

[1418] Input: Palm or face photo

[1419] Data processing: Image file format conversion

[1420] Output: Converted image file

[1421] Step 5:

[1422] The server uses an image analysis system (libraries such as OpenCV) to analyze the received image. As a result of the analysis, palm lines and facial features are extracted. Based on this, a list of potential partners suitable for the user is generated.

[1423] Input: Converted image file

[1424] Data calculation: Image analysis (palm lines and facial feature extraction)

[1425] Output: List of potential partners

[1426] Step 6:

[1427] The server sends the generated list of potential partners to the terminal, which notifies the user of the list and displays it.

[1428] Input: candidate list

[1429] Data processing: Sending list information

[1430] Output: Notification and display of candidate list

[1431] Step 7:

[1432] When users enter basic information and images, facial expressions and voices are captured through the built-in camera and microphone, and the device transmits the captured data to a server in real time.

[1433] Input: facial expression and voice data

[1434] Data processing: Real-time data transmission

[1435] Output: Captured data

[1436] Step 8:

[1437] The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (happiness, sadness, anger, etc.) and dynamically adjusts the responses of the generated chatbot based on the analysis results.

[1438] Input: Captured facial and voice data

[1439] Data Computing: Sentiment Analysis

[1440] Output: Tailored chatbot response

[1441] Step 9:

[1442] The server continuously monitors the results of the emotion engine and records the user's emotional state. This emotional data is used to dynamically adjust the matching algorithm.

[1443] Input: Sentiment analysis results

[1444] Data calculation: Adjusting the matching algorithm

[1445] Output: Adjusted match selection criteria

[1446] Step 10:

[1447] The server generates a new list of potential partners based on the adjusted matching selection criteria and notifies the user via the terminal.

[1448] Input: Adjusted match selection criteria

[1449] Data calculation: generating a new list of potential partners

[1450] Output: Notification of new match candidate list

[1451] Step 11:

[1452] The user selects the desired partner from the notified candidate list, and the selection information is sent from the terminal to the server.

[1453] Input: User selects a partner

[1454] Data processing: Sending selected information

[1455] Output: Selection information

[1456] Step 12:

[1457] The server accesses the external platform and automatically applies for a match. Once the application is complete, the matching results are obtained.

[1458] Input: Selection information

[1459] Data calculation: Application to external platform

[1460] Output: Matching results

[1461] Step 13:

[1462] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information in the user's schedule.

[1463] Input: Matching results

[1464] Data Calculation: Generating Date Details

[1465] Output: Date details

[1466] Step 14:

[1467] The server notifies the terminal of the generated date details, which are then displayed to the user, who receives the notification and confirms the details added to the schedule.

[1468] Input: Date Details

[1469] Data processing: Sending detailed information

[1470] Output: Notifications and schedule additions

[1471] (Application example 2)

[1472] 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."

[1473] The problem to be solved by this invention is a system that uses basic information from a user and an image of the palm or face to identify a suitable partner for the user and automatically performs matching. This system can notify the user of details of the date schedule with the identified partner and the matching results. It is also required to provide a more personalized customer service experience by suggesting products and services based on the user's emotional state.

[1474] 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 basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving an image of a palm or face from the user, means for analyzing the received image to identify a suitable partner for the user, means for automatically applying for a match, means for notifying the user of the match result and schedule details, means for proposing products and services based on the image analysis result and emotion recognition result, and means for notifying the user of information on the proposed products and services. This provides a personalized customer service experience based on the user's emotions and basic information, thereby improving user satisfaction.

[1475] "User" refers to any individual or organization that uses this system.

[1476] "Basic information" refers to information including personal data such as the user's name, age, and hobbies.

[1477] A "generative AI chatbot" refers to a dedicated conversational agent that is generated based on basic information about the user.

[1478] "Palm or face image" refers to a digital image of a user's palm or face.

[1479] "Image analysis" refers to the process of extracting features from a received palm or face image and analyzing those features.

[1480] "Emotion recognition" refers to the process of determining a user's emotions from facial expressions and text information.

[1481] "Matching" refers to the process of identifying the most suitable partner for a user based on analyzed information and connecting the user with that partner.

[1482] "Schedule" refers to detailed information such as the date, time, and location of a date that is generated as a result of matching.

[1483] "Product and service proposal" refers to the process of providing optimal products and services to users based on the results of image analysis and emotion recognition.

[1484] "Notification" refers to the action of communicating information to a user.

[1485] An embodiment of the present invention will be described.

[1486] First, the user enters basic information using a device such as a smartphone. This basic information includes personal data such as name, age, and hobbies. The device then sends this basic information to a server. The server uses the received information to create a generative AI chatbot and configures the chatbot specifically for the user. Once configuration is complete, the server sends a completion notification to the user.

[1487] Next, the user takes an image of their palm or face and uploads it to the app. The device then sends the uploaded image to the server, which uses an image analysis system to analyze the palm or facial features, applying algorithms to identify palm lines and facial features. Based on the analysis results, the server identifies suitable partners for the user and generates a list of candidates, which the user is notified of.

[1488] Additionally, when a user enters basic information and an image, the device uses sensors such as a camera to capture the user's facial expressions in real time, and the emotion engine recognizes the emotion from the image. The server flexibly adjusts the chatbot's responses based on the emotion engine's results. For example, if the user is nervous, the chatbot will engage in a conversation designed to relax the user. The emotion engine's results can also be used to adjust the matching selection criteria and identify more suitable partners.

[1489] Furthermore, once the user selects a suggested partner based on the results of image analysis and emotion recognition, the device sends the selection information to the server. The server then accesses an external service platform via the communications network and automatically requests a match. If the request is successful, date details (date, time, location, content, etc.) are generated and set as the user's schedule. This information is then notified to the user via the device.

[1490] In addition, the server will suggest optimal products and services to users based on the results of image analysis and emotion recognition, providing a personalized customer service experience based on the user's emotions and basic information, improving user satisfaction.

[1491] As a concrete example, let's take an example where User A uses the app to perform the following process:

[1492] User A enters and uploads basic information and a photo of their palm into the app.

[1493] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1494] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1495] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[1496] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1497] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1498] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1499] An example prompt is:

[1500] "Please enter the following information:

[1501] 1. Name

[1502] 2. Age

[1503] 3. Hobbies

[1504] 4. Palm reading image or face image

[1505] The above is an embodiment of the present invention.

[1506] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1507] Processing steps of the system that realizes the application example

[1508] Step 1:

[1509] A user accesses an application using a device such as a smartphone and enters basic information such as name, age, hobbies, etc. The entered basic information is sent to the server by the device. This is the input data.

[1510] Step 2:

[1511] The server generates a generative AI chatbot based on the received basic information. Specifically, a system analyzes the received data and creates a dialogue agent specifically for the user based on that information. The generated chatbot is stored on the server, and a dialogue model optimized for the user becomes the output data.

[1512] Step 3:

[1513] The user takes a picture of their palm or face using their device and uploads it to the application. The uploaded image data is sent to the server by the device. This image is the input data.

[1514] Step 4:

[1515] The server analyzes the uploaded image. Specifically, it uses an image analysis system (e.g., OpenCV or other image processing libraries) to extract palm or facial features. The results of this feature analysis are output data.

[1516] Step 5:

[1517] The server then applies an algorithm to identify potential partners based on the image analysis results. For example, it can use palm lines and facial features to determine the user's personality and potential compatible partners. The results are then output as a list of potential partners.

[1518] Step 6:

[1519] When a user inputs basic information and images, the device's camera and sensors capture the user's facial expressions in real time and send them to the server. This facial expression data is the input data.

[1520] Step 7:

[1521] The server uses an emotion engine to analyze the user's facial expression data and identify their emotions. The identification results are output data and used to adjust the chatbot's responses.

[1522] Step 8:

[1523] When a user selects a partner from the candidate list, the selection information is sent to the server by the terminal. This selection information is the input data.

[1524] Step 9:

[1525] Based on the selection information, the server accesses an external service platform via a communication network and automatically applies for matching. The matching results are output data.

[1526] Step 10:

[1527] If the matching result is successful, the server automatically generates date details (date, time, location, content, etc.) and saves them as schedule data. This date details information is the output data.

[1528] Step 11:

[1529] The server sends the date details to the user's terminal for notification, which becomes output data and is displayed in the user's application.

[1530] Step 12:

[1531] Finally, the server proposes optimal products and services to the user based on the results of image analysis and emotion recognition. The proposal information is sent to the user's device. This becomes the final output data.

[1532] 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.

[1533] 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.

[1534] 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.

[1535] [Fourth embodiment]

[1536] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1537] 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.

[1538] 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).

[1539] 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.

[1540] 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.

[1541] 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).

[1542] 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.

[1543] 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.

[1544] 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.

[1545] 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.

[1546] 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.

[1547] 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.

[1548] 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."

[1549] The system of the present invention receives basic information from a user and generates a dedicated generative AI chatbot based on that information. It then analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also automatically requests a match with the identified partner and notifies the user of the match results and schedule details.

[1550] 1. Entering user information and creating a chatbot

[1551] Users enter their basic information (name, age, hobbies, etc.) into the app.

[1552] The terminal sends this information to the server.

[1553] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[1554] Once the setup is complete, the server will notify the user that the setup is complete.

[1555] 2. Upload palm / face photo and analyze the image

[1556] Users take a photo of their palm or face and upload it to the app.

[1557] The terminal sends the uploaded image to the server.

[1558] The server uses an image analysis system to analyze palm lines and facial features.

[1559] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[1560] 3. Matching application and notification of results

[1561] The user selects the desired partner from the notified candidate list.

[1562] The terminal transmits the selection information to the server.

[1563] The server accesses an external service platform and automatically applies for a match.

[1564] The server checks the matching results, and if successful, generates date details (date, time, location, details, etc.) and adds them to the user's schedule.

[1565] The results and schedule details are notified to the user via the terminal.

[1566] 4. Specific Examples

[1567] For example, User A uses the app to perform the following process:

[1568] User A enters and uploads basic information and a photo of their palm into the app.

[1569] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1570] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1571] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1572] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1573] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1574] By linking the server, terminals, and users, the system is designed to allow users to easily and quickly match with their ideal partner. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[1575] The processing flow will be explained below.

[1576] Step 1:

[1577] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[1578] Step 2:

[1579] The terminal converts the input user information into a data format and transmits it to the server.

[1580] Step 3:

[1581] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[1582] Step 4:

[1583] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[1584] Step 5:

[1585] Users take a photo of their palm or face and upload it to the app.

[1586] Step 6:

[1587] The terminal transmits the uploaded image data to the server.

[1588] Step 7:

[1589] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[1590] Step 8:

[1591] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[1592] Step 9:

[1593] The terminal displays the candidate list to the user.

[1594] Step 10:

[1595] The user checks the list of candidates and selects the person with whom they wish to be matched.

[1596] Step 11:

[1597] The terminal transmits the information of the selected party to the server.

[1598] Step 12:

[1599] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1600] Step 13:

[1601] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1602] Step 14:

[1603] The server sends the matching results and schedule details to the terminal.

[1604] Step 15:

[1605] The terminal notifies and displays the matching results and schedule information to the user.

[1606] This series of processing flows allows users to efficiently match with the most suitable partner with minimal effort.

[1607] Example 1

[1608] 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."

[1609] Conventional matching systems have the problem that users must manually enter their own information to search for a suitable partner, which is a complicated process that takes time and effort. In addition, methods for searching for partners based on palm lines or facial features are not widely used, and their effectiveness is not fully utilized. Another issue is the difficulty of building a system that automatically connects with external service platforms and matches partners.

[1610] 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.

[1611] In this invention, the server includes: means for receiving basic information from a user; means for generating a dedicated generative AI chatbot based on the received basic information; means for receiving palm or facial images from the user; image analysis means for analyzing the received images; means for identifying a suitable partner for the user based on the analyzed characteristics; means for accessing an external service platform via a communication network and automatically applying for a match with the identified partner; and means for notifying the user of the match results and schedule details. This allows users to easily input information and quickly find a suitable partner. Furthermore, analyzing palm and facial features can achieve more accurate matching. Furthermore, automatic collaboration with external services can improve matching efficiency and significantly reduce user effort.

[1612] "User" refers to an individual who uses the system to enter their basic information and upload images of their palm or face to search for a match.

[1613] A "generative AI chatbot" refers to an AI that is generated specifically for a user based on their basic information and provides support through dialogue with the user.

[1614] "Basic information" refers to personal information entered by the user, such as their name, age, hobbies, etc.

[1615] "Palm or face image" refers to a photograph of the palm of the hand or face that a user uploads to the system.

[1616] "Image Analysis Means" refers to the technical means for analyzing the uploaded palm or face image to extract features.

[1617] "Identified partner" refers to a suitable candidate for the user, selected by the system based on the image analysis results and the user's basic information.

[1618] "Communications Network" refers to the Internet and other digital communications means used to send and receive information.

[1619] "External Service Platform" refers to a third-party platform that provides matching or dating services.

[1620] "Matching proposal" refers to the system automatically proposing dates or interactions to suitable partners for the user.

[1621] "Matching result" refers to the other party's response to the matching request.

[1622] "Schedule details" refers to information such as the date, time, location, and content of the date that will be set if the match is successful.

[1623] The present invention is a system that receives basic information from a user, generates a dedicated generative AI chatbot based on that information, and identifies the user's best match by analyzing palm reading or facial images uploaded by the user. Furthermore, the system automatically requests a match with the identified match and notifies the user of the match results and schedule details. Specific hardware and software are used to efficiently implement this process.

[1624] This system mainly consists of the following elements:

[1625] 1. Enter your user information

[1626] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[1627] The device receives this input information and sends it to the server. The basic information is used to generate a generative AI chatbot based on the user's hobbies and interests.

[1628] 2. Chatbot Creation

[1629] Based on the received user information, the server uses generative artificial intelligence (e.g., OpenAI's GPT-4) to generate a chatbot specifically for the user. This chatbot is customized for the user and provides support through dialogue with the user.

[1630] 3. Upload your palm / face photo

[1631] Users take a photo of their palm or face and upload it to the application.

[1632] The device receives the uploaded images and automatically sends them to the server.

[1633] 4. Image Analysis

[1634] The server uses an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze the received palm or face image. Based on the analyzed features, it applies an algorithm to match the user with the best possible partner.

[1635] 5. Identifying and notifying potential matches

[1636] Based on the analysis results, the server identifies the most suitable partner for the user and generates a list of candidates. This list is then notified to the user, allowing the user to select the partner they desire.

[1637] 6. Automatic matching application

[1638] Based on the user's selection, the server accesses an external service platform via a communication network and automatically sends a matching request to the identified person.

[1639] The server checks the match results and, if successful, generates the date details (date, time, location, details, etc.).

[1640] 7. Adding results and schedules

[1641] The server sends the date details to the device and notifies the user, and the date schedule is automatically added to the user's calendar.

[1642] Specific examples of operation

[1643] For example, consider the case where a user enters basic information such as "Taro Tanaka, 35 years old, hobby: reading" and uploads a photo of his palm.

[1644] The device formats this information into JSON format and sends it to the server.

[1645] The server uses OpenAI's GPT-4 to generate a chatbot specifically for Tanaka Taro.

[1646] The server uses the Google Cloud Vision API to analyze the characteristics of the palm lines and select the most suitable partner.

[1647] Next, based on the analysis results, a candidate list (for example, "Candidate A: Yamada Hanako, age 30, hobby: listening to music") is generated and notified to Tanaka Taro.

[1648] When Taro Tanaka selects Hanako Yamada, the server accesses an external dating platform and automatically requests a match.

[1649] If the match is successful, the details of the date (for example, "Date and time: July 10th, Location: Tokyo cafe, Content: Lunchtime") are generated, notified to Taro Tanaka via his device, and the date is automatically added to his calendar.

[1650] Example prompt sentence:

[1651] "You enter some basic information into the app, upload a photo of your palm, and it will then automatically find your ideal match and notify you of date details if a match is made."

[1652] This system is designed to enable users to easily and quickly find the perfect match through collaboration between users, devices, and servers. Users can leave most of the procedures to the automated system, significantly reducing the amount of work required.

[1653] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1654] Step 1:

[1655] The user accesses the application and enters their basic information (name, age, hobbies, etc.).

[1656] Input: User's basic information (name, age, hobbies, etc.)

[1657] Output: The terminal checks the input, formats it into JSON format, and sends it to the server.

[1658] Specific operation: For example, enter "Yamada Taro, 30 years old, hobby: cycling" and the device will convert this information into JSON format as shown below.

[1659] json

[1660] {

[1661] "name": "Yamada Taro",

[1662] "age": 30,

[1663] "hobbies": ["cycling"]

[1664] }

[1665] This JSON data is sent to the server.

[1666] Step 2:

[1667] The server generates a dedicated chatbot using generative artificial intelligence (e.g., OpenAI's GPT-4) based on the received user information.

[1668] Input: User basic information (JSON format)

[1669] Output: Chatbot generation result (user-specific bot)

[1670] Specific operation: The server analyzes the received JSON data and calls a generative AI API based on it to generate a chatbot for the user. The chatbot reflects the user's preferences and interests.

[1671] Step 3:

[1672] The server sends a notification of completion of the generated chatbot configuration to the terminal, and the terminal notifies the user of the same.

[1673] Input: Chatbot generation result (user-specific bot)

[1674] Output: Notification of successful setup

[1675] Specific operation: The server notifies the device that the chatbot configuration is complete, and the device displays a message to the user such as "Chatbot configuration is complete."

[1676] Step 4:

[1677] Users take a photo of their palm or face and upload it to the application.

[1678] Input: Palm or face photo (image file)

[1679] Output: Image file uploaded to the device

[1680] What happens: A user takes a photo of their palm using their smartphone camera and uploads it through the application.

[1681] Step 5:

[1682] The terminal sends the uploaded image to the server.

[1683] Input: Uploaded image file

[1684] Output: Image data sent to the server

[1685] Specific operation: The device receives the image file, encodes it as binary data, and sends it to the server.

[1686] Step 6:

[1687] The server sends the received images to an image analysis system (e.g., Google Cloud Vision API or Amazon Rekognition) to analyze palm lines and facial features.

[1688] Input: Image data (binary)

[1689] Output: Image analysis results (palm reading and facial feature data)

[1690] Specific operation: The server calls the image analysis API, analyzes the received image data, and obtains information such as the length and position of the palm lines, facial feature points, etc. The analysis results are saved in JSON format.

[1691] Step 7:

[1692] Based on the analysis results, the server applies an algorithm to select the most suitable partner to provide to the user and generates a list of candidates.

[1693] Input: Image analysis results (palm reading and facial feature data)

[1694] Output: Candidate list

[1695] Specific operation: The server analyzes the analysis results and selects suitable candidates according to an algorithm. For example, it generates a list containing information such as "Candidate B: Hanako Sato, 28 years old, hobby: trekking."

[1696] Step 8:

[1697] The server sends the candidate list to the terminal and notifies the user.

[1698] Input: Candidate list

[1699] Output: Notification of candidate list to terminal

[1700] Specific operation: The server sends the generated candidate list to the terminal, and the terminal displays it to the user in the form of "A list of the best possible candidates has been generated."

[1701] Step 9:

[1702] The user selects the desired partner from the notified candidate list.

[1703] Input: Candidate list

[1704] Output: Selected contact information

[1705] Specific operation: The user selects the desired partner from the displayed list of candidates, for example, selecting "Hanako Sato."

[1706] Step 10:

[1707] The terminal transmits the selection information to the server.

[1708] Input: User selection information

[1709] Output: Sends the selection to the server

[1710] Specific operation: The device converts the information selected by the user into JSON format and sends it to the server.

[1711] Step 11:

[1712] The server accesses an external service platform and automatically applies for a match.

[1713] Input: User selection information

[1714] Output: Matching application results

[1715] Specific operation: The server uses an external API to request a match with the selected partner and obtains the result of success or failure.

[1716] Step 12:

[1717] The server checks the match results and generates the date details if successful.

[1718] Input: Matching application results

[1719] Output: Date details (date, time, location, details, etc.)

[1720] Specific operation: If the match is successful, the server generates date details such as "Date and time: August 15th, Location: Tokyo cafe, Content: Lunchtime."

[1721] Step 13:

[1722] The server sends the date details to the terminal, which notifies the user and automatically adds them to the schedule.

[1723] Input: Date details (date, time, location, details, etc.)

[1724] Output: Notification to device and addition to user's calendar

[1725] Specific operation: The server sends the date details to the device, and the device sends a notification to the user saying "The date has been confirmed." The date information is also automatically added to the user's calendar.

[1726] (Application example 1)

[1727] 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."

[1728] Conventional AI chatbot systems based on user information are limited to simply sending messages to users, making it difficult to provide services optimized to individual users' needs and preferences. Even with the introduction of image analysis functions, advanced customization based on users' lifestyles and specific situations remains a challenge. In particular, there is no system that can individually optimize the riding experience inside an autonomous vehicle, making it necessary to address these challenges.

[1729] 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.

[1730] In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving palm or facial images from the user, means for analyzing the received images to identify a suitable partner for the user, means for automatically requesting a match with the identified partner, means for notifying the user of the match results and schedule details, and means for receiving the user's basic information and facial image, generating a driverbot equipped with a dedicated generative AI, and providing entertainment and relaxation support based on the user's preferences and facial data, thereby enabling users to individually optimize their riding experience in an autonomous vehicle and receive personalized entertainment and relaxation support.

[1731] "User basic information" refers to personal data such as the user's name, age, hobbies, and preferences.

[1732] A "generative AI chatbot" is an interactive AI system that is automatically generated based on basic information received from the user and communicates with the user.

[1733] "Palm or face image" refers to image data such as a photo of the user's palm or face.

[1734] "Image analysis" refers to the process of analyzing received palm or facial images to extract features and patterns to derive specific information.

[1735] "Identifying suitable partners" refers to the process of finding the most suitable partner for a user based on image analysis and basic information.

[1736] A "matching request" refers to a request to contact an automatically identified person and build a certain relationship.

[1737] "Notification" refers to the act of informing users of important information such as matching results and schedule details.

[1738] "DriverBot" is a dedicated AI driver that is generated based on the user's basic information and facial image, and provides entertainment and relaxation support according to the user's hobbies and preferences.

[1739] "Entertainment" refers to entertainment such as music, videos, and games provided in the autonomous vehicle.

[1740] "Relaxation support" refers to services and functions that allow users to relax inside an autonomous vehicle.

[1741] The system of the present invention generates an interactive AI chatbot and a driverbot that are optimal for a user based on the user's basic information and facial image. Detailed embodiments of this system are described below.

[1742] First, a user accesses the application using a device (e.g., a smartphone). The application obtains basic information from the user, such as name, age, hobbies, and favorite music, and then asks the user to upload an image of their palm or face. The hardware used in this case includes a smartphone with a camera, and the software used includes an application and an image processing library (e.g., OpenCV).

[1743] The device sends the acquired basic information and facial image to a server, which then creates a generative AI chatbot based on the information received. The software used includes AI models (e.g., TensorFlow) and image analysis algorithms.

[1744] The server analyzes the facial image and performs image analysis to identify the user's facial features and expressions. This process extracts features based on the user's facial data. Based on the analysis results, a driver bot is generated that best suits the user's preferences and needs.

[1745] The generated driver bot will individually optimize the user's riding experience based on user information and facial data. For example, it can play music that matches the user's preferences and provide entertainment tailored to the user's hobbies. The driver bot also has a relaxation support function, providing relaxing music and guidance.

[1746] Furthermore, the generated driver bot will suggest entertainment and relaxation support to the user and carry out them upon request. This process includes customization based on the user's basic information and facial data, allowing the user to maximize their riding experience in the autonomous vehicle.

[1747] (Example)

[1748] For example, a user can use an application to input their name, age, hobbies, and favorite music, and upload a facial image. This information is sent from the device to a server. The server then creates a generative AI chatbot and driver bot specifically for the user based on the received basic information and facial image. This driver bot then plays music and provides relaxation support according to the user's preferences. As a specific example, if the user likes classical music, the application can be set to play classical music in the car.

[1749] (Example of a prompt)

[1750] Use the following prompt sentence to perform processing based on an artificial intelligence model.

[1751] "We want a personal driver AI driver bot to be generated based on the basic information and facial photo provided by the user, and provide optimal car entertainment and relaxation support."

[1752] In this way, the system can utilize the user's basic information and facial image to generate a dedicated generative AI driverbot that can provide individually optimized entertainment and relaxation support.

[1753] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1754] Step 1: Enter your user information

[1755] A user uses a device to input their basic information (such as name, age, hobbies, and favorite music) into the application. The user also takes a picture of their face using a camera-equipped device and uploads it. The input information and face image are sent to the server via the device. The input here is the user's basic information and face image, and the output is user data sent to the server.

[1756] Step 2: Receiving user information and generating an AI chatbot

[1757] The server receives the user's basic information and facial image sent from the device. Based on the received information, the server uses a generative AI model to generate a generative AI chatbot dedicated to the user. The data processing in this process involves analyzing the user data and generating a chatbot based on the AI ​​model. The output is the generated chatbot.

[1758] Step 3: Analyze the facial image

[1759] The server analyzes the received facial image using an image analysis algorithm (e.g., OpenCV). Specifically, it uses facial recognition technology to extract facial features in the image and use them to identify the user's individual characteristics. The input to this process is the facial image, and the output is the analyzed facial feature data.

[1760] Step 4: Create a Driver Bot

[1761] The server generates a dedicated generative AI driver bot based on the user's basic information and facial feature data. The generative AI model used is input with a prompt statement: "Based on the basic information and facial photo provided by the user, I would like a personal driver AI driver bot to provide optimal car entertainment and relaxation support." The driver bot is constructed based on this statement. The input in this process is basic information and facial feature data, and the output is the generated driver bot.

[1762] Step 5: Providing customized entertainment and relaxation support

[1763] The generated driver bot provides optimal entertainment and relaxation support based on the user's basic information and facial features. Specific actions include playing the user's favorite music, providing relaxation music, and providing guidance. The input to this process is the driver bot and its configuration data, and the output is the provision of customized services.

[1764] Step 6: Get user feedback and update the system

[1765] Users provide feedback on the entertainment and relaxation support provided. This feedback is sent from the device to the server, which then uses this information to update the driver bot's settings and generative AI model. The input to this process is the user's feedback data, and the output is an improved driver bot and model.

[1766] Through the above steps, the system of the present invention uses the user's basic information and facial image to generate an interactive AI chatbot and driverbot that are optimal for the user, and is able to provide individually optimized entertainment and relaxation support.

[1767] 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.

[1768] The system of the present invention receives basic information from the user and generates a dedicated generative AI chatbot based on that information. It also analyzes palm or face images uploaded by the user to identify the most suitable partner for the user. It also combines an emotion engine that recognizes the user's emotions to improve matching accuracy and user experience. It automatically applies for a match with the most suitable partner and notifies the user of the matching results and schedule details.

[1769] 1. Entering user information and creating a chatbot

[1770] Users enter their basic information (name, age, hobbies, etc.) into the app.

[1771] The terminal sends this information to the server.

[1772] Based on the received information, the server generates a generative AI chatbot and sets up a bot specifically for the user.

[1773] Once the setup is complete, the server will notify the user that the setup is complete.

[1774] 2. Upload palm / face photo and analyze the image

[1775] Users take a photo of their palm or face and upload it to the app.

[1776] The terminal sends the uploaded image to the server.

[1777] The server uses an image analysis system to analyze palm lines and facial features.

[1778] The server selects the most suitable partner for the user based on the analysis results, and the results are generated as a candidate list and notified to the user.

[1779] 3. Emotion recognition and response adjustment using an emotion engine

[1780] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text.

[1781] The server adjusts the chatbot's responses based on the emotion recognition results of the emotion engine. For example, if the user is nervous, the server will respond in a way that helps them relax.

[1782] 4. Adjusting match selection criteria using an emotion engine

[1783] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine. For example, if the user is excited, it will select a partner with a calmer personality, achieving optimal matching according to the user's emotional state.

[1784] 5. Matching application and result notification

[1785] The user selects the desired partner from the notified candidate list.

[1786] The terminal transmits the selection information to the server.

[1787] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1788] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1789] The results and schedule details are notified and displayed to the user via the terminal.

[1790] 6. Specific Examples

[1791] For example, User A uses the app to perform the following process:

[1792] User A enters and uploads basic information and a photo of their palm into the app.

[1793] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1794] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1795] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[1796] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[1797] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1798] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1799] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1800] By linking the server, terminal, user, and emotion engine, this system can appropriately adjust dialogue and matching criteria according to the user's emotional state, efficiently matching the optimal partner with minimal effort.

[1801] The processing flow will be explained below.

[1802] Step 1:

[1803] After installing and opening the app, users are taken to a screen where they can enter basic information (name, age, hobbies, etc.) and press the send button once they have completed the entry.

[1804] Step 2:

[1805] The terminal converts the input user information into a data format and transmits it to the server.

[1806] Step 3:

[1807] The server analyzes the received user information and generates a dedicated generative AI chatbot based on that information. Once generation is complete, the server notifies the device that the chatbot configuration is complete.

[1808] Step 4:

[1809] The device will notify the user that the setup is complete and prompt them to move on to the next step, where they can upload photos of their palm or face.

[1810] Step 5:

[1811] Users take a photo of their palm or face and upload it to the app.

[1812] Step 6:

[1813] The terminal transmits the uploaded image data to the server.

[1814] Step 7:

[1815] The server launches an image analysis system to analyze the uploaded palm or face image, extracting palm or facial features and identifying the most suitable partner for the user.

[1816] Step 8:

[1817] The server generates a candidate list of the partners selected from the analysis results and transmits the list to the terminal.

[1818] Step 9:

[1819] The terminal displays the candidate list to the user.

[1820] Step 10:

[1821] The user checks the list of candidates and selects the person with whom they wish to be matched.

[1822] Step 11:

[1823] The terminal transmits the information of the selected party to the server.

[1824] Step 12:

[1825] The server accesses the external service platform and automatically applies for a match. After the application is completed, the matching results are obtained.

[1826] Step 13:

[1827] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information as the user's schedule.

[1828] Step 14:

[1829] The server sends the matching results and schedule details to the terminal.

[1830] Step 15:

[1831] The terminal notifies and displays the matching results and schedule information to the user.

[1832] Step 16:

[1833] When a user inputs basic information and images, the emotion engine recognizes emotions from the user's facial expressions and text, thereby understanding the user's psychological state.

[1834] Step 17:

[1835] The server adjusts the chatbot's responses based on the results of the emotion engine. For example, if the user is nervous, the server will respond in a way that relaxes them.

[1836] Step 18:

[1837] The server dynamically adjusts the matching selection criteria based on the results of the emotion engine, and creates a list of the most suitable partners according to the user's emotional state.

[1838] Step 19:

[1839] The server selects a partner based on the newly adjusted criteria, regenerates the candidate list, and sends this list to the terminal.

[1840] Step 20:

[1841] The terminal displays the regenerated candidate list to the user.

[1842] This series of processes allows for more accurate and satisfying matching by reflecting the user's emotional state.

[1843] Example 2

[1844] 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."

[1845] Conventional matching systems only identify potential partners based on basic user information and image analysis, and do not consider the user's emotional state. This results in problems such as insufficient matching accuracy and user experience with partners who are suited to the user's emotions.

[1846] The identification process by the identification processing unit 290 of the data processing device 12 in Example 2 is realized by the following means. In this invention, the server includes means for receiving basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving images from a user, means for analyzing the received images to identify a partner suitable for the user, means for recognizing emotions from the user's facial expressions and text, means for adjusting the chatbot's response content based on the emotion recognition result, means for adjusting the match selection criteria based on the emotion recognition result, means for automatically applying for matching with the identified partner, and means for notifying the user of the matching result and schedule details. This makes it possible to identify the most suitable partner according to the user's emotional state, improving matching accuracy and user experience.

[1847] A "user" is an individual who uses the system to input and upload their own basic information and images.

[1848] "Basic information" refers to profile data such as the user's name, age, hobbies, etc.

[1849] A "generative AI chatbot" is an AI program that is customized based on the user's basic information and engages in conversation.

[1850] "Image" refers to a photograph of your palm or face uploaded by you.

[1851] "Image analysis" is the process of processing uploaded image data to identify palm lines and facial features.

[1852] "Partner" refers to a potential match identified by the system.

[1853] "Emotion recognition" is the process of determining a user's emotional state from their facial expressions and text.

[1854] "Adjusting response content" refers to dynamically changing the chatbot's statements and actions based on the emotion recognition results.

[1855] "Matching selection criteria" refers to the criteria for selecting the most suitable partner based on the user's emotional state.

[1856] "Matching application" is the process by which the system automatically proposes a date or interaction to a identified person.

[1857] "Schedule details" refers to information such as the date, time, location, and content of a date or event that is generated if a match is successful.

[1858] "External Platform" refers to other services on a communications network that the system accesses.

[1859] MODE FOR CARRYING OUT THE INVENTION

[1860] The system of the present invention receives basic information and images from users, generates a generative AI chatbot, recognizes the user's emotions, and matches them with the most suitable partner. The main roles of this system are played by the user, the terminal, and the server.

[1861] Hardware and software used

[1862] User device: A device used by a user, such as a smartphone, tablet, or PC.

[1863] Server: A central server handles data processing, generative artificial intelligence, image analysis, and emotion recognition.

[1864] Generative artificial intelligence (AI) model: An AI model that generates a chatbot based on basic user information.

[1865] Image analysis system: Uses image processing libraries such as OpenCV to analyze palm lines and facial features.

[1866] Emotion recognition engine: Uses emotion analysis APIs such as IBM Watson to recognize emotions from user facial expressions and text.

[1867] Entering user information and generating a chatbot

[1868] 1. The user enters their basic information (name, age, hobbies, etc.) into the app on their device.

[1869] 2. The terminal checks the entered information in real time and sends it to the server in the appropriate format.

[1870] 3. The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user, which reflects the user's interests and hobbies.

[1871] 4. Once the setup is complete, the server sends a "Setup Complete" message to the terminal, which is displayed to the user.

[1872] Upload palm / face photo and analyze the image

[1873] 1. The user uses the camera function in the app to take a photo of their palm or face and presses the upload button.

[1874] 2. The device converts the uploaded image into a pre-specified format and sends it to the server.

[1875] 3. The server analyzes the image using an image analysis system (libraries such as OpenCV) to identify palm lines and facial features.

[1876] 4. The server creates a list of suitable potential partners based on the analysis results and notifies the user of the list via the terminal.

[1877] Emotion recognition and response adjustment with emotion engine

[1878] 1. When users enter basic information and images, their facial expressions and voice are captured through the built-in camera and microphone.

[1879] 2. The device transmits this data to the server in real time.

[1880] 3. The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (joy, sadness, anger, etc.).

[1881] 4. The server dynamically adjusts the responses of the generated chatbot based on the results of emotion recognition. For example, if the user is nervous, it will display a message such as "Relax."

[1882] Adjusting match selection criteria using an emotion engine

[1883] 1. The server continuously monitors the results of the emotion engine and records the user's emotional state.

[1884] 2. The server uses this emotional data to dynamically adjust the matching algorithm, for example, if the user is excited, it will choose a partner with a calmer personality.

[1885] 3. The server generates a new candidate list based on the adjusted selection criteria and notifies the user via the terminal.

[1886] Matching application and result notification

[1887] 1. The user selects the person of interest from the notified candidate list.

[1888] 2. The device sends the information of the selected person to the server.

[1889] 3. The server accesses the external platform and automatically applies for a match, for example, by sending data using an API.

[1890] 4. The server obtains the matching results and, if successful, automatically generates the date details (date, time, location, content, etc.).

[1891] 5. The server notifies the user of the generated date details through the terminal and automatically adds them to the user's schedule.

[1892] Specific examples

[1893] For example, User A uses the app to perform the following process:

[1894] User A enters and uploads basic information and a photo of their palm into the app.

[1895] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1896] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[1897] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[1898] The server adjusts the matching selection criteria based on the results of the emotion engine and selects a more suitable user B.

[1899] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[1900] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[1901] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[1902] Prompt Sentence Examples

[1903] Below are some example prompts to input to a generative AI model:

[1904] Describe how users can upload their basic information and a photo of their palm, and how the chatbot will tailor its responses using an emotion engine. Include specific use cases.

[1905] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1906] Step 1:

[1907] The user logs in to the app and enters their basic information (name, age, hobbies, etc.). The input data is entered in a text field. The device checks the entered information in real time and sends it to the server in an appropriate format (e.g., JSON format).

[1908] Input: Basic information such as name, age, hobbies, etc.

[1909] Data processing: Check the input information and convert the format (JSON format)

[1910] Output: Basic information formatted to the server

[1911] Step 2:

[1912] The server stores the received basic information in a database and uses a generative AI model to generate a chatbot specifically for the user. This chatbot reflects the user's interests and hobbies. Once setup is complete, a "Setup Complete" message is generated.

[1913] Input: Basic formatted information

[1914] Data Computation: Chatbot Generation with Generative AI Models Based on Basic Information

[1915] Output: The generated chatbot, and a "You're all set" message

[1916] Step 3:

[1917] The server sends the generated chatbot information to the device, and the device notifies the user of the "Settings complete" message. The user receives the notification.

[1918] Input: "Settings complete" message, generated chatbot

[1919] Data processing: Sending messages and chatbot information

[1920] Output: Notification with "Setup complete" message

[1921] Step 4:

[1922] Users can use the app's camera to take and upload a photo of their palm or face. The device then converts the image file into a pre-specified format (e.g., PNG, JPEG) and sends it to the server.

[1923] Input: Palm or face photo

[1924] Data processing: Image file format conversion

[1925] Output: Converted image file

[1926] Step 5:

[1927] The server uses an image analysis system (libraries such as OpenCV) to analyze the received image. As a result of the analysis, palm lines and facial features are extracted. Based on this, a list of potential partners suitable for the user is generated.

[1928] Input: Converted image file

[1929] Data calculation: Image analysis (palm lines and facial feature extraction)

[1930] Output: List of potential partners

[1931] Step 6:

[1932] The server sends the generated list of potential partners to the terminal, which notifies the user of the list and displays it.

[1933] Input: candidate list

[1934] Data processing: Sending list information

[1935] Output: Notification and display of candidate list

[1936] Step 7:

[1937] When users enter basic information and images, facial expressions and voices are captured through the built-in camera and microphone, and the device transmits the captured data to a server in real time.

[1938] Input: facial expression and voice data

[1939] Data processing: Real-time data transmission

[1940] Output: Captured data

[1941] Step 8:

[1942] The server uses an emotion engine (emotion analysis API such as IBM Watson) to analyze the user's emotional state (happiness, sadness, anger, etc.) and dynamically adjusts the responses of the generated chatbot based on the analysis results.

[1943] Input: Captured facial and voice data

[1944] Data Computing: Sentiment Analysis

[1945] Output: Tailored chatbot response

[1946] Step 9:

[1947] The server continuously monitors the results of the emotion engine and records the user's emotional state. This emotional data is used to dynamically adjust the matching algorithm.

[1948] Input: Sentiment analysis results

[1949] Data calculation: Adjusting the matching algorithm

[1950] Output: Adjusted match selection criteria

[1951] Step 10:

[1952] The server generates a new list of potential partners based on the adjusted matching selection criteria and notifies the user via the terminal.

[1953] Input: Adjusted match selection criteria

[1954] Data calculation: generating a new list of potential partners

[1955] Output: Notification of new match candidate list

[1956] Step 11:

[1957] The user selects the desired partner from the notified candidate list, and the selection information is sent from the terminal to the server.

[1958] Input: User selects a partner

[1959] Data processing: Sending selected information

[1960] Output: Selection information

[1961] Step 12:

[1962] The server accesses the external platform and automatically applies for a match. Once the application is complete, the matching results are obtained.

[1963] Input: Selection information

[1964] Data calculation: Application to external platform

[1965] Output: Matching results

[1966] Step 13:

[1967] If the match is successful, the server automatically generates the details of the date (date, time, location, content, etc.) and sets this information in the user's schedule.

[1968] Input: Matching results

[1969] Data Calculation: Generating Date Details

[1970] Output: Date details

[1971] Step 14:

[1972] The server notifies the terminal of the generated date details, which are then displayed to the user, who receives the notification and confirms the details added to the schedule.

[1973] Input: Date Details

[1974] Data processing: Sending detailed information

[1975] Output: Notifications and schedule additions

[1976] (Application example 2)

[1977] 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."

[1978] The problem to be solved by this invention is a system that uses basic information from a user and an image of the palm or face to identify a suitable partner for the user and automatically performs matching. This system can notify the user of details of the date schedule with the identified partner and the matching results. It is also required to provide a more personalized customer service experience by suggesting products and services based on the user's emotional state.

[1979] 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 basic information from a user, means for generating a dedicated generative AI chatbot based on the received basic information, means for receiving an image of a palm or face from the user, means for analyzing the received image to identify a suitable partner for the user, means for automatically applying for a match, means for notifying the user of the match result and schedule details, means for proposing products and services based on the image analysis result and emotion recognition result, and means for notifying the user of information on the proposed products and services. This provides a personalized customer service experience based on the user's emotions and basic information, thereby improving user satisfaction.

[1980] "User" refers to any individual or organization that uses this system.

[1981] "Basic information" refers to information including personal data such as the user's name, age, and hobbies.

[1982] A "generative AI chatbot" refers to a dedicated conversational agent that is generated based on basic information about the user.

[1983] "Palm or face image" refers to a digital image of a user's palm or face.

[1984] "Image analysis" refers to the process of extracting features from a received palm or face image and analyzing those features.

[1985] "Emotion recognition" refers to the process of determining a user's emotions from facial expressions and text information.

[1986] "Matching" refers to the process of identifying the most suitable partner for a user based on analyzed information and connecting the user with that partner.

[1987] "Schedule" refers to detailed information such as the date, time, and location of a date that is generated as a result of matching.

[1988] "Product and service proposal" refers to the process of providing optimal products and services to users based on the results of image analysis and emotion recognition.

[1989] "Notification" refers to the action of communicating information to a user.

[1990] An embodiment of the present invention will be described.

[1991] First, the user enters basic information using a device such as a smartphone. This basic information includes personal data such as name, age, and hobbies. The device then sends this basic information to a server. The server uses the received information to create a generative AI chatbot and configures the chatbot specifically for the user. Once configuration is complete, the server sends a completion notification to the user.

[1992] Next, the user takes an image of their palm or face and uploads it to the app. The device then sends the uploaded image to the server, which uses an image analysis system to analyze the palm or facial features, applying algorithms to identify palm lines and facial features. Based on the analysis results, the server identifies suitable partners for the user and generates a list of candidates, which the user is notified of.

[1993] Additionally, when a user enters basic information and an image, the device uses sensors such as a camera to capture the user's facial expressions in real time, and the emotion engine recognizes the emotion from the image. The server flexibly adjusts the chatbot's responses based on the emotion engine's results. For example, if the user is nervous, the chatbot will engage in a conversation designed to relax the user. The emotion engine's results can also be used to adjust the matching selection criteria and identify more suitable partners.

[1994] Furthermore, once the user selects a suggested partner based on the results of image analysis and emotion recognition, the device sends the selection information to the server. The server then accesses an external service platform via the communications network and automatically requests a match. If the request is successful, date details (date, time, location, content, etc.) are generated and set as the user's schedule. This information is then notified to the user via the device.

[1995] In addition, the server will suggest optimal products and services to users based on the results of image analysis and emotion recognition, providing a personalized customer service experience based on the user's emotions and basic information, improving user satisfaction.

[1996] As a concrete example, let's take an example where User A uses the app to perform the following process:

[1997] User A enters and uploads basic information and a photo of their palm into the app.

[1998] The device sends this information to the server, which then generates a dedicated chatbot for User A.

[1999] The server analyzes the palm reading photo and selects User B, who is the most suitable partner, as a candidate.

[2000] The emotion engine recognizes user A's emotions and flexibly adjusts the chatbot's responses.

[2001] User A wishes to apply for a match with User B, and the selection information is sent to the server via the terminal.

[2002] The server will submit a matching request via an external service platform, and if successful, date details will be generated.

[2003] The server notifies the device of the date details, and the date is automatically added to User A's schedule.

[2004] An example prompt is:

[2005] "Please enter the following information:

[2006] 1. Name

[2007] 2. Age

[2008] 3. Hobbies

[2009] 4. Palm reading image or face image

[2010] The above is an embodiment of the present invention.

[2011] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[2012] Processing steps of the system that realizes the application example

[2013] Step 1:

[2014] A user accesses an application using a device such as a smartphone and enters basic information such as name, age, hobbies, etc. The entered basic information is sent to the server by the device. This is the input data.

[2015] Step 2:

[2016] The server generates a generative AI chatbot based on the received basic information. Specifically, a system analyzes the received data and creates a dialogue agent specifically for the user based on that information. The generated chatbot is stored on the server, and a dialogue model optimized for the user becomes the output data.

[2017] Step 3:

[2018] The user takes a picture of their palm or face using their device and uploads it to the application. The uploaded image data is sent to the server by the device. This image is the input data.

[2019] Step 4:

[2020] The server analyzes the uploaded image. Specifically, it uses an image analysis system (e.g., OpenCV or other image processing libraries) to extract palm or facial features. The results of this feature analysis are output data.

[2021] Step 5:

[2022] The server then applies an algorithm to identify potential partners based on the image analysis results. For example, it can use palm lines and facial features to determine the user's personality and potential compatible partners. The results are then output as a list of potential partners.

[2023] Step 6:

[2024] When a user inputs basic information and images, the device's camera and sensors capture the user's facial expressions in real time and send them to the server. This facial expression data is the input data.

[2025] Step 7:

[2026] The server uses an emotion engine to analyze the user's facial expression data and identify their emotions. The identification results are output data and used to adjust the chatbot's responses.

[2027] Step 8:

[2028] When a user selects a partner from the candidate list, the selection information is sent to the server by the terminal. This selection information is the input data.

[2029] Step 9:

[2030] Based on the selection information, the server accesses an external service platform via a communication network and automatically applies for matching. The matching results are output data.

[2031] Step 10:

[2032] If the matching result is successful, the server automatically generates date details (date, time, location, content, etc.) and saves them as schedule data. This date details information is the output data.

[2033] Step 11:

[2034] The server sends the date details to the user's terminal for notification, which becomes output data and is displayed in the user's application.

[2035] Step 12:

[2036] Finally, the server proposes optimal products and services to the user based on the results of image analysis and emotion recognition. The proposal information is sent to the user's device. This becomes the final output data.

[2037] 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.

[2038] 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.

[2039] 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.

[2040] 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.

[2041] 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.

[2042] 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.

[2043] 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).

[2044] 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.

[2045] 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."

[2046] 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.

[2047] 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).

[2048] 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.

[2049] 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.

[2050] 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.

[2051] 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.

[2052] 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.

[2053] 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.

[2054] 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.

[2055] 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.

[2056] 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.

[2057] 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.

[2058] The following is further disclosed regarding the above embodiment.

[2059] (Claim 1)

[2060] a means for receiving basic information from a user;

[2061] A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and

[2062] means for receiving a palm or face image from a user;

[2063] A means for analyzing the received image to identify a suitable partner for the user;

[2064] A means for automatically applying for a match to the identified person;

[2065] a means for notifying the user of the matching results and schedule details;

[2066] A system including:

[2067] (Claim 2)

[2068] 2. The system of claim 1, wherein the image analysis means includes means for identifying suitable partners based on palm reading and physiognomy.

[2069] (Claim 3)

[2070] 2. The system according to claim 1, further comprising means for accessing an external service platform via a communication network and automatically performing operations.

[2071] "Example 1"

[2072] (Claim 1)

[2073] a means for receiving basic information from a user;

[2074] A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and

[2075] means for receiving a palm or face image from a user;

[2076] image analysis means for analyzing the received image;

[2077] means for identifying suitable contacts for the user based on the analyzed characteristics;

[2078] a means for accessing an external service platform via a communication network and automatically applying for matching with the identified person;

[2079] a means for notifying the user of the matching results and schedule details;

[2080] A system including:

[2081] (Claim 2)

[2082] 10. The system of claim 1, further comprising means for identifying suitable partners based on palm reading and facial features.

[2083] (Claim 3)

[2084] 2. The system according to claim 1, further comprising means for generating a list of match candidates and automatically performing operations based thereon.

[2085] "Application Example 1"

[2086] (Claim 1)

[2087] a means for receiving basic information from a user;

[2088] A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and

[2089] means for receiving a palm or face image from a user;

[2090] A means for analyzing the received image to identify a suitable partner for the user;

[2091] A means for automatically applying for a match to the identified person;

[2092] a means for notifying the user of the matching results and schedule details;

[2093] A means for receiving basic information and facial images of a user, generating a driver bot equipped with dedicated generative artificial intelligence, and providing entertainment and relaxation support based on the user's preferences and facial data;

[2094] A system including:

[2095] (Claim 2)

[2096] 2. The system of claim 1, wherein the image analysis means includes means for identifying suitable partners based on palm reading and physiognomy.

[2097] (Claim 3)

[2098] 2. The system according to claim 1, further comprising means for accessing an external service platform via a communication network and automatically performing operations.

[2099] "Example 2: Combining Emotion Engines"

[2100] (Claim 1)

[2101] a means for receiving basic information from a user;

[2102] A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and

[2103] means for receiving an image from a user;

[2104] A means for analyzing the received image to identify a suitable partner for the user;

[2105] A means for recognizing emotions from a user's facial expressions and text;

[2106] A means for adjusting the response content of the chatbot based on the emotion recognition result;

[2107] a means for adjusting a matching selection criterion based on the emotion recognition result;

[2108] A means for automatically applying for a match to the identified person;

[2109] a means for notifying the user of the matching results and schedule details;

[2110] A system including:

[2111] (Claim 2)

[2112] 2. The system of claim 1, wherein the image analysis means includes means for identifying suitable partners based on palm reading and facial features.

[2113] (Claim 3)

[2114] 2. The system according to claim 1, further comprising means for accessing an external platform via a communication network and automatically performing operations.

[2115] "Application example 2 when combining emotion engines"

[2116] (Claim 1)

[2117] a means for receiving basic information from a user;

[2118] A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and

[2119] means for receiving a palm or face image from a user;

[2120] A means for analyzing the received image to identify a suitable partner for the user;

[2121] A means for automatically applying for a match to the identified person;

[2122] a means for notifying the user of the matching results and schedule details;

[2123] A means for proposing products and services based on the results of image analysis and emotion recognition;

[2124] a means for notifying the user of information about the proposed product or service;

[2125] A system including:

[2126] (Claim 2)

[2127] 2. The system of claim 1, wherein the image analysis means includes means for identifying suitable partners based on palm reading and physiognomy.

[2128] (Claim 3)

[2129] 2. The system according to claim 1, further comprising means for accessing an external service platform via a communication network and automatically performing operations. [Explanation of symbols]

[2130] 10, 210, 310, 410 Data Processing Systems 12 Data Processing Device 14 Smart Devices 214 Smart Glasses 314 Headset-type terminal 414 Robot< / url:> < / url:> < / url:> < / url:>

Claims

1. a means for receiving basic information from a user; A means for generating a dedicated generative artificial intelligence chatbot based on the received basic information; and means for receiving a palm or face image from a user; A means for analyzing the received image to identify a suitable partner for the user; A means for automatically applying for a match to the identified person; a means for notifying the user of the matching results and schedule details; A system including:

2. 2. The system of claim 1, wherein the image analysis means includes means for identifying suitable partners based on palm reading and physiognomy.

3. 2. The system according to claim 1, further comprising means for accessing an external service platform via a communication network and automatically performing an operation.

Images