System

Abstract

A system is provided.SOLUTION: A system comprising: means for acquiring market data; artificial intelligence means for analyzing the acquired market data; means for converting the analyzed market data into a constellation or galactic shape for visualization; means for displaying the visualized data in a virtual reality environment; and means for a user to explore and manipulate the visualized market data in the virtual reality environment.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 market analysis tools make it difficult to efficiently collect and analyze investment information from vast amounts of data and develop investment strategies. Furthermore, these tools are difficult to operate intuitively, making them difficult to use for many users. As a result, investing can feel intimidating, especially for young people and those new to investing. To address these issues, the present invention provides a new investment experience platform that combines artificial intelligence and virtual reality, enabling users to intuitively and efficiently collect, analyze, and develop investment information and strategies. [Means for solving the problem]

[0005] The investment experience platform of the present invention provides a system including means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into the shape of a constellation or galaxy for visualization, means for displaying the visualized data in a virtual reality environment, and means for a user to explore and manipulate the visualized market data in the virtual reality environment. The system also includes means for providing detailed information about market data points identified by user manipulation in the virtual reality environment, means for a user to formulate and submit an investment strategy, means for analyzing market data in real time to suggest investment opportunities and risks, means for storing the results of the analyzed market data in a database for later access, an interface means for supporting intuitive manipulation, and means including an algorithm for locating data points in specific positions in the constellation or galaxy. This allows users to efficiently gather investment information and intuitively formulate investment strategies.

[0006] "Market data" is a general term for data that includes information on stock prices, trading volumes, exchange rates, interest rates, etc. in financial markets.

[0007] "Artificial intelligence means" refers to algorithms and programs such as machine learning and deep learning used to analyze market data.

[0008] "Visualization tools" refers to software and statistical methods used to transform analyzed data into something that can be intuitively understood by the user.

[0009] "Means for converting data points into constellations or galaxies" refers to algorithms or programs that display market data points as constellations or galaxies in a virtual space.

[0010] "Virtual reality environment" refers to a three-dimensional computer-generated space that a user experiences through a specialized device.

[0011] "Means for displaying" refers to software and hardware for visually displaying market data within a virtual reality environment.

[0012] "Means for exploration and manipulation" refers to the interface and input devices that allow a user to explore and intuitively manipulate the visualized data within the virtual reality environment.

[0013] "Means for Providing More Information" refers to software and networks for displaying additional information related to a user-identified market data point.

[0014] "Means for creating and submitting investment strategies" refers to the interface and software that allows users to create their own investment strategies based on acquired market data, enter them into the system, and submit them.

[0015] "Real-time analytical means" refers to algorithms and hardware for capturing and analyzing market data without delay.

[0016] "Instruments for suggesting investment opportunities and risks" refers to algorithms and programs that notify users of the timing and risks of investments based on analyzed market data.

[0017] "Means for storing in a database and making it accessible later" refers to a database and management software for storing analysis results and user operation history so that they can be referenced later.

[0018] "Interface means for supporting intuitive operation" refers to a graphical user interface and input device that can be easily operated by the user.

[0019] "Means including algorithms" refers to computational methods and programs for placing market data at specific locations in the constellations or galaxies. [Brief explanation of the drawings]

[0020] [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

[0021] 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.

[0022] First, the terms used in the following description will be explained.

[0023] 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).

[0024] 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.

[0025] 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.

[0026] 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.

[0027] 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."

[0028] [First embodiment]

[0029] FIG. 1 shows an example of the configuration of a data processing system 10 according to the first embodiment.

[0030] 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.

[0031] 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).

[0032] 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.

[0033] 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.

[0034] 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.

[0035] 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.

[0036] FIG. 2 shows an example of the main functions of the data processing device 12 and the smart device 14.

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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."

[0041] The present invention relates to a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a form that can be intuitively understood by a user. The following describes in detail embodiments of the present invention.

[0042] System configuration

[0043] server

[0044] The server has means for obtaining market data in real time. The market data obtained from the external API is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database for later access. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0045] Specifically, the server retrieves market data through external APIs and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze the data for trends and patterns. The results are stored in a database and can be searched as needed. The data from the database is transformed into constellations and galaxies by a visualization means.

[0046] Terminal

[0047] The terminal has a means for providing a virtual reality environment to a user, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for the user to explore and operate within the virtual reality environment.

[0048] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). Next, it uses the virtual reality data received from the server to render the galaxy and constellations in the VR space. The user can freely explore the VR space and focus on stars that interest them.

[0049] User

[0050] Users can explore and intuitively manipulate market data visualizations within a virtual reality environment. When users focus on a particular star, detailed information related to that star is displayed. Users can then use this information to develop investment strategies and submit them to the system.

[0051] For example, a user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user can use it to develop an investment strategy. This investment strategy is sent to a server and stored in a database.

[0052] Program processing

[0053] (Server behavior)

[0054] The server retrieves market data from external APIs and stores it temporarily.

[0055] The acquired data is passed to an artificial intelligence means for analysis in real time.

[0056] The analysis results are stored in a database and visualization data is generated as needed.

[0057] Send visualization data to the device.

[0058] (Device operation)

[0059] The device initializes the virtual reality system and loads the necessary resources.

[0060] The visualization data received from the server is used to render the image in a virtual reality space.

[0061] It provides an intuitive interface for users to explore and navigate.

[0062] (user actions)

[0063] The user wears a VR device and explores the virtual reality space.

[0064] Focus on a specific star to see more information about it.

[0065] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[0066] As a result, the present invention promotes intuitive understanding of market data and provides an environment in which users can effectively formulate investment strategies.

[0067] The processing flow will be explained below.

[0068] Step 1:

[0069] server

[0070] Obtain real-time market data from external APIs and temporarily store the data.

[0071] Specific actions

[0072] Call external APIs, receive market data, and store it in storage.

[0073] Step 2:

[0074] server

[0075] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[0076] Specific actions

[0077] Input the data into an analytical artificial intelligence module, triggering a task to analyze the data for trends and patterns.

[0078] Step 3:

[0079] server

[0080] The analysis results from the artificial intelligence means are received and stored in a database.

[0081] Specific actions

[0082] Save the analysis results in a database to ensure that the results can be accessed later.

[0083] Step 4:

[0084] server

[0085] The analysis results are extracted from the database and converted into constellation and galaxy shapes for visualization.

[0086] Specific actions

[0087] The analysis results are read and visualized using an algorithm that converts them into the shapes of constellations and galaxies.

[0088] Step 5:

[0089] server

[0090] The generated visualization data is sent to the terminal.

[0091] Specific actions

[0092] The visualization data is transmitted to a user terminal via a network.

[0093] Step 6:

[0094] Terminal

[0095] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[0096] Specific actions

[0097] Starts the VR system and loads the resource file into memory.

[0098] Step 7:

[0099] Terminal

[0100] The visualization data received from the server is used to render the image in a virtual reality space.

[0101] Specific actions

[0102] A 3D model is generated based on the received data, and then placed and rendered in the VR space.

[0103] Step 8:

[0104] Terminal

[0105] It provides an interface that allows users to explore and manipulate market data visualized in a VR space.

[0106] Specific actions

[0107] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[0108] Step 9:

[0109] User

[0110] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[0111] Specific actions

[0112] Select a specific star and navigate through menus and popups to view related data.

[0113] Step 10:

[0114] User

[0115] An investment strategy is developed based on the detailed information obtained and sent to the server.

[0116] Specific actions

[0117] Enter your plan and hit submit using the interface to analyze detailed information and develop new investment strategies.

[0118] Step 11:

[0119] server

[0120] The investment strategy sent by the user is received and stored in a database.

[0121] Specific actions

[0122] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[0123] In this way, through detailed step-by-step processing, the present invention realizes a series of processes for collecting, analyzing, and visualizing market data, and for users to develop investment strategies.

[0124] Example 1

[0125] 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."

[0126] The goal is to realize a system that analyzes market data in real time and visualizes it in a way that is easy for users to understand intuitively, provides an intuitive interface for exploring and manipulating this visualized data within a virtual reality environment, and provides detailed information about market data points of interest to users, allowing them to create and execute investment strategies based on that information.

[0127] 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.

[0128] In this invention, the server includes means for acquiring market data, machine learning means for analyzing the acquired market data, means for converting the analyzed market data into the shapes of constellations or galaxies and visualizing them, means for rendering the visualized data in a virtual reality environment, interface means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for saving the acquired market data in a database, and means for a user to submit an investment strategy developed in the virtual reality environment. This allows a user to visualize market data in an intuitively understandable form and explore the data in the virtual reality environment to obtain detailed information. Furthermore, investment strategies can be efficiently developed and submitted based on the acquired information.

[0129] "Market data" refers to data that can be obtained in real time, including transaction data, price data, trading volume data, market trend data, etc. from financial markets and commodity markets.

[0130] An "external API" refers to an application programming interface provided by an external system or service, and is an interface for obtaining information such as market data.

[0131] "Machine learning tools" refer to algorithms or models used to analyze market data and identify patterns and trends, for example, using machine learning frameworks such as TensorFlow or PyTorch.

[0132] "Visualization means" refers to a means for converting analyzed market data into the shapes of constellations or galaxies in a form that is intuitively easy for users to understand and display it, and includes 3D modeling and data visualization techniques.

[0133] "Virtual reality environment" refers to a three-dimensional computer-generated space experienced by a user using a VR device, including those that allow the user to experience and manipulate an environment that is not physically present.

[0134] "Interface means" refers to the operating elements and input devices required for a user to explore and manipulate the visualized market data within the virtual reality environment, including, for example, a VR controller and an intuitive operating panel.

[0135] "Database" refers to a system that efficiently stores and manages data and enables data search and retrieval through queries, including, for example, SQL databases.

[0136] "Investment Strategy" refers to the investment plans and decisions formulated by users based on the analysis results and detailed information of market data, which are submitted and executed through the system.

[0137] The present invention is a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a format that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[0138] Server configuration and operation

[0139] Obtaining Market Data

[0140] The server retrieves market data from an external API (e.g., a financial data API). The server sends an HTTP request, receives the market data in JSON format, and temporarily stores it.

[0141] Data analysis

[0142] The server analyzes the stored market data using artificial intelligence tools, specifically machine learning frameworks (e.g., TensorFlow and PyTorch), to extract trends and patterns based on past data and make future predictions.

[0143] Generate and save visualization data

[0144] The analysis results are stored in a database (e.g., PostgreSQL). The server then converts the analysis results into constellation and galaxy shapes through visualization tools, using 3D modeling techniques such as D3.js and Three.js.

[0145] Submitting visualization data

[0146] The server sends the generated visualization data to the terminal in JSON format using the HTTP protocol.

[0147] Terminal configuration and operation explanation

[0148] Initializing the Virtual Reality System

[0149] The device initializes the virtual reality system (e.g., Oculus Quest 2) and loads the necessary 3D models and scripts using a game engine (e.g., Unity or Unreal Engine).

[0150] Drawing visualized data

[0151] The device receives visualization data from the server and renders it in the virtual reality space. The data is received via WebSocket or HTTP communication and displayed as constellations and galaxies in 3D space.

[0152] Providing an interface

[0153] The device provides an intuitive interface that allows users to explore and manipulate virtual reality spaces using VR controllers, and includes scripts for rich interactions.

[0154] User Action Description

[0155] Access to virtual reality spaces

[0156] The user puts on a VR device, launches a VR application on the device, and enters the virtual reality space. Specifically, the user puts on a device such as Oculus Quest 2.

[0157] Explore and explore visualized data

[0158] Users explore visualized constellations and galaxies in a virtual reality space, and by using the VR controller to focus on a star of interest, detailed market data related to that star is displayed.

[0159] Investment strategy planning and submission

[0160] The user can create an investment strategy based on the displayed details and enter it in the input form provided in the VR space. The completed investment strategy is then sent to the server by clicking the submit button and saved in the database.

[0161] Examples of concrete examples and prompts

[0162] Specific examples

[0163] Users access the system using Oculus Quest 2 and explore market data visualized in virtual reality (for example, the shape of the galaxy). Focusing on a specific star displays stock price data for companies related to that star, and users can then develop investment strategies based on that information and submit them in the VR space.

[0164] Prompt Sentence Examples

[0165] "Please explain how a system for visualizing real-time market data in a virtual reality environment works. The system takes market data, analyzes it using artificial intelligence, and then displays it in a VR space as constellations or galaxies. For each step, please detail the specific hardware and software used, as well as the data generated and manipulated. Also, please provide examples of how a user might use the system to manipulate the data and develop an investment strategy."

[0166] As a result, the present invention provides an environment in which users can intuitively understand market data and plan and implement effective investment strategies.

[0167] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0168] Step 1: Obtain market data

[0169] The server sends an HTTP request to an external API to retrieve market data. The retrieved market data is received in JSON format and temporarily stored in memory. The input is the API endpoint and query parameters, and the output is a JSON object of market data. For example, a specific operation would be to query "https: / / api.financedata.com / marketdata" and retrieve the returned price and volume data.

[0170] Step 2: Analyze the data

[0171] The server inputs the acquired market data into a machine learning model for analysis. During this process, a Python script is used to run a TensorFlow or PyTorch model. The input is a JSON object of market data, and the output is the analysis results (prediction data including trends and patterns). Specifically, it runs a neural network model that uses past stock price data to predict future prices.

[0172] Step 3: Save your data

[0173] The server saves the analysis results in a database (PostgreSQL). The input is the data structure of the analysis results, and the output is the state of storage in the database. Specifically, the analysis results are saved in the appropriate table in the database using an SQL insert statement.

[0174] Step 4: Generate visualization data

[0175] The server generates visualization data based on the saved analysis results. The data is converted into the shapes of constellations and galaxies using 3D modeling software (D3.js or Three.js). The input is the analysis results and a template for the 3D modeling software, and the output is 3D visualization data. Specifically, the data points from the analysis results are converted into 3D coordinate data and output in WebGL format.

[0176] Step 5: Sending data

[0177] The server sends the generated visualization data to the terminal. The visualization data is sent in JSON format to the terminal using the HTTP protocol. The input is a JSON object of the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent using an HTTP POST request.

[0178] Step 6: Initializing the Virtual Reality System

[0179] The device starts the virtual reality system (Oculus Quest 2) and loads the necessary resources, including 3D models and scripts. The input is a list of required resources, and the output is an initialized virtual reality environment. Specifically, the 3D environment is built using Unity or Unreal Engine and initialized.

[0180] Step 7: Rendering the visualization

[0181] The device receives visualization data from the server and renders it in a virtual reality space. The input is a JSON object of the visualization data, and the output is a visualized 3D space. Specifically, the device receives data via WebSocket or HTTP communication and executes a script to render it in the 3D space.

[0182] Step 8: Providing an Interface

[0183] The device provides an intuitive interface for users to explore and manipulate the virtual reality space. The input is the user's operation input, and the output is an interface that can be explored and manipulated. Specific operations are implemented as scripts that accept user movement and selection operations via the VR controller.

[0184] Step 9: Access the virtual reality space

[0185] The user wears a VR device and accesses a virtual reality space. The input is the VR device, and the output is the accessed virtual reality space. Specifically, the user wears the Oculus Quest 2, launches a VR application, and enters the virtual reality space.

[0186] Step 10: Explore and review the visualized data

[0187] Users explore the visualized constellations and galaxies in a virtual reality space and focus on a specific star. The input is the visualization data and user operations, and the output is detailed information about the focused star. Specific actions include selecting a specific star using the VR controller and displaying a pop-up with market data related to that star.

[0188] Step 11: Develop and submit your investment strategy

[0189] The user creates an investment strategy based on the displayed detailed information and submits it using the input form provided within the system. The input is the detailed information and the user's input, and the output is data transmission to the server. Specifically, the user enters the investment strategy into the input form in the VR space and clicks the send button to send it to the server.

[0190] This allows users to intuitively understand market data and develop and submit effective investment strategies.

[0191] (Application example 1)

[0192] 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."

[0193] In today's investment environment, massive amounts of market data are generated in real time, making it difficult to effectively analyze and intuitively understand it. Furthermore, there are insufficient means to quickly develop and implement investment strategies based on the analyzed data. As a result, users are easily confused by information overload and complex data analysis when making investment decisions, which can make it difficult to make appropriate investment decisions.

[0194] 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.

[0195] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for a user to use the visualized market data on a smartphone platform to develop and submit an investment strategy, means for using a generative AI model to visualize the market data in the virtual reality environment based on criteria specified by the user, and means for inputting prompt statements to the generative AI model and adjusting the visualization of the market data based on the prompt statements, thereby enabling a user to intuitively understand the market data and develop and execute effective and rapid investment strategies.

[0196] "Market data" refers to data such as stock prices, trading volumes, and economic indicators obtained from stock exchanges and other financial markets.

[0197] "Artificial intelligence tools" are programs or systems that use machine learning or deep learning algorithms to analyze trends and patterns in market data.

[0198] "Visualization tools" are technologies and systems that convert data into the shapes of constellations and galaxies and display them in a way that users can intuitively understand.

[0199] A "virtual reality environment" is a computer-generated three-dimensional space and interface that allows users to freely explore and manipulate it.

[0200] "Smartphone platform" refers to applications and systems that run on smartphones and provide the infrastructure for users to view and manipulate market data.

[0201] "Generative AI models" refer to AI techniques and algorithms that analyze and visualize data based on user-specified criteria.

[0202] A "prompt" is text data that is input to a generative AI model, and is an instruction that adjusts the visualization of the data based on that text.

[0203] An "investment strategy" is an investment policy or plan that a user formulates based on market data and its analysis results.

[0204] MODE FOR CARRYING OUT THE INVENTION

[0205] The present invention relates to a system that acquires market data in real time, analyzes it using artificial intelligence means, and visualizes the results in a form that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[0206] Server configuration and operation

[0207] A server is a device that has the following main functions:

[0208] 1. Market data acquisition methods:

[0209] The server retrieves market data from stock exchanges and other financial markets through APIs, including stock prices, trading volumes, economic indicators, and more.

[0210] 2. Artificial Intelligence Means:

[0211] To analyze the acquired market data, machine learning and deep learning algorithms are used, specifically software such as TensorFlow and PyTorch, to analyze trends and patterns in the data.

[0212] 3. Visualization tools:

[0213] It uses algorithms to convert the results of the analysis into the shapes of constellations and galaxies, and this visualization data is stored in a database and generated as needed.

[0214] Terminal configuration and operation

[0215] The terminal is a device that allows a user to explore and manipulate market data within a virtual reality environment.

[0216] 1. Virtual reality systems:

[0217] The device uses a VR device (such as Oculus Rift or Google Cardboard) to provide the user with a virtual reality environment. The VR library used is Unity or Unreal Engine.

[0218] 2. Smartphone Platform:

[0219] It displays visualized market data through an application that runs on smartphones, allowing users to browse and explore the data using their smartphones.

[0220] 3. Generative AI Model:

[0221] The generative AI model is used to perform analysis and visualization based on user-specified criteria, and the user can make specific requests to the generative AI model by entering prompt statements.

[0222] User interaction and usage

[0223] Users can explore market data using their smartphones or VR devices, and then develop and submit investment strategies based on the visualized data.

[0224] 1. Exploration and manipulation in virtual reality environments:

[0225] Users explore market data visualized as constellations and galaxies in a VR space, and by focusing on a particular star, more information related to that star is displayed.

[0226] 2. Investment strategy planning and submission:

[0227] Based on the information obtained in the virtual reality environment, users can plan their investment strategies, which are then submitted to the server via a smartphone application and stored in a database.

[0228] Usage examples and prompt statements

[0229] For example, a user might input a prompt like, "Analyze the latest US stock market data and generate a galaxy visualization showing trends in the technology sector. By focusing on a specific star, display the company's financial forecast." Based on this prompt, the generative AI model analyzes the data and creates a visualization that meets the specified criteria.

[0230] This allows users to more intuitively understand market data and develop investment strategies quickly and effectively.

[0231] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0232] Step 1:

[0233] The server retrieves market data from an external API. Specifically, the server sends a request to the market data API and retrieves real-time market data as an API response. This market data includes stock prices, trading volume, economic indicators, etc. The server temporarily stores this data.

[0234] Input: Response data from the Market Data API

[0235] Output: Temporarily stored market data

[0236] Step 2:

[0237] The server analyzes the acquired market data using artificial intelligence means, specifically machine learning and deep learning algorithms (e.g., TensorFlow and PyTorch), to analyze the market data and extract trends and patterns. The analysis results are stored in a database.

[0238] Input: Temporarily stored market data

[0239] Output: Analysis results (trend and pattern information)

[0240] Step 3:

[0241] The server then visualizes the analyzed market data using an algorithm that converts the analysis results into the shapes of constellations and galaxies, generating visualizations that are then stored in a database.

[0242] Input: Analysis results

[0243] Output: Visualization data (shapes of constellations and galaxies)

[0244] Step 4:

[0245] The device initializes the virtual reality system. Specifically, it loads the necessary resources (models, textures, scripts, etc.) and creates the virtual reality environment. Unity or Unreal Engine is used as the VR library.

[0246] Input: Resources for a virtual reality environment

[0247] Output: Initialized virtual reality system

[0248] Step 5:

[0249] The device uses the visualization data received from the server to render the image in a virtual reality space. Specifically, the visualization data obtained from the server is displayed in the VR space, allowing the user to explore the space.

[0250] Input: Visualization data

[0251] Output: Visualization data rendered in virtual reality space

[0252] Step 6:

[0253] Users explore and interact with a virtual reality environment, using a VR device to explore market data visualized as constellations and galaxy shapes. By focusing on a star of interest, detailed market data related to that star is displayed.

[0254] Input: Visualization data of virtual reality space

[0255] Output: Detailed market data displayed as a result of the user's search

[0256] Step 7:

[0257] Users create investment strategies based on the information they obtain in the virtual reality environment and submit them to a server via a smartphone application. For example, a user might create an investment strategy such as "purchase stocks of a specific company based on trends in the technology sector" and send that strategy to the server.

[0258] Input: Investment strategy designed by the user

[0259] Output: Investment strategy submitted to the server

[0260] Step 8:

[0261] The server inputs prompts into the generative AI model, which then adjusts the visualization of the market data based on those prompts. Specifically, the server analyzes the prompts entered by the user, reanalyzes the market data based on those criteria, and generates updated visualizations.

[0262] Input: The prompt text entered by the user

[0263] Output: Visualization data regenerated based on the prompt statement

[0264] In this way, this system realizes a series of processes from acquiring market data to analyzing, visualizing, displaying in a virtual reality environment, and formulating and submitting investment strategies, allowing users to intuitively understand market data and effectively formulate investment strategies.

[0265] 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.

[0266] The present invention relates to a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by users in a virtual reality environment. The present invention also includes an emotion engine that recognizes users' emotions and optimizes the user experience based on their emotional state. Specific embodiments for implementing the present invention are described in detail below.

[0267] System configuration

[0268] server

[0269] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0270] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. Furthermore, an emotion engine is built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[0271] Terminal

[0272] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[0273] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[0274] User

[0275] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[0276] Specifically, the user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[0277] Program processing

[0278] (Server behavior)

[0279] The server retrieves market data from external APIs and stores it temporarily.

[0280] The acquired data is passed to an artificial intelligence means for analysis in real time.

[0281] The analysis results are stored in a database and visualization data is generated as needed.

[0282] Send visualization data to the device.

[0283] The emotion engine analyzes the user's emotion data and generates data to optimize the user experience.

[0284] (Device operation)

[0285] The device initializes the virtual reality system and loads the necessary resources.

[0286] The visualization data received from the server is used to render the image in a virtual reality space.

[0287] It provides an intuitive interface for users to explore and navigate.

[0288] The emotion engine obtains the user's emotional data in real time and adjusts the display method and interaction.

[0289] (user actions)

[0290] The user wears a VR device and explores the virtual reality space.

[0291] Focus on a specific star to see more information about it.

[0292] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[0293] Users receive feedback from the sentiment engine and adjust their investment strategies.

[0294] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[0295] The processing flow will be explained below.

[0296] Step 1:

[0297] server

[0298] Obtain real-time market data from external APIs and temporarily store the data.

[0299] Specific actions

[0300] Calls external APIs to obtain market data, which is then stored in storage.

[0301] Step 2:

[0302] server

[0303] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[0304] Specific actions

[0305] Input market data into the artificial intelligence module and trigger a task to analyze the data for trends and patterns.

[0306] Step 3:

[0307] server

[0308] The analysis results from the artificial intelligence means are received and stored in a database.

[0309] Specific actions

[0310] The analysis results are stored in a database and managed in a form that can be accessed later.

[0311] Step 4:

[0312] server

[0313] The analysis results are extracted from the database and data is converted for visualization.

[0314] Specific actions

[0315] The analysis results are read and visualized using algorithms that convert them into the shapes of constellations and galaxies.

[0316] Step 5:

[0317] server

[0318] The generated visualization data is sent to the terminal.

[0319] Specific actions

[0320] The visualization data is transmitted to the user's terminal via a network.

[0321] Step 6:

[0322] Terminal

[0323] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[0324] Specific actions

[0325] Starts the VR system, loads resource files, and prepares the virtual reality space.

[0326] Step 7:

[0327] Terminal

[0328] The visualization data received from the server is rendered in a virtual reality space.

[0329] Specific actions

[0330] It analyzes the received visualization data and draws it based on the shapes of constellations and galaxies.

[0331] Step 8:

[0332] Terminal

[0333] It provides an interface that allows users to explore and manipulate visualized market data within a virtual reality space.

[0334] Specific actions

[0335] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[0336] Step 9:

[0337] User

[0338] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[0339] Specific actions

[0340] Select a specific star. Detailed information related to the selected star will be displayed as a pop-up or menu.

[0341] Step 10:

[0342] server

[0343] Detailed information relating to a particular star selected by the user is retrieved from the database and transmitted to the user terminal.

[0344] Specific actions

[0345] It searches the database for information related to a specific star and transmits the obtained information to the user terminal.

[0346] Step 11:

[0347] User

[0348] An investment strategy is developed based on the detailed information obtained and sent to the server.

[0349] Specific actions

[0350] Analyze detailed information and enter and submit new investment strategies through the interface.

[0351] Step 12:

[0352] server

[0353] The investment strategy sent by the user is received and stored in a database.

[0354] Specific actions

[0355] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[0356] Step 13:

[0357] Terminal

[0358] An emotion engine is activated to obtain user emotion data in real time.

[0359] Specific actions

[0360] The emotion engine analyzes the user's facial expressions and biometric information to obtain their current emotional state.

[0361] Step 14:

[0362] server

[0363] The acquired emotional data is analyzed by an emotion engine, and the display method and interaction of the visualized data are dynamically adjusted.

[0364] Specific actions

[0365] Analyze emotional data and adjust presentation and interaction methods to optimize the user experience.

[0366] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[0367] Example 2

[0368] 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."

[0369] Modern market data is massive and complex, making it difficult for individual investors and analysts to intuitively understand and analyze the data. Furthermore, there is a lack of systems that can analyze data, including the user's emotional state, and provide appropriate feedback based on that data. This makes it difficult to make investment decisions and quickly respond to market fluctuations.

[0370] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0371] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, and means for analyzing the user's emotional data and generating feedback to optimize the user experience, thereby enabling the user to intuitively understand large amounts of complex market data and make more accurate and prompt investment decisions while receiving feedback that takes their emotional state into account.

[0372] "Market data" refers to trading information such as stock prices, foreign exchange rates, and commodity prices in the market, and related data.

[0373] "Means of Acquisition" refers to the methods and devices used to collect market data from external APIs and data providers.

[0374] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze trends and patterns in data.

[0375] "Visualization means" refers to a method or system for converting the analyzed data into visual shapes, such as constellations or galaxies, and displaying them to a user.

[0376] A "virtual reality environment" refers to an environment in which a user can experience a virtually constructed three-dimensional space using a dedicated device.

[0377] "Exploration and manipulation means" refers to the interfaces and devices that allow a user to move around in a virtual reality space and focus on specific objects.

[0378] "Emotional data" refers to data relating to the emotional state of a user obtained by analyzing the user's facial expressions, voice, heart rate, etc.

[0379] "Generated feedback" refers to advice or instructions provided to the user based on the analyzed emotional data.

[0380] The present invention is a system that acquires market data, analyzes it using artificial intelligence, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that analyzes the user's emotion data and enables the optimization of the user experience. Specific embodiments for implementing the present invention are described in detail below.

[0381] Server Operation

[0382] The server retrieves market data in real time through external APIs (e.g., Alpha Vantage API or Yahoo Finance API). This data is temporarily stored and then analyzed using artificial intelligence tools (e.g., TensorFlow or PyTorch). The results of the analysis are then stored in a database (e.g., MySQL or MongoDB) and visualizations (e.g., generated with SVG or D3.js) are generated as needed.

[0383] Example: A server retrieves TSLA stock price data from the Alpha Vantage API, analyzes this market data for trends using TensorFlow, and stores the results in MySQL.

[0384] Example prompt: Get TSLA stock price data from the Alpha Vantage API and store it in Redis.

[0385] Example prompt: Use TensorFlow to analyze this market data for trends and store the results in MySQL.

[0386] Additionally, the server is equipped with an emotion engine (e.g., Emotion AI API) that analyzes user emotion data and generates feedback to optimize the user experience.

[0387] Example: Analyzing the user's facial expression data with the Emotion AI API and generating feedback for relaxation.

[0388] Example prompt: Analyze the user's facial expression data using the Emotion AI API and generate feedback to help them relax.

[0389] Device behavior

[0390] The terminal uses a VR device (e.g., Oculus Rift, HTC Vive) to provide a virtual reality environment. It receives visualization data sent from the server and renders it in the virtual reality space. Within this space, an intuitive interface is provided for the user to explore and manipulate.

[0391] Example: Initialize the Oculus Rift, load the necessary 3D models and textures, and draw a galaxy in a virtual space based on the received data.

[0392] Example prompt: Initialize your Oculus Rift and load any necessary 3D models and textures.

[0393] Example prompt: Draw the received visualization data into the virtual reality space using the Unity engine.

[0394] The device also receives real-time feedback from the emotion engine and dynamically adjusts how it displays and interacts with the device.

[0395] Example: Changing the colors and effects of a virtual space based on the user's emotional data received in real time from the Emotion AI API.

[0396] Example prompt: Get the user's emotional data in real time and adjust the colors and effects of the virtual space.

[0397] User Actions

[0398] Users put on a VR device and explore the virtual reality space. By focusing on a specific star, detailed market data related to that star is displayed. Based on this information, users can create an investment strategy and submit it to the system. They can also receive feedback from the emotion engine and adjust their investment strategy based on that feedback.

[0399] Example: A user puts on an Oculus Rift, focuses on a star displaying TSLA market data, examines its details, and then uses a virtual keyboard to input their investment strategy and submit it to the system.

[0400] Sample prompt: Allow the user to put on a VR device and explore a virtual space.

[0401] Example prompt: Provide a system that displays detailed data for the star the user selects.

[0402] Example prompt: Please provide a system that allows users to input their investment strategies and submit them to the server.

[0403] Example prompt: Provide a system to adjust and resubmit investment strategies based on feedback from the sentiment engine.

[0404] In this way, the present invention can smoothly carry out a series of processes including collection, analysis, and visualization of market data, operation in a virtual reality space by the user, and feedback based on emotional data.

[0405] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0406] Step 1:

[0407] Obtaining Market Data

[0408] The server calls external APIs (e.g., Alpha Vantage API or Yahoo Finance API) to obtain market data. The server temporarily stores the obtained data in storage. At this time, a specific stock or product is specified in the request, and the data is received in JSON format as a response.

[0409] What happens: The server makes a request to the Alpha Vantage API to get the latest stock price data for TSLA, and temporarily stores this data in a Redis cache.

[0410] Input: API request (e.g., specific stock identifier)

[0411] Output: Market data in JSON format (e.g., TSLA stock price data)

[0412] Step 2:

[0413] Data analysis

[0414] The server passes the acquired market data to an artificial intelligence algorithm (e.g., TensorFlow, PyTorch) that analyzes the data for trends and patterns. The analysis results are stored in a database. At this time, the input data is processed by a machine learning model, and trend information and patterns are generated as output.

[0415] Specific operation: Using TensorFlow, the acquired TSLA stock price data is analyzed, trend information is generated, and the results are stored in a MySQL database.

[0416] Input: Market data in JSON format

[0417] Output: Analysis results (e.g., trend information)

[0418] Step 3:

[0419] Visualization data generation

[0420] The server generates visualization data based on the analyzed data and converts it into the shapes of constellations and galaxies. The visualization data is generated using SVG, D3.js, etc. In this case, the input data is the analysis results, and the output data is in a format that can be displayed visually.

[0421] Specific operation: Using the analysis results, the D3.js library is used to generate galaxy shape data and create visualization data in SVG format.

[0422] Input: Analysis results

[0423] Output: Visualization data (e.g., Galaxy shape in SVG format)

[0424] Step 4:

[0425] Emotional Data Analysis

[0426] The server uses an emotion engine (e.g., Emotion AI API) to analyze the user's emotional data. Based on the analysis results, it generates feedback to optimize the user experience. In this case, the input data is emotional data such as the user's facial expressions and voice, and the output data is feedback information.

[0427] Specific operation: Sends the user's facial expression data to the Emotion AI API, and generates feedback to help them relax as a result of the analysis.

[0428] Input: User emotion data (e.g., facial expression data)

[0429] Output: Feedback information

[0430] Step 5:

[0431] Initializing the Virtual Reality System

[0432] The device initializes the VR device (e.g., Oculus Rift, HTC Vive) and loads the necessary resources (models, textures, scripts, etc.) from pre-prepared files or databases.

[0433] Specific operation: Starts Oculus Rift and loads 3D model and texture files into the device's memory.

[0434] Input: VR device, resource files (e.g. 3D models, textures)

[0435] Output: Initialized virtual reality environment

[0436] Step 6:

[0437] Drawing visualized data

[0438] The device renders galaxies and constellations in the virtual reality space based on the visualization data received from the server, allowing users to intuitively grasp the data within the VR space.

[0439] Specific operation: Receives visualization data in SVG format from the server and draws a 3D model of the galaxy in virtual reality space using the Unity engine.

[0440] Input: Visualization data

[0441] Output: Rendered virtual reality space

[0442] Step 7:

[0443] Providing a user interface

[0444] The device provides an intuitive interface for users to explore and interact with, and when users focus on a particular object, detailed information about it is displayed.

[0445] What it does: Provides a UI that allows the user to select a constellation using a VR controller.

[0446] Input: User action

[0447] Output: Detailed information displayed

[0448] Step 8:

[0449] Real-time acquisition of user emotion data and interaction adjustment

[0450] The device receives data from the emotion engine in real time and adjusts how it displays and interacts with the device, dynamically optimizing the user experience.

[0451] Specific operation: Changes the colors and effects of the virtual space based on the user's emotional data received in real time from the Emotion AI API.

[0452] Input: Real-time user emotion data

[0453] Output: Calibrated virtual reality space

[0454] Step 9:

[0455] Verifying information, formulating investment strategies, and submitting them

[0456] Users can focus on a specific star in the VR space, check related information, and then create an investment strategy based on that information and submit it to the system.

[0457] Specific operation: The user uses the VR controller to focus on the star with TSLA market data to view detailed information, enter investment strategies using the virtual keyboard, and send them to the system.

[0458] Input: User actions, investment strategies

[0459] Output: Submitted investment strategy

[0460] Step 10:

[0461] Adjusting investment strategies

[0462] Users can reassess their investment strategy based on feedback from the sentiment engine and make adjustments as needed.

[0463] What happens: After receiving feedback from the sentiment engine indicating "tension," the user reevaluates, amends, and resubmits their investment strategy.

[0464] Input: Emotion engine feedback

[0465] Output: Adjusted investment strategy

[0466] (Application example 2)

[0467] 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."

[0468] Conventional virtual storefront systems lack functionality that allows users to intuitively understand market data and effectively plan investment strategies. Furthermore, they lack dynamic experience optimization that takes into account the user's emotional state, resulting in a lack of quality improvement in the user experience. Therefore, a new system is needed that not only analyzes market data in real time, intuitively visualizes it, and displays it in a virtual reality environment, but also optimizes the experience based on the user's emotions.

[0469] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0470] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, and means for converting the analyzed market data into the shapes of constellations or galaxies for visualization. This allows users to visually understand and explore the data within a virtual reality environment. Furthermore, the server includes an emotion engine that recognizes the user's emotional data and optimizes the user experience based on the user's emotional state. Having means for dynamically adjusting the layout and promotional strategies of the virtual store based on the emotion engine makes it possible to provide a high-quality experience tailored to the user's emotions.

[0471] "Market data" is a general term for information including prices, supply, demand, and trading volume of goods and services in the market.

[0472] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze, predict, and classify data.

[0473] "Visualization" refers to the process of transforming and displaying data in a way that is intuitively understandable to users.

[0474] "Constellations and galactic shapes" refers to the way data points are visualized, arranging them to resemble astronomical objects.

[0475] "Virtual reality environment" refers to a digital environment in which a user is immersed in a computer-generated three-dimensional space.

[0476] "User" means any person who utilizes the System to explore and manipulate Market Data.

[0477] An "emotion engine" refers to a system that has the ability to recognize a user's emotional state and optimize the experience based on that.

[0478] "Virtual store layout" refers to the product placement and spatial design within a virtual reality environment.

[0479] A "promotion strategy" refers to a plan or method for effectively selling a particular product or service.

[0480] The present invention is a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that recognizes the user's emotions and optimizes the user experience based on the user's emotional state. Specific embodiments for implementing the present invention are described in detail below.

[0481] System configuration

[0482] server

[0483] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0484] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms (e.g., Python libraries TensorFlow and Scikit-learn) to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. An emotion engine is also built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[0485] Terminal

[0486] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[0487] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. This visualization is achieved using a 3D rendering library such as Three.js. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[0488] User

[0489] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[0490] Specifically, the user puts on a VR device (e.g., Oculus Rift, HTC Vive, etc.) and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[0491] Program processing

[0492] The main hardware includes a server (data acquisition, analysis, and storage), a VR terminal (providing a virtual reality environment and drawing data), and a user device (VR device).The main software includes external API access, machine learning libraries (TensorFlow, Scikit-learn), a database management system, and a 3D drawing library (Three.js).

[0493] Adding specific examples

[0494] Examples of promotion optimization in virtual stores include:

[0495] 1. Providing optimal promotion strategies in real time based on customer data and market trends.

[0496] 2. An emotional engine determines whether customers are enjoying themselves and dynamically changes the interface and layout if a certain emotional state persists.

[0497] Prompt Sentence Examples

[0498] "Optimize the current virtual store layout based on the latest market data. Also show us what promotions are effective when customers are in a positive mood."

[0499] "Use customer sentiment data to suggest ways to deliver a customized user experience for customers in a specific emotional state."

[0500] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0501] Step 1:

[0502] The server retrieves market data from an external API. The input is the external API endpoint (e.g., https: / / externalapi.com / marketdata), and the output is the retrieved market data. This data is temporarily stored. Specifically, it sends an HTTP request and receives the market data in JSON format as a response.

[0503] Step 2:

[0504] The server passes the acquired market data to an artificial intelligence tool for analysis. The input is market data and the output is the analysis results. This analysis uses machine learning algorithms (e.g., Python's TensorFlow or Scikit-learn). Specific operations include data cleaning, feature engineering, model training, and prediction.

[0505] Step 3:

[0506] The server converts the analyzed market data into constellations or galaxies for visualization. The input is the analysis results, and the output is the visualization data. This visualization places the data points in a three-dimensional space and renders them as constellations or galaxies based on specific patterns. Specific operations include conversion to three-dimensional coordinates, color coding, and clustering.

[0507] Step 4:

[0508] The server sends the generated visualization data to the terminal. The input is the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent to the terminal via a WebSocket or HTTP endpoint.

[0509] Step 5:

[0510] The device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). The input is the path to the necessary resources, and the output is the initialized system. Specifically, it uses Three.js to initialize the 3D scene, configure the camera, and create a renderer.

[0511] Step 6:

[0512] The device renders data in a virtual reality space based on the visualization data received from the server. The input is the visualization data from the server, and the output is the rendered data. Specifically, the device places data points in a three-dimensional space and allows the user to explore them.

[0513] Step 7:

[0514] The user enters the virtual reality environment using a VR device to explore and manipulate visualized market data. The input is wearing the VR device and the user's operation, and the output is the exploration result (e.g., information on the focused data point). Specific operations include interpreting the input of the VR controller and enabling the selection and movement of data points through the user interface.

[0515] Step 8:

[0516] When the user focuses on a specific market data point, detailed information about that point is displayed. The input is the user's operation (selecting the focus point), and the output is the display of detailed information. Specifically, the behavior is to overlay information related to the selected data point.

[0517] Step 9:

[0518] The user then creates an investment strategy based on the details and submits it to the system. The input is the user's investment strategy (e.g., selection, input form, confirmation), and the output is the submitted investment strategy. Specific operations include collecting user input, recording the investment strategy, and sending it to the server.

[0519] Step 10:

[0520] The server recognizes the user's emotional data and analyzes the information. The input is the user's emotional data (e.g., heart rate, facial expression analysis data), and the output is the analyzed emotional information. Specifically, it runs the emotion recognition algorithm and stores the results in a database.

[0521] Step 11:

[0522] The emotion engine optimizes the user experience based on the recognized emotion information. The input is analyzed emotion information, and the output is an optimized user experience (e.g., interface adjustments, promotion suggestions). Specific operations include dynamic adjustment of the system according to the emotional state.

[0523] 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.

[0524] 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.

[0525] 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.

[0526] [Second embodiment]

[0527] FIG. 3 shows an example of the configuration of a data processing system 210 according to the second embodiment.

[0528] 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.

[0529] 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).

[0530] 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.

[0531] 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.

[0532] 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).

[0533] 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.

[0534] 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.

[0535] 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.

[0536] 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.

[0537] In the smart glasses 214, the processor 46 performs the reception output process. A reception output program 60 is stored in the storage 50. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output process is realized by the processor 46 operating as the control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0538] 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."

[0539] The present invention relates to a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a form that can be intuitively understood by a user. The following describes in detail embodiments of the present invention.

[0540] System configuration

[0541] server

[0542] The server has means for obtaining market data in real time. The market data obtained from the external API is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database for later access. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0543] Specifically, the server retrieves market data through external APIs and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze the data for trends and patterns. The results are stored in a database and can be searched as needed. The data from the database is transformed into constellations and galaxies by a visualization means.

[0544] Terminal

[0545] The terminal has a means for providing a virtual reality environment to a user, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for the user to explore and operate within the virtual reality environment.

[0546] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). Next, it uses the virtual reality data received from the server to render the galaxy and constellations in the VR space. The user can freely explore the VR space and focus on stars that interest them.

[0547] User

[0548] Users can explore and intuitively manipulate market data visualizations within a virtual reality environment. When users focus on a particular star, detailed information related to that star is displayed. Users can then use this information to develop investment strategies and submit them to the system.

[0549] For example, a user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user can use it to develop an investment strategy. This investment strategy is sent to a server and stored in a database.

[0550] Program processing

[0551] (Server behavior)

[0552] The server retrieves market data from external APIs and stores it temporarily.

[0553] The acquired data is passed to an artificial intelligence means for analysis in real time.

[0554] The analysis results are stored in a database and visualization data is generated as needed.

[0555] Send visualization data to the device.

[0556] (Device operation)

[0557] The device initializes the virtual reality system and loads the necessary resources.

[0558] The visualization data received from the server is used to render the image in a virtual reality space.

[0559] It provides an intuitive interface for users to explore and navigate.

[0560] (user actions)

[0561] The user wears a VR device and explores the virtual reality space.

[0562] Focus on a specific star to see more information about it.

[0563] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[0564] As a result, the present invention promotes intuitive understanding of market data and provides an environment in which users can effectively formulate investment strategies.

[0565] The processing flow will be explained below.

[0566] Step 1:

[0567] server

[0568] Obtain real-time market data from external APIs and temporarily store the data.

[0569] Specific actions

[0570] Call external APIs, receive market data, and store it in storage.

[0571] Step 2:

[0572] server

[0573] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[0574] Specific actions

[0575] Input the data into an analytical artificial intelligence module, triggering a task to analyze the data for trends and patterns.

[0576] Step 3:

[0577] server

[0578] The analysis results from the artificial intelligence means are received and stored in a database.

[0579] Specific actions

[0580] Save the analysis results in a database to ensure that the results can be accessed later.

[0581] Step 4:

[0582] server

[0583] The analysis results are extracted from the database and converted into constellation and galaxy shapes for visualization.

[0584] Specific actions

[0585] The analysis results are read and visualized using an algorithm that converts them into the shapes of constellations and galaxies.

[0586] Step 5:

[0587] server

[0588] The generated visualization data is sent to the terminal.

[0589] Specific actions

[0590] The visualization data is transmitted to a user terminal via a network.

[0591] Step 6:

[0592] Terminal

[0593] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[0594] Specific actions

[0595] Starts the VR system and loads the resource file into memory.

[0596] Step 7:

[0597] Terminal

[0598] The visualization data received from the server is used to render the image in a virtual reality space.

[0599] Specific actions

[0600] A 3D model is generated based on the received data, and then placed and rendered in the VR space.

[0601] Step 8:

[0602] Terminal

[0603] It provides an interface that allows users to explore and manipulate market data visualized in a VR space.

[0604] Specific actions

[0605] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[0606] Step 9:

[0607] User

[0608] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[0609] Specific actions

[0610] Select a specific star and navigate through menus and popups to view related data.

[0611] Step 10:

[0612] User

[0613] An investment strategy is developed based on the detailed information obtained and sent to the server.

[0614] Specific actions

[0615] Enter your plan and hit submit using the interface to analyze detailed information and develop new investment strategies.

[0616] Step 11:

[0617] server

[0618] The investment strategy sent by the user is received and stored in a database.

[0619] Specific actions

[0620] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[0621] In this way, through detailed step-by-step processing, the present invention realizes a series of processes for collecting, analyzing, and visualizing market data, and for users to develop investment strategies.

[0622] Example 1

[0623] 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."

[0624] The goal is to realize a system that analyzes market data in real time and visualizes it in a way that is easy for users to understand intuitively, provides an intuitive interface for exploring and manipulating this visualized data within a virtual reality environment, and provides detailed information about market data points of interest to users, allowing them to create and execute investment strategies based on that information.

[0625] 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.

[0626] In this invention, the server includes means for acquiring market data, machine learning means for analyzing the acquired market data, means for converting the analyzed market data into the shapes of constellations or galaxies and visualizing them, means for rendering the visualized data in a virtual reality environment, interface means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for saving the acquired market data in a database, and means for a user to submit an investment strategy developed in the virtual reality environment. This allows a user to visualize market data in an intuitively understandable form and explore the data in the virtual reality environment to obtain detailed information. Furthermore, investment strategies can be efficiently developed and submitted based on the acquired information.

[0627] "Market data" refers to data that can be obtained in real time, including transaction data, price data, trading volume data, market trend data, etc. from financial markets and commodity markets.

[0628] An "external API" refers to an application programming interface provided by an external system or service, and is an interface for obtaining information such as market data.

[0629] "Machine learning tools" refer to algorithms or models used to analyze market data and identify patterns and trends, for example, using machine learning frameworks such as TensorFlow or PyTorch.

[0630] "Visualization means" refers to a means for converting analyzed market data into the shapes of constellations or galaxies in a form that is intuitively easy for users to understand and display it, and includes 3D modeling and data visualization techniques.

[0631] "Virtual reality environment" refers to a three-dimensional computer-generated space experienced by a user using a VR device, including those that allow the user to experience and manipulate an environment that is not physically present.

[0632] "Interface means" refers to the operating elements and input devices required for a user to explore and manipulate the visualized market data within the virtual reality environment, including, for example, a VR controller and an intuitive operating panel.

[0633] "Database" refers to a system that efficiently stores and manages data and enables data search and retrieval through queries, including, for example, SQL databases.

[0634] "Investment Strategy" refers to the investment plans and decisions formulated by users based on the analysis results and detailed information of market data, which are submitted and executed through the system.

[0635] The present invention is a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a format that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[0636] Server configuration and operation

[0637] Obtaining Market Data

[0638] The server retrieves market data from an external API (e.g., a financial data API). The server sends an HTTP request, receives the market data in JSON format, and temporarily stores it.

[0639] Data analysis

[0640] The server analyzes the stored market data using artificial intelligence tools, specifically machine learning frameworks (e.g., TensorFlow and PyTorch), to extract trends and patterns based on past data and make future predictions.

[0641] Generate and save visualization data

[0642] The analysis results are stored in a database (e.g., PostgreSQL). The server then converts the analysis results into constellation and galaxy shapes through visualization tools, using 3D modeling techniques such as D3.js and Three.js.

[0643] Submitting visualization data

[0644] The server sends the generated visualization data to the terminal in JSON format using the HTTP protocol.

[0645] Terminal configuration and operation explanation

[0646] Initializing the Virtual Reality System

[0647] The device initializes the virtual reality system (e.g., Oculus Quest 2) and loads the necessary 3D models and scripts using a game engine (e.g., Unity or Unreal Engine).

[0648] Drawing visualized data

[0649] The device receives visualization data from the server and renders it in the virtual reality space. The data is received via WebSocket or HTTP communication and displayed as constellations and galaxies in 3D space.

[0650] Providing an interface

[0651] The device provides an intuitive interface that allows users to explore and manipulate virtual reality spaces using VR controllers, and includes scripts for rich interactions.

[0652] User Action Description

[0653] Access to virtual reality spaces

[0654] The user puts on a VR device, launches a VR application on the device, and enters the virtual reality space. Specifically, the user puts on a device such as Oculus Quest 2.

[0655] Explore and explore visualized data

[0656] Users explore visualized constellations and galaxies in a virtual reality space, and by using the VR controller to focus on a star of interest, detailed market data related to that star is displayed.

[0657] Investment strategy planning and submission

[0658] The user can create an investment strategy based on the displayed details and enter it in the input form provided in the VR space. The completed investment strategy is then sent to the server by clicking the submit button and saved in the database.

[0659] Examples of concrete examples and prompts

[0660] Specific examples

[0661] Users access the system using Oculus Quest 2 and explore market data visualized in virtual reality (for example, the shape of the galaxy). Focusing on a specific star displays stock price data for companies related to that star, and users can then develop investment strategies based on that information and submit them in the VR space.

[0662] Prompt Sentence Examples

[0663] "Please explain how a system for visualizing real-time market data in a virtual reality environment works. The system takes market data, analyzes it using artificial intelligence, and then displays it in a VR space as constellations or galaxies. For each step, please detail the specific hardware and software used, as well as the data generated and manipulated. Also, please provide examples of how a user might use the system to manipulate the data and develop an investment strategy."

[0664] As a result, the present invention provides an environment in which users can intuitively understand market data and plan and implement effective investment strategies.

[0665] The flow of the identification process in the first embodiment will be described with reference to FIG.

[0666] Step 1: Obtain market data

[0667] The server sends an HTTP request to an external API to retrieve market data. The retrieved market data is received in JSON format and temporarily stored in memory. The input is the API endpoint and query parameters, and the output is a JSON object of market data. For example, a specific operation would be to query "https: / / api.financedata.com / marketdata" and retrieve the returned price and volume data.

[0668] Step 2: Analyze the data

[0669] The server inputs the acquired market data into a machine learning model for analysis. During this process, a Python script is used to run a TensorFlow or PyTorch model. The input is a JSON object of market data, and the output is the analysis results (prediction data including trends and patterns). Specifically, it runs a neural network model that uses past stock price data to predict future prices.

[0670] Step 3: Save your data

[0671] The server saves the analysis results in a database (PostgreSQL). The input is the data structure of the analysis results, and the output is the state of storage in the database. Specifically, the analysis results are saved in the appropriate table in the database using an SQL insert statement.

[0672] Step 4: Generate visualization data

[0673] The server generates visualization data based on the saved analysis results. The data is converted into the shapes of constellations and galaxies using 3D modeling software (D3.js or Three.js). The input is the analysis results and a template for the 3D modeling software, and the output is 3D visualization data. Specifically, the data points from the analysis results are converted into 3D coordinate data and output in WebGL format.

[0674] Step 5: Sending data

[0675] The server sends the generated visualization data to the terminal. The visualization data is sent in JSON format to the terminal using the HTTP protocol. The input is a JSON object of the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent using an HTTP POST request.

[0676] Step 6: Initializing the Virtual Reality System

[0677] The device starts the virtual reality system (Oculus Quest 2) and loads the necessary resources, including 3D models and scripts. The input is a list of required resources, and the output is an initialized virtual reality environment. Specifically, the 3D environment is built using Unity or Unreal Engine and initialized.

[0678] Step 7: Rendering the visualization

[0679] The device receives visualization data from the server and renders it in a virtual reality space. The input is a JSON object of the visualization data, and the output is a visualized 3D space. Specifically, the device receives data via WebSocket or HTTP communication and executes a script to render it in the 3D space.

[0680] Step 8: Providing an Interface

[0681] The device provides an intuitive interface for users to explore and manipulate the virtual reality space. The input is the user's operation input, and the output is an interface that can be explored and manipulated. Specific operations are implemented as scripts that accept user movement and selection operations via the VR controller.

[0682] Step 9: Access the virtual reality space

[0683] The user wears a VR device and accesses a virtual reality space. The input is the VR device, and the output is the accessed virtual reality space. Specifically, the user wears the Oculus Quest 2, launches a VR application, and enters the virtual reality space.

[0684] Step 10: Explore and review the visualized data

[0685] Users explore the visualized constellations and galaxies in a virtual reality space and focus on a specific star. The input is the visualization data and user operations, and the output is detailed information about the focused star. Specific actions include selecting a specific star using the VR controller and displaying a pop-up with market data related to that star.

[0686] Step 11: Develop and submit your investment strategy

[0687] The user creates an investment strategy based on the displayed detailed information and submits it using the input form provided within the system. The input is the detailed information and the user's input, and the output is data transmission to the server. Specifically, the user enters the investment strategy into the input form in the VR space and clicks the send button to send it to the server.

[0688] This allows users to intuitively understand market data and develop and submit effective investment strategies.

[0689] (Application example 1)

[0690] 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."

[0691] In today's investment environment, massive amounts of market data are generated in real time, making it difficult to effectively analyze and intuitively understand it. Furthermore, there are insufficient means to quickly develop and implement investment strategies based on the analyzed data. As a result, users are easily confused by information overload and complex data analysis when making investment decisions, which can make it difficult to make appropriate investment decisions.

[0692] 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.

[0693] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for a user to use the visualized market data on a smartphone platform to develop and submit an investment strategy, means for using a generative AI model to visualize the market data in the virtual reality environment based on criteria specified by the user, and means for inputting prompt statements to the generative AI model and adjusting the visualization of the market data based on the prompt statements, thereby enabling a user to intuitively understand the market data and develop and execute effective and rapid investment strategies.

[0694] "Market data" refers to data such as stock prices, trading volumes, and economic indicators obtained from stock exchanges and other financial markets.

[0695] "Artificial intelligence tools" are programs or systems that use machine learning or deep learning algorithms to analyze trends and patterns in market data.

[0696] "Visualization tools" are technologies and systems that convert data into the shapes of constellations and galaxies and display them in a way that users can intuitively understand.

[0697] A "virtual reality environment" is a computer-generated three-dimensional space and interface that allows users to freely explore and manipulate it.

[0698] "Smartphone platform" refers to applications and systems that run on smartphones and provide the infrastructure for users to view and manipulate market data.

[0699] "Generative AI models" refer to AI techniques and algorithms that analyze and visualize data based on user-specified criteria.

[0700] A "prompt" is text data that is input to a generative AI model, and is an instruction that adjusts the visualization of the data based on that text.

[0701] An "investment strategy" is an investment policy or plan that a user formulates based on market data and its analysis results.

[0702] MODE FOR CARRYING OUT THE INVENTION

[0703] The present invention relates to a system that acquires market data in real time, analyzes it using artificial intelligence means, and visualizes the results in a form that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[0704] Server configuration and operation

[0705] A server is a device that has the following main functions:

[0706] 1. Market data acquisition methods:

[0707] The server retrieves market data from stock exchanges and other financial markets through APIs, including stock prices, trading volumes, economic indicators, and more.

[0708] 2. Artificial Intelligence Means:

[0709] To analyze the acquired market data, machine learning and deep learning algorithms are used, specifically software such as TensorFlow and PyTorch, to analyze trends and patterns in the data.

[0710] 3. Visualization tools:

[0711] It uses algorithms to convert the results of the analysis into the shapes of constellations and galaxies, and this visualization data is stored in a database and generated as needed.

[0712] Terminal configuration and operation

[0713] The terminal is a device that allows a user to explore and manipulate market data within a virtual reality environment.

[0714] 1. Virtual reality systems:

[0715] The device uses a VR device (such as Oculus Rift or Google Cardboard) to provide the user with a virtual reality environment. The VR library used is Unity or Unreal Engine.

[0716] 2. Smartphone Platform:

[0717] It displays visualized market data through an application that runs on smartphones, allowing users to browse and explore the data using their smartphones.

[0718] 3. Generative AI Model:

[0719] The generative AI model is used to perform analysis and visualization based on user-specified criteria, and the user can make specific requests to the generative AI model by entering prompt statements.

[0720] User interaction and usage

[0721] Users can explore market data using their smartphones or VR devices, and then develop and submit investment strategies based on the visualized data.

[0722] 1. Exploration and manipulation in virtual reality environments:

[0723] Users explore market data visualized as constellations and galaxies in a VR space, and by focusing on a particular star, more information related to that star is displayed.

[0724] 2. Investment strategy planning and submission:

[0725] Based on the information obtained in the virtual reality environment, users can plan their investment strategies, which are then submitted to the server via a smartphone application and stored in a database.

[0726] Usage examples and prompt statements

[0727] For example, a user might input a prompt like, "Analyze the latest US stock market data and generate a galaxy visualization showing trends in the technology sector. By focusing on a specific star, display the company's financial forecast." Based on this prompt, the generative AI model analyzes the data and creates a visualization that meets the specified criteria.

[0728] This allows users to more intuitively understand market data and develop investment strategies quickly and effectively.

[0729] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[0730] Step 1:

[0731] The server retrieves market data from an external API. Specifically, the server sends a request to the market data API and retrieves real-time market data as an API response. This market data includes stock prices, trading volume, economic indicators, etc. The server temporarily stores this data.

[0732] Input: Response data from the Market Data API

[0733] Output: Temporarily stored market data

[0734] Step 2:

[0735] The server analyzes the acquired market data using artificial intelligence means, specifically machine learning and deep learning algorithms (e.g., TensorFlow and PyTorch), to analyze the market data and extract trends and patterns. The analysis results are stored in a database.

[0736] Input: Temporarily stored market data

[0737] Output: Analysis results (trend and pattern information)

[0738] Step 3:

[0739] The server then visualizes the analyzed market data using an algorithm that converts the analysis results into the shapes of constellations and galaxies, generating visualizations that are then stored in a database.

[0740] Input: Analysis results

[0741] Output: Visualization data (shapes of constellations and galaxies)

[0742] Step 4:

[0743] The device initializes the virtual reality system. Specifically, it loads the necessary resources (models, textures, scripts, etc.) and creates the virtual reality environment. Unity or Unreal Engine is used as the VR library.

[0744] Input: Resources for a virtual reality environment

[0745] Output: Initialized virtual reality system

[0746] Step 5:

[0747] The device uses the visualization data received from the server to render the image in a virtual reality space. Specifically, the visualization data obtained from the server is displayed in the VR space, allowing the user to explore the space.

[0748] Input: Visualization data

[0749] Output: Visualization data rendered in virtual reality space

[0750] Step 6:

[0751] Users explore and interact with a virtual reality environment, using a VR device to explore market data visualized as constellations and galaxy shapes. By focusing on a star of interest, detailed market data related to that star is displayed.

[0752] Input: Visualization data of virtual reality space

[0753] Output: Detailed market data displayed as a result of the user's search

[0754] Step 7:

[0755] Users create investment strategies based on the information they obtain in the virtual reality environment and submit them to a server via a smartphone application. For example, a user might create an investment strategy such as "purchase stocks of a specific company based on trends in the technology sector" and send that strategy to the server.

[0756] Input: Investment strategy designed by the user

[0757] Output: Investment strategy submitted to the server

[0758] Step 8:

[0759] The server inputs prompts into the generative AI model, which then adjusts the visualization of the market data based on those prompts. Specifically, the server analyzes the prompts entered by the user, reanalyzes the market data based on those criteria, and generates updated visualizations.

[0760] Input: The prompt text entered by the user

[0761] Output: Visualization data regenerated based on the prompt statement

[0762] In this way, this system realizes a series of processes from acquiring market data to analyzing, visualizing, displaying in a virtual reality environment, and formulating and submitting investment strategies, allowing users to intuitively understand market data and effectively formulate investment strategies.

[0763] 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.

[0764] The present invention relates to a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by users in a virtual reality environment. The present invention also includes an emotion engine that recognizes users' emotions and optimizes the user experience based on their emotional state. Specific embodiments for implementing the present invention are described in detail below.

[0765] System configuration

[0766] server

[0767] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0768] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. Furthermore, an emotion engine is built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[0769] Terminal

[0770] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[0771] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[0772] User

[0773] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[0774] Specifically, the user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[0775] Program processing

[0776] (Server behavior)

[0777] The server retrieves market data from external APIs and stores it temporarily.

[0778] The acquired data is passed to an artificial intelligence means for analysis in real time.

[0779] The analysis results are stored in a database and visualization data is generated as needed.

[0780] Send visualization data to the device.

[0781] The emotion engine analyzes the user's emotion data and generates data to optimize the user experience.

[0782] (Device operation)

[0783] The device initializes the virtual reality system and loads the necessary resources.

[0784] The visualization data received from the server is used to render the image in a virtual reality space.

[0785] It provides an intuitive interface for users to explore and navigate.

[0786] The emotion engine obtains the user's emotional data in real time and adjusts the display method and interaction.

[0787] (user actions)

[0788] The user wears a VR device and explores the virtual reality space.

[0789] Focus on a specific star to see more information about it.

[0790] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[0791] Users receive feedback from the sentiment engine and adjust their investment strategies.

[0792] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[0793] The processing flow will be explained below.

[0794] Step 1:

[0795] server

[0796] Obtain real-time market data from external APIs and temporarily store the data.

[0797] Specific actions

[0798] Calls external APIs to obtain market data, which is then stored in storage.

[0799] Step 2:

[0800] server

[0801] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[0802] Specific actions

[0803] Input market data into the artificial intelligence module and trigger a task to analyze the data for trends and patterns.

[0804] Step 3:

[0805] server

[0806] The analysis results from the artificial intelligence means are received and stored in a database.

[0807] Specific actions

[0808] The analysis results are stored in a database and managed in a form that can be accessed later.

[0809] Step 4:

[0810] server

[0811] The analysis results are extracted from the database and data is converted for visualization.

[0812] Specific actions

[0813] The analysis results are read and visualized using algorithms that convert them into the shapes of constellations and galaxies.

[0814] Step 5:

[0815] server

[0816] The generated visualization data is sent to the terminal.

[0817] Specific actions

[0818] The visualization data is transmitted to the user's terminal via a network.

[0819] Step 6:

[0820] Terminal

[0821] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[0822] Specific actions

[0823] Starts the VR system, loads resource files, and prepares the virtual reality space.

[0824] Step 7:

[0825] Terminal

[0826] The visualization data received from the server is rendered in a virtual reality space.

[0827] Specific actions

[0828] It analyzes the received visualization data and draws it based on the shapes of constellations and galaxies.

[0829] Step 8:

[0830] Terminal

[0831] It provides an interface that allows users to explore and manipulate visualized market data within a virtual reality space.

[0832] Specific actions

[0833] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[0834] Step 9:

[0835] User

[0836] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[0837] Specific actions

[0838] Select a specific star. Detailed information related to the selected star will be displayed as a pop-up or menu.

[0839] Step 10:

[0840] server

[0841] Detailed information relating to a particular star selected by the user is retrieved from the database and transmitted to the user terminal.

[0842] Specific actions

[0843] It searches the database for information related to a specific star and transmits the obtained information to the user terminal.

[0844] Step 11:

[0845] User

[0846] An investment strategy is developed based on the detailed information obtained and sent to the server.

[0847] Specific actions

[0848] Analyze detailed information and enter and submit new investment strategies through the interface.

[0849] Step 12:

[0850] server

[0851] The investment strategy sent by the user is received and stored in a database.

[0852] Specific actions

[0853] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[0854] Step 13:

[0855] Terminal

[0856] An emotion engine is activated to obtain user emotion data in real time.

[0857] Specific actions

[0858] The emotion engine analyzes the user's facial expressions and biometric information to obtain their current emotional state.

[0859] Step 14:

[0860] server

[0861] The acquired emotional data is analyzed by an emotion engine, and the display method and interaction of the visualized data are dynamically adjusted.

[0862] Specific actions

[0863] Analyze emotional data and adjust presentation and interaction methods to optimize the user experience.

[0864] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[0865] Example 2

[0866] 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."

[0867] Modern market data is massive and complex, making it difficult for individual investors and analysts to intuitively understand and analyze the data. Furthermore, there is a lack of systems that can analyze data, including the user's emotional state, and provide appropriate feedback based on that data. This makes it difficult to make investment decisions and quickly respond to market fluctuations.

[0868] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[0869] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, and means for analyzing the user's emotional data and generating feedback to optimize the user experience, thereby enabling the user to intuitively understand large amounts of complex market data and make more accurate and prompt investment decisions while receiving feedback that takes their emotional state into account.

[0870] "Market data" refers to trading information such as stock prices, foreign exchange rates, and commodity prices in the market, and related data.

[0871] "Means of Acquisition" refers to the methods and devices used to collect market data from external APIs and data providers.

[0872] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze trends and patterns in data.

[0873] "Visualization means" refers to a method or system for converting the analyzed data into visual shapes, such as constellations or galaxies, and displaying them to a user.

[0874] A "virtual reality environment" refers to an environment in which a user can experience a virtually constructed three-dimensional space using a dedicated device.

[0875] "Exploration and manipulation means" refers to the interfaces and devices that allow a user to move around in a virtual reality space and focus on specific objects.

[0876] "Emotional data" refers to data relating to the emotional state of a user obtained by analyzing the user's facial expressions, voice, heart rate, etc.

[0877] "Generated feedback" refers to advice or instructions provided to the user based on the analyzed emotional data.

[0878] The present invention is a system that acquires market data, analyzes it using artificial intelligence, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that analyzes the user's emotion data and enables the optimization of the user experience. Specific embodiments for implementing the present invention are described in detail below.

[0879] Server Operation

[0880] The server retrieves market data in real time through external APIs (e.g., Alpha Vantage API or Yahoo Finance API). This data is temporarily stored and then analyzed using artificial intelligence tools (e.g., TensorFlow or PyTorch). The results of the analysis are then stored in a database (e.g., MySQL or MongoDB) and visualizations (e.g., generated with SVG or D3.js) are generated as needed.

[0881] Example: A server retrieves TSLA stock price data from the Alpha Vantage API, analyzes this market data for trends using TensorFlow, and stores the results in MySQL.

[0882] Example prompt: Get TSLA stock price data from the Alpha Vantage API and store it in Redis.

[0883] Example prompt: Use TensorFlow to analyze this market data for trends and store the results in MySQL.

[0884] Additionally, the server is equipped with an emotion engine (e.g., Emotion AI API) that analyzes user emotion data and generates feedback to optimize the user experience.

[0885] Example: Analyzing the user's facial expression data with the Emotion AI API and generating feedback for relaxation.

[0886] Example prompt: Analyze the user's facial expression data using the Emotion AI API and generate feedback to help them relax.

[0887] Device behavior

[0888] The terminal uses a VR device (e.g., Oculus Rift, HTC Vive) to provide a virtual reality environment. It receives visualization data sent from the server and renders it in the virtual reality space. Within this space, an intuitive interface is provided for the user to explore and manipulate.

[0889] Example: Initialize the Oculus Rift, load the necessary 3D models and textures, and draw a galaxy in a virtual space based on the received data.

[0890] Example prompt: Initialize your Oculus Rift and load any necessary 3D models and textures.

[0891] Example prompt: Draw the received visualization data into the virtual reality space using the Unity engine.

[0892] The device also receives real-time feedback from the emotion engine and dynamically adjusts how it displays and interacts with the device.

[0893] Example: Changing the colors and effects of a virtual space based on the user's emotional data received in real time from the Emotion AI API.

[0894] Example prompt: Get the user's emotional data in real time and adjust the colors and effects of the virtual space.

[0895] User Actions

[0896] Users put on a VR device and explore the virtual reality space. By focusing on a specific star, detailed market data related to that star is displayed. Based on this information, users can create an investment strategy and submit it to the system. They can also receive feedback from the emotion engine and adjust their investment strategy based on that feedback.

[0897] Example: A user puts on an Oculus Rift, focuses on a star displaying TSLA market data, examines its details, and then uses a virtual keyboard to input their investment strategy and submit it to the system.

[0898] Sample prompt: Allow the user to put on a VR device and explore a virtual space.

[0899] Example prompt: Provide a system that displays detailed data for the star the user selects.

[0900] Example prompt: Please provide a system that allows users to input their investment strategies and submit them to the server.

[0901] Example prompt: Provide a system to adjust and resubmit investment strategies based on feedback from the sentiment engine.

[0902] In this way, the present invention can smoothly carry out a series of processes including collection, analysis, and visualization of market data, operation in a virtual reality space by the user, and feedback based on emotional data.

[0903] The flow of the identification process in the second embodiment will be described with reference to FIG.

[0904] Step 1:

[0905] Obtaining Market Data

[0906] The server calls external APIs (e.g., Alpha Vantage API or Yahoo Finance API) to obtain market data. The server temporarily stores the obtained data in storage. At this time, a specific stock or product is specified in the request, and the data is received in JSON format as a response.

[0907] What happens: The server makes a request to the Alpha Vantage API to get the latest stock price data for TSLA, and temporarily stores this data in a Redis cache.

[0908] Input: API request (e.g., specific stock identifier)

[0909] Output: Market data in JSON format (e.g., TSLA stock price data)

[0910] Step 2:

[0911] Data analysis

[0912] The server passes the acquired market data to an artificial intelligence algorithm (e.g., TensorFlow, PyTorch) that analyzes the data for trends and patterns. The analysis results are stored in a database. At this time, the input data is processed by a machine learning model, and trend information and patterns are generated as output.

[0913] Specific operation: Using TensorFlow, the acquired TSLA stock price data is analyzed, trend information is generated, and the results are stored in a MySQL database.

[0914] Input: Market data in JSON format

[0915] Output: Analysis results (e.g., trend information)

[0916] Step 3:

[0917] Visualization data generation

[0918] The server generates visualization data based on the analyzed data and converts it into the shapes of constellations and galaxies. The visualization data is generated using SVG, D3.js, etc. In this case, the input data is the analysis results, and the output data is in a format that can be displayed visually.

[0919] Specific operation: Using the analysis results, the D3.js library is used to generate galaxy shape data and create visualization data in SVG format.

[0920] Input: Analysis results

[0921] Output: Visualization data (e.g., Galaxy shape in SVG format)

[0922] Step 4:

[0923] Emotional Data Analysis

[0924] The server uses an emotion engine (e.g., Emotion AI API) to analyze the user's emotional data. Based on the analysis results, it generates feedback to optimize the user experience. In this case, the input data is emotional data such as the user's facial expressions and voice, and the output data is feedback information.

[0925] Specific operation: Sends the user's facial expression data to the Emotion AI API, and generates feedback to help them relax as a result of the analysis.

[0926] Input: User emotion data (e.g., facial expression data)

[0927] Output: Feedback information

[0928] Step 5:

[0929] Initializing the Virtual Reality System

[0930] The device initializes the VR device (e.g., Oculus Rift, HTC Vive) and loads the necessary resources (models, textures, scripts, etc.) from pre-prepared files or databases.

[0931] Specific operation: Starts Oculus Rift and loads 3D model and texture files into the device's memory.

[0932] Input: VR device, resource files (e.g. 3D models, textures)

[0933] Output: Initialized virtual reality environment

[0934] Step 6:

[0935] Drawing visualized data

[0936] The device renders galaxies and constellations in the virtual reality space based on the visualization data received from the server, allowing users to intuitively grasp the data within the VR space.

[0937] Specific operation: Receives visualization data in SVG format from the server and draws a 3D model of the galaxy in virtual reality space using the Unity engine.

[0938] Input: Visualization data

[0939] Output: Rendered virtual reality space

[0940] Step 7:

[0941] Providing a user interface

[0942] The device provides an intuitive interface for users to explore and interact with, and when users focus on a particular object, detailed information about it is displayed.

[0943] What it does: Provides a UI that allows the user to select a constellation using a VR controller.

[0944] Input: User action

[0945] Output: Detailed information displayed

[0946] Step 8:

[0947] Real-time acquisition of user emotion data and interaction adjustment

[0948] The device receives data from the emotion engine in real time and adjusts how it displays and interacts with the device, dynamically optimizing the user experience.

[0949] Specific operation: Changes the colors and effects of the virtual space based on the user's emotional data received in real time from the Emotion AI API.

[0950] Input: Real-time user emotion data

[0951] Output: Calibrated virtual reality space

[0952] Step 9:

[0953] Verifying information, formulating investment strategies, and submitting them

[0954] Users can focus on a specific star in the VR space, check related information, and then create an investment strategy based on that information and submit it to the system.

[0955] Specific operation: The user uses the VR controller to focus on the star with TSLA market data to view detailed information, enter investment strategies using the virtual keyboard, and send them to the system.

[0956] Input: User actions, investment strategies

[0957] Output: Submitted investment strategy

[0958] Step 10:

[0959] Adjusting investment strategies

[0960] Users can reassess their investment strategy based on feedback from the sentiment engine and make adjustments as needed.

[0961] What happens: After receiving feedback from the sentiment engine indicating "tension," the user reevaluates, amends, and resubmits their investment strategy.

[0962] Input: Emotion engine feedback

[0963] Output: Adjusted investment strategy

[0964] (Application example 2)

[0965] 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."

[0966] Conventional virtual storefront systems lack functionality that allows users to intuitively understand market data and effectively plan investment strategies. Furthermore, they lack dynamic experience optimization that takes into account the user's emotional state, resulting in a lack of quality improvement in the user experience. Therefore, a new system is needed that not only analyzes market data in real time, intuitively visualizes it, and displays it in a virtual reality environment, but also optimizes the experience based on the user's emotions.

[0967] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[0968] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, and means for converting the analyzed market data into the shapes of constellations or galaxies for visualization. This allows users to visually understand and explore the data within a virtual reality environment. Furthermore, the server includes an emotion engine that recognizes the user's emotional data and optimizes the user experience based on the user's emotional state. Having means for dynamically adjusting the layout and promotional strategies of the virtual store based on the emotion engine makes it possible to provide a high-quality experience tailored to the user's emotions.

[0969] "Market data" is a general term for information including prices, supply, demand, and trading volume of goods and services in the market.

[0970] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze, predict, and classify data.

[0971] "Visualization" refers to the process of transforming and displaying data in a way that is intuitively understandable to users.

[0972] "Constellations and galactic shapes" refers to the way data points are visualized, arranging them to resemble astronomical objects.

[0973] "Virtual reality environment" refers to a digital environment in which a user is immersed in a computer-generated three-dimensional space.

[0974] "User" means any person who utilizes the System to explore and manipulate Market Data.

[0975] An "emotion engine" refers to a system that has the ability to recognize a user's emotional state and optimize the experience based on that.

[0976] "Virtual store layout" refers to the product placement and spatial design within a virtual reality environment.

[0977] A "promotion strategy" refers to a plan or method for effectively selling a particular product or service.

[0978] The present invention is a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that recognizes the user's emotions and optimizes the user experience based on the user's emotional state. Specific embodiments for implementing the present invention are described in detail below.

[0979] System configuration

[0980] server

[0981] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[0982] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms (e.g., Python libraries TensorFlow and Scikit-learn) to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. An emotion engine is also built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[0983] Terminal

[0984] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[0985] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. This visualization is achieved using a 3D rendering library such as Three.js. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[0986] User

[0987] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[0988] Specifically, the user puts on a VR device (e.g., Oculus Rift, HTC Vive, etc.) and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[0989] Program processing

[0990] The main hardware includes a server (data acquisition, analysis, and storage), a VR terminal (providing a virtual reality environment and drawing data), and a user device (VR device).The main software includes external API access, machine learning libraries (TensorFlow, Scikit-learn), a database management system, and a 3D drawing library (Three.js).

[0991] Adding specific examples

[0992] Examples of promotion optimization in virtual stores include:

[0993] 1. Providing optimal promotion strategies in real time based on customer data and market trends.

[0994] 2. An emotional engine determines whether customers are enjoying themselves and dynamically changes the interface and layout if a certain emotional state persists.

[0995] Prompt Sentence Examples

[0996] "Optimize the current virtual store layout based on the latest market data. Also show us what promotions are effective when customers are in a positive mood."

[0997] "Use customer sentiment data to suggest ways to deliver a customized user experience for customers in a specific emotional state."

[0998] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[0999] Step 1:

[1000] The server retrieves market data from an external API. The input is the external API endpoint (e.g., https: / / externalapi.com / marketdata), and the output is the retrieved market data. This data is temporarily stored. Specifically, it sends an HTTP request and receives the market data in JSON format as a response.

[1001] Step 2:

[1002] The server passes the acquired market data to an artificial intelligence tool for analysis. The input is market data and the output is the analysis results. This analysis uses machine learning algorithms (e.g., Python's TensorFlow or Scikit-learn). Specific operations include data cleaning, feature engineering, model training, and prediction.

[1003] Step 3:

[1004] The server converts the analyzed market data into constellations or galaxies for visualization. The input is the analysis results, and the output is the visualization data. This visualization places the data points in a three-dimensional space and renders them as constellations or galaxies based on specific patterns. Specific operations include conversion to three-dimensional coordinates, color coding, and clustering.

[1005] Step 4:

[1006] The server sends the generated visualization data to the terminal. The input is the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent to the terminal via a WebSocket or HTTP endpoint.

[1007] Step 5:

[1008] The device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). The input is the path to the necessary resources, and the output is the initialized system. Specifically, it uses Three.js to initialize the 3D scene, configure the camera, and create a renderer.

[1009] Step 6:

[1010] The device renders data in a virtual reality space based on the visualization data received from the server. The input is the visualization data from the server, and the output is the rendered data. Specifically, the device places data points in a three-dimensional space and allows the user to explore them.

[1011] Step 7:

[1012] The user enters the virtual reality environment using a VR device to explore and manipulate visualized market data. The input is wearing the VR device and the user's operation, and the output is the exploration result (e.g., information on the focused data point). Specific operations include interpreting the input of the VR controller and enabling the selection and movement of data points through the user interface.

[1013] Step 8:

[1014] When the user focuses on a specific market data point, detailed information about that point is displayed. The input is the user's operation (selecting the focus point), and the output is the display of detailed information. Specifically, the behavior is to overlay information related to the selected data point.

[1015] Step 9:

[1016] The user then creates an investment strategy based on the details and submits it to the system. The input is the user's investment strategy (e.g., selection, input form, confirmation), and the output is the submitted investment strategy. Specific operations include collecting user input, recording the investment strategy, and sending it to the server.

[1017] Step 10:

[1018] The server recognizes the user's emotional data and analyzes the information. The input is the user's emotional data (e.g., heart rate, facial expression analysis data), and the output is the analyzed emotional information. Specifically, it runs the emotion recognition algorithm and stores the results in a database.

[1019] Step 11:

[1020] The emotion engine optimizes the user experience based on the recognized emotion information. The input is analyzed emotion information, and the output is an optimized user experience (e.g., interface adjustments, promotion suggestions). Specific operations include dynamic adjustment of the system according to the emotional state.

[1021] 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.

[1022] 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.

[1023] 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.

[1024] [Third embodiment]

[1025] FIG. 5 shows an example of the configuration of a data processing system 310 according to the third embodiment.

[1026] 5, the data processing system 310 includes the data processing device 12 and a headset terminal 314. An example of the data processing device 12 is a server.

[1027] 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).

[1028] 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.

[1029] 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.

[1030] 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).

[1031] 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.

[1032] 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.

[1033] 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.

[1034] 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.

[1035] 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.

[1036] 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."

[1037] The present invention relates to a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a form that can be intuitively understood by a user. The following describes in detail embodiments of the present invention.

[1038] System configuration

[1039] server

[1040] The server has means for obtaining market data in real time. The market data obtained from the external API is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database for later access. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1041] Specifically, the server retrieves market data through external APIs and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze the data for trends and patterns. The results are stored in a database and can be searched as needed. The data from the database is transformed into constellations and galaxies by a visualization means.

[1042] Terminal

[1043] The terminal has a means for providing a virtual reality environment to a user, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for the user to explore and operate within the virtual reality environment.

[1044] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). Next, it uses the virtual reality data received from the server to render the galaxy and constellations in the VR space. The user can freely explore the VR space and focus on stars that interest them.

[1045] User

[1046] Users can explore and intuitively manipulate market data visualizations within a virtual reality environment. When users focus on a particular star, detailed information related to that star is displayed. Users can then use this information to develop investment strategies and submit them to the system.

[1047] For example, a user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user can use it to develop an investment strategy. This investment strategy is sent to a server and stored in a database.

[1048] Program processing

[1049] (Server behavior)

[1050] The server retrieves market data from external APIs and stores it temporarily.

[1051] The acquired data is passed to an artificial intelligence means for analysis in real time.

[1052] The analysis results are stored in a database and visualization data is generated as needed.

[1053] Send visualization data to the device.

[1054] (Device operation)

[1055] The device initializes the virtual reality system and loads the necessary resources.

[1056] The visualization data received from the server is used to render the image in a virtual reality space.

[1057] It provides an intuitive interface for users to explore and navigate.

[1058] (user actions)

[1059] The user wears a VR device and explores the virtual reality space.

[1060] Focus on a specific star to see more information about it.

[1061] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[1062] As a result, the present invention promotes intuitive understanding of market data and provides an environment in which users can effectively formulate investment strategies.

[1063] The processing flow will be explained below.

[1064] Step 1:

[1065] server

[1066] Obtain real-time market data from external APIs and temporarily store the data.

[1067] Specific actions

[1068] Call external APIs, receive market data, and store it in storage.

[1069] Step 2:

[1070] server

[1071] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[1072] Specific actions

[1073] Input the data into an analytical artificial intelligence module, triggering a task to analyze the data for trends and patterns.

[1074] Step 3:

[1075] server

[1076] The analysis results from the artificial intelligence means are received and stored in a database.

[1077] Specific actions

[1078] Save the analysis results in a database to ensure that the results can be accessed later.

[1079] Step 4:

[1080] server

[1081] The analysis results are extracted from the database and converted into constellation and galaxy shapes for visualization.

[1082] Specific actions

[1083] The analysis results are read and visualized using an algorithm that converts them into the shapes of constellations and galaxies.

[1084] Step 5:

[1085] server

[1086] The generated visualization data is sent to the terminal.

[1087] Specific actions

[1088] The visualization data is transmitted to a user terminal via a network.

[1089] Step 6:

[1090] Terminal

[1091] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[1092] Specific actions

[1093] Starts the VR system and loads the resource file into memory.

[1094] Step 7:

[1095] Terminal

[1096] The visualization data received from the server is used to render the image in a virtual reality space.

[1097] Specific actions

[1098] A 3D model is generated based on the received data, and then placed and rendered in the VR space.

[1099] Step 8:

[1100] Terminal

[1101] It provides an interface that allows users to explore and manipulate market data visualized in a VR space.

[1102] Specific actions

[1103] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[1104] Step 9:

[1105] User

[1106] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[1107] Specific actions

[1108] Select a specific star and navigate through menus and popups to view related data.

[1109] Step 10:

[1110] User

[1111] An investment strategy is developed based on the detailed information obtained and sent to the server.

[1112] Specific actions

[1113] Enter your plan and hit submit using the interface to analyze detailed information and develop new investment strategies.

[1114] Step 11:

[1115] server

[1116] The investment strategy sent by the user is received and stored in a database.

[1117] Specific actions

[1118] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[1119] In this way, through detailed step-by-step processing, the present invention realizes a series of processes for collecting, analyzing, and visualizing market data, and for users to develop investment strategies.

[1120] Example 1

[1121] 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."

[1122] The goal is to realize a system that analyzes market data in real time and visualizes it in a way that is easy for users to understand intuitively, provides an intuitive interface for exploring and manipulating this visualized data within a virtual reality environment, and provides detailed information about market data points of interest to users, allowing them to create and execute investment strategies based on that information.

[1123] 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.

[1124] In this invention, the server includes means for acquiring market data, machine learning means for analyzing the acquired market data, means for converting the analyzed market data into the shapes of constellations or galaxies and visualizing them, means for rendering the visualized data in a virtual reality environment, interface means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for saving the acquired market data in a database, and means for a user to submit an investment strategy developed in the virtual reality environment. This allows a user to visualize market data in an intuitively understandable form and explore the data in the virtual reality environment to obtain detailed information. Furthermore, investment strategies can be efficiently developed and submitted based on the acquired information.

[1125] "Market data" refers to data that can be obtained in real time, including transaction data, price data, trading volume data, market trend data, etc. from financial markets and commodity markets.

[1126] An "external API" refers to an application programming interface provided by an external system or service, and is an interface for obtaining information such as market data.

[1127] "Machine learning tools" refer to algorithms or models used to analyze market data and identify patterns and trends, for example, using machine learning frameworks such as TensorFlow or PyTorch.

[1128] "Visualization means" refers to a means for converting analyzed market data into the shapes of constellations or galaxies in a form that is intuitively easy for users to understand and display it, and includes 3D modeling and data visualization techniques.

[1129] "Virtual reality environment" refers to a three-dimensional computer-generated space experienced by a user using a VR device, including those that allow the user to experience and manipulate an environment that is not physically present.

[1130] "Interface means" refers to the operating elements and input devices required for a user to explore and manipulate the visualized market data within the virtual reality environment, including, for example, a VR controller and an intuitive operating panel.

[1131] "Database" refers to a system that efficiently stores and manages data and enables data search and retrieval through queries, including, for example, SQL databases.

[1132] "Investment Strategy" refers to the investment plans and decisions formulated by users based on the analysis results and detailed information of market data, which are submitted and executed through the system.

[1133] The present invention is a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a format that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[1134] Server configuration and operation

[1135] Obtaining Market Data

[1136] The server retrieves market data from an external API (e.g., a financial data API). The server sends an HTTP request, receives the market data in JSON format, and temporarily stores it.

[1137] Data analysis

[1138] The server analyzes the stored market data using artificial intelligence tools, specifically machine learning frameworks (e.g., TensorFlow and PyTorch), to extract trends and patterns based on past data and make future predictions.

[1139] Generate and save visualization data

[1140] The analysis results are stored in a database (e.g., PostgreSQL). The server then converts the analysis results into constellation and galaxy shapes through visualization tools, using 3D modeling techniques such as D3.js and Three.js.

[1141] Submitting visualization data

[1142] The server sends the generated visualization data to the terminal in JSON format using the HTTP protocol.

[1143] Terminal configuration and operation explanation

[1144] Initializing the Virtual Reality System

[1145] The device initializes the virtual reality system (e.g., Oculus Quest 2) and loads the necessary 3D models and scripts using a game engine (e.g., Unity or Unreal Engine).

[1146] Drawing visualized data

[1147] The device receives visualization data from the server and renders it in the virtual reality space. The data is received via WebSocket or HTTP communication and displayed as constellations and galaxies in 3D space.

[1148] Providing an interface

[1149] The device provides an intuitive interface that allows users to explore and manipulate virtual reality spaces using VR controllers, and includes scripts for rich interactions.

[1150] User Action Description

[1151] Access to virtual reality spaces

[1152] The user puts on a VR device, launches a VR application on the device, and enters the virtual reality space. Specifically, the user puts on a device such as Oculus Quest 2.

[1153] Explore and explore visualized data

[1154] Users explore visualized constellations and galaxies in a virtual reality space, and by using the VR controller to focus on a star of interest, detailed market data related to that star is displayed.

[1155] Investment strategy planning and submission

[1156] The user can create an investment strategy based on the displayed details and enter it in the input form provided in the VR space. The completed investment strategy is then sent to the server by clicking the submit button and saved in the database.

[1157] Examples of concrete examples and prompts

[1158] Specific examples

[1159] Users access the system using Oculus Quest 2 and explore market data visualized in virtual reality (for example, the shape of the galaxy). Focusing on a specific star displays stock price data for companies related to that star, and users can then develop investment strategies based on that information and submit them in the VR space.

[1160] Prompt Sentence Examples

[1161] "Please explain how a system for visualizing real-time market data in a virtual reality environment works. The system takes market data, analyzes it using artificial intelligence, and then displays it in a VR space as constellations or galaxies. For each step, please detail the specific hardware and software used, as well as the data generated and manipulated. Also, please provide examples of how a user might use the system to manipulate the data and develop an investment strategy."

[1162] As a result, the present invention provides an environment in which users can intuitively understand market data and plan and implement effective investment strategies.

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

[1164] Step 1: Obtain market data

[1165] The server sends an HTTP request to an external API to retrieve market data. The retrieved market data is received in JSON format and temporarily stored in memory. The input is the API endpoint and query parameters, and the output is a JSON object of market data. For example, a specific operation would be to query "https: / / api.financedata.com / marketdata" and retrieve the returned price and volume data.

[1166] Step 2: Analyze the data

[1167] The server inputs the acquired market data into a machine learning model for analysis. During this process, a Python script is used to run a TensorFlow or PyTorch model. The input is a JSON object of market data, and the output is the analysis results (prediction data including trends and patterns). Specifically, it runs a neural network model that uses past stock price data to predict future prices.

[1168] Step 3: Save your data

[1169] The server saves the analysis results in a database (PostgreSQL). The input is the data structure of the analysis results, and the output is the state of storage in the database. Specifically, the analysis results are saved in the appropriate table in the database using an SQL insert statement.

[1170] Step 4: Generate visualization data

[1171] The server generates visualization data based on the saved analysis results. The data is converted into the shapes of constellations and galaxies using 3D modeling software (D3.js or Three.js). The input is the analysis results and a template for the 3D modeling software, and the output is 3D visualization data. Specifically, the data points from the analysis results are converted into 3D coordinate data and output in WebGL format.

[1172] Step 5: Sending data

[1173] The server sends the generated visualization data to the terminal. The visualization data is sent in JSON format to the terminal using the HTTP protocol. The input is a JSON object of the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent using an HTTP POST request.

[1174] Step 6: Initializing the Virtual Reality System

[1175] The device starts the virtual reality system (Oculus Quest 2) and loads the necessary resources, including 3D models and scripts. The input is a list of required resources, and the output is an initialized virtual reality environment. Specifically, the 3D environment is built using Unity or Unreal Engine and initialized.

[1176] Step 7: Rendering the visualization

[1177] The device receives visualization data from the server and renders it in a virtual reality space. The input is a JSON object of the visualization data, and the output is a visualized 3D space. Specifically, the device receives data via WebSocket or HTTP communication and executes a script to render it in the 3D space.

[1178] Step 8: Providing an Interface

[1179] The device provides an intuitive interface for users to explore and manipulate the virtual reality space. The input is the user's operation input, and the output is an interface that can be explored and manipulated. Specific operations are implemented as scripts that accept user movement and selection operations via the VR controller.

[1180] Step 9: Access the virtual reality space

[1181] The user wears a VR device and accesses a virtual reality space. The input is the VR device, and the output is the accessed virtual reality space. Specifically, the user wears the Oculus Quest 2, launches a VR application, and enters the virtual reality space.

[1182] Step 10: Explore and review the visualized data

[1183] Users explore the visualized constellations and galaxies in a virtual reality space and focus on a specific star. The input is the visualization data and user operations, and the output is detailed information about the focused star. Specific actions include selecting a specific star using the VR controller and displaying a pop-up with market data related to that star.

[1184] Step 11: Develop and submit your investment strategy

[1185] The user creates an investment strategy based on the displayed detailed information and submits it using the input form provided within the system. The input is the detailed information and the user's input, and the output is data transmission to the server. Specifically, the user enters the investment strategy into the input form in the VR space and clicks the send button to send it to the server.

[1186] This allows users to intuitively understand market data and develop and submit effective investment strategies.

[1187] (Application example 1)

[1188] 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."

[1189] In today's investment environment, massive amounts of market data are generated in real time, making it difficult to effectively analyze and intuitively understand it. Furthermore, there are insufficient means to quickly develop and implement investment strategies based on the analyzed data. As a result, users are easily confused by information overload and complex data analysis when making investment decisions, which can make it difficult to make appropriate investment decisions.

[1190] 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.

[1191] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for a user to use the visualized market data on a smartphone platform to develop and submit an investment strategy, means for using a generative AI model to visualize the market data in the virtual reality environment based on criteria specified by the user, and means for inputting prompt statements to the generative AI model and adjusting the visualization of the market data based on the prompt statements, thereby enabling a user to intuitively understand the market data and develop and execute effective and rapid investment strategies.

[1192] "Market data" refers to data such as stock prices, trading volumes, and economic indicators obtained from stock exchanges and other financial markets.

[1193] "Artificial intelligence tools" are programs or systems that use machine learning or deep learning algorithms to analyze trends and patterns in market data.

[1194] "Visualization tools" are technologies and systems that convert data into the shapes of constellations and galaxies and display them in a way that users can intuitively understand.

[1195] A "virtual reality environment" is a computer-generated three-dimensional space and interface that allows users to freely explore and manipulate it.

[1196] "Smartphone platform" refers to applications and systems that run on smartphones and provide the infrastructure for users to view and manipulate market data.

[1197] "Generative AI models" refer to AI techniques and algorithms that analyze and visualize data based on user-specified criteria.

[1198] A "prompt" is text data that is input to a generative AI model, and is an instruction that adjusts the visualization of the data based on that text.

[1199] An "investment strategy" is an investment policy or plan that a user formulates based on market data and its analysis results.

[1200] MODE FOR CARRYING OUT THE INVENTION

[1201] The present invention relates to a system that acquires market data in real time, analyzes it using artificial intelligence means, and visualizes the results in a form that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[1202] Server configuration and operation

[1203] A server is a device that has the following main functions:

[1204] 1. Market data acquisition methods:

[1205] The server retrieves market data from stock exchanges and other financial markets through APIs, including stock prices, trading volumes, economic indicators, and more.

[1206] 2. Artificial Intelligence Means:

[1207] To analyze the acquired market data, machine learning and deep learning algorithms are used, specifically software such as TensorFlow and PyTorch, to analyze trends and patterns in the data.

[1208] 3. Visualization tools:

[1209] It uses algorithms to convert the results of the analysis into the shapes of constellations and galaxies, and this visualization data is stored in a database and generated as needed.

[1210] Terminal configuration and operation

[1211] The terminal is a device that allows a user to explore and manipulate market data within a virtual reality environment.

[1212] 1. Virtual reality systems:

[1213] The device uses a VR device (such as Oculus Rift or Google Cardboard) to provide the user with a virtual reality environment. The VR library used is Unity or Unreal Engine.

[1214] 2. Smartphone Platform:

[1215] It displays visualized market data through an application that runs on smartphones, allowing users to browse and explore the data using their smartphones.

[1216] 3. Generative AI Model:

[1217] The generative AI model is used to perform analysis and visualization based on user-specified criteria, and the user can make specific requests to the generative AI model by entering prompt statements.

[1218] User interaction and usage

[1219] Users can explore market data using their smartphones or VR devices, and then develop and submit investment strategies based on the visualized data.

[1220] 1. Exploration and manipulation in virtual reality environments:

[1221] Users explore market data visualized as constellations and galaxies in a VR space, and by focusing on a particular star, more information related to that star is displayed.

[1222] 2. Investment strategy planning and submission:

[1223] Based on the information obtained in the virtual reality environment, users can plan their investment strategies, which are then submitted to the server via a smartphone application and stored in a database.

[1224] Usage examples and prompt statements

[1225] For example, a user might input a prompt like, "Analyze the latest US stock market data and generate a galaxy visualization showing trends in the technology sector. By focusing on a specific star, display the company's financial forecast." Based on this prompt, the generative AI model analyzes the data and creates a visualization that meets the specified criteria.

[1226] This allows users to more intuitively understand market data and develop investment strategies quickly and effectively.

[1227] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1228] Step 1:

[1229] The server retrieves market data from an external API. Specifically, the server sends a request to the market data API and retrieves real-time market data as an API response. This market data includes stock prices, trading volume, economic indicators, etc. The server temporarily stores this data.

[1230] Input: Response data from the Market Data API

[1231] Output: Temporarily stored market data

[1232] Step 2:

[1233] The server analyzes the acquired market data using artificial intelligence means, specifically machine learning and deep learning algorithms (e.g., TensorFlow and PyTorch), to analyze the market data and extract trends and patterns. The analysis results are stored in a database.

[1234] Input: Temporarily stored market data

[1235] Output: Analysis results (trend and pattern information)

[1236] Step 3:

[1237] The server then visualizes the analyzed market data using an algorithm that converts the analysis results into the shapes of constellations and galaxies, generating visualizations that are then stored in a database.

[1238] Input: Analysis results

[1239] Output: Visualization data (shapes of constellations and galaxies)

[1240] Step 4:

[1241] The device initializes the virtual reality system. Specifically, it loads the necessary resources (models, textures, scripts, etc.) and creates the virtual reality environment. Unity or Unreal Engine is used as the VR library.

[1242] Input: Resources for a virtual reality environment

[1243] Output: Initialized virtual reality system

[1244] Step 5:

[1245] The device uses the visualization data received from the server to render the image in a virtual reality space. Specifically, the visualization data obtained from the server is displayed in the VR space, allowing the user to explore the space.

[1246] Input: Visualization data

[1247] Output: Visualization data rendered in virtual reality space

[1248] Step 6:

[1249] Users explore and interact with a virtual reality environment, using a VR device to explore market data visualized as constellations and galaxy shapes. By focusing on a star of interest, detailed market data related to that star is displayed.

[1250] Input: Visualization data of virtual reality space

[1251] Output: Detailed market data displayed as a result of the user's search

[1252] Step 7:

[1253] Users create investment strategies based on the information they obtain in the virtual reality environment and submit them to a server via a smartphone application. For example, a user might create an investment strategy such as "purchase stocks of a specific company based on trends in the technology sector" and send that strategy to the server.

[1254] Input: Investment strategy designed by the user

[1255] Output: Investment strategy submitted to the server

[1256] Step 8:

[1257] The server inputs prompts into the generative AI model, which then adjusts the visualization of the market data based on those prompts. Specifically, the server analyzes the prompts entered by the user, reanalyzes the market data based on those criteria, and generates updated visualizations.

[1258] Input: The prompt text entered by the user

[1259] Output: Visualization data regenerated based on the prompt statement

[1260] In this way, this system realizes a series of processes from acquiring market data to analyzing, visualizing, displaying in a virtual reality environment, and formulating and submitting investment strategies, allowing users to intuitively understand market data and effectively formulate investment strategies.

[1261] 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.

[1262] The present invention relates to a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by users in a virtual reality environment. The present invention also includes an emotion engine that recognizes users' emotions and optimizes the user experience based on their emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1263] System configuration

[1264] server

[1265] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1266] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. Furthermore, an emotion engine is built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[1267] Terminal

[1268] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[1269] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[1270] User

[1271] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[1272] Specifically, the user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[1273] Program processing

[1274] (Server behavior)

[1275] The server retrieves market data from external APIs and stores it temporarily.

[1276] The acquired data is passed to an artificial intelligence means for analysis in real time.

[1277] The analysis results are stored in a database and visualization data is generated as needed.

[1278] Send visualization data to the device.

[1279] The emotion engine analyzes the user's emotion data and generates data to optimize the user experience.

[1280] (Device operation)

[1281] The device initializes the virtual reality system and loads the necessary resources.

[1282] The visualization data received from the server is used to render the image in a virtual reality space.

[1283] It provides an intuitive interface for users to explore and navigate.

[1284] The emotion engine obtains the user's emotional data in real time and adjusts the display method and interaction.

[1285] (user actions)

[1286] The user wears a VR device and explores the virtual reality space.

[1287] Focus on a specific star to see more information about it.

[1288] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[1289] Users receive feedback from the sentiment engine and adjust their investment strategies.

[1290] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[1291] The processing flow will be explained below.

[1292] Step 1:

[1293] server

[1294] Obtain real-time market data from external APIs and temporarily store the data.

[1295] Specific actions

[1296] Calls external APIs to obtain market data, which is then stored in storage.

[1297] Step 2:

[1298] server

[1299] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[1300] Specific actions

[1301] Input market data into the artificial intelligence module and trigger a task to analyze the data for trends and patterns.

[1302] Step 3:

[1303] server

[1304] The analysis results from the artificial intelligence means are received and stored in a database.

[1305] Specific actions

[1306] The analysis results are stored in a database and managed in a form that can be accessed later.

[1307] Step 4:

[1308] server

[1309] The analysis results are extracted from the database and data is converted for visualization.

[1310] Specific actions

[1311] The analysis results are read and visualized using algorithms that convert them into the shapes of constellations and galaxies.

[1312] Step 5:

[1313] server

[1314] The generated visualization data is sent to the terminal.

[1315] Specific actions

[1316] The visualization data is transmitted to the user's terminal via a network.

[1317] Step 6:

[1318] Terminal

[1319] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[1320] Specific actions

[1321] Starts the VR system, loads resource files, and prepares the virtual reality space.

[1322] Step 7:

[1323] Terminal

[1324] The visualization data received from the server is rendered in a virtual reality space.

[1325] Specific actions

[1326] It analyzes the received visualization data and draws it based on the shapes of constellations and galaxies.

[1327] Step 8:

[1328] Terminal

[1329] It provides an interface that allows users to explore and manipulate visualized market data within a virtual reality space.

[1330] Specific actions

[1331] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[1332] Step 9:

[1333] User

[1334] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[1335] Specific actions

[1336] Select a specific star. Detailed information related to the selected star will be displayed as a pop-up or menu.

[1337] Step 10:

[1338] server

[1339] Detailed information relating to a particular star selected by the user is retrieved from the database and transmitted to the user terminal.

[1340] Specific actions

[1341] It searches the database for information related to a specific star and transmits the obtained information to the user terminal.

[1342] Step 11:

[1343] User

[1344] An investment strategy is developed based on the detailed information obtained and sent to the server.

[1345] Specific actions

[1346] Analyze detailed information and enter and submit new investment strategies through the interface.

[1347] Step 12:

[1348] server

[1349] The investment strategy sent by the user is received and stored in a database.

[1350] Specific actions

[1351] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[1352] Step 13:

[1353] Terminal

[1354] An emotion engine is activated to obtain user emotion data in real time.

[1355] Specific actions

[1356] The emotion engine analyzes the user's facial expressions and biometric information to obtain their current emotional state.

[1357] Step 14:

[1358] server

[1359] The acquired emotional data is analyzed by an emotion engine, and the display method and interaction of the visualized data are dynamically adjusted.

[1360] Specific actions

[1361] Analyze emotional data and adjust presentation and interaction methods to optimize the user experience.

[1362] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[1363] Example 2

[1364] 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."

[1365] Modern market data is massive and complex, making it difficult for individual investors and analysts to intuitively understand and analyze the data. Furthermore, there is a lack of systems that can analyze data, including the user's emotional state, and provide appropriate feedback based on that data. This makes it difficult to make investment decisions and quickly respond to market fluctuations.

[1366] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1367] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, and means for analyzing the user's emotional data and generating feedback to optimize the user experience, thereby enabling the user to intuitively understand large amounts of complex market data and make more accurate and prompt investment decisions while receiving feedback that takes their emotional state into account.

[1368] "Market data" refers to trading information such as stock prices, foreign exchange rates, and commodity prices in the market, and related data.

[1369] "Means of Acquisition" refers to the methods and devices used to collect market data from external APIs and data providers.

[1370] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze trends and patterns in data.

[1371] "Visualization means" refers to a method or system for converting the analyzed data into visual shapes, such as constellations or galaxies, and displaying them to a user.

[1372] A "virtual reality environment" refers to an environment in which a user can experience a virtually constructed three-dimensional space using a dedicated device.

[1373] "Exploration and manipulation means" refers to the interfaces and devices that allow a user to move around in a virtual reality space and focus on specific objects.

[1374] "Emotional data" refers to data relating to the emotional state of a user obtained by analyzing the user's facial expressions, voice, heart rate, etc.

[1375] "Generated feedback" refers to advice or instructions provided to the user based on the analyzed emotional data.

[1376] The present invention is a system that acquires market data, analyzes it using artificial intelligence, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that analyzes the user's emotion data and enables the optimization of the user experience. Specific embodiments for implementing the present invention are described in detail below.

[1377] Server Operation

[1378] The server retrieves market data in real time through external APIs (e.g., Alpha Vantage API or Yahoo Finance API). This data is temporarily stored and then analyzed using artificial intelligence tools (e.g., TensorFlow or PyTorch). The results of the analysis are then stored in a database (e.g., MySQL or MongoDB) and visualizations (e.g., generated with SVG or D3.js) are generated as needed.

[1379] Example: A server retrieves TSLA stock price data from the Alpha Vantage API, analyzes this market data for trends using TensorFlow, and stores the results in MySQL.

[1380] Example prompt: Get TSLA stock price data from the Alpha Vantage API and store it in Redis.

[1381] Example prompt: Use TensorFlow to analyze this market data for trends and store the results in MySQL.

[1382] Additionally, the server is equipped with an emotion engine (e.g., Emotion AI API) that analyzes user emotion data and generates feedback to optimize the user experience.

[1383] Example: Analyzing the user's facial expression data with the Emotion AI API and generating feedback for relaxation.

[1384] Example prompt: Analyze the user's facial expression data using the Emotion AI API and generate feedback to help them relax.

[1385] Device behavior

[1386] The terminal uses a VR device (e.g., Oculus Rift, HTC Vive) to provide a virtual reality environment. It receives visualization data sent from the server and renders it in the virtual reality space. Within this space, an intuitive interface is provided for the user to explore and manipulate.

[1387] Example: Initialize the Oculus Rift, load the necessary 3D models and textures, and draw a galaxy in a virtual space based on the received data.

[1388] Example prompt: Initialize your Oculus Rift and load any necessary 3D models and textures.

[1389] Example prompt: Draw the received visualization data into the virtual reality space using the Unity engine.

[1390] The device also receives real-time feedback from the emotion engine and dynamically adjusts how it displays and interacts with the device.

[1391] Example: Changing the colors and effects of a virtual space based on the user's emotional data received in real time from the Emotion AI API.

[1392] Example prompt: Get the user's emotional data in real time and adjust the colors and effects of the virtual space.

[1393] User Actions

[1394] Users put on a VR device and explore the virtual reality space. By focusing on a specific star, detailed market data related to that star is displayed. Based on this information, users can create an investment strategy and submit it to the system. They can also receive feedback from the emotion engine and adjust their investment strategy based on that feedback.

[1395] Example: A user puts on an Oculus Rift, focuses on a star displaying TSLA market data, examines its details, and then uses a virtual keyboard to input their investment strategy and submit it to the system.

[1396] Sample prompt: Allow the user to put on a VR device and explore a virtual space.

[1397] Example prompt: Provide a system that displays detailed data for the star the user selects.

[1398] Example prompt: Please provide a system that allows users to input their investment strategies and submit them to the server.

[1399] Example prompt: Provide a system to adjust and resubmit investment strategies based on feedback from the sentiment engine.

[1400] In this way, the present invention can smoothly carry out a series of processes including collection, analysis, and visualization of market data, operation in a virtual reality space by the user, and feedback based on emotional data.

[1401] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1402] Step 1:

[1403] Obtaining Market Data

[1404] The server calls external APIs (e.g., Alpha Vantage API or Yahoo Finance API) to obtain market data. The server temporarily stores the obtained data in storage. At this time, a specific stock or product is specified in the request, and the data is received in JSON format as a response.

[1405] What happens: The server makes a request to the Alpha Vantage API to get the latest stock price data for TSLA, and temporarily stores this data in a Redis cache.

[1406] Input: API request (e.g., specific stock identifier)

[1407] Output: Market data in JSON format (e.g., TSLA stock price data)

[1408] Step 2:

[1409] Data analysis

[1410] The server passes the acquired market data to an artificial intelligence algorithm (e.g., TensorFlow, PyTorch) that analyzes the data for trends and patterns. The analysis results are stored in a database. At this time, the input data is processed by a machine learning model, and trend information and patterns are generated as output.

[1411] Specific operation: Using TensorFlow, the acquired TSLA stock price data is analyzed, trend information is generated, and the results are stored in a MySQL database.

[1412] Input: Market data in JSON format

[1413] Output: Analysis results (e.g., trend information)

[1414] Step 3:

[1415] Visualization data generation

[1416] The server generates visualization data based on the analyzed data and converts it into the shapes of constellations and galaxies. The visualization data is generated using SVG, D3.js, etc. In this case, the input data is the analysis results, and the output data is in a format that can be displayed visually.

[1417] Specific operation: Using the analysis results, the D3.js library is used to generate galaxy shape data and create visualization data in SVG format.

[1418] Input: Analysis results

[1419] Output: Visualization data (e.g., Galaxy shape in SVG format)

[1420] Step 4:

[1421] Emotional Data Analysis

[1422] The server uses an emotion engine (e.g., Emotion AI API) to analyze the user's emotional data. Based on the analysis results, it generates feedback to optimize the user experience. In this case, the input data is emotional data such as the user's facial expressions and voice, and the output data is feedback information.

[1423] Specific operation: Sends the user's facial expression data to the Emotion AI API, and generates feedback to help them relax as a result of the analysis.

[1424] Input: User emotion data (e.g., facial expression data)

[1425] Output: Feedback information

[1426] Step 5:

[1427] Initializing the Virtual Reality System

[1428] The device initializes the VR device (e.g., Oculus Rift, HTC Vive) and loads the necessary resources (models, textures, scripts, etc.) from pre-prepared files or databases.

[1429] Specific operation: Starts Oculus Rift and loads 3D model and texture files into the device's memory.

[1430] Input: VR device, resource files (e.g. 3D models, textures)

[1431] Output: Initialized virtual reality environment

[1432] Step 6:

[1433] Drawing visualized data

[1434] The device renders galaxies and constellations in the virtual reality space based on the visualization data received from the server, allowing users to intuitively grasp the data within the VR space.

[1435] Specific operation: Receives visualization data in SVG format from the server and draws a 3D model of the galaxy in virtual reality space using the Unity engine.

[1436] Input: Visualization data

[1437] Output: Rendered virtual reality space

[1438] Step 7:

[1439] Providing a user interface

[1440] The device provides an intuitive interface for users to explore and interact with, and when users focus on a particular object, detailed information about it is displayed.

[1441] What it does: Provides a UI that allows the user to select a constellation using a VR controller.

[1442] Input: User action

[1443] Output: Detailed information displayed

[1444] Step 8:

[1445] Real-time acquisition of user emotion data and interaction adjustment

[1446] The device receives data from the emotion engine in real time and adjusts how it displays and interacts with the device, dynamically optimizing the user experience.

[1447] Specific operation: Changes the colors and effects of the virtual space based on the user's emotional data received in real time from the Emotion AI API.

[1448] Input: Real-time user emotion data

[1449] Output: Calibrated virtual reality space

[1450] Step 9:

[1451] Verifying information, formulating investment strategies, and submitting them

[1452] Users can focus on a specific star in the VR space, check related information, and then create an investment strategy based on that information and submit it to the system.

[1453] Specific operation: The user uses the VR controller to focus on the star with TSLA market data to view detailed information, enter investment strategies using the virtual keyboard, and send them to the system.

[1454] Input: User actions, investment strategies

[1455] Output: Submitted investment strategy

[1456] Step 10:

[1457] Adjusting investment strategies

[1458] Users can reassess their investment strategy based on feedback from the sentiment engine and make adjustments as needed.

[1459] What happens: After receiving feedback from the sentiment engine indicating "tension," the user reevaluates, amends, and resubmits their investment strategy.

[1460] Input: Emotion engine feedback

[1461] Output: Adjusted investment strategy

[1462] (Application example 2)

[1463] 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."

[1464] Conventional virtual storefront systems lack functionality that allows users to intuitively understand market data and effectively plan investment strategies. Furthermore, they lack dynamic experience optimization that takes into account the user's emotional state, resulting in a lack of quality improvement in the user experience. Therefore, a new system is needed that not only analyzes market data in real time, intuitively visualizes it, and displays it in a virtual reality environment, but also optimizes the experience based on the user's emotions.

[1465] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1466] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, and means for converting the analyzed market data into the shapes of constellations or galaxies for visualization. This allows users to visually understand and explore the data within a virtual reality environment. Furthermore, the server includes an emotion engine that recognizes the user's emotional data and optimizes the user experience based on the user's emotional state. Having means for dynamically adjusting the layout and promotional strategies of the virtual store based on the emotion engine makes it possible to provide a high-quality experience tailored to the user's emotions.

[1467] "Market data" is a general term for information including prices, supply, demand, and trading volume of goods and services in the market.

[1468] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze, predict, and classify data.

[1469] "Visualization" refers to the process of transforming and displaying data in a way that is intuitively understandable to users.

[1470] "Constellations and galactic shapes" refers to the way data points are visualized, arranging them to resemble astronomical objects.

[1471] "Virtual reality environment" refers to a digital environment in which a user is immersed in a computer-generated three-dimensional space.

[1472] "User" means any person who utilizes the System to explore and manipulate Market Data.

[1473] An "emotion engine" refers to a system that has the ability to recognize a user's emotional state and optimize the experience based on that.

[1474] "Virtual store layout" refers to the product placement and spatial design within a virtual reality environment.

[1475] A "promotion strategy" refers to a plan or method for effectively selling a particular product or service.

[1476] The present invention is a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that recognizes the user's emotions and optimizes the user experience based on the user's emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1477] System configuration

[1478] server

[1479] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1480] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms (e.g., Python libraries TensorFlow and Scikit-learn) to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. An emotion engine is also built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[1481] Terminal

[1482] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[1483] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. This visualization is achieved using a 3D rendering library such as Three.js. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[1484] User

[1485] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[1486] Specifically, the user puts on a VR device (e.g., Oculus Rift, HTC Vive, etc.) and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[1487] Program processing

[1488] The main hardware includes a server (data acquisition, analysis, and storage), a VR terminal (providing a virtual reality environment and drawing data), and a user device (VR device).The main software includes external API access, machine learning libraries (TensorFlow, Scikit-learn), a database management system, and a 3D drawing library (Three.js).

[1489] Adding specific examples

[1490] Examples of promotion optimization in virtual stores include:

[1491] 1. Providing optimal promotion strategies in real time based on customer data and market trends.

[1492] 2. An emotional engine determines whether customers are enjoying themselves and dynamically changes the interface and layout if a certain emotional state persists.

[1493] Prompt Sentence Examples

[1494] "Optimize the current virtual store layout based on the latest market data. Also show us what promotions are effective when customers are in a positive mood."

[1495] "Use customer sentiment data to suggest ways to deliver a customized user experience for customers in a specific emotional state."

[1496] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1497] Step 1:

[1498] The server retrieves market data from an external API. The input is the external API endpoint (e.g., https: / / externalapi.com / marketdata), and the output is the retrieved market data. This data is temporarily stored. Specifically, it sends an HTTP request and receives the market data in JSON format as a response.

[1499] Step 2:

[1500] The server passes the acquired market data to an artificial intelligence tool for analysis. The input is market data and the output is the analysis results. This analysis uses machine learning algorithms (e.g., Python's TensorFlow or Scikit-learn). Specific operations include data cleaning, feature engineering, model training, and prediction.

[1501] Step 3:

[1502] The server converts the analyzed market data into constellations or galaxies for visualization. The input is the analysis results, and the output is the visualization data. This visualization places the data points in a three-dimensional space and renders them as constellations or galaxies based on specific patterns. Specific operations include conversion to three-dimensional coordinates, color coding, and clustering.

[1503] Step 4:

[1504] The server sends the generated visualization data to the terminal. The input is the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent to the terminal via a WebSocket or HTTP endpoint.

[1505] Step 5:

[1506] The device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). The input is the path to the necessary resources, and the output is the initialized system. Specifically, it uses Three.js to initialize the 3D scene, configure the camera, and create a renderer.

[1507] Step 6:

[1508] The device renders data in a virtual reality space based on the visualization data received from the server. The input is the visualization data from the server, and the output is the rendered data. Specifically, the device places data points in a three-dimensional space and allows the user to explore them.

[1509] Step 7:

[1510] The user enters the virtual reality environment using a VR device to explore and manipulate visualized market data. The input is wearing the VR device and the user's operation, and the output is the exploration result (e.g., information on the focused data point). Specific operations include interpreting the input of the VR controller and enabling the selection and movement of data points through the user interface.

[1511] Step 8:

[1512] When the user focuses on a specific market data point, detailed information about that point is displayed. The input is the user's operation (selecting the focus point), and the output is the display of detailed information. Specifically, the behavior is to overlay information related to the selected data point.

[1513] Step 9:

[1514] The user then creates an investment strategy based on the details and submits it to the system. The input is the user's investment strategy (e.g., selection, input form, confirmation), and the output is the submitted investment strategy. Specific operations include collecting user input, recording the investment strategy, and sending it to the server.

[1515] Step 10:

[1516] The server recognizes the user's emotional data and analyzes the information. The input is the user's emotional data (e.g., heart rate, facial expression analysis data), and the output is the analyzed emotional information. Specifically, it runs the emotion recognition algorithm and stores the results in a database.

[1517] Step 11:

[1518] The emotion engine optimizes the user experience based on the recognized emotion information. The input is analyzed emotion information, and the output is an optimized user experience (e.g., interface adjustments, promotion suggestions). Specific operations include dynamic adjustment of the system according to the emotional state.

[1519] 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.

[1520] 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.

[1521] 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.

[1522] [Fourth embodiment]

[1523] FIG. 7 shows an example of the configuration of a data processing system 410 according to the fourth embodiment.

[1524] 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.

[1525] 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).

[1526] 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.

[1527] 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.

[1528] 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).

[1529] 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.

[1530] 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.

[1531] 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.

[1532] 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.

[1533] 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.

[1534] 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.

[1535] 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."

[1536] The present invention relates to a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a form that can be intuitively understood by a user. The following describes in detail embodiments of the present invention.

[1537] System configuration

[1538] server

[1539] The server has means for obtaining market data in real time. The market data obtained from the external API is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database for later access. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1540] Specifically, the server retrieves market data through external APIs and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze the data for trends and patterns. The results are stored in a database and can be searched as needed. The data from the database is transformed into constellations and galaxies by a visualization means.

[1541] Terminal

[1542] The terminal has a means for providing a virtual reality environment to a user, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for the user to explore and operate within the virtual reality environment.

[1543] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). Next, it uses the virtual reality data received from the server to render the galaxy and constellations in the VR space. The user can freely explore the VR space and focus on stars that interest them.

[1544] User

[1545] Users can explore and intuitively manipulate market data visualizations within a virtual reality environment. When users focus on a particular star, detailed information related to that star is displayed. Users can then use this information to develop investment strategies and submit them to the system.

[1546] For example, a user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user can use it to develop an investment strategy. This investment strategy is sent to a server and stored in a database.

[1547] Program processing

[1548] (Server behavior)

[1549] The server retrieves market data from external APIs and stores it temporarily.

[1550] The acquired data is passed to an artificial intelligence means for analysis in real time.

[1551] The analysis results are stored in a database and visualization data is generated as needed.

[1552] Send visualization data to the device.

[1553] (Device operation)

[1554] The device initializes the virtual reality system and loads the necessary resources.

[1555] The visualization data received from the server is used to render the image in a virtual reality space.

[1556] It provides an intuitive interface for users to explore and navigate.

[1557] (user actions)

[1558] The user wears a VR device and explores the virtual reality space.

[1559] Focus on a specific star to see more information about it.

[1560] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[1561] As a result, the present invention promotes intuitive understanding of market data and provides an environment in which users can effectively formulate investment strategies.

[1562] The processing flow will be explained below.

[1563] Step 1:

[1564] server

[1565] Obtain real-time market data from external APIs and temporarily store the data.

[1566] Specific actions

[1567] Call external APIs, receive market data, and store it in storage.

[1568] Step 2:

[1569] server

[1570] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[1571] Specific actions

[1572] Input the data into an analytical artificial intelligence module, triggering a task to analyze the data for trends and patterns.

[1573] Step 3:

[1574] server

[1575] The analysis results from the artificial intelligence means are received and stored in a database.

[1576] Specific actions

[1577] Save the analysis results in a database to ensure that the results can be accessed later.

[1578] Step 4:

[1579] server

[1580] The analysis results are extracted from the database and converted into constellation and galaxy shapes for visualization.

[1581] Specific actions

[1582] The analysis results are read and visualized using an algorithm that converts them into the shapes of constellations and galaxies.

[1583] Step 5:

[1584] server

[1585] The generated visualization data is sent to the terminal.

[1586] Specific actions

[1587] The visualization data is transmitted to a user terminal via a network.

[1588] Step 6:

[1589] Terminal

[1590] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[1591] Specific actions

[1592] Starts the VR system and loads the resource file into memory.

[1593] Step 7:

[1594] Terminal

[1595] The visualization data received from the server is used to render the image in a virtual reality space.

[1596] Specific actions

[1597] A 3D model is generated based on the received data, and then placed and rendered in the VR space.

[1598] Step 8:

[1599] Terminal

[1600] It provides an interface that allows users to explore and manipulate market data visualized in a VR space.

[1601] Specific actions

[1602] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[1603] Step 9:

[1604] User

[1605] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[1606] Specific actions

[1607] Select a specific star and navigate through menus and popups to view related data.

[1608] Step 10:

[1609] User

[1610] An investment strategy is developed based on the detailed information obtained and sent to the server.

[1611] Specific actions

[1612] Enter your plan and hit submit using the interface to analyze detailed information and develop new investment strategies.

[1613] Step 11:

[1614] server

[1615] The investment strategy sent by the user is received and stored in a database.

[1616] Specific actions

[1617] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[1618] In this way, through detailed step-by-step processing, the present invention realizes a series of processes for collecting, analyzing, and visualizing market data, and for users to develop investment strategies.

[1619] Example 1

[1620] 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."

[1621] The goal is to realize a system that analyzes market data in real time and visualizes it in a way that is easy for users to understand intuitively, provides an intuitive interface for exploring and manipulating this visualized data within a virtual reality environment, and provides detailed information about market data points of interest to users, allowing them to create and execute investment strategies based on that information.

[1622] 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.

[1623] In this invention, the server includes means for acquiring market data, machine learning means for analyzing the acquired market data, means for converting the analyzed market data into the shapes of constellations or galaxies and visualizing them, means for rendering the visualized data in a virtual reality environment, interface means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for saving the acquired market data in a database, and means for a user to submit an investment strategy developed in the virtual reality environment. This allows a user to visualize market data in an intuitively understandable form and explore the data in the virtual reality environment to obtain detailed information. Furthermore, investment strategies can be efficiently developed and submitted based on the acquired information.

[1624] "Market data" refers to data that can be obtained in real time, including transaction data, price data, trading volume data, market trend data, etc. from financial markets and commodity markets.

[1625] An "external API" refers to an application programming interface provided by an external system or service, and is an interface for obtaining information such as market data.

[1626] "Machine learning tools" refer to algorithms or models used to analyze market data and identify patterns and trends, for example, using machine learning frameworks such as TensorFlow or PyTorch.

[1627] "Visualization means" refers to a means for converting analyzed market data into the shapes of constellations or galaxies in a form that is intuitively easy for users to understand and display it, and includes 3D modeling and data visualization techniques.

[1628] "Virtual reality environment" refers to a three-dimensional computer-generated space experienced by a user using a VR device, including those that allow the user to experience and manipulate an environment that is not physically present.

[1629] "Interface means" refers to the operating elements and input devices required for a user to explore and manipulate the visualized market data within the virtual reality environment, including, for example, a VR controller and an intuitive operating panel.

[1630] "Database" refers to a system that efficiently stores and manages data and enables data search and retrieval through queries, including, for example, SQL databases.

[1631] "Investment Strategy" refers to the investment plans and decisions formulated by users based on the analysis results and detailed information of market data, which are submitted and executed through the system.

[1632] The present invention is a system for acquiring market data, analyzing it using artificial intelligence means, and displaying the results in a virtual reality environment in a format that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[1633] Server configuration and operation

[1634] Obtaining Market Data

[1635] The server retrieves market data from an external API (e.g., a financial data API). The server sends an HTTP request, receives the market data in JSON format, and temporarily stores it.

[1636] Data analysis

[1637] The server analyzes the stored market data using artificial intelligence tools, specifically machine learning frameworks (e.g., TensorFlow and PyTorch), to extract trends and patterns based on past data and make future predictions.

[1638] Generate and save visualization data

[1639] The analysis results are stored in a database (e.g., PostgreSQL). The server then converts the analysis results into constellation and galaxy shapes through visualization tools, using 3D modeling techniques such as D3.js and Three.js.

[1640] Submitting visualization data

[1641] The server sends the generated visualization data to the terminal in JSON format using the HTTP protocol.

[1642] Terminal configuration and operation explanation

[1643] Initializing the Virtual Reality System

[1644] The device initializes the virtual reality system (e.g., Oculus Quest 2) and loads the necessary 3D models and scripts using a game engine (e.g., Unity or Unreal Engine).

[1645] Drawing visualized data

[1646] The device receives visualization data from the server and renders it in the virtual reality space. The data is received via WebSocket or HTTP communication and displayed as constellations and galaxies in 3D space.

[1647] Providing an interface

[1648] The device provides an intuitive interface that allows users to explore and manipulate virtual reality spaces using VR controllers, and includes scripts for rich interactions.

[1649] User Action Description

[1650] Access to virtual reality spaces

[1651] The user puts on a VR device, launches a VR application on the device, and enters the virtual reality space. Specifically, the user puts on a device such as Oculus Quest 2.

[1652] Explore and explore visualized data

[1653] Users explore visualized constellations and galaxies in a virtual reality space, and by using the VR controller to focus on a star of interest, detailed market data related to that star is displayed.

[1654] Investment strategy planning and submission

[1655] The user can create an investment strategy based on the displayed details and enter it in the input form provided in the VR space. The completed investment strategy is then sent to the server by clicking the submit button and saved in the database.

[1656] Examples of concrete examples and prompts

[1657] Specific examples

[1658] Users access the system using Oculus Quest 2 and explore market data visualized in virtual reality (for example, the shape of the galaxy). Focusing on a specific star displays stock price data for companies related to that star, and users can then develop investment strategies based on that information and submit them in the VR space.

[1659] Prompt Sentence Examples

[1660] "Please explain how a system for visualizing real-time market data in a virtual reality environment works. The system takes market data, analyzes it using artificial intelligence, and then displays it in a VR space as constellations or galaxies. For each step, please detail the specific hardware and software used, as well as the data generated and manipulated. Also, please provide examples of how a user might use the system to manipulate the data and develop an investment strategy."

[1661] As a result, the present invention provides an environment in which users can intuitively understand market data and plan and implement effective investment strategies.

[1662] The flow of the identification process in the first embodiment will be described with reference to FIG.

[1663] Step 1: Obtain market data

[1664] The server sends an HTTP request to an external API to retrieve market data. The retrieved market data is received in JSON format and temporarily stored in memory. The input is the API endpoint and query parameters, and the output is a JSON object of market data. For example, a specific operation would be to query "https: / / api.financedata.com / marketdata" and retrieve the returned price and volume data.

[1665] Step 2: Analyze the data

[1666] The server inputs the acquired market data into a machine learning model for analysis. During this process, a Python script is used to run a TensorFlow or PyTorch model. The input is a JSON object of market data, and the output is the analysis results (prediction data including trends and patterns). Specifically, it runs a neural network model that uses past stock price data to predict future prices.

[1667] Step 3: Save your data

[1668] The server saves the analysis results in a database (PostgreSQL). The input is the data structure of the analysis results, and the output is the state of storage in the database. Specifically, the analysis results are saved in the appropriate table in the database using an SQL insert statement.

[1669] Step 4: Generate visualization data

[1670] The server generates visualization data based on the saved analysis results. The data is converted into the shapes of constellations and galaxies using 3D modeling software (D3.js or Three.js). The input is the analysis results and a template for the 3D modeling software, and the output is 3D visualization data. Specifically, the data points from the analysis results are converted into 3D coordinate data and output in WebGL format.

[1671] Step 5: Sending data

[1672] The server sends the generated visualization data to the terminal. The visualization data is sent in JSON format to the terminal using the HTTP protocol. The input is a JSON object of the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent using an HTTP POST request.

[1673] Step 6: Initializing the Virtual Reality System

[1674] The device starts the virtual reality system (Oculus Quest 2) and loads the necessary resources, including 3D models and scripts. The input is a list of required resources, and the output is an initialized virtual reality environment. Specifically, the 3D environment is built using Unity or Unreal Engine and initialized.

[1675] Step 7: Rendering the visualization

[1676] The device receives visualization data from the server and renders it in a virtual reality space. The input is a JSON object of the visualization data, and the output is a visualized 3D space. Specifically, the device receives data via WebSocket or HTTP communication and executes a script to render it in the 3D space.

[1677] Step 8: Providing an Interface

[1678] The device provides an intuitive interface for users to explore and manipulate the virtual reality space. The input is the user's operation input, and the output is an interface that can be explored and manipulated. Specific operations are implemented as scripts that accept user movement and selection operations via the VR controller.

[1679] Step 9: Access the virtual reality space

[1680] The user wears a VR device and accesses a virtual reality space. The input is the VR device, and the output is the accessed virtual reality space. Specifically, the user wears the Oculus Quest 2, launches a VR application, and enters the virtual reality space.

[1681] Step 10: Explore and review the visualized data

[1682] Users explore the visualized constellations and galaxies in a virtual reality space and focus on a specific star. The input is the visualization data and user operations, and the output is detailed information about the focused star. Specific actions include selecting a specific star using the VR controller and displaying a pop-up with market data related to that star.

[1683] Step 11: Develop and submit your investment strategy

[1684] The user creates an investment strategy based on the displayed detailed information and submits it using the input form provided within the system. The input is the detailed information and the user's input, and the output is data transmission to the server. Specifically, the user enters the investment strategy into the input form in the VR space and clicks the send button to send it to the server.

[1685] This allows users to intuitively understand market data and develop and submit effective investment strategies.

[1686] (Application example 1)

[1687] 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."

[1688] In today's investment environment, massive amounts of market data are generated in real time, making it difficult to effectively analyze and intuitively understand it. Furthermore, there are insufficient means to quickly develop and implement investment strategies based on the analyzed data. As a result, users are easily confused by information overload and complex data analysis when making investment decisions, which can make it difficult to make appropriate investment decisions.

[1689] 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.

[1690] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, means for a user to use the visualized market data on a smartphone platform to develop and submit an investment strategy, means for using a generative AI model to visualize the market data in the virtual reality environment based on criteria specified by the user, and means for inputting prompt statements to the generative AI model and adjusting the visualization of the market data based on the prompt statements, thereby enabling a user to intuitively understand the market data and develop and execute effective and rapid investment strategies.

[1691] "Market data" refers to data such as stock prices, trading volumes, and economic indicators obtained from stock exchanges and other financial markets.

[1692] "Artificial intelligence tools" are programs or systems that use machine learning or deep learning algorithms to analyze trends and patterns in market data.

[1693] "Visualization tools" are technologies and systems that convert data into the shapes of constellations and galaxies and display them in a way that users can intuitively understand.

[1694] A "virtual reality environment" is a computer-generated three-dimensional space and interface that allows users to freely explore and manipulate it.

[1695] "Smartphone platform" refers to applications and systems that run on smartphones and provide the infrastructure for users to view and manipulate market data.

[1696] "Generative AI models" refer to AI techniques and algorithms that analyze and visualize data based on user-specified criteria.

[1697] A "prompt" is text data that is input to a generative AI model, and is an instruction that adjusts the visualization of the data based on that text.

[1698] An "investment strategy" is an investment policy or plan that a user formulates based on market data and its analysis results.

[1699] MODE FOR CARRYING OUT THE INVENTION

[1700] The present invention relates to a system that acquires market data in real time, analyzes it using artificial intelligence means, and visualizes the results in a form that can be intuitively understood by a user. Specific embodiments for carrying out the present invention will be described in detail below.

[1701] Server configuration and operation

[1702] A server is a device that has the following main functions:

[1703] 1. Market data acquisition methods:

[1704] The server retrieves market data from stock exchanges and other financial markets through APIs, including stock prices, trading volumes, economic indicators, and more.

[1705] 2. Artificial Intelligence Means:

[1706] To analyze the acquired market data, machine learning and deep learning algorithms are used, specifically software such as TensorFlow and PyTorch, to analyze trends and patterns in the data.

[1707] 3. Visualization tools:

[1708] It uses algorithms to convert the results of the analysis into the shapes of constellations and galaxies, and this visualization data is stored in a database and generated as needed.

[1709] Terminal configuration and operation

[1710] The terminal is a device that allows a user to explore and manipulate market data within a virtual reality environment.

[1711] 1. Virtual reality systems:

[1712] The device uses a VR device (such as Oculus Rift or Google Cardboard) to provide the user with a virtual reality environment. The VR library used is Unity or Unreal Engine.

[1713] 2. Smartphone Platform:

[1714] It displays visualized market data through an application that runs on smartphones, allowing users to browse and explore the data using their smartphones.

[1715] 3. Generative AI Model:

[1716] The generative AI model is used to perform analysis and visualization based on user-specified criteria, and the user can make specific requests to the generative AI model by entering prompt statements.

[1717] User interaction and usage

[1718] Users can explore market data using their smartphones or VR devices, and then develop and submit investment strategies based on the visualized data.

[1719] 1. Exploration and manipulation in virtual reality environments:

[1720] Users explore market data visualized as constellations and galaxies in a VR space, and by focusing on a particular star, more information related to that star is displayed.

[1721] 2. Investment strategy planning and submission:

[1722] Based on the information obtained in the virtual reality environment, users can plan their investment strategies, which are then submitted to the server via a smartphone application and stored in a database.

[1723] Usage examples and prompt statements

[1724] For example, a user might input a prompt like, "Analyze the latest US stock market data and generate a galaxy visualization showing trends in the technology sector. By focusing on a specific star, display the company's financial forecast." Based on this prompt, the generative AI model analyzes the data and creates a visualization that meets the specified criteria.

[1725] This allows users to more intuitively understand market data and develop investment strategies quickly and effectively.

[1726] The flow of the specific processing in the application example 1 will be described with reference to FIG.

[1727] Step 1:

[1728] The server retrieves market data from an external API. Specifically, the server sends a request to the market data API and retrieves real-time market data as an API response. This market data includes stock prices, trading volume, economic indicators, etc. The server temporarily stores this data.

[1729] Input: Response data from the Market Data API

[1730] Output: Temporarily stored market data

[1731] Step 2:

[1732] The server analyzes the acquired market data using artificial intelligence means, specifically machine learning and deep learning algorithms (e.g., TensorFlow and PyTorch), to analyze the market data and extract trends and patterns. The analysis results are stored in a database.

[1733] Input: Temporarily stored market data

[1734] Output: Analysis results (trend and pattern information)

[1735] Step 3:

[1736] The server then visualizes the analyzed market data using an algorithm that converts the analysis results into the shapes of constellations and galaxies, generating visualizations that are then stored in a database.

[1737] Input: Analysis results

[1738] Output: Visualization data (shapes of constellations and galaxies)

[1739] Step 4:

[1740] The device initializes the virtual reality system. Specifically, it loads the necessary resources (models, textures, scripts, etc.) and creates the virtual reality environment. Unity or Unreal Engine is used as the VR library.

[1741] Input: Resources for a virtual reality environment

[1742] Output: Initialized virtual reality system

[1743] Step 5:

[1744] The device uses the visualization data received from the server to render the image in a virtual reality space. Specifically, the visualization data obtained from the server is displayed in the VR space, allowing the user to explore the space.

[1745] Input: Visualization data

[1746] Output: Visualization data rendered in virtual reality space

[1747] Step 6:

[1748] Users explore and interact with a virtual reality environment, using a VR device to explore market data visualized as constellations and galaxy shapes. By focusing on a star of interest, detailed market data related to that star is displayed.

[1749] Input: Visualization data of virtual reality space

[1750] Output: Detailed market data displayed as a result of the user's search

[1751] Step 7:

[1752] Users create investment strategies based on the information they obtain in the virtual reality environment and submit them to a server via a smartphone application. For example, a user might create an investment strategy such as "purchase stocks of a specific company based on trends in the technology sector" and send that strategy to the server.

[1753] Input: Investment strategy designed by the user

[1754] Output: Investment strategy submitted to the server

[1755] Step 8:

[1756] The server inputs prompts into the generative AI model, which then adjusts the visualization of the market data based on those prompts. Specifically, the server analyzes the prompts entered by the user, reanalyzes the market data based on those criteria, and generates updated visualizations.

[1757] Input: The prompt text entered by the user

[1758] Output: Visualization data regenerated based on the prompt statement

[1759] In this way, this system realizes a series of processes from acquiring market data to analyzing, visualizing, displaying in a virtual reality environment, and formulating and submitting investment strategies, allowing users to intuitively understand market data and effectively formulate investment strategies.

[1760] 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.

[1761] The present invention relates to a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by users in a virtual reality environment. The present invention also includes an emotion engine that recognizes users' emotions and optimizes the user experience based on their emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1762] System configuration

[1763] server

[1764] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1765] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. Furthermore, an emotion engine is built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[1766] Terminal

[1767] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[1768] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[1769] User

[1770] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[1771] Specifically, the user puts on a VR device and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[1772] Program processing

[1773] (Server behavior)

[1774] The server retrieves market data from external APIs and stores it temporarily.

[1775] The acquired data is passed to an artificial intelligence means for analysis in real time.

[1776] The analysis results are stored in a database and visualization data is generated as needed.

[1777] Send visualization data to the device.

[1778] The emotion engine analyzes the user's emotion data and generates data to optimize the user experience.

[1779] (Device operation)

[1780] The device initializes the virtual reality system and loads the necessary resources.

[1781] The visualization data received from the server is used to render the image in a virtual reality space.

[1782] It provides an intuitive interface for users to explore and navigate.

[1783] The emotion engine obtains the user's emotional data in real time and adjusts the display method and interaction.

[1784] (user actions)

[1785] The user wears a VR device and explores the virtual reality space.

[1786] Focus on a specific star to see more information about it.

[1787] Based on the confirmed information, an investment strategy is developed and submitted to the server.

[1788] Users receive feedback from the sentiment engine and adjust their investment strategies.

[1789] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[1790] The processing flow will be explained below.

[1791] Step 1:

[1792] server

[1793] Obtain real-time market data from external APIs and temporarily store the data.

[1794] Specific actions

[1795] Calls external APIs to obtain market data, which is then stored in storage.

[1796] Step 2:

[1797] server

[1798] The temporarily stored market data is passed to an artificial intelligence means, which begins analysis.

[1799] Specific actions

[1800] Input market data into the artificial intelligence module and trigger a task to analyze the data for trends and patterns.

[1801] Step 3:

[1802] server

[1803] The analysis results from the artificial intelligence means are received and stored in a database.

[1804] Specific actions

[1805] The analysis results are stored in a database and managed in a form that can be accessed later.

[1806] Step 4:

[1807] server

[1808] The analysis results are extracted from the database and data is converted for visualization.

[1809] Specific actions

[1810] The analysis results are read and visualized using algorithms that convert them into the shapes of constellations and galaxies.

[1811] Step 5:

[1812] server

[1813] The generated visualization data is sent to the terminal.

[1814] Specific actions

[1815] The visualization data is transmitted to the user's terminal via a network.

[1816] Step 6:

[1817] Terminal

[1818] Initializes the virtual reality system and loads the required resources (models, textures, scripts, etc.).

[1819] Specific actions

[1820] Starts the VR system, loads resource files, and prepares the virtual reality space.

[1821] Step 7:

[1822] Terminal

[1823] The visualization data received from the server is rendered in a virtual reality space.

[1824] Specific actions

[1825] It analyzes the received visualization data and draws it based on the shapes of constellations and galaxies.

[1826] Step 8:

[1827] Terminal

[1828] It provides an interface that allows users to explore and manipulate visualized market data within a virtual reality space.

[1829] Specific actions

[1830] Enable user input devices (controllers and hand tracking) and display an intuitive interface.

[1831] Step 9:

[1832] User

[1833] Focus on a specific star in the virtual reality space to see detailed information related to that star.

[1834] Specific actions

[1835] Select a specific star. Detailed information related to the selected star will be displayed as a pop-up or menu.

[1836] Step 10:

[1837] server

[1838] Detailed information relating to a particular star selected by the user is retrieved from the database and transmitted to the user terminal.

[1839] Specific actions

[1840] It searches the database for information related to a specific star and transmits the obtained information to the user terminal.

[1841] Step 11:

[1842] User

[1843] An investment strategy is developed based on the detailed information obtained and sent to the server.

[1844] Specific actions

[1845] Analyze detailed information and enter and submit new investment strategies through the interface.

[1846] Step 12:

[1847] server

[1848] The investment strategy sent by the user is received and stored in a database.

[1849] Specific actions

[1850] The received investment strategies are stored in a database and analyzed and evaluated as necessary.

[1851] Step 13:

[1852] Terminal

[1853] An emotion engine is activated to obtain user emotion data in real time.

[1854] Specific actions

[1855] The emotion engine analyzes the user's facial expressions and biometric information to obtain their current emotional state.

[1856] Step 14:

[1857] server

[1858] The acquired emotional data is analyzed by an emotion engine, and the display method and interaction of the visualized data are dynamically adjusted.

[1859] Specific actions

[1860] Analyze emotional data and adjust presentation and interaction methods to optimize the user experience.

[1861] In this way, through detailed step-by-step processing, the present invention realizes a series of processes of market data collection, analysis, visualization, user operation, and feedback based on sentiment data.

[1862] Example 2

[1863] 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."

[1864] Modern market data is massive and complex, making it difficult for individual investors and analysts to intuitively understand and analyze the data. Furthermore, there is a lack of systems that can analyze data, including the user's emotional state, and provide appropriate feedback based on that data. This makes it difficult to make investment decisions and quickly respond to market fluctuations.

[1865] The specific processing by the specific processing unit 290 of the data processing device 12 in the second embodiment is realized by the following means.

[1866] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, means for converting the analyzed market data into constellation or galaxy shapes for visualization, means for displaying the visualized data in a virtual reality environment, means for a user to explore and manipulate the visualized market data in the virtual reality environment, and means for analyzing the user's emotional data and generating feedback to optimize the user experience, thereby enabling the user to intuitively understand large amounts of complex market data and make more accurate and prompt investment decisions while receiving feedback that takes their emotional state into account.

[1867] "Market data" refers to trading information such as stock prices, foreign exchange rates, and commodity prices in the market, and related data.

[1868] "Means of Acquisition" refers to the methods and devices used to collect market data from external APIs and data providers.

[1869] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze trends and patterns in data.

[1870] "Visualization means" refers to a method or system for converting the analyzed data into visual shapes, such as constellations or galaxies, and displaying them to a user.

[1871] A "virtual reality environment" refers to an environment in which a user can experience a virtually constructed three-dimensional space using a dedicated device.

[1872] "Exploration and manipulation means" refers to the interfaces and devices that allow a user to move around in a virtual reality space and focus on specific objects.

[1873] "Emotional data" refers to data relating to the emotional state of a user obtained by analyzing the user's facial expressions, voice, heart rate, etc.

[1874] "Generated feedback" refers to advice or instructions provided to the user based on the analyzed emotional data.

[1875] The present invention is a system that acquires market data, analyzes it using artificial intelligence, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that analyzes the user's emotion data and enables the optimization of the user experience. Specific embodiments for implementing the present invention are described in detail below.

[1876] Server Operation

[1877] The server retrieves market data in real time through external APIs (e.g., Alpha Vantage API or Yahoo Finance API). This data is temporarily stored and then analyzed using artificial intelligence tools (e.g., TensorFlow or PyTorch). The results of the analysis are then stored in a database (e.g., MySQL or MongoDB) and visualizations (e.g., generated with SVG or D3.js) are generated as needed.

[1878] Example: A server retrieves TSLA stock price data from the Alpha Vantage API, analyzes this market data for trends using TensorFlow, and stores the results in MySQL.

[1879] Example prompt: Get TSLA stock price data from the Alpha Vantage API and store it in Redis.

[1880] Example prompt: Use TensorFlow to analyze this market data for trends and store the results in MySQL.

[1881] Additionally, the server is equipped with an emotion engine (e.g., Emotion AI API) that analyzes user emotion data and generates feedback to optimize the user experience.

[1882] Example: Analyzing the user's facial expression data with the Emotion AI API and generating feedback for relaxation.

[1883] Example prompt: Analyze the user's facial expression data using the Emotion AI API and generate feedback to help them relax.

[1884] Device behavior

[1885] The terminal uses a VR device (e.g., Oculus Rift, HTC Vive) to provide a virtual reality environment. It receives visualization data sent from the server and renders it in the virtual reality space. Within this space, an intuitive interface is provided for the user to explore and manipulate.

[1886] Example: Initialize the Oculus Rift, load the necessary 3D models and textures, and draw a galaxy in a virtual space based on the received data.

[1887] Example prompt: Initialize your Oculus Rift and load any necessary 3D models and textures.

[1888] Example prompt: Draw the received visualization data into the virtual reality space using the Unity engine.

[1889] The device also receives real-time feedback from the emotion engine and dynamically adjusts how it displays and interacts with the device.

[1890] Example: Changing the colors and effects of a virtual space based on the user's emotional data received in real time from the Emotion AI API.

[1891] Example prompt: Get the user's emotional data in real time and adjust the colors and effects of the virtual space.

[1892] User Actions

[1893] Users put on a VR device and explore the virtual reality space. By focusing on a specific star, detailed market data related to that star is displayed. Based on this information, users can create an investment strategy and submit it to the system. They can also receive feedback from the emotion engine and adjust their investment strategy based on that feedback.

[1894] Example: A user puts on an Oculus Rift, focuses on a star displaying TSLA market data, examines its details, and then uses a virtual keyboard to input their investment strategy and submit it to the system.

[1895] Sample prompt: Allow the user to put on a VR device and explore a virtual space.

[1896] Example prompt: Provide a system that displays detailed data for the star the user selects.

[1897] Example prompt: Please provide a system that allows users to input their investment strategies and submit them to the server.

[1898] Example prompt: Provide a system to adjust and resubmit investment strategies based on feedback from the sentiment engine.

[1899] In this way, the present invention can smoothly carry out a series of processes including collection, analysis, and visualization of market data, operation in a virtual reality space by the user, and feedback based on emotional data.

[1900] The flow of the identification process in the second embodiment will be described with reference to FIG.

[1901] Step 1:

[1902] Obtaining Market Data

[1903] The server calls external APIs (e.g., Alpha Vantage API or Yahoo Finance API) to obtain market data. The server temporarily stores the obtained data in storage. At this time, a specific stock or product is specified in the request, and the data is received in JSON format as a response.

[1904] What happens: The server makes a request to the Alpha Vantage API to get the latest stock price data for TSLA, and temporarily stores this data in a Redis cache.

[1905] Input: API request (e.g., specific stock identifier)

[1906] Output: Market data in JSON format (e.g., TSLA stock price data)

[1907] Step 2:

[1908] Data analysis

[1909] The server passes the acquired market data to an artificial intelligence algorithm (e.g., TensorFlow, PyTorch) that analyzes the data for trends and patterns. The analysis results are stored in a database. At this time, the input data is processed by a machine learning model, and trend information and patterns are generated as output.

[1910] Specific operation: Using TensorFlow, the acquired TSLA stock price data is analyzed, trend information is generated, and the results are stored in a MySQL database.

[1911] Input: Market data in JSON format

[1912] Output: Analysis results (e.g., trend information)

[1913] Step 3:

[1914] Visualization data generation

[1915] The server generates visualization data based on the analyzed data and converts it into the shapes of constellations and galaxies. The visualization data is generated using SVG, D3.js, etc. In this case, the input data is the analysis results, and the output data is in a format that can be displayed visually.

[1916] Specific operation: Using the analysis results, the D3.js library is used to generate galaxy shape data and create visualization data in SVG format.

[1917] Input: Analysis results

[1918] Output: Visualization data (e.g., Galaxy shape in SVG format)

[1919] Step 4:

[1920] Emotional Data Analysis

[1921] The server uses an emotion engine (e.g., Emotion AI API) to analyze the user's emotional data. Based on the analysis results, it generates feedback to optimize the user experience. In this case, the input data is emotional data such as the user's facial expressions and voice, and the output data is feedback information.

[1922] Specific operation: Sends the user's facial expression data to the Emotion AI API, and generates feedback to help them relax as a result of the analysis.

[1923] Input: User emotion data (e.g., facial expression data)

[1924] Output: Feedback information

[1925] Step 5:

[1926] Initializing the Virtual Reality System

[1927] The device initializes the VR device (e.g., Oculus Rift, HTC Vive) and loads the necessary resources (models, textures, scripts, etc.) from pre-prepared files or databases.

[1928] Specific operation: Starts Oculus Rift and loads 3D model and texture files into the device's memory.

[1929] Input: VR device, resource files (e.g. 3D models, textures)

[1930] Output: Initialized virtual reality environment

[1931] Step 6:

[1932] Drawing visualized data

[1933] The device renders galaxies and constellations in the virtual reality space based on the visualization data received from the server, allowing users to intuitively grasp the data within the VR space.

[1934] Specific operation: Receives visualization data in SVG format from the server and draws a 3D model of the galaxy in virtual reality space using the Unity engine.

[1935] Input: Visualization data

[1936] Output: Rendered virtual reality space

[1937] Step 7:

[1938] Providing a user interface

[1939] The device provides an intuitive interface for users to explore and interact with, and when users focus on a particular object, detailed information about it is displayed.

[1940] What it does: Provides a UI that allows the user to select a constellation using a VR controller.

[1941] Input: User action

[1942] Output: Detailed information displayed

[1943] Step 8:

[1944] Real-time acquisition of user emotion data and interaction adjustment

[1945] The device receives data from the emotion engine in real time and adjusts how it displays and interacts with the device, dynamically optimizing the user experience.

[1946] Specific operation: Changes the colors and effects of the virtual space based on the user's emotional data received in real time from the Emotion AI API.

[1947] Input: Real-time user emotion data

[1948] Output: Calibrated virtual reality space

[1949] Step 9:

[1950] Verifying information, formulating investment strategies, and submitting them

[1951] Users can focus on a specific star in the VR space, check related information, and then create an investment strategy based on that information and submit it to the system.

[1952] Specific operation: The user uses the VR controller to focus on the star with TSLA market data to view detailed information, enter investment strategies using the virtual keyboard, and send them to the system.

[1953] Input: User actions, investment strategies

[1954] Output: Submitted investment strategy

[1955] Step 10:

[1956] Adjusting investment strategies

[1957] Users can reassess their investment strategy based on feedback from the sentiment engine and make adjustments as needed.

[1958] What happens: After receiving feedback from the sentiment engine indicating "tension," the user reevaluates, amends, and resubmits their investment strategy.

[1959] Input: Emotion engine feedback

[1960] Output: Adjusted investment strategy

[1961] (Application example 2)

[1962] 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."

[1963] Conventional virtual storefront systems lack functionality that allows users to intuitively understand market data and effectively plan investment strategies. Furthermore, they lack dynamic experience optimization that takes into account the user's emotional state, resulting in a lack of quality improvement in the user experience. Therefore, a new system is needed that not only analyzes market data in real time, intuitively visualizes it, and displays it in a virtual reality environment, but also optimizes the experience based on the user's emotions.

[1964] The specific processing by the specific processing unit 290 of the data processing device 12 in the application example 2 is realized by the following means.

[1965] In this invention, the server includes means for acquiring market data, artificial intelligence means for analyzing the acquired market data, and means for converting the analyzed market data into the shapes of constellations or galaxies for visualization. This allows users to visually understand and explore the data within a virtual reality environment. Furthermore, the server includes an emotion engine that recognizes the user's emotional data and optimizes the user experience based on the user's emotional state. Having means for dynamically adjusting the layout and promotional strategies of the virtual store based on the emotion engine makes it possible to provide a high-quality experience tailored to the user's emotions.

[1966] "Market data" is a general term for information including prices, supply, demand, and trading volume of goods and services in the market.

[1967] "Artificial intelligence means" refers to technologies that use algorithms such as machine learning and deep learning to analyze, predict, and classify data.

[1968] "Visualization" refers to the process of transforming and displaying data in a way that is intuitively understandable to users.

[1969] "Constellations and galactic shapes" refers to the way data points are visualized, arranging them to resemble astronomical objects.

[1970] "Virtual reality environment" refers to a digital environment in which a user is immersed in a computer-generated three-dimensional space.

[1971] "User" means any person who utilizes the System to explore and manipulate Market Data.

[1972] An "emotion engine" refers to a system that has the ability to recognize a user's emotional state and optimize the experience based on that.

[1973] "Virtual store layout" refers to the product placement and spatial design within a virtual reality environment.

[1974] A "promotion strategy" refers to a plan or method for effectively selling a particular product or service.

[1975] The present invention is a system that acquires market data, analyzes it using artificial intelligence means, and displays the results in a form that can be intuitively understood by the user in a virtual reality environment. It also combines an emotion engine that recognizes the user's emotions and optimizes the user experience based on the user's emotional state. Specific embodiments for implementing the present invention are described in detail below.

[1976] System configuration

[1977] server

[1978] The server has means for retrieving market data in real time from external APIs. This data is temporarily stored and then analyzed by artificial intelligence means. The analysis results are stored in a database and can be accessed as needed. Furthermore, the server has means for visualizing the analysis results, converting the data into constellations and galaxy shapes.

[1979] Specifically, the server retrieves market data through an external API and passes it to an artificial intelligence means. The artificial intelligence means uses machine learning and deep learning algorithms (e.g., Python libraries TensorFlow and Scikit-learn) to analyze trends and patterns in the data. The results are stored in a database and can be searched later. Data from the database is transformed into constellations and galaxies using visualization means. An emotion engine is also built in to analyze user emotion data, allowing the system to dynamically optimize the user experience.

[1980] Terminal

[1981] The device has a means for providing a virtual reality environment, receives visualization data sent from the server, and renders it in the virtual reality space. It also provides an intuitive interface for users to explore and operate the device.

[1982] Specifically, the device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). It then renders the galaxy and constellations based on the visualization data received from the server. This visualization is achieved using a 3D rendering library such as Three.js. The user can explore this virtual reality space and focus on specific stars. The emotion engine recognizes the user's current emotional state in real time and dynamically adjusts visual feedback and interaction methods based on that information.

[1983] User

[1984] Using a VR device, users can enter a virtual reality environment to explore and manipulate visualized market data. By focusing on a specific star, detailed information related to that star is displayed. Furthermore, users can develop investment strategies based on the information and submit them to the system. An emotion engine monitors the user's emotional state and provides emotion-based feedback to support investment strategy development.

[1985] Specifically, the user puts on a VR device (e.g., Oculus Rift, HTC Vive, etc.) and enters a virtual reality space. Within this space, the user explores stars and focuses on a specific star. Market data related to the focused star is displayed, and the user uses this information to develop an investment strategy. This investment strategy is sent to a server and stored in a database. The emotion engine collects the user's emotional data and uses it to personalize the user experience and provide feedback and advice at the appropriate time.

[1986] Program processing

[1987] The main hardware includes a server (data acquisition, analysis, and storage), a VR terminal (providing a virtual reality environment and drawing data), and a user device (VR device).The main software includes external API access, machine learning libraries (TensorFlow, Scikit-learn), a database management system, and a 3D drawing library (Three.js).

[1988] Adding specific examples

[1989] Examples of promotion optimization in virtual stores include:

[1990] 1. Providing optimal promotion strategies in real time based on customer data and market trends.

[1991] 2. An emotional engine determines whether customers are enjoying themselves and dynamically changes the interface and layout if a certain emotional state persists.

[1992] Prompt Sentence Examples

[1993] "Optimize the current virtual store layout based on the latest market data. Also show us what promotions are effective when customers are in a positive mood."

[1994] "Use customer sentiment data to suggest ways to deliver a customized user experience for customers in a specific emotional state."

[1995] The flow of the specific processing in the application example 2 will be described with reference to FIG.

[1996] Step 1:

[1997] The server retrieves market data from an external API. The input is the external API endpoint (e.g., https: / / externalapi.com / marketdata), and the output is the retrieved market data. This data is temporarily stored. Specifically, it sends an HTTP request and receives the market data in JSON format as a response.

[1998] Step 2:

[1999] The server passes the acquired market data to an artificial intelligence tool for analysis. The input is market data and the output is the analysis results. This analysis uses machine learning algorithms (e.g., Python's TensorFlow or Scikit-learn). Specific operations include data cleaning, feature engineering, model training, and prediction.

[2000] Step 3:

[2001] The server converts the analyzed market data into constellations or galaxies for visualization. The input is the analysis results, and the output is the visualization data. This visualization places the data points in a three-dimensional space and renders them as constellations or galaxies based on specific patterns. Specific operations include conversion to three-dimensional coordinates, color coding, and clustering.

[2002] Step 4:

[2003] The server sends the generated visualization data to the terminal. The input is the visualization data, and the output is the data sent to the terminal. Specifically, the data is sent to the terminal via a WebSocket or HTTP endpoint.

[2004] Step 5:

[2005] The device initializes the virtual reality system and loads the necessary resources (models, textures, scripts, etc.). The input is the path to the necessary resources, and the output is the initialized system. Specifically, it uses Three.js to initialize the 3D scene, configure the camera, and create a renderer.

[2006] Step 6:

[2007] The device renders data in a virtual reality space based on the visualization data received from the server. The input is the visualization data from the server, and the output is the rendered data. Specifically, the device places data points in a three-dimensional space and allows the user to explore them.

[2008] Step 7:

[2009] The user enters the virtual reality environment using a VR device to explore and manipulate visualized market data. The input is wearing the VR device and the user's operation, and the output is the exploration result (e.g., information on the focused data point). Specific operations include interpreting the input of the VR controller and enabling the selection and movement of data points through the user interface.

[2010] Step 8:

[2011] When the user focuses on a specific market data point, detailed information about that point is displayed. The input is the user's operation (selecting the focus point), and the output is the display of detailed information. Specifically, the behavior is to overlay information related to the selected data point.

[2012] Step 9:

[2013] The user then creates an investment strategy based on the details and submits it to the system. The input is the user's investment strategy (e.g., selection, input form, confirmation), and the output is the submitted investment strategy. Specific operations include collecting user input, recording the investment strategy, and sending it to the server.

[2014] Step 10:

[2015] The server recognizes the user's emotional data and analyzes the information. The input is the user's emotional data (e.g., heart rate, facial expression analysis data), and the output is the analyzed emotional information. Specifically, it runs the emotion recognition algorithm and stores the results in a database.

[2016] Step 11:

[2017] The emotion engine optimizes the user experience based on the recognized emotion information. The input is analyzed emotion information, and the output is an optimized user experience (e.g., interface adjustments, promotion suggestions). Specific operations include dynamic adjustment of the system according to the emotional state.

[2018] 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.

[2019] 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.

[2020] 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.

[2021] 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.

[2022] 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.

[2023] 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.

[2024] 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).

[2025] 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.

[2026] 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."

[2027] 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.

[2028] 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 ...

Claims

1. a means of obtaining market data; artificial intelligence means for analyzing the acquired market data; A means of visualizing the analyzed market data by converting it into constellations or galaxies. means for displaying the visualized data in a virtual reality environment; A system including means for a user to explore and manipulate visualized market data within a virtual reality environment.

2. The system of claim 1 , further comprising means for providing detailed information regarding a market data point identified by a user's action within the virtual reality environment.

3. The system of claim 1 , further comprising means for a user to develop and submit an investment strategy based on the market data points identified by the user's actions.

4. 10. The system of claim 1, wherein the artificial intelligence means further comprises means for analyzing market data in real time to suggest investment opportunities and risks.

5. 10. The system of claim 1, wherein said means further comprises means for storing the results of the analyzed market data in a database for later access.

6. 10. The system of claim 1, further comprising interface means for supporting intuitive manipulation of a user as they explore visualized market data within the virtual reality environment.

7. 10. The system of claim 1, further comprising means for including an algorithm for placing data points in specific locations in a constellation or galaxy based on the analyzed market data.

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